We study the energy efficiency of pinching-antenna systems (PASSs) by developing a consistent formulation for power distribution in these systems. The per-antenna power distribution in PASSs is not controlled explicitly by a power allocation policy, but rather implicitly through tuning of pinching couplings and locations. Both these factors are tunable: (i) pinching locations are tuned using movable elements, and (ii) couplings can be tuned by varying the effective coupling length of the pinching elements. While the former is feasible to be addressed dynamically in settings with low user mobility, the latter cannot be addressed at a high rate. We thus develop a class of hybrid dynamic-static algorithms, which maximize the energy efficiency by updating the system parameters at different rates. Our experimental results depict that dynamic tuning of pinching locations can significantly boost energy efficiency of PASSs.

In this paper, we address the complex resource allocation problem in a flexible-antenna architecture, referred to as a pinching-antenna (PA) system. This system utilizes a dielectric waveguide and dynamically activated small dielectric particles to serve the multiple single-antenna users via non-orthogonal multiple access (NOMA). To address the challenges posed by dynamic operating environments that necessitate real-time reconfiguration, we develop a low-complexity framework for PA placement and power allocation optimization, as traditional iterative methods are computationally prohibitive. We first formulate the optimization problem as a mixed-integer non-linear programming problem to maximize the sum rate performance under physical constraints. Due to the inherent complexity and the need for rapid inference, a two-stage solution is introduced: a user-geometry aware initialization followed by a gradient-based refinement, achieving near-optimal performance efficiently. We then model the power allocation challenge as a max-min fairness problem via quasi-convex programming and low complexity, bisection-based algorithms that achieve globally optimal solutions using only simple scalar evaluations. To enable real-time application, we employ a convolutional neural network (CNN)-based learning framework to capture the highly complex, non-linear mapping between instantaneous channel conditions and optimal power coefficients. This work is motivated by the need to achieve near-optimal performance with significantly lower inference complexity than conventional optimization-based methods. By leveraging the generalization capability of CNNs, the proposed approach enables fast inference and can predict near-optimal power allocations for unseen network configurations without retraining. Simulation results demonstrate that this integrated CNN-based NOMA approach for PA systems delivers enhanced performance in terms of sum rate and user fairness.

A sensing-aided covert communication network empowered by pinching antenna systems (PASS) is proposed in this work. Unlike conventional fixed-position multiple-input multiple-output (MIMO) arrays, PASS reconfigures wireless channels by repositioning pinching antennas (PAs) to enhance transmission covertness. To further obtain the adversary’s channel state information (CSI), a sensing function is leveraged to track the malicious warden’s movements. In particular, this paper first proposes an extended Kalman filter (EKF) based approach to fulfilling the tracking function. Building on this, a covert communication problem is formulated as a joint design of beamforming, artificial noise (AN) signals, and PA positions. Then, the beamforming and AN design subproblems are resolved using a subspace approach, while the PA position optimization subproblem is handled by a deep reinforcement learning (DRL) approach by treating the evolution of the warden’s mobility status as a temporally correlated process. Numerical results are presented and demonstrate that: i) the EKF approach can accurately track the warden’s CSI with low complexity, ii) the effectiveness of the proposed solution is verified by its outperformance over the greedy and searching-based benchmarks, and iii) with new design degrees of freedom (DoFs), the performance of PASS is superior to the conventional fully-digital MIMO systems.

Recent advances in large language models (LLMs) have driven remarkable progress across diverse NLP benchmarks. However, the application of these models to sophisticated domains such as wireless communications raises new challenges. This paper addresses the evaluation gap for LLMs in telecommunications by introducing Last Dance of Telecommunications (LDOT) – a comprehensive benchmark suite for telecom-related tasks. LDOT encompasses a broad range of problem categories, including conceptual telecom questions, mathematical and logical reasoning problems, and complex network optimization scenarios, specifically designed to challenging LLMs’ high-level reasoning and domain-specific knowledge. Using LDOT, we rigorously assess state-of-the-art (SOTA) LLMs (both closed-source and open-source) on domain-specific tasks. Our results reveal that while general-purpose LLMs exhibit strong performance on basic telecom knowledge questions, they struggle with reasoning-intensive wireless problems. Notably, certain multi-step optimization and planning tasks in LDOT remain unsolved by even the best models, exposing performance gaps that are not apparent from existing saturated benchmarks. We provide a detailed failure analysis to pinpoint whether these limitations arise from insufficient telecom-specific knowledge or from inadequate reasoning capabilities. The LDOT dataset and our evaluation findings aim to facilitate the development of more robust domain-adapted LLMs for next-generation wireless communications.

Pinching-antenna systems (PASSs) are a recent flexible-antenna technology that is realized by attaching simple components, referred to aspinching elements, to dielectric waveguides. This work explores the potential of deploying PASS for uplink and downlink transmission in multiuser MIMO settings. For downlink PASS-aided communication, we formulate the optimal hybrid beamforming, in which the digital precoding matrix at the access point and the pinching locations on the waveguides are jointly optimized to maximize the achievable weighted sum-rate. We discuss the key challenges in this design problem and propose two low-complexity algorithms to iteratively update the precoding matrix and activated pinching locations.We further formulate the design problem for uplink transmission in a PASS and develop an iterative scheme for the underlying hybrid multiuser detection problem. We validate the proposed schemes through extensive numerical experiments. The results demonstrate that using a PASS, the throughput in both uplink and downlink is significantly enhanced compared to baseline MIMO architectures, such as massive MIMO and classical hybrid analog-digital designs. This highlights the great potential of the PASS, making it a promising reconfigurable antenna technology for next-generation wireless systems.

The fundamental sensing limit of pinching-antenna systems (PASS) is studied from a Bayesian Cramér-Rao bound (BCRB) perspective. Compared to conventional CRB, the BCRB is independent of the exact values of sensing parameters and is not restricted by the unbiasedness of estimators, thus offering a global lower bound for evaluating sensing performance. A system where multiple targets transmit uplink pilots to a single-waveguide PASS under a time-division multiple access (TDMA) scheme is analyzed. In the single-target scenario, our analysis reveals a unique mismatch between the sensing centroid (i.e., the PA position that minimizes the BCRB) and the distribution centroid (i.e., the center of the target’s prior distribution), underscoring the necessity of pinching beamforming, i.e., repositioning PAs along the waveguide. In the multi-target scenario, two scheduling protocols are proposed: 1) pinch switching (PS), which performs separate pinching beamforming for each time slot, and 2) pinch multiplexing (PM), which applies a single pinching beamforming across all slots. Based on these protocols, both the total power minimization problem under a BCRB threshold and the min-max BCRB problem under a total power constraint are formulated. By leveraging Karush-Kuhn-Tucker (KKT) conditions, these problems are equivalently converted into a search over PA positions and solved using an element-wise algorithm. Numerical results show that: i) PASS, endowed with large-scale reconfigurability, can significantly enhance the sensing performance compared with conventional fixed-position arrays, and ii) PS provides more robust performance than PM at the cost of higher computational complexity.

In this paper, we investigate the performance of a non-orthogonal multiple access (NOMA)-enhanced active reconfigurable intelligent surface (RIS)-assisted integrated sensing and communication (ISAC) system under a non-terrestrial network (NTN) framework. The performance is analyzed in terms of outage probability, ergodic capacity, beampattern gain, and probability of detection (PoD). To this end, the end-to-end equivalent channel distribution under maximum ratio transmission beamforming is derived and modeled as a Gamma distribution. Based on this, a closed-form expression for the outage probability (OP) is obtained in terms of Meijer G-functions. The accuracy of the analytical results is validated through Monte Carlo simulations. To provide further insight, we derive the asymptotic expression of the OP and the corresponding diversity order. Additionally, an approximate expression for the ergodic capacity is derived using the method of moments, along with its upper and lower bounds. To evaluate the impact of the active RIS in mitigating the impact of multiplicative fading through amplification of the incident signal, its performance is compared against a baseline passive RIS scheme, revealing significant performance improvements. In particular, the outage probability is improved by approximately 72.94% and 73.33% for the weak user (D1) and strong user (D2), respectively, when employing an active RIS compared to a passive RIS at a transmit SNR of 22 dBm. The influence of practical impairments, including hardware impairments, imperfect channel state information, and imperfect successive interference cancellation, is also examined. The results show that increasing the number of RIS elements and the number of antennas at the satellite can effectively alleviate the adverse effects of these impairments. On the sensing side, the proposed ISAC system is compared with a conventional radar system in terms of the PoD for aerial targets located at various positions, and it additionally demonstrates beampattern gain. The results are obtained under the assumptions of ideal RIS phase configuration and line-of-sight (LoS) between the satellite and targets, representing key limitations of the analysis.

A segmented waveguide-enabled pinching-antenna system (SWAN) is proposed, in which a segmented waveguide composed of multiple short dielectric waveguide segments is employed to radiate or receive signals through the pinching antennas (PAs) deployed on each segment. Based on this architecture, three practical operating protocols are proposed: segment selection (SS), segment aggregation (SA), and segment multiplexing (SM). For uplink SWAN communications, where one PA is activated per segment, the segmented structure eliminates the inter-antenna radiation effect, i.e., signals captured by one PA may re-radiate through other PAs along the same waveguide. This yields a tractable and physically consistent uplink signal model for a multi-PA pinching-antenna system (PASS), which has not been established for conventional PASS using a single long waveguide. Building on this model, PA placement algorithms are proposed to maximize the uplink signal-to-noise ratio (SNR). Closed-form expressions for the received SNR under the three protocols are derived, and the corresponding scaling laws with respect to the number of segments are analyzed. It is proven that the segmented architecture reduces both the average PA-to-user distance and the PA-to-feed distance, thereby mitigating both large-scale path loss and in-waveguide propagation loss. These results are extended to downlink SWAN communications, where multiple PAs are activated per segment, and PA placement methods are proposed to maximize the downlink received SNR under the three protocols. Numerical results demonstrate that: i) among the three protocols, SM achieves the best performance, followed by SA and then SS; and ii) for all protocols, the proposed SWAN achieves a higher SNR than conventional PASS with a single long waveguide in both uplink and downlink scenarios.

The Pinching-Antenna SyStem (PASS) reconstructs wireless channels throughpinching beamforming, wherein the activated positions of pinching antennas along dielectric waveguides are optimized to shape the radiation pattern. The aim of this article is to analyze the performance limits of employing PASS in integrated sensing and communications (ISAC). Specifically, a PASS-assisted ISAC system is considered, where a pinched waveguide is utilized to simultaneously communicate with a user and sense a target. Closed-form expressions for the achievable communication rate (CR) and sensing rate (SR) are derived to characterize the information-theoretic limits of this dual-functional operation. i) For the single-pinch case, closed-form solutions for the optimal pinching antenna location are derived undersensing-centric (S-C),communications-centric (C-C), andPareto-optimaldesigns. On this basis, the CR-SR trade-off is characterized by deriving the full CR-SR rate region, which is shown to encompass that of conventional fixed-antenna systems. ii) For the multiple-pinch case, an antenna location refinement method is applied to obtain the optimal C-C and S-C pinching beamformers. As a further advance, inner and outer bounds on the achievable CR-SR region are derived using an element-wise alternating optimization technique and by invoking Cauchy-Schwarz and Karamata’s inequalities, respectively. Numerical results demonstrate that: i) the derived bounds closely approximate the true CR-SR region; and ii) PASS can achieve a significantly larger rate region than conventional-antenna systems.

In this paper, we consider a novel optimization design for multi-waveguide pinching-antenna systems, aiming to maximize the weighted sum rate (WSR) by jointly optimizing beamforming coefficients and antenna position. To handle the formulated non-convex problem, a gradient-based meta-learning joint optimization (GML-JO) algorithm is proposed. Specifically, the original problem is initially decomposed into two sub-problems of beamforming optimization and antenna position optimization through equivalent substitution. Then, the convex approximation methods are used to deal with the nonconvex constraints of sub-problems, and two sub-neural networks are constructed to calculate the sub-problems separately. Different from alternating optimization (AO), where two sub-problems are solved alternately and the solutions are influenced by the initial values, two sub-neural networks of proposed GML-JO with fixed channel coefficients are considered as local sub-tasks and the computation results are used to calculate the loss function of joint optimization. Finally, the parameters of sub-networks are updated using the average loss function over different sub-tasks and the solution that is robust to the initial value is obtained. Simulation results demonstrate that the proposed GML-JO algorithm achieves 5.6 bits/s/Hz WSR within 100 iterations, yielding a 32.7% performance enhancement over conventional AO with substantially reduced computational complexity. Moreover, the proposed GML-JO algorithm is robust to different choices of initialization and yields better performance compared with the existing optimization methods.

This article presents a physical layer security (PLS) technique for non-orthogonal multiple access (NOMA), which can provide joint secrecy, fairness, and bit error rate (BER) improvement. The approach employs power hopping (PH), where users’ power coefficients are dynamically varied according to the instantaneous channel conditions. By randomizing both the detection order and the effective power allocation, PH obscures the underlying NOMA structure from a passive eavesdropper (Eve), thereby severely degrading the data detection capability. To enable secure coordination, a precoding-based mechanism is developed for sharing the PH patterns among legitimate users, leveraging the random and independent nature of wireless channels. The BER and secrecy outage probability (SOP) of the proposed framework are analytically characterized and compared to conventional NOMA under various channel and eavesdropping configurations. The obtained analytical results, corroborated by Monte Carlo simulations, confirm the effectiveness of the proposed scheme, where the SOP of legitimate users is never compromised regardless of Eve’s channel conditions, while incurring only negligible additional complexity compared to conventional NOMA. Furthermore, the fairness and BER performance of stronger users are significantly improved through the combined use of PH and optimal power allocation.

As the main issue in pinching-antenna system design, antenna location optimization is key to realizing channel reconfigurability and system flexibility. Most existing works in this area adopt sophisticated optimization and learning tools to identify the optimal antenna locations in a numerical manner, where insightful understandings of the pinching antenna placement are still missing. Motivated by this research gap, this paper aims to carry out analytical optimization for pinching antenna placement, where closed-form solutions for the optimal antenna locations are obtained to reveal the impact of antenna placement on the system performance. In particular, for the user-fairness-oriented orthogonal multiple access (OMA) based transmission, analytical results are obtained to reveal that the pinching antenna needs to be activated at the place that would be beneficial to all served users; however, the users' distances to the waveguide have no impact on the location selection. For the greedy-allocation-based OMA transmission, an asymptotic study based on a high signal-to-noise ratio approximation is carried out to show that the optimal antenna location is in close proximity to the user who is nearest to the waveguide. For non-orthogonal multiple access (NOMA) based transmission, even with a user-fairness-oriented objective, the obtained analytical results show that the optimal antenna location is not the position that can benefit all users, but rather is near the user positioned closest to the waveguide.

This paper exploits the dynamic features of wireless propagation environments as the basis for a new multiple access technique, termed environment division multiple access (EDMA). In particular, with the proposed pinching-antenna-assisted EDMA, the multi-user propagation environment is intelligently reconfigured to improve the signal strength at intended receivers and simultaneously suppress multiple-access interference, without requiring complex signal processing, e.g., precoding, beamforming, or multi-user detection. The key to creating a favorable propagation environment is to utilize the capability of pinching antennas to reconfigure line-of-sight (LoS) links, e.g., pinching antennas are placed at specific locations, such that interference links are blocked on purpose. Based on a straightforward choice of the pinching-antenna locations, the ergodic sum-rate gain of EDMA over conventional multiple access and the probability that EDMA achieves a larger instantaneous sum rate than the considered benchmarking scheme are derived in closed form. The obtained analytical results demonstrate the significant potential of EDMA for supporting multi-user communications. Furthermore, pinching antenna location optimization is also investigated, since the locations of the pinching antennas are critical for reconfiguring LoS links and large-scale path losses. Two low-complexity algorithms are developed for uplink and downlink transmission, respectively, and simulation results are provided to show their optimality in comparison to exhaustive searches.

This paper addresses the challenge of training federated learning (FL) algorithms over practical wireless networks enhanced by non-orthogonal multiple access (NOMA). In FL procedures, model parameters are transmitted over wireless links, and factors such as packet errors can significantly impact training quality, especially with non-independent and identically distributed (non-IID) datasets. To address this issue, we formulate the complex learning and wireless resource allocation problem as an optimization task aimed at minimizing an FL loss function, thereby capturing the performance of the FL algorithm. Under mild assumptions, we derive the expected convergence rate of the FL algorithm, quantifying the impact of wireless factors on FL. Leveraging this convergence analysis, we determine the optimal transmit power for each user through quadratic transform (QT) and a proposed low-complexity iterative method with successive convex approximation (SCA) serving as benchmark. Extensive simulation results demonstrate that the proposed scheme significantly outperforms traditional schemes from both the optimization and FL performance perspectives.

This article investigates the beam training design for pinching-antenna systems (PASS) in the near-field communication region, where single-waveguide-single-user (SWSU), single-waveguide-multi-user (SWMU) and multi-waveguide-multi-user (MWMU) scenarios are considered. For SWSU-PASS, we design a scalable codebook, based on which we propose a three-stage beam training (3SBT) scheme. Specifically, 1) firstly, the 3SBT scheme utilizes one activated pinching antenna to obtain a coarse one-dimensional location at the first stage; 2) secondly, it achieves further phase matching with an increased number of activated antennas at the second stage; 3) finally, it realizes precise beam alignment through an exhaustive search at the third stage. For SWMU-PASS, based on the scalable codebook design, we propose an improved 3SBT scheme to support non-orthogonal multiple access (NOMA) transmission. For MWMU-PASS, we first present a generalized expression of the received signal based on the partially-connected hybrid beamforming structure. Furthermore, we introduce an increased-dimensional scalable codebook design, based on which an increased-dimensional 3SBT scheme is proposed. Numerical results reveal that: i) the proposed beam training schemes can significantly reduce the training overhead compared to the two-dimensional exhaustive search, while maintaining the same training accuracy; ii) PASS yields better flexibility and improved performance compared to several benchmark schemes.

Unlike conventional systems using a fixed-location antenna, the channel capacity of the pinching-antenna system (PASS) is determined by the activated positions of pinching antennas. This article characterizes the capacity region of multiuser PASS, where a single pinched waveguide is deployed to enable both uplink and downlink communications. The capacity region of the uplink channel is first characterized. i) For the single-pinch case, closed-form expressions are derived for the optimal antenna activation position, along with the corresponding capacity region and the achievable data rate regions under time-division multiple access (TDMA) and frequency-division multiple access (FDMA). It is proven that the capacity region of PASS encompasses that of conventional fixed-antenna systems, and that the FDMA rate region contains the TDMA rate region. ii) For the multiple-pinch case, inner and outer bounds on the capacity region are derived using an element-wise alternating antenna position optimization technique and the Cauchy-Schwarz inequality, respectively. The achievable FDMA rate region is also derived using the same optimization framework, while the TDMA rate region is obtained through an antenna position refinement approach. The analysis is then extended to the downlink PASS using the uplink-downlink duality framework. It is proven that the relationships among the downlink capacity and rate regions are consistent with those in the uplink case. Numerical results demonstrate that: i) the derived bounds closely approximate the exact capacity region, ii) PASS yields a significantly enlarged capacity region compared to conventional fixed-antenna systems, and iii) in the multiple-pinch case, TDMA and FDMA are capable of approaching the channel capacity limit.

Hierarchical Federated Learning (HFL) has emerged as a promising approach for scalable and communication-efficient model training in wireless networks. However, achieving energy efficiency while ensuring convergence remains challenging due to limited bandwidth resource and strict latency constraints. This paper addresses energy-efficient HFL under both statistical and system heterogeneity, aiming to minimize long-term energy consumption through adaptive and unbiased edge scheduling and resource allocation in dynamic environments. A convergence analysis is first conducted without relying on a convex assumption, explicitly characterizing the influences of the number of scheduled edges and scheduling probabilities. An iterative algorithm is then proposed to jointly optimize these variables: the scheduling probabilities are solved by using a Barrier Method (BM) with an Infeasible-Start Newton Method (ISNM), while the number of scheduled edges is derived in a closed form. To further enhance communication efficiency, Non-Orthogonal Multiple Access (NOMA) is employed at the user–edge layer. Then, a joint optimization of inter-edge bandwidth allocation and intra-edge local resource allocation is developed to balance computation and communication overhead. Extensive simulations demonstrate that the proposed framework significantly outperforms existing benchmarks in terms of energy consumption under Non-Independent and Identically Distributed (Non-IID) data and dynamic wireless environments.

Cell-free massive multiple-input multiple-output (MIMO) utilizes multiple access points (APs) distributed over a large coverage area as distributed antennas to simultaneously serve multiple user equipments (UEs). In order to guarantee its scalability, it is necessary to optimally select AP-UE association clusters, which is a combinatorial problem with high complexity. Although deep reinforcement learning (DRL) has notably emerged as a potential solution, its application to AP-UE association is still challenging due to the difficulty in exploring such large action spaces and slow convergence. Existing work has tackled this challenge by heavily punishing invalid actions in the reward function, which does not scale well. In this paper, an alternative action space shaping approach is proposed, where a tailored mapping algorithm is added to the policy network, transforming invalid actions to feasible ones, thereby ensuring that training time is not wasted in discovering invalid actions. Additionally, we propose to incorporate behavior cloning (BC) with a heuristic teacher to speed up learning. We show that the proposed algorithm can improve the spectral and energy efficiency compared to existing schemes.

Pinching antennas, as a novel flexible-antenna technology capable of establishing line-of-sight (LoS) connections and effectively mitigating large-scale path loss, have recently attracted considerable research interest. However, the implementation of ideal pinching-antenna systems involves determining and adjusting pinching antennas to an arbitrary position on waveguides, which presents challenges to both practical deployment and related optimization. This paper investigates a practical pinching-antenna system in multi-waveguide scenarios, where pinching antennas are installed at pre-configured discrete positions to serve downlink users with non-orthogonal multiple access (NOMA). To improve system throughput, a sophisticated optimization problem is formulated by jointly considering waveguide assignment, antenna activation, successive interference cancellation (SIC) decoding order design, and power allocation. By treating waveguide assignment and antenna activation as two coalition-formation games, a novel game-theoretic algorithm is developed, in which the optimal decoding order is derived and incorporated. For power allocation, monotonic optimization and successive convex approximation (SCA) are employed to construct global optimal and low-complexity solutions, respectively. Simulation results demonstrate that the NOMA based pinching-antenna system exhibits superior performance compared to the considered benchmark systems, and the proposed solutions provide significant improvement in terms of sum rate and outage probability.

In the literature of pinching-antenna systems, in-waveguide attenuation is often neglected to simplify system design and enable more tractable analysis. However, its effect on overall system performance has received limited attention in the existing literature. While a recent study has shown that, in line-of-sight (LoS)-dominated environments, the data rate loss incurred by omitting in-waveguide attenuation is negligible when the communication area is not excessively large, its effect under more general conditions remains unclear. This work extends the analysis to more realistic scenarios involving arbitrary levels of LoS blockage. We begin by examining a single-user case and derive an explicit expression for the average data rate loss caused by neglecting in-waveguide attenuation. The results demonstrate that, even for large service areas, the rate loss remains negligible under typical LoS blockage conditions. We then consider a more general multi-user scenario, where multiple pinching antennas, each deployed on a separate waveguide, jointly serve multiple users. The objective is to maximize the average sum rate by jointly optimize antenna positions and transmit beamformers to maximize the average sum rate under probabilistic LoS blockage. To solve the resulting stochastic and nonconvex optimization problem, we propose a dynamic sample average approximation (SAA) algorithm. At each iteration, this method replaces the expected objective with an empirical average computed from dynamically regenerated random channel realizations, ensuring that the optimization accurately reflects the current antenna configuration. Extensive simulation results are provided to the proposed algorithm and demonstrate the substantial performance gains of pinching-antenna systems, particularly in environments with significant LoS blockage.

Pinching-antenna systems have emerged as a promising flexible-antenna architecture for next-generation wireless networks, enabling enhanced adaptability and user-centric connectivity through antenna repositioning along waveguides. However, existing studies often overlook in-waveguide signal attenuation and in the literature, there is no comprehensive analysis on whether and under what conditions such an assumption is justified. This paper addresses this gap by explicitly incorporating in-waveguide attenuation into both the system model and algorithm design, and studying its impact on the downlink user data rates. We begin with a single-user scenario and derive a closed-form expression for the globally optimal antenna placement, which reveals how the attenuation coefficient and the user-to-waveguide distance jointly affect the optimal antenna position. Based on this analytical solution, we further provide a theoretical analysis identifying the system conditions under which in-waveguide attenuation has an insignificant impact on the user achievable rate. The study is then extended to the multi-user multiple-input multiple-output setting, where two efficient algorithms are developed, based on the weighted minimum mean square error method and the maximum ratio combining method, to jointly optimize beamforming and antenna placement. Simulation results validate the efficacy of the proposed algorithms and demonstrate that pinching-antenna systems substantially outperform conventional fixed-antenna baselines, underscoring their potential for future flexible wireless communications.

Pinching antennas, realized through position-adjustable radiating elements along dielectric waveguides, have emerged as a promising flexible-antenna technology thanks to their ability to dynamically reshape large-scale channel conditions. However, most existing studies focus on idealized LoS-dominated environments, overlooking the stochastic nature of realistic wireless propagation. This paper investigates a more practical multiuser pinching-antenna system under a composite probabilistic channel model that captures distance-dependent LoS blockage and NLoS scattering. To account for both efficiency and reliability aspects of communication, two complementary design metrics are considered: an average signal-to-noise ratio (SNR) metric characterizing long-term link quality and fairness, and an outage-constrained metric ensuring a prescribed reliability level. Based on these metrics, we formulate two optimization problems: the first seeks to maximize the minimum average SNR across users, while the second seeks to maximize a guaranteed SNR threshold subject to per-user outage constraints. Although both problems are inherently nonconvex, we exploit their underlying monotonic structures and develop low-complexity, bisection-based algorithms that achieve globally optimal solutions using only simple scalar evaluations. Extensive simulations validate the effectiveness of the proposed methods and demonstrate that pinching-antenna systems significantly outperform conventional fixed-antenna designs even under random LoS and NLoS channels.

Pinching-antenna systems (PASS) have been recently proposed to improve the performance of wireless networks by reconfiguring both the large-scale and small-scale channel conditions. However, existing studies ignore the physical constraints of antenna placement and assume fixed antenna radiation power. To overcome this limitation, this paper investigates the design of PASS, taking into account the motion power consumption of pinching antennas (PAs) and the impact of adjustable antenna radiation power. To that end, we minimize the average power consumption for a given quality-of-service (QoS) requirement by jointly optimizing the antenna positions, antenna radiation power ratios, and transmit beamforming. To the best of the authors’ knowledge, this is the first work to consider radiation power optimization in PASS, which provides an additional degree of freedom (DoF) for system design. The cases with both continuous and discrete antenna placement are considered, where the main challenge lies in the fact that the antenna positions affect both the magnitude and phase of the channel coefficients of PASS, making system optimization very challenging. To tackle the resulting unique obstacles, an alternating direction method of multipliers (ADMM)-based framework is proposed to solve the problem for continuous antenna movement, while its discrete counterpart is formulated as a mixed integer nonlinear programming (MINLP) problem and solved by the block coordinate descent (BCD) method. Simulation results validate the performance enhancement achieved by incorporating PA movement power consumption and adjustable radiation power into the PASS design, while also demonstrating the efficiency of the proposed optimization framework. The benefits of PASS over conventional multiple-input multiple-output (MIMO) systems in mitigating the large-scale path loss and inter-user interference are also revealed.

As an emerging flexible antenna technology for wireless communications, pinching-antenna systems offer distinct advantages in terms of cost efficiency and deployment flexibility. This paper investigates joint transmission strategies of the base station (BS) and pinching antennas (PAS), focusing specifically on how to cooperate efficiently between the BS and waveguide-mounted pinching antennas for enhancing the performance of the user equipment (UE). By jointly considering the performance, flexibility, and complexity, we propose three BS-PAS joint transmission schemes along with the best beamforming designs, namely standalone deployment (SD), semi-cooperative deployment (SCD) and full-cooperative deployment (FCD). More specifically, for each BS-PAS joint transmission scheme, we conduct a comprehensive performance analysis in terms of the power allocation strategy, beamforming design, and practical implementation considerations. We also derive closed-form expressions for the average received SNR across the proposed BS-PAS joint transmission schemes, which are verified through Monte Carlo simulations. Finally, numerical results demonstrate that deploying pinching antennas in cellular networks, particularly through cooperation between the BS and PAS, can achieve significant performance gains. We further identify and characterize the key network parameters that influence the performance, providing insights for deploying pinching antennas.

This study investigates the application of non-orthogonal multiple access (NOMA) to enable massive connectivity for a stacked intelligent metasurface (SIM) system that performs signal processing in the electromagnetic wave domain. To realize the full potential of NOMA assisted SIM systems, a radio resource allocation problem is accordingly formulated to jointly optimize the key decision variables, including the decoding order of users, the transmit power at the base station, as well as the phase shift at the SIM. By adhereing to the users’ quality-of-service (QoS) requirements, as well as the power budget of the base station, the problem is aimed at maximizing the admission rate of the system. Due to the problem’s inherent non-convexity and complexity, we recast it as a Markov decision process and employ a quantile regression deep Q-network (QRDQN) agent to optimize the decision variables. Recognizing the mobility of users and the dynamic reconfiguration of the system, we further enhance the QR-DQN model’s adaptability and generalization capabilities by incorporating a meta-learning strategy. Simulation results demonstrate that integrating NOMA with SIM systems yields a significant increase of 39% in the average number of served users compared to the conventional orthogonal multiple access based approach. The proposed resource allocation mechanism additionally improves deep deterministic policy gradient (DDPG) in literature by 27% in the number of served users.

This paper aims to reveal the potential of hybrid non-orthogonal multiple access (NOMA) in improving energy efficiency, which combines the advantages of NOMA and conventional orthogonal multiple access (OMA). In particular, a novel hybrid NOMA scheme is proposed, which can be implemented as an simple add-on to the legacy OMA network. Specifically, in the proposed hybrid NOMA scheme, a user can transmit signals by using not only its own allocated channel resource block as in OMA, but also sharing the channel of other users via NOMA. To release the potential of hybrid NOMA, a flexible successive interference cancellation (SIC) method is adopted. Rigorous analysis is provided, which indicates that even with less energy consumption, the proposed hybrid NOMA scheme offers a higher data rate than the conventional OMA scheme. The numerical results support the analysis and highlight the superior performance of HSIC in comparison to FSIC.

This paper aims to study the impact of non-orthogonal multiple access (NOMA) assisted grant-free transmissions on reducing age of information (AoI) in status updating systems. Particularly, an uplink communication scenario is considered, where multiple users upload their status updates to a destination competitively. To mitigate collisions among users,$K$reception signal-to-noise ratio (SNR) levels are pre-configured, which can be chosen randomly by the users. By applying NOMA, successive interference cancellation (SIC) is carried out at the receiver to decode the signals from different users sequentially. Different from most existing works which adopt generate-at-will (GAW) model for modeling the generating process of status updates' arrivals, this paper considers a more general model to characterize the randomness of the status updates' arrivals. Closed-form expressions for AoI achieved by the proposed NOMA assisted grant-free scheme is obtained. Numerical results are provided to validate the accuracy of the analytical results and also demonstrate the superior performance of the proposed scheme in reducing AoI compared to conventional OMA based methods.

With the flourishing development of sixth-generation wireless networks, the demand of spectrum efficiency rapidly increases, in order to support the demands of high-quality data transmission and connections of massive users. Among various promising technologies, the technology of near-field communications provides a great potential to address such an issue due to the unique spherical-wave channels for electromagnetic (EM) propagation. In this article, multiple-input-single-output (MISO) near-field communications is comprehensively studied to clarify the influences of the shape and structure of uniform planar array (UPA) on the system performance, considering three cases with uniform linear array (ULA), rectangular UPA, and circular UPA. In particular, we reveal the properties of rapid deterioration for signal-to-noise ratio (SNR) from the reduced projection aperture in near-field communications and investigate the single spherical crown antenna design and spherical crown antenna array design in order to address this issue. Moreover, we also characterize the role of antenna projection aperture in detail, and theoretically analyze the shape of UPA, yielding the corresponding exact closed-form expressions for SNR and outage probability (OP). Based on these above analytical results, we find out that adjusting the spacing between adjacent antennas to control the relative angle between user and selected antennas is an efficient way to improve the projection aperture of antenna and SNR. Simulation results are shown to well match analytical results, which validate the correctness of our analysis, clarifying that our proposed designs outperform the conventional works and illustrating a better stability for angle variations.

International audience

Backscatter communication (BackCom) holds immense potential for enhancing the capabilities of energy-constrained Internet of Things (IoT) devices and supporting a wide range of applications. Nonorthogonal multiple-access (NOMA) schemes are advantageous for meeting the demands of massive connectivity in next-generation communication networks, and NOMA-aided BackCom can leverage the benefits of both BackCom and NOMA. This article covers the basics of BackCom, explores different types of BackCom systems, and explains how NOMA can be integrated with BackCom, where various crucial issues, including design principles, channel state information (CSI) estimation, node pairing schemes, and reflection coefficient (RC) designs, are illustrated. Furthermore, this survey evaluates the effectiveness of different network architectures for NOMA-aided BackCom, especially in IoT networks, and identifies potential research directions and future trends in this area. The key considerations for designing and optimizing NOMA-aided BackCom systems in real-world scenarios are also highlighted in this survey. In addition, by reviewing the existing literature and research on NOMA-aided BackCom, this article provides valuable insights for researchers and practitioners interested in this emerging wireless communication technique.

This article characterizes the performance of mixed free-space optical (FSO)/active intelligent reflecting surface (IRS)-aided nonorthogonal multiple access (NOMA) communication in the presence of imperfect channel state information (CSI) and imperfect successive interference cancelation (SIC). The detrimental effects of atmospheric turbulence on the FSO communication link, which affects end-to-end communication, are also presented. Considering practical implementation, we illustrate the impact of phase quantization error, imperfect SIC, and imperfect CSI on the outage performance. Our numerical analysis indicates that the outage performance can be significantly improved by utilizing multiple transmit apertures through transmit aperture selection at the base station and employing multiple transmit antennas via maximum ratio transmission at the relay. In addition, the numerical results demonstrate that performance improvements are achieved by mitigating double path loss through an active IRS compared to a passive IRS. The closed-form expression for the outage probability is derived using methods of moments and then verified through Monte Carlo simulations. To gain more valuable insights, asymptotic expressions are also provided for high RF transmit power and high FSO transmit power scenarios. Consequently, diversity orders are derived for an asymptotic study of the outage performance of the considered NOMA network.

The key idea of hybrid non-orthogonal multiple access (NOMA) is to allow users to use the bandwidth resources to which they cannot have access in orthogonal multiple access (OMA) based legacy networks while still guaranteeing its compatibility with the legacy network. However, in a conventional hybrid NOMA downlink network, some users have access to more bandwidth resources than others, which leads to a potential performance loss. So what if the users can access the same amount of bandwidth resources? This letter focuses on a simple two-user scenario, and develops analytical and simulation results to reveal that for this considered scenario, conventional hybrid NOMA is still an optimal transmission strategy.

Flexible-antenna systems have recently received significant research interest due to their capability to reconfigure wireless channels intelligently. This paper focuses on a new type of flexible-antenna technology, termed pinching antennas, which can be realized by applying small dielectric particles on a waveguide. Analytical results are first developed for the simple case with a single pinching antenna and a single waveguide, where the unique feature of the pinching-antenna system to create strong line-of-sight links and mitigate large-scale path loss is demonstrated. An advantageous feature of pinching-antenna systems is that multiple pinching antennas can be activated on a single waveguide at no extra cost; however, they must be fed with the same signal. This feature motivates the application of non-orthogonal multiple access (NOMA), and analytical results are provided to demonstrate the superior performance of NOMA-assisted pinching-antenna systems. Finally, the case with multiple pinching antennas and multiple waveguides is studied, which resembles a classical multiple-input single-output (MISO) interference channel. By exploiting the capability of pinching antennas to reconfigure the wireless channel, it is revealed that a performance upper bound on the interference channel becomes achievable, where the achievability conditions are also identified. Computer simulation results are presented to verify the developed analytical results and demonstrate the superior performance of pinching-antenna systems.

This paper considers the cost minimization problem in a heterogeneous mobile edge computing network, where the macro base stations are scattered over the ground to ensure the service coverage, and the small base stations are clustered around the user hotspots to improve the users’ quality of service. Specifically, the network-wide communication and computation performance are analyzed using stochastic geometry and queueing theory. Taking the obtained performance metrics as constraints, a cost minimization problem is formulated. To solve the formulated problem, we propose a globally optimal algorithm, whose optimality and complexity are theoretically analyzed. Then, to further reduce the computational complexity, the problem is reformulated as the difference of convex programming problems, which can be addressed by the concave-convex procedure. Numerical simulations verify the accuracy of the theoretical results and illustrate the superiority of the proposed algorithms.

Large language models (LLMs) have shown great promise in many domains, yet their potential to transform wireless communications, where the escalating complexity of the network outpaces traditional model-based methods, remains largely untapped. Addressing this gap is critical for the next generation of intelligent and adaptive 6G systems. In this work, we develop a specialized dataset aimed at enhancing the evaluation and fine-tuning of LLMs specifically for wireless communication applications. The dataset includes a diverse set of multi-hop questions, including true/false and multiple-choice types, spanning varying difficulty levels from easy to hard. By utilizing advanced language models for entity extraction and question generation, rigorous data curation processes are employed to maintain high quality and relevance. Additionally, we introduce a Pointwise V-Information (PVI) based fine-tuning method, providing a detailed theoretical analysis and justification for its use in quantifying the information content of training data with 2.24% and 1.31% performance boost for different models compared to baselines, respectively. To demonstrate the effectiveness of the fine-tuned models with the proposed methodologies on practical tasks, we also consider different tasks, including summarizing optimization problems from technical papers and solving the mathematical problems related to non-orthogonal multiple access (NOMA), which are generated by using the proposed multi-agent framework. Simulation results show significant performance gain in summarization tasks with 20.9% in the ROUGE-L metrics. We also study the scaling laws of fine-tuning LLMs and the challenges LLMs face in the field of wireless communications, offering insights into their adaptation to wireless communication tasks. This dataset and fine-tuning methodology aim to enhance the training and evaluation of LLMs, contributing to advancements in LLMs for wireless communication research and applications.

Non-orthogonal multiple access (NOMA) is recognized as a pivotal technology for enhancing spectral efficiency and facilitating massive connectivity in wireless communications. In practice, users are often divided into groups that occupy different resource blocks, while the users in the same group share the same resource through power-domain multiplexing, leading to multi-group NOMA (MG-NOMA). Hence, the full benefit of MG-NOMA relies on optimum power allocation, which, unfortunately, leads to difficult optimization problems that have not been well solved so far. This work investigates the optimal power allocation to achieve the maximum spectral efficiency and energy efficiency with quality-of-service (QoS) requirements and arbitrary user weights in MG-NOMA. We show that the complicated MG-NOMA power allocation problems can be decomposed into two layers, the lower layer for power allocation within each group and the upper layer for the power budget allocation among groups. More importantly, we reveal that, although quite difficult, the two-layer problems both contain the hidden convexity, indicating the achievability of the globally optimal solution. Then, we derive the optimal power allocation in either closed or semi-closed form for the maximum spectral efficiency and energy efficiency in MG-NOMA, respectively. The simulation results demonstrate the superiority of the proposed optimal power allocation schemes.

This paper studies the application of cognitive radio inspired non-orthogonal multiple access (CR-NOMA) to reduce age of information (AoI) for uplink transmission. In particular, a time division multiple access (TDMA) based legacy network is considered, where each user is allocated with a dedicated time slot to transmit its status update information. The CR-NOMA is implemented as an add-on to the TDMA legacy network, which enables each user to have more opportunities to transmit by sharing other user’s time slots. A rigorous analytical framework is developed to obtain the expressions for AoIs achieved by CR-NOMA with and without re-transmission, by taking the randomness of the status update generating process into consideration. Numerical results are presented to verify the accuracy of the developed analysis. It is shown that the AoI can be significantly reduced by applying CR-NOMA compared to TDMA.Moreover, the use of re-transmission is helpful to reduce AoI, especially when the status arrival rate is low.

In distributed edge networks employing frequency division duplex, the feedback of channel state information (CSI) from the edge devices to the edge server always consumes a lot of spectrum resources, resulting in a serious communication burden. In this paper, we first propose an end-to-end unfolding neural network framework inspired by the soft threshold iterative algorithm (U-ISTANet). The proposed U-ISTANet integrates the advantages of compression awareness and neural networks. Especially, the compression matrix and sparse transformation of channel matrix can be learned for accurate CSI compression and recovery. And a lightweight version of U-ISTANet, called U-ISTANet-L, is proposed to reduce the training parameters. To reduce the data transmission overhead in the centralized learning framework, we extend the proposed U-ISTANet-L to a federated U-ISTANet-L (FU-ISTANet-L), which can train a more generalizable model by increasing the number of edge devices to enlarge the data set in a distributed learning manner. The proposed FU-ISTANet-L reduces the transmission overhead and increases the training speed while achieving a performance close to that of centralized learning. Furthermore, we propose a personalized FU-ISTANet-L (P-FU-ISTANet-L) to solve the heterogeneous data training problem in different communication environments. Specifically, we first obtain a pre-trained model by federation unfolding learning, and then each edge device fine-tunes the model using only a small amount of train data to obtain a personalized model for local channel environment. Extensive experimental results are provided to show that the proposed networks achieve a significant performance over the benchmarking schemes in terms of the normalized mean square error.

The Pinching-Antenna SyStem (PASS) is a revolutionary flexible antenna technology designed to enhance wireless communication by establishing strong line-of-sight (LoS) links, reducing free-space path loss and enabling antenna array reconfigurability. PASS uses dielectric waveguides with low propagation loss for signal transmission, radiating via a passive pinching antenna, which is a small dielectric element applied to the waveguide. This paper first proposes a physics-based hardware model for PASS, where the pinching antenna is modeled as an open-ended directional coupler, and the electromagnetic field behavior is analyzed using coupled-mode theory. A simplified signal model characterizes the coupling effect between multiple antennas on the same waveguide. Based on this, two power models are proposed: equal power and proportional power models. Additionally, a transmit power minimization problem is formulated/studied for the joint optimization of transmit and pinching beamforming under both continuous and discrete pinching antenna activations. Two algorithms are proposed to solve this multimodal optimization problem: the penalty-based alternating optimization algorithm and a low-complexity zero-forcing (ZF)-based algorithm. Numerical results show that 1) the ZF-based low-complexity algorithm performs similarly to the penalty-based algorithm, 2) PASS reduces transmit power by over 95% compared to conventional and massive MIMO, 3) discrete activation causes minimal performance loss but requires a dense antenna set to match continuous activation, and 4) the proportional power model yields performance comparable to the equal power model.

Pinching antennas, implemented by applying small dielectric particles on a waveguide, have emerged as a promising flexible-antenna technology ideal for next-generation wireless communications systems. Unlike conventional flexible-antenna systems, pinching antennas offer the advantage of creating line-of-sight (LoS) links by enabling antennas to be activated on the waveguide at a position close to the users. This paper investigates a typical two-user non-orthogonal multiple access (NOMA) down-link scenario, where multiple pinching antennas are activated on a single dielectric waveguide to assist NOMA transmission. We formulate the problem of maximizing the data rate of one user subject to the quality-of-service (QoS) requirement of the other user by jointly optimizing the antenna positions and power allocation coefficients. The formulated problem is nonconvex and difficult to solve due to the impact of antenna positions on large-scale path loss and two types of phase shifts, namely in-waveguide phase shifts and free space propagation phase shifts. To this end, we propose an iterative algorithm based on block coordinate descent and successive convex approximation techniques. Moreover, we consider the special case with a single pinching antenna, which is a simplified version of the multi-antenna case. Although the formulated problem is still nonconvex, by using the inherent features of the formulated problem, we derive the global optimal solution in closed-form, which offers important insights on the performance of pinching-antenna systems. Simulation results demonstrate that the pinching-antenna system significantly outperforms conventional fixed-position antenna systems, and the proposed algorithm achieves performance comparable to the computationally intensive exhaustive search based approach.

As a new paradigm focusing on transmitting the meaning of information, semantic communications (SCs) have been revealed significant potential in alleviating network congestion and improving energy efficiency. By extracting a small-size semantic feature from the large-size raw-data, the communication loads can be reduced at a price of more computing power, i.e., the computational resource used in semantic extraction. In this paper, we explore the computation dimension to improve the communication performance in an uplink SC system. The SC-oriented user first compresses its original data via local computing during other users’ transmission time and then transmits it to the base station within the assigned time. To achieve a balanced tradeoff between communications and computing, we formulate an optimization problem to minimize the energy consumption of all users by jointly considering the compression ratio and time allocation. We first propose an efficient general algorithm that can be applied to different SC models. To gain more insights, we then derive the closed-form solutions for two special cases: equal-time allocation and two-user transmission. The obtained analytical results reveal a pronounced energy saving of adopting SC, especially for large transmitted data size, high transmission energy coefficient, scarce time resources, and poor channel conditions. Simulation results reveal that our proposed SC-based scheme achieves excellent performance in terms of saving energy consumption compared to the conventional communication.

This work proposes an efficient two-stage jamming detection and channel estimation algorithm for orthogonal frequency division multiplexing (OFDM)-based unmanned aerial vehicles (UAVs) communications. The proposed scheme is designed based on the unique time and frequency domain statistical characteristics of OFDM signals. In the time domain (TD), a likelihood ratio test (LRT)-based decision rule is derived as a function of the inherent correlation between the cyclic prefix (CP) samples and their counterparts in the OFDM symbol. In addition, in the frequency domain (FD), a closed-form joint jamming detection and channel estimation scheme is derived using the maximum a posteriori probability (MAP) principle as a function of the statistics of the received pilots and virtual subcarriers (VSCs) signals, which is then re-expressed using the generalized MAP ratio test (GMAPRT). The system’s complexity is reduced by applying the two stages sequentially, where the possible implementation of the second stage is conditioned on the outcome of the first stage. The performance of the proposed algorithm is evaluated using Monte Carlo simulations, where the results demonstrate its effectiveness compared to the TD-only and FD-only approaches. The results confirm the superior performance of the proposed scheme compared to the cyclostationary feature (CF)-based technique under various operating scenarios.

This paper investigates the graph neural network (GNN)-enabled beamforming design for interference channels. We propose a model termed interference channel GNN (ICGNN) to solve a quality-of-service constrained energy efficiency maximization problem. The ICGNN is two-stage, where the direction and power parts of beamforming vectors are learned separately but trained jointly via unsupervised learning. By formulating the dimensionality of features independent of the transceiver pairs, the ICGNN is scalable with the number of transceiver pairs. Besides, to improve the performance of the ICGNN, the hybrid maximum ratio transmission and zero-forcing scheme reduces the output ports, the feature enhancement module unifies the two types of links into one type, the subgraph representation enhances the message passing efficiency, and the multi-head attention and residual connection facilitate the feature extracting. Furthermore, we present the over-the-air distributed implementation of the ICGNN. Ablation studies validate the effectiveness of key components in the ICGNN. Numerical results also demonstrate the capability of ICGNN in achieving near-optimal performance with an average inference time less than 0.1 ms. The scalability of ICGNN for unseen problem sizes is evaluated and enhanced by transfer learning with limited fine-tuning cost. The results of the centralized and distributed implementations of ICGNN are illustrated.

Hybrid non-orthogonal multiple access (H-NOMA) has recently received significant attention as a general framework of multiple access, where both conventional orthogonal multiple access (OMA) and pure NOMA are its special cases. This paper focuses on the application of H-NOMA to ambient Internet of Things (IoT) with energy-constrained devices, where a new backscatter communication (BackCom) assisted H-NOMA uplink scheme is developed. Resource allocation for H-NOMA uplink transmission is also considered, where an overall power minimization problem is formulated. Insightful understandings for the key features of BackCom assisted H-NOMA and its difference from conventional H-NOMA are illustrated by developing analytical results for the two-user special case. For the general multi-user scenario, two algorithms, one based on the branch-bound (BB) principle and the other based on successive convex approximation (SCA), are developed to realize different tradeoffs between the system performance and complexity. The numerical results are also provided to verify the accuracy of the developed analytical results and demonstrate the performance gain of H-NOMA over OMA.

