In this paper, we investigate the downlink non-orthogonal multiple access (NOMA) secure transmission systems, where a base station (BS) uses superposition coding to transmit information to users in the presence of multiple colluding eavesdroppers. To improve the information security, we propose a movable antenna (MA) and active beamforming (AB) assisted NOMA (MAABaN) secure transmission scheme, in which the BS is equipped with multiple MAs to enhance the physical layer security (PLS). To this end, we formulate a sum secrecy rate maximization optimization problem by jointly optimizing the AB vectors and the MA positions. To solve the complex non-convex problem, we employ the alternating optimization method to transform the original problem into two subproblems. Regarding the subproblem of MA positions, we analyze the coupling relationship between the position variables, and optimize one set of position variables while keeping others fixed. Then, we propose a low-complexity iterative algorithm for the MA positions based on multi-start gradient ascent (MSGA), and construct a joint optimization framework of MA and AB. Numerical results demonstrate that the proposed MAABaN scheme can effectively enhance PLS performance, and the proposed MSGA-based algorithm can also be applied to MA-assisted NOMA secure transmission systems.

The growing reliance on mobile crowdsensing net-works for real-time data collection in various applications, from urban infrastructure monitoring to environmental sensing, ne-cessitates the reduction of latency for enhanced efficiency. In this work, we address this critical challenge by focusing on the joint subband and sensing task allocation for next-generation mobile crowdsensing networks, emphasizing the minimization of latency. To achieve this goal, an optimization problem is formulated to minimize the system's total latency, taking various practical constraints into account. Therein, the latency is comprised of sensing delay and transmission delay. The considered problem is a mixed-integer programming problem, which is also non-convex. To facilitate the analysis, we utilize the underlying structural properties of the problem and derive the optimal sensing task allocation strategy under a given sub band allocation scheme. With the discussions, we show that the original optimization problem can be transformed into a maximum weighted matching problem in a bipartite graph. This problem can be optimally solved by the Hungarian algorithm in a cubic time complexity. Building upon these analyses, we further approximate the optimal network delay in closed form under certain circumstances. Extensive simulation results validate that our proposed joint optimization method outperforms various benchmark strategies in terms of latency saving under comprehensive system settings.

This paper analyzes the block error rate (BLER) of hybrid automatic repeat request with incremental redundancy (HARQ-IR) assisted short packet communications. The small packet size leads to the occurrence of the time correlation among HARQ rounds. To accurately capture the effect of time correlation, a general correlated Nakagami-m fading channel model is first developed. However, the channel correlation, multiple transmissions, and finite blocklength information theory extremely challenge the analysis of BLER. To confront this, the average BLER is derived in a compact form by capitalizing on linearization approximation and conditional Laplace transform. To reveal more insights, the asymptotic BLER in high signal-to-noise ratio is obtained in a simple form. It is disclosed that full time diversity can be achieved by the proposed HARQ-IR-aided scheme. This justifies the feasibility of using retransmissions to offer reliable short packet communications. The numerical results finally corroborate the validity of our analysis.

Abstract This paper investigates the combination of collaborative reconfigurable intelligent surface (RIS) with non‐orthogonal multiple access (NOMA) to enhance the quality of service (QoS) in communication systems. By introducing collaborative RIS, a virtual line‐of‐sight (LoS) link can be established between the base station (BS) and the users. In this article, the aim is to minimize the total transmit power under the constraint of each user's QoS by optimizing the phase shifts and the power allocation coefficients. To proceed, two approaches are proposed with different complexities to solve the formulated power minimization problem. Specifically, in the first method, a sub‐channel allocation scheme based on the user locations is developed, and the phase shifts are optimized to obtain the minimum transmit power for fixed channel assignment, which is further addressed by using the alternating optimization and the sequence rotation methods. In the second approach, a joint optimization algorithm that achieves the channel assignment vectors and the phase shift coefficients in an alternative manner, and a sub‐channel assignment algorithm based on the equivalent channel gain is developed. The simulation results show that the proposed transmission scheme has the capability of improving system performance significantly compared with the conventional schemes.

