Direction-of-arrival (DOA) estimation for incoherently distributed (ID) sources is crucial for Industrial Internet of Things (IIoT) applications operating in complex multipath environments, yet it remains challenging due to the combined effects of angular spread and gain-phase uncertainties in cost-sensitive antenna arrays. This paper presents a two-stage sparse DOA estimation framework, transitioning from partial calibration to full potential, under the generalized array manifold (GAM) framework. In the first stage, coarse DOA estimates are obtained by exploiting the output from a subset of partly-calibrated arrays (PCAs). In the second stage, these estimates are utilized to determine and compensate for gain-phase uncertainties across all array elements. Then a sparse total least-squares optimization problem is formulated and solved via alternating descent to refine the DOA estimates. Simulation results demonstrate that the proposed method achieves superior estimation accuracy compared to existing approaches, while maintaining robustness against both noise and angular spread effects in practical industrial environments.

Fluid antenna systems (FAS) have emerged as a promising technology to achieve high spatial diversity by dynamically reconfiguring multiple closely spacedNantenna ports. However, the inherent spatial correlation among these ports poses significant challenges for accurate performance analysis. Traditional block-correlation modeling algorithms, which partition theN×NToeplitz-structured correlation matrix into independentDblocks with constant correlation coefficients, often yield substantial approximation errors to block-correlation models, especially in scenarios with limited ports. In this paper, we revisit the spatial block-correlation model for FAS and introduce a novel block-correlation modeling algorithm in tuning the model parameters, which realizes the variable block-correlation model in practice. Our proposed approach derives closed-form expressions for the optimal block-specific correlation coefficients and develops a low-complexity heuristic algorithm that reduces the computational complexity from exponentialDN–Dto linear (N–D) ×Dsearches,thereby achieving significantly lower approximation error compared to constant correlation models. To validate the effectiveness of our variable block-correlation modeling algorithm, we first apply it to point-to-point FAS communications with closely spaced ports, deriving analytical expressions for the joint probability density function (PDF) of channel amplitudes and outage probability. Our analysis shows that the proposed algorithm offers tractable performance evaluation and superior accuracy, particularly when the number of ports is small (NThese results underscore the practical value of our approach for the design and optimization of next-generation FAS-based wireless networks.

FAS-enabled cooperative non-orthogonal multiple access (FAS-CoNOMA) systems capture the potential of fluid antenna systems in enhancing network performance. In this system, a base station (BS) transmits a superposition signal to a central user (CU) and a cell-edge user (EU), both equipped with FAS. Specifically, the CU decodes the signal intended for the EU and cooperatively relays it to improve the EU’s communication performance. The EU employs selective combining (SC) or maximum ratio combining (MRC) to receive signals from both the BS and CU. By leveraging the dynamic properties of FAS to improve user differentiation, the CoNOMA system effectively enhances network performance compared to traditional NOMA, OMA, and fixed position antenna (FPA) systems. To address the challenging spatial correlation properties in FAS, we utilize the block-diagonal matrix approximation (BDMA) model to calculate the outage probabilities for both the CU and EU. We then derive upper bound, lower bound, and asymptotic approximation of the outage probabilities to gain deeper insights. Furthermore, we optimize the EU’s outage probability under the CU’s outage constraint and total transmit power limits by adjusting the power allocation coefficient for the CU and the transmit powers for both the BS and CU. To simplify the optimization process, we reduce the number of variables and apply the alternating optimization (AO) algorithm to break down the problem into two sub-problems. Each sub-problem is solved using the bisection search method and gradient descent algorithm (GDA). Simulation results demonstrate that FAS significantly improves outage performance, especially for the EU, and that CoNOMA notably captures the potential of FAS beyond NOMA and OMA, offering a promising solution for future wireless networks.

In this paper, we analyze the role of fluid antenna systems (FAS) in multi-user systems with hardware impairments (HIs). Specifically, we investigate a scenario where a base station (BS) equipped with multiple fluid antennas communicates with multiple communication users (CUs), each equipped with a single fluid antenna. Our objective is to maximize the minimum communication rate among all users by jointly optimizing the BS's transmit beamforming, the positions of its transmit fluid antennas, and the positions of the CUs' receive fluid antennas. To address this non-convex problem, we propose a block coordinate descent (BCD) algorithm integrating semidefinite relaxation (SDR), rank-one constraint relaxation (SRCR), successive convex approximation (SCA), and majorization-minimization (MM). Simulation results demonstrate that FAS significantly enhances system performance and robustness, with notable gains when both the BS and CUs are equipped with fluid antennas. Even under low transmit power conditions, deploying FAS at the BS alone yields substantial performance gains. However, the effectiveness of FAS depends on the availability of sufficient movement space, as space constraints may limit its benefits compared to fixed antenna strategies. Our findings highlight the potential of FAS to mitigate HIs and enhance multi-user system performance, while emphasizing the need for practical deployment considerations.

In this paper, we investigate a two-way backscatter communication system assisted by a dual-sided reconfigurable intelligent surface (RIS) which consists of active or passive elements. By altering the switch status within each RIS element, different transmission and reflection coefficients can be achieved, thus enabling a binary backscatter modulation. To begin with, we propose a maximum likelihood (ML) detector and a maximal-ratio-combining (MRC)-based detector for the proposed dual-sided RIS-assisted two-way communication system to decode the backscatter signal as well as the end-users’ respective signal. Moreover, we compare the underlying system with and without backscatter modulation at the dual-sided RIS. Subsequently, we analyze the corresponding symbol error rate (SER) and throughput to highlight the performance differences of the various communication modes under perfect channel state information (CSI) and imperfect CSI. Finally, numerical results reveal that: (1) the ML detector significantly outperforms the MRC-based detector in terms of SER and throughput; (2) the throughput performance can be significantly improved by adopting a backscatter modulation, especially in the medium and high signal-to-noise ratio regimes; (3) the phase shift of the dual-sided RIS element should be aligned with the signal to be decoded first, to guarantee an improvement in the SER performance.

In this paper, we investigate a cell-free massive multiple-input and multiple-output (MIMO)-enabled integration communication, computation, and sensing (ICCS) system, aiming to minimize the maximum overall latency to guarantee the stringent sensing requirements. We consider a two-tier offloading framework, where each multi-antenna terminal can optionally offload its local tasks to either multiple mobile-edge servers for distributed computation or the cloud server for centralized computation. The above offloading problem is formulated as a mixed-integer programming and non-convex problem, which can be decomposed into three sub-problems, namely, distributed offloading decision, beamforming design, and execution scheduling mechanism. First, the continuous relaxation and penalty-based techniques are applied to tackle the distributed offloading strategy. Then, the weighted minimum mean square error (WMMSE) and successive convex approximation (SCA)-based lower bound are utilized to design the integrated communication and sensing (ISAC) beamforming. Finally, the other resources can be judiciously scheduled to minimize the maximum latency. A rigorous convergence analysis and numerical results substantiate the effectiveness of our method. Furthermore, simulation results demonstrate the benefits of multi-point cooperation in cell-free massive MIMO-enabled ICCS and reveal the trade-off between the number of involved APs and the resulting latency, highlighting the inherent interplay among communication, sensing, and computation.

The deployment of extremely large antenna arrays (ELAAs) in extremely large-scale multiple-input multiple-output (XL-MIMO) systems introduces significant near-field effects, such as spherical wavefront propagation and spatially non-stationary (SnS) properties. When combined with the dual-wideband effects inherent to wideband systems, these phenomena fundamentally alter the channel’s sparsity patterns in the angular-delay domain, rendering existing estimation methods insufficient. To address these challenges, this paper reconsiders the channel estimation problem for wideband XL-MIMO systems. Leveraging the spatial-chirp property of array responses, we first quantitatively characterize the angular-delay domain sparsity of wideband XL-MIMO channels, revealing both global block sparsity and local common-delay sparsity. To effectively capture this structured sparsity, we then propose a novel column-wise hierarchical prior model that integrates a precision sharing mechanism and a Markov random field (MRF) structure. Building on this prior model, the channel estimation task is formulated as a multiple measurement vector (MMV)-based Bayesian inference problem. Tailored to the complex factor graph induced by this hierarchical prior, we develop a MMV-based hybrid message passing (MMV-HMP) algorithm. This algorithm performs message updates along the edges of the factor graph, and selectively applies either the variational message passing (VMP) or sum-product (SP) rules, depending on the factor-node structure and message tractability. Simulation results validate the effectiveness of the proposed column-wise hierarchical prior model through ablation studies and demonstrate that the MMV-HMP algorithm, while maintaining moderate computational complexity, consistently outperforms existing baselines which fail to capture the structured sparsity of wideband XL-MIMO channels.

Fluid antenna systems (FAS) are emerging as a transformative enabler for sixth-generation (6G) wireless communications, providing unprecedented spatial diversity through dynamic reconfiguration of antenna ports. However, the inherent spatial correlation among ports poses significant challenges for accurate analysis. Conventional models such as Jakes are analytically intractable, while oversimplified constant-correlation models fail to capture the true behavior. In this work, we address these challenges by applying the variable block-correlation model (VBCM) -- originally proposed by Ramírez-Espinosa \textit{et al.} in 2024 -- to FAS security analysis, and by developing comprehensive optimization methods to enhance analytical accuracy. We derive new closed-form expressions for average secrecy capacity (ASC) and secrecy outage probability (SOP), demonstrating that the VBCM framework achieves simulation-aligned accuracy, with relative errors consistently below $5\%$ (compared to $10$--$15\%$ for constant-correlation models). To maximize ASC, we further design two algorithms: a grid search (GS) method and a gradient descent (GD) method. Numerical results reveal that the VBCM-based approach not only provides reliable insights into FAS security performance, but also yields substantial gains -- ASC improvements exceeding $120\%$ in high-threat scenarios and $18$--$19\%$ performance enhancements for compact antenna configurations. These findings underscore the practical value of integrating VBCM into FAS security analysis and optimization, establishing it as a powerful tool for advancing 6G communication systems.

This paper investigates a design framework for sparse fluid antenna systems (FAS) enabling high-performance direction-of-arrival (DOA) estimation, particularly in challenging millimeter-wave (mmWave) environments. By ingeniously harnessing the mobility of fluid antenna (FA) elements, the proposed architectures achieve an extended range of spatial degrees of freedom (DoFs) compared to conventional fixed-position antenna (FPA) arrays. This innovation not only facilitates the seamless application of super-resolution DOA estimators but also enables robust DOA estimation, accurately localizing more sources than the number of physical antenna elements. We introduce two bespoke FA array structures and mobility strategies tailored to scenarios with aligned and misaligned received signals, respectively, demonstrating a hardware-driven approach to overcoming complexities typically addressed by intricate algorithms. A key contribution is a light-of-sight (LoS)-centric, closed-form DOA estimator, which first employs an eigenvalue-ratio test for precise LoS path number detection, followed by a polynomial root-finding procedure. This method distinctly showcases the unique advantages of FAS by simplifying the estimation process while enhancing accuracy. Numerical results compellingly verify that the proposed FA array designs and estimation techniques yield an extended DoFs range, deliver superior DOA accuracy, and maintain robustness across diverse signal conditions.

In this paper, we investigate reconfigurable intelligent surface (RIS)-assisted communication systems which involve a fixed-antenna base station (BS) and a mobile user (MU) that is equipped with fluid antenna system (FAS). Specifically, the RIS is utilized to enable communication for the user whose direct link from the base station is blocked by obstacles. We propose a comprehensive framework that provides transmission design for both static scenarios with the knowledge of channel state information (CSI) and harsh environments where CSI is hard to acquire. It leads to two approaches: a CSI-based scheme where CSI is available, and a CSI-free scheme when CSI is inaccessible. Given the complex spatial correlations in FAS, we employ block-diagonal matrix approximation and independent antenna equivalent models to simplify the derivation of outage probabilities in both cases. Based on the derived outage probabilities, we then optimize the throughput of the FAS-RIS system. For the CSI-based scheme, we first propose a gradient ascent-based algorithm to obtain a near-optimal solution. Then, to address the possible high computational complexity in the gradient algorithm, we approximate the objective function and confirm a unique optimal solution accessible through a bisection search method. For the CSI-free scheme, we apply the partial gradient ascent algorithm, reducing complexity further than full gradient algorithms. We also approximate the objective function and derive a locally optimal closed-form solution to maximize throughput. Simulation results validate the effectiveness of the proposed framework for the transmission design in FAS-RIS systems.

This paper proposes an amplitude-phase decoupling scheme for reconfigurable intelligent surface (RIS)-enabled backscatter systems, which aims to achieve the standard quadrature amplitude modulation (QAM) constellation on the harmonics by considering the amplitude-phase coupling effects in the non-linear modulation procedure. To begin with, we derive closed-form expressions of the symbol error rate (SER) and throughput of the underlying system with and without decoupling. Moreover, we formulate the maximum amplitude expression of the lthorder harmonic for the coupling amplitude-phase curve. Finally, numerical results show that the proposed amplitude-phase decoupling scheme significantly improves the system performance in terms of SER and throughput, very close to the performance of the ideal one with perfect fitting function.

Existing reconfigurable intelligent surface (RIS)-enabled symbiotic systems generally rely on a dynamic adjustment of the amplitude of the RIS’s reflection coefficient to continuously change from 0 to 1 to support the underlying symbiotic trans-missions, which is however infeasible for practical RIS hardware. To address this, we propose a novel on-off digitalized symbiotic backscatter non-orthogonal multiple access (NOMA) system that employs an on-off mechanism of the RIS’s reflecting elements. In particular, the adjustment of the on-off state of reflecting elements in batches is adaptively invoked to control the power gain of the backscatter channel, thereby changing the amplitude of backscatter signals to establish symbiotic transmissions. In order to evaluate the practicability of the proposed on-off symbiotic mechanism, an analytical expression of coexistence outage probability at high SNR has been derived. Moreover, the adjustment of RIS’s elements on-off state is discussed and extended to the scenarios of one-shot and one-by-one activation modes. Finally, representative numerical results show that when a sufficient number of reflecting elements is deployed on the RIS, our proposed on-off mechanism can fully support the symbiotic transmissions of the underlying systems.

In this paper, we propose a two-way backscatter communication system assisted by an active and passive dualsided reconfigurable intelligent surface (RIS) where the active RIS element contains an amplifier while the passive one does not. By altering the switch status within each RIS element, different transmission and reflection coefficients can be achieved, enabling a binary backscatter modulation. Moreover, a maximal-ratio-combining (MRC)-based detector is proposed to decode the backscatter signal and the end-user's signal, and the corresponding symbol error rate (SER) and throughput are subsequently analyzed. Numerical results show that by avoiding the additive thermal noise within each RIS element, passive dual-sided RISenabled communications outperform the active dual-sided RISenabled communications in terms of SER, and it is also revealed that the throughput can be significantly improved through backscatter modulation.

In frequency division duplex (FDD) massive multiple-input multiple-output (MIMO) communication systems, the base station (BS) requires channel state information (CSI) reported from user equipment (UE) for downlink precoding, which brings in significant feedback overhead. In this paper, we propose a position-based precoding method, where the precoder at the BS is directly derived from the location information of UE, without relying on channel measurement and CSI feedback. To achieve this, we devise a novel neural network (NN) structure called P2P-Net (Position-to-Precoder Net), which includes a position encoding module, an adaptive combination weight, and a refining module based on self-attention mechanism. With deep learning techniques, P2P-Net is able to learn the information about scatterers in the signal propagation environment, thereby realizing the mapping from position to precoder. Simulation results demonstrate the superiority of the proposed positionbased precoding method compared with existing feedback-based solutions in terms of spectral efficiency and communication overhead.

Fluid antenna systems (FAS) enable dynamic antenna positioning, offering new opportunities to enhance integrated sensing and communication (ISAC) performance. However, existing studies primarily focus on communication enhancement or single-target sensing, leaving multi-target scenarios underexplored. Additionally, the joint optimization of beamforming and antenna positions poses a highly non-convex problem, with traditional methods becoming impractical as the number of fluid antennas increases. To address these challenges, this letter proposes a block coordinate descent (BCD) framework integrated with a deep reinforcement learning (DRL)-based approach for intelligent antenna positioning. By leveraging the deep deterministic policy gradient (DDPG) algorithm, the proposed framework efficiently balances sensing and communication performance. Simulation results demonstrate the scalability and effectiveness of the proposed approach. Unlike traditional optimization approaches that suffer from exponential complexity growth, our DRL-based method achieves real-time decision-making with superior scalability for complex multi-target scenarios while maintaining computational efficiency.

Cognitive radio (CR) networks face significant challenges in spectrum sensing, especially under spectrum scarcity. Fluid antenna systems (FASs) can offer an unorthodox solution due to their ability to dynamically adjust antenna positions for improved channel gain. In this letter, we study an FAS-driven CR setup where a secondary user (SU) adjusts the positions of fluid antennas to detect signals from the primary user (PU). We aim to maximize the detection probability under the constraints of the false alarm probability and the received beamforming of the SU. To address this problem, we first derive a closed-form expression for the optimal detection threshold and reformulate the problem to find its solution. Then, an alternating optimization (AO) scheme is proposed to decompose the problem into several subproblems, addressing both the received beamforming and the antenna positions at the SU. The beamforming subproblem is addressed using a closed-form solution, while the fluid antenna positions are solved by successive convex approximation (SCA). Simulation results reveal that the proposed algorithm provides significant improvements over traditional fixed-position antenna (FPA) schemes in terms of spectrum sensing performance.

In frequency division duplex (FDD) massive multiple-input multiple-output (MIMO) communication systems, the base station (BS) requires channel state information (CSI) reported from user equipment (UE) for downlink precoding, which brings in significant feedback overhead. In this paper, we propose a position-based precoding method with sensing assistance to realize MIMO downlink transmission without CSI feedback from UE. By exploiting the location of UE and the information of the propagation environment provided by wireless sensing techniques, the BS is able to derive the precoder for downlink transmission. To achieve this, we devise a novel neural network (NN) structure called PS-Net (Position-based-precoding with Sensing-assistance Network), which includes an environmental feature extractor, a weight generation module, an adaptive position encoder, and a position-to-precoder mapper. Using the PS-Net, information about the scatters in the propagation environment can be extracted and fused with the UE’s location to realize position-based precoding for time-varying channels. We also propose a dedicated data augmentation method called random phase shifting to enhance the training data diversity, thus improving the generalization ability of PS-Net. Simulation results demonstrate the superiority of the proposed PS-Net compared with the existing feedback-based solutions and other position-based approaches in terms of spectral efficiency and communication overhead.