Hybrid non-orthogonal multiple access (NOMA) has received considerable recent interest due to its ability to efficiently use resources from different domains and also its compatibility with various orthogonal multiple access (OMA) based legacy networks. Unlike existing studies of hybrid NOMA that focus on combining NOMA with time-division multiple access (TDMA), this work considers hybrid NOMA assisted orthogonal frequency-division multiple access (OFDMA) uplink transmission. In particular, the impact of a unique feature of hybrid NOMA assisted OFDMA, i.e., the availability of users’ dynamic channel state information, on the system performance is analyzed from the following two perspectives. From the optimization perspective, analytical results are developed which show that with hybrid NOMA assisted OFDMA, the pure OMA mode is rarely adopted by the users, and the pure NOMA mode could be optimal for minimizing the users’ energy consumption, which differs from the hybrid TDMA case. From the statistical perspective, two new performance metrics, namely the power outage probability and the power diversity gain, are developed to quantitatively measure the performance gain of hybrid NOMA over OMA. The developed analytical results also demonstrate the ability of hybrid NOMA to meet the users’ diverse energy profiles.

The combination of non-orthogonal multiple access (NOMA) and mobile edge computing (MEC) has recently received great attention for maximizing energy efficiency (EE) in wireless networks. Previous studies mainly focus on single-ratio EE maximization using pure orthogonal multiple access (OMA) or NOMA scheme in MEC networks. This paper proposes a dynamic hybrid NOMA scheme that dynamically transforms between pure OMA and pure NOMA under the general network status in the multi-user MEC network. An offloading multi-ratio and non-convex EE problem is formulated. Two iterative algorithms, i.e., the successive Dinkelbach method-based algorithm and the closed-form nested fractional programming (FP) algorithm, are proposed to efficiently solve the offloading EE over multiple users’ time and power within polynomial time based on different FP techniques, which provides feasible ideas to solve such multi-ratio optimization problems. The Dinkelbach method-based algorithm decomposes and optimizes the offloading EE user-wise. The nested FP algorithm jointly maximizes multiple users’ EE by transforming the multi-ratio problem into equivalent linear forms, where the closed-form power solution is obtained. Simulation results show the superiority of the dynamic hybrid NOMA strategy and the feasibility of the two proposed algorithms. Critical insights are obtained over the dynamic hybrid NOMA strategies in the general MEC network.

This paper investigates a reconfigurable intelligent surface (RIS)-assisted wireless powered mobile edge computing (MEC) system, where an access point (AP) integrated with an MEC server first transmits energy signals to charge multiple energy-constrained devices in the downlink (DL), and then the devices utilize the harvested energy to perform MEC offloading in the uplink (UL) assisted by an RIS. Specifically, three multiple access protocols for MEC offloading, namely pure non-orthogonal multiple access (NOMA), pure orthogonal multiple access, and hybrid NOMA, are proposed to exploit dynamic RIS beamforming and energy recycling among devices to enhance the efficiencies of energy harvesting and MEC offloading. For each of the three protocols, a joint resource allocation framework of the AP/devices transmit power, the RIS phase shifts, and the DL/UL time allocation is formulated to minimize the energy consumption at the AP. Because of those highly coupled optimization variables, the formulated optimization problems are first shown to be non-convex, and then the intrinsic structure of the problems is exploited to devise computationally-efficient algorithms and solve them iteratively. Numverical results are provided to demonstrate the performance improvement of our proposed designs compared to various benchmark schemes, and reveal the practical significance of the considered multiple access protocols with dynamic RIS beamforming and energy recycling for spectral and energy efficient MEC offloading.

The sixth-generation (6G) wireless network aims to deliver remarkable advancements in system throughput, energy efficiency, traffic capacity per area, spectral efficiency, and low latency. Achieving these goals requires a highly adaptable radio interface capable of efficiently managing limited frequency resources, necessitating the development of new multiple access techniques and waveforms. In large-bandwidth multi-user networks, intersymbol interference (ISI) and inter-user interference (IUI) pose significant design challenges. Time reversal (TR) has emerged as a promising waveform candidate for 6G, as it focuses signal energy in both the time and space domains within multipath environments. Meanwhile, non-orthogonal multiple access (NOMA) offers high spectral efficiency and improved connectivity by serving multiple users over the same time-frequency-code resources. This paper explores the integration of NOMA and TR to address these challenges and proposes, for the first time in the literature, a novel receiver architecture for downlink NOMA-based TR communications, which does not require precoding at the transmitter. Specifically, power-domain NOMA is employed at the transmitter, and TR filtering is applied at each receiver. We derive novel approximated expressions for the pairwise error probability (PEP), a key element in determining the union bound on the bit error rate (BER), to assess user performance. Extensive Monte Carlo simulations are carried out to validate these analytical expressions, providing critical insights into the error rate performance for each user. Additionally, we evaluate the performance gains of the proposed NOMA-based TR receiver over the orthogonal multiple access scheme, known as time-reversal multiple access (TRMA). Results show that our approach significantly outperforms TRMA in terms of BER, particularly in sparse multipath environments, with an average BER improvement of 73.5% to 98.31%. Furthermore, our findings reveal that at high signal-to-noise ratios, the diversity gain for a specific user is proportional to the product of the user’s order, determined by its channel strength, and the number of its channel taps.

Hybrid non-orthogonal multiple access (NOMA), which organically combines pure NOMA and conventional OMA, has recently received significant attention to be a promising multiple access framework for future wireless communication networks. However, most of the literatures on hybrid NOMA only consider fixed order of successive interference cancellation (SIC), namely FSIC, for the NOMA transmission phase of hybrid NOMA, resulting in limited performance. Differently, this paper aims to reveal the potential of applying hybrid SIC (HSIC) to improve the energy efficiency of hybrid NOMA. Specifically, a HSIC aided hybrid NOMA scheme is proposed, which can be treated as a simple add-on to the legacy orthogonal multiple access (OMA) based network. The proposed scheme offers some users (termed “opportunistic users”) to have more chances to transmit by transparently sharing legacy users’ time slots. For a fair comparison, a power reducing coefficient$\beta $is introduced to ensure that the energy consumption of the proposed scheme is less than conventional OMA. Given$\beta $, the probability for the event that the achievable rate of the proposed HSIC aided hybrid NOMA scheme cannot outperform its OMA counterpart is obtained in closed-form, by considering impact of user pairing. Furthermore, asymptotic analysis shows that the aforementioned probability can approach zero in the high SNR regime under some given conditions, which are compositely determined by the users’ transmit powers, primary user’s target data rate and$\beta $, indicating that the energy efficiency of the proposed scheme is almost surely higher than that of OMA for these given conditions. Numerical results are presented to verify the analysis and also demonstrate the benefit of applying HSIC compared to FSIC.

This paper investigates wireless federated learning in data heterogeneous scenarios, where device selection usually leads to a degradation in learning performance. This paper is motivated by the fact that while training deep learning networks using federated stochastic gradient descent (FedSGD) on non-independent and identically distributed (non-IID) datasets, device selection can generate gradient errors that accumulate, leading to potential weight divergence, which is further exacerbated with low device participation. To mitigate weight divergence, an age-weighted FedSGD algorithm is designed in this paper to scale local gradients according to the previous device selection results. Furthermore, by revealing the relationship between device participation and latency, an energy consumption minimization problem is formulated accordingly, which consists of resource allocation and sub-channel assignment. By transforming the resource allocation problem into convex and utilizing KKT conditions, we derive the optimal resource allocation solution. Moreover, this paper develops a matching based algorithm to generate the enhanced sub-channel assignment. Simulation results indicate that 1) age-weighted FedSGD is able to outperform conventional FedSGD in terms of convergence rate and achievable accuracy, and 2) the proposed resource allocation and sub-channel assignment strategies can significantly reduce energy consumption and improve learning performance by increasing device participation.

This paper investigates the performance of simultaneously transmitting and reflecting surface (STARS) assisted semi-grant-free non-orthogonal multiple access network with randomly distributed users. By deploying STARS, the transmit signals of grant-based user (GBU) and grant-free users (GFUs) can be exquisitely adjusted to reduce interference. We propose a maximum channel scheduling (MCS) protocol that allows a GFU to access GBU’s channel with the assistance of STARS. In particular, the impacts of perfect/imperfect successive interference cancellation (pSIC/ipSIC) on MCS protocol are taken into account. To characterize the performance of STARS aided MCS (STARS-MCS) network, we derive the expressions of outage probability for GBU and GFU with pSIC/ipSIC. By applying convolution theorem and Laplace transform, the asymptotic expressions of outage probability and diversity orders for GBU and GFU are attained. We further design a STARS-based power control (SPC) strategy to eliminate the outage probability error floor and improve the outage performance. Numerical results show that: 1) The performance of STARS-MCS outperforms the existing benchmarks in terms of outage probability and system throughput; 2) The SPC strategy can effectively improve the performance of the STARS-MCS network and eliminate the outage probability error floor at high signal-to-noise ratios; and 3) By adjusting reflection and transmission coefficients of STARS, the outage performance of GBU and GFU can be greatly enhanced.

The integration of non-orthogonal multiple access (NOMA) into low earth orbit (LEO) systems has the potential to facilitate the ubiquitous coverage with high spectrum efficiency. To characterize the fundamental limits of NOMA assisted LEO systems, this paper proposes a model for downlink NOMA-LEO system via modelling the locations of terrestrial users and LEO satellites as two homogeneous spherical Poisson point processes. In particular, a typical satellite uses NOMA to simultaneously serve the nearest and the farthest users within its visible range. The novelty of this paper is to first introduce an equivalent two-dimensional model that can significantly simplify the performance analysis of LEO systems. Then, considering that the satellite-terrestrial channel follows the Nakagami-mfading, the closed-form expressions of the user association and the visible probability are studied under the scenario where the number of users visible to a randomly selected satellite is greater than one. Subsequently, the derived results are utilized to analyze the approximate moments of the conditional success probability and the signal-to-interference-plus-noise ratio Meta distribution for both NOMA-LEO and orthogonal multiple access (OMA) LEO transmissions. Finally, the numerical results demonstrate that:1)Asymmetric target rates can achieve a performance gain of NOMA over OMA in terms of the link reliability and the coverage probability, while symmetric settings still have merit for NOMA if there is a low requirement for reliability; and2)Enhancements in the link reliability and the coverage probability are achievable through improvements in channel quality and reductions in orbital altitude and density. However, improving path loss develops the coverage probability but may not always yield an increase in the link reliability.

This paper proposes a novel deep learning enabled beamforming design for ultra-dense wireless networks by integrating prior knowledge and graph neural network (GNN), termed model-based GNN. An energy efficiency (EE) maximization problem is first subject to the power budget and quality of service (QoS) requirements, and then reformulated based on the minimum mean square error scheme and the hybrid zero-forcing and maximum ratio transmission scheme. The model-based GNN is designed to realize the mapping from channel state information to beamforming vectors to address the reformulated problems. Particularly, the multi-head attention mechanism and the residual connection are adopted to enhance the feature extracting, and a scheme selection module is designed to improve the adaptability to channel conditions. The unsupervised learning is adopted, and a various-input training strategy is proposed to enhance the stability of the model-based GNN. Numerical results demonstrate that the proposed model-based GNN can realize a millisecond-level inference with limited performance loss, the scalability to different numbers of users and the adaptability to various channel conditions and QoS requirements in ultra-dense wireless networks.

In this paper, we focus on computation-aware offloading for executing deep neural network (DNN) inference tasks in a mobile edge computing (MEC) system. To cope with the challenges of insufficient wireless resources during task offloading, we resort to semantic communications (SCs), through which the users can offload the compressed task data to the edge server for remote execution. Specifically, we establish the relationship between the compression ratio and computation ratio for different DNN tasks. To achieve energy-efficient offloading, we formulate an optimization problem to minimize the energy consumption of all users by jointly optimizing the compression ratio, computation allocation, uploading time, and DNN layer selection. We first consider a special case with the preconfigured time scheduling and derive closed-form solutions to computation allocation and offloading time, which yield a threshold-based structure determined by users’ channel conditions and local computation consumption. Inspired by the characteristics of these optimal solutions, a general low-complexity iterative algorithm is then designed to solve the original non-convex problem. Simulation results demonstrate that our proposed SC-based computation -offloading scheme can substantially reduce users’ energy consumption compared to the conventional offloading and full offloading, especially with scarce wireless resources.

In this paper, we conduct a theoretical analysis of how to integrate reconfigurable intelligent surfaces (RIS) with cooperative non-orthogonal multiple access (NOMA), considering URLLC. We consider a downlink two-user cooperative NOMA system employing short-packet communications, where the two users are denoted by the central user (CU) and the cell-edge user (CEU), respectively, and an RIS is deployed to enhance signal quality. Specifically, compared to CEU, CU lies nearer from BS and enjoys the higher channel gains. Closed-form expressions for the CU’s average block error rate (BLER) are derived. Furthermore, we evaluate the CEU’s BLER performance utilizing selective combining (SC) and derive a tight lower bound under maximum ratio combining (MRC). Simulation results are provided to our analyses and demonstrate that the RIS-assisted system significantly outperforms its counterpart without RIS in terms of BLER. Notably, MRC achieves a squared multiple of the diversity gain of the SC, leading to more reliable performance, especially for the CEU. Furthermore, by dividing the RIS into two zones, each dedicated to a specific user, the average BLER can be further reduced, particularly for the CEU.

A near-field sensing (NISE)-enabled user tracking scheme is proposed. Compared to conventional angle-only sensing in the far-field scenario, NISE offers the capability of joint angle and distance sensing. In the proposed user tracking scheme, a deep unfolding neural network (DUNN)-based method is employed to sense radial and transverse velocities, which can further facilitate predicting the user’s location in the next time instant. Specifically, the DUNN is training on a synthesized dataset to update trainable parameters in an offline manner. Then, the DUNN is implemented online to extract the radial and transverse velocities from the received echo signal. Moreover, an online fine-tuning module is attached to the DUNN to refine the output of the pre-trained DUNN. Finally, based on estimated velocities, the user position in the consecutive time instant can be predicted, thus enabling user tracking. Simulation results show that the proposed scheme can extract velocities from echo signals and track the user accurately.

The beamforming performance of the uniform circular array (UCA) in near-field wideband communication systems is investigated. Firstly, the unique beam squint effect in near-field wideband UCA systems is analyzed in both the distance and angular domains. It is demonstrated that the generated beams at different frequencies are focused at different locations, resulting in significant beamforming loss. To alleviate this unique beam squint effect and facilitate beamfocusing, an energy-efficient beamforming scheme based on the true-time delay (TTD) architecture is proposed. Specifically, the phase shifters (PSs) and the time delay of TTDs are designed based on the analytical formula for beamforming gain. Additionally, the minimum number of TTDs required to achieve a predetermined beamforming gain while minimizing energy consumption is quantified. Numerical results show that the proposed beamforming scheme effectively eliminates the near-field beam squint and outperforms the conventional schemes in terms of spectral efficiency and energy efficiency.

The paper explores hybrid free-space optical (FSO) and active intelligent reflecting Surface (IRS)-aided radio frequency (RF) transmission in non-orthogonal multiple access (NOMA) networks to improve outage performance of internet of things (IoT) devices under imperfect channel state information (imCSI) and imperfect successive interference cancellation (imSIC). The superposed signal is transmitted from the source to the relay over FSO link exploiting the line of sight (LOS) path modeled as Gamma-Gamma distribution. Whereas RF signals transmission from the relay to IoT devices are boosted through an active-IRS. The multiplication factor of path-loss is prominent in the presence of a direct path from the relay to IoT devices. The active-IRS can mitigate the issue. In this paper, the direct path is modeled using a Rayleigh distribution, while the indirect paths via the Active-IRS are modeled using a Rician distribution. The paper demonstrates the impact of active noise introduced by the Active-IRS on outage performance. The closed-form expression for outage probability is derived under imCSI and imSIC, taking into account active-IRS noise. Additionally, it conducts an asymptotic analysis in a high signal-to-noise ratio (SNR) regime. The analytical results closely align with Monte Carlo simulation results, validating the accuracy of the findings.

This paper proposes a downlink non-orthogonal multiple access (NOMA) low earth orbit (LEO) satellite system by modeling the locations of terrestrial users and LEO satellites as two homogeneous spherical Poisson point processes, respectively. Firstly, considering that the satellite-terrestrial channel follows the Nakagami-m fading, the closed-form expressions of the user association and the visible probability are studied under the scenario where the number of user visible to the random selected satellite is greater than one. Subsequently, the above results are adopted to analyze the approximate results for the moments of the conditional success probability and the signal-to-interference-plus-noise ratio Meta distribution. The numerical results demonstrate that the asymmetric target rates can realize a performance gain of NOMA over orthogonal multiple access in terms of the link reliability and the coverage probability, while symmetric settings still have a merit for NOMA when there is a low requirement for the link reliability.

Integrated sensing and communication (ISAC) has been proved as a promising technique to further improve the performance for both the communication and the sensing tasks in wireless networks. However, due to the complicated and dynamic interference circumstances, the performance of ISAC cannot be guaranteed. To provide some insights for keeping a sophisticated balance between communication and sensing with considering co-channel interference, the theoretical performance of ISAC is studied in this paper. First, an analytical system model is provided based on stochastic geometry. Second, the success serving probability (SSP) is defined for both the communication and the sensing tasks based on mutual information, which provided a unified analysis framework for ISAC. The tractable expressions of SSP are also derived. Finally, the simulation results are shown to verify the analytical results of SSP, which can provide some insights for the tradeoff between sensing and communication of ISAC.

In this paper, the design of non-uniform antenna topology for 3D massive MIMO arrays in near-field communications is investigated. Specifically, the near-field spherical wavefront radiation characteristics are considered to accurately model the variations of signal phase across array elements. Subsequently, the closed-form expressions of the per-user signal-to-interference noise ratio (SINR) and achievable sum rate for a multi-user MIMO system with maximum-ratio transmission (MRT) precoding are derived. The focus is on the maximization of the achievable sum rate by optimizing the non-uniform 3D antenna array topology. Since the optimization problem exhibits highly nonlinear and nonconvex characteristics, an enhanced particle swarm optimization (EPSO) algorithm is proposed to effectively solve it. Numerical results demonstrate the superiority of the proposed non-uniform 3D array topology in near-field communications for enhancing the achievable sum rate.

The combination of non-orthogonal multiple access (NOMA) and mobile edge computing (MEC) has received considerable attention for maximizing energy efficiency (EE) in wireless networks. Previous studies focus on EE maximization based on pure OMA or NOMA offloading in MEC networks. In this paper, a hybrid NOMA (H-NOMA) scheme which dynamically transforms between pure OMA and pure NOMA offloading strategies is proposed under the general network status in the multi-user MEC network to maximize EE. An offloading multi-ratio EE problem is formulated. Two iterative algorithms, the successive Dinkelbach method-based algorithm and the quadratic transform-based fractional programming (FP) algorithm, are proposed to efficiently maximize the EE over multiple users' time and power within polynomial time via different FP techniques. Simulation results verify the properties of the proposed dynamic H-NOMA offloading strategy and show the superior performance of the H-NOMA strategy over EE in MEC systems.

Although Federated Learning (FL) has garnered increasing attention from researchers, the development of ad-vanced FL frameworks incorporating multiple access techniques remains relatively underexplored. This paper investigates the integration of a novel clustered federated learning (CFL) framework with non-orthogonal multiple access (NOMA) in environments with non-independent and identically distributed (non-iid) datasets. To explore the potential benefits of the proposed framework, the optimization problem is formulated as an energy minimization problem, which includes sub-channel and power allocation. The formulated problem is divided into two sub-problems, respectively solved by the matching-based algorithm and Karush-Kuhn-Tucker (KKT) conditions, in which the closed-form solution is derived. Our simulation results demon-strate that jointly optimizing sub-channel and power allocation in NOMA-enhanced networks can lead to a significant improvement in test accuracy and convergence speed in the proposed FL framework.

This paper aims to study the role of cognitive radio inspired non-orthogonal multiple access (CR-NOMA) in improving information freshness of status updating systems with random arrivals. Particularly, a time slotted multiuser scenario is considered, where each user transmits its status update to a receiver. Each user is allocated with a time slot. In CR-NOMA, each user can transmit signal as a primary user by using its own time slot, besides, it can also transmit signal as a secondary user by sharing the time slot of another user. Hence, more transmission opportunities are provided by CR-NOMA compared to conventional time division multiple access (TDMA) based schemes. In this paper, age of information (AoI) is utilized as the performance metric. For comparison purpose, exact expressions for the average AoIs achieved by CR-NOMA and benchmark TDMA are obtained. Numerical results are provided to validate the accuracy of the analytical results and also demonstrate the superior performance of CR-NOMA on reducing AoI. It is shown that the AoI can be significantly reduced by CR-NOMA compared to TDMA.

In this work, a simultaneous wireless information and power transmission (SWIPT) assisted full-duplex (FD) non-orthogonal multiple access (NOMA) mobile edge computing (MEC) transmission scheme is proposed for next-generation wireless networks. SWIPT, FD, NOMA, and MEC are used to help computational and energy-constrained IoT devices in next-generation wireless networks efficiently cope with their computational requirements. The computation energy efficiency (CEE) maximization of the SWIPT-assisted IoT devices performing par-tial offloading with the existence of a downlink user is considered in the proposed scheme. Accordingly, an optimization problem, optimizing power, time and frequency coefficients to maximize the CEE, is formulated, and an effective algorithm is proposed to optimize the coefficients jointly. The provided numerical studies demonstrate the significantly better performance of the proposed scheme over the benchmark schemes.

The need for physically charging mobile devices is anticipated to become a thing of the past in the not-too-distant future. In this paper, a novel approach for wireless-powered mobile devices is presented, which is based on non-orthogonal multiple access (NOMA) and multi-user multiple-input multiple-output (MU-MIMO) antenna systems. The proposed method is specifically designed for use in a cognitive underlay radio (CR) scenario, where the primary network requires a certain quality of service (QoS). Meanwhile, secondary network users can download their data using the same spectrum. The main objective of this paper is to maximize the sum rate of the secondary network. We have optimized a joint beamforming vector for both primary and secondary networks and a time-switching coefficient for energy harvesting and information transfer to achieve this objective. The initial problem formulation was non-convex, requiring the implementation of various techniques to ensure an efficient and low-complexity algorithm. To this end, we employed semi-definite programming, successive convex approximation, and alternating optimization. The proposed NOMA-based solution outperforms the TDMA-based benchmark scheme regarding sum data rate, specifically in the low transmit power region.

This paper investigates a backscatter communication (BackCom) based non‐orthogonal multiple access (NOMA) system in a multiple‐input and single‐output (MISO) scenario, where two decoding methods are deployed, including the sum‐capacity approach and QR decomposition. The goal is to maximize energy efficiency (EE) through the optimization of the beamforming matrix and the reflection coefficient of the BackCom devices. Two algorithms, Dinkelbach based on penalty semidefinite relaxation (SDR) and successive convex approximation (SCA), are proposed as high‐performance and low‐complexity solutions, respectively. Simulation results indicate that the combination of the sum‐capacity approach and Dinkelbach yields the best performance, though at the highest complexity, while the amalgamation of QR decomposition and SCA offers the lowest performance but with minimal complexity.

The rapid development of next-generation Internet of Things (IoT) applications, including integrated-sensing-and-communication (ISAC), smart grids, smart cities, intelligent transport networks, etc., enables at least tens of billions of bandwidth-thirsty IoT devices, which consume a deluge of data in the sixth-generation (6G) communication systems. In addition, future challenging heterogeneous services and applications, such as Industry 4.0, require the provisioning of unprecedented massive device access, heterogeneous data traffic, high spectral efficiency, and low latency. As a result, there is an urgent demand to pay more attention to IoT networks for high-reliable and low-delay massive access.

The combination of simultaneously transmitting and reflecting-reconfigurable intelligent surface (STAR-RIS) and nonorthogonal multiple access (NOMA) brings the necessary full-space degrees of freedom and spatial multiplexing gains for the Internet of Things (IoT) networks. The inherent network heterogeneity and sharing of wireless channels may however increase the exposure of the information interactions to the third party. To address this issue, we propose a covert communication scheme in STAR-RIS assisted NOMA networks over Nakagami-m fading channels, where both downlink and uplink IoT scenarios are considered. Under the NOMA protocol with imperfect successive interference cancelation (SIC), an IoT access point interacts with two IoT users aided by a STAR-RIS without being detected by two wardens. In this scenario, the two IoT users are located on both sides of the STAR-RIS which adopts coherent phase shifting and operates according to the mode switching protocol. To evaluate the wardens’ detection performance, the Kullback-Leibler (KL) divergence is used. Furthermore, the cascaded channel gains of IoT users and wardens are, respectively, characterized as Gamma and complex Gaussian random variables. The closed-form expressions of the expectations of KL divergence and the interruption probabilities for downlink and uplink are derived. To further improve the performance, we formulate the effective covert rate maximization as the joint optimization problems of the transmit power and power allocation coefficient for downlink and uplink, subject to the constraints for covertness, reliability and power budget, which are, respectively, resolved analytically. Extensive simulation results indicate that the proposed scheme improves covertness compared with the benchmarks.

In this article, we consider a simultaneous lightwave information and power transfer-enabled indoor visible light/radio frequency (RF) hybrid communication system. In this system, several luminaries are mounted on the ceiling of a room and sensors receive lightwave power and information from luminaries. Each sensor harvests energy from lightwave signals and uses them for uplink communication using RF signals. In general, blockages due to the movement of humans are common in indoor systems which results in severe performance degradation. We consider blockages due to such human movements in our system. An optimization problem is formulated to maximize the uplink weighted sum rate considering uplink orthogonal multiple access (OMA) and non-OMA cases. To find the optimal beamforming matrix and time allocation parameters, a lightweight artificial neural network architecture is proposed. Our solution is capable of predicting the human blockages and accordingly optimizing the beamforming matrices and time allocation parameters leading to a near-optimal uplink sum rate. Specifically, up to 30% rate improvement is observed compared to zero-forcing beamforming when the number of blockages is more than five. Further, the use of NOMA for uplink results in up to 25% sum rate improvement.

Recently, the multiple-input–multiple-output (MIMO) nonorthogonal multiple-access (NOMA) transmission, denoted as MIMO- NOMA, has been widely applied for Internet of Things (IoT) systems due to its spectral efficiency. As a promising precoding method, the generalized singular value decomposition (GSVD)-based precoding scheme has been studied in MIMO- NOMA. In this study, we apply the GSVD-based precoding scheme to a downlink MIMO- NOMA communication system with an amplify-and-forward (AF) relay and two IoT users. A closed-form expression of the probability density function (PDF) of two channel matrices’ generalized singular values (GSVs) is obtained in order to facilitate the performance analysis for cooperative MIMO- NOMA transmission. In particular, by this distribution characteristic result, the users’ rates and outage probabilities achieved by MIMO- NOMA are studied for the insightful performance evaluation. In addition, the asymptotic approximations for outage probabilities at the high signal-to-noise-ratio (SNR) condition are presented. In addition to characterize the performance achieved by cooperative MIMO- NOMA, resource allocation for the addressed NOMA system is also investigated in this article, where a suboptimal power allocation algorithm to maximize the sum rate is given. The solution obtained by the proposed algorithm is studied, where the optimality condition of the solution is obtained. Finally, simulation results are presented to show the superiority of the scheme and verify these analytical results.

This article investigates the combination of active reconfigurable intelligent surfaces (aRISs) with cognitive radio networks (CRns) enabled by nonorthogonal multiple access (NOMA) to enhance the capability of aRIS-based Internet of Things (IoT) systems. The proposed system model enhances overall performance and energy allocation by combining aRIS and NOMA. In this proposed system paradigm, the secondary source (SS) controls the information transmission to two secondary users (SUs) via the aRIS element. Transmission power limitations are put in place to lessen the impression that base stations are interfering with the main purpose. This article evaluates critical system performance indicators, such as outage probability (OP), achievable ergodic rate (AER), throughput, and energy efficiency (EE). Specifically, the impact of the distance between the aRIS unit and the base station on AER is explored. The examination of the correlation among SS-aRIS-Users in the presence of the Nakagami-m fading scenario is further investigated. Such discoveries offer significant perspectives for the enhancement and configuration of aRIS-NOMA frameworks in CRn, contributing to the advancement of adaptable communication infrastructures. In contrast to the traditional method that uses orthogonal multiple access (OMA), the aRIS-NOMA system proposed in CRn appears to be a promising way to improve the performance of IoT networks based on aRIS. Simulations have demonstrated significant improvements in spectral efficiency, with gains as high as 10%–20% observed. This suggests that performance has significantly improved, particularly for OP and AER. Finally, the Monte Carlo simulation confirms and strengthens these findings.

To provide sustainable energy support while meeting the demands for serving a rapidly increasing number of devices, in this paper, we propose a new Reconfigurable intelligent surface (RIS) Assisted simultaneous wireless information and Power transfer (SWIPT) and over-the-aIr computation (AirComp) feDerated learning system which is termed RAPID. Specifically, at each training iteration, an access point (AP) first simultaneously broadcasts global model and transfers wireless energy to the selected devices via the RIS-assisted SWIPT. These devices then use the harvested power to compute and upload their local gradients to the AP for aggregation via the RIS-assisted AirComp. To identify the performance improvement to federated learning, we first analyze and derive the expected convergence rate for the proposed RAPID system taking into account factors of device selection and wireless communication. We then formulate a joint learning-communication optimization problem in terms of device selection, transmit beamforming, power splitting, receive beamforming, and RIS coefficients design. To solve the formulated non-convex problem, we propose a new two-stage algorithm by successively solving the downlink SWIPT and the uplink AirComp sub-problems based on alternating optimization and successive convex approximation techniques. Simulation results are presented to demonstrate that our proposed RAIPD system can significantly improve the convergence and accuracy of federated learning compared with benchmark schemes.

There is an urgent emergency for next-generation multiple access (NGMA) schemes to address the growing demands for our society by providing new services and practical scenarios to enhance our daily lives. The development of NGMA schemes is accelerating in terms of formulating capability objectives for the next-generation era and investigating state-of-art, promising, and tractable technology that may become part of the next-generation wireless communication systems in the future. Thus, it is anticipated that NGMA will address the requirements for the foundations of wireless communications (such as massive connectivity, stability, and wide-range coverage) and other applications (including data and computing assisted by machine learning, protocol designs, and other applications to encourage innovation and serve as the information backbone of society)..

The evolution of wireless communications has been significantly influenced by remarkable advancements in multiple access (MA) technologies over the past five decades, shaping the landscape of modern connectivity. Within this context, a comprehensive tutorial review is presented, focusing on representative MA techniques developed over the past 50 years. The following areas are explored: 1) the foundational principles and information-theoretic capacity limits of power-domain nonorthogonal multiple access (NOMA) are characterized, along with its extension to multiple-input multiple-output (MIMO)-NOMA; 2) several MA transmission schemes exploiting the spatial domain are investigated, encompassing both conventional space-division multiple access (SDMA)/MIMO-NOMA systems and near-field MA systems utilizing spherical-wave propagation models; 3) application of NOMA to integrated sensing and communications (ISAC) systems is studied. This includes an introduction to typical NOMA-based downlink (DL)/uplink (UL) ISAC frameworks, followed by an evaluation of their performance limits using a mutual information (MI)-based analytical framework; and 4) major issues and research opportunities associated with the integration of MA with other emerging technologies are identified to facilitate MA in the next-generation networks, i.e., next-generation multiple access (NGMA). Throughout this article, promising directions are highlighted to inspire future research endeavors in the realm of MA and NGMA.

The aim of this paper is to reveal the importance of hybrid successive interference cancellation (SIC) and power adaptation (PA) for improving transmission robustness of uplink non-orthogonal multiple access (NOMA). Particularly, a cognitive radio inspired uplink NOMA communication scenario is considered, where one primary user is allocated one dedicated resource block, while$M$secondary users compete with each other to be opportunistically served by using the same resource block of the primary user. Two novel schemes are proposed for the considered scenario, namely hybrid SIC with PA (HSIC-PA) scheme and fixed SIC with PA (FSIC-PA) scheme. Both schemes can ensure that the secondary users are served without degrading the transmission reliability of the primary user compared to conventional orthogonal multiple access (OMA) based schemes. The novelty of the proposed schemes compared to those existing schemes is the introduction of power adaptation. This paper presents rigorous analytical results to show that both schemes can avoid outage probability error floors without any constraints on users’ target rates in the high SNR regime, which cannot be achieved by the existing schemes. Furthermore, it is shown that the diversity gain achieved by the HSIC-PA scheme is$M$, while that of the FISC-PA scheme is only 1. Numerical results are provided to verify the developed analytical results and also demonstrate the superior performance achieved by the proposed schemes by comparing with the existing HSIC without PA (HSIC-NPA) scheme. The presented simulation results also show that HSIC-PA scheme performs the best among the three schemes, which indicates the importance of the combination of HSIC and PA for improving transmission robustness.

Existing integrated sensing and communication (ISAC) systems face two critical challenges: a trade-off between resource allocation and interference management, and a lack of a unified performance metric that can be simultaneously applied to both sensing and communication functions. To address two aforementioned issues, a non-orthogonal multiple access-assisted ISAC (NOMA-ISAC) scheme is first proposed in this paper, which can simultaneously perform the sensing and communication tasks on shared radio resource, significantly improving spectral efficiency while mitigating mutual interference. Furthermore, in order to provide a unified metric to simplify the performance analysis in ISAC systems, we extend the definition of the outage probability from a mean square error (MSE) perspective. Then based on the built framework, the tractable expressions of the outage probability are derived for both communication and sensing tasks to evaluate the performance of our proposed NOMA-ISAC scheme and the conventional orthogonal radio resource-based ISAC (OR-ISAC) scheme. Next, the asymptotic outage probability comparisons are carried out to show that the NOMA-ISAC scheme can achieve better performance than the OR-ISAC scheme. Finally, simulation results are provided to verify the analytical derivations, and also demonstrate the robustness and performance gains of our proposed NOMA-ISAC scheme over OR-ISAC scheme.

The intelligent transportation system (ITS) was supported by the sixth generation (6G) wireless networks, since it has great potential to realize intelligent transportation with the benefit for the society and economy. In order to overcome the practical problem of spectrum scarcity, ultra-low latency, large-scale connectivity in ITS, we propose a cooperative multiple-input single output non-orthogonal multiple access (MISO-NOMA) for ITS with intelligent reflecting surface (IRS) and simultaneous wireless information and power transfer (SWIPT). An user fairness optimization problem is formulated to maximize the fairness rate of the vehicles, subject to the quality of service requirements of the vehicles and the successive interference cancellation. The optimization problem involves the transmit beamformers design, the IRS reflection matrix design, and the power splitting ratio of the SWIPT, which lead to the problem is difficult to solve. For solving the challenging problem, an iterative successive convex approximation and semi-definite relaxation based algorithm is proposed. Explicitly, we firstly adopt the method of reconstructing epigraph for simplification due to the objective function is non-convex, and then the original problem is decomposed into two sub-problems that are easy to solve. Finally, Experimental results illustrate that the user fairness of the proposed cooperative MISO-NOMA for ITS with IRS and SWIPT is better than that of both the IRS-NOMA for ITS without SWIPT and the IRS-OMA for ITS.

This study investigates a two-way relaying non-orthogonal multiple access (TWR-NOMA) enabled Internet-of-Things (IoT) network, in which two NOMA users communicate via an IoT access point (IAP) relay using a decode-and-forward (DF) protocol. A power beacon (PB) is used to power the IAP to address the IAP's limited lifetime due to energy constraints. Since co-channel interference (CCI) is inevitable in IoT systems, this effect is also studied in the proposed system to improve practicality. Based on the proposed system model, the closed-form equations for the exact and asymptotic outage probability (OP) and ergodic data (ED) of the NOMA users' signals are first derived to describe the performance of TWR-NOMA systems. The system's diversity order and throughput are then evaluated according to the derived results. To further improve the system's performance, a low-complexity strategy 2D golden section search (GSS) is performed, subject to power allocation (PA) and time-switching (TS) factors, to optimize the outage performance. Finally, a deep learning design with minimal computing complexity and precision OP prediction is established for a real-time IoT network configuration. The numerical results are discussed and analyzed in terms of the effects of the CCI, the TS ratio, the PA factor, the fading parameter on the OP, system throughput, and ED.

While targeting the energy-efficient connectivity of the Internet-of-things (IoT) devices in the sixth-generation (6G) networks, in this paper, we explore the integration of non-orthogonal multiple access-based backscatter communication (BAC-NOMA) and simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs). To this end, first, for the performance evaluation of the STAR-RIS-assisted BAC-NOMA system, we derive the statistical distribution of the channels under Nakagami-m fading. Second, by leveraging the derived statistical channel distributions, we present the effective capacity analysis under the delay quality-of-service (QoS) constraint. In particular, we derive the closed-form expressions for the effective capacity of the reflecting and transmitting backscatter nodes (BSNs) under the energy-splitting protocol of STAR-RIS. To obtain more insight into the performance of the considered system, we provide the asymptotic analysis, and derive the upper bound on the effective capacity, which represents the ergodic capacity. Our simulation results validate the analytical analysis, and reveal the effectiveness of the STAR-RIS-assisted BAC-NOMA system over the conventional RIS (C-RIS)- and orthogonal multiple access (OMA)-based counterparts. Finally, to highlight the trade-off between the effective capacity and energy consumption, we analyze the link-layer energy efficiency. Overall, this paper provides useful guidelines for the performance analysis and design of the STAR-RIS-assisted BAC-NOMA systems.

Full duplex (FD) radios have attracted extensive attention due to the co-time and co-frequency transceiving capability. However, the potential gain brought by FD radios is closely related to the management of self-interference (SI), which imposes high or even stringent requirements on SI cancellation (SIC) techniques. When the FD deployment evolves into next-generation mobile networking, the SI problem becomes more complicated, significantly limiting its potential gains. In this paper, we conceive a multi-cell FD networking scheme by deploying a reconfigurable intelligent surface (RIS) at the cell boundary to configure the radio environment proactively. To achieve the full potential of the system, we aim to maximize the sum rate (SR) of multiple cells by jointly optimizing the transmit precoding (TPC) matrices at FD base stations (BSs) and users, as well as the phase shift matrix at the RIS. Since the original problem is non-convex, we reformulate and decouple it into a pair of subproblems by utilizing the relationship between the SR and minimum mean square error (MMSE). The optimal solutions of TPC matrices are obtained in closed form, while both complex circle manifold (CCM) and successive convex approximation (SCA) based algorithms are developed to resolve the phase shift matrix suboptimally. Our simulation results show that introducing an RIS into an FD networking system not only improves the overall SR significantly but also enhances the cell edge performance prominently. More importantly, we validate that the RIS deployment with optimized phase shifts can reduce the requirement for SIC and the number of BS antennas, which further reduces the hardware cost and power consumption, especially with a sufficient number of reflecting elements. As a result, the utilization of an RIS enables the originally cumbersome FD networking system to become efficient and practical.

The aim of this paper is to characterize the impact of non-orthogonal multiple access (NOMA) on the age of information (AoI) of grant-free transmission. In particular, a low-complexity form of NOMA, termed NOMA-assisted random access, is applied to grant-free transmission in order to illustrate the two benefits of NOMA for AoI reduction, namely increasing channel access and reducing user collisions. Closed-form analytical expressions for the time average AoI achieved by NOMA assisted grant-free transmission are obtained, and asymptotic studies are carried out to demonstrate that the use of the simplest form of NOMA is already sufficient to reduce the AoI of orthogonal multiple access (OMA) by more than 40%. In addition, the developed analytical expressions are also shown to be useful for optimizing the users’ transmission attempt probabilities, which are key parameters for grant-free transmission.

The aim of this paper is to develop hybrid non-orthogonal multiple access (NOMA) assisted downlink transmission. First, for the single-input single-output (SISO) scenario, i.e., each node is equipped with a single antenna, a novel hybrid NOMA scheme is introduced, where NOMA is implemented as an add-on of a legacy time division multiple access (TDMA) network. Because of the simplicity of the SISO scenario, analytical results can be developed to reveal important properties of downlink hybrid NOMA. For example, in the case that the users’ channel gains are ordered and the durations of their time slots are the same, downlink hybrid NOMA is shown to always outperform TDMA, which is different from the existing conclusion for uplink hybrid NOMA. Second, the proposed downlink SISO hybrid NOMA scheme is extended to the multiple-input single-output (MISO) scenario, i.e., the base station has multiple antennas. For the MISO scenario, near-field communication is considered to illustrate how NOMA can be used as an add-on in legacy networks based on space division multiple access and TDMA. Simulation results verify the developed analytical results and demonstrate the superior performance of downlink hybrid NOMA compared to conventional orthogonal multiple access.

To fully exploit the potential of reconfigurable intelligent surface (RIS), the controllable channel state information (CSI) should be accurate for its future applications. Unfortunately, in vehicular communications, obtaining exact instantaneous CSI presents substantial challenges. Moreover, even with an instantaneous CSI acquisition, a processing latency for RIS phase shift adaption might occur before the vehicular system reacts to the instantaneous CSI information. To effectively introduce RIS into Internet of vehicle (IoV) networks, we employ a more realistic statistical CSI approach in designing RIS-assisted vehicular communication systems that are robust to the general characteristics of the channel, rather than its instantaneous fluctuations. We present a practical system framework, where a roadside unit employs an RIS to facilitate indirect wireless communications for vehicle-to-vehicle (V2V) communications. Particularly, the direct links between vehicles are susceptible to blockages caused by surrounding obstacles/vehicles. The deployment of RIS is to establish supplementary communication links between a multi-antenna vehicle source (VS) and multiple vehicular users (VUs) as they traverse areas with a poor service coverage. With the objective to maximize the time-averaged sum-rate of VUs, instead of instantaneous CSI, we rely on the delayed statistical CSI feedback to design active beamforming at the VS and passive beamforming at RIS. Moreover, we develop an efficient algorithm, named JAPBNB, which leverages the fractional programming technique to find a stationary solution for the formulated sum-of-logarithms-of-ratio problem. Specifically, a non-convex block coordinate descent (BCD) approach, collaborating with the alternating direction method of multipliers (ADMM), is applied for the joint optimization of active and passive beamforming. Finally, the complexity and convergence of the proposed JAPBNB algorithm are thoroughly discussed and validated. Simulation results demonstrate that the time-averaged sum-rate obtained by the proposed JAPBNB algorithm approaches that obtained by the instantaneous CSI scheme, when the delayed statistical CSI feedback interval is adequately small.

The advantages of graph neural networks (GNNs) in leveraging the graph topology of wireless networks have drawn increasing attentions. This paper studies the GNN-based learning approach for the sum-rate maximization in multiple-user multiple-input single-output (MU-MISO) networks subject to the users’ individual data rate requirements and the power budget of the base station (BS). By modeling the MU-MISO network as a graph, a GNN-based architecture named complex residual graph attention network (CRGAT) is proposed to directly map channel state information to beamforming vectors. The attention-enabled aggregation and the residual-assisted combination are adopted to enhance the learning capability and mitigate the oversmoothing issue. Furthermore, a novel activation function is proposed for the constraint due to the limited power budget at the BS. The CRGAT is trained via unsupervised learning with two proposed loss functions. An evaluation method is proposed for the learning-based approaches, based on which the effectiveness of the proposed CRGAT is validated in comparison with several convex optimization and learning based approaches. Numerical results are provided to reveal the advantages of the CRGAT including the millisecond-level response with limited optimality performance loss, the scalability to different number of users and power budgets, and the adaptability to different system settings.

As a revolutionary technology, reconfigurable intelligent surface (RIS) has been deemed as an indispensable part of the 6th generation communications due to its inherent ability to regulate the wireless channels. However, passive RIS (PRIS) still suffers from some pressing issues, one of which is that the fading of the entire reflection link is proportional to the product of the distances from the base station to the PRIS and from the PRIS to the users, i.e., the productive attenuation. To tackle this problem, active RIS (ARIS) has been proposed to reconfigure the wireless propagation condition and alleviate the productive attenuation. In this paper, we investigate the physical layer security of the ARIS assisted non-orthogonal multiple access (NOMA) networks with the attendance of external and internal eavesdroppers. To be specific, the closed-form expressions of secrecy outage probability (SOP) and secrecy system throughput are derived by invoking both imperfect successive interference cancellation (ipSIC) and perfect SIC. The secrecy diversity orders of legitimate users are obtained at high signal-to-noise ratios. Numerical results are presented to verify the accuracy of the theoretical expressions and indicate that: i) The SOP of ARIS assisted NOMA networks exceeds that of PRIS-NOMA, ARIS/PRIS-assisted orthogonal multiple access (OMA); ii) Due to the balance between the thermal noise and residual interference, introducing excess reconfigurable elements at ARIS is not helpful to reduce the SOP; and iii) The secrecy throughput performance of ARIS-NOMA networks outperforms that of PRIS-NOMA and ARIS/PRIS-OMA networks.

This study explores the benefits of integrating the novel clustered federated learning (CFL) approach with non-orthogonal multiple access (NOMA) under non-independent and identically distributed (non-IID) datasets, where multiple devices participate in the aggregation with time limitations and a finite number of sub-channels. A detailed theoretical analysis of the generalization gap that measures the degree of non-IID in the data distribution is presented. Following that, solutions to address the challenges posed by non-IID conditions are proposed with the analysis of the properties. Specifically, users’ data distributions are parameterized as concentration parameters and grouped using spectral clustering, with Dirichlet distribution serving as the prior. The investigation into the generalization gap and convergence rate guides the design of sub-channel assignments through the matching-based algorithm, and the power allocation is achieved by Karush-Kuhn-Tucker (KKT) conditions with the derived closed-form solution. The extensive simulation results show that the proposed cluster-based FL framework can outperform FL baselines in terms of both test accuracy and convergence rate. Moreover, jointly optimizing sub-channel and power allocation in NOMA-enhanced networks can lead to a significant improvement.

In this paper, we investigate a cognitive multicast communication system aided by active reconfigurable intelligent surface (active RIS). Specifically, for an underlay spectrum sharing cognitive multicast network, a cognitive radio base station (CRBS) communicates with secondary users (SUs) assisted by an active RIS. Meanwhile, the interference to primary users (PUs) is suppressed within the constraints of the transmit power of both the CRBS and active RIS, together with the restriction of the active RIS amplitude gain. We aim at the fairness problem for maximizing the minimum signal-to-interference-plus-noise-ratio (SINR) via joint beamforming design at the CRBS and the active RIS. To cope with this problem, the optimization and deep reinforcement learning (DRL) based algorithms are proposed. Specifically, the decision variables are decoupled by the alternating optimization (AO) method and then, the non-convex problem is transformed into a solvable convex form by using the successive convex approximation (SCA), Schur complement, and penalty convex-concave procedure (PCCP) methods. Furthermore, we design an AO-based algorithm for the formulated problem. Due to the characteristics of both exploration and exploitation, the DRL-based algorithms outperform the AO-based algorithm with proper parameter settings. Meanwhile, the DRL algorithm inherits the advantages of low execution complexity. The original optimization problem is first converted into a Markov decision process (MDP) form in DRL. Due to the complex objective function and various restrictions of power/amplification gain budget and quality of service (QoS), the constraints are categorized as the switching constraints for action adjustment and performance constraints for reward function setting, respectively. Subsequently, a segmented incentive-based reward function is developed to attain higher performance on SINR. We also propose two effective deep deterministic policy gradient (DDPG)-based and twin delayed deep deterministic policy gradient (TD3)-based algorithms. Finally, the simulation results demonstrate a notable enhancement in system performance upon the introduction of active RIS compared to the case with a passive RIS and the case without using an RIS. Moreover, with appropriately configured parameters, DRL algorithms outperform the AO-based algorithm, and notably, the TD3 algorithm is superior to the DDPG algorithm in optimization effectiveness.