Blockage effects can dramatically deteriorate high frequency cellular network performance. One practical solution is to apply macro-diversity technique, where the user associates with more than one Base Station (BS), to improve the chance of Light-Of-Sight (LOS) link availability. However, how the correlations are brought by both blockages and cooperative BSs is still unclear due to the analytical complexity. In addition, these two kinds of correlations are highly coupled and further impact macro-diversity gain. On basis of the cascade blockage model, this paper proposes a new functional framework to evaluate macro-diversity gains from the perspective of a typical user subjected to three metrics: joint LOS probability, conditional LOS probability and coverage probability. We first derive a set of tractable functional equations to describe three performance metrics. Then corresponding iterative algorithms that can be solved efficiently are designed respectively for three metrics. This analytical framework gains insight into contradictory requirements for macro-diversity, which not only guide the usage of Coordinated MultiPoint (CoMP) in realistic environments, but also determine the beamforming usage in mmWave band. We demonstrate the feasibility and flexibility of this functional framework by a simplified joint transmission example.

A variable-length cross-packet hybrid automatic repeat request (VL-XP-HARQ) is proposed to boost the spectral efficiency (SE) and the energy efficiency (EE) of communications. The SE is firstly derived in terms of the outage probabilities, with which the SE is proved to be upper bounded by the ergodic capacity (EC). Moreover, to facilitate the maximization of the SE, the asymptotic outage probability is obtained at high signal-to-noise ratio (SNR), with which the SE is maximized by properly choosing the number of new information bits while guaranteeing outage requirement. By applying Dinkelbach’s transform, the fractional objective function is transformed into a subtraction form, which can be decomposed into multiple sub-problems through alternating optimization. By noticing that the asymptotic outage probability is a convex function, each sub-problem can be easily relaxed to a convex problem by adopting successive convex approximation (SCA). Besides, the EE of VL-XP-HARQ is also investigated. An upper bound of the EE is found and proved to be attainable. Furthermore, by aiming at maximizing the EE via power allocation while confining outage within a certain constraint, the methods to the maximization of SE are invoked to solve the similar fractional problem. Finally, numerical results are presented for verification.

Massive multiple-input multiple-output (MIMO), non-orthogonal multiple access (NOMA), and millimeter-wave (mmWave) are key technologies in the upcoming beyond fifth generation (B5G)/sixth generation (6G) era. As mmWave massive MIMO will likely use hybrid beamforming (HBF) to reduce radio frequency (RF) chains without an obvious performance loss to fulfill the urgent requirement for immense connectivity and huge throughput, it is necessary to integrate mmWave massive MIMO-NOMA with HBF structure. This work devises a novel structure for uplink mmWave massive MIMO-HBF-NOMA system based on group-level successive interference cancellation (GSIC), aiming at maximizing the spectrum efficiency (SE) of the whole system. In our paradigm, users are grouped in terms of channel gain. Space division multiple access (SDMA) is deployed between users in the same group, while NOMA is applied among different groups. The analog beamforming vectors are selected through beam sweeping. An iterative algorithm is proposed to optimize the power allocation and the digital beamforming matrix. Therein, a quadratic transform (QT) algorithm is introduced to solve the power allocation and zero forcing (ZF) method is invoked to obtain the digital beamformer. According to the simulation, the novel GSIC-based structure outperforms the benchmark clustering-based successive interference cancellation (SIC) schemes in SE and energy efficiency (EE) measurably.

Both intelligent reflecting surface (IRS) and non-orthogonal multiple access (NOMA) are considered as potential techniques for the next-generation mobile communication system. In this paper, we concentrate on the power minimization problem for a multi-antenna IRS-NOMA uplink system, which is addressed by alternatively optimizing transceivers and phase shifts. Particularly, the users are divided into one central group and one edge group according to their propagation distances to the base station, where the data transmission of the edge group is assisted by the IRS. Besides, from the perspective of practice, a non-ideal group-based successive interference cancellation (GSIC) is taken into account. To proceed, an iterative algorithm with the minimum mean square error equalizer is leveraged to design the transceivers and a sequential rotation algorithm is developed to optimize the phase shifts. Simulation results indicate the superiority of the proposed scheme compared with various benchmarks in terms of transmit power consumption.

In this paper, reconfigurable intelligent surface (RIS) and hybrid automatic repeat request with incremental redundancy (HARQ-IR) are amalgamated to lower power expenditure, shorten latency and strengthen reliability of the internet of things (IoT) communications. By considering Rician fading channels and multiple RISs, the outage probability of single-input single-output (SISO) HARQ-IR-RIS aided IoT networks is derived in closed-form, with which the asymptotic outage analysis is carried out. The asymptotic results are further extended to single-input multiple-output (SIMO)/multiple-input multiple-output (MIMO) HARQ-IR-RIS aided IoT networks by using random matrix theory. Thereafter, the asymptotic expressions are invoked to reduce the design complexity of the phase shifts, transmit powers, and rate, which aims at minimizing the age of information (AoI) while ensuring the power and outage constraints. Particularly, the optimal phase shifts are firstly determined. The alternating optimization technique is then applied to solve the transmit rate and powers, which are iteratively updated based on majorization-minimization (MM) principle and geometric programming (GP) approximation, respectively. The numerical results consequently corroborate our theoretical analysis. More interestingly, the HARQ-IR-aided scheme with fixed power is found to provide a comparable performance as the proposed scheme with variable power especially for numerous reflecting elements at RIS.