This paper characterizes the physical layer security (PLS) in a network utilizing massive multiple-input multiple-output (MIMO) for over-the-air computation (AirComp). When the direct links between the access point (AP) and the sensors are blocked, an intelligent reflecting surface (IRS) is employed to establish communication. Furthermore, the AP sends artificial noise (AN) to the eavesdropper to prevent wiretapping. We study the problem of minimizing the mean-square-error (MSE) between the original and intercepted signals subject to the transmit power constraints at the AP and the sensors, as well as how the MSE threshold hinders the eavesdropper under both perfect and imperfect channel state information (CSI). In the case of perfect CSI, obtaining a globally optimal solution for the investigated non-convex problem is challenging due to the optimization variables’ couple nature. Hence, we convert the problem into two sub-problems to obtain locally optimal solutions. One sub-problem can be solved by an exact penalty-based algorithm, while the other has a closed-form solution using the popular majorization-minimization (MM) algorithm. For the imperfect CSI, the robust beamforming optimization problem formulated is still non-convex. To address this, we harness the block coordinate descent (BCD) algorithm for alternately optimizing the variables to solve it. The results of our simulations demonstrate that the superior MSE performance exhibited by the proposed scheme.

The allocation of secure resources in non-orthogonal multiple access (NOMA) systems has gained significant recognition as a vital research focus in the realm of the Internet of Things (IoT). Previous studies have overlooked the security challenges associated with integrating NOMA with finite blocklength (FBL) transmission. Therefore, this paper examines a secure downlink NOMA system utilizing FBL transmission, which includes a base station (BS), a near user, a far user, and an external eavesdropper. We develop an optimization problem with the objective of maximizing the near user’s effective secrecy throughput, considering the secrecy rates, decoding error probabilities (DEPs), and effective secrecy throughput for both users. Notably, by meticulously defining the DEPs of the users as optimization variables, the monotonicity and concavity of these DEPs in relation to the blocklength, transmission power, and transmission rate can be established effectively. The problem is divided into two sub-problems focusing on the essential conditions for the secrecy rate of the near user, especially in scenarios where successive interference cancellation (SIC) is unsuccessful. These sub-problems are addressed using the block coordinate descent (BCD) algorithm and an exact penalty method. For comparison, the BCD algorithm is also applied to solve the optimization problem using the orthogonal multiple access (OMA) scheme. Numerical simulations confirm the effectiveness of our proposed approaches in improving secure resource allocation when NOMA is combined with FBL transmission.

As a recently proposed reconfigurable intelligent surface (RIS) architecture, active RIS has drawn considerable interest. The important feature of the active RIS is its ability to strengthen the impinging signals to mitigate the multiplicative fading effect inherent in passive RIS-aided systems. Herein, we explore the performance of an active RIS-aided uplink multi-user massive multiple-input multiple-output (MIMO) system, considering the phase noise at the RIS. Furthermore, a two-timescale scheme is utilized, where the base station (BS) beamforming is designed based on the instantaneous aggregated channel state information (CSI), while the statistical CSI is used for designing the phase shifts of the active RIS. In addition, the linear minimum mean square error (LMMSE) estimator is adopted to estimate the aggregated channel, which combines both the cascaded and direct channels. According to the estimated channel, a closedform expression for the lower bound of achievable rate is derived. Based on the theoretical expressions, the power scaling laws for the considered system are also investigated. Specifically, when each user’s transmit power is proportionally reduced by the quantity of BS antennasMor RIS elementsN, we find that the amplified thermal noise causes the lower bound of the achievable rate to approach zero asMorNtends to infinity. Moreover, an optimization approach based on a genetic algorithm (GA) is introduced to obtain the optimal phase shifts for maximizing the achievable rate. Numerical results reveal that the active RIS can greatly enhance the performance of the massive MIMO system compared to its passive counterpart.

This paper proposes a fast-decoding scheme based on the successive interference cancellation (SIC) framework for symbiotic backscatter multi-user non-orthogonal multiple access (NOMA) systems, which aims to decode the desired primary NOMA signal and the backscatter signal for the end-users in an efficient manner. Under the proposed decoding framework, we derive a closed-form expression of the coexistence outage probability (COP) with perfect SIC for the end-users over Nakagami-m fading channel. More importantly, the diversity order is determined by the bottleneck fading parameter of the two-hop backscatter channels in most general cases, but is dominated by the bottleneck fading parameter of the primary and backscatter channels in a rare special case. Due to the influence of the residual interference, the COP with imperfect SIC would converge to an error floor. Moreover, we formulate the symbiotic constraints to guarantee the minimum decoding times and a shorter decoding time than the conventional solutions, and further derive the corresponding successful fast-decoding probability at high transmit signal-to-noise ratio (SNR). The results show that by keeping a weak primary channel statistics or lowering the threshold to decode the backscatter signal, the proposed fast-decoding scheme outperforms conventional schemes in terms of decoding times.

This paper addresses the fairness issue within fluid antenna system (FAS)-assisted non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA) systems, where a single fixed-antenna base station (BS) transmits superposition-coded signals to two users, each with a single fluid antenna. We define fairness through the minimization of the maximum outage probability for the two users, under total resource constraints for both FAS-assisted NOMA and OMA systems. Specifically, in the FAS-assisted NOMA systems, we study both a special case and the general case, deriving a closed-form solution for the former and applying a bisection search method to find the optimal solution for the latter. Moreover, for the general case, we derive a locally optimal closed-form solution to achieve fairness. In the FAS-assisted OMA systems, to deal with the non-convex optimization problem with coupling of the variables in the objective function, we employ an approximation strategy to facilitate a successive convex approximation (SCA)-based algorithm, achieving locally optimal solutions for both cases. Besides, we address a more general scenario involving interference and channel estimation overheads, deriving exact users’ outage probabilities and employing a combination of bisection, one-dimensional (1D) search, and SCA algorithms to efficiently and effectively solve max-min optimization problems in both NOMA and OMA systems, significantly enhancing system fairness and computational efficiency. Our numerical results demonstrate that the proposed schemes significantly enhance outage performance over conventional OMA and NOMA benchmarks, even in the presence of interference, confirming their effectiveness in realistic scenarios. The performance of our closed-form and SCA algorithm-based solutions in FAS-assisted NOMA and OMA systems closely approaches that of the optimal solutions, further validated by the effective approximation of users’ outage probabilities in simulations.

This paper proposes a simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) segmented symbiotic backscatter non-orthogonal multiple access (NOMA) system. Specifically, the STAR-RIS is divided into an enchancing primary signal (EP) zone and a backscatter device (BD) zone. To characterize the overall transmission effectiveness, the metric of sum ergodic capacity (EC) of the considered symbiotic system is established and the corresponding suboptimal approximation solutions are derived in closed-form for three typical NOMA channel conditions. Our results show that the sum EC obeys the scaling law of $\log \left(P_{s}\right)$ where $P_{s}$ is the total transmit power, and is dominated by the weaker one of the transmission and reflection channels. Moreover, our simulation results show that both the instantaneous sum rate and the sum EC derived by the proposed suboptimal solution are very close to the optimal one obtained through exhaustive search. More importantly, the transmission effectiveness of the proposed system is superior to the STAR-RIS-assisted NOMA system and the STAR-RIS-segmented symbiotic backscatter orthogonal multiple access (OMA) system. Additionally, it is shown that as the quantification order of the imperfect channel state information (ipCSI) increases, the sum EC performance gradually improves.

This paper puts forth a proposal for a reconfigurable intelligent surface (RIS) enabled symbiotic backscatter system riding over a multiuser non-orthogonal multiple access (NOMA) carrier, where the RIS is employed as a substitute for the conventional backscatter device (BD) with the objective of enhancing both primary NOMA transmission and backscatter communications. In particular, a symbiotic mechanism is proposed to control the mutual interference by means of an adaptive adjustment of the reflection coefficient at the RIS. Moreover, a novel and effective multiuser decoding scheme is proposed, based on successive interference cancellation (SIC), with the objective of ensuring the successful transmission of the symbiotic system. To this end, analytical expressions re derived for the closed-form outage lower bounds, asymptotic outage behavior and outage error floors are derived. Furthermore, the upper bounds of the ergodic capacity and its asymptote at high signal-to-noise ratio (SNR) are developed in order to illustrate the spectral efficiency of the proposed symbiotic system. Theoretical analysis and numerical results demonstrate that a stronger backscatter channel with a greater number of elements deployed on a segmented RIS results in a reduction in transmission outage and an increase in system capacity. Additionally, numerical results illustrate the spectral efficiency advantage of the proposed symbiotic system over the conventional solutions.

This paper presents a comprehensive framework for jointly analyzing the angle estimation error and designing a three-dimensional (3D) positioning algorithm for an Internet of Things (IoT) millimeter wave (mmWave) positioning system. Initially, the azimuth and elevation angles of arrival (AoAs) at the anchors are estimated by applying the two-dimensional discrete Fourier transform (2D-DFT) algorithm. The angle estimation error is then analyzed in terms of probability density functions (PDF) by utilizing the properties of the 2D-DFT algorithm and employing challenging derivations and linear approximations. The analysis reveals that the resulting angle estimation error is non-Gaussian, distinguishing it from previous studies. Next, the complex expression of the PDF for the AoA estimation error is simplified using the first-order linear approximation of triangle functions. Subsequently, a complex expression for the variance is derived based on the obtained PDF. Specifically, the variance for the azimuth estimation error is integrated separately according to the different non-zero intervals of the obtained PDF. Additionally, the closed-form expressions of the variances are formulated using generalized hypergeometric series. Finally, the two-stage weighted least square (TSWLS) algorithm is employed to estimate the 3D position of the mobile user (MU) using the estimated AoAs and the obtained non-Gaussian variance. Extensive simulation results confirm the non-Gaussian nature of the derived angle estimation error and demonstrate the superiority of the proposed framework.

This paper proposes a novel localization algorithm using the reconfigurable intelligent surface (RIS) received signal, i.e., RIS information. Compared with BS received signal, i.e., BS information, RIS information offers higher dimension and richer feature set, thereby providing an enhanced capacity to distinguish positions of the mobile users (MUs). Additionally, we address a practical scenario where RIS contains some unknown (number and places) faulty elements that cannot receive signals. Initially, we employ transfer learning to design a two-phase transfer learning (TPTL) algorithm, designed for accurate detection of faulty elements. Then our objective is to regain the information lost from the faulty elements and reconstruct the complete high-dimensional RIS information for localization. To this end, we propose a transfer-enhanced dual-stage (TEDS) algorithm. In Stage I, we integrate the CNN and variational autoencoder (VAE) to obtain the RIS information, which in Stage II, is input to the transferred DenseNet 121 to estimate the location of the MU. To gain more insight, we propose an alternative algorithm named transfer-enhanced direct fingerprint (TEDF) algorithm which only requires the BS information. The comparison between TEDS and TEDF reveals the effectiveness of faulty element detection and the benefits of utilizing the high-dimensional RIS information for localization. Besides, our empirical results demonstrate that the performance of the localization algorithm is dominated by the high-dimensional RIS information and is robust to unoptimized phase shifts and signal-to-noise ratio (SNR).

This paper proposes a simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) segmented symbiotic backscatter non-orthogonal multiple access (NOMA) system, where the STAR-RIS is composed of an enhancing primary signal (EP) zone and a backscatter device (BD) zone. To evaluate the overall system transmission reliability, we derive a tight lower bound of the coexistence outage probability (COP), where an imperfect/realistic successive interference cancellation (SIC) is considered. It is shown analytically that the error floor of the COP in both the near field and far field coverages would appear as long as the residual interference due to SIC is non-negligible, resulting in a diversity order of zero. Such an error floor is mainly dominated by the residual interference parameters, the decoding thresholds, and the power allocation ratios. More importantly, unlike the Gamma approximation approach, the adopted Laplace approach can capture the true diversity order with perfect SIC in the near-field/far-field coverage, which is dominated by the bottleneck number of the STAR-RIS elements belonging to the EP and BD zones, regardless of the dual-hop channel statistics. In addition, it is shown that the COP performance improves with either the quantification order or the concentration parameter of the imperfect channel state information.

In this paper, to tackle the blockage issue in massive multiple-input-multiple-output (mMIMO) systems, a reconfigurable intelligent surface (RIS) is seamlessly deployed to support devices with ultra-reliable and low-latency communications (URLLC). The transmission power of the base station and the phase shifts of the RIS are jointly devised to maximize the weighted sum rate while considering the spatially correlation and channel estimation errors. Firstly, the relationship between the channel estimation error and spatially correlated RIS’s elements is revealed by using the linear minimum mean square error. Secondly, based on the maximum-ratio transmission precoding, a tight lower bound of the rate under short packet transmission is derived. Finally, the NP-hard problem is decomposed into two optimization problems, where the transmission power is obtained by geometric programming and phase shifts are designed by using gradient ascent method. Besides, we have rigorously proved that the proposed algorithm can rapidly converge to a sub-optimal solution with low complexity. Simulation results confirm the tightness between the analytic results and Monte Carlo simulations. Furthermore, the two-timescale scheme provides a practical solution for the short packet transmission.

With the increasing security concerns of the satellite network due to the broadcasting nature and the inherent openness of satellite-terrestrial communications, the satellite spectrum and terrestrial node resource trading based cooperation in cognitive satellite terrestrial networks (CSTNs) has gained a lot attention. However, the existing literature has not well considered the fairness issue in resource trading, which may cause cooperation failure between the satellite and terrestrial networks when their own benefits are impaired. To tackle this issue, in this paper we propose a two-layer hierarchical game framework for a multi-terrestrial base stations (BSs) CSTN scenario to guarantee the fairness of resource trading between the satellite and terrestrial networks and thus achieve a win-win situation for both networks. Specifically, a coalition formation game is adopted to study the cooperative behaviors among the terrestrial BSs. Herein, we propose a distributed merge-and-split based coalition formation algorithm to determine the coalition structure, of which the stability, convergence, and complexity are theoretically investigated. Moreover, a Stackelberg game is introduced to model the competition between the satellite and terrestrial BSs, where the satellite acts as the leader and the terrestrial BSs act as the followers. The Stackelberg equilibrium (SE) for the Stackelberg game is derived based on the backward induction method. We then design a distributed algorithm to obtain the coalition structure and SE for the proposed two-layer hierarchical game framework. Finally, simulations are presented to validate our theoretical results.

In this paper, the reconfigurable intelligent surface (RIS)-aided massive multiple-input-multiple-output (mMIMO) system with ultra-reliability and low latency communications (URLLC) is investigated. Specifically, the spatial correlation and imperfect channel estate information (CSI) are considered, where the phase shifts of the RIS and the transmission power of the base station (BS) are jointly optimized to maximize the weighted sum rate. Firstly, the aggregated channel is estimated relying on the linear minimum mean square error (LMMSE) method, and the normalized mean square error (NMSE) is analyzed. Secondly, the lower bound for the achievable data rate is derived for maximum-ratio transmission (MRT). Finally, the non-convex problem is separated into two optimization problems. Then, based on the statistical CSI, geometric programming and gradient descent are adopted to optimize the transmission power of the BS and the phase shifts of the RIS, respectively. Simulation results confirm the accuracy of the analytic results and the superiority of our proposed algorithm.

Magnetic induction (MI) communication in nearfield scenarios has gained much attention in recent years. From the perspective of practical applications, nearfield magnetic induction (NFMI) communication limits its application in high rate demanded scenarios. In this paper, we propose the orthogonal frequency division multiplexing (OFDM) modulated orbital angular momentum (OAM)-based NFMI communication, which is called O2N communication, to increase the channel capacity where capacity limitation is a major bottleneck problem in magnetic communication systems. The O2N communication can adaptively optimize power allocation on subcarriers in association with OAM modes, significantly increasing the spectrum utilization of frequency-selective MI systems. Numerical results verify the transmission feasibility and capacity enhancement of O2N communication over multi-input multi-output (MIMO) OFDM-based magnetic communications in the near-field region. Moreover, the impact of misalignment on the O2N communication is also evaluated. High-capacity O2N communication based on the advantages of OAM and OFDM, can effectively support NFMI communication.

Resource allocation is conceived for cell-free (CF) massive multi-input multi-output (MIMO)-aided ultra-reliable and low latency communication (URLLC) systems. Specifically, to support multiple devices with limited pilot overhead, pilot reuse among the users is considered, where we formulate a joint pilot length and pilot allocation strategy for maximizing the number of devices admitted. Then, the pilot power and transmit power are jointly optimized while simultaneously satisfying the devices’ decoding error probability, latency, and data rate requirements. Firstly, we derive the lower bounds (LBs) of ergodic data rate under finite channel blocklength (FCBL). Then, we propose a novel pilot assignment algorithm for maximizing the number of devices admitted. Based on the pilot allocation pattern advocated, the weighted sum rate (WSR) is maximized by jointly optimizing the pilot power and payload power. To tackle the resultant NP-hard problem, the original optimization problem is first simplified by sophisticated mathematical transformations, and then approximations are found for transforming the original problems into a series of subproblems in geometric programming (GP) forms that can be readily solved. Simulation results demonstrate that the proposed pilot allocation strategy is capable of significantly increasing the number of admitted devices and the proposed power allocation achieves substantial WSR performance gain.

Grant-free non-orthogonal multiple access (GF-NOMA) is a potential technique to support massive Ultra-Reliable and Low-Latency Communication (mURLLC) service. However, the dynamic resource configuration in GF-NOMA systems is challenging due to random traffics and collisions, that are unknown at the base station (BS). Meanwhile, joint consideration of the latency and reliability requirements makes the resource configuration of GF-NOMA for mURLLC more complex. To address this problem, we develop a novel learning framework for signature-based GF-NOMA in mURLLC service taking into account the multiple access signature collision, the UE detection, as well as the data decoding procedures for the K-repetition GF and the Proactive GF schemes. The goal of our learning framework is to maximize the long-term average number of successfully served users (UEs) under the latency constraint. We first perform a real-time repetition value configuration based on a double deep Q-Network (DDQN) and then propose a Cooperative Multi-Agent learning technique based DQN (CMA-DQN) to optimize the configuration of both the repetition values and the contention-transmission unit (CTU) numbers. Our results show the superior performance of CMA-DQN over the conventional load estimation-based uplink resource configuration approach (LE-URC) in heavy traffic and demonstrate its capability in dynamically configuring in long term for mURLLC service. In addition, with our learning optimization, the Proactive scheme always outperforms the K-repetition scheme in terms of the number of successfully served UEs, especially under the high backlog traffic scenario.