This paper investigates a new self-sustainable intelligent omni-surface (S-IOS) aided multi-user wireless network, where the S-IOS harvests the radio frequency energy from the signals transmitted by the access point (AP) and exploits the harvested energy to provide full-dimensional beamforming services for the users. Three efficient operating protocols for the S-IOS, namely time switching, power splitting, and mode switching, are proposed to enable the dual-functionality of energy harvesting and information transmission. For each protocol, we design a joint optimization framework of transmit beamforming at the AP, refraction/reflection beamforming at the S-IOS, and energy harvesting schedule at the S-IOS, to maximize the network sum rate. Despite the challenging non-convex optimization problems with highly coupled and/or integer optimization variables, we develop computationally-efficient algorithms to solve them in an iterative manner, which exploit the intrinsic structure of the problems and employ the penalty-based method and the successive convex approximation. Numerical results confirm the efficiency of our developed optimization algorithms, demonstrate the significant importance of the S-IOS for spectral and energy efficient wireless communications, and quantify the performance advantage of the proposed designs over the baseline schemes.

This paper investigates the system model and the transmit beamforming design for the Cell-Free massive multi-input multi-output (MIMO) integrated sensing and communication (ISAC) system. The impact of the uncertainty of the target locations on the propagation of wireless signals is considered during both uplink and downlink phases, and especially, the main statistics of the MIMO channel estimation error are theoretically derived in the closed-form fashion. A fundamental performance metric, termed communication-sensing (C-S) region, is defined for the considered system via three cases, i.e., the sensing-only case, the communication-only case and the ISAC case. The transmit beamforming design problems for the three cases are respectively carried out through different reformulations, e.g., the Lagrangian dual transform and the quadratic fractional transform, and some combinations of the block coordinate descent method and the successive convex approximation method. Numerical results present a 3-dimensional C-S region with a dynamic number of access points to illustrate the trade-off between communication and radar sensing. The advantage for radar sensing of the Cell-Free massive MIMO system is also studied via a comparison with the traditional cellular system. Finally, the efficacy of the proposed beamforming schemes is validated in comparison with zero-forcing and maximum ratio transmission schemes.

In this study, we investigate the performance of a hybrid reconfigurable intelligent surface (RIS)-assisted non-orthogonal multiple access (NOMA) network, augmented with backscattering capabilities, designed to facilitate integrated sensing and communication (ISAC). Our primary objective is two-fold: first, to enhance the overall communication throughput, and second, to strengthen the sensing power for target detection. To achieve these goals, we introduce two novel dynamic user clustering algorithms namely composite distance and angle-based (CDA) and channel-oriented adaptive (COA) algorithm for grouping users into clusters with fixed base station and RIS positions, where the successive interference cancellation (SIC) is employed for effective communication within each pair. Moreover, we present a comprehensive optimization problem that jointly maximizes the sum rate and sensing power. This problem involves optimizing the transmit beamformer at the base station, the power allocation factors within each cluster, and the phase shifts at the RIS. This methodology not only adheres to strict power constraints and quality of service requirements at each receiving node but also ensures equitable resource allocation among the targets and enforces unit modulus phase shifts at each RIS element. To tackle the complex interdependencies and non-convex nature of the optimization problem, we introduce an advanced iterative algorithm based on alternative optimization (AO). This state-of-the-art technique employs successive convex approximation (SCA) to systematically address this multifaceted problem. Finally, the simulation results empirically validate the proposed algorithm’s effectiveness, considering the number of RIS elements, maximum power budget, number of targets, and imperfect channel state information (CSI) while showing the trade-off between communication and sensing performance.

In recent years, the multiple-input multiple-output (MIMO) non-orthogonal multiple-access (NOMA) systems have attracted a significant interest in the relevant research communities. As a potential precoding scheme, the generalized singular value decomposition (GSVD) can be adopted in MIMO-NOMA systems and has been proved to have a good trade-off for complexity and performance. In this paper, the performance of the GSVD-based MIMO-NOMA communications with Rician fading is studied. In particular, the distribution characteristics of generalized singular values (GSVs) of channel matrices are analyzed. Two novel mathematical tools, the linearization trick and the deterministic equivalent method, which are based on operator-valued free probability theory, are exploited to derive the Cauchy transform of GSVs. An iterative process is proposed to obtain the numerical values of the Cauchy transform of GSVs, which can be exploited to derive the average data rates of the communication system. In addition, the special case when the channel is modeled as Rayleigh fading, i.e., the line-of-sight propagation is trivial, is analyzed. In this case, the closed-form expressions of average rates are derived from the proposed iterative process. Simulation results are provided to validate the derived analytical results.

Communication networks are becoming increasingly content-centric, and reusable content like viral information and video on demand are often requested by multiple users. Caching at the user equipment enables device-to-device (D2D) communications to be used to deliver requested contents which will help reduce data traffic at base stations and also enhance the achievable data rates. In this paper, we propose a system whereby users are able to exchange valuable cached content with each other via a D2D link which underlays the reception of a downlink non-orthogonal multiple access (NOMA) signal. We formulated a sum rate maximization problem that is subject to minimum rate constraints and derived optimal solutions depending on which user is the D2D transmitter. Additionally, sub-optimal solutions based on a negligible self-interference assumption are also proposed. Simulation results demonstrate the significant performance gains of underlaid D2D communications as compared with optimal downlink cellular NOMA. Furthermore, results on the self-interference (SI) cancellation factor highlight that the sub-optimal power allocation solution offers sum rate performance close to the optimal case. The performance gains are further enhanced when SI cancellation is high.

Mobile edge computing (MEC) enables communication users with limited computation power to offload computation-intensive tasks to the edge server, thus dramatically enhancing the limited computing capabilities of the users. As the reality of scarce spectrum resources and the energy-constrained nature of communication users, this paper introduces non-orthogonal multiple access (NOMA) and simultaneous wireless information and power transfer (SWIPT) techniques to achieve more efficient task offloading in MEC. To minimize the number of computationally failed tasks while simultaneously satisfying different quality of service (QoS) requirements of users, a joint resource management problem of the spectrum, computation, and energy resources is formulated. Due to the non-convexity of the offloading optimization problem and the stochastic nature of the constructed MEC environment, a multiple agents deep deterministic policy gradient (MADDPG)-based resource management algorithm is proposed to manage each user’s multidimensional resources without collaborating. The simulation results show that compared to other benchmark schemes, the proposed algorithm can effectively improve both the communication and computational performances in MEC.

The application of network non-orthogonal multiple access (N-NOMA) technique to coordinated multi-point (CoMP) systems has attracted significant attention due to its superior capability to improve connectivity and maintain reliable transmission for CoMP users simultaneously. Based on the concept of quasi-degraded channel for N-NOMA, this paper studies the precoding design for downlink N-NOMA scenarios with two base stations (BSs) equipped with multiple antennas. In specific, under quasi-degraded channels, simple linear precoding based N-NOMA can achieve the same minimal total transmission power as theoretically optimal but complicated dirty paper coding (DPC) scheme, when the users’ target rates and minimal transmission power of each BS are given. In this paper, the channel quasi-degradation (QD) condition is first rigorously derived for the scenario with single CoMP user and two NOMA users. The closed-form optimal precoders for N-NOMA under quasi-degraded channels are also provided. Then, based on QD condition, a novel hybrid N-NOMA (H-N-NOMA) scheme is proposed, which is a mixture of N-NOMA and conventional zero-forcing beamforming (ZFBF) scheme. Further, for the scenarios with more users, a low-complexity QD based user pairing (QDUP) algorithm is proposed, which is then combined with H-N-NOMA to make a novel scheme termed H-N-NOMA/QDUP into being. Numerical results are presented to reveal the impact factors on QD channels, and also demonstrate the superior performance of the proposed H-N-NOMA/QDUP scheme. It is shown that the proposed H-N-NOMA/QDUP scheme can effectively exploit the benefit of multi user diversity.

Spatial non-stationarity channel estimation for uplink massive MIMO systems can be formulated as a non-uniform block sparse signal recovery problem, in which the hierarchical sparsity of the channel matrix is classified as row sparsity and in-row sparsity. This paper proposes an efficient threshold-enhanced hierarchical estimation (TEHE) algorithm without prior information. More precisely, the non-zero rows of spatial non-stationarity channel matrix are estimated according to the in-row correlation in the first layer; while the non-zero elements of the estimated non-zero rows are further refined in the second layer. Different from the existing two-layer iteration algorithms, an adaptive threshold is designed to estimate the non-zero elements replacing the iterative algorithm in the second layer. In the proposed TEHE algorithm, row-wise sparse adaptive matching pursuit (SAMP) is used to find the non-zero rows in the first layer, which has high precision and lower complexity, compared to the conventional SAMP. To further improve the efficiency of the row estimation for larger antenna array, an adaptive threshold-enhanced hierarchical estimation (A-TEHE) algorithm is proposed. In addition, a sufficient condition and a halting condition for theoretical guarantee to obtain accurate row estimation are developed. Finally, the computation complexity is analyzed and compared. The simulation results demonstrate that the proposed threshold-enhanced hierarchical spatial non-stationary channel estimation algorithms achieve better performance compared to various state-of-the-art baselines in terms of support set estimation, channel coefficient estimation, and computational efficiency. Specifically, the proposed algorithms are robust to the in-row sparsity.

In this paper, a federated learning (FL) based system is investigated with non-independent and identically distributed (non-IID) dataset, where multiple devices participate in the global model aggregation through a limited number of sub-channels. By analyzing weight divergence and convergence rate, a new metric is proposed based on age-of-information (AoI), which incorporates latency and can provide an advanced device selection standard. After that, device selection, sub-channel assignment and resource allocation are jointly designed in an overall AoI minimization problem under the maximum energy consumption constraint. The formulated problem is decoupled into two sub-problems. After analyzing the feasibility, the resource allocation problem is transformed to a convex problem, and the closed-from solution is obtained based on KKT conditions. By introducing virtual sub-channels, device selection and sub-channel assignment are jointly solved by a matching based algorithm. Simulation results indicate that the proposed scheme is able to outperform all baselines in terms of both test accuracy and sum AoI, and the developed strategies can achieve significant improvements for all schemes.

Hierarchical federated learning (HFL) shows great advantages over conventional two-layer federated learning (FL) in reducing network overhead and interaction latency while still retaining the data privacy of distributed FL clients. However, the communication and energy overhead still pose a bottleneck for HFL performance, especially as the number of clients raises dramatically. To tackle this issue, we propose a non-orthogonal multiple access (NOMA) enabled HFL system under semi-synchronous cloud model aggregation in this paper, aiming to minimize the total cost of time and energy at each HFL global round. Specifically, we first propose a novel fuzzy logic based client selection policy considering client heterogeneity in multiple aspects, including channel quality, data quantity and model staleness. Subsequently, given the fuzzy based client-edge association, a joint edge server scheduling and resource allocation problem is formulated. Utilizing problem decomposition, we firstly derive the closed-form solution for the edge server scheduling subproblem via the penalty dual decomposition (PDD) method. Next, a deep deterministic policy gradient (DDPG) based algorithm is proposed to tackle the resource allocation subproblem considering time-varying environments. Finally, extensive simulations demonstrate that the proposed scheme outperforms the considered benchmarks regarding HFL performance improvement and total cost reduction.

We investigate joint power allocation and decoding order selection (PA-DOS) aimed at enhancing the outage performance of non-orthogonal multiple access (NOMA) systems. By considering the diverse target rates of users, new important properties of NOMA are revealed: When users’ target rates satisfy certain conditions, the channel state information (CSI) is not required by PA-DOS to minimize the system outage probability, and different users’ outage probabilities can be minimized simultaneously; When such conditions are not satisfied, the opposite situation occurs. Following these properties, two PA-DOS strategies are designed regarding distinct user priorities, which ensure the minimization of the system outage probability and the user outage probability of the high-priority user. Especially, these strategies do not require CSI or only require one-bit CSI feedback depending on users’ target rates. Analytical and numerical results are provided to demonstrate that the proposed strategies significantly outperform the existing strategies in terms of both system and user outage performance. Furthermore, the results show that although under some target rates the minimum user outage probabilities cannot be simultaneously achieved, they can be closely approached at the same time in the high-signal-to-noise-ratio regime by the proposed strategies.

The key idea of this paper is to leverage channel angle information to propose a low-complexity mode switching design in simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) aided multi-antenna non-orthogonal multiple access (NOMA) systems, which is suitable to both downlink and uplink transmissions by applying the concept of angle reciprocity. Particularly, a location-based assignment algorithm is firstly provided to perform NOMA pairing, then the equal gain transmission at the base station and the cophase matching criterion at STAR-RIS are adopted to improve the performance of the reflected user and the effective channel gain of the paired users, respectively. According to the proposed design, considering the difference in the Rician factors of the channel from the base station to STAR-RIS caused by the change of line-of-sight and non-line-of-sight components, two different cases for channel statistics of the paired users are rigorously characterized. Subsequently, we utilize the above results to analyze the closed-form expressions for the outage probability and ergodic rate of all users under downlink and uplink transmissions. Further, the diversity orders and the high slopes corresponding to all expressions are also determined to pursue more insights. Finally, numerical results are presented to demonstrate our analysis and reveal that: 1) the various system factors have significant impact on the performances of the proposed design; and 2) the low-complexity design can reduce the overheads of channel estimation and signal processing at the expense of extremely-low or even no performance loss in contrast to the traditional maximum ratio transmission based design.

Grant-free (GF) low-density signature orthogonal frequency division multiplexing (LDS-OFDM) is one of the most generic grant-free non-orthogonal multiple access (GF-NOMA) schemes. This paper proposes a two-stage active user detection (AUD) consisting of the initial AUD stage and the false alarm correction stage. In the initial AUD stage, an initial active user set is efficiently estimated by the conventional cover decoder, which may still contain a few false alarms. Hence, a false alarm correction stage is further invoked, which consists of two cooperative and iterative detection components, namely, message passing algorithm (MPA) based data decoder and belief propagation (BP) based false alarm corrector. Based on users’ signature spreading sequences in the initial active user set, a tanner graph with potential redundant-edges is constructed, on which MPA is executed for data decoding. In turn, with the aid of decoded data symbols, the remaining false alarms in the initial active user set are further removed by the false alarm corrector. Hence, the tanner graph could evolve iteratively. Furthermore, the false alarm performance of the initial AUD stage is theoretically analyzed. Based on this analysis, the LDS matrix used in GF LDS-OFDM is optimized. Finally, the complexity of our proposal is also provided.

The novel active simultaneously transmitting and reflecting surface (ASTARS) has recently received a lot of attention due to its capability to conquer the multiplicative fading loss and achieve full-space smart radio environments. This paper introduces the ASTARS to assist non-orthogonal multiple access (NOMA) communications, where the paring users are uniformly distributed within the service area. We design the independent reflection/transmission phase-shift controllers of ASTARS to align the phases of cascaded channels at pairing users. We derive new approximate and asymptotic expressions of the outage probability and ergodic data rate for ASTARS-NOMA networks in the presence of perfect/imperfect successive interference cancellation (pSIC/ipSIC). The diversity orders and multiplexing gains for ASTARS-NOMA are derived to provide more insights. Furthermore, the system throughputs of ASTARS-NOMA are investigated in both delay-tolerant and delay-limited transmission modes. The numerical results are presented and show that: 1) ASTARS-NOMA with pSIC outperforms ASTARS assisted-orthogonal multiple access (ASTARS-OMA) in terms of outage probability and ergodic data rate; 2) The outage probability of ASTARS-NOMA with pSIC/ipSIC can be further reduced within a certain range by increasing the power amplification factors; and 3) The system throughputs of ASTARS-NOMA are superior to that of ASTARS-OMA in both delay-limited and delay-tolerant transmission modes.

Federated learning is a promising technique to implement network intelligence for the sixth generation (6G) communication systems. However, the collected data in wireless networks is non-independent and identically distributed (non-IID), which leads to severe deterioration of model performance. Although various enhanced schemes are proposed, it is still challenging to balance the communication cost and the model performance, due to the scarcity of radio resource for model update in wireless networks. In this paper, an ensemble federated learning paradigm is proposed for handling non-IID data, which is also optimized for its deployment in wireless networks in a cost efficient way. First, the framework of ensemble federated learning is designed. By formulating individual user clusters, intra-cluster federated learning models can be generated to reduce the impact of non-IID data, which can be integrated to adapt to various learning data via model ensemble. Second, the optimization of user cluster formation is studied to improve the performance of ensemble federated learning, which is modeled as a coalition formation game to design a Nash-stable algorithm. Finally, the simulation results on the public data sets are provided to verify the performance gains of our proposed schemes for deploying federated learning with non-IID data in wireless networks.

This paper investigates the beamforming design in the Cell-Free massive multi-input multi-output (MIMO) integrated sensing and communication (ISAC) system, termed as the CF-ISAC system, in presence of the channel state information (CSI) estimation error. The beamforming design is formulated into a sensing beampattern matching mean square error minimization problem under the constraints of the power budgets of the access points (APs) and the ergodic rate requirements of the users. A computationally tractable lower bound of the ergodic rate over the imperfect CSI is derived based on the Jensen's Inequality, and then a successive convex approximation based algorithm is proposed to solve the considered problem. Numerical results illustrate the beampatterns for different direction of arrival estimations of the targets. The advantage of the CF-ISAC system for radar sensing is revealed based on the relative location between the AP and the target.

This paper proposes a hierarchical sparse estimation of spatial non-stationarity channel for uplink massive multiple-input multiple-output (MIMO) systems without prior information. Especially, the non-zero rows of non-stationarity channel matrix are estimated according to the in-row correlation in the first layer; while the non-zero elements of the estimated non-zero rows are further refined in the second layer. A row-wise sparse adaptive matching pursuit (SAMP) is used to find the non-zero rows in the first layer of the proposed algorithms, and multiple non-zero rows can be estimated in one iteration, which has higher precision and lower complexity, compared to the conventional SAMP. Different from the existing two-layer iteration algorithms, a threshold is designed to estimate the non-zero elements replacing the iterative algorithm in the second layer. Further, the computation complexity is analyzed and compared. The simulation results demonstrate that the proposed threshold-enhanced hierarchical spatial non-stationary channel estimation algorithms achieve better performance compared to various state-of-the-art baselines in terms of channel coefficient estimation, and computational efficiency.

In this paper, we propose a low-complexity mode switching design in a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) aided multi-antenna non-orthogonal multiple access (NOMA) system via exploiting channel angle information only. Particularly, a location-based assignment algorithm is firstly provided to perform NOMA pairing, then the equal gain transmission at base station and cophase matching criterion at STAR-RIS are adopted to improve the performance of reflected user and the effective channel gain of paired users, respectively. On the basis of to the above design, we study the exact channel statistics in two different cases to further derive the outage probability of reflected and transmitted users. Numerical results are presented to demonstrate our analyses and reveal that: 1) the various system factors have markedly impacts on our proposed design; and 2) the low-complexity design can reduce the overheads of channel estimation and signal processing at the expense of extremely low performance loss.

In today's world of burgeoning IoT and 6G communications, supporting low-powered devices is crucial to fully capitalizing on the Next Generation Internet of Things (NG-IoT) revolution. The proliferation of these devices will unlock unprecedented opportunities for energy efficiency, sustainability, and ubiquitous connectivity. This paper investigates the sum rate optimization of a quality-of-service (QoS)-aware EH-enabled passive IoT device in a cognitive radio inspired non-orthogonal multiple access (CR-NOMA)-assisted backscatter communication network. Our goal is to optimize the sum rate of a secondary passive IoT device while guaranteeing the QoS requirements of the scheduled primary device. The deep deterministic policy gradient (DDPG) algorithm is employed to dynamically adjust the reflection coefficient of the backscatter node, yielding optimal performance. Our results demonstrate significant improvements in the sum rate, highlighting the importance of incorporating advanced machine learning (ML) techniques into IoT and wireless communication domains to address critical challenges and enhance the overall performance of NG-IoT networks.

This paper investigates the energy-efficient beamforming design in a simultaneous transmission and reflection-reconfigurable intelligent surface (STAR-RIS) assisted wireless communication system, where the antenna selection scheme is adopted. An energy efficiency (EE) maximization problem is formulated by optimizing the transmit beamformers and the phase shift vectors subject to the power budget constraint of the base station (BS), the maximum transmit power constraint per antenna and the users' data rate requirements. An alternating optimization-based algorithm is proposed to tackle the coupled variables, and the quadratic transform is used to deal with the fractional formulations. Simulation results demonstrate that the antenna selection scheme can significantly improve the EE performance by suppressing the energy consumption due to massive antennas. With the assistance of the STAR-RIS, the EE performance is further enhanced.

The aim of this paper is to exploit cognitive-ratio inspired non-orthogonal multiple access (CR-NOMA) transmission to reduce the age of information (AoI) in wireless networks, where the key features of different data generation models are effectively utilized. Analytical results for the AoI achieved by CR-NOMA are developed to demonstrate two benefits of using NOMA to reduce the AoI in wireless networks. One is that the use of NOMA provides users more opportunities to transmit, which means that the users can update their base station more frequently. The other is that the use of NOMA can reduce access delay, i.e., the users are scheduled to transmit earlier than in the orthogonal multiple access (OMA) case, which is useful to improve the freshness of the data available in the wireless network.

In this paper, we propose a multi-cell full-duplex (FD) networking scheme by deploying a reconfigurable intelligent surface (RIS) at the cell boundary to configure the radio environment proactively. We aim to maximize the sum rate (SR) of multiple cells by jointly optimizing the transmit precoding (TPC) matrices at FD base stations (BSs) and the phase shift matrix at RIS. Since the original problem is non-convex, we reformulate and decouple it into a pair of subproblems by utilizing the relationship between SR and minimum mean square error. The optimal solutions of TPC matrices are obtained in closed form, while a successive convex approximation-based algorithm is developed to resolve the phase shift matrix suboptimally. Simulation results show that introducing an RIS into the FD networking system can improve the overall SR significantly. More importantly, we validate that the RIS deployment with optimized phase shifts can reduce the requirement for self-interference cancellation (SIC) and the number of BS antennas effectively, especially with enough reflecting elements. As a result, the utilization of RIS enables the originally cumbersome FD networking system to become efficient and practical.

This paper investigates the transmission design of an active reconfigurable intelligent surface (RIS)-assisted integrated sensing and communication (ISAC) system. A sensing beampattern matching mean squared error (MSE) minimization problem is formulated under constraints of the power budgets at the base station and the RIS, the amplification factor of the RIS and the information rate requirements of users, by jointly optimizing the transmit beamforming vectors, the covariance matrix of the sensing signal and the reflection coefficients of the RIS. The considered problem is solved in an alternative optimization manner by decomposing the original problem into two sub-problems, where each sub-problem is solved via semi-definite relaxation (SDR) and successive convex approximation (SCA). The tightness of applying SDR is theoretically proved. Simulation results verify the convergence behavior and effectiveness of the proposed algorithm. It is also shown that the active RIS is able to improve the sensing beampattern matching performance by enhancing the information transmission.

One of the emerging computing paradigms, mobile edge computing (MEC, also known as fog computing), has been developed to reduce both energy consumption and computation latency for computation-extensive IoT applications. Further, thanks to advantages brought by non-orthogonal multiple access (NOMA) in increasing the capacity of multiple-access channels (MAC), and by service caching in alleviating the burden of responding to repeated computation requests, this paper considers the joint design of communication, computation, and caching for multi-user MEC systems. Aiming for minimizing the weighted-sum energy consumption of communication and computation, given a finite set of computation services, we jointly optimize the NOMA transmission, the computation resources, and the Boolean-variable modeled cache placement, subject to the computation and caching capacity of the edge server as well as the computation latency constraints. To solve the formulated mixed-integer non-convex problem, first, given the cache placement, we solve the non-differentiable convex problem by Lagrangian dual method leveraging a semi-closed form of NOMA transmission power, followed by a one-dimension search for the optimal common task offloading time. Next, an optimal branch-and-bound (BnB) based caching strategy is proposed. Meanwhile, we also provide a heuristic suboptimal cache placement design to reduce computational complexity. Finally, numerical results show the striking performance of the proposed joint optimization of NOMA-based task offloading and service caching compared to the greedy cache placement and other benchmarks without either NOMA-based task offloading or service caching.

We investigate a new self-sustainable intelligent omni-surface (S-IOS) aided multi-user wireless network, where the S-IOS harvests the radio frequency energy from the signals transmitted by the access point (AP) and exploits the harvested energy to provide full-dimensional beamforming services for the users. We design a joint optimization problem of transmit beamforming at the AP, refraction/reflection beamforming at the S-IOS, and energy harvesting schedule at the S-IOS, to maximize the sum rate of the overall network. A computationally-efficient algorithm is developed to solve the problem. Numerical results demonstrate the significant importance of the S-IOS for spectral and energy efficient wireless communications.

We investigate a reconfigurable intelligent surface (RIS)-aided wireless powered mobile edge computing (MEC) network, where a new RIS-aided hybrid non-orthogonal multiple access (NOMA) offloading scheme is proposed to improve the efficiency of both MEC offloading and energy harvesting. A joint optimization framework for the transmit power, time allocation, and RIS phase shifts is developed to minimize the overall energy consumption of the network, subject to the energy causality and MEC offloading constraints. Despite of the optimization problem's non-convexity with highly coupled optimization variables, we devise a computationally-efficient algorithm to solve it iteratively. Simulation results are also provided to facilitate the performance evaluation of the RIS-aided wireless powered MEC, quantify the value of the RIS for energy efficient MEC offloading, and validate the performance gains of the proposed hybrid NOMA offloading over various baseline schemes.

Mobile edge computing (MEC) is a distributed computing paradigm that brings computing and data storage closer to the network’s edge. This paper considers a multiple-input multiple-output (MIMO) uplink scenario where non-orthogonal multiple access (NOMA) users partially offload their data to a MEC server. The objective of this study is to minimize the total energy consumption during local computing, task offloading, and MEC computing. To this end, the base station optimizes power allocation vectors and task assignment coefficients under time and power constraints. The generalized singular value decomposition-based linear beamforming method integrates NOMA, MIMO, and MEC technologies. Due to the non-convex nature of the problem, a successive convex optimization (SCA) and alternation optimization (AO) based low-complex solution is proposed. The impact of the delay tolerance, the size of the offloaded task, and the distance of the users are investigated concerning energy consumption. The simulation results show that the proposed method achieves better energy performance than the orthogonal multiple access (OMA) schemes. More importantly, the performance gap increases when the data size is large, and the delay requirement is stringent, as 6G networks require.

Abstract While Doppler resilient complementary waveforms (DRCWs) have previously been considered to suppress range sidelobes within a Doppler interval of interest in radar systems, their ability to provide Doppler resilience can be further improved. A new singular value decomposition (SVD)‐based DRCW construction is proposed, in which both transmit pulse trains (made up of complementary pairs) and receive pulse weights are jointly considered. Besides, using the proposed SVD‐based method, a theoretical bound is derived for the range sidelobes within the Doppler interval of interest. Moreover, based on the SVD solutions, a challenging non‐convex optimization problem is formulated and solved to maximise the signal‐to‐noise ratio (SNR) with the constraint of low range sidelobes. It is shown that, compared with existing DRCWs, the proposed SVD‐based DRCW has better Doppler resilience. Further, the new optimised SVD‐based DRCW has a higher SNR while maintaining the same Doppler resilience.

Abstract Non‐orthogonal multiple access (NOMA) technique introduces spectrum cooperation among different users and devices, which improves spectrum efficiency significantly. Energy‐limited devices benefit from the backscatter (BAC) technique to transmit signals without extra energy consumption. The combination of NOMA and BAC provides a promising solution for Internet of Things (IoT) networks, where massive devices simultaneously transmit and receive signals. This study investigates a system model with two NOMA downlink users and an uplink device. The aim is to maximise the data rate of the uplink device by optimising the power allocation coefficient and the backscattering coefficient. Meanwhile the quality of service requirements of two NOMA users are guaranteed. The closed‐form solution of two optimisation variables is derived, and an alternating algorithm is also proposed to solve the formulated optimisation problem efficiently. The proposed system verifies the feasibility of IoT devices being added into existing networks and provides a promising solution for wireless communication networks in the future.

The Internet of Things (IoT) is a major driving force for future sixth-generation (6G) wireless systems. With the emergence of various novel IoT applications, more data should be collected and transmitted. However, IoT devices are constrained by battery, transmit power, and processing capacity. Featured by line-of-sight communication links, favorable channels, and better coverage, aerial access networks have been proposed to facilitate data transmission from IoT devices. In parallel, by shifting the computing and storage resources from the cloud to the edge of the network, edge computing [e.g., fog and mobile-edge computing (MEC)] can better support various computing-intensive and low-latency IoT applications. The integration of aerial access networks and edge computing, so-called aerial computing, is anticipated to provide not only traditional communication services but also advanced services for the IoT on a global scale.

This paper investigates a semi-grant-free (SGF) based transmission strategy to provide a flexible connectivity for various kinds of users in an integrated satellite-aerial-terrestrial network (ISATN). Herein, a high-altitude platform (HAP) termed as a grant-based user (GBU), which serves multiple mobile terminals (MTs) through space division multiple access (SDMA), wants to access a satellite network with multiple earth stations (ESs) termed as grant-free users (GFUs) simultaneously via non-orthogonal multiple access (NOMA) assisted SGF. To this end, we first propose two SGF-based uplink transmission schemes for both perfect channel state information (CSI) and imperfect CSI cases. When perfect CSI is available, a zero-forcing based beamforming (BF) scheme is used in HAP network while an adaptive transmit power allocation (ATPA) approach is adopted for SGF transmission. When only imperfect CSI is available, BF scheme employing the derived channel correlation matrix of HAP-MT link is proposed to achieve SDMA, and a novel ATPA strategy with rate probability constraint is proposed to guarantee quality-of-service of the GBU. Next, we derive the closed-form throughput expressions to evaluate the performance of the considered ISATN with the proposed two SGF-based schemes. Finally, computer simulations are conducted to validate the theoretical performance analysis and show the superiority of the proposed schemes over the related works. Moreover, our numerical results not only demonstrate a satisfactory performance of the proposed SGF-based scheme using imperfect CSI, but also reveal the impact of CSI errors on the system performance.

A multi-cell cluster-free NOMA framework is proposed, where both intra-cell and inter-cell interference are jointly mitigated via flexible cluster-free successive interference cancellation (SIC) and coordinated beamforming design. The joint design problem is formulated to maximize the system sum rate while satisfying the SIC decoding requirements and users’ minimum data rate requirements. To address this highly complex and coupling non-convex mixed integer nonlinear programming (MINLP), a novel distributed auto-learning graph neural network (AutoGNN) architecture is proposed to alleviate the overwhelming information exchange burdens among base stations (BSs). The proposed AutoGNN can train the GNN model weights whilst automatically optimizing the GNN architecture, namely the GNN network depth and message embedding sizes, to achieve communication-efficient distributed scheduling. Based on the proposed architecture, a bi-level AutoGNN learning algorithm is further developed to efficiently approximate the hypergradient in model training. It is theoretically proved that the proposed bi-level AutoGNN learning algorithm can converge to a stationary point. Numerical results reveal that: 1) the proposed cluster-free NOMA framework outperforms the conventional cluster-based NOMA framework in the multi-cell scenario; and 2) the proposed AutoGNN architecture significantly reduces the computation and communication overheads compared to the conventional convex optimization-based methods and the conventional GNNs with fixed architectures.

This paper investigates how to apply non-orthogonal multiple access (NOMA) as an add-on in terahertz (THz) networks. In particular, prior to the implementation of NOMA, it is assumed that there exists a legacy THz system, where spatial beams have already been configured to serve legacy primary users. The aim of this paper is to study how these pre-configured spatial beams can be used as a type of bandwidth resources, on which additional secondary users are served without degrading the performance of the legacy primary users. A joint beam management and power allocation problem is first formulated as a mixed combinatorial non-convex optimization problem, and then solved by two methods with different performance-complexity tradeoffs, one based on the branch and bound method and the other based on successive convex approximation. Both analytical and simulation results are presented to illustrate the new features of beam-based resource allocation in THz-NOMA networks and also demonstrate that those pre-configured spatial beams can be employed to improve the system throughput and connectivity in a spectrally efficient manner.

The aim of this paper is to exploit cognitive-radio inspired NOMA (CR-NOMA) transmission to reduce the age of information in wireless networks. In particular, two CR-NOMA transmission protocols are developed by utilizing the key features of different data generation models and applying CR-NOMA as an add-on to a legacy orthogonal multiple access (OMA) based network. The fact that the implementation of CR-NOMA causes little disruption to the legacy OMA network means that the proposed CR-NOMA protocols can be practically implemented in various communication systems which are based on OMA. Closed-form expressions for the AoI achieved by the proposed NOMA protocols are developed to facilitate performance evaluation, and asymptotic studies are carried out to identify two benefits of using NOMA to reduce the AoI in wireless networks. One is that the use of NOMA provides users more opportunities to transmit, which means that the users can update their base station more frequently. The other is that the use of NOMA can reduce access delay, i.e., the users are scheduled to transmit earlier than in the OMA case, which is useful to improve the freshness of the data available in the wireless network.

Simultaneous transmission and reflection-reconfigurable intelligent surface (STAR-RIS) can provide expanded coverage compared with the conventional reflection-only RIS. This paper exploits the energy efficient potential of STAR-RIS in a multiple-input and multiple-output (MIMO) enabled non-orthogonal multiple access (NOMA) system. Specifically, we mainly focus on energy-efficient resource allocation with MIMO technology in the STAR-RIS assisted NOMA network. To maximize the system energy efficiency, we propose an algorithm to optimize the transmit beamforming and the phases of the low-cost passive elements on the STAR-RIS alternatively until the convergence. Specifically, we first decompose the formulated energy efficiency problem into beamforming and phase shift optimization problems. To efficiently address the non-convex beamforming optimization problem, we exploit signal alignment and zero-forcing precoding methods in each user pair to decompose MIMO-NOMA channels into single-antenna NOMA channels. Then, the Dinkelbach approach and dual decomposition are utilized to optimize the beamforming vectors. In order to solve non-convex phase shift optimization problem, we propose a successive convex approximation (SCA) based method to efficiently obtain the optimized phase shift of STAR-RIS. Simulation results demonstrate that the proposed algorithm with NOMA technology can yield superior energy efficiency performance over the orthogonal multiple access (OMA) scheme and the random phase shift scheme.

In this paper, we propose a new simultaneous information relaying and jamming (SIRJ) scheme based on a dual-functional reconfigurable intelligent surface (RIS) to achieve secure non-orthogonal multiple access communications. Specifically, the RIS elements are split into two groups, where elements in one group perform signal reflection to enhance the legitimate reception quality while elements in the other group generate artificial jamming to interfere with the eavesdropper (Eve). Based on different channel state information (CSI) availabilities of Eve, the system sum-rate is maximized by jointly optimizing the transmit beamforming of the base station, reflect beamforming of the RIS, and mode selection of each RIS element, subject to a maximum tolerable information leakage to Eve. For the case with perfect Eve’s CSI, a penalty based alternating algorithm is proposed to deal with the challenging multivariate coupled and mixed integer non-convex optimization problem. For the case with imperfect Eve’s CSI, we consider the infinite number of secrecy constraints, for which the traditional$\mathcal {S}$-procedure cannot be directly applied. To tackle this challenge, we devise an efficient transformation that fits the$\mathcal {S}$-procedure to the problem and propose a robust secure beamforming design. Simulation results demonstrate the performance advantage of the proposed SIRJ scheme over the existing baseline schemes.

An active reconfigurable intelligent surface (RIS)-aided multi-user downlink communication system is investigated, where non-orthogonal multiple access (NOMA) is employed to improve spectral efficiency, and the active RIS is powered by energy harvesting (EH). The problem of joint control of the RIS’s amplification matrix and phase shift matrix is formulated to maximize the communication success ratio with considering the quality of service (QoS) requirements of users, dynamic communication state, and dynamic available energy of RIS. To tackle this non-convex problem, a cascaded deep learning algorithm namely long short-term memory-deep deterministic policy gradient (LSTM-DDPG) is designed. First, an advanced LSTM based algorithm is developed to predict users’ dynamic communication state. Then, based on the prediction results, a DDPG based algorithm is proposed to joint control the amplification matrix and phase shift matrix of the RIS. Finally, simulation results verify the accuracy of the prediction of the proposed LSTM algorithm, and demonstrate that the LSTM-DDPG algorithm has a significant advantage over other benchmark algorithms in terms of communication success ratio performance.

A generalized downlink multi-antenna non-orthogonal multiple access (NOMA) transmission framework is proposed with the novel concept of cluster-free successive interference cancellation (SIC). In contrast to conventional NOMA approaches, where SIC is successively carried out within the same cluster, the key idea is that the SIC can be flexibly implemented between any arbitrary users to achieve efficient interference elimination. Based on the proposed framework, a sum rate maximization problem is formulated for jointly optimizing the transmit beamforming and the SIC operations between users, subject to the SIC decoding conditions and users’ minimal data rate requirements. To tackle this highly-coupled mixed-integer nonlinear programming problem, an alternating direction method of multipliers-successive convex approximation (ADMM-SCA) algorithm is developed. The original problem is first reformulated into a tractable biconvex augmented Lagrangian (AL) problem by handling the non-convex terms via SCA. Then, this AL problem is decomposed into two subproblems that are iteratively solved by the ADMM to obtain the stationary solution. Furthermore, to reduce the computational complexity and alleviate the parameter initialization sensitivity of ADMM-SCA, a Matching-SCA algorithm is proposed. The intractable binary SIC operations are solved through an extended many-to-many matching, which is jointly combined with an SCA process to optimize the transmit beamforming. The proposed Matching-SCA can converge to an enhanced exchange-stable matching that guarantees the local optimality. Numerical results demonstrate that: i) the proposed Matching-SCA algorithm achieves comparable performance and a faster convergence compared to ADMM-SCA; ii) the proposed generalized framework realizes scenario-adaptive communications and outperforms traditional multi-antenna NOMA approaches in various communication regimes.

To enhance the outage performance of downlink non-orthogonal multiple access (NOMA) systems, we investigate opportunistic user pair scheduling (UPS) as well as the joint power allocation and decoding order selection (PA-DOS) for the scheduled user pair. Unlike most existing literature where the UPS and PA-DOS schemes are solely driven by channel conditions, we consider the impact of both the channel conditions and users’ target rates in the scheme design, since these two factors jointly determine the occurrence of transmission outages. Specifically, a two-stage rate-aware scheme for joint UPS and PA-DOS is proposed, which is proved to achieve the minimum system outage probability and guarantee fair access opportunities among users. For performance evaluation, the exact system outage probability achieved by the proposed scheme is derived in closed form, based on which a high-signal-to-noise-ratio asymptotic result is further derived for meaningful insights. Our analytical results reveal a new finding: The diversity order achieved by our proposed scheme, which is also the maximum achievable diversity order of the considered NOMA system, varies with the users’ target rates. Simulations confirm our findings and demonstrate that the proposed scheme can achieve a significant outage performance gain over the existing benchmark schemes.

Current fifth-generation (5G) networks do not cover maritime areas, causing difficulties in developing maritime Internet of Things (IoT). To tackle this problem, we establish a nearshore network by collaboratively using on-shore terrestrial base stations (TBSs) and tethered unmanned aerial vehicles (UAVs). These TBSs and UAVs form virtual clusters in a user-centric manner. Within each virtual cluster, non-orthogonal multiple access (NOMA) is adopted for agilely including various maritime IoT devices, which are sparsely distributed over the vast ocean. The nearshore network also shares the spectrum with marine satellites. In such a NOMA-based hybrid satellite-UAV-terrestrial network, interference among different network segments, different clusters, and different users occurs. We thereby formulate a joint power allocation problem to maximize the sum rate of the network. Different from existing studies, we use large-scale channel state information (CSI) only for optimization to reduce system overhead. The large-scale CSI is obtained by using the position information of maritime IoT devices. The problem is non-convex with intractable non-linear constraints. We tackle these difficulties by adopting max-min optimization, the auxiliary function method, and the successive convex approximation technique. An iterative power allocation algorithm is accordingly proposed, which is shown to be effective for coverage enhancement by simulations. This shows the potential of NOMA-based hybrid satellite-UAV-terrestrial networks for maritime on-demand coverage.

In this paper, the robust design for the intelligent reflective surface (IRS) assisted wireless multi-group multicast system is considered, in which two optimization design problems under two different channel state information (CSI) error models are separately discussed, i.e., the fairness-based problems and the quality-of-service (QoS)-based problems for both the bounded CSI error model and the statistical CSI error model. In order to deal with the non-convex constraints of the considered problems, i.e., bounded CSI error based constraint and statistical CSI error based constraint, S-procedure is adopted to convert the non-convex SINR constraint with bounded CSI error into linear matrix inequalities (LMIs), and the Bernstein-type inequality is utilized to transform the outage probability constraint with statistical CSI error into a second-order cone (SOC) constraint and linear inequalities. Following that, two efficient algorithms based on alternate optimization (AO) are proposed to solve the fairness problems and QoS problems, wherein the semi-definite programming (SDP), penalty convex-concave procedure (CCP) and semi-definite relaxation (SDR) are utilized. Furthermore, we analyze the complexity of the proposed algorithms. Finally, some numerical simulation results are presented to verify the effectiveness of the proposed algorithms, and the impacts of the CSI error and the discrete precision of IRS reflection phase shift on the system performance are analyzed, which provides some insights for the IRS deployment and system robust design.

This paper investigates the robust and secure task transmission and computation scheme in multi-antenna unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) networks, where the UAV is dual-function, i.e., aerial MEC and aerial relay. The channel uncertainty is considered during information offloading and downloading. An energy consumption minimization problem is formulated under some constraints including users’ quality of service and information security requirements and the UAV’s trajectory’s causality, by jointly optimizing the CPU frequency, the offloading time, the beamforming vectors, the artificial noise and the trajectory of the UAV, as well as the CPU frequency, the offloading time and the transmit power of each user. To solve the non-convex problem, a reformulated problem is first derived by a series of convex reformation methods, i.e., semi-definite relaxation, S-Procedure and first-order approximation, and then, solved by a proposed successive convex approximation (SCA)-based algorithm. The convergence performance and computational complexity of the proposed algorithm are analyzed. Numerical results demonstrate that the proposed scheme outperforms existing benchmark schemes. Besides, the proposed SCA-based algorithm is superior to traditional alternative optimization-based algorithm.

In this paper, physical layer security (PLS) in a non-orthogonal multiple access (NOMA)-based mobile edge computing (MEC) system is investigated, where hybrid successive interference cancellation (SIC) decoding is considered. Specifically, users intend to complete confidential tasks with the help of the MEC server, while an eavesdropper attempts to intercept the offloaded tasks. By jointly designing computational resource allocation, task assignment, and power allocation, a latency minimization problem is formulated. Based on the interactions between local computing time and MEC processing time, the closed-from solutions of computational resource allocation and task assignment are derived. After that, a strategy selection mechanism is established to select offloading strategies based on the corresponding conditions. Moreover, according to the analysis of hybrid SIC decoding, the conditions of different decoding orders in secure NOMA networks are derived. Furthermore, a reinforcement learning based algorithm is proposed to solve the power allocation problems for NOMA and OMA offloading strategies. This work is extended to a multi-user scenario, in which a matching-based algorithm is proposed to solve the formulated sub-channel assignment problem. Simulation results indicate that: i) the proposed solution can significantly reduce the latency and provide dynamic strategy selection for various scenarios; ii) the NOMA offloading strategy with hybrid SIC decoding can outperform other strategies in the considered system.

Simultaneously transmitting/refracting and reflecting reconfigurable intelligent surface (STAR-RIS) has been introduced to achieve full coverage area. This paper investigate the performance of STAR-RIS assisted non-orthogonal multiple access (NOMA) networks over Rician fading channels, where the incidence signals sent by base station are reflected and transmitted to the nearby user and distant user, respectively. To evaluate the performance of STAR-RIS-NOMA networks, we derive new approximate expressions of outage probability and ergodic rate for a pair of users, in which the imperfect successive interference cancellation (ipSIC) and perfect SIC (pSIC) schemes are taken into consideration. Based on the asymptotic expressions, the diversity orders of the nearby user with ipSIC/pSIC and distant user are achieved carefully. The high signal-to-noise ratio slopes of ergodic rates for nearby user with pSIC and distant user are equal to $one$ and $zero$, respectively. In addition, the system throughput of STAR-RIS-NOMA is discussed in delay-limited and delay-tolerant modes. Simulation results are provided to verify the accuracy of the theoretical analyses and demonstrate that: 1) The outage probability of STAR-RIS-NOMA outperforms that of STAR-RIS assisted orthogonal multiple access (OMA) and conventional cooperative communication systems; 2) With the increasing of reflecting elements $K$ and Rician factor $\kappa $, the STAR-RIS-NOMA networks are capable of attaining the enhanced performance; and 3) The ergodic rates of STAR-RIS-NOMA are superior to that of STAR-RIS-OMA.

Different from traditional reflection-only reconfigurable intelligent surfaces (RISs), simultaneously transmitting and reflecting RISs (STAR-RISs) represent a novel technology, which extends the half-space coverage to full-space coverage by simultaneously transmitting and reflecting incident signals. STAR-RISs provide new degrees-of-freedom (DoF) for manipulating signal propagation. Motivated by the above, a novel STAR-RIS assisted non-orthogonal multiple access (NOMA) (STAR-RIS-NOMA) system is proposed in this paper. Our objective is to maximize the achievable sum rate by jointly optimizing the decoding order, power allocation coefficients, active beamforming, and transmission and reflection beamforming. However, the formulated problem is non-convex with intricately coupled variables. To tackle this challenge, a suboptimal two-layer iterative algorithm is proposed. Specifically, in the inner-layer iteration, for a given decoding order, the power allocation coefficients, active beamforming, transmission and reflection beamforming are optimized alternatingly. For the outer-layer iteration, the decoding order of NOMA users in each cluster is updated with the solutions obtained from the inner-layer iteration. Moreover, an efficient decoding order determination scheme is proposed based on the equivalent-combined channel gains. Simulation results are provided to demonstrate that the proposed STAR-RIS-NOMA system, aided by our proposed algorithm, outperforms conventional RIS-NOMA and RIS assisted orthogonal multiple access (RIS-OMA) systems.

In this paper, we study an uplink reconfigurable intelligent surfaces-non-orthogonal multiple access (RIS-NOMA) assisted mobile edge computing (MEC) network with simultaneous wireless information and power transfer (SWIPT), where the users want to offload their computing tasks to the BS via a RIS and a relay based on the SWIPT technique. The goal of the paper is to minimize the delay concerning the computing tasks of the users by jointly optimizing the power allocation ratio, the phase shift matrix of the RIS, the offloading task ratio, and the offloading transmit power. For solving the challenging optimization problem, we conceive a low-complexity algorithm by optimizing two subproblems separately, based on the penalty method as well as the successive convex approximation. Simulation results demonstrate that the proposed RIS-NOMA assisted MEC network with SWIPT outperforms both the conventional RIS-NOMA assisted MEC network without SWIPT and the RIS-orthogonal multiple access assisted MEC network.

Unmanned aerial vehicle (UAV) communication is a promising technology that provides swift and flexible on-demand wireless connectivity for devices without infrastructure support. The proliferation of UAV communication equipment is causing the limited spectrum to become crowded. To deal with this issue, spectrum sharing policy (SSP) is introduced to support UAV communication. Spectrum sensing in SSP must be carefully formulated to control interference to the primary users and ground communications. In this paper, we propose spectrum sensing for opportunistic spectrum access in UAV communication to improve the spectrum utilization efficiency. Different from most existing works, we focus on the problem of spectrum sensing with randomly arriving primary signals in the presence of non-Gaussian noise/interference. We propose a novel spectrum sensing scheme to improve the spectrum utilization efficiency in UAV communication. We construct the p-norm decision statistic based on the assumption that the random arrivals of signals follow a Poisson process. Simulation results illustrate the validity and superiority of the proposed scheme when the primary signals are corrupted by additive non-Gaussian noise and are arriving randomly during spectrum sensing in the UAV communication.