Abstract Simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR‐RIS) is capable of achieving full coverage area compared with conventional reflection‐only reconfigurable intelligent surface (RIS). Motivated by this observation, the secrecy performance of STAR‐RIS‐assisted non‐orthogonal multiple access (NOMA) systems over Rayleigh fading channels is investigated, where the incident signals sent by base station are reflected and transmitted to a pair of NOMA users in the presence of two eavesdroppers. To evaluate the secrecy performance of STAR‐RIS‐NOMA systems, the exact and asymptotic expressions of secrecy outage probability (SOP) and secrecy diversity order are derived, in which the correlation of the channels between the elements of each column on STAR‐RIS is taken into consideration. As a benchmark, the secrecy performance of the STAR‐RIS strategy for orthogonal multiple access (OMA) system is also analysed. Numerical results are provided to verify the effectiveness of the analytical results and demonstrate that: The SOP of STAR‐RIS‐NOMA outperforms that of STAR‐RIS‐assisted OMA and conventional cooperative communication systems. Furthermore, the scheme proposed here can obtain full order of secrecy diversity.

To accommodate the stringent requirements of massive connectivity and ultra-high throughput, both reconfigurable intelligent surface (RIS) and non-orthogonal multiple access (NOMA) have been perceived as the key techniques for future communication networks. In this paper, a versatile framework is conceived to boost transmit power efficiency for RIS-enabled multi-group NOMA networks in the presence of coordinated multi-point (CoMP) reception and imperfect successive interference cancellation (SIC). Particularly, a group-level SIC (GSIC) method is proposed to eliminate the decoded group’s interference together with the well-designed transceivers to mitigate the aggregated interference, including the intra-group interference, the residual interference caused by imperfect SIC, and the interference of NOMA users decoded later. According to the novel framework, a power minimization problem is formulated by collaboratively optimizing the transmit power and the phase shifts. To render the problem tractable, an alternating scheme is developed to optimize the transmit power and the phase shifts iteratively. Specifically, the transmit powers for the users in the same group are devised by a parallel iteration algorithm, whilst the phase shifts are optimized by a sequential rotation method. In simulations, it is shown that the proposed scheme requires less transmit power than various benchmark methods under the constraint of each user’s quality of service.

We thoroughly investigate the outage performance of reconfigurable intelligent surface (RIS) aided multi-input multi-output (MIMO) communications by exploiting statistical channel state information (CSI). Kornecker channel model is adopted to characterize the impact of spatial correlations among MIMO antennas and reconfigurable reflectors. Mellin transform and random matrix theory are then utilized to derive the outage probability, with which we further conduct the asymptotic outage analysis to obtain insightful findings. In particular, the asymptotic analysis reveals that the number of reflecting elements at the RIS should not be smaller than the total number of MIMO transmit and receive antennas to get rid of the rank deficiency of the cascaded MIMO channels. Moreover, the asymptotic outage probability is a monotonically increasing and convex function with respect to the transmission rate. The numerical outcomes not only corroborate our analytical results, but also demonstrate the negative impact of the spatial correlation and the benefit of increasing the number of reconfigurable reflectors. Finally, we apply the asymptotic results to optimally devise the phase shifts with a low computational complexity.

Reconfigurable intelligent surface (RIS) has recently attracted a spurt of interest due to its innate advantages over massive MIMO on power consumption. In this paper, we study the outage performance of multi-RIS system with the help of hybrid automatic repeat request (HARQ) to improve the RIS system reliability, where the fading channels are modeled by Rician fading and the phase shift setting only depends on the line-of-sight (LoS) component. Both the exact and asymptotic outage probabilities under Type-I HARQ and HARQ with chase combining (HARQ-CC) schemes are derived. Particularly, the tractable asymptotic results empower us to derive meaningful insights for HARQ-aided multi-RIS systems. On the one hand, we find that both the Type-I and the HARQ-CC schemes can achieve full diversity that is equal to the maximal number of HARQ rounds. On the other hand, the closed-form expression of the optimal phase shift setting with respect to outage probability minimization is obtained. The optimal solution indicates that the reflecting link direction should be consistent with the direct link LoS component. Finally, the analytical results are validated by Monte-Carlo simulations.