Smart factories need to support the simultaneous communication of multiple industrial Internet-of-Things (IIoT) devices with ultra-reliability and low-latency communication (URLLC). Meanwhile, short packet transmission for IIoT applications incurs performance loss compared to traditional long packet transmission for human-to-human communications. On the other hand, cell-free massive multiple-input and multiple-output (CF mMIMO) technology can provide uniform services for all devices by deploying distributed access points (APs). In this paper, we adopt CF mMIMO to support URLLC in a smart factory. Specifically, we first derive the lower bound (LB) on achievable uplink data rate under the finite blocklength (FBL) with imperfect channel state information (CSI) for both maximum-ratio combining (MRC) and full-pilot zero-forcing (FZF) decoders. The derived LB rates based on the MRC case have the same trends as the ergodic rate, while LB rates using the FZF decoder tightly match the ergodic rates, which means that resource allocation can be performed based on the LB data rate rather the exact ergodic data rate under FBL. The log-function method and successive convex approximation (SCA) are then used to approximately transform the non-convex weighted sum rate problem into a series of geometric program (GP) problems, and an iterative algorithm is proposed to jointly optimize the pilot and payload power allocation. Simulation results demonstrate that CF mMIMO significantly improves the average weighted sum rate (AWSR) compared to centralized mMIMO. An interesting observation is that increasing the number of devices improves the AWSR for CF mMIMO whilst the AWSR remains relatively constant for centralized mMIMO.

This paper investigates the two-timescale transmission scheme for reconfigurable intelligent surface (RIS)-aided massive multiple-input multiple-output (MIMO) systems, where the beamforming at the base station (BS) is adapted to the rapidly-changing instantaneous channel state information (CSI), while the nearly-passive beamforming at the RIS is adapted to the slowly-changing statistical CSI. Specifically, we first consider a system model with spatially independent Rician fading channels, which leads to tractable expressions and offers analytical insights on the power scaling laws and on the impact of various system parameters. Then, we analyze a more general system model with spatially correlated Rician fading channels and consider the impact of electromagnetic interference (EMI) caused by any uncontrollable sources present in the considered environment. For both case studies, we apply the linear minimum mean square error (LMMSE) estimator to estimate the aggregated channel from the users to the BS, utilize the low-complexity maximal ratio combining (MRC) detector, and derive a closed-form expression for a lower bound of the achievable rate. Besides, an accelerated gradient ascent-based algorithm is proposed for solving the minimum user rate maximization problem. Numerical results show that, in the considered setup, the spatially independent model without EMI is sufficiently accurate when the inter-distance of the RIS elements is sufficiently large and the EMI is mild. In the presence of spatial correlation, we show that an RIS can better tailor the wireless environment. Furthermore, it is shown that deploying an RIS in a massive MIMO network brings significant gains when the RIS is deployed close to the cell-edge users. On the other hand, the gains obtained by the users distributed over a large area are shown to be modest.

Realizing efficient, delay-bounded, and reliable communications for a massive number of user equipments (UEs) in massive Ultra-Reliable and Low-Latency Communications (mURLLC) is extremely challenging as it needs to simultaneously take into account the latency, reliability, and massive access requirements. To support these requirements, the third generation partnership project (3GPP) has introduced grant-free non-orthogonal multiple access (GF-NOMA) with multiple configured-grants (MCGs), where UE can choose any of these grants as soon as the data arrives. In this paper, we develop a novel learning framework for MCG-GF-NOMA systems. We first design the MCG-GF-NOMA model by characterizing each CG. We then formulate the MCG-GF-NOMA resources configuration problem taking into account three constraints. Finally, we propose a Cooperative Multi-Agent based Double Deep Q-Network (CMA-DDQN) algorithm to allocate the channel resources among MCGs to maximize the number of successful transmissions under the latency constraint. Our results show that the MCG-GF-NOMA framework can simultaneously improve the low latency and high reliability performances for mURLLC.

This paper analyzes and optimizes the reconfigurable intelligent surface (RIS)-aided massive multiple-input multiple-output (MIMO) systems with zero-forcing (ZF) detectors under imperfect channel state information (CSI). We first propose a low-overhead minimum mean square error (MMSE) channel estimator, and then derive and analyze closed-form expressions for the uplink achievable rate. Our analytical results prove that: 1) regardless of the RIS phase shift design, the rate of all users scales at least on the order of $\mathcal{O}\left( {{{\log }_2}(MN)} \right)$, where M and N are the numbers of antennas and reflecting elements, respectively; 2) by aligning the RIS phase shifts to one user, the rate of this user can at most scale on the order of $\mathcal{O}\left( {{{\log }_2}(MN)} \right)$. Furthermore, we propose a low-complexity majorization-minimization (MM)-based algorithm to optimize the sum user rate, where closed-form solutions are obtained in each iteration. Finally, simulation results validate all derived analytical results. Our simulation results also show that the maximum sum rate can be closely approached by simply aligning the RIS phase shifts to an arbitrary user.

Cascaded fading plays a vital role in backscatter communications but its effect on the transmission robustness of symbiotic backscatter system has not been well understood yet. In this paper, we investigate this effect under three symbiotic mechanisms, namely commensal, parasitic and competitive schemes. Our analysis indicates that: 1) For the commensal scheme, cascaded backscatter fading incurs an inferior outage performance of the backscatter system in comparison with the counterpart over single-hop backscatter fading; 2) For the parasitic scheme, cascaded backscatter fading leads to a superior outage performance of the primary system in comparison with the counterpart over single-hop backscatter fading; 3) For the backscatter system, regardless of single-hop or cascaded backscatter fading, the exact outage probability of the parasitic scheme overlaps with the asymptotic of the commensal scheme; 4) For the competitive scheme, as the decoding threshold of the primary system approaches zero, the asymptotic outage performance of the primary system in cascaded and single-hop backscatter fading tend to be the same; and 5) Unlike single-hop backscatter fading, as the decoding threshold of backscatter signal approaches zero, the outage probability of the competitive and parasitic schemes for the backscatter system in cascaded backscatter fading approaches that of the competitive scheme for the primary system.

Massive Ultra-Reliable and Low-Latency Communications (mURLLC), which integrates URLLC with massive access, is emerging as a new and important service class in the next generation (6G) for time-sensitive traffics and has recently received tremendous research attention. However, realizing efficient, delay-bounded, and reliable communications for a massive number of user equipments (UEs) in mURLLC, is extremely challenging as it needs to simultaneously take into account the latency, reliability, and massive access requirements. To support these requirements, the third generation partnership project (3GPP) has introduced enhanced grant-free (GF) transmission in the uplink (UL), with multiple active configured-grants (CGs) for URLLC UEs. With multiple CGs (MCG) for UL, UE can choose any of these grants as soon as the data arrives. In addition, non-orthogonal multiple access (NOMA) has been proposed to synergize with GF transmission to mitigate the serious transmission delay and network congestion problems. In this paper, we develop a novel learning framework for MCG-GF-NOMA systems with bursty traffic. We first design the MCG-GF-NOMA model by characterizing each CG using the parameters: the number of contention-transmission units (CTUs), the starting slot of each CG within a subframe, and the number of repetitions of each CG. Based on the model, the latency and reliability performances are characterized. We then formulate the MCG-GF-NOMA resources configuration problem taking into account three constraints. Finally, we propose a Cooperative Multi-Agent based Double Deep Q-Network (CMA-DDQN) algorithm to balance the allocations of the channel resources among MCGs so as to maximize the number of successful transmissions under the latency constraint. Our results show that the MCG-GF-NOMA framework can simultaneously improve the low latency and high reliability performances in massive URLLC.

This paper provides a theoretical framework for understanding the performance of reconfigurable intelligent surface (RIS)-aided massive multiple-input multiple-output (MIMO) with zero-forcing (ZF) detectors under imperfect channel state information (CSI). We first introduce a low-overhead minimum mean square error (MMSE) channel estimator, and then derive and analyze closed-form expressions for the uplink achievable rate. Our analytical results demonstrate that: 1) regardless of the RIS phase shift design, the rate of all users scales at least on the order of$\mathcal {O}\left ({\log _{2}\left ({MN}\right)}\right)$, where$M$and$N$are the numbers of antennas and reflecting elements, respectively; 2) by aligning the RIS phase shifts to one user, the rate of this user can at most scale on the order of$\mathcal {O}\left ({\log _{2}\left ({MN^{2}}\right)}\right)$; 3) either$M$or the transmit power can be reduced inversely proportional to$N$, while maintaining a given rate. Furthermore, we propose two low-complexity majorization-minimization (MM)-based algorithms to optimize the sum user rate and the minimum user rate, respectively, where closed-form solutions are obtained in each iteration. Finally, simulation results validate the accuracy of all derived analytical results. Our simulation results also show that the maximum sum rate can be closely approached by simply aligning the RIS phase shifts to an arbitrary user.

Hovering inaccuracy of unmanned aerial vehicle (UAV) degrades the performance of UAV-aided radio frequency energy transfer (RFET). Such inaccuracy arises due to positioning error and rotational motion of UAV, which lead to localization mismatch (LM) and orientation mismatch (OM). In this paper, antenna array beam steering based UAV hovering inaccuracy mitigation strategy is presented. The antenna beam does not accurately point towards the field sensor node due to rotational motion of the UAV along with pitch, roll, and yaw, which leads to deviation in the elevation angle. An analytical framework is developed to model this deviation, and its variation is estimated using the data collected through an experimental setup. Closed-form expressions of received power at the field node are obtained for the four cases arising from LM and OM. An optimization problem to estimate the optimal system parameters (transmit power, UAV hovering altitude, and antenna steering parameter) is formulated. The problem is proven to be nonconvex. Therefore, an algorithm is proposed to solve this problem. Simulation results demonstrate that the proposed framework significantly mitigates the hovering inaccuracy; compared to reported state-of-the-art the same performance can be achieved with substantially less transmit power.

Queuing delay is of essential importance in the Internet-of-Things scenarios where the buffer sizes of devices are limited. The existing cross-layer research contributions aiming at minimizing the queuing delay usually rely on either transmit power control or dynamic spectrum allocation. Bearing in mind that the transmission throughput is dependent on the distance between the transmitter and the receiver, in this context we exploit the agility of the unmanned-aerial-vehicle (UAV)-mounted base stations (BSs) for proactively adjusting the aerial BS (ABS)’s placement in accordance with wireless teletraffic dynamics. Specifically, we formulate a minimum-delay ABS placement problem for UAV-enabled networks, subject to realistic constraints on the ABS’s battery life and velocity. Its solutions are technically realized under three different assumptions in regard to the wireless teletraffic dynamics. The backward induction technique is invoked for both the scenario where the full knowledge of the wireless teletraffic dynamics is available, and for the case where only their statistical knowledge is available. In contrast, a reinforcement learning aided approach is invoked for the case when neither the exact number of arriving packets nor that of their statistical knowledge is available. The numerical results demonstrate that our proposed algorithms are capable of improving the system’s performance compared to the benchmark schemes in terms of both the average delay and of the buffer overflow probability.

5G New Radio (NR) is expected to support new ultra-reliable low-latency communication (URLLC) service targeting at supporting the small packets transmissions with very stringent latency and reliability requirements. Current Long Term Evolution (LTE) system has been designed based on grant-based (GB) (i.e., dynamic grant) random access, which can hardly support the URLLC requirements. Grant-free (GF) (i.e., configured grant) access is proposed as a feasible and promising technology to meet such requirements, especially for uplink transmissions, which effectively saves the time of requesting/waiting for a grant. While some basic GF access features have been proposed and standardized in NR Release-15, there is still much space to improve. Being proposed as 3GPP study items, three GF access schemes with Hybrid Automatic Repeat reQuest (HARQ) retransmissions including Reactive, K-repetition, and Proactive, are analyzed in this article. Specifically, we present a spatio-temporal analytical framework for the contention-based GF access analysis. Based on this framework, we define the latent access failure probability to characterize URLLC reliability and latency performances. We propose a tractable approach to derive and analyze the latent access failure probability of the typical UE under three GF HARQ schemes. Our results show that under shorter latency constraints, the Proactive scheme provides the lowest latent access failure probability, whereas, under longer latency constraints, the K-repetition scheme achieves the lowest latent access failure probability, which depends on K. If K is overestimated, the Proactive scheme provides lower latent access failure probability than the K-repetition scheme.

NarrowBand-Internet of Things (NB-IoT) is a new 3GPP radio access technology designed to provide better coverage for a massive number of low-throughput low-cost devices in delay-tolerant applications with low power consumption. To provide reliable connections with extended coverage, a repetition transmission scheme is introduced to NB-IoT during both Random Access CHannel (RACH) procedure and data transmission procedure. To avoid the difficulty in replacing the battery for IoT devices, the energy harvesting is considered as a promising solution to support energy sustainability in the NB-IoT network. In this work, we analyze RACH success probability in a self-powered NB-IoT network taking into account the repeated preamble transmissions and collisions, where each IoT device with data is active when its battery energy is sufficient to support the transmission. We model the temporal dynamics of the energy level as a birth-death process, derive the energy availability of each IoT device, and examine its dependence on the energy storage capacity and the repetition value. We show that in certain scenarios, the energy availability remains unchanged despite randomness in the energy harvesting. We also derive the exact expression for the RACH success probability of a randomly chosen IoT device under the derived energy availability, which is validated under different repetition values via simulations. We show that the repetition scheme can efficiently improve the RACH success probability in a light traffic scenario, but only slightly improves that performance with very inefficient channel resource utilization in a heavy traffic scenario.

In this paper, we propose a low-latency virtual reality (VR) delivery system where an unmanned aerial vehicle (UAV) base station (U-BS) is deployed to deliver VR content from a cloud server to multiple ground VR users. Each VR input data requested by the VR users can be either projected at the U-BS before transmission or processed locally at each user. Popular VR input data is cached at the U-BS to further reduce backhaul latency from the cloud server. For this system, we design a low-complexity iterative algorithm to minimize the maximum communications and computing latency among all VR users subject to the computing, caching and transmit power constraints, which is guaranteed to converge. Numerical results indicate that our proposed algorithm can achieve a lower latency compared to other benchmark schemes. Moreover, we observe that the maximum latency mainly comes from communication latency when the bandwidth resource is limited, while it is dominated by computing latency when computing capacity is low. In addition, we find that caching is helpful to reduce latency.

Wireless powered mobile edge computing (WP-MEC) has been recognized as a promising technique to provide both enhanced computational capability and sustainable energy supply to massive low-power wireless devices. However, its energy consumption becomes substantial, when the transmission link used for wireless energy transfer (WET) and for computation offloading is hostile. To mitigate this hindrance, we propose to employ the emerging technique of intelligent reflecting surface (IRS) in WP-MEC systems, which is capable of providing an additional link both for WET and for computation offloading. Specifically, we consider a multi-user scenario where both the WET and the computation offloading are based on orthogonal frequency-division multiplexing (OFDM) systems. Built on this model, an innovative framework is developed to minimize the energy consumption of the IRS-aided WP-MEC network, by optimizing the power allocation of the WET signals, the local computing frequencies of wireless devices, both the sub-band-device association and the power allocation used for computation offloading, as well as the IRS reflection coefficients. The major challenges of this optimization lie in the strong coupling between the settings of WET and of computing as well as the unit-modules constraint on IRS reflection coefficients. To tackle these issues, the technique of alternating optimization is invoked for decoupling the WET and computing designs, while two sets of locally optimal IRS reflection coefficients are provided for WET and for computation offloading separately relying on the successive convex approximation method. The numerical results demonstrate that our proposed scheme is capable of monumentally outperforming the conventional WP-MEC network without IRSs. Quantitatively, about 80% energy consumption reduction is attained over the conventional MEC system in a single cell, where 3 wireless devices are served via 16 sub-bands, with the aid of an IRS comprising of 50 elements.

NarrowBand-Internet of Things (NB-IoT) is a new 3GPP radio access technology designed to provide better coverage for Low Power Wide Area (LPWA) networks. To provide reliable connections with extended coverage, a repetition transmission scheme and up to three Coverage Enhancement (CE) groups are introduced into NB-IoT during both Random Access CHannel (RACH) procedure and data transmission procedure, where each CE group is configured with different repetition values and transmission resources. To characterize the RACH performance of the NB-IoT network with three CE groups, this paper develops a novel traffic-aware spatio-temporal model to analyze the RACH success probability, where both the preamble transmission outage and the collision events of each CE group jointly determine the traffic evolution and the RACH success probability. Based on this analytical model, we derive the analytical expression for the RACH success probability of a randomly chosen IoT device in each CE group over multiple time slots with different RACH schemes, including baseline, back-off (BO), access class barring (ACB), and hybrid ACB and BO schemes (ACB&BO). Our results have shown that the RACH success probabilities of the devices in three CE groups outperform that of a single CE group network but not for all the groups, which is affected by the choice of the categorizing parameters.This mathematical model and analytical framework can be applied to evaluate the performance of multiple group users of other networks with spatial separations.

In this paper, we study the resource allocation for a secure mission-critical IoT communication system with URLLC, where the security capacity formula under finite blocklength is adopted. In specific, we jointly optimize the power and channel bandwidth unit allocation to minimize the system power consumption subject to each device's security capacity requirement and total available channel bandwidth. We express the power for each device as a function of channel bandwidth unit, and equivalently transform the original problem into a channel bandwidth unit allocation problem. By relaxing the discrete variables into continuous ones, a sufficient condition when the transformed problem is a convex problem is provided. Efficient method is proposed to solve the problem. Simulation results confirm the performance advantage of our proposed algorithm over the benchmark method.

Computation off-loading in mobile edge computing (MEC) systems constitutes an efficient paradigm of supporting resource-intensive applications on mobile devices. However, the benefit of MEC cannot be fully exploited, when the communications link used for off-loading computational tasks is hostile. Fortunately, the propagation-induced impairments may be mitigated by intelligent reflecting surfaces (IRS), which are capable of enhancing both the spectral- and energy-efficiency. Specifically, an IRS comprises an IRS controller and a large number of passive reflecting elements, each of which may impose a phase shift on the incident signal, thus collaboratively improving the propagation environment. In this paper, the beneficial role of IRSs is investigated in MEC systems, where single-antenna devices may opt for off-loading a fraction of their computational tasks to the edge computing node via a multi-antenna access point with the aid of an IRS. Pertinent latency-minimization problems are formulated for both single-device and multi-device scenarios, subject to practical constraints imposed on both the edge computing capability and the IRS phase shift design. To solve this problem, the block coordinate descent (BCD) technique is invoked to decouple the original problem into two subproblems, and then the computing and communications settings are alternatively optimized using low-complexity iterative algorithms. It is demonstrated that our IRS-aided MEC system is capable of significantly outperforming the conventional MEC system operating without IRSs. Quantitatively, about 20 % computational latency reduction is achieved over the conventional MEC system in a single cell of a 300 m radius and 5 active devices, relying on a 5-antenna access point.