A non-orthogonal multiple access (NOMA) inspired integrated sensing and communication (ISAC) system is investigated. A dual-functional base station (BS) serves multiple communication users while sensing multiple targets, by trans-mitting the non-orthogonal superposition of the communication and sensing signals. A NOMA inspired interference cancellation scheme is proposed, where part of the dedicated sensing signal is treated as the virtual communication signals to be mitigated at each communication user via successive interference cancellation (SIC). Based on this framework, the transmitted communication and sensing signals are jointly optimized to match the desired sensing beampattern, while satisfying the minimum rate requirement and the SIC condition at the communication users. Then, the formulated non-convex optimization problem is solved by invoking the successive convex approximation (SCA) to obtain a near-optimal solution. The numerical results show the proposed NOMA-inspired ISAC system can achieve better performance than the conventional ISAC system and comparable performance to the ideal ISAC system where all sensing interference is assumed to be removed unconditionally.

Vehicular networks are vulnerable to large scale attacks. Blockchain, implemented upon application layer, is recommended as one of the effective security and privacy solutions for vehicular networks. However, due to an increasing complexity of connected nodes, heterogeneous environment and rising threats, a robust security solution across multiple layers is required. Motivated by the Physical Layer Security (PLS) which utilizes physical layer characteristics such as channel fading to ensure reliable and confidential transmission, in this paper we analyze the impact of PLS on a blockchain-enabled vehicular network with two types of physical layer attacks, i.e., jamming and eavesdropping. Throughout the analysis, a Full Duplex Non-Orthogonal Multiple Access (FD-NOMA) based vehicle-to-everything (V2X) is considered to reduce interference caused by jamming and meet 5G communication requirements. Simulation results show enhanced goodput of a blockckchain enabled vehicular network integrated with PLS as compared to the same solution without PLS.

Reconfigurable intelligent surface (RIS) has been regarded as a promising technology since it has ability to create the favorable channel conditions. This paper investigates the secrecy performance of RIS aided non-orthogonal multiple access (NOMA) networks, where the internal eavesdropping scenario is taken into consideration. More specifically, novel closed-form and asymptotic expressions of secrecy outage probability for the k-th user are derived. According to the analytical results, the secrecy diversity orders at users are acquired in the high signal-to-noise ratio region. Simulation results show that the applying of RIS in NOMA networks can remarkably improve the performance of secrecy outage behaviour and secrecy system throughput compared to RIS aided orthogonal multiple access networks.

Non-orthogonal multiple access (NOMA) has been recognized as one of the key enabling technologies for future generation wireless networks. Sharing the same time-frequency resource among users imposes secrecy challenges in NOMA in the presence of untrusted users. This paper characterizes the impact of user-pair selection on the secrecy performance of an untrusted NOMA system. In this regard, an optimization problem is formulated to maximize the secrecy rate of the strong user while satisfying the quality of service (QoS) demands of the user with poorer channel conditions. To solve this problem, we first obtain optimal power allocation in a two-user NOMA system, and then investigate the user-pair selection problem in a more generalized four user NOMA system. Extensive performance evaluations are conducted to validate the accuracy of the proposed results and present valuable insights on the impact of various system parameters on the secrecy performance of the NOMA communication system.

In this paper, we consider a downlink multiple-input single-output non-orthogonal multiple access (MISO-NOMA) network with several legitimate users and a eavesdropper using successive interference cancellation (SIC). The purpose of this paper is to maximize the secrecy performance of the MISO-NOMA network by designing the transmit power between the legitimate users and the artificial jamming. Explicitly, the secrecy sum rate of the MISO-NOMA network is to be maximized by optimizing the transmit beamforming vectors and the artificial jamming vector, subject to the required quality of service of each legitimate user, the artificial jamming beamforming design constraint and the SIC decoding condition. Due to the non-convexity of the optimization problem, we reformulate the original problem into an equivalent optimization problem and then provide a successive convex approximation based iterative algorithm for solving it. Simulation results demonstrate that the proposed optimization scheme outperforms the existing schemes.

The initiation of fifth-generation (5G) wireless networks has been one of the latest innovations that the world has seen in recent years, which has also formed the foundation for the upcoming sixth-generation (6G) and beyond networks. The demand for high reliability with minimal delay of Internet of Things (IoT) applications has led to transmissions of short packets, which give rise to the proposal of ultra reliable and low-latency communications (URLLC). At a glance, the simultaneous demand for both reliability and minimal latency appears to be contradicting. However, by considering the impact of finite blocklength (FBL) regimes, the formulation of URLLC can be theoretically established under a wide range of practical scenarios such as severe fading, imperfect channel state information (iCSI), line-of-sight (LoS) fading and channel correlation. It has been noted that LoS, channel correlation and iCSI conditions have received interests among the community and their formulation illustrates practicality of theoretical signal processing research. Diversity has been deployed to combat fading, strengthen reliability and simultaneously reduce latency. Under specific environment, significant research has been developed and formulated to further the application of URLLC. The deployment of short packets however challenges Shannon's classical theory and opens a new research direction, which has attracted wide attention and research efforts around the world. Further, URLLC fundamentals can also be applied to intelligent reflective surface techniques, which clearly shows their applicability and usefulness. Myriads of work have been published and much more are coming to showcase the practicality of URLLC techniques and to explore its immense potential. This Special Issue (SI) has been formed to reflect on the latest developments on URLLC amid the fast-paced initiations and ideas. Through rigorous peer review processes, the selected papers have been chosen based on their high standard and diverse topics related to URLLC. The first paper by Q. Huang et al. examines the impact of cyclic redundancy check and rateless characteristic of cascading analogue fountain code under URLLC platform. The advanced inclusion of URLLC to 5G and 6G is also addressed and outlined, which makes this work timely. Cross verification and comparisons have been performed to show the effectiveness of their proposed method. Aiming to minimise end-to-end latency, the next paper of the SI treats the application of unmanned aerial vehicles (UAVs) under an URLLC platform using a Digital Twin (DT) approach. Edge computing is deployed to ensure that latency can be reduced to its minimum, and then optimisation is extra performed so that satisfactory results can be obtained. This work brings direct benefit to industry automation by exploiting K-mean algorithms for optimisation. Task offloading has been specifically considered to test the efficiency of the propped DT framework under URLLC platform. The third paper is dedicated to vehicular communications and the effectiveness of energy harvesting roadside units. This paper begins by proposing an attention-based spatial-temporal graph convolutional network to estimate vehicular communication load. A simulated data set was created to validate the proposed work, which potentially has commercialisation by lowering the cost of EHU-RSs. The fourth paper addresses one of the most fundamental problems of URLLC, which is joint power and blocklength optimisation for reflective intelligent surfaces (RIS) under FBL regimes using time division multiple access techniques. The effectiveness of the RIS under the FBL regimes has been clearly shown. Summary: This Special Issue has given a glimpse of URLLC capability from theoretical point of view to its wide applications, which involve UAVs and other smart devices. The prospect of URLLC is evolving into its advanced version in future wireless networks. The functionality of URLLC and other techniques is to ultimately serve the end user to strengthen convenience, practicality and technology advancement. From this point of view, the current URLLC framework has sufficiently ticked certain boxes. The Special Issue Editors would like to thank the Editor in Chief Professor James Hopgood, the Managing Editor Emily Summerbell and the editorial office for their constant support without which this Special Issue would not be possible. Research data are not shared. Khoa N. Le received his Ph.D. in October 2002 from Monash University, Melbourne, Australia. From April 2003 to June 2009, he was a Lecturer at Griffith University, Gold Coast campus, Griffith School of Engineering. From January to July 2008, he was a visiting professor at Intelligence Signal Processing Laboratory, Korea University, Seoul, Korea. From January 2009 to February 2009, he was a visiting professor at the Wireless Communication Centre, University Technology Malaysia, Johor Bahru, Malaysia. He is currently Associate Professor and Director of Academic Programme, Undergraduate, Electrical Engineering, School of Engineering, Design and Built Environment, Kingswood, Western Sydney University. His research interests are in wireless communications theory with applications to physical layer security and URLLC. Dr. Le has been Editor for IEEE Transactions on Vehicular Technology, IEEE Wireless Communication Magazine, and he is currently Deputy Editor In Chief of IET Signal Processing. He was listed in World's Top 2% scientists for 2021 and Bayu Chair Professor, Chongqing University of Science and Technology, Chongqing, China, 2020–2022. Derrick Wing Kwan Ng (S′06-M′12-SM′17-F′21) received a bachelor's degree with first-class honours and a Master of Philosophy (M.Phil.) degree in electronic engineering from the Hong Kong University of Science and Technology (HKUST) in 2006 and 2008, respectively. He received his Ph.D. degree from the University of British Columbia (UBC) in Nov. 2012. He was a senior postdoctoral fellow at the Institute for Digital Communications, Friedrich-Alexander-University Erlangen-N\"urnberg (FAU), Germany. He is now working as a Scientia Associate Professor at the University of New South Wales, Sydney, Australia. His research interests include global optimization, physical layer security, IRS-assisted communication, UAV-assisted communication, wireless information and power transfer, and green (energy-efficient) wireless communications. Ng has been listed as a Highly Cited Researcher by Clarivate Analytics (Web of Science) since 2018. He received the Australian Research Council (ARC) Discovery Early Career Researcher Award 2017, the IEEE Communications Society Stephen O. Rice Prize 2022, the Best Paper Awards at the WCSP 2020, 2021, IEEE TCGCC Best Journal Paper Award 2018, INISCOM 2018, IEEE International Conference on Communications (ICC) 2018, 2021, IEEE International Conference on Computing, Networking and Communications (ICNC) 2016, IEEE Wireless Communications and Networking Conference (WCNC) 2012, the IEEE Global Telecommunication Conference (Globecom) 2011, 2021 and the IEEE Third International Conference on Communications and Networking in China 2008. He served as an editorial assistant to the Editor-in-Chief of the IEEE Transactions on Communications from Jan. 2012 to Dec. 2019. He is now serving as an editor for the IEEE Transactions on Communications, the IEEE Transactions on Wireless Communications, and an Associate Editor-in-Chief for the IEEE Open Journal of the Communications Society. Zhiguo Ding (S′03-M′05-F′20) received his B.Eng in Electrical Engineering from the Beijing University of Posts and Telecommunications in 2000, and the Ph.D degree in Electrical Engineering from Imperial College London in 2005. From Jul. 2005 to Apr. 2018, he was working in Queen's University Belfast, Imperial College, Newcastle University and Lancaster University. Since Apr. 2018, he has been with the University of Manchester as a Professor in Communications. From Oct. 2012 to Sept. 2022, he has also been an academic visitor in Princeton University. Ding’ research interests are B5G networks, machine learning, cooperative and energy harvesting networks and statistical signal processing. He is serving as an Area Editor for the IEEE Open Journal of the Communications Society, an Editor for IEEE Transactions on Vehicular Technology, and IEEE Communications Surveys & Tutorials, and was an Editor for IEEE Wireless Communication Letters, IEEE Transactions on Communications, IEEE Communication Letters from 2013 to 2016. He recently received the EU Marie Curie Fellowship 2012–2014, the Top IEEE TVT Editor 2017, IEEE Heinrich Hertz Award 2018, IEEE Jack Neubauer Memorial Award 2018, IEEE Best Signal Processing Letter Award 2018, Friedrich Wilhelm Bessel Research Award 2020, and Best Paper Award at IEEE ICCC-2021. He is a Fellow of the IEEE, a Distinguished Lecturer of IEEE ComSoc, and a Web of Science Highly Cited Researcher in two categories 2020.

In existing computing systems, such as edge computing and cloud computing, several emerging applications and practical scenarios are mostly unavailable or only partially implemented. To overcome the limitations that restrict such applications, the development of a comprehensive computing paradigm has garnered attention in both academia and industry. However, a gap exists in the literature, owing to the scarce research, and a comprehensive computing paradigm is yet to be systematically designed and reviewed. This study introduces a novel concept, calledaerial computing, via the amalgamation of aerial radio access networks and edge computing, which attempts to bridge the gap. Specifically, first, we propose a novel comprehensive computing architecture that is composed of low-altitude computing (LAC), high-altitude computing (HAC), and satellite computing platforms, along with conventional computing systems. We determine that aerial computing offers several desirable attributes: global computing service, better mobility, higher scalability and availability, and simultaneity. Second, we comprehensively discuss key technologies that facilitate aerial computing, including energy refilling, edge computing, network softwarization, frequency spectrum, multiaccess techniques, artificial intelligence, and big data. In addition, we discuss vertical domain applications (e.g., smart cities, smart vehicles, smart factories, and smart grids) supported by aerial computing. Finally, we highlight several challenges that need to be addressed and their possible solutions.

The intelligent reflecting surface (IRS) technology is emerged as an enabling technology for beyond fifth-generation systems and Internet of Things networks in which the signal propagation is reconfigured to enhance wireless system performance. IRS consists of many passive elements and each reflecting the incident signal with a certain phase shift to collectively achieve the required beamforming. The IRS is to be a low profile and lightweight setting with a conformal geometry; hence, its position can be easily engineered to achieve certain performance enhancements. In the current literature, however, the flexibility in the IRS position is often overlooked since it is considered as a given fixture. We argue that optimizing the IRS position provides a new degree of freedom in the network design and enables extra performance gain. In this article, we analytically characterize the optimal IRS’s position to maximize the achievable system rate. We then obtain the optimal IRS positions for different IRS settings with fixed height and variable height and consider both cost-efficient equal phase shift IRS, and nonequal phase shift IRS that enables sophisticated beamforming. We further incorporate antenna directivity in our analysis and investigate its effect on the optimal IRS position in each case. Simulation results show that the provided optimal position yields higher performance than settings with random IRS locations. Our results provide significant practical insights on the network coverage design using the IRS.

As the long-term evolution (LTE) system is reaching maturity and the fifth-generation (5G) systems are being commercially deployed, researchers have turned their attention to the development of next-generation wireless networks. Compared to current wireless networks, on the one hand, next-generation wireless networks are expected to achieve significantly higher capacity, extremely low latency, ultra-high reliability, as well as massive and ubiquitous connectivity for supporting diverse disruptive applications (e.g., virtual reality (VR), augmented reality (AR), and industry 4.0). On the other hand, the evolution toward next-generation wireless networks requires a paradigm shift from the communication-oriented design to a multi-functional design, including communication, sensing, imaging, computing, and localization. Looking back at the history of wireless communication systems, multiple access (MA) techniques have been key enablers. From the first generation (1G) to the fifth generation (5G), orthogonal multiple access (OMA) schemes are mainly employed, where multiple users are allotted in orthogonal frequency/time/code resources, and the uplink transmission of the code code-division multiple-access (CDMA) uses non-orthogonal code resources. However, given the enormous challenges and diverse services of next-generation wireless networks, which significantly differ from that in current and previous wireless networks, existing MA schemes may not be applicable. As a result, a fundamental issue is the design of next-generation multiple access (NGMA) techniques. The key concept of NGMA is to enable a very large number of users/devices to be efficiently, flexibly, and intelligently connected with the network over the given wireless radio resources to not only satisfy stringent communication requirements but also realize heterogeneous functions. The investigation of NGMA is still in the infancy stage, and extensive research efforts have to be devoted to areas, including but not limited to 1) the development of new MA schemes, such as non-orthogonal multiple access (NOMA) and space division multiple access (SDMA), which are capable of achieving higher bandwidth efficiency and higher connectivity compared with conventional MA schemes; 2) the development of innovative techniques, such as reconfigurable metasurfaces, random access, advanced modulation, and channel coding, which are beneficial to the overall design of NGMA; and 3) the exploitation of advanced machine learning (ML) tools and big data techniques for providing effective solutions to address newly emerging NGMA problems.

As the long-term evolution (LTE) system is reaching maturity and the fifth-generation (5G) systems are being commercially deployed, researchers have turned their attention to the development of next-generation wireless networks. Compared to current wireless networks, on the one hand, next-generation wireless networks are expected to achieve significantly higher capacity, extremely low latency, ultra-high reliability, as well as massive and ubiquitous connectivity for supporting diverse disruptive applications (e.g., virtual reality (VR), augmented reality (AR), and industry 4.0). On the other hand, the evolution toward next-generation wireless networks requires a paradigm shift from the communication-oriented design to a multi-functional design, including communication, sensing, imaging, computing, and localization. Looking back at the history of wireless communication systems, multiple access (MA) techniques have been key enablers. From the first generation (1G) to the fifth generation (5G), orthogonal multiple access (OMA) schemes are mainly employed, where multiple users are allotted in orthogonal frequency/time/code resources, and the uplink transmission of the code code-division multiple-access (CDMA) uses non-orthogonal code resources. However, given the enormous challenges and diverse services of next-generation wireless networks, which significantly differ from that in current and previous wireless networks, existing MA schemes may not be applicable. As a result, a fundamental issue is the design of next-generation multiple access (NGMA) techniques. The key concept of NGMA is to enable a very large number of users/devices to be efficiently, flexibly, and intelligently connected with the network over the given wireless radio resources to not only satisfy stringent communication requirements but also realize heterogeneous functions. The investigation of NGMA is still in the infancy stage, and extensive research efforts have to be devoted to areas, including but not limited to 1) the development of new MA schemes, such as non-orthogonal multiple access (NOMA) and space division multiple access (SDMA), which are capable of achieving higher bandwidth efficiency and higher connectivity compared with conventional MA schemes; 2) the development of innovative techniques, such as reconfigurable metasurfaces, random access, advanced modulation, and channel coding, which are beneficial to the overall design of NGMA; and 3) the exploitation of advanced machine learning (ML) tools and big data techniques for providing effective solutions to address newly emerging NGMA problems.

Due to the explosive growth in the number of wireless devices and diverse wireless services, such as virtual/augmented reality and Internet-of-Everything, next generation wireless networks face unprecedented challenges caused by heterogeneous data traffic, massive connectivity, and ultra-high bandwidth efficiency and ultra-low latency requirements. To address these challenges, advanced multiple access schemes are expected to be developed, namely next generation multiple access (NGMA), which are capable of supporting massive numbers of users in a more resource- and complexity-efficient manner than existing multiple access schemes. As the research on NGMA is in a very early stage, in this paper, we explore the evolution of NGMA with a particular focus on non-orthogonal multiple access (NOMA), i.e., the transition from NOMA to NGMA. In particular, we first review the fundamental capacity limits of NOMA, elaborate on the new requirements for NGMA, and discuss several possible candidate techniques. Moreover, given the high compatibility and flexibility of NOMA, we provide an overview of current research efforts on multi-antenna techniques for NOMA, promising future application scenarios of NOMA, and the interplay between NOMA and other emerging physical layer techniques. Furthermore, we discuss advanced mathematical tools for facilitating the design of NOMA communication systems, including conventional optimization approaches and new machine learning techniques. Next, we propose a unified framework for NGMA based on multiple antennas and NOMA, where both downlink and uplink transmissions are considered, thus setting the foundation for this emerging research area. Finally, several practical implementation challenges for NGMA are highlighted as motivation for future work.

Reconfigurable intelligent surfaces (RISs) and nonorthogonal multiple access (NOMA) have been recognized as key enabling techniques for the envisioned sixth generation (6G) of mobile communication networks. The key feature of RISs is to intelligently reconfigure the wireless propagation environment, which was once considered to be fixed and untunable. The key idea of NOMA is to utilize users’ dynamic channel conditions to improve spectral efficiency and user fairness. Naturally, the two communication techniques are complementary to each other and can be integrated to cope with the challenging requirements envisioned for 6G mobile networks. This survey provides a comprehensive overview of the recent progress on the synergistic integration of RISs and NOMA. In particular, the basics of both techniques are introduced first, and then, the fundamentals of RIS-NOMA are discussed for two communication scenarios with different transceiver capabilities. Resource allocation is of paramount importance for the success of RIS-assisted NOMA networks, and various approaches, including artificial intelligence (AI)-empowered designs, are introduced. Security provisioning in RIS-NOMA networks is also discussed as wireless networks are prone to security attacks due to the nature of the shared wireless medium. Finally, the survey is concluded with detailed discussions of the challenges arising in the practical implementation of RIS-NOMA, future research directions, and emerging applications.

Non-orthogonal multiple access (NOMA) allows multiple users to share link resource for higher spectrum efficiency. It can be applied to unmanned aerial vehicle (UAV) and mobile edge computing (MEC) networks to provide convenient offloading computing service for ground users (GUs) with large-scale access. However, due to the line-of-sight (LoS) of UAV transmission, the information can be easily eavesdropped in NOMA-based UAV-MEC networks. In this paper, we propose a secure communication scheme for the NOMA-based UAV-MEC system towards a flying eavesdropper. In the proposed scheme, the average security computation capacity of the system is maximized while guaranteeing a minimum security computation requirement for each GU. Due to the uncertainty of the eavesdropper’s position, the coupling of multi-variables and the non-convexity of the problem, we first study the worst security situation through mathematical derivation. Then, the problem is solved by utilizing successive convex approximation (SCA) and block coordinate descent (BCD) methods with respect to channel coefficient, transmit power, central processing unit (CPU) computation frequency, local computation and UAV trajectory. Simulation results show that the proposed scheme is superior to the benchmarks in terms of the system security computation performance.

In this paper, we address the antenna selection (AS) problem in full-duplex (FD) cooperative non-orthogonal multiple access (NOMA) systems, where a multi-antenna FD relay bridges the connection between the multi-antenna base station and NOMA far user. Specifically, two AS schemes, namely max-U1 and max-U2, are proposed to maximize the end-to-end signal-to-interference-plus-noise ratio at either or both near and far users, respectively. Moreover, a two-stage AS scheme, namely quality-of-service (QoS) provisioning scheme, is designed to realize a specific rate at the far user while improving the near user’s rate. To enhance the performance of the QoS provisioning AS scheme, the idea of dynamic antenna clustering is applied at the relay to adaptively partition the relay’s antennas into transmit and receive subsets. The proposed AS schemes’ exact outage probability and achievable rate expressions are derived. To provide more insight, closed-form asymptotic outage probability expressions for the max-U1 and max-U2 AS schemes are obtained. Our results show that while the QoS provisioning AS scheme can deliver a near-optimal performance for static antenna setup at the relay, it provides up to 12% average sum rate gain over the optimum AS selection with fixed antenna setup.

The combination of energy harvesting (EH), cognitive radio (CR), and non-orthogonal multiple access (NOMA) is a promising solution to improve energy efficiency and spectral efficiency of the upcoming beyond fifth generation network (B5G), especially for support the wireless sensor communications in Internet of things (IoT) system. However, how to realize intelligent frequency, time, and energy resource allocation to support better performances is an important problem to be solved. In this paper, we study joint spectrum, energy, and time resource management for the EH-CR-NOMA IoT systems. Our goal is to minimize the number of data packets losses for all secondary sensing users (SSU), while satisfying the constraints on the maximum charging battery capacity, maximum transmitting power, maximum buffer capacity, and minimum data rate of primary users (PU) and SSUs. Due to the non-convexity of this optimization problem and the stochastic nature of the wireless environment, we propose a distributed multidimensional resource management algorithm based on deep reinforcement learning (DRL). Considering the continuity of the resources to be managed, the deep deterministic policy gradient (DDPG) algorithm is adopted, based on which each agent (SSU) can manage its own multidimensional resources without collaboration. In addition, a simplified but practical action adjuster (AA) is introduced for improving the training efficiency and battery performance protection. The provided results show that the convergence speed of the proposed algorithm is about 4 times faster than that of DDPG, and the average number of packet losses (ANPL) is about 8 times lower than that of the greedy algorithm.

Owing to the factors such as controllable mobility, ready-to-use technology, low cost, easy implementation, and so on, unmanned aerial vehicle (UAV) possesses tremendous potential to be one of the primary candidates for next-generation (6G) wireless networks. This paper presents a UAV-assisted multiuser communication network where a multiple antenna UAV base station (BS) serves multiple single antenna ground users (GUs). UAV-BS uses a laser source-based charging mechanism to fulfill its power requirement and applies simultaneous wireless information and power transfer (SWIPT) in the downlink in order to provide desired power to energy-constrained GUs. Also, a clustering-based hybrid multiple access technique is used that combines both orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA) signaling to transmit the information to all GUs, simultaneously. Due to the involved analytical complexity corresponding to the multiple antennas and users, we use a hybrid beamforming method for efficient communication. Next, we analyze the performance of the proposed framework in terms of user outage probabilities, their respective throughput, and average power harvested considering non-linear energy harvesting and derive expressions of these performance metrics. Moreover, we formulate an optimization problem where the throughput of one GU is maximized by optimally choosing the power allocation parameter while ensuring the desired target throughput at other GU in each cluster. We also illustrate how crucial is the optimal selection of the target rates to maximize the network performance. Simulation results are provided to validate the accuracy of derived expressions and to highlight the dominance of hybrid beamforming and hybrid NOMA compared to conventional methods on the performance of the considered network.

In this work, we consider a hybrid aerial full-duplex (FD) relaying protocol consisting of a reconfigurable intelligent surface (RIS) mounted over an FD unmanned aerial vehicle (UAV) relay operating in the decode and forward mode to assist the information transfer between the base station and multiple users. For better spectral efficiency, we investigate the use of non-orthogonal multiple access (NOMA) in such networks and focus on both the performance analysis and design optimization of the considered RIS-NOMA network under imperfect channel state information (CSI) and successive interference cancellation (SIC) at each user, and residual-self interference (RSI) at UAV. We first formulate the sum rate maximization problem and adopt the block coordinate descent method to deal with the non-convex nature of the problem. Thereafter, we propose an algorithm based on the Riemannian conjugate gradient method to get the optimal phase shifts at the RIS, an iterative algorithm to obtain the optimal UAV/RIS position and the exhaustive method to obtain the optimum power allocation coefficients. Next, with obtained optimal position, phase shift and power coefficients, we further analyze the performance of the network and derive the closed-form expressions of outage probability, achievable throughput and ergodic capacity. We present Monte Carlo simulation-based results to validate the accuracy of the proposed algorithms and derived expressions and demonstrate the superiority of NOMA over OMA.

By activating blocked users and altering successive interference cancellation (SIC) sequences, reconfigurable intelligent surfaces (RISs) become promising for enhancing non-orthogonal multiple access (NOMA) systems. To evaluate the benefits between RISs and NOMA, a downlink RIS-aided multi-cell-NOMA network is investigated via stochastic geometry. We first introduce the unique path loss model for RIS reflecting channels. Then, we evaluate the angle distributions based on a Poisson cluster process (PCP) model, which theoretically demonstrates that the angles of incidence and reflection are uniformly distributed. Additionally, we derive closed-form analytical and asymptotic expressions for coverage probabilities of the paired NOMA users. Lastly, we derive the analytical expressions of the ergodic rate for both of the paired NOMA users and calculate the asymptotic expressions for the typical user. The analytical results indicate that 1) the achievable rates reach an upper limit when the length of RIS increases; 2) exploiting RISs can enhance the path loss intercept to improve the performance without influencing the bandwidth. The simulation results show that 1) RIS-aided networks have superior performance than the networks without RISs; and 2) the SIC order in NOMA systems can be altered since RISs are able to change the channel quality of NOMA users.

The wireless networks beyond the fifth generation (5G) are envisioned to be the platform that will support a vast amount of diversified data-driven applications with stringent requirements in terms of computational accuracy, delay, and energy efficiency. The fulfillment of this objective can be achieved by the convergence of communication and computing networks, enabling the exploitation of edge computing resources and the joint orchestration of the corresponding resources. Mobile edge computing (MEC), which refers to the use of edge serves for offloading tasks from mobile devices, is a particularly promising approach to provide the required computational performance for emerging internet-of-things applications, such as the smart grids, smart industry, healthcare, and smart farming. In this work, we propose the use of an advanced multiple access technique and its joint design with adaptive task offloading, in order to reduce delay and energy consumption. More specifically, the use of generalized hybrid orthogonal/non-orthogonal multiple access (OMA/NOMA) for MEC is introduced, which is theoretically superior to other alternatives from the existing literature. In more detail, the proposed scheme is based on the joint utilization of dynamic user scheduling among OMA/NOMA phases and variable decoding order during the successive interference cancellation in NOMA phase. Also, the system’s orchestration is optimized for both full and partial task offloading. Specifically, in full offloading scenario, the user scheduling, time allocation, and power control are jointly optimized. Regarding partial offloading, the computational resources, i.e., the clock speed of the local processors and the number of offloaded bits, are jointly optimized with the communication resources, taking into account the constraint of the energy that is consumed for both local processing and task offloading, which is particularly challenging due to the non-convex nature of the corresponding optimization problem. All optimization problems are efficiently solved by either using closed-form solutions that provide useful insights or low-complexity algorithms. Finally, simulation results demonstrate the effectiveness of the proposed techniques and provide useful insights on the system’s performance, in terms of average delay and energy consumption.

Non-orthogonal multiple access (NOMA) assisted mobile edge computing (MEC) has recently attracted significant attention due to its superior capability to reduce the energy consumption and the latency of MEC offloading. In this paper, a general hybrid NOMA-MEC offloading strategy is proposed, which includes conventional orthogonal multiple access (OMA) and pure NOMA based offloading as special cases. A multi-objective optimization problem is formulated to minimize the energy consumption for MEC offloading, and a low-complexity resource allocation solution is derived and shown to be Pareto-optimal. Furthermore, by analyzing the properties of the obtained resource allocation solution, important insights regarding NOMA-MEC offloading are obtained. For example, it is proved that pure NOMA-MEC offloading cannot outperform hybrid NOMA-MEC. In addition, a precise condition under which NOMA-MEC outperforms OMA-MEC is established, and shown to match the one previously developed for the two-user special case. Furthermore, the developed analytical results also establish an interesting analogy between the proposed hybrid NOMA-MEC power allocation scheme and the well-known water-filling strategy.

Due to the proliferation of mobile devices, provisioning of massive connectivity has become a major challenge for future networks. The combination of millimeter wave (mmWave) with non-orthogonal multiple access (NOMA) provides a promising solution to massive connectivity. However, the security issue therein cannot be ignored due to the openness of wireless channels. To overcome the security challenge in mmWave-NOMA based networks, the nonorthogonal interference can be exploited to improve the security. In this paper, we propose a novel mmWave-NOMA framework where the users are classified as secure users (SUs) and common users (CUs), to satisfy their heterogeneous security service needs with the presence of randomly located eavesdroppers. According to their channel disparity, the NOMA users with stronger channel gains are deemed as SUs for better secrecy performance, while the remaining ones are served as CUs. To further enhance the security, hybrid precoding for SUs is designed to strengthen the desired signal and reduce interference. In addition, to reduce the complexity and satisfy the diverse demands, user grouping and power allocation are jointly optimized to maximize the sum rate of CUs subject to the SUs’ requirements. To solve the intractable non-convex problem, we decompose it into two subproblems, i.e., user grouping and power optimization, and a hybrid SU-CU grouping algorithm and a successive convex approximation based algorithm are proposed to solve them, respectively. Finally, simulation results are provided to show the advantages of the proposed scheme.

Coded multicasting is considered to be an effective approach to simultaneously serve multiple users in the same frequency/time/code resource, which is made possible by exploiting the information available in users’ caches. Recently, non-orthogonal multiple access (NOMA) has emerged as an alternative transmission technique for cache-aided network. In cache-aided NOMA system, cache-enabled interference cancellation (CIC) is employed to cancel the interference using the information in the cache, and thus enhance the user transmission rate, particularly for the weak users. Despite the enhanced spectral efficiency offered by both techniques, complexity issue arises from handling large number of users. Therefore, user pairing/clustering should be employed to limit the number of users served in the same time-frequency resource. However, the key question is which delivery technique performs better under different pairing scenarios. In this paper, the performance of NOMA and coded multicasting for two-user pairing are investigated in terms of probability of sum rate comparison and outage probability. In order to exploit the benefits of NOMA and coded multicasting, we also propose a hybrid delivery scheme, which select either NOMA or coded multicasting depending on the channel conditions of the paired users in each resource block (RB). A joint mode selection, power allocation and user pairing scheme is developed to enhance the performance of the hybrid scheme. Both analytical and simulation results demonstrate that NOMA outperforms coded multicasting when pairing users whose channel gains are highly distinctive, while coded multicasting is preferred when the paired users have similar channel gains. In addition, the hybrid scheme is demonstrated to offer enhanced sum rate performance in comparison to NOMA and coded multicasting.

In this paper, we consider an intelligent reflecting surface (IRS)-assisted downlink cognitive radio (CR) system, in which a secondary access point (SAP) communicates with multiple secondary users (SUs) without affecting multiple primary users (PUs) in the primary network and all nodes are equipped with multiple antennas. Our design objective is to maximize the achievable weighted sum rate (WSR) of SUs subject to the total transmit power constraint at the SAP and the interference constraints at PUs, by jointly optimizing the transmit precoding at the SAP and the reflecting coefficients at the IRS. To deal with the complex objective function, the problem is reformulated by employing the well-known weighted minimum mean-square error (WMMSE) method and an alternating optimization (AO)-based algorithm is proposed. Furthermore, a special scenario with only a single PU and multiple SUs is considered and AO algorithm is adopted again. It is worth mentioning that the proposed algorithm has a much lower computational complexity than the above algorithm without the performance loss. Finally, some numerical simulations have been provided to demonstrate that the proposed algorithm outperforms other benchmark schemes.

This paper investigates unmanned aerial vehicles (UAVs)-assisted full-duplex (FD) non-orthogonal multiple access (NOMA) system based cellular network, aiming to improve overall sum-rate throughput of the system through dynamic user clustering, optimal UAV placement and power allocation. Since each UAV operates in FD mode, self-interference (SI), co-channel interference (CCI), inter-UAV interference (IUI) and intra-node interference (INI) dominate the system’s performance. Consequently, we propose an unconventional two-stage dynamic user clustering for user nodes (UNs) to reduce the cross-interference in multi-UAV aided FD-NOMA system. Particularly, all UNs are initially clustered into$K$clusters using k-means clustering in the first stage where each cluster is served by an UAV. Furthermore, each cluster is further divided into sub-clusters and each sub-clusters are operated in FD-NOMA scheme. Finally, to control interferences, a sum-rate throughput maximization problem is formulated for each UAV to jointly optimize uplink and downlink power allocation and UAV placement. The joint optimization problem is non-convex and difficult to solve directly, for which we decoupled the original problem by addressing UAV placement and power allocation separately. We first fix the UAV position and then solve the problem iteratively using successive convex approximation (SCA) method. By utilizing brute-force search algorithm, an optimal UAV placement is later performed which corresponds to maximum possible sum-rate throughput. Simulation results demonstrate that the proposed solution for the considered FD-NOMA system outperforms the conventional schemes.

In this paper, we investigate covert communication in an intelligent reflecting surface (IRS)-assisted non-orthogonal multiple access (NOMA) system, where a legitimate transmitter (Alice) applies NOMA for downlink and uplink transmissions with a covert user (Bob) and a public user (Roy) aided by an IRS. Specifically, we propose new IRS-assisted downlink and uplink NOMA schemes to hide the existence of Bob’s covert transmission from a warden (Willie), which cost-effectively exploits the phase-shift uncertainty of the IRS and the non-orthogonal signal transmission of Roy as the cover medium without requiring additional uncertainty sources. Assuming the worst-case covert communication scenario where Willie can optimally adjust the detection threshold for his detector, we derive an analytical expression for the minimum average detection error probability of Willie achieved by each of the proposed schemes. To further enhance the covert communication performance, we propose to maximize the covert rates of Bob by jointly optimizing the transmit power and the IRS reflect beamforming, subject to given requirements on the covertness against Willie and the quality-of-service at Roy. Simulation results demonstrate the covertness advantage of the proposed schemes and confirm the accuracy of the derived analytical results. Interestingly, it is found that covert communication is impossible without using IRS or NOMA for the considered setup while the proposed schemes can always guarantee positive covert rates.

We introduce a set of multiple access protocols, calledhierarchical multiple access (HiMA), which are based on non-orthogonal multiple access (NOMA) and time-division multiple access (TDMA), optimized for the hierarchical network scenario. The proposed protocols can be efficiently utilized in various network configurations with an hierarchical form, such as relay networks, cloud-radio access networks (C-RANs), and fog-radio access networks (F-RANs). In particular, C-RANs and, more recently, F-RANs are regarded as promising paradigms to fully utilize the edge of the networks. Therefore, the implementation of novel multiple access protocols to properly exploit these configurations is critical for the fifth generation and beyond of wireless access. Furthermore, the resource allocation problem is formulated for each protocol with respect to the timeslot duration and power. As a result two fairness metrics are optimized, namely max-min rate fairness and proportional fairness. Finally, numerical results reveal the effectiveness of the joint design in the hierarchical network and an interesting trade-off is identified between fairness and achievable rate. Interestingly, despite NOMA being a very promising alternative to conventional multiple access schemes, the protocol that is solely based on NOMA does not always outperform the rest.

In limited space scenarios, the antennas in a multiantenna cognitive radio (CR) system are closely spaced and often experience correlation among them. In this paper, the sensing performance of arbitrarily correlated antennas over the Nakagami-$m$fading channel for the mobile CR user is analysed. In particular, the analytical expression for the average detection probability for a mobile CR user employing the selection combining with arbitrarily correlated triple diversity branches is derived as a special case. Moreover, to characterize the performance of an energy detector under mobility, the area under the curve of a receiver operating characteristic is analysed. Furthermore, as the sensing decisions can be utilized to improve the sensing performance, a comprehensive analysis of sensing performance of the mobile secondary user conditioned on the primary user (PU) activity statistics is carried out. We assume the PU traffic to be following the Discrete-Time Markov Chain (DTMC) model, and its$idle$and$busy$periods to be following generalised Pareto distribution. The analytical framework is substantiated by Monte Carlo simulations. Results indicate that antenna correlation deteriorates detection performance. Moreover, the detection performance deteriorates further due to the mobility of CR users, especially in the deep fading channel scenarios. Furthermore, findings also suggest that under mobility, the sensing performance improves if the duty cycle of the PU channel is low. This work provides a realistic sensing framework for CR enabled vehicles.

The integration of intelligent reflecting surface (IRS) and multiple access provides a promising solution to improved coverage and massive connections at low cost. However, securing IRS-aided networks remains a challenge since the potential eavesdropper also has access to an additional IRS reflection link, especially when the eavesdropping channel state information is unknown. In this paper, we propose an IRS-assisted non-orthogonal multiple access (NOMA) scheme to achieve secure communication via artificial jamming, where the multi-antenna base station sends the NOMA and jamming signals together to the legitimate users with the assistance of IRS, in the presence of a passive eavesdropper. The sum rate of legitimate users is maximized by optimizing the transmit beamforming, the jamming vector and the IRS reflecting vector, satisfying the quality of service requirement, the IRS reflecting constraint and the successive interference cancellation (SIC) decoding condition. In addition, the received jamming power is adapted at the highest level at all legitimate users for successful cancellation via SIC. To tackle this non-convex optimization problem, we first decompose it into two subproblems, and then each subproblem is converted into a convex one using successive convex approximation. An alternate optimization algorithm is proposed to solve them iteratively. Numerical results show that the secure transmission in the proposed IRS-NOMA scheme can be effectively guaranteed with the assistance of artificial jamming.

Grant-free (GF) transmission holds promise in terms of low latency communication by directly transmitting messages without waiting for any permissions. However, collision situations may frequently happen when limited spectrum is occupied by numerous GF users. The non-orthogonal multiple access (NOMA) technique can be a promising solution to achieve massive connectivity and fewer collisions for GF transmission by multiplexing users in power domain. We utilize a semi-grant-free (semi-GF) NOMA scheme for enhancing network connectivity and spectral efficiency by enabling grant-based (GB) and GF users to share the same spectrum resources. With the aid of semi-GF protocols, uplink NOMA networks are investigated by invoking stochastic geometry techniques. We propose a noveldynamic protocolto interpret which part of the GF users are allocated in NOMA transmissions via transmitting various channel quality thresholds by an added handshake. We utilize open-loop protocol with a fixed average threshold as the benchmark to investigate performance improvement. It is observed that dynamic protocol provides more accurate channel quality thresholds than open-loop protocol, thereby the interference from the GF users is reduced to a large extent. We analyze the outage performance and diversity gains under two protocols. Numerical results demonstrate that dynamic protocol is capable of enhancing the outage performance than open-loop protocol.

Compared with the conventional reconfigurable intelligent surfaces (RIS), simultaneous transmitting and reflecting intelligent omini-surfaces (STAR-IOSs) are able to achieve 360° coverage “smart radio environments”. By splitting the energy or altering the active number of STAR-IOS elements, STAR-IOSs provide high flexibility of successive interference cancellation (SIC) orders for non-orthogonal multiple access (NOMA) systems. Based on the aforementioned advantages, this paper investigates a STAR-IOS-aided downlink NOMA network with randomly deployed users. We first propose three tractable channel models for different application scenarios, namely the central limit model, the curve fitting model, and the M-fold convolution model. More specifically, the central limit model fits the scenarios with large-size STAR-IOSs while the curve fitting model is extended to evaluate multi-cell networks. However, these two models cannot obtain accurate diversity orders. Hence, we figure out the M-fold convolution model to derive accurate diversity orders. We consider three protocols for STAR-IOSs, namely, the energy splitting (ES) protocol, the time switching (TS) protocol, and the mode switching (MS) protocol. Based on the ES protocol, we derive closed-form analytical expressions of outage probabilities for the paired NOMA users by the central limit model and the curve fitting model. Based on three STAR-IOS protocols, we derive the diversity gains of NOMA users by the M-fold convolution model. The analytical results reveal that the diversity gain of NOMA users is equal to the active number of STAR-IOS elements. Numerical results indicate that 1) in high signal-to-noise ratio regions, the central limit model performs as an upper bound of the simulation results, while a lower bound is obtained by the curve fitting model; 2) the TS protocol has the best performance but requesting more time blocks than other protocols; 3) the ES protocol outperforms the MS protocol as the ES protocol has higher diversity gains.

Considering the security issue in mmWave-NOMA based networks, the nonorthogonal interference can be exploited to improve the security. In this paper, we propose a novel mmWave-NOMA framework where the users are classified as secure users (SUs) and common users (CUs), to satisfy their heterogeneous security service needs with the presence of ran-domly located eavesdroppers. For better secrecy performance, the NOMA users with stronger channel gains are deemed as SUs, and the hybrid precoding for SUs is designed to strengthen the desired signal and reduce interference. In addition, to reduce the complexity and satisfy the diverse demands, user grouping and power allocation are jointly optimized to maximize the sum rate of CUs subject to the SUs' requirements. The non-convex problem is decomposed into two subproblems, i.e., user grouping and power optimization, and a hybrid SU-CU grouping algorithm and a successive convex approximation based algorithm are proposed to solve them, respectively. Finally, simulation results are provided to show the advantages of the proposed scheme.

To achieve 360ºcoverage, we investigate a simulta-neous transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS) aided downlink non-orthogonal multiple access (NOMA) network with randomly deployed users. For different scenarios, we first derive two STAR- RIS-aided channel models, namely the central limit model and the curve fitting model. More specifically, the central limit model fits the scenarios with numerous RIS elements while the curve fitting model can be extended to multi-cell scenarios. The analytical results reveal that 1) the central limit model has closed-form expressions calculated as the error functions, and 2) the curve fitting model can be closely modeled as a Gamma distribution. We then derive the closed-form outage probability expressions for the NOMA users. Numerical results indicate that 1) the two channel models match the simulation results well in low signal-to-noise-ratio (SNR) regions and perform as boundaries in high SNR regions, 2) the central limit model performs as an upper bound of the simulation results, while a lower bound can be obtained by the curve fitting model, and 3) the both users in the NOMA pair have no error floor.

In this paper, a novel simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) assisted non-orthogonal multiple access (NOMA) system is proposed, where the STAR-RIS can simultaneously transmit and reflect the incident signals. Our objective is to maximize the achievable sum rate by jointly optimizing the decoding order, power allocation coefficients, active beamforming, transmission and reflection beamformings. However, the formulated problem is non-convex with intricately coupled variables. To tackle this challenge, a suboptimal two-layer iterative algorithm is proposed. Specifically, in the inner-layer iteration, for a given decoding order, the power allocation coefficients, active beamforming, transmission and reflection beamformings are optimized alternatively. For the outer-layer iteration, the decoding order of NOMA users in each cluster is updated with the solutions obtained from the inner-layer iteration. Simulation results are provided to demonstrate that the proposed STAR-RSI-NOMA system outperforms conventional RIS assisted systems.

The increase of mobile applications in the internet of vehicles (IoVs), necessitates the demand for higher computation capabilities. Vehicles can transfer related applications to another nodes for processing. In this paper, an efficient task offloading scheme for cellular vehicle to everything (C-V2X) is proposed to improve offloading reliability and latency. Vehicles are grouped into clusters, where vehicles in need of assistance can transfer their task to other vehicles for processing through the vehicle to vehicle (V2V) link, or transfer their task to the mobile edge computing (MEC) server via the vehicle to network (V2N) link. Matching theory is exploited for the task assignments. Simulation results reveals that the proposed scheme performs better than the existing schemes.

Non-orthogonal multiple access (NOMA) is an important technology for the forthcoming 5G and beyond. However, its privacy often suffers from adversarial eavesdropping, especially for the users with higher transmit power. In this paper, we propose a jamming-aided secure transmission scheme for cooperative NOMA networks with a full-duplex (FD) relay. In this scheme, two pairs of users perform secure transmission with the help of a decode-forward (DF) relay, which forwards information and generates artificial jamming to counteract eavesdropping. The precoding vectors are designed to zero-force the artificial jamming at legal receivers. Then, the channel statistics are calculated, based on which the expressions of secrecy outage probability (SOP) are derived. Simulation results show the accuracy of our analysis, and demonstrate that the proposed scheme can effectively reduce the SOP and improve the effective secrecy throughput via artificial jamming and FD relaying.

Abstract Unmanned aerial vehicles (UAVs) have gained considerable interests in numerous civil applications. To push forward its potentials, cellular-connected UAVs have been introduced. Nevertheless, cellular networks face several bottlenecks such as spectrum scarcity and limited concurrent connectivity. To address these issues, non-orthogonal multiple access (NOMA) can be adopted. NOMA provides several opportunities for cellular-connected UAVs such as larger rate region, balanced performance between system throughput and fairness, and reduced delay. In this paper, we review important findings of the related studies, and outline new opportunities and challenges in NOMA for cellular-connected UAVs. Monte-Carlo simulations are then performed to analyze the new aerial user’s (AU)’s signal characteristics and evaluate the NOMA performance for co-existence of AU and terrestrial user (TU). Our preliminary results show that NOMA is a promising strategy for cellular-connected UAVs.

Abstract The fifth generation (5G) wireless communication networks are being deployed worldwide from 2020 and more capabilities are in the process of being standardized, such as mass connectivity, ultra-reliability, and guaranteed low latency. However, 5G will not meet all requirements of the future in 2030 and beyond, and sixth generation (6G) wireless communication networks are expected to provide global coverage, enhanced spectral/energy/cost efficiency, better intelligence level and security, etc. To meet these requirements, 6G networks will rely on new enabling technologies, i.e., air interface and transmission technologies and novel network architecture, such as waveform design, multiple access, channel coding schemes, multi-antenna technologies, network slicing, cell-free architecture, and cloud/fog/edge computing. Our vision on 6G is that it will have four new paradigm shifts. First, to satisfy the requirement of global coverage, 6G will not be limited to terrestrial communication networks, which will need to be complemented with non-terrestrial networks such as satellite and unmanned aerial vehicle (UAV) communication networks, thus achieving a space-air-ground-sea integrated communication network. Second, all spectra will be fully explored to further increase data rates and connection density, including the sub-6 GHz, millimeter wave (mmWave), terahertz (THz), and optical frequency bands. Third, facing the big datasets generated by the use of extremely heterogeneous networks, diverse communication scenarios, large numbers of antennas, wide bandwidths, and new service requirements, 6G networks will enable a new range of smart applications with the aid of artificial intelligence (AI) and big data technologies. Fourth, network security will have to be strengthened when developing 6G networks. This article provides a comprehensive survey of recent advances and future trends in these four aspects. Clearly, 6G with additional technical requirements beyond those of 5G will enable faster and further communications to the extent that the boundary between physical and cyber worlds disappears.