Abstract Both cooperative non‐orthogonal multiple access (NOMA) and physical layer security (PLS) are promising techniques for future communication systems. This paper investigates the PLS performance of a cooperative NOMA system where multiple sources transmit a superposed message to two users by utilizing either amplify‐and‐forward (AF) or decode‐and‐forward (DF) relays in both non‐colluding and colluding eavesdropper scenarios. A source‐relay selection scheme is proposed for this system aiming at improving the secrecy performance. Additionally, the closed‐form expression of the secrecy outage probability (SOP) is derived for the proposed source‐relay selection schemes. It is demonstrated that in the proposed schemes, the theoretical results match well with the simulation results. In addition, the proposed schemes outperform the conventional OMA system in terms of SOP.

Multiaccess edge computing (MEC), which brings computing capability close to the user equipment (UE) within a radio access network (RAN), is a promising technique to meet the challenges of explosive growth in edge data traffic and the number of connected devices. Nevertheless, MEC offloading failures, i.e., interruption of task offloading due to UE mobility and limited battery capacity, are still an important issue. In this article, we aim to minimize the total energy consumption in dual connectivity (DC)- and nonorthogonal multiple access (NOMA)-assisted computation offloading systems. This problem is formulated as a mixed-integer nonlinear programming (MINLP) problem with nonconvex constraints, which is a nondeterministic polynomial-time (NP)-hard and perplexing problem. To address this problem, we propose an iterative optimization algorithm to obtain a suboptimal time scheduling and task allocation solution. Specifically, we solve the nonconvex constrained MINLP problems by exploiting the successive convex approximation (SCA) algorithm and the nonlinear optimization algorithm with the mesh adaptive direct search (MADS) (NOMAD). Furthermore, a deep learning-based intelligent offloading scheme is introduced, called a cyclic branch network, to fully utilize data traffic and the computing capability on the network edge. Numerical results show that the proposed intelligent offloading scheme has comparable performance and dramatically reduces the inference time compared with the traditional optimization algorithm.

In this paper, a full-stack perspective that involves content coding, caching and recommendation is presented for wireless edge caching networks. Therein, content coding and recommendations are utilized to ensure the reliability of the network and to boost the gain of edge caching, respectively. Specifically, with a well-designed coding pattern, the concurrently occurred data corruptions of multiple access points (APs) can be successfully recovered. Whilst, the successful content retrieval is warranted with highly selective retrieval sets. Further, by offering personalized recommendations, the cache hitting at network edges can be promoted. On these grounds, a cache hit ratio maximization problem for reliability-aware wireless edge caching system is formulated, considering the successful content retrieval and repair, total repair cost requirements, cache capacity budget of each AP, and recommendation quality and quantity per user. To solve this intractable problem, a framework with two steps is developed, which leads to construction of a suitable coding schema with the minimum repair cost per content to satisfy the retrieval and repair criteria, thus achieving a stabilized optimal solution regarding the joint cache placement and recommendation decisions from a game-theoretical viewpoint. Finally, extensive numerical simulations are performed to confirm the superior performance of our devised algorithms compared with benchmark baselines.

To support massive connectivity and boost spectral efficiency for Internet of Things (IoT), a downlink scheme combining virtual multiple-input-multiple-output (MIMO) and nonorthogonal multiple access (NOMA) is proposed. All the single-antenna IoT devices in each cluster cooperate with each other to establish a virtual MIMO entity, and multiple independent data streams are requested by each cluster. NOMA is employed to superimpose all the requested data streams, and each cluster leverages zero-forcing detection to demultiplex the input data streams. Only statistical channel state information (CSI) is available at the base station to avoid the waste of the energy and bandwidth on frequent CSI estimations. The outage probability and goodput of the virtual MIMO-NOMA system are thoroughly investigated by considering the Kronecker model, which embraces both the transmit and receive correlations. Furthermore, the asymptotic results facilitate not only the exploration of physical insights but also the goodput maximization. In particular, the asymptotic outage expressions provide quantitative impacts of various system parameters and enable the investigation of diversity-multiplexing tradeoff (DMT). Moreover, power allocation coefficients and/or transmission rates can be properly chosen to achieve the maximal goodput. By favor of the Karush-Kuhn-Tucker conditions, the goodput maximization problems can be solved in closed form, with which the joint power and rate selection is realized by using alternately iterating optimization. Besides, the optimization algorithms tend to allocate more power to clusters under unfavorable channel conditions and support clusters with a higher transmission rate under benign channel conditions.