An intelligent reflecting surface (IRS) is invoked for enhancing the energy harvesting performance of a simultaneous wireless information and power transfer (SWIPT) aided system. Specifically, an IRS-assisted SWIPT system is considered, where a multi-antenna aided base station (BS) communicates with several multi-antenna assisted information receivers (IRs), while guaranteeing the energy harvesting requirement of the energy receivers (ERs). To maximize the weighted sum rate (WSR) of IRs, the transmit precoding (TPC) matrices of the BS and passive phase shift matrix of the IRS should be jointly optimized. To tackle this challenging optimization problem, we first adopt the classic block coordinate descent (BCD) algorithm for decoupling the original optimization problem into several subproblems and alternately optimize the TPC matrices and the phase shift matrix. For each subproblem, we provide a low-complexity iterative algorithm, which is guaranteed to converge to the Karush-Kuhn-Tucker (KKT) point of each subproblem. The BCD algorithm is rigorously proved to converge to the KKT point of the original problem. We also conceive a feasibility checking method to study its feasibility. Our extensive simulation results confirm that employing IRSs in SWIPT beneficially enhances the system performance and the proposed BCD algorithm converges rapidly, which is appealing for practical applications.

The Fourth Industrial Revolution (Industrial 4.0) is coming, and this revolution will fundamentally enhance the way factories manufacture products. The conventional wired lines connecting central controller to robots or actuators will be replaced by wireless communication networks due to its low cost of maintenance and high deployment flexibility. However, some critical industrial applications require ultra-high reliability and low latency communication (URLLC). In this paper, we advocate the adoption of massive multiple-input multiple output (MIMO) to support the wireless transmission for industrial applications as it can provide deterministic communications similar as wired lines thanks to its channel hardening effects. To reduce the latency, the channel blocklength for packet transmission is finite, which incurs transmission rate degradation and decoding error probability. Thus, conventional resource allocation for massive MIMO transmission based on Shannon capacity assuming the infinite channel blocklength is no longer optimal. We first derive the closed-form expression of lower bound (LB) of achievable uplink data rate for massive MIMO system with imperfect channel state information (CSI) for both maximum-ratio combining (MRC) and zero-forcing (ZF) receivers. Then, we propose novel low complexity algorithms to solve the achievable data rate maximization problems by jointly optimizing the pilot and payload transmission power for both MRC and ZF. Simulation results confirm the rapid convergence speed and performance advantage over the existing benchmark algorithms.

Ultra-reliable low latency communication (URLLC) is one of three primary use cases in the fifth-generation (5G) networks, and its research is still in its infancy due to its stringent and conflicting requirements in terms of extremely high reliability and low latency. To reduce latency, the channel blocklength for packet transmission is finite, which incurs transmission rate degradation and higher decoding error probability. In this case, conventional resource allocation based on Shannon capacity achieved with infinite blocklength codes is not optimal. Security is another critical issue in mission-critical internet of things (IoT) communications, and physical-layer security is a promising technique that can ensure the confidentiality for wireless communications as no additional channel uses are needed for the key exchange as in the conventional upper-layer cryptography method. This paper is the first work to study the resource allocation for a secure mission-critical IoT communication system with URLLC. Specifically, we adopt the security capacity formula under finite blocklength and consider two optimization problems: weighted throughput maximization problem and total transmit power minimization problem. Each optimization problem is non-convex and challenging to solve, and we develop efficient methods to solve each optimization problem. Simulation results confirm the fast convergence speed of our proposed algorithm and demonstrate the performance advantages over the existing benchmark algorithms.

In this paper, we propose a secure unmanned aerial vehicle (UAV) mobile edge computing (MEC) system where multiple ground users offload large computing tasks to a nearby legitimate UAV in the presence of multiple eavesdropping UAVs with imperfect locations. To enhance security, jamming signals are transmitted from both the full-duplex legitimate UAV and non-offloading ground users. For this system, we design a low-complexity iterative algorithm to maximize the minimum secrecy capacity subject to latency, minimum offloading and total power constraints. Specifically, we jointly optimize the UAV location, users' transmit power, UAV jamming power, offloading ratio, UAV computing capacity, and offloading user association. Numerical results show that our proposed algorithm significantly outperforms baseline strategies over a wide range of UAV self-interference (SI) efficiencies, locations and packet sizes of ground users. Furthermore, we show that there exists a fundamental tradeoff between the security and latency of UAV-enabled MEC systems which depends on the UAV SI efficiency and total UAV power constraints.

Intelligent reflecting surfaces (IRSs) constitute a disruptive wireless communication technique capable of creating a controllable propagation environment. In this paper, we propose to invoke an IRS at the cell boundary of multiple cells to assist the downlink transmission to cell-edge users, whilst mitigating the inter-cell interference, which is a crucial issue in multicell communication systems. We aim for maximizing the weighted sum rate (WSR) of all users through jointly optimizing the active precoding matrices at the base stations (BSs) and the phase shifts at the IRS subject to each BS's power constraint and unit modulus constraint. Both the BSs and the users are equipped with multiple antennas, which enhances the spectral efficiency by exploiting the spatial multiplexing gain. Due to the non-convexity of the problem, we first reformulate it into an equivalent one, which is solved by using the block coordinate descent (BCD) algorithm, where the precoding matrices and phase shifts are alternately optimized. The optimal precoding matrices can be obtained in closed form, when fixing the phase shifts. A pair of efficient algorithms are proposed for solving the phase shift optimization problem, namely the Majorization-Minimization (MM) Algorithm and the Complex Circle Manifold (CCM) Method. Both algorithms are guaranteed to converge to at least locally optimal solutions. We also extend the proposed algorithms to the more general multiple-IRS and network MIMO scenarios. Finally, our simulation results confirm the advantages of introducing IRSs in enhancing the cell-edge user performance.

Ultra-reliable and low-latency communication (URLLC) is one of three pillar applications defined in the fifth generation new radio (5G NR), and its research is still in its infancy due to the difficulties in guaranteeing extremely high reliability (say 10-9packet loss probability) and low latency (say 1 ms) simultaneously. In URLLC, short packet transmission is adopted to reduce latency, such that conventional Shannon's capacity formula is no longer applicable, and the achievable data rate in finite blocklength becomes a complex expression with respect to the decoding error probability and the blocklength. To provide URLLC service in a factory automation scenario, we consider that the central controller transmits different packets to a robot and an actuator, where the actuator is located far from the controller, and the robot can move between the controller and the actuator. In this scenario, we consider four fundamental downlink transmission schemes, including orthogonal multiple access (OMA), non-orthogonal multiple access (NOMA), relay-assisted, and cooperative NOMA (C-NOMA) schemes. For all these transmission schemes, we aim for jointly optimizing the blocklength and power allocation to minimize the decoding error probability of the actuator subject to the reliability requirement of the robot, the total energy constraints, as well as the latency constraints. We further develop low-complexity algorithms to address the optimization problems for each transmission scheme. For the general case with more than two devices, we also develop a low-complexity efficient algorithm for the OMA scheme. Our results show that the relay-assisted transmission significantly outperforms the OMA scheme, while the NOMA scheme performs well when the blocklength is very limited. We further show that the relay-assisted transmission has superior performance over the C-NOMA scheme due to larger feasible region of the former scheme.

NarrowBand-Internet of Things (NB-IoT) is a new 3GPP radio access technology designed to provide better coverage for Low Power Wide Area (LPWA) networks. To provide reliable connections with extended coverage, a repetition transmission scheme and up to three Coverage Enhancement (CE) groups are introduced into NB-IoT during both Random Access CHannel (RACH) procedure and data transmission procedure, where each CE group is configured with different repetition values. Rather than our previous work only modeled RACH success probability in NB-IoT networks with a single CE group, this paper develops a novel model to analyze the RACH success probabilities in NB-IoT networks with three CE groups, which allow flexible RACH configuration for each CE group. Based on this analytical model, we derive the expression for the RACH success probability of a randomly chosen IoT device in each CE group. The analytical results can also be extended to analyze multiple group users of other networks with spatial separations.

To provide reliable connections with extended coverage in NarrowBand-Internet of Things (NB-IoT), a repetition transmission scheme is introduced during both Random Access CHannel (RACH) procedure and data transmission procedure. To avoid the difficulty in replacing the battery for IoT devices, energy harvesting from natural resources is considered to be a promising solution to support energy sustainability of NB-IoT network. In this work, we analyze RACH in the self-powered NB-IoT network taking into account the repeated preamble transmission and collision using stochastic geometry. We model the temporal dynamics of the energy level as a birth-death process, and we derive the energy availability of each IoT device and examine its dependence on the energy storage capacity, the cutoff value, and the repetition value. We also derive the exact expression for the RACH success probability of NB-IoT network under time correlated interference and the energy availability, which is validated under different repetition values via practical packet evolution simulations.

Ultra-reliable and low-latency communication (URLLC) is one of three pillar applications that should be supported by the fifth generation (5G) communications. The research on this topic is still in its infancy due to the difficulties in guaranteeing extremely high reliability (say 10-9) and low latency (say 1 ms) simultaneously. The achievable data rate under the short packet transmission is a complicated function of the transmission power, the blocklength and the decoding error probability. In this paper, we consider resource allocation problem in a factory automation scenario, where the central controller aims for transniitting different packets to two devices (e.g., a robot and an actuator). Two transmission schemes are considered: orthogonal multiple access (OMA) and relay-assisted transmission. We aim to jointly optimize the blocklength and power allocation to minimize the error probability of the actuator subject to reliability requirement of the robot as well as the latency constraints. We develop low-complexity algorithms to address the optimization problems for each transmission scheme. Simulation results demonstrate that the relay-assisted transmission significantly outperforms the OMA scheme.

In recent years, communicating information using molecules via diffusion has attracted significant interest in bio-medical applications. To date, most of the studies have concentrated on point-to-point molecular communication (MC), whereas in a realistic environment, multiple MC transmitters are likely to transmit molecular messages simultaneously sharing the same propagation medium, resulting in significant performance variation of the MC system. In this type of large-scale MC system, the collective signal strength at the desired receiver can be impaired by the interference caused by other MC transmitters, which may degrade the system reliability and efficiency. This paper presents the first tractable analytical framework for the collective signal strength at a partially absorbing receiver due to the desired transmitter under the impact of a swarm of interfering transmitters in a 3D large-scale MC system using stochastic geometry. To combat the multi-user interference and the intersymbol interference (ISI) in the multi-user environment, we propose Reed-Solomon (RS) error correction coding, due to its high effectiveness in combating burst and random errors, as well as the two types of information molecule modulating scheme, where the transmitted bits are encoded using two types of information molecules at consecutive bit intervals. We derive analytical expressions for the bit error probability (BEP) of the large-scale MC system with the proposed two schemes to show their effectiveness. The results obtained using Monte Carlo simulations, match exactly with the analytical results, justifying the accuracy of the derivations. Results reveal that both schemes improve the BEP by a factor of 3-4 compared with that of a conventional MC system without using any ISI mitigation techniques. Due to the implementation simplicity, the two-type molecule encoding scheme is better than the RS error correction coding scheme, as the RS error correction coding scheme involves additional encoding and decoding process at both the transmitter and receiver nodes. Furthermore, the proposed analytical framework can be generalized to the analysis of other types of receiver designs and performance characterization in multi-user large-scale MC systems. Also, the two types of information molecule modulating scheme can be extended to M-type of information molecule modulating scheme without loss of generality.

We introduce clustered millimeter-wave (mmWave) networks with invoking non-orthogonal multiple access (NOMA) techniques, where the NOMA users are modeled as Poisson cluster processes and each cluster contains a base station (BS) located at the center. To provide realistic directional beamforming, an actual antenna array pattern is deployed at all BSs. We propose three distance-dependent user selection strategies to appraise the path loss impact on the performance of our considered networks. With the aid of such strategies, we derive tractable analytical expressions for the coverage probability and system throughput. Specifically, closed-form expressions are deduced under a sparse network assumption to improve the calculation efficiency. It theoretically demonstrates that the large antenna scale benefits the near user, while such influence for the far user is fluctuant due to the randomness of the beamforming. Moreover, the numerical results illustrate that: 1) the proposed system outperforms traditional orthogonal multiple access techniques and the commonly considered NOMA-mmWave scenarios with the random beamforming; 2) the coverage probability has a negative correlation with the variance of intra-cluster receivers; 3) 73 GHz is the best carrier frequency for the near user, and 28 GHz is the best choice for the far user; and 4) an optimal number of the antenna elements exists for maximizing the system throughput.

In recent studies, a simple non-coherent communication scheme based on energy detection is proposed in massive single-input multiple-output (SIMO) systems. Before data transmission, the transmitter sends pilots to the receiver for the purpose of estimating the channel statistics. However, this training phase unintentionally provides opportunity for a malicious jammer to attack legitimate communication. In order to secure the legitimate communication, this paper proposes a jamming detection method in non-coherent SIMO systems, in which the information of channel statistics is not required. First, the transmitter sends pilots to the receiver, then the receiver sends the conjugate of its received signal (which may contain jammer signal) back to the transmitter, where the final decision on jamming detection is made. According to the likelihood ratio test principle, two detectors based on variance and standard variance normalization are proposed. The performance analysis indicates that these two detectors are of similar detection performance but of different complexity. Furthermore, it is revealed that the probability of detection initially grows with the number of receive antennas but converges quickly then, whereas the channel statistics from the jammer to the receiver always greatly influences the performance. Finally, the numerical simulations are carried out to validate the proposed detection method.

The ultra-dense cloud radio access network (UD-CRAN), in which remote radio heads are densely deployed in the network, is considered. To reduce the channel estimation overhead, we focus on the design of robust transmit beamforming for user-centric frequency division duplex UD-CRANs, where only limited channel state information (CSI) is available. Specifically, we conceive a complete procedure for acquiring the CSI that includes two key steps: channel estimation and channel quantization. The phase ambiguity (PA) is also quantized for coherent cooperative transmission. Based on the imperfect CSI, we aim to optimize the beamforming vectors in order to minimize the total transmit power subject to the users' rate requirements and fronthaul capacity constraints. We derive the closed-form expression of the achievable data rate by exploiting the statistical properties of multiple uncertain terms. Then, we propose a low-complexity iterative algorithm for solving this problem based on the successive convex approximation technique. In each iteration, the Lagrange dual-decomposition method is employed for obtaining the optimal beamforming vector. Furthermore, a pair of low-complexity user selection algorithms is provided to guarantee the feasibility of the problem. The simulation results confirm the accuracy of our robust algorithm in terms of meeting the rate requirements. Finally, our simulation results verify that using a single bit for quantizing the PA achieves good performance.

The weighted sum-rate maximization problem of ultra-dense cloud radio access networks is considered. The user-centric clustering is adopted for reducing the complexity. To reduce the training overhead, one only needs to estimate the intra-cluster channel-state information (CSI), while only the large-scale channel gains are available outside the cluster. We first derive the rate lower bound (LB) relying on Jensen's inequality. For the special case of non-overlapping clusters, the accurate data rate expression is derived in the closed form. The simulation results show the tightness of the LB for both the overlapped and non-overlapped cases. Then, we consider an alternative problem where the actual data rate is replaced by its LB, which constitutes a non-convex optimization problem. First, the globally optimal solution is obtained by applying the high-complexity outer polyblock approximation (OPA) algorithm. Then, we invoke the reduced-complexity modified weighted minimum mean square error (WMMSE) algorithm for mitigating the deleterious effects of the realistic imperfect CSI. For the subproblem solved by each WMMSE iteration, the beamforming vectors are derived in the closed form relying on the Lagrangian dual decomposition method. Finally, our simulation results show that the modified WMMSE algorithm's performance is comparable to that of the high-complexity OPA algorithm, which outperforms other benchmark algorithms.

To estimate the molecular communication (MC) parameters (e.g., diffusion coefficient, reaction rate, and absorption rate) via observations at the transmitter and the receiver, we present an analytical framework for a diffusive MC system with a partially absorbing receiver and a general first-order chemical reaction during propagation, in both spherically asymmetric and spherically symmetric scenarios. The time-varying spatial distributions and the expected numbers of messenger molecules and their first-order reaction products inside the transmitter, as well as at the surface of the partially absorbing receiver, are derived in both scenarios, which can be simplified in the special cases of a fully absorbing receiver. Importantly, our analytical expressions are verified by particle-based simulations, which showcase the effect of the reaction rate on the transmitter and the receiver observations. The analytical results of channel impulse responses at the absorbing receiver as well as that inside the transmitter are first treated and solved for spherically asymmetric scenario in this work.

Dense deployment of small base stations (SBSs) is one of the main methods to meet the 5G data rate requirements. However, high density of independent SBSs will increase the interference within the network. To circumvent this interference, there is a need to develop self-organizing methods to manage the resources of the network. In this paper, we present a distributed power allocation algorithm based on multi-agent Q-learning in an interference-limited network. The proposed method leverages coordination through simple message passing between SBSs to achieve an optimal joint power allocation. Simulation results show the optimality of the proposed method for a two-user case.

The weighted sum rate maximization problem of ultra-dense cloud radio access networks (C-RANs) is considered, where realistic fronthaul capacity constraints are incorporated. To reduce the training overhead, pilot reuse is adopted and the transmit beamforming is designed to be robust to the channel estimation errors. In contrast to the conventional C-RAN where the remote radio heads (RRHs) coherently transmit their data symbols to the user, we consider their non-coherent transmission, where no strict phase synchronization is required. By exploiting the classic successive interference cancellation technique, we first derive the closed-form expressions of the individual data rates from each serving RRH to the user and the overall data rate for each user that is not related to their decoding order. Then, we adopt the reweighted l1-norm technique to approximate the l0-norm in the fronthaul capacity constraints as the weighted power constraints. A low-complexity algorithm based on a novel sequential convex approximation (SCA) algorithm is developed to solve the resultant optimization problem with convergence guarantee. A beneficial initialization method is proposed to find the initial points of the SCA algorithm. Our simulation results show that in the high fronthaul capacity regime, the coherent transmission is superior to the non-coherent one in terms of its weighted sum rate. However, significant performance gains can be achieved by the non-coherent transmission over the coherent one in the low fronthaul capacity regime, which is the case in ultradense C-RANs, where mmWave fronthaul links with stringent capacity requirements are employed.

This paper focuses on edge caching in dense heterogeneous cellular networks, in which small base stations (SBSs) with limited cache size store the popular contents, and massive multiple-input multiple-output (MIMO)-aided macro base stations provide wireless self-backhaul when SBSs require the non-cached contents. Our aim is to address the effects of cell load and hit probability on the successful content delivery (SCD) and present the minimum required base station density for avoiding the access overload in an arbitrary small cell and backhaul overload in an arbitrary macrocell. The achievable rate of massive MIMO backhaul without any downlink channel estimation is derived to calculate the backhaul time, and the latency is also evaluated in such networks. The analytical results confirm that hit probability needs to be appropriately selected in order to achieve SCD. The interplay between cache size and SCD is explicitly quantified. It is theoretically demonstrated that when non-cached contents are requested, the average delay of the non-cached content delivery could be comparable to the cached content delivery with the help of massive MIMO-aided self-backhaul, if the average access rate of cached content delivery is lower than that of self-backhauled content delivery. Simulation results are presented to validate our analysis.