Mobile-edge computing (MEC) is considered as a promising technology to enable low latency applications while consuming less energy, and nonorthogonal multiple access (NOMA) is regarded as a hopeful method of increasing spectrum efficiency and the wireless network capacity. In this article, we consider a NOMA-MEC-based Internet-of-Things (IoT) network, and propose a joint optimization framework to maximize the effective system capacity, i.e., the number of IoT devices whose tasks are processed successfully, and meanwhile to maximize the total energy saving. First, we concentrate on improving the effective system capacity from the wireless side by introducing NOMA, and from the IoT device side by task offloading decision optimization, where distributed optimization is conducted and closed-form solution is obtained. Then, we maximize the total energy saving also from two aspects, i.e., the device-side computation resource allocation, and the wireless side joint admission control, user clustering, orthogonal subcarrier assignment, and transmit power control, where we resort to graph theory and propose a low-complexity heuristic algorithm to solve it. Abundant simulation results demonstrate our proposed joint optimization algorithm performs well in both effective system capacity optimization and energy saving maximization.

The high spectrum efficiency of nonorthogonal multiple access (NOMA) is attractive to solve the massive number of connections in the Internet of Things (IoT). This article investigates a buffer-aided cooperative NOMA (C-NOMA) system in the IoT, where the intended users are equipped with buffers for cooperation. The direct transmission from the access point to the users and the buffer-aided cooperative transmission between the intended users are coordinated. In particular, a novel buffer-aided C-NOMA scheme is proposed to adaptively select a direct or cooperative transmission mode, based on the instantaneous channel state information and the buffer state. Then, the performance of the proposed scheme, in terms of the system outage probability and average delay, is theoretically derived with closed-form expressions. Furthermore, the full diversity order of three is demonstrated to be achieved for each user pair if the buffer size is not less than three, which is larger than conventional nonbuffer-aided C-NOMA schemes whose diversity order is only two in the considered C-NOMA system in the IoT.

This article investigates a multifog server (FS)-assisted nonorthogonal multiple access (NOMA)-based wireless powered network, where an energy-limited wireless device (WD) first harvests energy from a power transmitter (PT) and multiple helping FSs and then uses the harvested energy to partially offload its computing task to the FSs with NOMA for computing. To explore the WD's performance limit in terms of achievable computation rate, an optimization problem is formulated by jointly optimizing the time assignment, the power allocation, and the computation frequency under multiple system constraints. Since the problem is nonconvex with no known solution, an efficient solution approach is designed to achieve the ε-optimal solution, in which the transmit power vector and the computation frequency are jointly optimized with fixed-time assignment, and then, a golden section search (GSS)-based algorithm is designed to find the optimal time assignment. For the case when the FS is with sufficiently strong computation capability, some semiclosed-form results are derived. Numerous results show that our proposed design achieves much higher computation rate than benchmark schemes. Moreover, with the increment of the helping FSs, the achievable computation rate increases while the increasing rate is decreased. Besides, by employing NOMA, the WD's computation rate is also improved compared with orthogonal multiple access (OMA)-based scheme. Additionally, in such a system, with nonlinear energy harvesting (EH) model adopted, the more the helping FSs are deployed, the more the performance loss caused by the traditional linear EH model can be reduced.

Efficiency of cellular-connected UAVs is challenged by spectrum inefficiency, limited number of concurrent connectivity, and strong interference. To overcome these issues, in this paper, we study the performance of downlink non-orthogonal multiple access for cellular-connected UAVs. We develop a novel framework based on stochastic geometry for the co-existence of aerial users (AUs) and terrestrial users (TUs), where the spatial distribution of the base stations (BSs) follows a Poisson Point Process. In our analysis, two user association policies and two types of receive antennas are considered while an inter-cell interference coordination (ICIC) technique is also in place. As the main performance measures, we then analytically derive the coverage probability and average rate of AUs and TUs. These derivations are then used to provide quantitative insights on the impact of different system parameters and settings including AU's altitude, TU's distance from the BS, power allocation, successive interference cancellation (SIC) constraints, user association policy, antenna beamwidth, and the number of coordinated BSs. Based on our analysis we then propose an interference-aware scheme based on maximum-SINR user association, directional antenna, and ICIC. A benchmark scheme based on minimum-distance user association, omni-directional antenna, and without ICIC is considered. Compared to the benchmark scheme, our proposed scheme improves the AU's coverage probability by threefold and TU's average rate by six-fold. Compared to the orthogonal multiple access, our proposed scheme trades off a slight reduction in the AU's coverage probability (~1%) with a significant increase in the achieved rate of the TUs (603Kbps/resource block).

This paper investigates a dual-unmanned aerial vehicle (UAV)-enabled secure communication system, in which, a UAV moves around to send confidential messages to a mobile user while another cooperative UAV transmits artificial noise signals to confuse malicious eavesdroppers. Both UAVs have energy constraints and the location information of eavesdroppers is imperfect. We consider a worst-case secrecy rate maximization problem of the mobile user over all time slots. This optimization problem is solved by jointly designing the three-dimensional (3D) trajectory of UAVs and the time allocation (recharging and service or jamming) under practical constraints including maximum UAV speed, UAV collision avoidance, UAV positioning error, and UAV energy harvesting. Specifically, we adopt a more practical UAV-ground channel model with both large-scale and small-scale fading components. Due to the non-convex feasible region constructed by the complicated constraints, directly finding the optimal solution of the original problem is intractable. To address this issue, we decouple the original optimization problem into three subproblems and develop an iterative algorithm to find its suboptimal solution by using the block coordinate descent technique. To solve each subproblem, certain advanced optimization tools, such as integer relaxation, S-procedure, and successive convex approximation techniques, are utilized. Numerical simulation results are provided to corroborate the theoretical derivations and to evaluate the performance of the proposed algorithm. Additionally, the numerical results assist to draw new insights on the 3D UAV trajectory by comparing the performance with conventional two-dimensional (2D) schemes.

In-home health networks greatly rely on the massive connected monitoring devices. Compared to orthogonal multiple access (OMA), non-orthogonal multiple access (NOMA) can connect more monitoring devices and enhance the spectrum efficiency (SE) performance, which makes it an ideal solution to in-home health networks. However, conventional NOMA (C-NOMA) is mostly constrained to single-carrier scenario. The problem of multi-carrier NOMA lies in the inter-carrier interference (ICI) from neighboring carriers. In this article, we propose a sparse vector coding-based NOMA (SVC-NOMA) to suppress the ICI. We give closed-form expressions of capacity and symbol error rate (SER) performances for both C-NOMA and SVC-NOMA within the considered multi-carrier scenario. Simulation results demonstrate that compared to C-NOMA, SVC-NOMA has better capacity and SER performances. In addition, we find from our results that there is a trade-off between SVC-NOMA's ICI suppression ability and the system capacity performance.

In this paper, we consider a light fidelity (LiFi)-enabled bidirectional Internet of Things (IoT) communication system, where visible light and infrared light are used in the downlink and uplink, respectively. In order to efficiently improve the energy efficiency (EE) of the bidirectional LiFi-IoT system, non-orthogonal multiple access (NOMA) with a quality-of-service (QoS)-guaranteed optimal power allocation (OPA) strategy is applied to maximize the EE of both downlink and uplink channels. We derive closed-form OPA sets based on the identification of the optimal decoding orders in both downlink and uplink channels, which can enable low-complexity power allocation. Moreover, we propose an adaptive channel and QoS-based user pairing approach by jointly considering users' channel gains and QoS requirements. We further analyze the EE and the user outage probability (UOP) performance of both downlink and uplink channels in the bidirectional LiFi-IoT system. Extensive analytical and simulation results demonstrate the superiority of NOMA with OPA in comparison to orthogonal multiple access (OMA) and NOMA with typical channel-based power allocation strategies. It is also shown that the proposed adaptive channel and QoS-based user pairing approach greatly outperforms individual channel/QoS-based approaches, especially when users have diverse QoS requirements.

The next generation Internet of Things (IoT) exhibits a unique feature that IoT devices have different energy profiles and quality of service (QoS) requirements. In this paper, two energy and spectrally efficient transmission strategies, namely wireless power transfer assisted non-orthogonal multiple access (WPT-NOMA) and backscatter communication (Back-Com) assisted NOMA (BAC-NOMA), are proposed by utilizing this feature of IoT and employing spectrum and energy cooperation among the devices. In particular, the use of NOMA ensures that the devices with different QoS requirements can share the same spectrum, and WPT and Back-Com are employed to utilize the cooperation among the devices with different energy profiles, which avoids the use of a dedicated power beacon. Furthermore, for the proposed WPT-NOMA scheme, the application of hybrid successive interference cancelation (SIC) decoding order is also considered, and analytical results are developed to demonstrate that WPT-NOMA can avoid outage probability error floors and realize the full diversity gain. Unlike WPT-NOMA, BAC-NOMA suffers from an outage probability error floor, and the asymptotic behavior of this error floor is analyzed in the paper by applying the extreme value theory. In addition, the effect of a unique feature of BAC-NOMA, i.e., employing one device's signal as the carrier signal for another device, is studied, and its impact on the diversity gain is revealed. Simulation results are also provided to compare the performance of the proposed strategies and verify the developed analytical results.

This paper applies machine learning to optimize the transmission policies of cognitive radio inspired non-orthogonal multiple access (CR-NOMA) networks, where time-division multiple access (TDMA) is used to serve multiple primary users and an energy-constrained secondary user is admitted to the primary users' time slots via NOMA. During each time slot, the secondary user performs the two tasks: data transmission and energy harvesting based on the signals received from the primary users. The goal of the paper is to maximize the secondary user's long-term throughput, by optimizing its transmit power and the time-sharing coefficient for its two tasks. The long-term throughput maximization problem is challenging due to the need for making decisions that yield long-term gains but might result in short-term losses. For example, when in a given time slot, a primary user with large channel gains transmits, intuition suggests that the secondary user should not carry out data transmission due to the strong interference from the primary user but perform energy harvesting only, which results in zero data rate for this time slot but yields potential long-term benefits. In this paper, a deep reinforcement learning (DRL) approach is applied to emulate this intuition, where the deep deterministic policy gradient (DDPG) algorithm is employed together with convex optimization. Our simulation results demonstrate that the proposed DRL assisted NOMA transmission scheme can yield significant performance gains over two benchmark schemes.

Semi-grant-free (SGF) transmission has recently received significant attention due to its capability to accommodate massive connectivity and reduce access delay by admitting grant-free users to channels which would otherwise be solely occupied by grant-based users. In this paper, a new SGF transmission scheme that exploits the flexibility in choosing the decoding order in non-orthogonal multiple access (NOMA) is proposed. Compared to existing SGF schemes, this new scheme can ensure that admitting the grant-free users is completely transparent to the grant-based users, i.e., the grant-based users’ quality-of-service experience is guaranteed to be the same as for orthogonal multiple access. In addition, compared to existing SGF schemes, the proposed SGF scheme can significantly improve the robustness of the grant-free users’ transmissions and effectively avoid outage probability error floors. To facilitate the performance evaluation of the proposed SGF transmission scheme, an exact expression for the outage probability is obtained and an asymptotic analysis is conducted to show that the achievable multi-user diversity gain is proportional to the number of participating grant-free users. Computer simulation results demonstrate the performance of the proposed SGF transmission scheme and verify the accuracy of the developed analytical results.

The combination of non-orthogonal multiple access (NOMA) and multi-access edge computing (MEC) can significantly improve the system performance including communication coverage, spectrum efficiency, etc. In this article, we focus on energy-efficient resource allocation for a multi-user multi-BS NOMA-MEC network with imperfect channel state information (CSI), where each user can upload its tasks to multiple base stations (BSs) for remote executions. We propose an optimization scheme, including task assignment, power allocation and user association, to minimize energy consumption. Specifically, we transform the probabilistic problem into a non-probabilistic one. To efficiently solve this nonconvex energy minimization problem, we first investigate the one-user two-BS case and derive the optimal closed-form expressions of task assignment and power allocation via the bilevel programming method. Subsequently, based on the derived optimal solution, we propose a low complexity algorithm for the user association in the multi-user multi-BS scenario. Simulations demonstrate that the proposed algorithm can yield much better performance than the conventional OMA scheme and the identical results with lower complexity from the exhaustive search with the small number of BSs.

In contrast with the traditional cryptography, physical layer security has attracted the attention of many researchers having aim at reinforcing the security of communication systems. As far as vehicular communication is concerned, it is challenging to maintain secure and reliable communication between the connected vehicles due to the density, mobility, and dynamic network topology. This paper considers a vehicle to infrastructure communication in which a legitimately fixed transmitter equipped with a single antenna transmits a confidential message to a legitimate mobile receiver equipped with multiple antennas in the presence of a passive mobile eavesdropper. In such a single input multiple output wireless system, the receiver performs the maximal ratio combining technique assuming constant vehicle speed. We assume that the antennas are closely spaced and depending upon the imperfect channel state information (CSI), we derive the closed-form expressions for the average outage probability, secrecy outage probability, and average secrecy outage rate over the uniform, exponential, and arbitrary correlated Nakagami- m channels for dual antenna branches. In order to gain insight we also perform the high SNR asymptotic analysis of the outage probability and secrecy outage probability. Simulations are conducted to validate the accuracy of our derived analytic expressions. The computation error analysis is carried out to provide the suitability of the correlation type at the legitimate receiver side. Our findings suggest that the performance of the case with exponential channel correlation is better than those for the uniform and arbitrary. Numerical results show the joint effect of vehicle mobility and the antenna correlation on secrecy performance. Moreover, we also observed that the imperfect knowledge of the CSI degrades the security of the confidential messages severely under the effect of mobility.

In this paper, we investigate the downlink precoder design for two-user power-domain multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA). We propose a novel user-assisted (UA) simultaneous diagonalization (SD) based MIMO-NOMA scheme that achieves SD of the MIMO channels of both users through a combination of precoder design and low-complexity self-interference cancellation at the users, thereby considerably lowering the overall decoding complexity compared to joint decoding. The achievable ergodic user rates of the proposed scheme are analyzed for Rayleigh fading channels based on a finite-size random matrix theory framework, which is further exploited to develop a statistical power allocation algorithm. Simulation and numerical results show that the proposed UA-SD MIMO-NOMA scheme significantly outperforms orthogonal multiple access and a benchmark precoder design performing SD via generalized singular value decomposition in terms of the achievable ergodic rate region for most user rates. The ergodic rate region is further enhanced by a hybrid scheme which performs time sharing between the proposed UA-SD MIMO-NOMA scheme and single-user MIMO.

Non-orthogonal multiple access (NOMA) and ambient backscatter communication have been envisioned as two promising technologies for the Internet-of-things due to their high spectral efficiency and energy efficiency. Motivated by this fact, we consider an ambient backscatter NOMA system in the presence of a malicious eavesdropper. Under the realistic assumptions of residual hardware impairments (RHIs), channel estimation errors (CEEs) and imperfect successive interference cancellation (ipSIC), we investigate the physical layer security (PLS) of the ambient backscatter NOMA systems with emphasis on reliability and security. In order to further improve the security of the considered system, an artificial noise scheme is proposed where the radio frequency (RF) source acts as a jammer that transmits interference signals to the legitimate receivers and eavesdropper. On this basis, the analytical expressions for the outage probability (OP) and the intercept probability (IP) are derived. To gain more insights, the asymptotic analysis and corresponding diversity orders for the OP in the high signal-to-noise ratio (SNR) regime are carried out, and the asymptotic behaviors of the IP in the high main-to-eavesdropper ratio (MER) region are explored as well. Finally, the correctness of the theoretical analysis is verified by the Monte Carlo simulation results. These results show that compared with the non-ideal conditions, the reliability of the considered system is high under ideal conditions, but the security is low.

In this paper, we consider a wireless communication system, where a full-duplex hybrid access point (HAP) transmits to a set of cellular users (CUs) in the downlink channel, while receiving data from a set of energy-constrained communication devices like user equipments (UEs) in the uplink channel. The HAP has a massive antenna array, while all CUs and UEs nodes are equipped with single antenna each. Time switching protocol is adopted, where channel estimation, wireless power transfer, and information transfer between UEs, CUs and full-duplex HAP are performed in two phases. By adopting maximum ratio combining/maximum ratio transmission (MRC/MRT) and zero-forcing (ZF) processing at the HAP, the uplink and downlink achievable rate expressions in the large-antenna limit and approximate results that hold for any finite number of antennas are derived. Moreover, the optimum energy beamformer and time-split parameter at the HAP are found to maximize the downlink sum-rate under a constraint on uplink sum-rate. Our findings reveal that our proposed energy beamforming with ZF and MRC/MRT processing for information transfer achieves up to 47% and 14% average sum rate gains as compared with the suboptimum energy beamformer, respectively.

In this article, a two-user scenario of a non-orthogonal multiple access (NOMA)-based mobile edge computing (MEC) network is investigated. By treating the users and the MEC server as leader and follower, respectively, a Stackelberg game is formulated. More specifically, the leader tends to minimize the total energy consumption for task offloading and local computing by optimizing the task assignment coefficients and transmit power. On the other side, the follower aims to minimize the total execution time by allocating different computational resources for processing the offloaded tasks. In order to solve the formulated problem, the Stackelberg equilibrium is considered. Based on the given insights, a closed-form solution of the follower level problem is obtained and included in the leader level one. Furthermore, by analyzing the leader's strategies, the leader level problem is solved through the Karush-Kuhn-Tucker (KKT) conditions, and closed-form expressions for the optimal task assignment coefficients and offloading time, are derived. Finally, this work is extended to the multi-user scenario, where a matching-based user pairing algorithm is proposed to assign users into different sub-channels. Simulation results indicate that: i) the derived closed-form solutions and the proposed user pairing algorithm can significantly improve energy efficiency; ii) the different task assignment strategies can be dynamically implemented to handle the varying wireless environment.

In this paper, sub-channel scheduling, task assignment and power allocation are investigated for orthogonal multiple access (OMA)-based and non-orthogonal multiple access (NOMA)-based mobile edge computing (MEC) systems. Based on different channel conditions and computational capacities, computational tasks are partially offloaded to the MEC server via OMA or NOMA protocols. In order to minimize the total energy consumption, an optimization problem under the task execution latency constraint is formulated and divided into two sub-problems. By utilizing matching theory, the formulated sub-channel allocation problem is solved by a proposed low-complexity algorithm, where the joint optimization of task assignment and power allocation is performed at each iteration. Based on the delay constraint, some insights are obtained, and the closed-form solutions of task assignment coefficients and transmit power are derived. Furthermore, the offloading strategy in both OMA and NOMA schemes is analyzed, which shows that the optimal task assignment coefficient is decided by the energy consumption efficiency (ECE). Simulation results indicate that: i) the proposed sub-channel allocation algorithm and derived closed-form solutions can significantly improve the MEC system in terms of the energy consumption; ii) the provided offloading strategy can be dynamically and efficiently employed with different channel conditions and computational capacities.

This paper employs hybrid automatic repeat request (HARQ) to assist the cognitive non-orthogonal multiple access (NOMA) scheme for secure transmission in Internet of Things networks where the security-required (SR) users with high-security requirements and quality of services (QoS)-sensitive (QS) users with real-time process requirements are paired to perform NOMA for increasing the network connectivity. In addition, the imperfect successive interference cancellation (SIC) is considered at both legitimate users and eavesdropper for providing a realistic analysis. The closed-form expressions for the connection outage probability (COP), the secrecy transmission probability (RSP), and effective secrecy throughput (EST) of the SR user are derived in the proposed lightweight but efficient randomized retransmission scheme (RRS). As benchmarks, the secrecy performances of the fixed retransmission scheme (FRS) and orthogonal multiple access (OMA) scheme are also investigated. Besides, the asymptotic secrecy analysis is given to gain a better insight into secrecy performance. The analytical results developed in the paper demonstrate that HARQ is beneficial to secrecy transmission and the RRS outperforms or equals to the FRS and OMA scheme when the transmit power and secrecy coding redundancy is sufficiently high.

Although the use of coordinated direct and relay transmission (CDRT) in non-orthogonal multiple access (NOMA) can extend the coverage, its duplicated transmission reduces the spectrum efficiency (SE) of NOMA. To improve the SE, we propose a spectrum-efficient scheme for NOMA-based CDRT over Nakagami-m fading channels. In this scheme, the base station (BS) connects with a cell-center user (CCU) directly while communicating with a cell-edge user (CEU) via a relay and the CCU. Then, the relay and the CCU use network coding to process and retransmit the signals sent by the BS first and the CEU later. Finally, the BS and the relay simultaneously broadcast downlink signals. We derive the closed-form expressions for the average SE, the user fairness index and the energy efficiency (EE) as well as the asymptotic average SE using both perfect and imperfect successive interference cancellation (SIC). Simulations verify the correctness of our theoretical analysis and the superiority of the proposed scheme in SE and EE.

In this paper, we investigate the application of the non-orthogonal multiple access (NOMA) technique into the unmanned aerial vehicle (UAV) aided relay networks. Specifically, we first incorporate the NOMA protocol with the decode-and-forward (DF) relay protocol to enhance the performance of the cell edge users in a macrocell network. Theoretical analysis indicates that the NOMA-DF-relay protocol outperforms the conventional orthogonal multiple access (OMA) based DF-relay protocol in terms of data rate. To fully exploit the advantages of the proposed protocol, we formulate a joint UAV height optimization, channel allocation, and power allocation problem with the objective to maximize the total data rate of the cell edge users under the coverage of the UAV. For solving the formulated problem effectively, we first analyze its property and employ the golden section method to propose a general framework to obtain the optimal height of the UAV. Then, we design a low-complexity iterative algorithm to solve the joint channel-and-power allocation problem based on the matching theory and the Lagrangian dual decomposition technique. Finally, simulation results demonstrate that the NOMA-DF-relay protocol is superior to the OMA-DF-relay protocol even when the system parameters are not optimized, and the proposed algorithms can further significantly improve the network performance in comparison with the other schemes.

In this paper, we propose a downlink multiple-input single-output (MISO) transmission scheme, which is assisted by an intelligent reflecting surface (IRS) consisting of a large number of passive reflecting elements. In the literature, it has been proved that nonorthogonal multiple access (NOMA) can achieve the same performance as computationally complex dirty paper coding, where the quasi-degradation condition is satisfied, conditioned on the users' channels fall in the quasi-degradation region. However, in a conventional communication scenario, it is difficult to guarantee the quasi-degradation, because the channels are determined by the propagation environments and cannot be reconfigured. To overcome this difficulty, we focus on an IRS-assisted MISO NOMA system, where the wireless channels can be effectively tuned. We optimize the beamforming vectors and the IRS phase shift matrix for minimizing transmission power. Furthermore, we propose an improved quasi-degradation condition by using IRS, which can ensure that NOMA achieves the capacity region with high possibility. For a comparison, we study zero-forcing beamforming (ZFBF) as well, where the beamforming vectors and the IRS phase shift matrix are also jointly optimized. Comparing NOMA with ZFBF, it is shown that, with the same IRS phase shift matrix and the improved quasi-degradation condition, NOMA always outperforms ZFBF. At the same time, we identify the condition under which ZFBF outperforms NOMA, which motivates the proposed hybrid NOMA transmission. Simulation results show that the proposed IRS-assisted MISO system outperforms the MISO case without IRS, and the hybrid NOMA transmission scheme always achieves better performance than orthogonal multiple access.

In this paper, we investigate secure content delivery in a two-tier cache-enabled millimeter wave (mmWave) heterogeneous network composed of a macro base station (MBS) and K small base stations (SBSs) with caching capabilities. We allocate finite cache units at the SBSs and MBS to pre-store files with high popularities, where the SBSs store the most popular files, and the MBS stores the less popular ones. To deliver the file requested by a legitimate user securely, two secure transmission schemes, namely, distributed beamforming and direct transmission, are employed at the SBSs and MBS, respectively. Moreover, artificial noise (AN) is combined with the above two transmission schemes to further improve transmission security. The connection outage probability, secrecy outage probability, and secrecy throughput for the proposed mmWave transmission schemes are obtained. Based on these results, we jointly design the transmission rates and the cache resource allocation between the SBSs and MBS to maximize the overall secrecy throughput. We also provide insights into how the overall secrecy throughput is influenced by various parameters, including transmission rates, power allocation ratio of the AN scheme, and cache allocation factor. Numerical results are eventually presented to validate our theoretical analysis and demonstrate the effectiveness of the proposed transmission schemes and cache resource allocation strategy.

In this paper, a new transmit diversity scheme is proposed for cooperative pseudo-non-orthogonal multiple access (Pseudo-NOMA) without assuming full channel state information at the transmitter (CSIT). To support two users under the near-far user pairing constraint, a distributed cyclic delay diversity (dCDD) scheme is adapted into NOMA by dividing a set of remote radio heads (RRHs) into two groups for multiple cyclic-prefixed single carrier transmissions. To maximize a far user's rate and two users' sum rate over independently but non-identically distributed frequency selective fading channels and under a near-far user pairing constraint, we first derive closed-form expressions for the rates of the two users with full CSIT. Considering that only partial CSIT is available, a new RRH assignment and power allocation scheme is proposed for dCDD-Pseudo-NOMA. For various simulation scenarios, the provided link-level simulations verify that higher rates can be achieved by dCDD-Pseudo-NOMA compared with the traditional orthogonal multiple access with dCDD and dCDD-Conventional-NOMA that uses the superimposed signals. Furthermore, the proposed RRH assignment and power allocation scheme makes dCDD-Pseudo-NOMA achieve almost the same rate as that of ideal dCDD-Pseudo-NOMA which requires full CSIT.

Attracted by the advantages of multi-access edge computing (MEC) and non-orthogonal multiple access (NOMA), this article studies the resource allocation problem of a NOMA-MEC system in an ultra-dense network (UDN), where each user may opt for offloading tasks to the MEC server when it is computationally intensive. Our optimization goal is to minimize the system computation cost, concerning the energy consumption and task delay of users. In order to tackle the non-convexity issue of the objective function, we decouple this problem into two sub-problems: user clustering as well as jointly power and computation resource allocation. Firstly, we propose a user clustering matching (UCM) algorithm exploiting the differences in channel gains of users. Then, relying on the mean-field game (MFG) framework, we solve the resource allocation problem for intensive user deployment, using the novel deep deterministic policy gradient (DDPG) method, which is termed by a mean-field-deep deterministic policy gradient (MF-DDPG) algorithm. Finally, a jointly iterative optimization algorithm (JIOA) of UCM and MF-DDPG is proposed to minimize the computation cost of users. The simulation results demonstrate that the proposed algorithm exhibits rapid convergence, and is capable of efficiently reducing both the energy consumption and task delay of users.

This paper investigates the performance of non-orthogonal multiple access (NOMA) in vehicular networks where a base station (BS) communicates with the vehicles moving away from the BS with single-input multiple-output. To combine the signals received at the antennas, diversity combining techniques such as maximal ratio combining (MRC) and selection combining (SC) are performed at the receiver of each vehicle. However, in practice, the expected performance from the diversity techniques may not be achieved due to the fact that all the diversity branches are not independent and identically distributed (i.i.d) all the time. In this context, analytical expressions of the outage probability and ergodic sum rate are derived for the considered vehicular networks with the assumption of independent but not necessarily identically distributed (i.n.i.d) Nakagami-${m}$fading channels. The performance analysis of NOMA vehicular networks is also extended for multiple-input multiple-output antenna configurations and evaluated in the presence of successive interference cancellation (SIC) error propagation. The obtained analytical results are validated by Monte Carlo simulations. Furthermore, the performance of NOMA is verified with conventional orthogonal multiple access (OMA) for fading parameter$m=1$and$m=2$with perfect channel knowledge and channel estimation. Numerical results show that NOMA outperforms the conventional OMA by approximately 20% and has high sum rate with i.n.i.d as well as i.i.d channel consideration. However, i.n.i.d consideration degrades the performance of NOMA and OMA as the diversity gain achieved with i.n.i.d consideration is less as compared to i.i.d consideration. The performance is further deteriorated with SIC error and channel estimation.

A dual-polarized intelligent reflecting surface (IRS) can contribute to a better multiplexing of interfering wireless users. In this paper, we use this feature to improve the performance of dual-polarized massive multiple-input multiple-output (MIMO) with non-orthogonal multiple access (NOMA) under imperfect successive interference cancellation (SIC). By considering the downlink of a multi-cluster scenario, the IRSs assist the base station (BS) to multiplex subsets of users in the polarization domain. Our novel strategy alleviates the impact of imperfect SIC and enables users to exploit polarization diversity with near-zero inter-subset interference. To this end, the IRSs are optimized to mitigate transmissions originated at the BS from the interfering polarization. The formulated optimization is transformed into quadratically constrained quadratic sub-problems, which makes it possible to obtain the optimal solution via interior-points methods. We also derive analytically a closed-form expression for the users’ ergodic rates by considering large numbers of reflecting elements. This is followed by representative simulation examples and comprehensive discussions. The results show that when the IRSs are large enough, the proposed scheme always outperforms conventional massive MIMO-NOMA and MIMO-OMA systems even if SIC error propagation is present. It is also confirmed that dual-polarized IRSs can make cross-polar transmissions beneficial to the users, allowing them to improve their performance through diversity.

Connecting aerial users (AU)s to cellular networks expands the potential of many applications. Nevertheless, existing cellular networks are not designed to efficiently serve AUs and terrestrial users (TU)s. Limited spectrum and high interference make the task even more challenging. Thus, in this paper, we examine the feasibility of fixed-power non-orthogonal multiple access (NOMA) scheme in meeting the demands of AUs and TUs by leveraging stochastic geometry. To this end, we propose a tractable framework for evaluating the coverage of AU and TU in cellular networks, where BSs are distributed using Poisson Point Process (PPP). We then derive the coverage probability of AU and TU. Using these analytical expressions, we further analyze the impact of different network parameters such as AU's altitude, TU's distance, and power allocation, and obtain key insights for designing an efficient NOMA scheme. Our results show that i) increasing AU's altitude does not always degrade the signal-to-interference ratio (SIR), ii) fixed-power NOMA scheme cannot be employed solely to serve AU's control and command (C& C) link, iii) pairing a near TU with a typical AU may prevent significant performance degradation, and iv) mitigating the interference of TU could improve the performance of AU.

In this paper, a new transmit diversity scheme for cooperative non-orthogonal multiple access (NOMA) is proposed without perfect channel state information at the transmitter (CSIT). To support two users under a near-far user pairing constraint, a distributed cyclic delay diversity (dCDD) scheme is adjusted into NOMA by dividing a set of remote radio heads (RRHs) into two groups for multiple cyclic-prefixed single carrier transmissions. Using only a limited channel relevant information needed to make dCDD work, a new RRH assignment and power allocation mechanism is proposed. After then, closed-form expressions for the rates of two users achieved by the proposed RRH assignment and power allocation mechanism are derived. For various scenarios, link-level simulations verify that superior rates can be achieved by NOMA with dCDD over the traditional orthogonal multiple access with dCDD.

In this paper, we investigate a NOMA assisted multi-antenna two-way relay system, where users apply NOMA to support bidirectional superposition transmission with the aid of multiple relays. Specifically, we propose a multiple-access broadcast NOMA strategy together with a joint antenna-and-relay selection scheme to enhance its transmission reliability. Analytical closed-form expressions for the outage probability and diversity order are derived to evaluate the system performance achieved by the proposed strategy with the joint antenna-and-relay selection scheme. Based on the analytical result, we further optimize the power allocation to reduce the outage probability. Our numerical results show that the proposed mechanism significantly outperforms existing benchmark strategies in terms of the outage probability.

In this paper, we consider a non-orthogonal multiple access (NOMA) underwater optical wireless communication system in which a full-duplex decode-and-forward relay is used to assist the far user with weak channel conditions. Full-duplex operation introduces interference to the near user with strong channel conditions and our model covers several practical assumptions such as imperfect interference cancellation and random receiver orientation at the near/far user. In particular, we derive the exact outage probability at the near user and far user valid for log-normal weak turbulence conditions. An accurate outage approximation for the near user is also derived in closed-form. The correctness of the analysis has been verified through simulation results where they both match closely. Moreover, the derived expressions are useful to investigate the impact of various system and channel parameters such as the access point/relay transmit power, node locations, strength of the residual interference and random receiver orientation at the near and far user. Our results reveal that the outage probability of the near user is more sensitive to receiver orientation errors as compared to the far user.

In this paper, we propose a novel successive sub-array activation (SSAA) diversity scheme for a massive multiple-input multiple-output (MIMO) system in combination with non-orthogonal multiple access (NOMA). A single-cell multi-cluster downlink scenario is considered, where the base station (BS) sends redundant symbols through multiple transmit sub-arrays to multi-antenna receivers. An in-depth analytical analysis is carried out, in which an exact closed-form expression for the outage probability is derived. Also, a high signal-to-noise ratio (SNR) outage approximation is obtained and the system diversity order is determined. Our results show that the proposed scheme outperforms conventional full array massive MIMO setups.

Non-orthogonal multiple access (NOMA) aided unmanned aerial vehicle (UAV) is becoming a promising technique for future wireless networks. However, its security remains a great challenge due to the line-of-sight in UAV communications and high transmit power for weak users in NOMA. Thus, in this paper, we propose a power allocation (PA) scheme for NOMA-UAV networks with circular trajectory, to maximize the sum rate of common users while guaranteeing the security for a specific user. To achieve this, we consider three cases based on the distance from the UAV to the secure user. Specifically, the lowest transmit power is assigned to the secure user in each time slot to guarantee its security, with the remaining power allocated to common users to maximize their sum rate. To further improve the transmission rate of the secure user, we also derive the upper bound for its decoding threshold, and analyze the linear relationship between the secure decoding threshold and the sum rate of common users. Simulation results are demonstrated to evaluate the effectiveness of the proposed secure PA scheme in NOMA-UAV networks.

Scarcity of the radio spectrum and high inter-cell interference (ICI) are major impediments to efficient connectivity in cellular-connected unmanned aerial vehicles (UAV)s. To address these issues, we propose aerial-terrestrial network non-orthogonal multiple access (ATN-NOMA). In the proposed scheme, we pair the aerial user (AU) and terrestrial user (TU) in a NOMA setting to leverage their asymmetric channel gains and rate demands in downlink communication. The high ICI issue at the AU receiver is further managed by equipping the AU with an adjustable beamwidth directional antenna and forming a distributed beamforming among the coordinated terrestrial base stations (BSs). The proposed ATN-NOMA scheme obtains the optimal beamwidth and power allocation to maximize the TUs' sum-rate subject to the AU's Quality-of-Service (QoS) requirement. The corresponding optimization is a non-convex optimization problem for which we exploit the structure of the problem to obtain a local optimal solution. We further compare TUs' sum-rate and AU's outage probability of the proposed scheme with multiple schemes. Simulation results show that our proposed scheme significantly outperforms the existing schemes and further demonstrate a robust performance against UAV altitude variations.

This paper investigates a secrecy energy efficiency (SEE) optimization problem for a multiple-input multiple-output non-orthogonal multiple access network. In particular, a multi-antenna transmitter intends to send two integrated service messages: a confidential message for the stronger user and a broadcast message for both stronger and weaker users. It is assumed that both users are equipped with multi-antennas. In this secure wireless network, we consider the transmit covariance matrices design of confidential and broadcast message, under broadcast energy efficiency (BEE) constraint. In addition, it is assumed that the weaker user might turn out to be a potential eavesdropper due to the broadcast nature of wireless transmission. We formulate this transmit covariance matrices design as an SEE maximization problem which is non-convex in its original form due the non-linear fractional objective function and constraints. To realize the solution for this problem, we utilize non-linear fractional programming and difference of concave (DC) functions approach which facilitate to reformulate it into a tractable form. Based on the Dinkelbach's algorithm and DC approximation method, we propose iterative algorithms to determine a solution to the original SEE maximization problem. Numerical results are provided to demonstrate the performance of the proposed transmit covariance matrices design to maximize the SEE.

Non‐orthogonal multiple access (NOMA) has been considered a key technology to address the increasing traffic demands for fifth‐generation (5G) cellular wireless communication networks and internet of things. The NOMA technique offers efficient bandwidth utilisation, low latency, and support for the massive connectivity of devices in 5G networks. In the conventional NOMA system, orthogonal frequency division multiplexing (OFDM) is used as a pulse‐shaping technique that causes high peak to average power ratio (PAPR) due to the superposition of signals of multiple users after passing through inverse fast Fourier transform and spectral inefficiency due to the cyclic prefix insertion. Therefore, an alternate methodology using wavelet OFDM is proposed in this research work, as a pulse‐shaping technique for NOMA‐based communication systems to improve spectral efficiency and system capacity The main contribution of this study is the analysis of the bit error rate (BER) performance and the effect of carrier frequency offset on system performance of wavelet NOMA (W‐NOMA) technique in 5G networks. The simulation results demonstrate that W‐NOMA outperforms the conventional NOMA with reference to PAPR and BER.

In this study, a simple two‐user multiple‐input multiple‐output (MIMO) relaying scenario is considered. To efficiently exploit the spectrum resources, a generalised singular value decomposition (GSVD) based precoding scheme with non‐orthogonal multiple access (NOMA) is proposed, which converts the multiple channels into several parallel single channels. The performance of the proposed GSVD‐MIMO relaying scheme is evaluated by using the distribution characteristics of squared generalised singular values of two users' channel matrices and the eigenvalues of the relay's channel matrix to obtain the expressions of the average data rate and outage probabilities. Both the asymptotic case and a practical scenario with nodes equipped with finite numbers of antennas are analysed because the distribution characteristics of squared generalised singular values in the two cases are different. Two special cases, single‐input multiple‐output and multiple‐input single‐output are considered. Simulation experiments are carried out to verify the effectiveness and accuracy of the obtained analytical results.

Considering the diversified communication requirements in the Internet-of-Things (IoT) networks, this article proposes a nonorthogonal multiple access (NOMA) scheme which pairs two types of typical users, i.e., delay-sensitive user (DSU) and security-required user (SRU) to share the same nonorthogonal communication resources. We focus on the investigation of the secure transmission for the SRU while guaranteeing the communication requirements of the DSUs at the high priority. Specifically, the delay requirement of the DSUs and the security demand of the SRU are guaranteed by using short-packet communications and the maximal ratio transmission (MRT) scheme, respectively. Since the packets cannot always be detected correctly in the short-packet communications, a novel power allocation strategy is designed sophisticatedly to avoid the outage performance floor at the SRU caused by the short-packet communications. A set of closed-form expressions of the connection outage probability (COP), secrecy outage probability, and effective secrecy throughput (EST) of the SRU are derived over Nakagami-m channels in the proposed NOMA scheme and also the benchmark OMA scheme. Besides, we provide the security- reliability tradeoff (SRT) and security-efficiency tradeoff (SET) results for obtaining more insights into system performance. Results demonstrate the superiority of the proposed NOMA scheme over the benchmark OMA scheme in terms of the COP, EST, SRT, and SET when the transmitter is equipped with multiple antennas.

Multi-access edge computing (MEC) can enhance the computing capability of mobile devices, while non-orthogonal multiple access (NOMA) can provide high data rates. Combining these two strategies can effectively benefit the network with spectrum and energy efficiency. In this paper, we investigate the task delay minimization in multi-user NOMA-MEC networks, where multiple users can offload their tasks simultaneously through the same frequency band. We adopt the partial offloading policy, in which each user can partition its computation task into offloading and locally computing parts. We aim to minimize the task delay among users by optimizing their tasks partition ratios and offloading transmit power. The delay minimization problem is first formulated, and it is shown that it is a nonconvex one. By carefully investigating its structure, we transform the original problem into an equivalent quasi-convex. In this way, a bisection search iterative algorithm is proposed in order to achieve the minimum task delay. To reduce the complexity of the proposed algorithm and evaluate its optimality, we further derive closed-form expressions for the optimal task partition ratio and offloading power for the case of two-user NOMA-MEC networks. Simulations demonstrate the convergence and optimality of the proposed algorithm and the effectiveness of the closed-form analysis.

This paper investigates the diversity gain of a distributed cyclic delay diversity (dCDD) scheme for cyclic-prefixed single carrier systems in non-identical fading channels. Non-identical small-scale fading is assumed in the environment, in which non-identical line-of-sight and non-line-of-sight fading coexist. A condition for dCDD resulting in intersymbol interference free reception at the receiver, is extended to this new channel environment. For an overpopulated system setup, a generalized performance analysis, is not available from existing works, is conducted after developing closed-form expressions for the distribution of the signal-to-noise ratio (SNR) realized at the receiver. Since the order statistics are involved in the statistical properties of the SNR, the corresponding spacing statistics are utilized to derive feasible closed-form expressions. The finalized closed-form expressions are shown to provide very reliable outage probability and spectral efficiency of dCDD for underpopulated and overpopulated systems. An asymptotic performance analysis verifies the maximum achievable diversity of the dCDD even in the overpopulated case within the considered channel environment. Link-level simulations are conducted and these verify the maximum achievable diversity gain.

We investigate a secrecy-enhancing design for cooperative downlink and uplink non-orthogonal multiple access (NOMA) transmissions with an untrusted relay. A source uses the NOMA principle to have downlink and uplink transmissions with a near user and a far user, and the communications between the source and the far user are aided by an untrusted relay. To minimize information leakage at the untrusted relay and achieve secure NOMA communications, adaptive downlink and uplink cooperative jamming schemes are proposed, where the far user in downlink and the near user in uplink adaptively emit a jamming signal to the untrusted relay to impair its eavesdropping capability. Both downlink and uplink jamming power are optimized to fully exploit the benefits of the proposed schemes for security enhancement. Then, for each scheme, we quantify the secrecy performance by deriving the ergodic secrecy sum rate lower bound and its scaling law. Finally, computer simulation is used to demonstrate the effectiveness of the proposed adaptive downlink and uplink cooperative jamming schemes and verify the accuracy of the derived analytical results.

Unmanned aerial vehicles (UAVs) are playing an important role in wireless networks, due to their cost effectiveness and flexible deployment. Particularly, integrating UAVs into existing cellular networks has great potential to provide high-rate and ultra-reliable communications. In this paper, we investigate the uplink transmission in a cellular network from a UAV using non-orthogonal multiple access (NOMA) and from ground users to base stations (BSs). Specifically, we aim to maximize the sum rate of uplink from UAV to BSs in a specific band as well as from the UAV's co-channel users to their associated BSs via optimizing the precoding vectors at the multi-antenna UAV. To mitigate the interference, we apply successive interference cancellation (SIC) not only to the UAV-connected BSs, but also to the BSs associated with ground users in the same band. The precoding optimization problem with constraints on the SIC decoding and the transmission rate requirements is formulated, which is non-convex. Thus, we introduce auxiliary variables and apply approximations based on the first-order Taylor expansion to convert it into a second-order cone programming. Accordingly, an iterative algorithm is designed to obtain the solution to the problem with low complexity. Numerical results are presented to demonstrate the effectiveness of our proposed scheme.

In this paper, we aim to design an adaptive power allocation scheme to minimize the average transmit power of a hybrid automatic repeat request with chase combining (HARQ-CC) enabled non-orthogonal multiple access (NOMA) system under strict outage constraints of users. Specifically, we assume that the base station only knows the statistical channel state information of the users. To achieve power efficient design and cope with the reliable transmissions of users, a partial HARQ-CC scheme is proposed. We first focus on the two-user case. To evaluate the performance of the two-user partial HARQ-CC enabled NOMA system, we first analyze the outage probability of each user. Then, an average power minimization problem is formulated. However, the attained expressions of the outage probabilities are nonconvex, and thus make the problem challenging to solve. Hence, we propose to use a successive convex approximation (SCA) based algorithm to solve the problem iteratively. Meanwhile, we prove that the proposed algorithm can converge to a Karush-Kuhn-Tucker point of the original problem. For more practical applications, we also investigate the partial HARQ-CC enabled transmissions in the multi-user scenario. The user pairing and power allocation problem is considered. With the aid of matching theory, a low complexity algorithm is presented to first handle the user pairing problem. Then the power allocation problem for each user pair is solved by the proposed SCA-based algorithm. Simulation results show the efficiency of the proposed transmission strategy and the near-optimality of the proposed algorithms.

Dynamic adaptive video streaming over hypertext transfer protocol (DASH) plays a key role in video transmission over the Internet. The conventional DASH adaptation approaches mainly focus on optimizing the overall quality of experience (QoE) for all client sides, neglecting the QoE diversity of different users. In this paper, we propose a meta-learning framework for multi-user preferences (MLMP) as a new DASH adaptation approach, which is able to optimize the diverse QoE of different users. Specifically, we first design a subjective experiment to analyze the difference of QoE preferences across users, in which QoE refers to the metrics of visual quality, fluctuation, and rebuffering events. Based on our findings, we formulate the QoE optimization of multi-user preferences as a multi-task deep reinforcement learning (DRL) problem. In our formulation, the QoE preference of each user is modeled in the overall QoE calculation via assigning the weights to the three QoE metrics. Then, the MLMP framework is developed to solve the proposed multi-task DRL problem, such that the preferences regarding visual quality, fluctuation, and rebuffering events can be optimized for different users in DASH adaptation. Finally, the simulation results show that the proposed approach outperforms state-of-the-art DASH adaptation approaches in satisfying the different users' QoE preferences regarding visual quality, fluctuation, and rebuffering events.

In this paper, we design a secure transmission scheme in hybrid automatic repeat request (HARQ) assisted cognitive non-orthogonal multiple access (NOMA) networks, where a security-required user (SRU) is paired with a quality of service (QoS)-sensitive user (QSU) to perform NOMA. To elaborate, the QoS requirement of the QSU is guaranteed by a cognitive power allocation scheme, while the HARQ technique is employed to mitigate the successive interference cancellation (SIC) errors and improve the secrecy performance of the SRU. For reducing information leakage, a randomized retransmission NOMA (RR-NOMA) scheme is designed, where the retransmitted signals are generated from independent randomized codebooks. In this scheme, the closed-form expressions for the connection outage probability (COP), the average number of transmission (ANT), the secrecy outage probability (SOP), and effective secrecy throughput (EST) of the SRU are derived. In addition, as benchmarks, the performance analyses for the fixed retransmission (FR-NOMA) scheme and the randomized retransmission orthogonal multiple access (RR-OMA) scheme are also provided. Results show a trade-off between SOP and COP or EST, which is denoted by security-reliability trade-off (SRT) or security-efficiency trade-off (SET). Furthermore, simulation results show that the HARQ technique improves SRT and the RR-NOMA scheme achieves better SET than the FR-NOMA scheme in the low SOP region. We further conduct asymptotic analysis in the RR-NOMA, FR-NOMA and RR-OMA schemes. Asymptotic results demonstrate that the three schemes achieve the same ANT and the RR-NOMA scheme obtains better secrecy performance than the RR-OMA scheme and equal secrecy performance to the FR-NOMA scheme in terms of both EST and SOP.

Energy efficiency (EE) and spectral efficiency (SE) are two of the key performance metrics in future wireless networks, covering both design and operational requirements. For previous conventional resource allocation techniques, these two performance metrics have been considered in isolation, resulting in severe performance degradation in either of these metrics. Motivated by this problem, in this paper, we propose a novel beamforming design that jointly considers the trade-off between the two performance metrics in a multiple-input single-output non-orthogonal multiple access system. In particular, we formulate a joint SE-EE based design as a multi-objective optimization (MOO) problem to achieve a good trade-off between the two performance metrics. However, this MOO problem is not mathematically tractable and, thus, it is difficult to determine a feasible solution due to the conflicting objectives, where both need to be simultaneously optimized. To overcome this issue, we exploit a priori articulation scheme combined with the weighted sum approach. Using this, we reformulate the original MOO problem as a conventional single objective optimization (SOO) problem. In doing so, we develop an iterative algorithm to solve this non-convex SOO problem using the sequential convex approximation technique. Simulation results are provided to demonstrate the advantages and effectiveness of the proposed approach over the available beamforming designs.