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.

The combination between non-orthogonal multiple access (NOMA) and hybrid automatic repeat request (HARQ) is capable of realizing ultra-reliability, high throughput and massive concurrent connections particularly for emerging communication systems. This paper focuses on characterizing the asymptotic scaling law of the outage probability of the HARQ with chase combining (HARQ-CC)-aided downlink NOMA scheme with respect to the transmit power, i.e., diversity order. The diversity order of the two- user HARQ-CC-aided NOMA system is derived in closed-form, where an integration domain partition trick is developed to obtain the upper and lower bounds of the outage probability. The analytical results show that the diversity order is a decreasing step function of transmission rate given the ratio between the transmit powers allocated to the two users. Moreover, full time diversity can only be achieved under a sufficiently low transmission rate. Additionally, the users' diversity orders follow a descending order according to their respective average channel gains. Monte Carlo simulations finally confirm the analysis.

Both small cells and non-orthogonal multiple access (NOMA) are cutting-edge technologies to boost the system capacity for the future wireless communications. In this paper, an analytical framework for small cell uplinks using NOMA transmissions is developed. To facilitate the detection of both near and far user signals, dual path loss compensation factors (PLCFs) are exploited for uplink power control. With the aid of stochastic geometry, the average successful transmission probability are derived for small cell networks with opportunistic NOMA transmissions and dual PLCFs. Based on the derived results, optimal PLCFs are obtained by two-dimension search methods. It is shown by simulation that the proposed NOMA scheme with optimal dual PLCFs outperforms the existing NOMA scheme with a unique PLCF in terms of both average successful transmission probability and spectrum efficiency.

Group paging is a baseline solution proposed by the long-term evolution (LTE) standardization body for supporting machine-to-machine (M2M) communications in the current-generation and the next-generation cellular networks. Yet, in conventional group paging scheme, upon the reception of paging message, all machine-type devices (MTDs) in a group will simultaneously access the base station, leading to severe network congestion and intolerably low access efficiency. To handle this issue, in this article, we propose a dynamic group paging mechanism, where only the MTDs with packets to send will join the contention process, and the collisions in the random access channel are addressed by the contention resolution scheme. Explicit expressions of key performance measures including the mean access delay of each MTD are derived as functions of the length of waiting period (interval between two consecutive paging periods) TW, where a smaller TWindicates a higher frequency of group paging. It is shown that TWis a key system parameter that determines the crucial tradeoff between the signaling overheads of the system during the paging period and the access delay performance of each MTD. To study how to properly tune the waiting period length, a utility-based analytical framework is established by taking the aforementioned tradeoff into consideration. The optimal waiting period length for maximizing the network utility is derived and verified by simulation results. The analysis in this article reveals that the network should increase the group paging frequency as the traffic becomes heavier or the number of preambles decreases. Providing more preambles can indeed improve the delay performance, while the gain becomes marginal if the number of preambles is large.

This paper investigates the performance of Multipleinput multiple-output non-orthogonal multiple access (MIMONOMA) systems with randomly deployed users, where the randomly deployed NOMA users follow Poisson point process (PPP), the spatial correlation between MIMO channels are characterized by using Kronecker model, and the composite channel model is used to capture large-scale fading as well as small-scale fading. The spatial randomness of users' distribution, the spatial correlation among antennas and large-scale fading will severally impact the system performance, but they are seldom considered in prior literature for MIMO-NOMA systems, and the consideration of all these impact factors challenges the analysis. Based on zeroforcing (ZF) detection, the exact expressions for both the average outage probability and the average goodput are derived in closedform. Moreover, the asymptotic analyses are conducted for both high signal-to-noise ratio (SNR) (/small cell radius) and low SNR (/large cell radius) to gain more insightful results. In particular, the diversity order is given by δ = Nr- M + 1, the average outage probability of k-th nearest user to the base station follows a scaling law of O (Dα(Nr-M+1)+2k), the average goodput scales as O(D2) and O(D-2) as D → 0 and D → ∞, respectively, where Nr, M, α and D stand for the number of receive antennas, the total number of data streams, the path loss exponent and the cell radius, respectively. The analytical results are finally validated through the numerical analysis.