This paper considers the unavailability of complete channel state information (CSI) in ultra-dense cloud radio access networks. The user-centric cluster is adopted to reduce the computational complexity, while the incomplete CSI is considered to reduce the heavy channel training overhead, where only large-scale inter-cluster CSI is available. Channel estimation for intra-cluster CSI is also considered, where we formulate a joint pilot allocation and user equipment (UE) selection problem to maximize the number of admitted UEs with fixed number of pilots. A novel pilot allocation algorithm is proposed by considering the multi-UE pilot interference. Then, we consider robust beam-vector optimization problem subject to UEs' data rate requirements and fronthaul capacity constraints, where the channel estimation error and incomplete inter-cluster CSI are considered. The exact data rate is difficult to obtain in closed form, and instead we conservatively replace it with its lower-bound. The resulting problem is non-convex, combinatorial, and even infeasible. A practical algorithm, based on UE selection, successive convex approximation and semi-definite relaxation approach, is proposed to solve this problem with guaranteed convergence. We strictly prove that the semidefinite relaxation is tight with probability 1. Finally, extensive simulation results are presented to show the fast convergence of our proposed algorithm and demonstrate its superiority over the existing algorithms.

In this paper, we investigate the problems of sum power minimization and sum rate maximization for multi-cell networks with non-orthogonal multiple access. Considering the sum power minimization, we obtain closed-form solutions to the optimal power allocation strategy and then successfully transform the original problem to a linear one with a much smaller size, which can be optimally solved by using the standard interference function. To solve the nonconvex sum rate maximization problem, we first prove that the power allocation problem for a single cell is a convex problem. By analyzing the Karush-Kuhn-Tucker conditions, the optimal power allocation for users in a single cell is derived in closed form. Based on the optimal solution in each cell, a distributed algorithm is accordingly proposed to acquire efficient solutions. Numerical results verify our theoretical findings showing the superiority of our solutions compared with the orthogonal frequency division multiple access and broadcast channel.

Massive multiple input multiple output (MIMO) and full duplex (FD) communication are being considered as potential candidates for the spectrum efficient 5G wireless networks. In this paper, we develop a tractable model for downlink (DL) and uplink (UL) transmission in K-tier heterogeneous cellular networks (HCNs) with massive MIMO macrocells and full duplex (FD) small cells for spectrum efficiency. In the considered HCNs, the performance of the mobile user (MU) is limited by several sources of interference, specifically due to FD nature of small cell base stations (SBSs). A stochastic geometry based model of the proposed HCNs is provided which allows to derive the DL and UL rate coverage probabilities of such a system. Monte Carlo simulations confirm the accuracy of the analytical results, while numerical results reveal that equipping large number of MIMO antennas at macro base stations (MBSs) enhances the DL rate coverage probability of a random MU in HCNs. The results show that to achieve the maximum joint DL and UL performance gain in HCNs with FD small cells, both SBSs' density and SBSs' transmit power should be optimized. Moreover, the UL performance can be improved by decreasing the SBSs receivers sensitivity and increasing the UL power control factor.

In this paper, a novel non-orthogonal multiple access (NOMA)-enabled framework for cloud-radio access networks (CRANs) is proposed. In this framework, two users are scheduled in the same resources according to NOMA; however the performance of cell-edge users is enhanced by means of coordinating beamforming. Stochastic geometry is invoked for modeling the proposed framework, where the positions of BSs follow a cluster point process. In an effort to characterize the performance of the proposed framework, simple expressions in terms of outage probability are derived for both nearby users and the cell-edge users. It is analytically demonstrated that the average beamforming gain is a liner function with respect to the number of cooperating base stations. Numerical results verify the accuracy of analysis and reveal that the proposed framework is capable of greatly enhancing the performance of cell-edge users.

This paper deals with the unavailability of full CSI in ultra-dense user-centric TDD C-RAN. To reduce the channel training overhead, we consider the incomplete CSI case, where only large-scale inter-cluster CSI is available. Channel estimation for intra-cluster CSI is also considered, where we formulate a joint pilot allocation and user equipment (UE) selection problem to maximize the number of admitted UEs with fixed number of pilots. A novel pilot allocation algorithm is proposed by considering the multi-UE pilot interference. Then, we consider robust beam-vector optimization problem subject to UEs' data rate requirements and fronthaul capacity constraints, where the channel estimation error and incomplete inter-cluster CSI are considered. Simulation results demonstrate its superiority over the existing algorithms.

One of key 5G scenarios is that device-to-device (D2D) and massive multiple-input multiple-output (MIMO) will be co-existed. However, interference in the uplink D2D underlaid massive MIMO cellular networks needs to be coordinated, due to the vast cellular and D2D transmissions. To this end, this paper introduces a spatially dynamic power control solution for mitigating the cellular-to-D2D and D2D-to-cellular interference. In particular, the proposed D2D power control policy is rather flexible including the special cases of no D2D links or using maximum transmit power. Under the considered power control, an analytical approach is developed to evaluate the spectral efficiency (SE) and energy efficiency (EE) in such networks. Thus, the exact expressions of SE and EE for a cellular user or D2D transmitter are derived, which quantify the impacts of key system parameters such as massive MIMO antennas and D2D density. Numerical results corroborate our analysis and show that the proposed power control solution can efficiently mitigate interference between the cellular and D2D tier.

In this paper, the potential benefits of applying non-orthogonal multiple access (NOMA) technique in K -tier hybrid heterogeneous networks (HetNets) is explored. A promising new transmission framework is proposed, in which NOMA is adopted in small cells and massive multiple-input multiple-output (MIMO) is employed in macro cells. For maximizing the biased average received power for mobile users, a NOMA and massive MIMO based user association scheme is developed. To evaluate the performance of the proposed framework, we first derive the analytical expressions for the coverage probability of NOMA enhanced small cells. We then examine the spectrum efficiency of the whole network by deriving exact analytical expressions for NOMA enhanced small cells and a tractable lower bound for massive MIMO enabled macro cells. Finally, we investigate the energy efficiency of the hybrid HetNets. Our results demonstrate that: 1) the coverage probability of NOMA enhanced small cells is affected to a large extent by the targeted transmit rates and power sharing coefficients of two NOMA users; 2) massive MIMO enabled macro cells are capable of significantly enhancing the spectrum efficiency by increasing the number of antennas; 3) the energy efficiency of the whole network can be greatly improved by densely deploying NOMA enhanced small cell base stations; and 4) the proposed NOMA enhanced HetNets transmission scheme has superior performance compared with the orthogonal multiple access-based HetNets.

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.

Full duplex (FD) communication has emerged as an attractive solution for increasing the network throughput, by allowing downlink (DL) and uplink (UL) transmissions in the same spectrum. However, only employing FD base stations in heterogeneous cellular networks (HCNs) cause coverage reduction, due to the DL and UL interferences as well as the residual loop interference. We, therefore, propose HCNs with half duplex massive multiuser multiple-input multiple-output macrocell base stations (MBSs) to relax the coverage reduction, and FD small cell base stations (SBSs) to improve spectrum efficiency. A tractable framework of the proposed system is presented, which allows to derive exact and asymptotic expressions for the DL and the UL rate coverage probabilities, and the DL and the UL area spectral efficiencies (ASEs). Monte Carlo simulations confirm the accuracy of the analytical results, and it is revealed that the equipping massive number of antennas at MBSs enhances the DL rate coverage probability, whereas increasing FD SBSs increases the DL and the UL ASEs. The results also demonstrate that by tuning the UL fractional power control, a desirable performance in both UL and DL can be achieved.

One of the key 5G scenarios is that device-to-device (D2D) and massive multiple-input multiple-output (MIMO) will be co-existed. However, interference in the uplink D2D underlaid massive MIMO cellular networks needs to be coordinated, due to the vast cellular and D2D transmissions. To this end, this paper introduces a spatially dynamic power control solution for mitigating the cellular-to-D2D and D2D-to-cellular interference. In particular, the proposed D2D power control policy is rather flexible, including the special cases of no D2D links or using maximum transmit power. Under the considered power control, an analytical approach is developed to evaluate the spectral efficiency (SE) and energy efficiency (EE) in such networks. Thus, the exact expressions of SE for a cellular user or D2D transmitter are derived, which quantify the impacts of key system parameters, such as massive MIMO antennas and D2D density. Moreover, the D2D scale properties are obtained, which provide the sufficient conditions for achieving the anticipated SE. Numerical results corroborate our analysis and show that the proposed power control solution can efficiently mitigate interference between the cellular and the D2D tier. The results demonstrate that there exists the optimal D2D density for maximizing the area SE of D2D tier. In addition, the achievable EE of a cellular user can be comparable with that of a D2D user.

In this paper, we consider cognitive radio networks in which energy constrained secondary users (SUs) can harvest energy from the randomly deployed power beacons. A new frame structure is proposed for the considered networks. In the considered network, a wireless power transfer model is proposed, and the closed-form expressions for the power outage probability are derived. In addition, in order to reduce the energy consumption at SUs, sub-Nyquist sampling are performed at SUs. Subsequently, compressive sensing and matrix completion techniques are invoked to recover the original signals at the fusion center by utilizing the sparsity property of spectral signals. Throughput optimizations of the secondary networks are formulated into two linear constrained problems, which aim to maximize the throughput of a single SU and the whole cooperative network, respectively. Three methods are provided to obtain the maximal throughput of secondary networks by optimizing the time slots allocation and the transmit power. Simulation results show that the maximum throughput can be improved by implementing compressive spectrum sensing in the proposed frame structure design.

In this paper, a novel non-orthogonal multiple access (NOMA) enhanced device-to-device (D2D) communication scheme is considered. Our objective is to maximize the system sum rate by optimizing subchannel and power allocation. We propose a novel solution that jointly assigns subchannels to D2D groups and allocates power to receivers in each D2D group. For the subchannel assignment, a novel algorithm based on the many-to-one two-sided matching theory is proposed for obtaining a suboptimal solution. Since the power allocation problem is nonconvex, sequential convex programming is adopted to transform the original power allocation problem to a convex one. The power allocation vector is obtained by iteratively tightening the lower bound of the original power allocation problem until convergence. Numerical results illustrate that: 1) the proposed joint subchannel and power allocation algorithm are an effective approach for obtaining near-optimal performance with acceptable complexity and 2) the NOMA enhanced D2D communication scheme is capable of achieving promising gains in terms of network sum rate and the number of accessed users, compared to a traditional OMA-based D2D communication scheme.

This paper investigates the physical layer security of non-orthogonal multiple access (NOMA) in large-scale networks with invoking stochastic geometry. Both single-antenna and multiple-antenna aided transmission scenarios are considered, where the base station (BS) communicates with randomly distributed NOMA users. In the single-antenna scenario, we adopt a protected zone around the BS to establish an eavesdropper-exclusion area with the aid of careful channel ordering of the NOMA users. In the multiple-antenna scenario, artificial noise is generated at the BS for further improving the security of a beamforming-aided system. In order to characterize the secrecy performance, we derive new exact expressions of the security outage probability for both single-antenna and multiple-antenna aided scenarios. For the single-antenna scenario, we perform secrecy diversity order analysis of the selected user pair. The analytical results derived demonstrate that the secrecy diversity order is determined by the specific user having the worse channel condition among the selected user pair. For the multiple-antenna scenario, we derive the asymptotic secrecy outage probability, when the number of transmit antennas tends to infinity. Monte Carlo simulations are provided for verifying the analytical results derived and to show that: 1) the security performance of the NOMA networks can be improved by invoking the protected zone and by generating artificial noise at the BS and 2) the asymptotic secrecy outage probability is close to the exact secrecy outage probability.

Information delivery using chemical molecules is an integral part of biology at multiple distance scales and has attracted recent interest in bioengineering and communication. The collective signal strength at the receiver (i.e., the expected number of observed molecules inside the receiver), resulting from a large number of transmitters at random distances (e.g., due to mobility), can have a major impact on the reliability and efficiency of the molecular communication system. Modeling the collective signal from multiple diffusion sources can be computationally and analytically challenging. In this paper, we present the first tractable analytical model for the collective signal strength due to randomly-placed transmitters, whose positions are modelled as a homogeneous Poisson point process in three-dimensional (3D) space. By applying stochastic geometry, we derive analytical expressions for the expected number of observed molecules at a fully absorbing receiver and a passive receiver. Our results reveal that the collective signal strength at both types of receivers increases proportionally with increasing transmitter density. The proposed framework dramatically simplifies the analysis of large-scale molecular systems in both communication and biological applications.

This paper considers the massive multiple-input multiple-output (MIMO) enabled heterogeneous cloud radio access network (C-RAN), in which both remote radio heads (RRHs) and massive MIMO macrocell base stations (BS) are deployed to potentially accomplish high throughput and energy efficiency (EE). In this network, the soft fractional frequency reuse (S-FFR) is employed to mitigate the inter-tier interference. We develop a tractable analytical approach to evaluate the throughput and EE of the entire network, which can well predict the impacts of the key system parameters such as number of macrocell BS antennas, RRH density, and S-FFR factor, etc. Our results demonstrate that massive MIMO is still a powerful tool for improving the throughput of the heterogeneous C-RAN while RRHs are capable of achieving higher EE. The impact of S-FFR on the network throughput is dependent on the density of RRHs. Furthermore, more radio resources allocated to the RRHs can greatly improve the EE of the network.

In this paper, the application of non-orthogonal multiple access (NOMA) into K-tier heterogeneous networks (HetNets) is investigated. A new promising transmission framework is proposed, in which massive multiple-input multiple-output (MIMO) is employed in macro cells and NOMA is adopted in small cells. For maximizing the biased average received power at mobile users, a massive MIMO and NOMA based user association scheme is developed. In an effort to evaluate the performance of the proposed framework, analytical expressions for the spectrum efficiency of each tier are derived using stochastic geometry. Simulation results are presented to verify the accuracy of the proposed analytical derivations and confirm that NOMA is capable of enhancing the spectrum efficiency of the network compared to the orthogonal multiple access (OMA) based HetNets.

In this paper, a novel non-orthogonal multiple access (NOMA)-based device-to-device (D2D) communications framework is proposed. A major novelty of the proposed framework is that it introduces the new concept of ``D2D group" which utilizes NOMA transmission, enabling one D2D transmitter to communicate with multiple D2D receivers simultaneously. Based on the considered framework, a resource allocation optimization problem is formulated, where multiple D2D groups are allowed to reuse the same subchannel. The objective of this work is to maximize the system sum rate by satisfying the signal-to-interference- plus-noise (SINR) constraints of both D2D and traditional cellular users. Note that the formulated problem is non-deterministic polynomial-time (NP) hard in nature, thus a novel resource allocation algorithm based on the many- to-one two-sided matching theory is proposed for obtaining a suboptimal solution. It is proved that the proposed algorithm converges to a stable state within limited number of iterations. Numerical results illustrate that: i) the proposed algorithm is an effective approach for obtaining near- optimal performance with acceptable complexity; and ii) the proposed NOMA-based D2D framework is capable of achieving promising gains over traditional orthogonal multiple access (OMA)-based D2D framework.

In this paper, we present an analytical model for a diffusive molecular communication (MC) system with a reversible adsorption receiver in a fluid environment. The time-varying spatial distribution of the information molecules under the reversible adsorption and desorption reaction at the surface of a bio-receiver is analytically characterized. Based on the spatial distribution, we derive the number of newly-adsorbed information molecules expected in any time duration. Importantly, we present a simulation framework for the proposed model that accounts for the diffusion and reversible reaction. Simulation results show the accuracy of our derived expressions, and demonstrate the positive effect of the adsorption rate and the negative effect of the desorption rate on the net number of newly-adsorbed information molecules expected. Moreover, our analytical results simplify to the special case of an absorbing receiver.

In this paper, we model and analyze the downlink (DL) wireless power transfer and uplink (UL) information transmission of K-tier heterogeneous cellular networks (HCNs). Due to the densely located BSs and universal frequency reuse between all tiers in HCNs, the typical mobile terminal (MT) is allowed to harvest energy from the serving BS by direct beamforming, as well as from the other interfering BSs. Equipped with large storage battery, the typical MT utilizes the harvested energy to provide constant transmit power for the UL information transmission. Stochastic geometry is used to model and evaluate the intrinsic relationship between the energy harvested from the BSs in the DL and the information transmission performance in the UL. To well evaluate the system performance, we derive exact expressions for the maximum transmit power at MT and the UL average ergodic rate. Our results show that the UL average ergodic rate per random MT is not significantly improved by increasing the energy conversion efficiency.

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.

This paper considers a hybrid heterogeneous network (HetNet), where macro cells adopt massive multiple-input multiple-output (MIMO), and small cells adopt millimeter wave (mmWave) transmissions. We assume that all base stations (BSs) are solely powered by the renewable energy. The implementation of these emerging techniques has a substantial effect on the user association (UA). Motivated by this, we formulate a user association problem to maximize the network utility while the power cost of each BS does not exceed the harvested energy. To solve it, a low complexity distributed UA algorithm is proposed. The results demonstrate that the proposed algorithm achieves higher throughput than the max reference signal received power (RSRP) and max signal-to-interference-plus-noise ratio (SINR) UAs. It also shows that increasing the number of antennas at the macro cell BS with more power consumption, the throughput continues to increase by using the proposed algorithm, compared to the decrease in throughput by using the existing ones. Increasing the number of mmWave BSs, mmWave BS antennas or mmWave bandwidths can significantly improve the throughput. Compared with massive MIMO macro cells, mmWave small cells play a dominant role in enhancing the throughput of the networks due to the larger bandwidths.

This study considers amplify‐and‐forward two‐way relay networks, where an energy constrained relay node harvests energy from the received radio‐frequency signal. Based on time switching receiver, they separate the energy harvesting (EH) phase and the information processing (IP) phase in time. In the EH phase, three practical wireless power transfer policies are proposed: (i) dual‐source (DS) power transfer, where both sources transfer power to the relay; (ii) single‐fixed‐source power transfer, where a fixed source transfers power to the relay; and (iii) single‐best‐source (SBS) power transfer, where a source with the strongest channel transfers power to the relay. In the IP phase, a new comparative framework of the proposed wireless power transfer policies is presented in two bi‐directional relaying protocols, known as multiple access broadcast (MABC) and time division broadcast (TDBC). To characterise the performance of the proposed policies, new analytical expressions are derived for the outage probability, the throughput, and the system energy efficiency. Numerical results corroborate the authors’ analysis and show: (i) the DS policy performs the best in terms of both outage probability and throughput among the proposed policies, (ii) the TDBC protocol achieves lower outage probability than the MABC protocol, and (iii) there exits an optimal value of EH time fraction to maximise the throughput.