The increasing demands for massive connectivity, low latency, and high reliability of future communication networks require new techniques. Multiple-input-multiple-output non-orthogonal multiple access (MIMO-NOMA), which incorporates the NOMA concept into MIMO, is an appealing technology to enhance system throughput and energy efficiency. However, rapidly changing channel conditions and extremely complex spatial structure degrade the system performance and hinder its application. Thus, to tackle these limitations, in this paper, we propose a deep learning-based MIMO-NOMA framework for maximizing the sum data rate and energy efficiency. To be specific, we design an effective communication deep neural network (CDNN) in which several convolutional layers and multiple hidden layers are included. Thanks to the impressive representation ability of the deep learning technique, the CDNN framework addresses the power allocation problem for achieving higher data rate and energy efficiency of MIMO-NOMA with the aid of training algorithms. Additionally, simulation results corroborate that the proposed CDNN framework is a good candidate to enhance the performance of MIMO-NOMA in term of power allocation, and extensive simulations show that it realizes larger sum data rate and energy efficiency compared with conventional strategies.

This paper investigates the impact of residual transceiver hardware impairments (RTHIs) on cooperative nonorthogonal multiple access (NOMA) networks, where generic α - μ fading channel is considered. To be practical, imperfect channel state information (CSI) and imperfect successive interference cancellation (SIC) are taken into account. More particularly, two representative NOMA scenarios are proposed, namely non-cooperative NOMA and cooperative NOMA. For the non-cooperative NOMA, the base station (BS) directly performs NOMA with all users. For the cooperative NOMA, the BS communicates with NOMA users with the aid of an amplify-and-forward (AF) relay, and the direct links between BS and users are existent. To characterize the performance of the proposed networks, new closed-form and asymptotic expressions for the outage probability (OP), ergodic capacity (EC) and energy efficiency (EE) are derived, respectively. Specifically, we also design the relay location optimization algorithms from the perspectives of minimize the asymptotic OP. For non-cooperative NOMA, it is proved that the OP at high signal-to-noise ratios (SNRs) is a function of threshold, distortion noises, estimation errors and fading parameters, which results in 0 diversity order. In addition, high SNR slopes and high SNR power offsets achieved by users are studied. It is shown that there are rate ceilings for the EC at high SNRs due to estimation error and distortion noise, which cause 0 high SNR slopes and ∞ high SNR power offsets. For cooperative NOMA, similar results can be obtained, and it also demonstrates that the outage performance of cooperative NOMA scenario exceeds the non-cooperative NOMA scenario in the high SNR regime.

This paper studies the secrecy energy efficiency (SEE) for MISO power-splitting (PS) SWIPT networks in the presence of multiple passive eavesdroppers (Eves), where the non-linear energy harvesting (EH) model and the dual-layer PS receiver architecture are employed. With only channel distribution information (CDI) of Eves known and the artificial noise (AN) embedded into the transmit signals at the transmitter, a SEE maximization problem is formulated under constraints of the minimal rate and EH requirements of legitimate receivers and the power budget at the transmitter. To tackle the difficulty caused by the fractional objective function and the probability constraints in solving the considered problem, the second-layer PS ratios are firstly optimized by bisection and sum-of-ratios maximization methods, and then the transmit beamforming vectors, the AN covariance matrix and the first-layer PS ratios are jointly optimized by using successive convex approximation (SCA) and Dinkelbach's methods. The proposed solution approach is theoretically proved to converge to a stationary point of the SDR form of the considered problem, which is further shown to be the optimal one. Numerical results show that our proposed design achieves the highest SEE over traditional power minimization and secrecy rate maximization designs. Moreover, when the rate requirement is larger than a threshold or the available power is less than a threshold, traditional power minimization design or secrecy rate maximization design is able to achieve a similar SEE to our proposed design. Besides, the dual-layer PS receiver architecture is able to improve the EH efficiency and system SEE.

In this paper, we investigate a non-orthogonal multiple access (NOMA) assisted multi-antenna two-way relay system, where multi-antenna users apply NOMA to support bidirectional superposition transmission via multiple multi-antenna relays. Specifically, we propose two cooperative strategies, namely multiple-access broadcast NOMA and time division broadcast NOMA. For each of the two cooperative strategies, we devise a joint antenna-and-relay selection scheme to enhance the transmission reliability. Analytical expressions for the outage probability and diversity order are derived to evaluate the system performance achieved by the proposed cooperative strategies with the corresponding joint antenna-and-relay selection schemes. To further reduce the outage probability, we use the derived analytical results as objective functions to optimize the transmit power allocation under both cooperative strategies. Finally, extensive simulations are carried out to validate the accuracy of the derived analytical results. Our simulation results indicate that the proposed strategies significantly outperform existing benchmark strategies in terms of outage probability and diversity order.

In this paper, we consider a downlink wireless communication system with the co-existence of ground user (GU) and mobile aerial user (AU). Existing solutions rely on orthogonal multiple access (OMA) to support these users, however, OMA is unable to provide the best rate and outage performance because its spectral efficiency is limited by the users' channel conditions and rate requirements. Thus, we propose an aerial-ground non-orthogonal multiple access (AG-NOMA) scheme that pairs the GU and AU for data and control links, respectively. Unlike terrestrial non-orthgonal multiple access (NOMA), the key idea of AG-NOMA is to exploit the asymmetric features of the channels and rate demands of the GU and AU in the downlink communication. Based on these opportunities, we investigate the maximum achievable GU rate over a time-varying wireless channel while satisfying the AU Quality-of-Service (QoS) requirement with perfect and partial channel state information (CSI). For perfect CSI, we derive the optimal successive interference cancellation (SIC) policy, power allocation, GU rate, and feasibility conditions in closed-form expressions. For partial CSI, we also derive the suboptimal SIC policy and power allocation in closed-form expressions, and further discussed a tradeoff between the achievable rate and reliability. This tradeoff depends on the system parameters, and thus we have suggested some appropriate parameters based on theoretical support and standard requirements to strike a balance between rate and reliability. Our simulation results show that AG-NOMA scheme with perfect and partial CSI can achieve up to +99% GU rate-improvement as compared to OMA and provide a more sustainable rate-improvement and/or lower outage probability than terrestrial NOMA scheme.

In this paper, a cooperative hybrid visible light communication (VLC)-radio frequency (RF) system with spatially random terminals is considered. Especially, a source node ($S$) with a group of light-emitting diode (LED) lamps transmits information bits to a destination ($D$), which is located out of$S$’s coverage area, via a relay node ($R$).$R$is equipped with a photodetector and an antenna to set up a VLC link between$S$and$R$, and a radio frequency (RF) link between$R$and$D$, respectively. Meanwhile, an eavesdropper ($E$) equipped with a photodetector and an antenna tries to overhear the information delivery over VLC and RF links. Also, diversity receiving scheme is considered at$E$, while the same modulation scheme is considered over both VLC and RF links. Furthermore, decode-and-forward scheme is adopted at$R$to process and forward the received VLC signals. By employing stochastic geometry, we first characterize the probability density function and cumulative distribution function of the received signal-to-noise-ratio over both VLC and RF links, while considering the randomness of the locations of both$R$,$E$, and$D$. Then, the secrecy performance of the target system is studied by deriving the approximated expressions for the secrecy outage probability under various cases. Finally, the proposed analytical models are verified via Monte-Carlo simulations.

In this paper, we propose a novel successive sub-array activation (SSAA) diversity scheme for a massive multiple-input multiple-output (MIMO) system in combination with non-orthogonal multiple access (NOMA). Considering a single-cell multi-cluster downlink scenario, where the base station (BS) sends redundant symbols through multiple transmit sub-arrays to multi-antenna receivers, a low-complexity two-stage beamformer, that is constructed based only on the long-term channel statistical information, is proposed. An in-depth analytical analysis is carried out, in which an exact closed-form expression for the outage probability is derived. A high signal-to-noise ratio (SNR) outage approximation is obtained and the system diversity order is determined. The ergodic sum-rate is also investigated, in which a closed-form solution is evaluated considering a particular case. Numerical and simulation results are provided to validate the analytical analysis and to demonstrate the performance superiority of the proposed SSAA scheme. For example, our results show that the proposed system operating with SSAA outperforms conventional full array massive MIMO setups.

This paper addresses multi-user multi-cluster massive multiple-input-multiple-output (MIMO) systems with non-orthogonal multiple access (NOMA). Assuming the downlink mode, and taking into consideration the impact of imperfect successive interference cancellation (SIC), an in-depth analytical analysis is carried out, in which closed-form expressions for the outage probability and ergodic rates are derived. Subsequently, the power allocation coefficients of users within each sub-group are optimized to maximize fairness. The considered power optimization is simplified to a convex problem, which makes it possible to obtain the optimal solution via Karush-Kuhn-Tucker (KKT) conditions. Based on the achieved solution, we propose an iterative algorithm to provide fairness also among different sub-groups. Simulation results alongside with insightful discussions are provided to investigate the impact of imperfect SIC and demonstrate the fairness superiority of the proposed dynamic power allocation policies. For example, our results show that if the residual error propagation levels are high, the employment of orthogonal multiple access (OMA) is always preferable than NOMA. It is also shown that the proposed power allocation outperforms conventional massive MIMO-NOMA setups operating with fixed power allocation strategies in terms of outage probability.

This paper designs a novel opportunistic adaptive non-orthogonal multiple access (OA-NOMA) strategy, where a base station (BS) employs NOMA to serve a near user (NU)-far user (FU) pair opportunistically scheduled from M NUs and K FUs. In particular, the NOMA transmission to the scheduled NU-FU pair adaptively operates in one of two modes: Direct NOMA mode, in which the BS directly serves the scheduled NU-FU pair with using NOMA; Cooperative NOMA mode, in which the scheduled NU receives the messages intended by both scheduled users from the BS, and then forwards the message intended by the scheduled FU. For the OA-NOMA strategy, a scheduling candidate acquisition method and a probabilistic user pair scheduling scheme are proposed to guarantee the transmission reliability and improve the scheduling fairness, respectively. To evaluate the scheduling fairness, we develop a max-min fairness criterion and show that the OA-NOMA strategy approximately achieves max-min fairness. The reliability of the OA-NOMA strategy is also evaluated in terms of outage probability and diversity order. For the outage probability, we derive an approximate expression and numerically verify its tightness. For the diversity order, we show that the proposed OA-NOMA strategy achieves a diversity order of M.

Non-orthogonal multiple access (NOMA) and mobile edge computing (MEC) have been recognized as promising technologies for the beyond fifth generation networks to achieve significant capacity improvement and delay reduction. In this paper, the technologies of hybrid NOMA and MEC are integrated. In the hybrid NOMA MEC system, multiple users are classified into different groups and each group is allocated a dedicated time slot. In each group, a user first offloads its task by sharing a time slot with another user, and then solely offloads during a time interval. To reduce the delay and save the energy consumption, we consider jointly optimizing the power and time allocation in each group as well as the user grouping. As the main contribution, the optimal power and time allocation is characterized in closed form. In addition, by incorporating the matching algorithm with the optimal power and time allocation, we propose a low complexity method to efficiently optimize user grouping. Simulation results demonstrate that the proposed resource allocation method in the hybrid NOMA MEC systems not only yields better performance than the conventional OMA scheme but also achieves quite close performance as global optimal solution.

Mobile edge computing (MEC) can provide considerable computing capabilities for Internet of Things (IoT) devices, especially for applications with latency sensitive tasks. By applying non-orthogonal multiple access (NOMA) in MEC, multiple users can offload their tasks simultaneously on the same frequency band. In this paper, the minimization problem of task completion time is investigated for the NOMA enabled multi-user MEC networks. We adopt \emph{partial offloading}, in which each user's task can be partitioned, while the formulated problem is quasi-convex. Thus a bisection search (BSS) algorithm is proposed to achieve the minimum task completion time for the multi- user case. To reduce the complexity and evaluate the optimality of the BSS algorithm, we further derive closed- form expressions for the optimal task partition ratio and offloading power for a two-user NOMA-MEC network. Simulations demonstrate the convergence and optimality of the proposed BSS algorithm and the effectiveness of the optimal approach.

In this paper, we investigate energy harvesting capabilities of non-orthogonal multiple access (NOMA) scheme integrated with the conventional time division multiple access (TDMA) scheme, which is referred to as hybrid TDMA-NOMA system. In a such hybrid scheme, users are divided into a number of groups, with the total time allocated for transmission is shared between these groups through multiple time slots. In particular, a time slot is assigned to serve each group, whereas the users in the corresponding group are served based on power-domain NOMA technique. Furthermore, simultaneous wireless power and information transfer technique is utilized to simultaneously harvest energy and decode information at each user. Therefore, each user splits the received signal into two parts, namely, energy harvesting part and information decoding part. In particular, we jointly determine the power allocation and power splitting ratios for all users to minimize the transmit power under minimum rate and minimum energy harvesting requirements at each user. Furthermore, this joint design is a non-convex problem in nature. Hence, we employ successive interference cancellation to overcome these non- convexity issues and determine the design parameters (i.e., the power allocations and the power splitting ratios). In simulation results, we demonstrate the performance of the proposed hybrid TDMA-NOMA design and show that it outperforms the conventional TDMA scheme in terms of transmit power consumption.

In this paper, we consider an unmanned aerial vehicle (UAV) enabled wireless network with a set of ground devices that are randomly distributed in an area and each having a certain amount of data for transmission. The UAV flies over this region from a starting point to a destination. During its flight, the UAV wants to communicate to the ground devices for maximizing the cumulative collected data by optimizing the trajectory of the UAV subject to its flight time constraint. Due to uncertainty in the locations of the ground devices and the communication dynamics, an accurate system model is difficult to acquire and maintain. With the help of stochastic modelling, we present a reinforcement learning based automated trajectory optimization algorithm. By dividing the considered region into small grids with finite state space and action space, we apply the Q-learning based automated trajectory optimization approach for maximizing the cumulative collected data during its flight time. Simulation results demonstrate that the reinforcement learning approach can find an optimal strategy under the flight time constraint.

This paper investigates the performance of multi- cluster multi-user massive multiple-input multiple- output (MIMO) networks with non-orthogonal multiple access (NOMA) and a dual-polarized antenna array. Considering the downlink mode in which a single base station communicates with multiple users, a precoder design is proposed with the aim to maximize the number of user groups that are simultaneously served within a cluster. A closed- form expression for the outage probability is derived, based on which an asymptotic analysis is carried out and the diversity gain is determined. Moreover, the outage sum-rate is also examined. Representative numerical examples are presented along with insightful discussions. Our results show that the proposed dual-polarized MIMO-NOMA design outperforms conventional single-polarized systems, even for high cross-polar interference.

In this paper, task assignment and power allocation are investigated for the the non-orthogonal multiple access (NOMA)-aided mobile edge computing (MEC) system. Based on the different channel conditions and central processing units (CPUs), users can offload computational tasks to the MEC server or process tasks locally. In order to minimize the energy consumption of the proposed NOMA- aided MEC system, the task assignment and power allocation optimization problem is formulated. Based on the insight derived from the delay constraint, the closed-form expressions of task ratios and transmit power are derived. Furthermore, the optimality of the derived closed-form solutions is analyzed, which shows that the optimal task assignment of any user is based on the energy consumption efficiency (ECE) of offloading and local computing. Simulation results indicate that: i) the derived closed-form solutions can significantly reduce the energy consumption of the NOMA-MEC system, and ii) the analysis of the derived closed-form solutions is confirmed.

In this paper, we study a joint energy harvesting (EH) and task offloading (TO) design for an energy- constrained fog computing network, which consists of a mobile terminal and two fog nodes. The energy- constrained terminal employs time switching (TS) protocol to harvest energy from the signals sent by the circuit-powered fog node, and then exploits the harvested energy to perform local computing and offload computing. Our aim is to minimize the product of energy consumption and time delay with the constraints of TS ratio and EH requirements. To determine the optimal solution of the original non-convex problem, we decouple it into three subproblems based on the time delay assumption and then solve these subproblems through our proposed constraints activation algorithm. Furthermore, we also derive the closed form expressions for the optimal TO and TS ratios. Simulation results are presented to illustrate the effectiveness and superior performance of the proposed joint design against other conventional schemes in the literature.

In this paper, we consider a nonorthogonal multiple access (NOMA) assisted mobile edge computing (MEC) system where the power and time are jointly optimized to reduce the energy consumption and delay. In order to achieve a tradeoff between energy consumption and delay, we introduce weighting factors, and the optimization problem is formulated to minimize the weighted sum of energy consumption and delay. In the literature, only two offloading strategies, i. e., orthogonal multiple access (OMA) and pure NOMA, are mainly considered. In this paper, we investigate a third strategy, hybrid NOMA, which contains the strategies of OMA and pure NOMA. As the main contribution, we analytically characterize the optimal resource allocation, i. e., the joint power and time allocation, for two-scheduled-user case. Simulation results show that the proposed resource allocation method in hybrid NOMA systems yields lower energy consumption and delay than the conventional OMA scheme.

Dynamic adaptive video streaming over HTTP (DASH) plays a key role in video transmission over the Internet. The conventional DASH adaptation approaches concentrate on optimizing the overall quality of experience (QoE) for all client sides, neglecting the QoE diversity of different users. In this paper, we formulate the QoE optimization of multi-user preferences as a multi-task deep reinforcement learning problem, in which QoE refers to the metrics of visual quality, fluctuation and rebuffing events. Then, we propose a meta-learning framework for multi-user preferences (MLMP) as a new DASH adaptation approach. Finally, the simulation results show that the proposed approach outperforms state-of-the-art DASH adaptation approaches in satisfying the different users' QoE preferences regarding the three metrics.

Non-orthogonal multiple access (NOMA) is one of the most promising technologies in fifth-generation mobile communication system for its advantages in serving multiuser simultaneously and enhancing spectrum efficiency. In this paper, we investigate the optimization problem of sum-rate maximization for NOMA-based system, and mainly focus on user clustering. Inspired by the correlation features of users, we introduce machine learning in user clustering. We first develop an expectation maximization (EM) based algorithm for fixed user scenario. Then, the dynamic user scenario is considered and an online EM (OLEM) based clustering algorithm is proposed. Simulation results show that the proposed EM-based and OLEM-based algorithms outperform the state-of-the-art algorithms in fixed and dynamic user scenario, respectively.

We study secure communications with an untrusted relay for a cooperative non-orthogonal multiple access (NOMA) system, where a base station (BS) serves a near user (NU) and a far user (FU) by the NOMA principle, and transmission between BS and FU is aided by an untrusted relay. We propose an adaptive jamming scheme to enhance transmission security, in which FU is asked to adaptively emit a jamming signal to confuse the untrusted relay. The transmission rate for jamming is designed to ensure that only NU can decode the jamming signal correctly, and the jamming power is optimized for maximizing the secrecy sum rate. We analyze the security performance of the proposed scheme and derive the ergodic secrecy sum rate and its scaling law. Simulation results are presented to validate the effectiveness of the proposed adaptive jamming scheme.

Recently, power allocation has attracted more and more attention in order to optimize the performance of non-orthogonal multiple access (NOMA) systems. Different from existing works, the power allocation problems are investigated for cooperative NOMA systems with dedicated amplify-and-forward half-duplex relay (NOMA-HDR) and full-duplex relay (NOMA-FDR). From the fairness standpoint, the power allocation problems are formulated to maximize the minimum achievable user rate in the considered systems. The problems for both NOMA-HDR and NOMA-FDR systems with two-user and M-user are addressed. The closed-form power allocation policy of two-user NOMA-HDR system is obtained. Also, the optimal numerical power allocation policies for two-user NOMA-FDR and M-user NOMA-HDR systems are obtained. In addition, the problem for M-user NOMA-FDR systems is solved in noise-limited environment. Simulation results show that the proposed NOMA-HDR or NOMA-FDR scheme with power adaption clearly outperforms the NOMA-HDR or NOMA-FDR scheme with fixed power allocation. Besides, when the residual self-interference channel gain is small, the performance of NOMA-FDR system is better than the NOMA-HDR system.

In fog-radio access networks (F-RANs), the loadings of backhaul is the bottleneck to fully explore the potential of cloud computing capability, which provide abundant computation resources to execute the computation tasks. In this paper, the performance of computation offloading F-RANs is studied to keep a balance between the tradeoff between the costs and the gains of different computation task processing modes. First, we focus on an opportunistic computation offloading strategy in F-RANs, and the computation offloading probability is analyzed based on a stochastic geometry-based model. Second, the computation offloading procedure in F-RANs can be modeled as a Jackson network of queueing system. A closed-form expression of average delay performance is derived, and the global optimal solution of the ratio of computation tasks handled by the cloud computing center is also provided to minimize the average processing delay. Finally, the simulation results are shown to verify the accuracy of analytical results and evaluate the performance gains of hybrid computation offloading in F-RANs.

Non-orthogonal multiple access (NOMA) is a prospective technology for radio resource constrained future mobile networks. However, NOMA users far from base station (BS) tend to be more susceptible to eavesdropping because they are allocated more transmit power. In this paper, we aim to jointly optimize the precoding vectors at BS to ensure the legitimate security in a downlink multiple-input single-output (MISO) NOMA network. In the proposed scheme, we can maximize the sum secrecy rate by joint precoding optimization. Owing to its non-convexity, the problem is converted into a convex one, which is solved by a second-order cone programming based iterative algorithm. Simulation results are presented to demonstrate that the proposed schemes can improve the security performance for MISO NOMA systems effectively.

In this paper, we investigate the uplink transmission in a cellular network from a UAV and ground users to ground base stations (BSs). Specifically, we aim to maximize the sum rate of the uplink from the UAV to ground BSs in a specific idle frequency band as well as from the co-channel users to their associated BSs by optimizing precoding vectors at UAV. To mitigate the interference, we apply successive interference cancellation (SIC) not only to the BSs connected with UAV using non-orthogonal multiple access (NOMA) for transmission, but also to other BSs communicating with ground users in the same band. The precoding optimization problem with constraints on the SIC decoding and the uplink transmission rate is formulated, which is non-convex and intractable. Thus, we introduce auxiliary variables and apply first-order approximations based on Taylor expansion to convert it into a second-order cone programming. An iterative algorithm is proposed with low complexity to calculate the solution to the non-convex precoding optimization problem. Numerical results demonstrate the effectiveness of our proposed scheme.

Resource allocation in fog radio access networks (F- RANs) is a hot topic but with challenges, especially combined with non-orthogonal multiple access (NOMA) technique which is promised to enhance spectral efficiency (SE). In NOMA-based F-RANs, radio subchannels occupied by remote radio heads (RRHs) can be reused by fog access points (F-APs) and power domain NOMA technique is applied for the link from F-APs to fog user equipments (FUEs). In this paper, an energy efficiency (EE) maximization problem consisting of subchannel reuse assignment and NOMA-based power allocation is formulated for NOMA-based F-RANs. To solve it efficiently, the problem is modeled as a Stackelberg game and two game-theoretic algorithms are developed for two sub-problems, respectively. In particular, The subchannel reuse assignment is modeled as a one-to-many matching game and the power allocation is modeled as a non-cooperative game. The low complexity of proposed algorithms make the problem tractable and fast to converge to the Nash equilibrium (NE). Simulation results show that the proposed algorithms achieve the significant performance gains on system EE, users' latency with an accurate and low complexity way compared to other baselines.

Random matrix theory (RMT) has been used to derive the asymptotic capacity of multiple-input-multiple-output (MIMO) channels by approximating the asymptotic eigenvalue distributions (AEDs) of the associated channel matrices. A novel methodology is introduced which enables the computation of the asymptotic capacity for a generalised system in which two relays cooperate to facilitate communication between two remote devices. It is computationally demanding to calculate this capacity using RMT when nodes are equipped with large-scale antenna arrays, and impossible in the case where asymmetry exists between channels within the system. This is because deriving the capacity across the combined channels from the relays to the receiver involves polynomials in large and non-commutative random matrix variables. This paper uses free probability theory (FPT) as an efficient alternative tool for analysis in these circumstances. The method described can be applied with no additional complexity for arbitrarily large antenna arrays. The minimum SNR required to achieve a given asymptotic capacity is computed and the simulation results verify the accuracy of the FPT approach.

In this paper, the distributed edge caching problem in fog radio access networks (F-RANs) is investigated. By considering the unknown spatio-temporal content popularity and user preference, a user request model based on hidden Markov process is proposed to characterize the fluctuant spatio-temporal traffic demands in F-RANs. Then, the Q-learning method based on the reinforcement learning (RL) framework is put forth to seek the optimal caching policy in a distributed manner, which enables fog access points (F-APs) to learn and track the potential dynamic process without extra communications cost. Furthermore, we propose a more efficient Q-learning method with value function approximation (Q-VFA-learning) to reduce complexity and accelerate convergence. Simulation results show that the performance of our proposed method is superior to those of the traditional methods.

Motivated by the move towards the next generation of green communications, we study a power beacon (PB) assisted wireless-powered cooperative communication network (PBWPCCN). A new system model is proposed where a source and a number of relay terminals are not directly connected to the power grid. These terminals, including the source, need to harvests energy from radio frequency (RF) signals radiated from PB and works cooperatively to deliver the information to the target device successfully. The system executes this process in a two-stage relay selection decode-then-forward (2SRS-DF). First, the system selects a group of relay candidates that can successfully decode the received signal from the source. Second, from the first relays group that successfully decodes the source signal, the best relay with the maximum capability to forward the decoded message to the destination is selected. The closed-form expression for the average outage probability and the throughput of the proposed system is derived and presented. We validate the theoretical results by numerical simulations. The impact of position and number of relay terminals along with time allocation parameters are also studied.

This paper studies the application of the unmanned aerial vehicles (UAVs) to a malfunction area. Note that the ground base stations (GBSs) inside the malfunction area are broken, whereas the GBSs outside work well and are distributed according to a homogeneous Poisson point process (HPPP). A user-centric cooperative scheme is proposed to serve the user equipments(UEs) in the malfunction area. Specifically, based on the UEs' connections to the UAV and nearest GBS, the users in the malfunction area can be served by the UAV only, both the UAV and the nearest GBS or the nearest GBS only. The proposed scheme can be tuned by a parameter δ. Analytical framework is developed to obtain the expression for the coverage probability achieved by a UE in the malfunction area, which is verified by computer simulations.

Non-orthogonal multiple access (NOMA) has been developed as a key multi-access technique for 5G. However, secure transmission remains a challenge in NOMA. Especially, the user with weakest channel is most threatened by eavesdropping, due to its highest transmit power. In this paper, we propose a novel scheme to generate artificial jamming at the NOMA base station (BS), aiming at disrupting the potential eavesdropping without affecting the legitimate transmission. In the scheme, the transmit power of artificial jamming is maximized, with its received power at each receiver higher than that of other users. Thus, the jamming signal can be eliminated via successive interference cancellation before others, and the eavesdropping can be disrupted effectively. Due to the non-convexity of the optimization problems, we first convert it to a convex one and then provide an iterative algorithm to solve it. Simulation results are presented to show the effectiveness of the proposed scheme in guaranteeing the security of NOMA networks.

In this paper, we propose two beamforming designs for a multiple-input single-output non-orthogonal multiple access system considering the energy efficiency (EE) fairness between users. In particular, two quantitative fairness-based designs are developed to maintain fairness between the users in terms of achieved EE: max-min energy efficiency (MMEE) and proportional fairness (PF) designs. While the MMEE-based design aims to maximize the minimum EE of the users in the system, the PF-based design aims to seek a good balance between the global energy efficiency of the system and the EE fairness between the users. Detailed simulation results indicate that our proposed designs offer many-fold EE improvements over the existing energy-efficient beamforming designs.

In this paper, we propose a beamforming design that jointly considers two conflicting performance metrics, namely the sum rate and fairness, for a multiple-input single-output non-orthogonal multiple access system. Unlike the conventional rate-aware beamforming designs, the proposed approach has the flexibility to assign different weights to the objectives (i.e., sum rate and fairness) according to the network requirements and the channel conditions. In particular, the proposed design is first formulated as a multi-objective optimization problem, and subsequently mapped to a single objective optimization (SOO) problem by exploiting the weighted sum approach combined with a prior articulation method. As the resulting SOO problem is non-convex, we use the sequential convex approximation technique, which introduces multiple slack variables, to solve the overall problem. Simulation results are provided to demonstrate the performance and the effectiveness of the proposed approach along with detailed comparisons with conventional rate-aware-based beamforming designs.

This paper studies device-to-device (D2D) group association and channel assignment in uplink multi-cell non-orthogonal multiple-access (NOMA) networks. In particular, the goal is to assign D2D groups to cellular user channels at each base-station, while accounting for the interference caused by pairing users with D2D groups. To that end, a multi-objective signal-to-interference-plus-noise ratio (SINR)-maximizing power allocation solution procedure is proposed to determine the optimal power allocation for each (D2D group, user) pair, while meeting quality-of-service (QoS) requirements. After that, the joint D2D group association and channel assignment problem is modeled as a student-project allocation with preferences over (student, project) pairs matching problem. Then, a polynomial-time complexity stable matching algorithm is proposed to pair D2D groups with users, and associate them with base-stations. Simulation results are presented to evaluate the proposed matching algorithm, and compare it to a joint D2D group association, channel assignment and power allocation (J-GA-CA-PA) scheme. The proposed algorithm is shown to efficiently yield comparable SINR-per user and D2D receiver-to the J-GA-CA-PA scheme, while maintaining QoS requirements.

In this study, the authors consider the secrecy communication of one source–destination pair in a wireless multi‐hop relay network, where each node is equipped with multiple antennas. They use the method of interference alignment for secrecy transmission in the presence of an eavesdropper. Firstly, they propose a decode‐and‐forward (DF) relaying protocol and give a new result on the joint probability density function of the first, second, …, k th ( ) largest eigenvalues of the complex Wishart matrices , where is an matrix whose elements are independent identically distributed complex Gaussian variables with zero mean and unit variance. They then utilise this result to characterise the legitimate outage probability and the diversity order of the proposed DF protocol. The case where the relay works in the amplify‐and‐forward (AF) mode is considered at last, and the diversity order of the proposed AF protocol is given.

To achieve low-latency and high-reliability (LLHR) for the vehicle-to-everything (V2X) services, the Long Term Evolution (LTE)-based solution has been considered as a promising technology. Since the existing LTE networks are based on the orthogonal multiple access (OMA), the limited spectrum resources have not been fully and efficiently utilized, so that severe data congestion and low access efficiency cannot be avoided in dense networks. Non-OMA (NOMA) provides a new solution for 5G V2X services to mitigate traffic congestion and reduce latency. Different from existing works, we propose two relay-assisted NOMA transmission schemes for 5G V2X communications, i.e., half-duplex relay-assisted NOMA (HDR-NOMA) broadcasting/multicasting and full-duplex relay-assisted NOMA (FDR-NOMA) broadcasting/multicasting, and investigate the optimal power allocation problems for them. To improve the quality of service (QoS) for the users with the poor channel conditions and to guarantee the fairness, the power allocation problems are formulated to maximize the minimum achievable rate for all users. Even though both of the formulated problems are neither concave nor convex, it is shown that the considered problems are quasi-concave. Hence, a bisection-based power allocation algorithm is proposed to obtain the optimal solutions to the problems. Numerical results demonstrate that the proposed schemes outperform the scheme with fixed power allocation obviously and achieve a significant performance improvement with respect to a suboptimal fractional transmit power allocation (FTPA) method and the optimized time division multiple access (TDMA) scheme. Besides, compared with HDR-NOMA, better performance can be achieved by FDR-NOMA scheme when the self-interference is sufficiently suppressed.

Nonorthogonal multiple access (NOMA) and device-to-device (D2D) are two promising technologies that have great potential in improving user connectivity. In this paper, we incorporate NOMA into the D2D-capable cellular networks and propose a new NOMA-aided D2D access scheme. In the proposed scheme, the D2D users (DUEs) can operate in four spectrum-sharing modes, which are the extension of the traditional underlay mode. To fully exploit the advantages of the NOMA-and-D2D integrated framework, we formulate a connectivity-maximization problem by jointly considering user pairing, mode selection, and power control under the constraints of the decoding thresholds of cellular users and DUEs. Based on the graph theory, we devise an efficient algorithm with polynomial complexity to solve the formulated problem optimally. We first analytically obtain the optimal transmission power and spectrum-sharing mode for every possible user pair through a graphical method. Based on the power control and mode selection policies, we transform the user pairing problem into a min-cost max-flow problem which can be tackled by the Ford-Fulkerson algorithm. Finally, simulation results indicate that the NOMA-aided D2D access scheme outperforms the traditional underlay mode, and the proposed algorithm yields a large performance gain in comparison with other schemes in terms of user connectivity and power consumption.

This paper considers an MISO simultaneous wireless information and power transfer (SWIPT) system, where one transmitter serves multiple authorized receivers in the presence of several potential eavesdroppers (idle receivers). To prevent the information interception by eavesdroppers, artificial noise (AN) is embedded into the transmit signals. The non-linear energy harvesting (EH) model is adopted and a novel power-splitting (PS) EH receiver architecture is proposed. Stochastic uncertainty channel model (SUM) is considered for the idle receivers due to outdated channel feedback. A global energy efficiency (GEE) maximization problem is formulated by jointly optimizing the transmit beamforming vectors, the AN covariance matrix, and the PS ratios, under the minimal rate and secure transmission constraints of authorized receivers, the EH requirement constraints of idle receivers, and the total available power constraint at the transmitter. Since the problem is non-convex with no known solution, it is solved based on the following solution framework. Firstly, the PS ratios are optimized by using the bisection method and successive convex approximation (SCA), and then, the transmit beamforming vectors and the AN covariance matrix are jointly optimized by using a Dinkelbach's Algorithm based method, where SCA is applied to solve its inner subproblem. It is theoretically proved that by involving AN, the system GEE can be improved. Numerous results show that system GEE first increases and then keeps unchanged with the increment of the total available power, but it first keeps unchanged and then decreases with the increment of the minimal rate requirement. It is also observed that compared with traditional EH receiver architecture and linear EH model, our proposed PS EH receiver architecture is able to achieve higher GEE and avoid false output power at idle receivers.

Simultaneous wireless information and power transfer (SWIPT) technique offers a potential solution to ease the contradiction between high data rate and long standby time in the fifth generation (5G) mobile communication systems. In this paper, we focus on the SWIPT network design and optimization with 5G new frequencies. To design an efficient SWIPT network, we first investigate the propagation properties of 5G low-frequency (LF) and high-frequency (HF) channels. Specifically, a measurement campaign focusing on 3.5 GHz and 28 GHz is conducted in both outdoor and outdoor-to-indoor scenarios. Motivated by the measurement results, we design a dual-band SWIPT network, where the HF band is used for short-distance information delivery, while the LF band is used for short-distance energy transfer and long-distance information delivery. The designed network has a win-win architecture which can enhance the throughput of cell-edge users and improve the energy-harvesting efficiency of cell-center users. To further boost the network performance, we devise a joint power-and-channel allocation algorithm, which has the advantages of low complexity and fast convergence. Finally, simulation results demonstrate that the designed dual-band network outperforms the conventional single-band network in terms of energy-harvesting efficiency and user fairness, and the proposed algorithm can further upgrade the network performance significantly.

When considering the future generation wireless networks, non-orthogonal multiple access (NOMA) represents a viable multiple access technique for improving the spectral efficiency. The basic performance of the NOMA is often enhanced using downlink beamforming and power allocation techniques. Although downlink beamforming has been previously studied with different performance criteria, such as sum-rate and max-min rate, it has not been studied in the multiuser, multiple-input single-output (MISO) case, particularly with the energy efficiency criteria. In this paper, we investigate the design of an energy efficient beamforming technique for downlink transmission in the context of a multiuser MISO-NOMA system. In particular, this beamforming design is formulated as a global energy efficiency (GEE) maximization problem with minimum user rate requirements and transmit power constraints. By using the sequential convex approximation technique and the Dinkelbach's algorithm to handle the non-convex nature of the GEE-Max problem, we propose two novel algorithms for solving the downlink beamforming problem for the MISO-NOMA system. Our evaluation of the proposed algorithms shows that they offer similar optimal designs and are effective in offering substantial energy efficiencies compared with the designs based on conventional methods.

Non-orthogonal multiple access (NOMA) has been envisioned as a promising multiple access technique for 5G and beyond wireless networks due to its significant enhancement of spectral efficiency. In this paper, we investigate a robust energy efficiency design for multi-user multiple-input single-output (MISO) NOMA systems, where the imperfect channel state information is available at the base station (BS). A clustering algorithm is applied to group the users into different clusters, and then, the NOMA technique is employed to share the available resources fairly among the users in each cluster. To remove the interference between clusters, two different types of zero-forcing (ZF) designs, namely, hybrid-ZF and full-ZF, are employed at the BS. The full-ZF scheme completely removes the interference leakage at the cost of more number of antennas, and the hybrid-ZF scheme partially mitigates the interference leakage. To solve the problem, Dinkelbach’s algorithm is employed to convert the non-linear fractional programming problem into a simple subtractive form. Finally, simulation results reveal that hybrid-ZF outperforms the full-ZF scheme with a few clusters, while full-ZF shows a better performance with higher number of clusters. Numerical results confirm that our proposed robust scheme outperforms the non-robust scheme in terms of the rate-satisfaction ratio at each user.

This paper studies joint device-to-device (D2D) group association and channel assignment in uplink multi-cell non-orthogonal multiple-access (NOMA) networks. Particularly, the goal is to assign D2D groups to cellular user channels at each base-station, while accounting for negative network externality due to the interference caused by pairing a user with a D2D group. To that end, a multi-objective signal-to-interference-plus-noise ratio (SINR)-maximizing power allocation solution procedure is proposed to determine the optimal power allocation for each (D2D group, user) pair, while meeting quality-of-service (QoS) requirements. After that, the joint D2D group association and channel assignment problem is modeled as a student-project allocation with preferences over (student, project) pairs matching problem. More specifically, two polynomial-time complexity stable matching algorithms are proposed to pair D2D groups with users, and associate them with base-stations. Simulation results are presented to evaluate the proposed matching algorithms when combined with the devised solution procedure, and compare them to a joint D2D group association, channel assignment and power allocation (J-GA-CA-PA) scheme. More importantly, the proposed algorithms are shown to efficiently yield comparable SINR-per user and D2D receiver-to the J-GA-CA-PA scheme, while maintaining QoS requirements.

This paper investigates the performance of non-orthogonal multiple access (NOMA) systems over time-correlated Rayleigh fading channels, where the users have heterogeneous quality of service requirements, e.g., a latency-critical user with a low target rate and a delay-tolerant user with a large target rate. In order to meet the different requirements of the users, two partial hybrid automatic repeat request (HARQ) schemes, including partial HARQ with chase combining (HARQ-CC) and HARQ with incremental redundancy (HARQ-IR), are proposed. The closed-form expressions of outage probabilities for NOMA with and without re-transmission are derived. With the developed outage probabilities, a condition on the superiority of NOMA to orthogonal multiple access (OMA) is obtained. In particular, the condition is characterized by the transmit powers for NOMA without re-transmission and is obtained by using the bisection method in the case with re-transmission. To further improve the performance of the HARQ enabled NOMA schemes, we consider an average transmit power minimization problem by optimizing the transmit power among different transmission rounds with outage constraints. However, due to the complexity of the developed outage probabilities, the formulated problem is non-convex and challenging to solve. Then we approximate the original problem by deriving the upper-bound approximations of the outage probabilities and solve it by using the geometric programming method. Simulation results demonstrate the accuracy of the developed analytical results. It is shown that the performance of NOMA is superior to OMA, only when the obtained condition is satisfied. HARQ-CC and HARQ-IR can enhance the outage performance of NOMA over time-correlated fading channels and the HARQ-IR has excellent performance in terms of energy efficiency.

This paper considers the co-existence of two important communication techniques, non-orthogonal multiple access (NOMA) and mobile edge computing (MEC). Both NOMA uplink and downlink transmissions are applied to MEC, and analytical results are developed to demonstrate that the use of NOMA can efficiently reduce the latency and energy consumption of MEC offloading. In addition, various asymptotic studies are carried out to reveal the impact of the users' channel conditions and transmit powers on the application of NOMA to MEC are quite different from those in conventional NOMA scenarios. Computer simulation results are also provided to facilitate the performance evaluation of NOMA-MEC and also verify the accuracy of the developed analytical results.

Grant-free transmission is an important feature to be supported by future wireless networks since it reduces the signaling overhead caused by conventional grant-based schemes. However, for grant-free transmission, the number of users admitted to the same channel is not capped, which can lead to a failure of multi-user detection. This paper proposes non-orthogonal multiple-access (NOMA) assisted semi-grant-free (SGF) transmission, which is a compromise between grant-free and grant-based schemes. In particular, instead of reserving channels either for grant-based users or grant-free users, the focus here is on an SGF communication scenario, where users are admitted to the same channel via a combination of grant-based and grant-free protocols. As a result, a channel reserved by a grant-based user can be shared by grant-free users, which improves both connectivity and spectral efficiency. Two NOMA assisted SGF contention control mechanisms are developed to ensure that, with a small amount of signaling overhead, the number of admitted grant-free users is carefully controlled and the interference from the grant-free users to the grant-based users is effectively suppressed. Analytical results are provided to demonstrate that the two proposed SGF mechanisms employing different successive interference cancelation decoding orders are applicable to different practical network scenarios.

This paper considers a challenging communication scenario, in which users have heterogenous mobility profiles, e.g., some users are moving at high speeds and some users are static. A new non-orthogonal multiple-access (NOMA) transmission protocol that incorporates orthogonal time frequency space (OTFS) modulation is proposed. Thereby, users with different mobility profiles are grouped together for the implementation of NOMA. The proposed OTFS-NOMA protocol is shown to be applicable to both uplink and downlink transmission, where sophisticated transmit and receive strategies are developed to remove inter-symbol interference and harvest both multi-path and multi-user diversity. Analytical results demonstrate that both the high-mobility and the low-mobility users benefit from the application of OTFS-NOMA. In particular, the use of NOMA allows the spreading of the high-mobility users’ signals over a large amount of time-frequency resources, which enhances the OTFS resolution and improves the detection reliability. In addition, OTFS-NOMA ensures that low-mobility users have access to bandwidth resources which in conventional OTFS-orthogonal multiple access (OTFS-OMA) would be solely occupied by the high-mobility users. Thus, OTFS-NOMA improves the spectral efficiency and reduces latency.

Multi-carrier based non-orthogonal multiple access (NOMA) is an effective method to meet the ever-increasing demands of both user throughput and energy efficiency by multiplexing multiple users on the same carrier. Since interference from users with a poorer channel gain can be canceled at a user with a strong channel gain by successive interference cancellation, NOMA can enhance the system performance. To improve the downlink system performance, it is crucial to appropriately determine users scheduled on each carrier and power allocation at the base station. However, the existing works are generally either heuristic or local optimal due to the mixed optimization problem. In this paper, we focus on the global optimal solutions to maximize user throughput and energy efficiency in NOMA, respectively. In particular, we first formulate the mixed integer optimization problem which are intractable to be solved. Fortunately, by the provided analytical results, the optimization models can be largely simplified. Then, we propose the architectures of joint user scheduling and power allocation in NOMA, as well as the corresponding optimal algorithms. Simulation results demonstrate that our proposed algorithms indeed outperform existing works in terms of the user throughput and energy efficiency, respectively.

Power domain non-orthogonal multiple access (NOMA), with the ability to serve multiple users within one resource block, is one of the most promising technologies for the fifth generation. In this paper, we study the downlink millimeter wave (mmWave) NOMA-based system, where the base station sends messages to multiple clusters and serves multiple users simultaneously, and sum-rate maximization problem is investigated. Since users are multiplexed on one resource block, user clustering is important for NOMA and has a great influence on sum-rate optimization problem. Inspired by correlation features of users' spatial distributions in mmWave NOMA-based system, we introduce unsupervised learning method into user clustering. We first develop an Expectation Maximization (EM)-based algorithm in fixed user scenario. Then, the dynamic user scenario is introduced, which includes user reduction, increment and movement situations. After that, an online EM-based clustering algorithm is proposed to fast update user distribution parameters with lower computational complexity compared to the conventional complete re-clustering methods. Simulation results show that the proposed EM-based algorithm can improve the performance of NOMA-based system in fixed user scenario. In addition, the proposed online EM-based algorithm can achieve similar performance as the complete EM-based algorithm with less computational complexity in dynamic user scenario.

A promising application of unmanned aerial vehicles (UAVs) to the future communication networks is to address emergency communications. This paper considers such a scenario where a UAV is employed to a malfunction area (modeled as a circular disc) in which all ground base stations (BSs) break down. The ground BSs outside the malfunction area are modelled as a homogeneous Poisson point process (HPPP). Particularly, a user-centric cooperative scheme is proposed to serve the UEs in the malfunction area. According to the user equipment's (UE's) connections to the UAV and the nearest ground BS, the malfunction area is divided into three regions, namely the UAV region, the cooperation region and the nearest ground BS region, in which the UEs are served by the UAV only, both the UAV and the nearest ground BS, and the nearest ground BS, respectively. The region size of each type can be adjusted by a cooperation parameter $\delta$. Through rigorous derivations, an expression for the coverage probability achieved by the UE in the malfunction area is obtained. In order to provide a fair comparison, the normalized spectral efficiency (NSE) which is defined by taking both system throughput and the number of serving BSs into consideration, is used as a criterion for the performance evaluation. Numerical results are presented to verify the accuracy of the analytical results and also to demonstrate the superior performance of the proposed scheme.

To improve the system throughput, this paper proposes a network non-orthogonal multiple access (N-NOMA) technique for the uplink coordinated multi-point transmission (CoMP). In the considered scenario, multiple base stations collaborate with each other to serve a single user, referred to as the CoMP user, which is the same as for conventional CoMP. However, unlike conventional CoMP, each base station in N-NOMA opportunistically serves an extra user, referred to as the NOMA user, while serving the CoMP user at the same bandwidth. The CoMP user is typically located far from the base stations, whereas users close to the base stations are scheduled as NOMA users. Hence, the channel conditions of the two kinds of users are very distinctive, which facilitates the implementation of NOMA. Compared to the conventional orthogonal multiple access-based CoMP scheme, where multiple base stations serve a single CoMP user only, the proposed N-NOMA scheme can support larger connectivity by serving the extra NOMA users, and improve the spectral efficiency by avoiding the CoMP user solely occupying the spectrum. A stochastic geometry approach is applied to model the considered N-NOMA scenario as a Poisson cluster process, based on which insightful closed-form or quasi closed-form analytical expressions for outage probabilities and ergodic rates are obtained. Numerical results are presented to show the accuracy of the analytical results and also demonstrate the superior performance of the proposed N-NOMA scheme.

This paper studies a multiuser mobile edge computing (MEC) system in which one base station (BS) serves multiple users with intensive computation tasks. We exploit the multi-antenna non-orthogonal multiple access (NOMA) technique for multiuser computation offloading, such that different users can simultaneously offload their computation tasks to the multi-antenna BS over the same time/frequency resources, and the BS can employ successive interference cancelation (SIC) to efficiently decode all users' offloaded tasks for remote execution. In particular, we pursue energy-efficient MEC designs by considering two cases with partial and binary offloading, respectively. We aim to minimize the weighted sum-energy consumption at all users subject to their computation latency constraints, by jointly optimizing the communication and computation resource allocation as well as the BS's decoding order for SIC. For the case with partial offloading, the weighted sum-energy minimization is a convex optimization problem, for which an efficient algorithm based on the Lagrange duality method is presented to obtain the globally optimal solution. For the case with binary offloading, the weighted sum-energy minimization corresponds to a mixed Boolean convex optimization problem that is generally more difficult to be solved. We first use the branch-and-bound (BnB) method to obtain the globally optimal solution and then develop two low-complexity algorithms based on the greedy method and the convex relaxation, respectively, to find suboptimal solutions with high quality in practice. Via numerical results, it is shown that the proposed NOMA-based computation offloading design significantly improves the energy efficiency of the multiuser MEC system as compared to other benchmark schemes. It is also shown that for the case with binary offloading, the proposed greedy method performs close to the optimal BnB-based solution, and the convex relaxation-based solution achieves a suboptimal performance but with lower implementation complexity.

A novel cooperative non-orthogonal multiple access (NOMA) strategy is proposed, where a full-duplex cell-center user acts as a friendly relay to help a cell-edge user. An advanced energy harvesting technology based on simultaneous wireless information and power transfer (SWIPT) is used at the cell-center user to harvest energy used at the cooperative stage. We propose a joint design to optimize the power splitting (PS) ratio and the beamforming vectors. The proposed design aims to maximize energy efficiency (EE) of the system while guaranteeing the minimum required target rate of the cell-edge user and the successful decoding rate at the cell-center user. To make the problem tractable, we use Dinkelbachs method to address the fractional functions and the semidefinite relaxation (SDR) technique to deal with the rank constraint. Then, an iterative algorithm based on successive convex approximation (SCA) is proposed to finally solve the reformulated problem. In order to rich the application of the proposed power allocation algorithm, we extend the proposed strategy to an imperfect channel state information (CSI) mode. S-Procedure is introduced to approximate the channel uncertainties. Numerical results reveal that our proposed iterative algorithms have a good convergence rate. In addition, the proposed strategy offers a significant increase in energy efficiency compared to the existing strategies, especially at the low power region.

Radio frequency (RF) signals can be relied upon for conventional wireless information transfer (WIT) and for challenging wireless power transfer (WPT), which triggers the significant research interest in the topic of simultaneous wireless information and power transfer (SWIPT). By further exploiting the advanced non-orthogonal-multiple-access (NOMA) technique, we are capable of improving the spectrum efficiency of the resource-limited SWIPT system. In our SWIPT system, a hybrid access point (H-AP) superimposes the modulated symbols destined to multiple WIT users by exploiting the power-domain NOMA, while WPT users are capable of harvesting the energy carried by the superposition symbols. In order to maximize the amount of energy transferred to the WPT users, we propose a joint design of the energy interleaver and the constellation rotation-based modulator in the symbol-block level by constructively superimposing the symbols destined to the WIT users in the power domain. Furthermore, a transmit power allocation scheme is proposed to guarantee the symbol-error-ratio (SER) of all the WIT users. By considering the sensitivity of practical energy harvesters, simulation results demonstrate that our scheme is capable of substantially increasing the WPT performance without any remarkable degradation of the WIT performance.

The explosive data traffic and connections in 5G networks require the use of non-orthogonal multiple access (NOMA) to accommodate more users. Unmanned aerial vehicle (UAV) can be exploited with NOMA to improve the situation further. In this paper, we propose a UAV-assisted NOMA network, in which the UAV and base station (BS) cooperate with each other to serve ground users simultaneously. The sum rate is maximized by jointly optimizing the UAV trajectory and the NOMA precoding. To solve the optimization, we decompose it into two steps. First, the sum rate of the UAV-served users is maximized via alternate user scheduling and UAV trajectory with its interference to the BS-served users below a threshold. Then, the optimal NOMA precoding vectors are obtained using two schemes with different constraints. The first scheme intends to cancel the interference from the BS to the UAV-served user, while the second one restricts the interference to a given threshold. In both schemes, the non-convex optimization problems are converted into tractable ones. An iterative algorithm is designed. Numerical results are provided to evaluate the effectiveness of the proposed algorithms for the hybrid NOMA and UAV network.

Non-orthogonal multiple access (NOMA) has been developed as a key multi-access technique for 5G. However, secure transmission remains a challenge in NOMA. Especially, the user with weakest channel is most threatened by eavesdropping, due to its highest transmit power. Two schemes are proposed to generate artificial jamming at the NOMA base station (BS), aiming at disrupting the potential eavesdropping without affecting the legitimate transmission. In the first scheme, the transmit power of artificial jamming is maximized, with its received power at each receiver higher than that of other users. Thus, the jamming signal can be eliminated via successive interference cancellation before others. When the transmit power of the BS is inadequate, the transmit jamming power is maximized with the jamming signal zero-forced at each receiver. Thus, the legitimate transmission is not affected by the jamming, and the eavesdropping can be disrupted effectively. Due to the non-convexity of these two optimization problems, we first convert them to convex ones and, then, provide an iterative algorithm to solve them. Simulation results are presented to show the effectiveness of the proposed schemes in guaranteeing the security of NOMA networks.

In this paper, a joint transmitter and receiver design for pattern division multiple access (PDMA) is proposed. At the transmitter, pattern mapping utilizes power allocation to improve the overall sum rate, and beam allocation to enhance the access connectivity. At the receiver, hybrid detection utilizes a spatial filter to suppress the inter-beam interference caused by beam-domain multiplexing, and successive interference cancellation to remove the intra-beam interference caused by power-domain multiplexing. Furthermore, we propose a PDMA joint design approach to optimize pattern mapping based on both the power domain and beam domain. The optimization of power allocation is achieved by maximizing the overall sum rate, and the corresponding optimization problem is shown to be convex theoretically. The optimization of beam allocation is achieved by minimizing the maximum of the inner product of any two beam allocation vectors, and an effective dimension reduction method is proposed through the analysis of pattern structure and proper mathematical manipulations. Simulation results show that the proposed PDMA approach outperforms the orthogonal multiple access and power-domain non-orthogonal multiple access approaches even without any optimization of pattern mapping, and the optimization of beam allocation yields a significant performance improvement than the optimization of power allocation.

Non-orthogonal multiple access (NOMA) has been proposed as a promising multiple access approach for 5G mobile systems because of its superior spectrum efficiency. However, the privacy between the NOMA users may be compromised due to the transmission of a superposition of all users' signals to successive interference cancellation (SIC) receivers. In this paper, we propose two schemes based on beamforming optimization for NOMA that can enhance the security of a specific private user while guaranteeing the other users' quality of service (QoS). Specifically, in the first scheme, when the transmit antennas are inadequate, we intend to maximize the secrecy rate of the private user, under the constraint that the other users' QoS is satisfied. In the second scheme, the private user's signal is zero-forced at the other users when redundant antennas are available. In this case, the transmission rate of the private user is also maximized while satisfying the QoS of the other users. Due to the non-convexity of optimization in these two schemes, we first convert them into convex forms, and then, an iterative algorithm based on the Concave-Convex Procedure is proposed to obtain their solutions. The extensive simulation results are presented to evaluate the effectiveness of the proposed schemes.

This paper considers a multiple-input multipleoutput (MIMO) downlink communication scenario with one base station and two users, where each user is equipped with m antennas and the base station is equipped with n antennas. To efficiently exploit the spectrum resources, we propose a transmission protocol which combines generalized singular value decomposition (GSVD) and non-orthogonal multiple access (NOMA). The expected data rates achieved by the two users are adopted as performance metrics for the evaluation of the proposed GSVD-NOMA scheme. In particular, we first characterize the limiting distribution of the squared generalized singular values of the two users' channel matrices for the asymptotic case, where the numbers of transmit and receive antennas approach infinity. Then, we calculate the expected normalized individual rates of the users in the considered asymptotic regime. Furthermore, we extend the proposed GSVD-NOMA scheme to the general MIMO downlink communication scenario with more than two users. To this end, we propose a hybrid multiple access approach, where the base station divides the users into different groups, the proposed GSVD-NOMA scheme is implemented within each group, and different groups are allocated orthogonal bandwidth resources. Finally, numerical results are provided to validate the effectiveness of the proposed GSVD-NOMA protocol and the accuracy of the developed analytical results.

The fifth-generation (5G) air interface, namely, dynamic multiple access (MA) based on multiuser superposition transmission (MUST) and orthogonal MA (OMA), may require a complicated scheduling and heavy signaling overhead. To address these challenges, we propose a unified MA scheme for future cellular networks, which we refer to as structured MUST (S-MUST). In S-MUST, we apply complex power allocation coefficients (CPACs) over multiuser legacy constellations to generate a composite constellation. In particular, the in-phase (I) and quadrature (Q) components of the legacy constellation of each user are separately multiplied by those of the CPACs. As such, the CPACs offer an extra degree of freedom for multiplexing users and guarantee fairness in symmetric broadcast channels. This new paradigm of superposition coding allows us to design IQ separation at the user side, which significantly reduces the decoding complexity without degrading performance. Hence, it supports low-complexity frequency-selective scheduling that does not entail dynamical switching between MUST and OMA. We further propose to quantize the CPACs into complex numbers where I and Q components of each quantized coefficient are primes, facilitating parallel interference cancellation at each user via modulo operations; last but not least, we generalize the design of S-MUST to exploit the capabilities of multiantenna base stations. The proposed S-MUST exhibits an improved user fairness with respect to conventional MUST (134% spectral efficiency enhancement) and a lower system complexity compared with dynamically alternating MUST and OMA.

We consider downlink non-orthogonal multiple access transmission where an access point communicates with a set of near and far users via a full-duplex multiple antenna relay. To deal with the inter-user interference at the near user and self-interference at the relay, we propose the optimum and suboptimal beamforming schemes. In addition, we consider two different user selection criteria, namely: 1) random near user and random far user (RNRF) selection and 2) nearest near user and nearest far user (NNNF) selection, and we derive the outage probabilities of the near and far users. Our findings reveal that as compared to half-duplex operation, full-duplex relaying can reduce the outage probability of the near users up to 63% in the case of NNNF user selection. With suboptimal beamforming schemes, the NNNF user selection shows a superior performance as compared to the RNRF user selection for all choices of transmit power, while with the optimum beamforming, the performance of the RNRF user selection converges to the NNNF user selection at high transmit power. The simulation results are provided to confirm the accuracy of the developed analytical results and facilitate a better performance comparison.

This paper aims to design and evaluate the performance of multi-cluster multi-user dual-polarized massive multiple-input multiple-output (MIMO) systems with non-orthogonal multiple access (NOMA). Assuming the downlink mode in which a single base station communicates with multiple users, with all terminals being equipped with multiple co-located dual-polarized antennas, two precoder designs are proposed: (i) the first one aims to maximize the number of user groups that are simultaneously served within a cluster; and (ii) the second approach aims to provide further improvements compared to the first one by exploring polarization diversity. Closed-form expressions for the outage probability are derived for both approaches, based on which the respective asymptotic studies are carried out and the diversity gains are determined. The ergodic sum-rates are also derived. Representative numerical examples are presented along with insightful discussions. For instance, our results show that the proposed dual-polarized MIMO-NOMA designs outperform conventional single-polarized systems, even for high cross-polar interference. Simulation results are plotted to corroborate the analytical framework and analysis.

In this paper, we investigate the tradeoff between security and throughput and between security and queuing delay in wiretap time-division multiple access (TDMA) networks. We derive a simple relationship, characterized by a single key system parameter, between the stable-throughput region, where there are no perfect secrecy constraints on the data transmissions, and the secure stable-throughput region, where there are perfect secrecy constraints. We quantify the impact of the perfect secrecy constraints on the network's average queuing delay and propose a novel cross-layer security scheme for delay-limited applications. We establish an insightful link between computational security (i.e., upper-layer security implemented through cryptographic schemes) and physical-layer (information-theoretically proved) security. For the two-user case, we derive a closed-form expression for the network's minimum average queuing delay under the proposed security scheme and provide a relationship between the network's minimum queuing delay under perfect secrecy constraints and computational-only secrecy constraints. Moreover, we investigate the impact of cooperative jamming on achieving perfect secrecy, minimum network's queuing delay, and maximum throughput. We verify our theoretical findings through simulations.

In this paper, we investigate a full duplex (FD) multi-user non-orthogonal multiple access (NoMA) communication system based on the optimization of received signal-to-interference-plus-noise ratio (SINR) per unit power. Since the communication system operates in the FD mode, co-channel interference (CCI) and self-interference (SI) dominate the system's performance. Accordingly, to combat the CCI, we adopt a game-theoretic approach and propose users' clustering algorithms and to suppress the SI, we formulate an optimization problem to maximize the power-normalized SINR (PN-SINR). While the user clustering optimization problem is constrained by: 1) the successive interference cancellation (SIC) constraint and 2) two binary constraints for the allocations of uplink (UL) and downlink (DL) users, the PN-SINR problem is constrained by: 1) total transmit power budget at the base station and UL users; 2) the fundamental condition for the implementation of successive interference cancellation in the NoMA; and 3) the minimum fairness condition for the UL users. The original PN-SINR problem is non-convex and hence is converted into an equivalent subtractive-form problem, after which we propose an iterative algorithm to find the optimal power allocation policy. Properties of all the proposed algorithms are thoroughly investigated and the numerical results are provided. Based on the channel conditions and suppression level of SI and CCI, the superiority of the proposed FD-NoMA system over half-duplex NoMA and FD orthogonal multiple access systems is verified.

In this paper, the joint design of user clustering and power allocation is investigated in a downlink non-orthogonal multiple access-based millimeter wave (mm-wave-NOMA) system. To reduce the system overhead, hybrid precoding techniques are adopted at the base station by using the channel state information of cluster heads (CHs) only. In order to maximize the sum rate of the system, Stackelberg game-based optimization problems are formulated for two cases with different quality of some targets: Case 1 focuses on improving the data rates of CHs; and Case 2 aims to increase the rates of cluster members when the CHs' data rates are caped. With the aid of coalitional game theory, a low complexity algorithm is proposed to dynamically allocate users into different clusters. Then, the optimal power allocation coefficients of the users in each cluster are obtained by the derived closed-form expressions. The properties of the proposed joint algorithms are analyzed in terms of Stackelberg equilibrium, the complexity, the convergence and the stability. The simulation results demonstrate that: 1) the proposed algorithms can significantly improve the sum rate and reduce the outage probability of the mm-wave-NOMA system and 2) the application of NOMA in mm-wave systems is capable of achieving promising gains over conventional orthogonal multiple access-based frameworks in both cases.

In this paper, user association and power allocation are investigated in a non-orthogonal multiple access (NOMA)-based multi-cell network. In order to perform successive interference cancellation (SIC) techniques for removing the intra-base station (BS) interference, the optimal decoding order is derived for all users associated with the same BS. In an effort to improve the system, a sum rate maximization problem is formulated by jointly designing user association and power allocation. Two game theory based algorithms are proposed to obtain the stable user structure by dividing users into different BSs' clusters, where the sub-optimal and global optimal solutions can be achieved. The properties of the proposed algorithms, including complexity, convergence, stability and optimality, are analyzed. Based on the quality-of-service (QoS) constraint, the closed-from solutions for power allocation are derived, and thus the expressions for the sum rate of all users in each cluster is obtained. Moreover, the case that the QoS threshold cannot be achieved by all users in each cluster is considered. Simulation results demonstrate that: i) the proposed user association algorithms and the closed-form solutions for power allocation can significantly enhance the sum rate and outage probability; and ii) the proposed NOMA-based system is capable of achieving promising gains over the conventional orthogonal multiple access (OMA)-based framework in the multi-cell scenario.

In applications of the Internet of Things (IoT), the use of short packets is expected to meet the stringent latency requirement in ultra-reliable low-latency communications; however, the incurred security issues and the impact of finite blocklength coding on the physical-layer security are not well understood. This paper investigates the performance of secure short-packet communications in a mission-critical IoT system with an external multi-antenna eavesdropper. An analytical framework is proposed to approximate the average achievable secrecy throughput of the system with finite blocklength coding. To gain more insight, a simple case with a single-antenna access point (AP) is considered first, in which the secrecy throughput is approximated in a closed form. Based on that result, the optimal blocklengths to maximize the secrecy throughput with and without the reliability and latency constraints, respectively, are derived. For the case with a multi-antenna AP, following the proposed analytical framework, closed-form approximations for the secrecy throughput are obtained under both beamforming and artificial-noise-aided transmission schemes. The numerical results verify the accuracy of the proposed approximations and illustrate the impact of the system parameters on the tradeoff between transmission latency and reliability under a secrecy constraint.

We investigate the outage performance of cooperative non-orthogonal multiple access (NOMA) networks with transceiver hardware impairments, where the estimated channel state information and α - μ fading channels are considered. Closed-form expressions for the outage probability of cooperative NOMA networks are derived for two representative scenarios. The first scenario is the base station (BS) directly communicates with NOMA users. The second scenario is BS communicates with NOMA users via the AF relaying. The diversity orders are presented for the two scenarios. It reveals that there is an error floor for the outage probability due to the distortion noise and estimation error.

Recently, visible light communication (VLC) networks have emerged as a possible alternative for data access, primarily indoors. The very high data rates, low implementation cost and free from radio frequency (RF) interference property make them particularly attractive for the next generation of indoor networking. Furthermore, non-orthogonal multiple access (NOMA) is a very promising candidate technique for the next generation of wireless networks, mainly due to its increased spectrum efficiency, compared to orthogonal access techniques. In this paper, we investigate, for the first time in existing literature, the practical indoor scenario of a hybrid VLC/RF network, where both VLC and RF subsystems perform NOMA. More specifically, we study the user grouping through the coalitional game theory, where each coalition is assigned to a specific access point, VLC or RF. Note that due to NOMA's particularities, optimal user grouping is still an open problem of research. Computer simulations illustrate the accuracy of the analysis and reveal the effectiveness of the proposed scheme compared to the standard opportunistic one, as well as its robustness with respect to the number of users.

In this paper, the joint design of user clustering and power allocation is investigated in a downlink non-orthogonal multiple access based millimeter wave (mmWave-NOMA) system. In order to maximize the sum rate of the system, the Stackelberg game based optimization problem is formulated. With the aid of game theory, a low complexity algorithm is proposed to dynamically allocate users into different clusters. By deriving the closed-form expressions, the optimal power allocation coefficients of the users in each cluster are obtained. The properties of the proposed joint algorithm, including complexity, convergence and stability, are analyzed. Simulation results demonstrate that: i) the proposed algorithm can significantly improve the sum rate and reduce the outage probability of the mmWave- NOMA system; ii) the application of NOMA in mmWave systems is capable of achieving promising gains over conventional orthogonal multiple access (OMA) based frameworks in both cases.

In this paper, we aim to design a power allocation strategy to minimize the average consumed power of a hybrid automatic repeat request with chase combining (HARQ-CC) enabled system under a strict outage constraint for each user. In particular, the non-orthogonal multiple access (NOMA) is incorporated to further improve the system spectrum efficiency and we assume the base station only knows the statistical channel state information of the users. To evaluate the performance of the HARQ-CC enabled NOMA system, we first analyze the outage probability of each user. Then, based on the derived outage probabilities, by optimizing the transmit power, an average power minimization problem is considered. However, the attained expressions of the outage probabilities are nonconvex and extremely complicated, and thus make the formulated problem difficult to deal with. To efficiently solve the original problem, we first conservatively approximate it by a tractable one and then use a successive convex approximation based algorithm to handle the relaxed problem iteratively. And the presented algorithm can be guaranteed to converge to at least a stationary point of the problem. The simulation results show the efficacy of the proposed transmission strategy and the near-optimality of the proposed approximation approach and algorithm.

This paper investigates the impact of non-orthogonal multiple access (NOMA) on wireless caching. Two NOMA caching strategies are developed, namely the push-then- deliver strategy and the push-and-deliver strategy, with the objective to improve the spectral efficiency of the two caching phases, content pushing and content delivery, compared to the conventional orthogonal multiple-access (OMA) based strategy. Both analytical and computer simulation results are provided to demonstrate the performance of the proposed caching strategies and verify the accuracy of the developed analytical results.

We investigate the problem of antenna selection (AS) in full-duplex (FD) cooperative non-orthogonal multiple access (NOMA) systems, where a multi-antenna FD relay assists transmission from a multi-antenna base station (BS) to a far user, while at the same, the BS transmits to a near user. Specifically, based on the end-to-end signal-to-interference-plus-noise ratio at the near and far users, two AS schemes to select a single transmit antenna at both the BS and the relay, respectively, as well as a single receive antenna at relay are proposed. In order to study the ergodic sum rate and outage probability of these AS schemes, we have derived closed-form expressions assuming Rayleigh fading channels. The sum rate and outage probability of the AS schemes are also compared with the optimum selection scheme that maximizes the performance as well as with a random AS scheme. Our results show that the proposed AS schemes can deliver a near-optimal performance for near and far users, respectively.

In this paper, the flexible user association is inves- tigated in non- orthogonal multiple access (NOMA)-based multi- ple base stations (BSs) networks. More particularly, users are partitioned into multiple orthogonal clusters to allocate into different resource blocks (RBs) for avoiding serious co-channel interferences. In an effort to maximize the weighted sum rate of the system, a user association optimization problem is formulated. Two algorithms based on coalitional game are proposed for obtaining suboptimal and global optimal solutions, respectively. The properties of the proposed algorithms, including complexity, convergence, stability and optimality are analyzed. Simulation re- sults demonstrate that: i) the proposed algorithms can significantly enhance the weighted sum rate of the considered systems; ii) the proposed NOMA-based system is capable of achieving promising gains over conventional orthogonal multiple access (OMA)-based framework, and iii) the considered distance based weight factor can greatly improve the fairness of users.

In this paper, we investigate distributed subchannel allocation problem in small cell network (SCN) with non-orthogonal multiple access (NOMA) enhancement. Different from existing studies, we exploit NOMA for the purpose of mitigating aggregate inter-cell and intra-cell interference. The problem is analyzed through a locally cooperative game model, in which information is exchanged only among neighboring small cell base stations (SBSs) instead of all SBSs in the SCN. The existence of Nash equilibrium (NE) is confirmed by proving the formulated game as an exact potential game, which allows the application of best response algorithm to solve the problem locally or globally. It is shown that the aggregate interference can be more efficiently suppressed in the NOMA system, compared with traditional orthogonal multiple access (OMA) system. Furthermore, as the network grows denser, higher percentage of SBSs have the incentive to multiplex users via the NOMA technique, revealing the superiority of NOMA over OMA in future ultra dense network.

In this paper, we propose a novel joint caching and non-orthogonal multiple access (NOMA) scheme to facilitate advanced downlink transmission for next generation cellular networks. In addition to reaping the conventional advantages of caching and NOMA transmission, the proposed cache-aided NOMA scheme also exploits cached data for interference cancellation which is not possible with separate caching and NOMA transmission designs. Furthermore, as caching can help to reduce the residual interference power, several decoding orders are feasible at the receivers, and these decoding orders can be flexibly selected for performance optimization. We characterize the achievable rate region of cache-aided NOMA and investigate its benefits for minimizing the time required to complete video file delivery. Our simulation results reveal that, compared to several baseline schemes, the proposed cache-aided NOMA scheme significantly expands the achievable rate region for downlink transmission, which translates into substantially reduced file delivery times.

Realising both wireless information transfer (WIT) and wireless power transfer (WPT) in the same RF spectral band has imposed great challenges on the system design but the spectral efficiency can be substantially improved, which triggers the significant research interest in the simultaneous wireless information and power transfer (SWIPT). In order to fully exploit the limited spectral resources, a non-orthogonal-multiple-access (NOMA) technique aided SWIPT system is considered for simultaneously realising both of WIT and WPT, which consists of a single access point (AP), a single WPT user and a pair of WIT users. The AP delivers the requested information to the pair of WIT users by adopting the NOMA technique. In order to maximise the amount of energy received by the WPT user, a novel constellation rotation based modulation scheme is proposed for constructively combining the symbols requested by the pair of the WIT users by optimising the constellation rotation angle. By considering the sensitivity of the energy harvester, the simulation results demonstrate that our modulation scheme is capable of efficiently increasing the energy harvested by the WPT user without incurring additional symbol detection errors.

Unmanned aerial vehicles (UAVs) have found many important applications in communications. They can serve as either aerial base stations or mobile relays to improve the quality of services. In this paper, we study the use of multiple UAVs in relaying. Considering two typical uses of multiple UAVs as relays that form either a single multi-hop link or multiple dual-hop links, we first optimize the placement of the UAVs by maximizing the end-to- end signal-to-noise ratio for two common relaying protocols. Based on the optimum placement, the two relaying uses are then compared in terms of outage and bit error rate. Numerical results show that the dual-hop option is better when the source-to- destination distance is small. Also, decode-and- forward UAVs provide better performances than amplify-and-forward UAVs. The investigation has also revealed the effects of important system parameters on the optimum UAV positions and the relaying performances to provide useful design guidelines.

Machine learning has been used to develop efficiently optimizing algorithms for practical communication systems. This paper investigates the user clustering and power allocation problem in the millimeter wave non-orthogonal multiple access (mmWave-NOMA) transmission scenario, where we assume that the users' locations of different clusters follows a Poisson cluster process (PCP). Specifically, we develop a machine learning based user clustering algorithm for the application of NOMA. Moreover, to investigate the performance of the proposed mmWave-NOMA system, we derive the optimal power allocation coefficients in closed-form by assuming equal power on each beam. In the simulation results, we firstly investigate the impact of the number of clusters on the system performance. We further show the validation of the proposed machine-learning based user clustering algorithm in the mmWave-NOMA system.

In this paper we study on a massive MIMO relay system with linear precoding under the conditions of imperfect channel state information at the transmitter (CSIT) and per-user channel transmit correlation. In our system the source-relay channels are massive multiple-input multiple-output (MIMO) ones and the relay-destination channels are massive multiple-input single-output (MISO) ones. Large random matrix theory (RMT) is used to derive a deterministic equivalent of the signal-to-interference-plus-noise ratio (SINR) at each user in massive MIMO amplify-forward and decode-forward (M-MIMO-ADF) relaying with regularized zero-forcing (RZF) precoding, as the number of transmit antennas and users M,K→∞ and M≫K. Simulation results show that the deterministic equivalent of the SINR at each user in M-MIMO-ADF relaying and the results of Theorem 1, Theorem 2 are accurate.

Recently, non-orthogonal multiple access (NOMA) transmission has aroused an upsurge of interest due to its obvious superiority in spectral efficiency and user connectivity for the next generation cellular networks. However, as NOMA is intrinsically in favour of the users with strong channels who are capable of carrying out successive decoding, judicious design is required for ensuring user fairness. In this paper, we consider a two-user downlink NOMA with delay-tolerant transmission over fading channels in both scenarios of full and partial channel state information at the transmitter (CSIT). The average sum-rate is maximized subject to both an average and a peak power constraint as well as a minimum individual rate constraint. The dynamic resource allocation policy is optimally obtained using Lagrangian dual decomposition in the full CSIT case, while the power allocation in the partial CSIT case is also developed based on analytical results. Finally, the effectiveness of the proposed algorithms for NOMA over orthogonal multiple access (OMA) are verified in simulations by means of trade-offs for the average sum-rate and/or individual rate versus the minimum average rate requirement.

This paper provides a comprehensive survey of the impact of the emerging communication technique, non-orthogonal multiple access (NOMA), on future wireless networks. Particularly, how the NOMA principle affects the design of the generation multiple access techniques is introduced first. Then the applications of NOMA to other advanced communication techniques, such as wireless caching, multiple-input multiple-output techniques, millimeter-wave communications, and cooperative relaying, are discussed. The impact of NOMA on communication systems beyond cellular networks is also illustrated, through the examples of digital TV, satellite communications, vehicular networks, and visible light communications. Finally, the study is concluded with a discussion of important research challenges and promising future directions in NOMA.

This letter considers the minimization of the offloading delay for nonorthogonal multiple access assisted mobile edge computing (NOMA-MEC). By transforming the delay minimization problem into a form of fractional programming, two iterative algorithms based on, respectively, Dinkelbach's method and Newton's method are proposed. The optimality of both methods is proved and their convergence is compared. Furthermore, criteria for choosing between three possible modes, namely orthogonal multiple access, pure NOMA, and hybrid NOMA, for MEC offloading are established.

Conventional wireless caching assumes that content can be pushed to local caching infrastructure during off-peak hours in an error-free manner; however, this assumption is not applicable if local caches need to be frequently updated via wireless transmission. This paper investigates a new approach to wireless caching for situations in which the cache content has to be updated during on-peak hours. Two non-orthogonal multiple access (NOMA)-assisted caching strategies are developed, namely, the push-then-deliver strategy and the push-and-deliver strategy. In the push-then-deliver strategy, the NOMA principle is applied to push more content files to the content servers during a short time interval reserved for content pushing during on-peak hours and to provide more connectivity for content delivery, compared with the conventional orthogonal multiple access (OMA) strategy. The push-and-deliver strategy is motivated by the fact that some users’ requests cannot be accommodated locally and the base station has to serve them directly. These events during the content delivery phase are exploited as opportunities for content pushing, which further facilitates the frequent update of the files cached at the content servers. It is also shown that this strategy can be straightforwardly extended to device-to-device caching, and various analytical results are developed to illustrate the superiority of the proposed caching strategies compared with OMA based schemes.

In this paper, we consider a non-orthogonal multiple access cognitive radio network, where a full-duplex (FD) multi-antenna relay assists transmission from an access point (AP) to a cognitive far user, while at the same time, the AP transmits to a cognitive near user. Our objective is to maximize the rate of the near user under a constraint that the rate of the far user is above a certain threshold. To this end, a non-convex joint optimization problem of relay beamforming and the transmit powers at the AP and FD relay is solved as a semi-definite relaxation problem, in conjunction with an efficiently solvable line-search approach. We also consider a low complexity fixed beamformer design, where the optimum power allocation between the AP and FD relay is solved. Several fixed beamforming designs based on the zero-forcing criterion are proposed for which exact and asymptotic outage probability expressions corresponding to the near and far users are derived. Our results demonstrate that the proposed joint optimization can significantly reduce the self-interference impact at the FD relay and inter-user interference in the near user case.

To study the feasibility of network non-orthogonal multiple access (N-NOMA) techniques, this paper proposes a N-NOMA scheme for a downlink coordinated multipoint (CoMP) communication scenario, with randomly deployed users. In the considered N-NOMA scheme, superposition coding (SC) is employed to serve cell-edge users as well as users close to base stations (BSs) simultaneously, and distributed analog beamforming by the BSs to meet the cell-edge user's quality of service requirements. The combination of SC and distributed analog beamforming significantly complicates the expressions for the signal-to-interference-plus-noise ratio at the receiver, which makes the performance analysis particularly challenging. However, by using rational approximations, insightful analytical results are obtained in order to characterize the outage performance of the considered N-NOMA scheme. Computer simulation results are provided to show the superior performance of the proposed scheme as well as to demonstrate the accuracy of the analytical results.

In this paper, a novel cooperative non-orthogonal multiple access (NOMA) system is proposed, where one near user is employed as decode-and-forward relaying switching between full-duplex (FD) and half-duplex (HD) mode to help a far user. Two representative cooperative relaying scenarios are investigated insightfully. The first scenario is that no direct link exists between the base station (BS) and far user. The second scenario is that the direct link exists between the BS and far user. To characterize the performance of potential gains brought by the FD NOMA in two considered scenarios, three performance metrics outage probability, ergodic rate, and energy efficiency are discussed. More particularly, we derive new closed-form expressions for both exact and asymptotic outage probabilities as well as delay-limited throughput for two NOMA users. Based on the derived results, the diversity orders achieved by users are obtained. We confirm that the use of direct link overcomes zero diversity order of far NOMA user inherent to FD relaying. In addition, we derive new closed-form expressions for asymptotic ergodic rates. Based on these, the high signal-to-noise ratio (SNR) slopes of two users for FD NOMA are obtained. Simulation results demonstrate that: 1) the FD NOMA is superior to the HD NOMA in terms of outage probability and ergodic sum rate in the low SNR region; and 2) in delay-limited transmission mode, the FD NOMA has higher energy efficiency than the HD NOMA in the low SNR region; However, in delay-tolerant transmission mode, the system energy efficiency of the HD NOMA exceeds the FD NOMA in the high SNR region.

This paper investigates the impact of relay selection (RS) on the performance of cooperative non-orthogonal multiple access (NOMA), where relays are capable of working in either full-duplex (FD) or half-duplex (HD) mode. A number of relays (i.e., K relays) are uniformly distributed within the disc. A pair of RS schemes are considered insightfully: 1) single-stage RS (SRS) scheme; and 2) two-stage RS (TRS) scheme. In order to characterize the performance of these two RS schemes, new closed-form expressions for both exact and asymptotic outage probabilities are derived. Based on analytical results, the diversity orders achieved by the pair of RS schemes for FD/HD cooperative NOMA are obtained. Our analytical results reveal that: 1) the FD-based RS schemes obtain a zero diversity order, which is due to the influence of loop interference at the relay; and 2) the HD-based RS schemes are capable of achieving a diversity order of K , which is equal to the number of relays. Finally, simulation results demonstrate that: 1) the FD-based RS schemes have better outage performance than HD-based RS schemes in the low signal-to-noise ratio (SNR) region; 2) as the number of relays increases, the pair of RS schemes considered are capable of achieving the lower outage probability; and 3) the outage behaviors of FD/HD-based NOMA SRS/TRS schemes are superior to that of random RS and orthogonal multiple access based RS schemes.

Ultra-dense networks (UDNs) are the promising technology for the fifth-generation wireless networks and beyond to significantly boost network capacity and improve network coverage by exploiting spatial spectrum reuse through the deployment of massive base stations (BSs). In this paper, the fundamental tradeoffs of non-orthogonal multicast, multicast, and unicast in the UDN are studied, to understand the impact of network densitification on them and provide some insights on UDN deployment. Non-orthogonal multicast with imperfect channel estimation and successive interference cancellation is also investigated. To evaluate the performance, a tractable model for performance analysis is developed by using stochastic geometry, and then the analytical expressions for downlink signal-to-interference-plus-noise ratio coverage probability, spectrum efficiency, area traffic capacity, and energy efficiency are derived. The numerical results together with the Monte Carlo simulations are also provided. The results demonstrate that non-orthogonal multicast can further improve the performance of multicast and achieve higher spectrum efficiency, area traffic capacity, and energy efficiency than unicast from the low-to-high BS density regions, but suffers from inferior performance to unicast in the very high BS density region. The results also show that the non-orthogonal multicast and multicast exhibit different performance trends from unicast.

In this paper, a cooperative hybrid visible light communication (VLC)-radio frequency (RF) relay system, which includes a transmitter (S) with a cluster of light emitting diodes (LED) lamps, a relay (R), and a destination (D), is taken into consideration. Moreover, decode-forward (DF) and amplify-forward (AF) schemes are considered at R to aid the data transmissions between S and D. Specially, R is randomly located in the coverage of the LED lamps, D is randomly distributed out of the coverage of the LED lamps. Then, VLC is employed for S-R link, and a traditional RF communication technology is adopted over the R-D link. Considering Nakagami-$m$fading over the R-D link, and the randomness of the locations of R and D, the statistical characteristics of the received signal-to-noise ratio at D under AF scheme, and the ones at R and D under the DF scheme are characterized, respectively. Subsequently, approximated analytical and asymptotic expressions for the outage probability of the considered system are derived, as well as the approximated expression for the average symbol error rate of M-ary quadrature amplitude modulation scheme under the DF scheme. Finally, simulation and numerical analysis are conducted to verify the correctness of our proposed models.

In this paper, we consider the design of a new secure transmission scheme for a four-node relay-eavesdropper channel, where user cooperation is used to facilitate secure communications. The key idea of the proposed achievable scheme is to apply the compression relaying concept of noisy network coding (NNC) to the secrecy communication scenario. But different from the original non-secrecy NNC, the compression rate at the relay is adaptively chosen according to the eavesdropping channel. Particularly, helping interference information is injected into the compression codebook at the relay by simply enlarging the compression rate, which is to effectively suppress the eavesdropping channel. Closed-form expressions of the secrecy rates achieved by the proposed NNC-based secure scheme are characterized for both the discrete memoryless and Gaussian relay-eavesdropper channels, where the optimal compression rate and the optimal transmit power at the relay are also determined. The proposed secure scheme can be viewed as a general framework, which naturally combines the NNC compression relaying scheme with the interference-assisted scheme. Analytical and numerical results demonstrate that the proposed secure scheme offers constant performance gains over typical existing cooperative secure schemes.

Unmanned aerial vehicles (UAVs) have found many important applications in communications. They can serve as either aerial base stations or mobile relays to improve the quality of services. In this paper, we study the use of multiple UAVs in relaying. Considering two typical uses of multiple UAVs as relays that form either a single multi-hop link or multiple dual-hop links, we first optimize the placement of the UAVs by maximizing the end-to-end signal-to-noise ratio for three useful channel models and two common relaying protocols. Based on the optimum placement, the two relaying setups are then compared in terms of outage and bit error rate. Numerical results show that the dual-hop multi-link option is better than the multi-hop single link option when the air-to-ground path loss parameters depend on the UAV positions. Otherwise, the dual-hop option is only better when the source-to-destination distance is small. Also, decode-and-forward UAVs provide better performances than the amplify-and-forward UAVs. The investigation also reveals the effects of important system parameters on the optimum UAV positions and relaying performances to provide useful guidelines.

Non-orthogonal multiple access (NOMA) has been recognized as a promising multiple access scheme to be used in fifth-generation wireless networks. In this paper, multiple-input and multiple-output (MIMO) techniques are applied to NOMA systems by considering two types of imperfect channel state information-channel distribution information (CDI) and channel estimation uncertainty. Based on the two considered channel models, the power allocation and beamforming vectors are jointly designed to maximize the system utility of MIMO-NOMA, subjected to probabilistic constraints. Due to the implementation of successive interference cancellation in NOMA, the power allocation coefficients of the users in each cluster become coupled, which complicates the rate outage probability constraints and results in two challenging non-convex problems. For the optimization problem under CDI, we propose an efficient successive convex approximation (SCA) algorithm based on first-order approximation and semidefinite programming (SDP). For the optimization problem under channel estimation uncertainty, a new algorithm for the joint power allocation and receive beamforming design is developed to maximize the system utility based on SCA and an efficient 1-D search. In addition, the convergence and the feasibility are discussed for the two formulated problems. Furthermore, an efficient method to find a feasible initial solution is provided. Finally, the presented simulation results validate that the proposed two algorithms outperform MIMO-orthogonal multiple access and MIMO fixed NOMA (MIMO F-NOMA) with fixed power allocation and beamforming.

Millimeter-wave non-orthogonal multiple access (mm-wave-NOMA) systems exploit the power domain for multiple accesses to further enhance the spectral efficiency. User clustering and power allocation can effectively exploit the potential of NOMA in mm-wave systems. This paper investigates the sum rate maximization problem of mm-wave-NOMA systems under the constraints of the total transmission power and users' predefined rate requirements. The formulated optimization problem is a non-linear programming problem and, thus, is non-convex and challenging to solve, especially when the number of users becomes large. Sparked by the correlation features of the users' channels in mm-wave-NOMA systems, we develop a K-means-based machine learning algorithm for user clustering. Moreover, for a practical dynamic scenario where the new users keep arriving in a continuous fashion, we propose a K-means-based online user clustering algorithm to reduce the computational complexity. Furthermore, to further enhance the performance of the proposed mm-wave-NOMA system, we derive the optimal power allocation policy in a closed form by exploiting the successive decoding feature. Simulation results reveal that: 1) the proposed machine learning framework enhances the performance of mm-wave-NOMA systems compared to the conventional user clustering algorithms and 2) the proposed K-means-based online user clustering algorithm provides a comparable performance to the conventional K-means algorithm and strikes a good balance between performance and computational complexity.

This paper investigates the application of non-orthogonal multiple access (NOMA) in millimeter wave (mm-Wave) communications by exploiting beamforming, user scheduling, and power allocation. Random beamforming is invoked for reducing the feedback overhead of the considered system. A non-convex optimization problem for maximizing the sum rate is formulated, which is proved to be NP-hard. The branch and bound approach is invoked to obtain the ∈-optimal power allocation policy, which is proved to converge to a global optimal solution. To elaborate further, a low-complexity suboptimal approach is developed for striking a good computational complexity-optimality tradeoff, where the matching theory and successive convex approximation techniques are invoked for tackling the user scheduling and power allocation problems, respectively. Simulation results reveal that: 1) the proposed low complexity solution achieves a near-optimal performance and 2) the proposed mm-Wave NOMA system is capable of outperforming conventional mm-Wave orthogonal multiple access systems in terms of sum rate and the number of served users.

Quality of experience (QoE) is an important indicator in the fifth generation (5G) wireless communication systems. For characterizing user-base station (BS) association, subchannel assignment, and power allocation, we investigate the resource allocation problem in multi-cell multicarrier non-orthogonal multiple access (MC-NOMA) networks. An optimization problem is formulated with the objective of maximizing the sum mean opinion scores (MOSs) of users in the networks. To solve the challenging mixed integer programming problem, we first decompose it into two subproblems, which are characterized by combinational variables and continuous variables, respectively. For the combinational subproblem, a 3-D matching problem is proposed for modeling the relation among users, BSs, and subchannels. Then, a two-step approach is proposed to attain a suboptimal solution. For the continuous power allocation subproblem, the branch and bound approach is invoked to obtain the optimal solution. Furthermore, a low complexity suboptimal approach based on successive convex approximation techniques is developed for striking a good computational complexity-optimality tradeoff. Simulation results reveal that: 1) the proposed NOMA networks is capable of outperforming conventional orthogonal multiple access networks in terms of QoE and 2) the proposed algorithms for sum-MOS maximization can achieve significant fairness improvement against the sum-rate maximization scheme.

Power allocation is an important issue in order to optimize the performance of non-orthogonal multiple access (NOMA) systems. However, the power allocation problem for cooperative NOMA systems has not been well investigated. In this paper, we investigate the power allocation problems for half-duplex cooperative NOMA (HD-CNOMA) and full-duplex cooperative NOMA (FD-CNOMA) systems, respectively. From the fairness standpoint, the optimization problem for each system is formulated to maximize the minimum achievable user rate in a NOMA user pair. Even though both of the formulated problems are neither concave nor quasi-concave, the optimal closed-form solutions of both cases are still obtained with the proposed two-step method. First, we transform the initial problem into a quasi-concave problem by treating the relay transmit power, namely R, as a constant, and then solve the obtained quasiconcave problem. Second, we convert the original problem into a univariate problem of R based on the results of the first step, and eventually obtain the optimal power allocation. In addition, a hybrid half/full-duplex cooperative NOMA scheme, which dynamically switches between the HD-CNOMA and FD-CNOMA mode, is proposed. After that, a relay selection scheme is also investigated to extend the hybrid scheme into general networks with multiple users. Numerical results demonstrate that the proposed hybrid relaying scheme can achieve a significant performance improvement with respect to the conventional NOMA, HD-CNOMA, and FD-CNOMA scheme.

This paper investigates a cooperative non-orthogonal multiple access system, in which a base station communicates with two far users with the aid of a decode-and-forward (DF) relay. Three cooperative relaying schemes, namely, the fixed relaying (FR), the selective DF with coordinated direct and relay transmission (SDF-CDRT), and the incremental-selective DF (ISDF) relaying are proposed to enhance the outage performance for the two far users by utilizing both the direct and relay links. Taking into account the received signal-to-noise ratio (SNR) events at the relay, the SDF-CDRT scheme adaptively forms an orthogonal transmission branch with respect to the direct link or keeps silent to reduce error propagation. Besides considering the relay detection results, the ISDF scheme further exploits the limited feedback of the received SNR events from two users, so that error propagation can be avoided and unnecessary relaying can be reduced. Analytical expressions for the outage probabilities and average throughputs of the paired users are derived in closed-form for the three cooperative relaying schemes. Asymptotic expressions for the outage probabilities are derived in the high SNR region. It is shown that the FR and SDF-CDRT schemes achieve a diversity order of one for both users, while the ISDF scheme achieves a diversity order of two for both users. The superior system performance achieved by the proposed schemes over those of the existing methods is verified by Monte Carlo simulations.

In this paper, a novel joint design of beamforming and power allocation is proposed for a multi-cell multiuser multiple-input multiple-output non-orthogonal multiple access network. In this network, base stations adopt coordinated multipoint for downlink transmission. We study a new scenario where the users are divided into two groups according to their quality-of-service requirements, rather than their channel qualities as investigated in the literature. Our proposed joint design aims to maximize the sum rate of the users in one group with the best effort while guaranteeing the minimum required target rates of the users in the other group. The joint design is formulated as a non-convex NP-hard problem. To make the problem tractable, a series of transformations is adopted to simplify the design problem. Then, an iterative suboptimal resource allocation algorithm based on successive convex approximation is proposed. In each iteration, a rank-constrained optimization problem is solved optimally via semidefinite program relaxation. Numerical results reveal that the proposed scheme offers significant sum-rate gains compared to the existing schemes and converges fast to a suboptimal solution.

This paper introduces downlink non-orthogonal multiple access (NOMA) into short-packet communications. NOMA has great potential to improve fairness and spectral efficiency with respect to orthogonal multiple access (OMA) for low-latency downlink transmission, thus making it attractive for the emerging Internet of Things. We consider a two-user downlink NOMA system with finite blocklength constraints, in which the transmission rates and power allocation are optimized. To this end, we investigate the trade-off among the transmission rate, decoding error probability, and the transmission latency measured in blocklength. Then, a 1-D search algorithm is proposed to resolve the challenges mainly due to the achievable rate affected by the finite blocklength and the unguaranteed successive interference cancellation. We also analyze the performance of OMA as a benchmark to fully demonstrate the benefit of NOMA. Our simulation results show that NOMA significantly outperforms OMA in terms of achieving a higher effective throughput subject to the same finite blocklength constraint, or incurring a lower latency to achieve the same effective throughput target. Interestingly, we further find that with the finite blocklength, the advantage of NOMA relative to OMA is more prominent when the effective throughput targets at the two users become more comparable.

Recently, non-orthogonal multiple access (NOMA) has attracted considerable interest as one of the 5G-enabling techniques. However, the users with better channel conditions in downlink communications intrinsically benefit more from NOMA than the users with worse channel conditions thanks to successive decoding, judicious designs are required to guarantee user fairness. In this paper, a two-user downlink NOMA system over fading channels is considered. For delay-tolerant transmission, the average sum rate is maximized subject to both average and peak-power constraints as well as a minimum average user rate constraint. The optimal resource allocation is obtained using the Lagrangian dual decomposition under full channel state information at the transmitter (CSIT), while an effective power allocation policy under partial CSIT is also developed based on analytical results. In parallel, for delay-limited transmission, the sum of delay-limited throughput (DLT) is maximized subject to a maximum allowable user outage constraint under full CSIT, and the analysis for the sum of DLT is also performed under partial CSIT. Furthermore, an optimal orthogonal multiple access (OMA) scheme is also studied as a benchmark to prove the superiority of NOMA over OMA under full CSIT. Finally, the theoretical analysis is verified by simulations via different tradeoffs for the average sum rate (sum-DLT) versus the minimum (maximum) average user rate (outage) requirement.

This paper considers a downlink single-cell non-orthogonal multiple access (NOMA) network, where the base station, which has multiple antennas, broadcasts the mixed multicast and unicast messages to multiple users with a single antenna. We propose two types of power allocation schemes for NOMA networks with multicast-unicast transmission to investigate the impact of performance, namely, cognitive radio inspired NOMA with dynamic quality of service (QoS) at multicast users (CR-NOMA-D-M), and CR-NOMA constrains the dynamic QoS at the unicast user (CR-NOMA-D-U). Based on the proposed schemes, we drive the exact/closed-form expressions for the secrecy outage probability, outage probability, as well as the approximate outage probability at high signal-to-noise ratio to study the diversity gain. Compared with existing works, the derived analytical results show that both proposed schemes cannot only significantly improve the outage performance for multicast users, but also remarkably enhance the diversity gain and the secrecy outage probability for the unicast user. Finally, the theoretical results are validated by the numerical results.

This paper investigates the power allocation problem of full-duplex cooperative non-orthogonal multiple access (FD-CNOMA) systems, in which the strong users relay data for the weak users via a full duplex relaying mode. For the purpose of fairness, our goal is to maximize the minimum achievable user rate in a NOMA user pair. More specifically, we consider the power optimization problem for two different relaying schemes, i.e., the fixed relaying power scheme and the adaptive relaying power scheme. For the fixed relaying scheme, we demonstrate that the power allocation problem is quasi-concave and a closed-form optimal solution is obtained. Then, based on the derived results of the fixed relaying scheme, the optimal power allocation policy for the adaptive relaying scheme is also obtained by transforming the optimization objective function as a univariate function of the relay transmit power $P_R$. Simulation results show that the proposed FD- CNOMA scheme with adaptive relaying can always achieve better or at least the same performance as the conventional NOMA scheme. In addition, there exists a switching point between FD-CNOMA and half- duplex cooperative NOMA.