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 this paper, we model and analyze the downlink (DL) wireless power transfer and uplink (UL) information transmission of K-tier heterogeneous cellular networks (HCNs) with randomly located base stations (BSs) and mobile terminals (MTs). In the DL and UL, each energy-constrained MT pairs up with its corresponding BS, which provides the maximum received power at the MT. Due to the densely located BSs and universal frequency reuse between all tiers in HCNs, the typical MT is allowed to harvest energy from the serving BS by direct beamforming as well as from the other interfering BSs. Equipped with large storage battery, the typical MT utilizes the harvested energy to provide constant transmit power for the UL information transmission. Stochastic geometry is used to model and evaluate the intrinsic relationship between the energy harvested from the BSs in the DL and the information transmission performance in the UL. To well evaluate the system performance, we first derive exact expressions for the maximum transmit power at MT, the UL outage probability, and the UL average ergodic rate per MT. As the number of BS antennas goes to infinity, we further derive asymptotic expressions for the maximum transmit power at MT, the UL outage probability, and the UL average ergodic rate per MT. Our results show that the UL outage probability per MT first decreases and then increases with increasing the time allocation factor (the fraction of time allocated to the DL), and the UL outage probability, and the UL average ergodic rate per MT, can be largely improved by using the massive antenna arrays at the BSs.

We investigate beamforming and artificial noise generation at the secondary transmitters to establish secure transmission in large scale spectrum sharing networks, where multiple noncolluding eavesdroppers attempt to intercept the secondary transmission. We develop a comprehensive analytical framework to accurately assess the secrecy performance under the primary users' quality of service constraint. Our aim is to characterize the impact of beamforming and artificial noise generation (BF&AN) on this complex large scale network. We first derive exact expressions for the average secrecy rate and the secrecy outage probability. We then derive an easy-to-evaluate asymptotic average secrecy rate and asymptotic secrecy outage probability when the number of antennas at the secondary transmitter goes to infinity. Our results show that the equal power allocation between the useful signal and artificial noise is not always the best strategy to achieve maximum average secrecy rate in large scale spectrum sharing networks. Another interesting observation is that the advantage of BF&AN over BF on the average secrecy rate is lost when the aggregate interference from the primary and secondary transmitters is strong, such that it overtakes the effect of the generated AN.

In this paper, we investigate secure device-to-device (D2D) communication in energy harvesting large-scale cognitive cellular networks. The energy constrained D2D transmitter harvests energy from multiantenna equipped power beacons (PBs), and communicates with the corresponding receiver using the spectrum of the primary base stations (BSs). We introduce a power transfer model and an information signal model to enable wireless energy harvesting and secure information transmission. In the power transfer model, three wireless power transfer (WPT) policies are proposed: 1) co-operative power beacons (CPB) power transfer, 2) best power beacon (BPB) power transfer, and 3) nearest power beacon (NPB) power transfer. To characterize the power transfer reliability of the proposed three policies, we derive new expressions for the exact power outage probability. Moreover, the analysis of the power outage probability is extended to the case when PBs are equipped with large antenna arrays. In the information signal model, we present a new comparative framework with two receiver selection schemes: 1) best receiver selection (BRS), where the receiver with the strongest channel is selected; and 2) nearest receiver selection (NRS), where the nearest receiver is selected. To assess the secrecy performance, we derive new analytical expressions for the secrecy outage probability and the secrecy throughput considering the two receiver selection schemes using the proposed WPT policies. We presented Monte carlo simulation results to corroborate our analysis and show: 1) secrecy performance improves with increasing densities of PBs and D2D receivers due to larger multiuser diversity gain; 2) CPB achieves better secrecy performance than BPB and NPB but consumes more power; and 3) BRS achieves better secrecy performance than NRS but demands more instantaneous feedback and overhead. A pivotal conclusion is reached that with increasing number of antennas at PBs, NPB offers a comparable secrecy performance to that of BPB but with a lower complexity.

This paper develops a tractable framework for exploiting the potential benefits of physical layer security in three-tier wireless sensor networks (WSNs) using stochastic geometry. In such networks, the sensing data from the remote sensors are collected by sinks with the help of access points, and the external eavesdroppers intercept the data transmissions. We focus on the secure transmission in two scenarios: 1) the active sensors transmit their sensing data to the access points and 2) the active access points forward the data to the sinks. We derive new compact expressions for the average secrecy rate in these two scenarios. We also derive a new compact expression for the overall average secrecy rate. Numerical results corroborate our analysis and show that multiple antennas at the access points can enhance the security of three-tier WSNs. Our results show that increasing the number of access points decreases the average secrecy rate between the access point and its associated sink. However, we find that increasing the number of access points first increases the overall average secrecy rate, with a critical value beyond which the overall average secrecy rate then decreases. When increasing the number of active sensors, both the average secrecy rate between the sensor and its associated access point, and the overall average secrecy rate decrease. In contrast, increasing the number of sinks improves both the average secrecy rate between the access point and its associated sink, and the overall average secrecy rate.

In this paper, we develop a tractable model for joint downlink (DL) and uplink (UL) transmission of K -tier heterogeneous cellular networks (HCNs) with simultaneous wireless information and power transfer (SWIPT) for efficient spectrum and energy utilization. In the DL, the mobile users (MUs) with power splitting receiver architecture decode information and harvest energy based on SWIPT. While in the UL, the MUs use the harvested energy for information transmission. Since cell association greatly affects the energy harvesting in the DL and the performance of wireless powered HCNs in the UL, we compare the DL and UL performance of a random MU in HCNs with nearest base station (NBS) cell association to that with maximum received power (MRP) cell association. We first derive the DL average received power for the MU with the NBS and the MRP cell associations. To evaluate the system performance, we then derive the outage probability and the average ergodic rate in the DL and UL of a random MU in HCNs with the NBS and MRP cell associations. Our results show that increasing the small cell base station (BS) density, the BS transmit power, the time allocation factor, and the energy conversion efficiency, weakly affects the DL and UL performance of both the cell associations. However, the UL performance of both the cell associations can be improved by increasing the fraction of the DL received power used for energy harvesting.

We present two physical layer secure transmission schemes for multiuser multirelay networks, where the communication from M users to the base station is assisted by direct links and by N decode-and-forward relays. In this network, we consider that a passive eavesdropper exists to overhear the transmitted information, which entails exploiting the advantages of both direct and relay links for physical layer security enhancement. To fulfill this requirement, we investigate two criteria for user and relay selection and examine the achievable secrecy performance. Criterion I performs a joint user and relay selection, while Criterion II performs separate user and relay selections, with a lower implementation complexity. We derive a tight lower bound on the secrecy outage probability for Criterion I and an accurate analytical expression for the secrecy outage probability for Criterion II. We further derive the asymptotic secrecy outage probabilities at high transmit signal-to-noise ratios and high main-to-eavesdropper ratios for both criteria. We demonstrate that the secrecy diversity order is min (MN, M + N) for Criterion I, and N for Criterion II. Finally, we present numerical and simulation results to validate the proposed analysis, and show the occurrence condition of the secrecy outage probability floor.

Wireless energy harvesting is regarded as a promising energy supply alternative for energy-constrained wireless networks. In this paper, a new wireless energy harvesting protocol is proposed for an underlay cognitive relay network with multiple primary user (PU) transceivers. In this protocol, the secondary nodes can harvest energy from the primary network (PN) while sharing the licensed spectrum of the PN. In order to assess the impact of different system parameters on the proposed network, we first derive an exact expression for the outage probability for the secondary network (SN) subject to three important power constraints: 1) the maximum transmit power at the secondary source (SS) and at the secondary relay (SR); 2) the peak interference power permitted at each PU receiver; and 3) the interference power from each PU transmitter to the SR and to the secondary destination (SD). To obtain practical design insights into the impact of different parameters on successful data transmission of the SN, we derive throughput expressions for both the delay-sensitive and the delay-tolerant transmission modes. We also derive asymptotic closed-form expressions for the outage probability and the delay-sensitive throughput and an asymptotic analytical expression for the delay-tolerant throughput as the number of PU transceivers goes to infinity. The results show that the outage probability improves when PU transmitters are located near SS and sufficiently far from SR and SD. Our results also show that when the number of PU transmitters is large, the detrimental effect of interference from PU transmitters outweighs the benefits of energy harvested from the PU transmitters.

The emerging fifth-generation (5G) wireless communication system is expected to provide higher capacity, seamless connectivity and reduced energy consumption to support data intensive multimedia applications. Simultaneous wireless information and power transfer (SWIPT) in heterogeneous cellular networks (HCNs) is a promising approach to offer efficient spectrum and energy utilization in the 5G system. In this paper, we develop a tractable model for joint uplink (UL) and downlink (DL) transmission in a K-tier HCN with SWIPT. In this model, we use the power splitting (PS) protocol where the receiver splits the received signal power in two parts for harvesting the energy and decoding the information. The harvested energy in the DL is utilized for UL information transmission. We derive the exact analytical expressions for the average received power and the outage probability for both DL and UL for the system design. Monte carlo simulations confirm the accuracy of the derived results, and numerical analysis reveal that SWIPT is a reasonably efficient technique to power the cellular users. In particular, we observe that with the increase of the picocell density, both the DL and the UL outage probability in macrocell decreases significantly. Moreover, the DL and the UL outage probability in a tier is shown to decrease with the increase of BS transmit power of its own tier.

This paper develops a tractable framework for exploiting the potential benefits of physical layer security in three-tier wireless sensor networks. In such networks, the sensing data from the remote sensors are collected by sinks with the help of access points, and the external eavesdroppers intercept the data transmissions. We adopt the stochastic geometry approach to model the random locations and spatial densities of the sensors, access points, sinks, and eavesdroppers. We focus on the secure transmission in two scenarios: i) the active sensors transmit their sensing data to the access points, and ii) the active access points forward the data to the sinks. We derive new compact expressions for the overall average secrecy rate in such networks. Numerical results corroborate our analysis and show that multiple- antenna technique at the access points can enhance the security. Our results show that the overall average secrecy rate first increases with increasing the number of access points, and there exists a critical value beyond which the overall average secrecy rate decreases with increasing the number of access points. When adding the number of active sensors, the overall average secrecy rate decreases. In contrast, increasing the number of sinks improves the overall average secrecy rate.

This paper exploits the potential of massive multiple input multiple output (MIMO) in K-tier heterogeneous cellular networks (HCNs), to enhance the data rate for 5G. In such a network, macro base stations (MBSs) are equipped with large number of antennas and support multi-user transmission. We first examine the impact of massive MIMO on user association in K-tier HCNs. Exact and asymptotic expressions for the probability of a user being associated with a macro cell or a small cell are derived. Based on the asymptotic analysis, the impacts of system parameters such as tier's density and BS transmit power on user association are explicitly identified. Furthermore, we derive the coverage probability and rate of the proposed network. Numerical results corroborate our analysis and show that the implementation of massive MIMO in macro cells can significantly enhance the performance of HCNs in terms of coverage and rate. A guideline for practical cellular deployment is reached that MBSs with large antenna arrays can decrease the demands for small cells.

In this paper, we consider a cognitive radio network in which energy constrained secondary users (SUs) can harvest energy from the randomly deployed power beacons. A new frame structure with four time slots, namely, energy harvesting, spectrum sensing, energy harvesting and data transmission is proposed. In the energy harvesting slot, a new wireless power transfer (WPT) scheme in a bounded power transfer model is proposed to enable power SUs wirelessly. Closed-form expression for the power outage probability of the proposed WPT scheme is derived. In the spectrum sensing slot, we propose to utilize the compressive sensing technique which enables sub-Nyquist sampling to further reduce the energy consumption at SUs. Throughput of the secondary network with the proposed frame structure is formulated into a nonlinear constraint problem. Three optimization methods are provided to obtain the maximal throughput of secondary network by optimizing the time slots allocation and the transmit power of SUs.

Compared to the existing lower frequency wireless power transfer, millimeter wave (mmWave) power transfer takes advantage of the high-dimensional multi-antenna and narrow beam transmission. In this paper we introduce wireless power transfer for mmWave cellular networks. Here, we consider users with large energy storage that are recharged by the mmWave base stations prior to uplink information transmission, and analyze the average harvested energy and average achievable rate. Numerical results corroborate our analysis and show that the serving base station plays a dominant role in wireless power transfer, and the contribution of the interference power from the interfering base stations is negligible, even when the interfering base stations are dense. By examining the average achievable rate in the uplink, when increasing the base station density, a transition from a noise-limited regime to an interference-limited regime is observed.

We investigate beamforming and artificial noise generation at the secondary transmitters to establish secure transmission in large scale spectrum sharing networks, where multiple non-colluding eavesdroppers attempt to intercept the secondary transmission. We develop a comprehensive analytical framework to accurately assess the secrecy performance under the primary user's quality of service constraint. Our aim is to characterize the impact of beamforming and artificial noise generation on this complex large scale network. We first derive the exact expressions for the average secrecy rate and the secrecy outage probability. Our results show that there exists an average secrecy rate wall beyond which the primary user's quality of service is violated. Interestingly, we find that different from the conventional network with fixed nodes where equal power allocation achieves near optimal average secrecy rate, the equal power allocation may not be a good option for large scale spectrum sharing networks.

In this paper, we investigate secure device-to-device (D2D) communication in energy harvesting large-scale cognitive cellular networks. The energy constrained D2D transmitter harvests energy from multi-antenna equipped power beacons (PBs), and communicates with the corresponding receiver using the spectrum of the cellular base stations (BSs). We introduce a power transfer model and an information signal model to enable wireless energy harvesting and secure information transmission. In the power transfer model, we propose a new power transfer policy, namely, best power beacon (BPB) power transfer. To characterize the power transfer reliability of the proposed policy, we derive new closed-form expressions for the exact power outage probability and the asymptotic power outage probability with large antenna arrays at PBs. In the information signal model, we present a new comparative framework with two receiver selection schemes: 1) best receiver selection (BRS), and 2) nearest receiver selection (NRS). To assess the secrecy performance, we derive new expressions for the secrecy throughput considering the two receiver selection schemes using the BPB power transfer policies. We show that secrecy performance improves with increasing densities of PBs and D2D receivers because of a larger multiuser diversity gain. A pivotal conclusion is reached that BRS achieves better secrecy performance than NRS but demands more instantaneous feedback and overhead.

A multiuser scheduling multiple-input multiple-output (MIMO) cognitive radio network (CRN) with space-time block coding (STBC) is considered in this paper, where one secondary base station (BS) communicates with one secondary user (SU) selected from K candidates. The joint impact of imperfect channel state information (CSI) in BS → SUs and BS → PU due to channel estimation errors and feedback delay on the outage performance is firstly investigated. We obtain the exact outage probability expressions for the considered network under the peak interference power IPat PU and maximum transmit power Pmat BS which cover perfect/imperfect CSI scenarios in BS → SUs and BS → PU. In addition, asymptotic expressions of outage probability in high SNR region are also derived from which we obtain several important insights into the system design. For example, only with perfect CSIs in BS → SUs, i.e., without channel estimation errors and feedback delay, the multiuser diversity can be exploited. Finally, simulation results confirm the correctness of our analysis.

In this paper, we propose cyclic prefix single carrier (CP-SC) full-duplex transmission in cooperative spectrum sharing to achieve multipath diversity gain and full-duplex spectral efficiency. Integrating full-duplex transmission into cooperative spectrum sharing systems results in two intrinsic problems: 1) the peak interference power constraint at the PUs are concurrently inflicted on the transmit power at the secondary source (SS) and the secondary relays (SRs); and 2) the residual loop interference occurs between the transmit and the receive antennas at the secondary relays. Thus, examining the effects of residual loop interference under peak interference power constraint at the primary users and maximum transmit power constraints at the SS and the SRs is a particularly challenging problem in frequency selective fading channels. To do so, we derive and quantitatively evaluate the exact and the asymptotic outage probability for several relay selection policies in frequency selective fading channels. Our results manifest that a zero diversity gain is obtained with full-duplex.

The papers in this special issue focus on the topic of location awareness for radio and networks. Localization-awareness using radio signals stands to revolutionize the fields of navigation and communication engineering. It can be utilized to great effect in the next generation of cellular networks, mining applications, health-care monitoring, transportation and intelligent highways, multi-robot applications, first responders operations, military applications, factory automation, building and environmental controls, cognitive wireless networks, commercial and social network applications, and smart spaces. A multitude of technologies can be used in location-aware radios and networks, including GNSS, RFID, cellular, UWB, WLAN, Bluetooth, cooperative localization, indoor GPS, device-free localization, IR, Radar, and UHF. The performances of these technologies are measured by their accuracy, precision, complexity, robustness, scalability, and cost. Given the many application scenarios across different disciplines, there is a clear need for a broad, up-to-date and cogent treatment of radio-based location awareness. This special issue aims to provide a comprehensive overview of the state-of-the-art in technology, regulation, and theory. It also presents a holistic view of research challenges and opportunities in the emerging areas of localization.

The papers in this special issue on location awareness will continue with the state-of-the-art in technology, regulation, and theory for the emerging field of localization. This second part issue continues from the July 2015, Part I, issue which discusses location awareness for radio and networks.

In this paper, we investigate the end-to-end performance of dual-hop proactive decode-and-forward relaying networks with Nth best relay selection in the presence of two practical deleterious effects: i) hardware impairment and ii) co-channel interference. In particular, we derive new exact and asymptotic closed-form expressions for the outage probability and average channel capacity of Nth best partial and opportunistic relay selection schemes over Rayleigh fading channels. Insightful discussions are provided. It is shown that, when the system cannot select the best relay for cooperation, the partial relay selection scheme outperforms the opportunistic method under the impact of the same co-channel interference (CCI) . In addition, without CCI but under the effect of hardware impairment, it is shown that both selection strategies have the same asymptotic channel capacity. Monte Carlo simulations are presented to corroborate our analysis.

In green communications, it is imperative to reduce the total on-grid energy consumption as well as minimize the peak on-grid energy consumption, since the large peak on-grid energy consumption will translate into the high operational expenditure (OPEX) for mobile network operators. In this paper, we consider the two-dimensional optimization to lexicographically minimize the on-grid energy consumption in heterogeneous networks (HetNets). All the base stations (BSs) therein are envisioned to be powered by both power grid and renewable energy sources, and the harvested energy can be stored in rechargeable batteries. The lexicographic minimization of on-grid energy consumption involves the optimization in both the space and time dimensions, due to the temporal and spatial dynamics of mobile traffic and green energy generation. The reasonable assumption of time scale separation allows us to decompose the problem into two sub-optimization problems without loss of optimality of the original optimization problem. We first formulate the user association optimization in space dimension via convex optimization to minimize total energy consumption through distributing the traffic across different BSs appropriately in a certain time slot. We then optimize the green energy allocation across different time slots for an individual BS to lexicographically minimize the on-grid energy consumption. To solve the optimization problem, we propose a low complexity optimal offline algorithm with infinite battery capacity by assuming non-causal green energy and traffic information. The proposed optimal offline algorithm serves as performance upper bound for evaluating practical online algorithms. We further develop some heuristic online algorithms with finite battery capacity which require only causal green energy and traffic information. The performance of the proposed optimal offline and online algorithms is evaluated by simulations.