Cooperative non-orthogonal multiple access (NOMA) has attracted more and more attentions recently, in which NOMA-strong users play as relays to help the data transmission of NOMA-weak users. Different from existing works, we study the problem of power allocation for cooperative NOMA systems with half-duplex relaying mode. From a fairness standpoint, our proposed scheme aims at maximizing the minimum achievable user rate in a paired user group. More specifically, we divide the cooperative NOMA systems into two categories, i.e., fixed relaying scheme and adaptive relaying scheme. Fixed relaying scheme means the transmit power at the relay node, namely , is a given fixed constant while adaptive relaying scheme implies that can adapt to channel conditions according to our strategy. It is shown that the formulated power allocation problem for fixed relaying scheme is quasi-concave while the problem for adaptive relaying scheme is not. Hence, we firstly solve the former problem using a bisection algorithm by transforming it into a sequence of convex feasibility problems. Then, relying on the derived results of fixed relaying scheme, we find that the problem for adaptive relaying scheme can be converted into a univariate function about , in which the optimum can be also obtained by a similar bisection procedure. Numerical results reveal that the proposed adaptive relaying scheme always outperforms the proposed fixed relaying scheme. In addition, we also show that the cooperative NOMA systems are especially appropriate for systems under low SNR environments or having significantly different fading coefficients between NOMA users.

This paper investigates the application of nonorthogonal multiple access (NOMA) in millimeter wave (mmWave) communication with beamforming, user selection and power allocation. To overcome the burden of feedback, random beamforming to mmWave NOMA systems is considered. We then formulate an optimization problem to maximize the sum rate of the proposed mmWave NOMA systems, which is nonconvex. To solve the challenging problem, we invoke the branch and bound (BB) technique to develop an optimal power allocation algorithm. Then a low complexity suboptimal algorithm based on matching theory is proposed to realize user selection. Simulation results are provided for validating the effectiveness of the proposed algorithms and to show that the sum rate performance of the mmWave NOMA systems can be substantially improved by the proposed algorithms compared to the conventional mmWave orthogonal multiple access (OMA) systems.

We consider a cooperative non-orthogonal multiple access (NOMA) network in which a full-duplex (FD) multi-antenna relay assists transmission from a base station (BS) to a set of far users with poor channel conditions, while at the same time the BS transmits to a set of near users with strong channel conditions. We assume imperfect self- interference (SI) cancellation at the FD relay and imperfect inter-user interference cancellation at the near users. In order to cancel the SI at the relay a zero-forcing based beamforming scheme is used and the corresponding outage probability analysis of two user selection strategies, namely random near user and random far user (RNRF), and nearest near user and nearest far user (NNNF), are derived. Our finding suggests that significant performance improvement can be achieved by using the FD multi- antenna relay compared to the counterpart system with a half-duplex relay. The achieved performance gain depends on network parameters such as the user density, user zones, path loss and the strength of the inter-user interference in case of near users. We also show that the NNNF strategy exhibits a superior outage performance compared to the RNRF strategy, especially in the case of near user.

In this paper, we consider a non-orthogonal multiple access cognitive radio network, where a full-duplex multi-antenna relay assists transmission from a base station (BS) to a cognitive far user, whereas, at the same time, the BS transmits to a cognitive near user. Our objective is to enlarge the far-near user rate region by maximizing the rate of the near user under a constraint that the rate of the far user is above a certain threshold. To this end, a non- convex joint optimization problem of relay beamforming and the transmit powers at the BS and cognitive relay is solved as a semi-definite relaxation problem, in conjunction with an efficiently solvable line-search approach. For comparisons, we also consider low complexity fixed beamformer design, where the optimum power allocation between the BS and cognitive relay is solved. Our results demonstrate that the proposed joint optimization can significantly reduce the impact of the residual self-interference at the FD relay and inter-user interference in the near user case.

In this paper, an indoor 3-dimensional (3-D) hybrid visible light communication (VLC)-radio frequency (RF) system with spatially random terminals is considered. Specifically, VLC and RF communications are employed over downlink and uplink, respectively. Meanwhile, the devices, like sensor nodes, are designed to harvest the energy from the light emitted by the light-emitting diode over the downlink, which is used for the transmissions over the uplink. The light energy harvesting model is proposed after introducing the line of sight propagation model for VLC. Then, the outage performance for orthogonal multiple access (OMA) scheme over the uplink has been studied by using stochastic geometry theory, while considering all devices are spatially random distributed in the 3-D room and all uplinks follow independent/correlated Rician fading. Finally, the analytical expressions for the outage probability with OMA scheme are derived and verified through Monte Carlo simulations.

This paper investigates the impact of relay selection (RS) on the performance of cooperative non-orthogonal multiple access (NOMA), where relays are capable of working in either full-duplex (FD) or half-duplex (HD) mode. The locations of relays considered in the networks are modeled using stochastic geometry. The single-stage relay selection (SRS) scheme is proposed. In order to characterize the performance of SRS scheme, new closed-form expressions for both exact and asymptotic outage probabilities are derived. Based on the analytical results, the diversity orders achieved by the SRS scheme for FD/HD cooperative NOMA are obtained. It is confirmed that the FD-based SRS schemes obtain a zero diversity order, while the HD-based RS is capable of achieving a diversity order of K. Simulation results show that the outage performance of FD-based RS scheme outperforms HD-based RS scheme in the low signal-to-noise radio (SNR) region rather than in the high SNR region.

This paper studies the power minimization problem for non-orthogonal multiple access (NOMA) downlink systems, in which nodes are equipped with multiple antennas. We develop a joint power allocation and receive beamforming algorithm using the fixed-point update power allocation method under two types of channel state information (CSI). Particularly, we first assume that perfect CSI is available for the base station (BS) and the users, where a closed-form expression for every receive detection vector is derived. Then, we consider only channel distribution information (CDI) is known to the BS and the users, where one-dimension search and semi-definite programming (SDP) relaxation are used to derive the receive detection vectors.

In this paper, the application of non-orthogonal multiple access (NOMA) to millimeter-wave (mmWave) communications is considered, where random beamforming is used in order to reduce the system overhead. Stochastic geometry is used to characterize the performance of the proposed mmWave-NOMA transmission scheme, by using the key features of mmWave systems, e.g., mmWave transmission is highly directional and potential blockages will thin the user distribution. The provided analytical and numerical results demonstrate that the combination of NOMA and mmWave yields significant gains in terms of sum rates and outage probabilities, compared to conventional orthogonal multiple access based mmWave systems.

Recently, there has been a surge of increased interest in using physical layer security to safeguard the fifth generation (5G) mobile networks. In this paper, we study the problem of secure communications in untrusted relay networks. A new nonorthogonal relaying protocol is proposed, aiming at maximizing the secrecy rate. Specifically, we allow the source and relay to transmit signals simultaneously over non-orthogonal channels, and apply successive interference cancellation at the destination to separate the multiplexed signals. We also propose two transmit antenna selection schemes to further improve security. To evaluate the secrecy performance, closed-form expressions for ergodic secrecy rate (ESR) and ESR scaling law are derived. The results show that the proposed non-orthogonal relaying protocol yields a considerable ESR improvement than conventional orthogonal relaying, despite the presence of co-channel interference. It is also revealed that the ESR scales with the average signal-to-noise ratio γ̅ and the number of available transmit antennas Ntaccording to log (√γ̅ log Nt), thus achieving superior secrecy performance in the untrusted relay networks.

We consider a multiuser wireless system with a full-duplex hybrid access point (HAP) that transmits to a set of users in the downlink channel, while receiving data from a set of energy-constrained sensors in the uplink channel. We assume that the HAP is equipped with a massive antenna array, while all users and sensor nodes have a single antenna. We adopt a time-switching protocol where in the first phase, sensors are powered through wireless energy transfer from HAP and HAP estimates the downlink channel of the users. In the second phase, sensors use the harvested energy to transmit to the HAP. The downlink-uplink sum-rate region is obtained by solving downlink sum-rate maximization problem under a constraint on uplink sum-rate. Moreover, assuming perfect and imperfect channel state information, we derive expressions for the achievable uplink and downlink rates in the large-antenna limit and approximate results that hold for any finite number of antennas. Based on these analytical results, we obtain the power-scaling law and analyze the effect of the number of antennas on the cancellation of intra-user interference and the self-interference.

This paper investigates the application of simultaneous wireless information and power transfer (SWIPT) to nonorthogonal multiple access (NOMA). A new cooperative multiple-input-single-output (MISO) SWIPT NOMA protocol is proposed, where user 2 who has a strong channel condition acts as an energy-harvesting relay to help user 1 who has a poor channel condition. Our objective is to maximize the data rate of user 2 while satisfying the QoS requirement of user 1. The formulated problem boils down to a complicated nonconvex problem. We first use the semidefinite relaxation (SDR) technique to relax the nonconvex problem. Then, an iterative algorithm with the successive convex approximation (SCA) method is proposed to solve the relaxed problem. As a result, a local optimal solution is obtained. Motivated by the practical applications, the cooperative SWIPT NOMA protocol design in SISO case is investigated and a semiclosed-form solution is derived, which can strictly guarantee the global optimality. It is worth pointing out that the SCA method also admits a global optimal solution in SISO case. Simulation results show that the SWIPT-aided NOMA protocol outperforms the existing transmission protocols.

This paper considers the joint antenna selection (AS) problem for a classical two-user non-orthogonal multiple access (NOMA) network where both the base station and users are equipped with multiple antennas. Since the exhaustive-search-based optimal AS scheme is computationally prohibitive when the number of antennas is large, two computationally efficient joint AS algorithms, namely max-min-max AS (AIA-AS) and max-max-max AS (A3-AS), are proposed to maximize the system sum-rate. The asymptotic closed-form expressions for the average sum-rates for both AIA-AS and A3-AS are derived in the high signal-to-noise ratio (SNR) regime, respectively. Numerical results demonstrate that both AIA-AS and A3-AS can yield significant performance gains over comparable schemes. Furthermore, AIA-AS can provide better user fairness, while the A3-AS scheme can achieve the near-optimal sum-rate performance.

This paper investigates the performance of cooperative non-orthogonal multiple access (NOMA) systems, where one near user works as a decode-and-forward (DF) full-duplex (FD) or half-duplex (HD) relaying to help far user. Two cooperative relay scenarios are considered insightfully. 1) The first scenario is that no direct link exists between the base station (BS) and the far user; and 2) The second scenario is that direct link exists between the BS and the far user. To characterize the performance of FD NOMA in two considered scenarios, new closed-form expressions for both exact and asymptotic outage probability as well as delay-limited throughput are derived for each NOMA user. Based on the analytical results derived, the diversity orders achieved by users are obtained. It is confirmed that the use of the direct link overcomes the zero diversity order of far NOMA user inherent to FD relaying. Simulation results demonstrate that the outage performance of FD NOMA is superior to HD NOMA at low SNR region rather than at high SNR region.

Recently, non-orthogonal multiple access (NOMA) has received considerable attention as a promising candidate for 5G systems. In this paper, a robust beamforming approach is investigated for NOMA based multiple-input single-output (MISO) downlink transmission. We consider an outage probability based robust scheme by incorporating channel uncertainties, where the total transmit power is minimized while satisfying these outage constraints at each user. Although the original problem is non-convex in terms of beamforming vectors, an intractable optimization problem is reformulated with a linear matrix inequality (LMI) form by exploiting semidefinite relaxation (SDR) technique. Finally, simulation results have been provided to validate the performance of the proposed robust design, where these results confirm that the robust scheme outperforms the non-robust scheme in terms of the rate satisfaction ratio at each user.

The power allocation for multi-user sparse code multiple access (SCMA) downlink systems with finite- alphabet constraints is investigated. An explicit expression for the achievable rate for downlink SCMA systems with finite-alphabet inputs is derived, which is applicable to arbitrary number of users. Moreover, a novel power allocation scheme that can ensure users' fairness for multi-user SCMA downlink systems is proposed. In an effort to solve the formulated non-convex optimization problem, a low- complexity polynomial algorithm is proposed, which yields an optimal solution. Simulation results demonstrate that the proposed power allocation algorithm is capable of enhancing the performance significantly compared to the equal power allocation scheme.

A dilemma in cloud radio access networks (C-RANs) is how to keep a balance between the performance and the efficiency of centralized processing. To solve this problem, the joint design of channel estimation and cluster formation are studied in this paper. In particular, a data-assisted channel estimation scheme is used to reduce the redundant cost of training sequences, and C-RAN clusters are formed by the remote radio heads (RRHs) to provide efficient cooperation strategies. To ensure the performance of channel estimation and data transmission, the cluster formation and the channel estimation are optimized jointly. An iterative channel estimation scheme is designed by using convex optimization and the Broyden-Fletcher- Goldfarb-Shanno (BFGS) algorithm jointly. Moreover, a utility function of cluster formation can be established based on the estimates and the mean squared error (MSE) of our proposed channel estimation algorithm, and the cluster formation of RRHs can be formulated as a coalitional formation game. Finally, the simulation results are shown to evaluate the performance of our proposed algorithms.

Non‐orthogonal multiple access (NOMA) is a promising multiple access scheme to enhance the spectrum efficiency of fifth generation networks. In this study, the authors study a downlink multiple‐input single‐output (MISO) system combined with NOMA, where a single beamforming (BF) vector is shared by a group of users. A joint BF and power allocation algorithm is proposed to maximise the sum rate of the users with better channel conditions while guaranteeing the quality of service at the user with poor channel conditions. The formulated problem for sum rate maximisation can be shown as non‐deterministic Polynomial‐time‐hard, and therefore an effective solution based on branch and bound (BB) techniques is proposed. Numerical results are provided to verify that the proposed NOMA‐BF system with the BB algorithm improves the sum capacity significantly compared with the NOMA‐BF system with zero forcing.

Non-orthogonal multiple access (NOMA) is an essential enabling technology for the fifth-generation (5G) wireless networks to meet the heterogeneous demands on low latency, high reliability, massive connectivity, improved fairness, and high throughput. The key idea behind NOMA is to serve multiple users in the same resource block, such as a time slot, subcarrier, or spreading code. The NOMA principle is a general framework, and several recently proposed 5G multiple access schemes can be viewed as special cases. This survey provides an overview of the latest NOMA research and innovations as well as their applications. Thereby, the papers published in this special issue are put into the context of the existing literature. Future research challenges regarding NOMA in 5G and beyond are also discussed.

Driven by the rapid escalation of the wireless capacity requirements imposed by advanced multimedia applications (e.g., ultrahigh-definition video, virtual reality, etc.), as well as the dramatically increasing demand for user access required for the Internet of Things (IoT), the fifth-generation (5G) networks face challenges in terms of supporting large-scale heterogeneous data traffic. Nonorthogonal multiple access (NOMA), which has been recently proposed for the third-generation partnership projects long-term evolution advanced (3GPP-LTE-A), constitutes a promising technology of addressing the aforementioned challenges in 5G networks by accommodating several users within the same orthogonal resource block. By doing so, significant bandwidth efficiency enhancement can be attained over conventional orthogonal multiple-access (OMA) techniques. This motivated numerous researchers to dedicate substantial research contributions to this field. In this context, we provide a comprehensive overview of the state of the art in power-domain multiplexing-aided NOMA, with a focus on the theoretical NOMA principles, multiple-antenna-aided NOMA design, on the interplay between NOMA and cooperative transmission, on the resource control of NOMA, on the coexistence of NOMA with other emerging potential 5G techniques and on the comparison with other NOMA variants. We highlight the main advantages of power-domain multiplexing NOMA compared to other existing NOMA techniques. We summarize the challenges of existing research contributions of NOMA and provide potential solutions. Finally, we offer some design guidelines for NOMA systems and identify promising research opportunities for the future.

This paper considers the secrecy communication of a wirelessly powered network, where an energy-constrained legitimate transmitter (Alice) sends message to a legitimate receiver (Bob) with the energy harvested from a dedicated power beacon, while an eavesdropper (Eve) intends to intercept the information. A simple time-switching protocol with a time-switching ratio α is used to supply power for the energy-constrained legitimate transmitter. To improve the physical layer security, we first propose a protocol that combines maximum ratio transmission with zero-forcing (ZF) jamming for the case without Eve's channel state information (CS!), i.e., Alice has access to Bob's CSI only. Then, we propose a protocol that uses a ZF transmitting strategy to minimize the signal-to-noise ratio (SNR) at Eve for the case that Alice is capable of obtaining partial CSI related to Eve. Closed-form expressions and simple approximations of the connection outage probability and secrecy outage probability are derived for both protocols. Furthermore, the secrecy throughput as well as the diversity orders achieved by our proposed protocols are characterized, and the optimal time-switching ratio α and power allocation coefficient β for secrecy throughput maximization are derived in the high SNR regime. Finally, numerical results validate the effectiveness of the proposed schemes.

This paper considers the application of non-orthogonal multiple access (NOMA) to a multi-user network with mixed multicasting and unicasting traffic. The proposed design of beamforming and power allocation ensures that the unicasting performance is improved while maintaining the reception reliability of multicasting. Both analytical and simulation results are provided to demonstrate that the use of the NOMA assisted multicast-unicast scheme yields a significant improvement in spectral efficiency compared with orthogonal multiple access (OMA) schemes which realize multicasting and unicasting services separately. Since unicast messages are broadcast to all the users, how the use of NOMA can prevent those multicast receivers intercepting the unicasting messages is also investigated, where it is shown that the secrecy unicasting rate achieved by NOMA is always larger than or equal to that of OMA. Simulation results are provided to verify the developed analytical results and demonstrate the superior performance of the proposed NOMA scheme.

In this paper, we study the user pairing in a downlink non-orthogonal multiple access (NOMA) network, where the base station allocates the power to the pairwise users within the cluster. In the considered NOMA network, a user with poor channel condition is paired with a user with good channel condition, when both their rate requirements are satisfied. Specifically, the quality of service for weak users can be guaranteed, since the transmit power allocated to strong users is constrained following the concept of cognitive radio. A distributed matching algorithm is proposed in the downlink NOMA network, aiming to optimize the user pairing and power allocation between weak users and strong users, subject to the users' targeted rate requirements. Our results show that the proposed algorithm outperforms the conventional orthogonal multiple access scheme and approaches the performance of the centralized algorithm, despite its low complexity. In order to improve the system's throughput, we design a practical adaptive turbo trellis coded modulation scheme for the considered network, which adaptively adjusts the code rate and the modulation mode based on the instantaneous channel conditions. The joint design work leads to significant mutual benefits for all the users as well as the improved system throughput.

Non-orthogonal multiple access (NOMA) is emerging as a promising, yet challenging, multiple access technology to improve spectrum utilization for the fifth generation (5G) wireless networks. In this paper, the application of NOMA to multicast cognitive radio networks (termed as MCR-NOMA) is investigated. A dynamic cooperative MCR-NOMA scheme is proposed, where the multicast secondary users serve as relays to improve the performance of both primary and secondary networks. Based on the available channel state information (CSI), three different secondary user scheduling strategies for the cooperative MCR-NOMA scheme are presented. To evaluate the system performance, we derive the closed-form expressions of the outage probability and diversity order for both networks. Furthermore, we introduce a new metric, referred to as mutual outage probability to characterize the cooperation benefit compared to non-cooperative MCR-NOMA scheme. Simulation results demonstrate significant performance gains are obtained for both networks, thanks to the use of our proposed cooperative MCR-NOMA scheme. It is also demonstrated that higher spatial diversity order can be achieved by opportunistically utilizing the CSI available for the secondary user scheduling.

This paper investigates and optimizes the performance of simultaneous wireless information and power transfer (SWIPT) in wireless sensor networks over Nakagami-m fading channels. In the considered system, there is one mobile reader (R), which is equipped with one transmit antenna and one receive antenna, and a group of passive sensors. The information delivery includes two stages: (1) R broadcasts a command with radio-frequency energy to the sensors, which adopt time splitting (TS)/power splitting (PS) schemes to harvest energy and (2) sensors deliver their information to R over orthogonal channels by using the harvested energy. In this paper, we propose a unified framework to study and optimize the impact of SWIPT on the system performance with both TS and PS schemes. First, we characterize the probability density function and cumulative distribution function of the signal-to-interference-plus-noise-ratio in high signal-to-noise ratio region, then we study the outage and ergodic capacity performance of the backward links. The approximated closed-form expressions for the outage probability and ergodic capacity are derived and validated through Monte Carlo simulations. Finally, we also evaluate the energy efficiency of the target system, and propose an optimal splitting scheme for TS and PS to maximize the throughput of the target system.

In this paper, a hybrid visible light communication-radio frequency (RF) system, including a legitimate receiver (R) and an eavesdropper (E) is considered. R can harvest energy from the light emitted by light emitting diodes (LEDs), which is used for the information transmission between R and the RF receiver which is close to the LED. It is assumed that E tries to eavesdrop the information delivered from R to the RF receiver and R is with finite energy storage. Considering the randomness of the locations of R and E, the statistical characteristics of the received signal-to-noise ratio at the RF receiver and E are characterized; then, we derive the analytical expressions for exact and asymptotic secrecy outage probability by using the stochastic geometry method. Finally, simulations are carried out to verify our proposed analytical models.

In this paper, we investigate resource allocation algorithm design for multicarrier non-orthogonal multiple access (MC-NOMA) systems employing a full-duplex (FD) base station for serving multiple half-duplex (HD) downlink and uplink users simultaneously. The proposed algorithm is obtained from the solution of a non-convex optimization problem for the maximization of the weighted sum system throughput. We apply monotonic optimization to develop an optimal joint power and subcarrier allocation policy. The optimal resource allocation policy serves as a system performance benchmark due to its high computational complexity. Furthermore, a suboptimal iterative scheme based on successive convex approximation is proposed to strike a balance between computational complexity and optimality. Our simulation results reveal that the proposed suboptimal algorithm achieves a close-to-optimal performance. In addition, FD MC-NOMA systems employing the proposed resource allocation algorithms provide a substantial system throughput improvement compared with conventional HD multicarrier orthogonal multiple access (MC-OMA) systems and other baseline schemes. In addition, our results unveil that FD MC-NOMA systems enable a fairer resource allocation compared with traditional HD MC-OMA systems.

In this paper, a dual-hop decode-to-forward cooperative system is considered where multiple relays are with finite energy storage and can harvest energy from the destination. In our analysis, the relays are spatially randomly located with invoking stochastic geometry. In an effort to improve spectral efficiency, an optimal source-relay link scheme is employed. Assuming Nakagami-m fading, two different scenarios are considered: 1) the single-antenna source with perfect channel state information (CSI) and 2) the multiple-antenna source with transmit antenna selection and imperfect CSI. In both scenarios, the destination node is equipped with a single transmit antenna to forward power via frequency radio signal to the relay candidates. For improving the system performance, multiple antennas at the destination are considered to process the multiple copies of the received signal from the best relay. For characterizing the performance of the proposed scenarios, exact closed-form analytical expressions for the outage probability are derived. To obtain further insights, we carry out diversity gain analysis by adopting asymptotic relative diversity. We also derive the exact closed-form analytical expression for the system throughput. Finally, simulation results are presented to corroborate the proposed analysis and to show that: 1) the system performance is improved by enlarging the area of the circle and the density of the relays and 2) the energy storage size has impacts on the performance of considered networks, which determines the maximal transmit power at relays.

The non-regenerative massive multi-input-multi-output (MIMO) non-orthogonal multiple access (NOMA) relay systems are introduced in this paper. The NOMA is invoked with a superposition coding technique at the transmitter and successive interference cancellation (SIC) technique at the receiver. In addition, a maximum mean square error-SIC receiver design is adopted. With the aid of deterministic equivalent and matrix analysis tools, a closed-form expression of the signal to interference plus noise ratio (SINR) is derived. To characterize the performance of the considered systems, closed-form expressions of the capacity and sum rate are further obtained based on the derived SINR expression. Insights from the derived analytical results demonstrate that the ratio between the transmitter antenna number and the relay number is a dominate factor of the system performance. Afterward, the correctness of the derived expressions are verified by the Monte Carlo simulations with numerical results. Simulation results also illustrate that: 1) the transmitter antenna, averaged power value, and user number display the positive correlations on the capacity and sum rate performances, whereas the relay number displays a negative correlation on the performance and 2) the combined massive-MIMO-NOMA scheme is capable of achieving higher capacity performance compared with the conventional MIMO-NOMA, relay-assisted NOMA, and massive-MIMO orthogonal multiple access (OMA) scheme.

The massive amounts of machine-type user equipments (UEs) will be supported in the future fifth generation (5G) networks. However, the potential large random access (RA) delay calls for a new RA scheme and for a detailed assessment of its performance. Motivated by the key idea of non-orthogonal multiple access, the non-orthogonal RA (NORA) scheme based on successive interference cancellation (SIC) is proposed in this paper to alleviate the access congestion problem. Specifically, NORA utilizes the difference of time of arrival to identify multiple UEs with the identical preamble, and enables power domain multiplexing of collided UEs in the following access process, while the base station performs SIC based on the channel conditions obtained through preamble detection. Our analysis shows that the performance of the NORA is superior to the conventional orthogonal RA (ORA) scheme in terms of the preamble collision probability, access success probability, and the throughput of RA. Simulation results verify our analysis and further show that our NORA scheme can improve the number of the supported UEs by more than 30%. Moreover, the number of preamble transmissions and the access delay for successfully accessed UEs are also reduced significantly by using the proposed RA scheme.

In this paper, a cooperative non-orthogonal multiple access (NOMA) network is considered, where a source communicates with two users through an energy harvesting relay. The impact of two types of NOMA power allocation policies, namely NOMA with fixed power allocation (F-NOMA) and cognitive radio inspired NOMA (CR-NOMA), on the considered cooperative simultaneous wireless information and power transfer (SWIPT) system is investigated. In particular, closed-form expressions for the outage probability and their high SNR approximations are derived to characterize the performance of SWIPT-F-NOMA and SWIPT-CR-NOMA. These developed analytical results demonstrate that the two power allocation policies realize different tradeoffs between the reception reliability, user fairness and system complexity. Compared with the conventional SWIPT relaying networks with orthogonal multiple access (OMA), the proposed NOMA schemes can effectively reduce the outage probability, although all of them realize the same diversity gain.

In this paper, we propose a new downlink non-orthogonal multiuser superposition transmission scheme for future 5G cellular networks, which we refer to as the lattice partition multiple access (LPMA). In this proposed design, the base station transmits multilevel lattice codes for multiple users. Each user's code level corresponds to a distinct prime and is weighted by a product of all distinct primes of the other users excluding its own. Due to the structural property of lattice codes, each user can cancel out the interference from the other code levels by using the modulo lattice operation in a successive/parallel manner. LPMA can provide better user fairness in symmctrical broadcast channels, compared with non- orthogonal multiple access (NOMA). We demonstrate that the proposed LPMA shows a clear throughput enhancement over the current NOMA scheme.

This paper investigates artificial noise injection into the temporal and spatial dimensions of a legitimate wireless communication system to secure its transmissions from potential eavesdropping. We consider a multiple-input single-output (MISO) orthogonal frequency division multiplexing (OFDM) system in the presence of a single-antenna passive eavesdropper and derive both the secrecy rate and average secrecy rate of the legitimate system. It is assumed that the legitimate transmitter knows the full channel information of the legitimate transceivers but does not know the instantaneous channel state information of the passive eavesdropper. Closed-form expressions for the secrecy rate and average secrecy rate are derived for the asymptotic case with a large number of transmit antennas. We also investigate 1) the power allocation between the data and the AN; 2) the power allocation between the spatial and the temporal AN. Computer simulations are carried out to evaluate the performance of our proposed artificial noise scheme.

In this paper, we investigate the resource allocation algorithm design for multicarrier non-orthogonal multiple access (MC-NOMA) systems. The proposed algorithm is obtained from the solution of a non-convex optimization problem for the maximization of the weighted system throughput. We employ monotonic optimization to develop the optimal joint power and subcarrier allocation policy. The optimal resource allocation policy serves as a performance benchmark due to its high complexity. Furthermore, to strike a balance between computational complexity and optimality, a suboptimal scheme with low computational complexity is proposed. Our simulation results reveal that the suboptimal algorithm achieves a close-to-optimal performance and MC-NOMA employing the proposed resource allocation algorithm provides a substantial system throughput improvement compared to conventional multicarrier orthogonal multiple access (MC-OMA).

We study a wireless-powered uplink communication system with non-orthogonal multiple access (NOMA), consisting of one base station and multiple energy harvesting users. We focus on data rates optimization and fairness increase. We show that the formulated optimization problems can be optimally and efficiently solved by either linear programming methods or convex optimization, which means that the proposed scheme can be easily implemented in practical applications. Simulation results illustrate that the proposed scheme outperforms the baseline orthogonal multiple access scheme, while they reveal the dependence between sum-throughput, minimum data rate, and harvested energy.

In this paper, a novel MIMO-NOMA framework for downlink and uplink transmission is proposed by applying the concept of signal alignment. By using stochastic geometry, closed-form analytical results are developed to facilitate the performance evaluation of the proposed framework for randomly deployed users and interferers. The impact of different power allocation strategies, such as fixed power allocation and cognitive radio inspired power allocation, on the performance of MIMO-NOMA is also investigated. Computer simulation results are provided to demonstrate the performance of the proposed framework and the accuracy of the developed analytical results.

In this paper, the physical layer security of applying non-orthogonal multiple access (NOMA) in large-scale networks is investigated. In the considered scenario, both the NOMA users and eavesdroppers are spatially randomly deployed. A protected zone around the source node is adopted to enhance the security of a random network. In order to characterize the secrecy performance of the considered scenario, new exact and asymptotic expressions for the security outage probability are derived. These analytical results demonstrate that the secrecy diversity order is m, which is determined by the user with poor channel condition. Monte Carlo simulations are provided to verify the derived analytical results. Furthermore, it is also confirmed that the secure performance of the NOMA networks can be improved by either enlarging the scope of the protected zone or reducing the scope of the user zone.

In this paper, a general framework of the multiple- input multiple-output (MIMO) transceiver design for 5G multiple access (5GMA), including both non- orthogonal multiple access (NOMA) and sparsity code multiple access (SCMA), is developed to enhance the system throughput of next generation of communication systems. By applying generalized singular value decomposition (GSVD), MIMO channels can be decomposed into multiple single-input single- output (SISO) channels, to which the concept of NOMA and SCMA can ideally be applied. GSVD based precoding is proposed to both uplink and downlink 5GMA transmissions, and simulation results are provided to demonstrate the performance of the proposed schemes.

This study considers the problem of beamforming optimisation in an amplify‐and‐forward relaying cooperative network, in which the relay node harvests the energy from the radio‐frequency signal. Based on the self‐energy recycling relay protocol, the authors study the beamforming optimisation problem. The formulated problem aims to maximise the achievable rate subject to the available transmitted power at the relay node. The authors develop a semidefinite programming (SDP) relaxation method to solve the proposed problem. They also use SDP and the full search to solve the beamforming optimisation based on a time‐switching relaying protocol as a benchmark. The simulation results are presented to verify that the self‐energy recycling protocol achieves a significant rate gain compared with the time‐switching relaying protocol and the power‐splitting relaying protocol.

In this paper, the application of simultaneous wireless information and power transfer (SWIPT) to nonorthogonal multiple access (NOMA) networks in which users are spatially randomly located is investigated. A new co-operative SWIPT NOMA protocol is proposed, in which near NOMA users that are close to the source act as energy harvesting relays to help far NOMA users. Since the locations of users have a significant impact on the performance, three user selection schemes based on the user distances from the base station are proposed. To characterize the performance of the proposed selection schemes, closed-form expressions for the outage probability and system throughput are derived. These analytical results demonstrate that the use of SWIPT will not jeopardize the diversity gain compared to the conventional NOMA. The proposed results confirm that the opportunistic use of node locations for user selection can achieve low outage probability and deliver superior throughput in comparison to the random selection scheme.

In cloud radio access networks (C-RANs), a substantial amount of data must be exchanged in both backhaul and fronthaul links, which causes high power consumption and poor quality of service (QoS) experience for real-time services. To solve this problem, a cluster content caching structure is proposed in this paper, which takes full advantages of distributed caching and centralized signal processing. In particular, redundant traffic on the backhaul can be reduced because the cluster content cache provides a part of required content objects for remote radio heads (RRHs) connected to a common edge cloud. Tractable expressions for both effective capacity and energy efficiency performance are derived, which show that the proposed structure can improve QoS guarantees with a lower cost of local storage. Furthermore, to fully explore the potential of the proposed cluster content caching structure, the joint design of resource allocation and RRH association is optimized, and two distributed algorithms are accordingly proposed. Simulation results verify the accuracy of the analytical results and show the performance gains achieved by cluster content caching in C-RANs.

In this letter, we study a downlink non-orthogonal multiple access (NOMA) transmission system, where only the average channel state information (CSI) is available at the transmitter. Two criteria in terms of transmit power and user fairness for NOMA systems are used to formulate two optimization problems, subjected to outage probabilistic constraints and the optimal decoding order. We first investigate the optimal decoding order when the transmitter knows only the average CSI, and then, we develop the optimal power allocation schemes in closed form by employing the feature of the NOMA principle for the two problems. Furthermore, the power difference between NOMA systems and OMA systems under outage constraints is obtained.

In this letter, a low-feedback nonorthogonal multiple access (NOMA) scheme using massive multiple-input multiple-output (MIMO) transmission is proposed. In particular, the proposed scheme can decompose a massive-MIMO-NOMA system into multiple separated single-input single-output (SISO) NOMA channels, and analytical results are developed to evaluate the performance of the proposed scheme for two scenarios, with perfect user ordering and with one-bit feedback, respectively.

In this paper, a multiple-input single-output (MISO) simultaneous wireless information and power transfer (SWIPT) system, including one base station (BS) equipped with multiple antennas, one desired single-antenna information receiver (IR), and N (N > 1) single-antenna energy-harvesting receivers (ERs) is considered. Assuming that the information signal to the desired IR may be eavesdropped by ERs if ERs are malicious, we investigate the secrecy performance of the target MISO SWIPT system when imperfect channel state information (CSI) is available and adopted for transmit antenna selection at the BS. Considering that each eavesdropping link experiences independent but not necessarily identically distributed Rayleigh fading, the closed-form expressions for the exact and the asymptotic secrecy outage probability, and the average secrecy capacity are derived and verified by simulations. Furthermore, the optimal power splitting factor is derived for each ER to realize the tradeoff between the energy harvesting and the information eavesdropping. Our results reveal the impact of the imperfect CSI on the secrecy performance of MISO SWIPT systems in the presence of multiple wiretap channels.

In this paper, a downlink single-cell non-orthogonal multiple access (NOMA) network with uniformly deployed users is considered and an analytical framework to evaluate its performance is developed. Particularly, the performance of NOMA is studied by assuming two types of partial channel state information (CSI). For the first one, which is based on imperfect CSI, we present a simple closed-form approximation for the outage probability and the average sum rate, as well as their high signal-to-noise ratio (SNR) expressions. For the second type of CSI, which is based on second order statistics (SOS), we derive a closed-form expression for the outage probability and an approximate expression for the average sum rate for the special case two users. For the addressed scenario with the two types of partial CSI, the results demonstrate that NOMA can achieve superior performance compared to the traditional orthogonal multiple access (OMA). Moreover, SOS-based NOMA always achieves better performance than that with imperfect CSI, while it can achieve similar performance to the NOMA with perfect CSI at the low SNR region. The provided numerical results confirm that the derived expressions for the outage probability and the average sum rate match well with the Monte Carlo simulations.

We propose a novel two-timeslot two-way full-duplex (FD) relaying scheme, in which the access link and the backhaul link are divided in the time domain, and we study the average end-to-end rate and the outage performance. According to the user equipment capability and services, we investigate two scenarios: three-node I- and four-node Y-relaying channels. Among various relaying protocols, the well-known amplify-and-forward and decode-and-forward are considered. Closed-form expressions for the average end-to-end rate and the outage probability, under the effect of residual self-interference and inter-user interference, are presented. The results show that the proposed two-timeslot two-way FD relaying scheme can achieve higher rate and better outage performance than the half-duplex one, when residual self-interference is below a certain level. Therefore, this relaying scheme presents a reasonable tradeoff between performance and complexity, and so, it could be efficiently used in the fifth-generation wireless networks.

This paper investigates group secret key generation problems for different types of wireless networks, by exploiting physical layer characteristics of wireless channels. A new group key generation strategy with low complexity is proposed, which combines the well-established point-to-point pairwise key generation technique, the multisegment scheme, and the one-time pad. In particular, this group key generation process is studied for three types of communication networks: 1) the three-node network; 2) the multinode ring network; and 3) the multinode mesh network. Three group key generation algorithms are developed for these communication networks, respectively. The analysis shows that the first two algorithms yield optimal group key rates, whereas the third algorithm achieves the optimal multiplexing gain. Next, for the first two types of networks, we address the time allocation problem in the channel estimation step to maximize the group key rates. This non-convex max-min time allocation problem is first reformulated into a series of geometric programming, and then, a single-condensation-method-based iterative algorithm is proposed. Numerical results are also provided to validate the performance of the proposed key generation algorithms and the time allocation algorithm.

This paper studies the problem of simultaneously generating a secret key (SK) and a private key (PK) between Alice and Bob, in a cooperative pairwise-independent network (PIN) with two relays. In the PIN, the pairwise source observed by every pair of terminals is independent of those sources observed by any other pairs. The SK needs to be protected from Eve, while the PK needs to be protected not only from Eve but also from the two relays. Two cooperative SK-PK generation algorithms are proposed: both of them first generate common randomness, based on the well-established pairwise key generation technique and the application of the one-time pad; but then, the two algorithms utilize the XOR operation and a specific random-binning-based SK-PK codebook to generate the expected keys, respectively. The achievable SK-PK rate regions of both the two proposed algorithms are analyzed. Of particular interest is the second algorithm with random-bing based codebook, whose achievable key rate region is demonstrated to be exactly the same as the derived outer bound, a crucial step for establishing the key capacity of this PIN model. Finally, the two proposed SK-PK generation algorithms are extended to a cooperative wireless network, where the correlated source observations are obtained from estimating wireless channels during a training phase.

We study the problem of private key generation in a cooperative pairwise independent network (PIN), with M + 2 terminals (Alice, Bob, and M relays), M ≥ 2. In the PIN, the correlated source observed by every pair of terminals is independent of the sources observed by any other pairs of terminals. Moreover, all terminals can communicate with each other over a public channel, which is also observed by Eve, noiselessly. The objective is to generate a private key between Alice and Bob with the help of the M relays; such a private key needs to be protected not only from Eve but also from all relays. A single-letter expression for the private key capacity of this PIN model is obtained, where the achievability part is established by proposing a random binning (RB)-based key generation algorithm, and the converse part is established by deriving upper bounds of M enhanced source models. Next, we consider a cooperative wireless network and use the estimates of fading channels to generate private keys. It has been shown that the proposed RB key generation algorithm can achieve a multiplexing gain of M - 1, which is an improvement compared with the existing XOR algorithm, whose achievable multiplexing gain is IM/2J.

We study a wireless-powered uplink communication system with non-orthogonal multiple access (NOMA), consisting of one base station and multiple energy harvesting users. More specifically, we focus on the individual data rate optimization and fairness improvement and we show that the formulated problems can be optimally and efficiently solved by either linear programming or convex optimization. In the provided analysis, two types of decoding order strategies are considered, namely fixed decoding order and time sharing. Furthermore, we propose an efficient greedy algorithm, which is suitable for the practical implementation of the time-sharing strategy. The simulation results illustrate that the proposed scheme outperforms the baseline orthogonal multiple access scheme. More specifically, it is shown that the NOMA offers a considerable improvement in throughput, fairness, and energy efficiency. Also, the dependence among system throughput, minimum individual data rate, and harvested energy is revealed, as well as an interesting tradeoff between rates and energy efficiency. Finally, the convergence speed of the proposed greedy algorithm is evaluated, and it is shown that the required number of iterations is linear with respect to the number of users.

This paper considers the application of multiple-input multiple-output (MIMO) techniques to nonorthogonal multiple access (NOMA) systems. A new design of precoding and detection matrices for MIMO-NOMA is proposed and its performance is analyzed for the case with a fixed set of power allocation coefficients. To further improve the performance gap between MIMO-NOMA and conventional orthogonal multiple access schemes, user pairing is applied to NOMA and its impact on the system performance is characterized. More sophisticated choices of power allocation coefficients are also proposed to meet various quality-of-service requirements. Finally, computer simulation results are provided to facilitate the performance evaluation of MIMO-NOMA and also demonstrate the accuracy of the developed analytical results.

This paper considers a general energy harvesting cooperative network with M source-destination (SD) pairs and one relay, where the relay schedules only m user pairs for transmissions. For the special case of m = 1, the addressed scheduling problem is equivalent to relay selection for the scenario with one SD pair and M relays. In conventional cooperative networks, the max-min selection criterion has been recognized as a diversity-optimal strategy for relay selection and user scheduling. The main contribution of this paper is to show that the use of the max-min criterion will result in loss of diversity gains in energy harvesting cooperative networks. Particularly, when only a single user is scheduled, analytical results are developed to demonstrate that the diversity gain achieved by the max-min criterion is only M+1/2 , much less than the maximal diversity gain M. This finding is important since it illustrates that the use of energy harvesting brings fundamental changes to the design of cooperative networks. Motivated by the loss of the max-min criterion, several user scheduling approaches tailored to energy harvesting networks are developed and their performance is analyzed. Simulation results are provided to demonstrate the accuracy of the developed analytical results and facilitate the performance comparison.

The application of multiple-input multiple-output (MIMO) techniques to nonorthogonal multiple access (NOMA) systems is important to enhance the performance gains of NOMA. In this paper, a novel MIMO-NOMA framework for downlink and uplink transmission is proposed by applying the concept of signal alignment. By using stochastic geometry, closed-form analytical results are developed to facilitate the performance evaluation of the proposed framework for randomly deployed users and interferers. The impact of different power allocation strategies, namely fixed power allocation and cognitive radio inspired power allocation, on the performance of MIMO-NOMA is also investigated. Computer simulation results are provided to demonstrate the performance of the proposed framework and the accuracy of the developed analytical results.

In this paper, the outage performance of downlink non-orthogonal multiple access (NOMA) is investigated for the case where each user feeds back only one bit of its channel state information (CSI) to the base station. Conventionally, opportunistic one-bit feedback has been used in fading broadcast channels to select only one user for transmission. In contrast, the considered NOMA scheme adopts superposition coding to serve all users simultaneously in order to improve user fairness. A closed-form expression for the common outage probability (COP) is derived, along with the optimal diversity gains under two types of power constraints. Particularly, it is demonstrated that the diversity gain under a long-term power constraint is twice as large as that under a short-term power constraint. Furthermore, we study dynamic power allocation optimization for minimizing the COP, based on one-bit CSI feedback. This problem is challenging, since the objective function is non-convex; however, under the short-term power constraint, we demonstrate that the original problem can be transformed into a set of convex problems. Under the long-term power constraint, an asymptotically optimal solution is obtained for high signal-to-noise ratio.

In this paper, a novel dynamic power allocation scheme is proposed to downlink and uplink non-orthogonal multiple access (NOMA) scenarios with two users for more flexibly meeting various quality of service requirements. The exact expressions for the outage probability and the average rate achieved by the proposed scheme, as well as their high signal-to-noise ratio approximations, are established. Compared with the existing works, such as NOMA with fixed power allocation and cognitive radio inspired NOMA, the proposed scheme can: 1) strictly guarantee a performance gain over conventional orthogonal multiple access; and 2) offer more flexibility to realize different tradeoffs between the user fairness and system throughput. Monte Carlo simulation results are provided to demonstrate the accuracy of the developed analytical results and the performance gain of the proposed power allocation scheme.

In this paper, we systematically study the average rate and outage probability tradeoffs of full-duplex two-way and one-way relaying under residual self-interference. Among various relaying protocols, two common of them are considered: amplify-and-forward (AF) and decode-and-forward (DF). Furthermore, we consider the application of physical-layer network coding (PNC) and analog network coding (ANC) to full-duplex two-way relaying. Novel closed-form expressions for the average rate and outage probability, are presented. The results show that full-duplex two-way relaying can achieve higher rate than one-way relaying in the medium to high signal-to-noise ratio (SNR) region, at the cost of a certain loss in the outage performance. Moreover, DF protocol can achieve better outage performance than the AF one, but it suffers from a certain loss in the rate in the high SNR region. It is also shown that PNC can further improve the rate and outage performance. In addition, the results clearly reveal the effects of time multiplexing, forward protocol, and network coding on relaying systems, which would shed light on designing practical full-duplex relaying schemes.

In this paper, a non-orthogonal multiple access (NOMA) downlink scenario is considered, in which all nodes are equipped with multiple antennas. A new design of precoding and detection matrices for multiple-input-multiple-output (MIMO) downlink transmissions is proposed and its performance is analyzed by using the criteria of outage probabilities and diversity orders. To further enlarge the performance gap between MIMO-NOMA and conventional orthogonal multiple access schemes, user pairing is applied to NOMA and its impact on the system performance is characterized. Finally computer simulation results are provided to facilitate the performance evaluation of MIMO-NOMA and also demonstrate the accuracy of the developed analytical results.

The aim of this paper is to study how to enlarge the performance gap between non-orthogonal multiple access (NOMA) and conventional orthogonal multiple access (MA) by applying user pairing. Particularly two user pairing schemes achieving different quality of service (QoS) requirements, namely NOMA with fixed power allocation (F-NOMA) and cognitive radio inspired NOMA (CR-NOMA), are proposed. For F-NOMA, both analytical and numerical results are provided to demonstrate that F-NOMA can offer a larger sum rate than orthogonal MA, and the performance gain of F-NOMA over conventional MA can be further enlarged by selecting users whose channel conditions are more distinctive. For CR-NOMA, the QoS requirements for users with poorer channel conditions can be guaranteed since the transmit power allocated to other users is constrained following the concept of cognitive radio networks. Because of this constraint, CR-NOMA has different behavior compared to F-NOMA, as demonstrated by the developed analytical results.

A dilemma in cloud-radio access networks (C-RANs) is to balance the cluster scale and the cooperative gains. In this paper, cluster formation for downlink transmissions in C-RANs is studied. In particular, with a fixed intro-cluster cooperation strategy, an explicit expression for the successful access probability is derived by applying stochastic geometry. By using the obtained theoretical result as a utility function, the problem of grouping remote radio heads is formulated as a coalitional formation game, and then two distributed algorithms based on the merge and split approach are obtained as efficient solutions for the cases with and without cluster size constraints, respectively. Compared with grand cluster formation, which is a centralized method, simulation results show that the proposed approaches can achieve better performance with smaller cluster settings.

This paper studies the private key generation of a cooperative pairwise-independent network (PIN) with M + 2 terminals, where Alice and Bob wish to generate a private key under the help of the M relays, M ≥ 2; such a private key needs to be protected not only from Eve but also from individual relays simultaneously. In this PIN, the correlated source observed by every pair of terminals is independent of those sources observed by any other pair of terminals. All the terminals can communicate with each other over a public channel which is also observed by Eve noiselessly. The private key capacity of this PIN model is established, whose lower bound is obtained by proposing a novel random binning (RB) based key generation algorithm, and the upper bound is obtained based on the construction of M enhanced source models. The two bounds are shown to be exactly the same. Then, we consider a cooperative wireless network and use the estimates of fading channels to generate private keys. Compared to the existing XOR-based algorithm whose achievable multiplexing gain is ⌊M/2⌋, the proposed RB-based algorithm is demonstrated to achieve the optimal multiplexing gain M - 1.

A multi-pair two-way amplify-and-forward relaying system is considered in this paper, where the K-pair users exchange information within pairs, with the help of a shared relay station. Each user is equipped with a single antenna while the relay station is equipped with a very large number of antennas N, where N≫2K. The impact of imperfect channel state information (CSI) due to the channel estimation errors on spectral efficiency (SE) and energy efficiency (EE) is investigated. Asymptotic expressions for EE and SE are obtained in this paper for three power-scaling schemes when maximum-ratio combining/maximum-ratio transmission (MRC/MRT) is adopted. Our analytical results reveal that when the number of relay station antennas N→∞, the effect of the small-scale fading can be averaged out; the residual self-interference and additional noise generated by channel estimation errors will completely vanish, and the inter-pair interference will disappear. However, the imperfect CSI deteriorates EE and SE. When there are no estimation errors, our analytical results reduce to the existing results. Simulation results confirm the validity of our analysis.