In this paper, the impact of multiple active eavesdroppers on cooperative single carrier systems with multiple relays and multiple destinations is examined. To achieve the secrecy diversity gains in the form of opportunistic selection, a two-stage scheme is proposed for joint relay and destination selection, in which, after the selection of the relay with the minimum effective maximum signal-to-noise ratio (SNR) to a cluster of eavesdroppers, the destination that has the maximum SNR from the chosen relay is selected. To accurately assess the secrecy performance, exact and asymptotic expressions are obtained in closed form for several security metrics, including the secrecy outage probability, probability of nonzero secrecy rate, and ergodic secrecy rate in frequency selective fading. Based on the asymptotic analysis, key design parameters, such as secrecy diversity gain, secrecy array gain, secrecy multiplexing gain, and power cost, are characterized, from which new insights are drawn. In addition, it is concluded that secrecy performance limits occur when the average received power at the eavesdropper is proportional to the counterpart at the destination. In particular, for the secrecy outage probability, it is confirmed that the secrecy diversity gain collapses to zero with outage floor, whereas for the ergodic secrecy rate, it is confirmed that its slope collapses to zero with capacity ceiling.

We propose a new partial feedback scheme in multiuser relay networks (MRNs) where a source communicates with K destinations via a relay. We focus on a practical network model where orthogonal frequency division multiple access (OFDMA) is adopted in the downlink and only limited feedback overhead is supported in the uplink. For this model, we consider that the OFDMA spectrum consists of MRB resource blocks (RBs). In the proposed scheme, the destinations feed back the channel quality information (CQI) for the best MFB RBs, instead of all MRB RBs, to the source through the relay, which fulfills the requirement of feedback overhead. Considering the highly versatile Nakagami-m fading, we derive new closed-form expressions for the exact sum rate for ideal CQI feedback and quantized CQI feedback. We also derive the asymptotic sum rate expression for ideal CQI feedback. We have some new findings to understand the impact of network and channel parameters on the sum rate. First, a more scattering fading environment with a lower m decreases the sum rate for a small K, but increases the sum rate for a large K. Second, the sum rate increases as MFB approaches MRB. Third, the sum rate gap between ideal CQI feedback and quantized CQI feedback increases when MFB or K increases. Fourth, we demonstrate that the proposed partial feedback scheme achieves almost the same sum rate as the full feedback scheme for a large number of destinations.

In this paper, we propose physical layer security for cooperative cognitive radio networks (CCRNs) with relay selection in the presence of multiple primary users and multiple eavesdroppers. To be specific, we propose three relay selection schemes, namely, opportunistic relay selection (ORS), suboptimal relay selection (SoRS), and partial relay selection (PRS) for secured CCRNs, which are based on the availability of channel state information (CSI) at the receivers. For each approach, we derive exact and asymptotic expressions for the secrecy outage probability. Results show that under the assumption of perfect CSI, ORS outperforms both SoRS and PRS.

Molecular communication is set to play an important role in the design of complex biological and chemical systems. An important class of molecular communication systems is based on the timing channel, where information is encoded in the delay of the transmitted molecule - a synchronous approach. At present, a widely used modeling assumption is the perfect synchronization between the transmitter and the receiver. Unfortunately, this assumption is unlikely to hold in most practical molecular systems. To remedy this, we introduce a clock into the model - leading to the molecular timing channel with synchronization error. To quantify the behavior of this new system, we derive upper and lower bounds on the variance-constrained capacity, which we view as the step between the mean-delay and the peak-delay constrained capacity. By numerically evaluating our bounds, we obtain a key practical insight: the drift velocity of the clock links does not need to be significantly larger than the drift velocity of the information link, in order to achieve the variance-constrained capacity with perfect synchronization.

In this paper, we study the information-theoretical security of a downlink multiuser cooperative relaying network with multiple intermediate amplify-and-forward (AF) relays, where there exist multiple eavesdroppers which can overhear the message. To prevent the wiretap and strength the network security, we select one best relay and user pair, so that the selected user can receive the message from the base station assisted by the selected relay. The relay and user selection is performed by maximizing the ratio of the received signal-to-noise ratio (SNR) at the user to the eavesdroppers, which is based on both the main and eavesdropper links. For the considered system, we derive the closed-form expression of the secrecy outage probability, and provide the asymptotic expression in high main-to-eavesdropper ratio (MER) region. From the asymptotic analysis, we can find that the system diversity order is equivalent to the number of relays regardless of the number of users and eavesdroppers.

This paper exploits an amplify-and-forward (AF) two-way relaying network (TWRN), where an energy constrained relay node harvests energy with wireless power transfer. Two bidirectional protocols, multiple access broadcast (MABC) protocol and time division broadcast (TDBC) protocol, are considered. Three wireless power transfer policies, namely, dual-source (DS) power transfer; single-fixed-source (SFS) power transfer; and single-best-source (SBS) power transfer are proposed and well-designed based on time switching receiver architecture. We derive analytical expressions to determine the throughput both for delay-limited transmission and delay-tolerant transmission. Numerical results corroborate our analysis and show that MABC protocol achieves a higher throughput than TDBC protocol. An important observation is that SBS policy offers a good tradeoff between throughput and power.

In this paper, the impact of multiple eavesdroppers on cooperative single carrier systems with multiple relays and multiple destinations is examined. To achieve the secrecy diversity gains in the form of opportunistic selection, a two-stage scheme is proposed for joint relay and destination selection, in which, after the selection of the relay with the minimum effective maximum signal-to-noise ratio (SNR) to a cluster of eavesdroppers, the destination that has the maximum SNR from the chosen relay is selected. In order to accurately assess the secrecy performance, the exact and asymptotic expressions are obtained in closed-form for the ergodic secrecy rate in frequency selective fading. Based on the asymptotic analysis, key design parameters such as multiplexing gain, and power cost are characterized, from which new insights are drawn. Moreover, it is concluded that capacity ceiling occurs when the average received power at the eavesdropper is proportional to the counterpart at the destination.

We propose transmit antenna selection with receive generalized selection combining (TAS/GSC) in dual-hop cognitive decode-and-forward (DF) relay networks for reliability enhancement and interference relaxation. In this paradigm, a single antenna which maximizes the receive signal-to-noise ratio (SNR) is selected at the secondary transmitter and a subset of receive antennas with the highest SNRs are combined at the secondary receiver. To demonstrate the impact of multiple primary users on the cognitive relay network, we derive new closed-form expressions for the exact and asymptotic outage probability with TAS/GSC in the secondary network. Several important design insights are reached. We corroborate that the full diversity gain is achieved, which is entirely determined by the total number of antennas in the secondary network. The negative impact of the primary network on the secondary network is reflected in the SNR gain.

We examine the impact of transmit antenna selection with receive generalized selection combining (TAS/GSC) for cognitive decode-and-forward (DF) relaying in Nakagami-m fading channels. We select a single transmit antenna at the secondary transmitter which maximizes the receive signal-to-noise ratio (SNR) and combine a subset of receive antennas with the largest SNRs at the secondary receiver. In an effort to assess the performance, we first derive the probability density function and cumulative distribution function of the end-to-end SNR using the moment generating function. We then derive new exact closed-form expression for the ergodic capacity. More importantly, by deriving the asymptotic expression for the high SNR approximation of the ergodic capacity, we gather deep insights into the high SNR slope and the power offset. Our results show that the high SNR slope is 1/2 under the proportional interference power constraint. Under the fixed interference power constraint, the high SNR slope is zero.

In this paper, we investigate a multiuser cognitive relay network with direct source-destination links and multiple primary destinations. In this network, multiple secondary users compete to communicate with a secondary destination assisted by an amplify-and-forward (AF) relay. We take into account the availability of direct links from the secondary users to the primary and secondary destinations. For the considered system, we select one best secondary user to maximize the received signal-to-noise ratio (SNR) at the secondary destination. We first derive an accurate lower bound of the outage probability, and then provide an asymptotic expression of outage probability in high SNR region. From the lower bound and the asymptotic expressions, we obtain several insights into the system design. Numerical and simulation results are finally demonstrated to verify the proposed studies.

This paper considers transmit antenna selection (TAS) and receive generalized selection combining (GSC) for secure communication in MIMO wiretap channel, where confidential messages transmitted from an NA-antenna transmitter to an NB-antenna legitimate receiver are overheard by an NE-antenna eavesdropper. We assume that the main channel and the eavesdropper's channel undergo Nakagami-m fading with fading parameters mBand mE, respectively. In an effort to assess the secrecy performance, we present a closed-form expression for the secrecy outage probability. We then derive closed-form expressions for the secrecy outage probability at high signal-to-noise ratio (SNR) for two realistic scenarios: 1) the legitimate receiver is located close to the transmitter, and 2) the legitimate receiver and the eavesdropper are located close to the transmitter. In the first scenario, we confirm that the secrecy diversity order is mBNBNA. In the second scenario, we confirm that the secrecy diversity order collapses to zero. While this may appear discouraging at a first glance, we show that low secrecy outage probability can still be achieved.

This paper advocates physical layer security in wiretap channels with two-wave with diffuse power fading. In such a wiretap channel, we consider that confidential messages transmitted from a single antenna transmitter to an M-antenna receiver is overheard by an N-antenna eavesdropper. The receiver adopts maximal-ratio combining (MRC) to enhance transmission security, whereas the eavesdropper adopts MRC to maximize the probability of successful eavesdropping. We develop a new analytical framework to characterize the average secrecy capacity as the principal security performance metric in active eavesdropping. Specifically, we derive new closed-form expressions for the exact and asymptotic average secrecy capacity. Based on these, we determine the high signal-to-noise ratio power offset to explicitly quantify the impact of the main channel and the eavesdropper's channel on the average secrecy capacity.

We examine the impact of primary and secondary interference on opportunistic relaying in cognitive spectrum sharing networks. In particular, new closed-form exact and asymptotic expressions for the outage probability of cognitive opportunistic relaying are derived over Rayleigh and Nakagami-m fading channels. Our analysis presents revealing insights into the diversity and array gains, diversity-multiplexing tradeoff, impact of primary transceivers' positions, and the optimal position of relays. We highlight that cognitive opportunistic relaying achieves the full diversity gain which is a product of the number of relays and the minimum Nakagami-m fading parameter in the secondary network. Furthermore, we confirm that the diversity gain reduces to zero when the peak interference constraint in the secondary network is proportional to the interference power from the primary network.

A wireless energy harvesting protocol is proposed for a decode-and-forward relay- assisted secondary user (SU) network in a cognitive spectrum sharing paradigm. An expression for the outage probability of the relay-assisted cognitive network is derived subject to the following power constraints: 1) the maximum power that the source and the relay in the SU network can transmit from the harvested energy, 2) the peak interference power from the source and the relay in the SU network at the primary user (PU) network, and 3) the interference power of the PU network at the relay-assisted SU network. The results show that as the energy harvesting conversion efficiency improves, the relay- assisted network with the proposed wireless energy harvesting protocol can operate with outage probabilities below 20% for some practical applications.

This paper investigates linear precoding designs for a cooperative amplify-and-forward (AF) network with a multi-antenna relay having complete channel state information (CSI). The focus is on both orthogonal AF (OAF) and non-orthogonal AF (NAF) protocols. The precoders at the relay are derived based on the maximum ratio combining (MRC) scheme, followed by an optimal power amplification factor to maximize the end-to-end achievable rate. For OAF, it is a concave optimization problem and the closed-form solution can be obtained using Karush-Kuhn-Tucker (KKT) conditions. However, the optimization problem for NAF is non-convex and getting globally optimal solution in closed-form is more challenging. Our approach is to investigate the achievable rate in different sub-domains of the channel matrix to upper-bound the original problem by a convex optimization problem. It is then shown that the optimal solution to the power amplification factor of the original optimization problem can be obtained in closed-form. The optimal MRC-based relay precoding vector is then established. Numerical results reveal that the proposed system achieves significant end-to-end rate gains over the conventional dual-hop AF multi-antenna as well as cooperative AF single-antenna systems.

In this paper, we investigate the performance of Nth best relay selection networks with secrecy constraints where several eavesdroppers try to overhear the source message. In order to enhance the network security, a single jammer is introduced to jam the eavesdroppers. In addition, sub-optimal selection strategy is introduced to combat the malicious attempt of eavesdroppers. We derive the exact secrecy performance in terms of probability of the non-zero secrecy capacity and the secrecy outage probability of the proposed relay selection approach. Based on these expressions, the effect of several important network parameters, i.e., the number of relays and the number of eavesdroppers, as well as the quality of the relay links, jammer links, and eavesdroppers links, on the proposed network are analytically characterized.

This paper proposes relay selection to increase the physical layer security in multiuser cooperative relay networks with multiple amplify-and-forward relays, in the presence of multiple eavesdroppers. To strengthen the network security against eavesdropping attack, we present three criteria to select the best relay and user pair. Specifically, criteria I and II study the received signal-to-noise ratio (SNR) at the receivers, and perform the selection by maximizing the SNR ratio of the user to the eavesdroppers. To this end, criterion I relies on both the main and eavesdropper links, while criterion II relies on the main links only. Criterion III is the standard max-min selection criterion, which maximizes the minimum of the dual-hop channel gains of main links. For the three selection criteria, we examine the system secrecy performance by deriving the analytical expressions for the secrecy outage probability. We also derive the asymptotic analysis for the secrecy outage probability with high main-to-eavesdropper ratio. From the asymptotic analysis, an interesting observation is reached: for each criterion, the system diversity order is equivalent to the number of relays regardless of the number of users and eavesdroppers.

This paper advocates physical layer security of maximal ratio combining (MRC) in wiretap two-wave with diffuse power fading channels. In such a wiretap channel, we consider that confidential messages transmitted from a single antenna transmitter to an M-antenna receiver are overheard by an N-antenna eavesdropper. The receiver adopts MRC to maximize the probability of secure transmission, whereas the eavesdropper adopts MRC to maximize the probability of successful eavesdropping. We derive the secrecy performance for two practical scenarios: 1) the eavesdropper's channel state information (CSI) is available at the transmitter and 2) the eavesdropper's CSI is not available at the transmitter. For the first scenario, we develop a new analytical framework to characterize the average secrecy capacity as the principal security performance metric. Specifically, we derive new closed-form expressions for the exact and asymptotic average secrecy capacity. Based on these, we determine the high signal-to-noise ratio power offset to explicitly quantify the impacts of the main channel and the eavesdropper's channel on the average secrecy capacity. For the second scenario, the secrecy outage probability is the primary security performance metric. Here, we derive new closed-form expressions for the exact and asymptotic secrecy outage probability. We also derive the probability of nonzero secrecy capacity. The asymptotic secrecy outage probability explicitly indicates that the positive impact of M is reflected in the secrecy diversity order and the negative impact of N is reflected in the secrecy array gain. Motivated by this, we examine the performance gap between N and N+1 antennas based on their respective secrecy array gains.

We propose transmit antenna selection with receive generalized selection combining in dual-hop cognitive decode-and-forward relay networks with spectrum sharing for reliability enhancement and interference relaxation. In this network, a single antenna, which maximizes the receive signal-to-noise ratio (SNR) is selected at the secondary transmitter, and a subset of receive antennas with the highest SNRs is combined at the secondary receiver. To demonstrate the advantages of our proposed framework, we derive new exact closed-form expressions for the outage probability and the symbol error rate of the secondary network in Rayleigh fading. We also derive easy-to-evaluate asymptotic expressions in the high-SNR regime to gain practical insights. Several important design insights are reached. Under the proportional interference power constraint, the full diversity gain is achieved and is entirely determined by the total number of antennas available in the secondary network. This result is independent of the number of receive antennas combined and the number of primary users. The positive impact of the number of receive antennas combined and the negative impact of the number of primary users on the secondary network are showcased in the SNR gain. Under the fixed interference power constraint, error floors are displayed, and the diversity gain is lost.

In this paper, we propose a multiuser cognitive relay network, where multiple secondary sources communicate with a secondary destination through the assistance of a secondary relay in the presence of secondary direct links and multiple primary receivers. We consider the two relaying protocols of amplify-and-forward (AF) and decode-and-forward (DF), and take into account the availability of direct links from the secondary sources to the secondary destination. With this in mind, we propose an optimal solution for cognitive multiuser scheduling by selecting the optimal secondary source, which maximizes the received signal-to-noise ratio (SNR) at the secondary destination using maximal ratio combining. This is done by taking into account both the direct link and the relay link in the multiuser selection criterion. For both AF and DF relaying protocols, we first derive closed-form expressions for the outage probability and then provide the asymptotic outage probability, which determines the diversity behavior of the multiuser cognitive relay network. Finally, this paper is corroborated by representative numerical examples.

In this paper, the impact of interference from multiple licensed transceivers on cognitive underlay single-carrier systems is examined. Specifically, the situation is considered in which the secondary network is limited by three key parameters: 1) maximum transmit power at the secondary transmitter, 2) peak interference power at the primary receivers, and 3) interference power from the primary transmitters. For this cognitive underlay single-carrier system, the signal-to-interference ratio (SIR) of the secondary network is obtained for transmission over frequency-selective fading channels. Based on this, a new closed-form expression for the cumulative distribution function of the SIR is evaluated, from which the outage probability and the ergodic capacity are derived. Further insights are established by analyzing the asymptotic outage probability and the asymptotic ergodic capacity in the high-transmission-power regime. In particular, it is corroborated that the asymptotic outage diversity gain is equal to the multipath gain of the frequency-selective channel in the secondary network. The asymptotic ergodic capacity also gives new insight into the additional power cost for different network parameters while maintaining a specified target ergodic capacity. Illustrative numerical examples are presented to validate the outage probability and ergodic capacity under different interference power profiles.

This paper considers transmit antenna selection (TAS) and receive generalized selection combining (GSC) for secure communication in the multiple-input-multiple-output wiretap channel, where confidential messages transmitted from an NA-antenna transmitter to an NB-antenna legitimate receiver are overheard by an NE-antenna eavesdropper. We assume that the main channel and the eavesdropper's channel undergo Nakagami-m fading with fading parameters mB and mE, respectively. In order to assess the secrecy performance, we present a new unifying framework for the average secrecy rate and the secrecy outage probability. We first derive expressions for the probability density function and the cumulative distribution function of the signal-to-noise ratio with TAS/GSC, from which we derive exact expressions for the average secrecy rate and the secrecy outage probability. We then derive compact expressions for the asymptotic average secrecy rate and the asymptotic secrecy outage probability for two distinct scenarios: 1) the legitimate receiver is located close to the transmitter, and 2) the legitimate receiver and the eavesdropper are located close to the transmitter. For these scenarios, we present new closed-form expressions for several key performance indicators: 1) the capacity slope and the power offset of the asymptotic average secrecy rate, and 2) the secrecy diversity order and the secrecy array gain of the asymptotic secrecy outage probability. For the first scenario, we confirm that the capacity slope is one and the secrecy diversity order is mBNBNA. For the second scenario, we confirm that the capacity slope and the secrecy diversity order collapse to zero.

This paper tackles the important question of how to compensate the inherent spectrum efficiency loss in cognitive relay networks. Particularly, by considering two-way cognitive relaying, we seek to enhance the performance of the secondary network in terms of the reliability due to limited transmit power, and the spectral efficiency of the half-duplex dual-hop relay transmission. We derive new closed-form expressions for the outage probability of a cognitive relay network with two-way communications in the presence of multiple primary users. Our expressions accurately take into account the impact of the maximum allowable interference constraint at the primary users on the secondary network.

We examine the impact of clusters of primary transceivers in cognitive multiple-input multiple-output (MIMO) relay networks with underlay spectrum sharing. In such a network, we propose antenna selection as an interference-aware design to satisfy the power constraints in the primary and secondary networks. To demonstrate this, we consider transmit antenna selection with maximal ratio combining (TAS/MRC) in the primary and secondary networks. With this in mind, we derive new closed-form asymptotic expressions for the outage probability and the symbol error rate (SER) over independent Nakagami-m fading channels. Our results lead to several new fundamental insights. In particular, we highlight that TAS/MRC achieves a full diversity gain when the maximum transmit power in the secondary network is proportional to the peak interference temperature in the primary network.

In this paper, we propose two cooperative jamming protocols in two-hop amplify-and-forward (AF) wiretap channels: 1) jamming signal at the source (JSS) and 2) jamming signal at the relay (JSR). We apply optimal power allocation (OPA) between the useful signal and the jamming signal to maximize the secrecy rate for each of the protocols. A fundamental question to address is “Which cooperative jamming protocol is superior under OPA?” To this end, we evaluate the maximum secrecy rate of JSS and JSR for the general scenario of independent but not necessarily identically distributed fading with distinct average signal-to-noise ratios (SNRs) in the first hop, the second hop, and the wiretap link. We demonstrate that the strong first and second hops equally benefit the secrecy rates of JSS and JSR, when the wiretap link is weak. When the wiretap link is strong, the secrecy rate of JSR is superior to JSS.

We examine the impact of multiple primary receivers on cognitive multiple-input multiple-output (MIMO) relay networks with underlay spectrum sharing. For such a network, we propose transmit antenna selection with receive maximal-ratio combining (TAS/MRC) as an interference-aware design to satisfy the power constraints in the primary and secondary networks. To demonstrate this, we derive new closed-form expressions for the exact and asymptotic outage probability with TAS/MRC and decode-and-forward (DF) relaying over independent Nakagami-m fading channels in the primary and secondary networks. Several important design insights are reached. We find that the TAS/MRC strategy achieves a full diversity gain when the transmit power in the secondary network is proportional to the peak interference power in the primary network. Furthermore, we highlight that the diversity-multiplexing tradeoff (DMT) of TAS/MRC is independent of the primary network and entirely dependent on the secondary network.

Coordinated multipoint (CoMP) is a base station (BS) cooperation technique to boost the signal-to-noise ratio (SNR) of cell-edge users in future generation wireless networks. We propose a fixed weight CoMP downlink scheduler to reduce the packet loss probability (PLP) due to buffer overflow in BSs with finite queues. The CoMP scheduler selects a single BS to serve the associated cell-edge user with the largest weighted SNR. To meet PLP targets, we develop a simple strategy to design the packet transmission time and the scheduling weights of each BS. The network design capitalizes on our new closed-form expression for the PLP that relates three key network parameters: packet arrival rate, packet transmission time, and probability that each BS is scheduled. We compare the proposed fixed weight scheduler with an adaptive weight scheduler that requires instantaneous packet delay information. We show via analysis and simulation that the fixed weight scheduler can achieve a comparable PLP to the adaptive weight scheduler, while reducing communication overheads for the BSs.

We propose transmit antenna selection (TAS) with decode-and-forward relaying as an effective approach to reduce interference in cognitive multiple-input multiple-output (MIMO) relay networks. To demonstrate this, we derive new closed-form expressions for the exact and asymptotic outage probability of TAS/MRC with multiple antennas at the primary and secondary users. We consider underlay spectrum sharing where the secondary users (SUs) transmit in the presence of multiple primary users (PUs). We consider independent Nakagami-m fading in both the primary and secondary networks. Several important design insights are revealed. We find that TAS/MRC achieves a full diversity when the transmit power at the SUs is proportional to the peak interference power at the PUs. Furthermore, we highlight that this diversity gain is completely independent of the number of antennas at the PUs.

We propose and analyze transmit antenna selection (TAS) to enhance physical layer security in a wiretap channel with NAantennas at the transmitter, NBantennas at the receiver, and NEantennas at the eavesdropper. We focus on the practical scenario where the transmitter does not have any channel state information (CSI) of the eavesdropper's channel. The transmitter selects a single antenna that maximizes the instantaneous signal-to-noise ratio (SNR) at the receiver. The receiver and the eavesdropper employ either maximal-ratio combining (MRC) or selection combining (SC) to combine the received signals. For the proposed protocols, we derive new closed-form expressions for the probability of non-zero secrecy capacity. We consider Nakagami-m fading with non-identical fading parameters of the main channel, mB, and of the eavesdropper's channel, mE. Next, we derive new closed-form expressions for the exact secrecy outage probability, based on which the ε-outage secrecy capacity is characterized. Based on the exact expressions, we derive the asymptotic secrecy outage probability which accurately reveals the secrecy diversity order and the secrecy array gain. We confirm that the proposed protocols achieve identical secrecy diversity orders of NANBmB. An interesting conclusion is reached that this diversity order is independent of NEand mE. Furthermore, we prove that under the proposed protocols, the secrecy outage probability and the ε-outage secrecy capacity improve with increasing NA.

We propose a new scheduler for wireless multimedia relay networks (WMRNs). Our scheduler is designed to account for delay, symbol error probability (SEP), and packet loss probability (PLP) due to buffer overflow. We develop a cross-layer scheduling approach for the downlink to balance these system metrics. Our scheduler is based on a new metric which is referred to as the delay in packet scheduling (DPS). The user with the largest weighted signal-to-noise ratio is scheduled, where the weight is a function of the DPS. We then derive analytical expressions for the probability mass function (PMF) of the DPS, and the SEP of the scheduled user in Rayleigh fading. We derive an analytical approximation for the PMF of the buffer state. An analytical expression is then derived for the PLP due to buffer overflow. Our analysis is verified via simulations. We show the probability that a target DPS is met is 30% higher for our new scheme compared to the standard opportunistic equal weight scheduler, with negligible degradation in the SEP of the scheduled user. This can lead to a 85% improvement in the PLP.

In this paper, maximal-ratio combining (MRC) and selection combining (SC) are proposed in spectrum sharing single-carrier networks with multiple primary user receivers (PU-Rxs). Taking into account the peak interference power at the PU-Rx's and the maximum transmit power at the secondary user (SU), the impact of multiple PU-Rx's on the secondary network is characterized when the secondary user receiver (SU-Rx) is equipped with multiple antennas. In doing so, exact and asymptotic expressions are derived for the cumulative distribution function, taking into account two realistic scenarios: non-identical frequency selective fading between the secondary user transmitter (SU-Tx) and the PUs, and frequency selective fading between the SU-Tx and the SU-Rx. Based on these, exact and asymptotic expressions for the outage probability and average bit error rate are derived. Furthermore, an exact closed-form expression for the ergodic capacity is derived. It is shown that the asymptotic diversity gain depends only on the number of receive antennas and the number of multipath channels. It is further shown that the number of PU-Rx's and fading severities between the SU-Tx and the PU-Rx's have no impact on the asymptotic diversity gain.

We propose and analyze transmit antenna selection (TAS) to enhance physical layer security in a wiretap channel with multiple antennas at the transmitter, the receiver, and the eavesdropper. We consider the practical scenario of passive eavesdropping, where the transmitter does not have any channel state information (CSI) of the eavesdropper's channel. In the main channel between the transmitter and the receiver, we select a single antenna at the transmitter that maximizes the instantaneous signal-to-noise ratio (SNR) at the receiver. At the receiver and the eavesdropper, we consider two combining techniques: 1) maximal-ratio combining (MRC) and 2) selection combining (SC). For non-identical Rayleigh fading between the main channel and the eavesdropper's channel, we first derive new closed-form expressions for the exact and asymptotic secrecy outage probabilities. The asymptotic results accurately reveal the secrecy diversity order and the secrecy array gain. Next, we derive new closed-form expressions for the probability of positive secrecy and characterize the ε-outage secrecy capacity. We show that, under TAS/MRC and TAS/SC protocols, the secrecy outage probability approaches zero and the ε-outage secrecy capacity increases with increasing number of transmitter antennas.

This paper investigates the outage performance of dual-hop decode-and-forward (DF) cooperative spectrum sharing systems in the presence of multiple primary user (PU) receivers and multiple secondary user (SU) destinations. Our analysis allows for a general Nakagami-m fading environment where distinct fading parameters as well as unequal average fading powers between the interference and relaying links are assumed. Focusing on the cooperation process among the SU nodes and making use of the underlay cognitive approach, an exact closed-form expression for the outage probability is derived. Our analysis employs an opportunistic scheduling algorithm for selecting one out of L SU destinations available. Additional interference constraints are also considered due to the presence of multiple PU receivers. The effects of fading severity, SU relay placement, and number of PU receivers, and SU destinations on the end-to-end system performance are examined through some representative numerical plots. Monte Carlo simulation results are presented to corroborate the proposed analysis.

Cooperative multiplexing has the potential to double the achievable throughput by allowing the base station (BS) and the relay station (RS) to transmit to different users at the same time in the second time slot of the half time division duplexed (TDD) relay transmission. This throughput improvement comes at a cost of performance degradation due to inter-user interference between the BS and the RS. To overcome this degradation, we propose cooperative multiplexing optimum combining (CMOC) for the relay-link users. The proposed CMOC receiver combines the signals in the first and second time slot of the half TDD transmission such that the output signal-to-interference-plus-noise ratio (SINR) is maximized. New insights are drawn from our exact closed-form expressions of SINR distributions. Based on these, we present new analytical expressions for the outage probability, symbol error rate, and achievable throughput. Our results show a 3.5 times improvement in the achievable throughput relative to the standard single-channel receiver in the high interference regime.

We examine transmit antenna selection with receiver maximal-ratio combining (TAS/MRC) and transmit antenna selection with receiver selection combining (TAS/SC) in multiple-input multiple-output (MIMO) relay networks. Amongst L two-hop relay links, a single relay offering the highest end-to-end signal-to-noise ratio (SNR) is activated. Assuming independent non-identically distributed Weibull fading between the hops, new closed-form asymptotic expressions for the outage probability and the symbol error rate are derived considering NS, NR, and NDantennas at the source, the relays, and the destination, respectively. Based on such expressions, the diversity order and the array gain for M-ary phase shift keying and M-ary quadrature amplitude modulation are analyzed. We highlight that the diversity order of TAS/MRC is the same as TAS/SC. As such, we explicitly characterize the SNR gap between TAS/MRC and TAS/SC as the ratio of their respective array gains. An interesting observation is reached that for equal per-hop SNRs, the SNR gap between the two protocols is independent of L.

We propose and analyze two MIMO protocols with analog network coding (ANC) in two-way amplify-and-forward (AF) relaying where multi-antenna nodes communicate via a single antenna relay. Specifically, we present a new framework for the comparative analysis of beamforming and antenna selection in two-way relaying with non-identical Rayleigh fading between the hops. To facilitate the comparison, we derive new closed-form expressions for the exact and asymptotic sum symbol error rate (SSER). We show that beamforming and antenna selection offer the same diversity order of min{NA, NB}, where NA and NB are the number of antennas at the two nodes. We proceed to characterize the fundamental difference between the two protocols in terms of their array gains. A pivotal conclusion is reached that when either of the two nodes is equipped with a single antenna, antenna selection provides identical performance to beamforming at medium and high signal-to-noise ratios without the added hardware and signaling overhead.

We examine the impact of multiple primary transmitters and receivers (PU-TxRx) on the outage performance of cognitive decode-and-forward relay networks. In such a joint relaying/spectrum-sharing arrangement, we address fundamental questions concerning three key power constraints: 1) maximum transmit power at the secondary transmitter (SU-Tx), 2) peak interference power at the primary receivers (PU-Rx), and 3) interference power at SU-Rx caused by the primary transmitter (PU-Tx). Our answers to these are given in new analytical expressions for the exact and asymptotic outage probability of the secondary relay network. Based on our asymptotic expressions, important design insights into the impact of primary transceivers on the performance of cognitive relay networks is reached. We have shown that zero diversity order is attained when the peak interference power at the PU-Rx is independent of the maximum transmit power at the SU-Tx.

In this letter, we investigate the effect of feedback delay on the performance of a dual-hop amplify-and-forward (AF) relay network with beamforming in the presence of multiple interferers over Rayleigh fading channels. Specifically, we derive closed-form expressions for the outage probability (OP) and the symbol error rate (SER). Furthermore, to render insights into the effect of feedback delay and interference on the network performance, asymptotic OP and SER are also presented. These asymptotic expressions are very tight in the high signal-to-noise ratio regime, readily enabling us to obtain the diversity and coding gains of the considered network.

This paper proposes a low complexity protocol that preserves full diversity in multiuser amplify-and-forward relay networks with NSantennas at the source, NRantennas at the relay, and NDantennas at each of the K destinations. In the proposed protocol, a two-fold diversity is guaranteed: 1) multi-antenna diversity via transmit antenna selection with maximal-ratio combining (TAS/MRC), and 2) multiuser diversity via opportunistic scheduling. Under perfect feedback with precise channel state information (CSI), we derive new exact and asymptotic symbol error rate (SER) expressions in closed-form for the general case of Nakagami-m fading. We prove that the full diversity order of NSNDKmX+ min{NSNRmY, NRNDKmZ} is guaranteed, where mX, mY, and mZdenote the fading parameters of the source-destination, source-relay, and relay-destination links, respectively. To examine the impact of delayed feedback, we next derive new exact and asymptotic SER expressions in closed-form. We prove that in the presence of delayed feedback, outdated CSI degrades the diversity order to NDmX+ min{NRmY, NDmZ}. In addition, based on our asymptotic expressions, we determine the optimal power allocation between the source and the relay such that the SER is minimized. We show that optimal power allocation offers superior performance over uniform power allocation; highlighting a pivotal design choice for maximizing network performance without investing additional resources.

We propose cascaded transmit antenna selection with maximal-ratio combining (TAS/MRC) for use in multiuser relay networks (MRN) with NS, NR, and NDantennas at the source, the relay, and each of the K destinations, respectively. We consider opportunistic scheduling where the destination with the highest instantaneous end-to-end signal-to-noise ratio (SNR) is scheduled for transmission. In cascaded TAS/MRC, a single transmit antenna that maximizes the instantaneous received SNR in each hop is selected, and all the receive antennas are MRC combined. We derive new exact closed-form statistics of the end-to-end SNR, from which we derive the exact and the approximate symbol error rate (SER) for M-ary quadrature amplitude modulation (M-QAM) and M-ary phase-shift keying (M-PSK). New concise expressions are derived to characterize the diversity order and the array gain. We highlight that our proposed scheme attains the maximum diversity order of NR× min{NS, NDK}. Furthermore, we determine the optimal power assignment at the source and the relay that minimizes the SER.

We propose transmit antenna selection with maximal-ratio combining (TAS/MRC) for use in multiple-input-multiple-output (MIMO) multiuser relay networks (MRN). The network under consideration is equipped with NS, NR, and NDantennas at the source, the relay, and each of the K destinations, respectively. For this network, the destination with the highest instantaneous end-to-end signal-to-noise ratio (SNR) is scheduled for transmission. In each hop, a single transmit antenna that maximizes the post-processing SNR is selected, while all the receive antennas are MRC combined. We first derive new closed-form expressions for the outage probability and the symbol error rate (SER) for amplify-and-forward (AaF) relaying. Next, we present compact and easy-to-compute expressions for the diversity order and the array gain to provide practical insights into the network behavior. We highlight the fact that our proposed scheme attains the maximum diversity order of NR× min{NS,NDK}.

This paper proposes multiple-input multiple-output (MIMO) transmission in fixed gain amplify-and-forward relaying to allow for high data rate coverage in wireless distributed networks. We consider a hierarchical network architecture in which the relay is a multiple antenna static node assisting single antenna mobile nodes. We derive new exact closed-form expressions for the outage probability and the symbol error rate (SER) valid for arbitrary N antennas at the relay under independent but not necessarily identically distributed (i.n.d.) Rayleigh fading. Our solutions apply to general operating scenarios with distinct average received signal-to-noise ratios (SNRs) throughout the network. Based on these, we derive new concise asymptotic expressions which accurately characterizes the outage probability and the SER in the high SNR regime. In our asymptotic solutions, we present an exact expression for the array gain in terms of the average received SNRs and the number of antennas N. We further show that the maximum achievable diversity order is N+1.

We present new statistical properties of the end-to-end signal-to-noise ratio (SNR) in multiple-input multiple-output (MIMO) relaying with distributed transmit antenna selection and receiver maximal-ratio combining (TAS/MRC). In particular, we derive new expressions for the exact and the first order expansions of the cumulative distribution function (cdf). Based on these, new closed-form expressions are derived for the exact and the first order expansions of the moment generating function (mgf). We then present a new concise expression for the symbol error rate (SER) with M-ary phase-shift keying in the high SNR regime. Our asymptotic SER expression explicitly reveals the diversity order and the array gain of the MIMO relay network.

We propose opportunistic scheduling with cooperative selection diversity (CSD) in wireless multiuser relay networks (MRN). In this policy, the destination with the highest instantaneous end-to-end signal-to-noise ratio (SNR), either directly from the source or indirectly through the relay, is scheduled for transmission. For the practical case of unbalanced Nakagami-m fading channels, we derive new exact closed-form expressions for the outage probability and the symbol error rate (SER) for amplify-and-forward (AaF) relaying. Next, we quantify the asymptotic network behavior in the low SER regime by presenting concise expressions for the diversity order and the array gain. We demonstrate that our two-step policy achieves the maximum diversity order. We further prove that both the diversity order and the array gain are jointly influenced by the direct link and the weaker hop of the relay link.

Distributed transmit antenna selection with maximal-ratio combining (TAS/MRC) is proposed for use in multiple-input multiple-output (MIMO) multiuser relay networks (MRN), where NS, NR, and NDantennas are equipped at the source, the relay, and each of the K destinations, respectively. For such networks, the destination with the highest instantaneous end-to-end signal-to-noise ratio (SNR) is scheduled for transmission. In each hop, a single transmit antenna that maximizes the post-processing SNR is selected, while all the receive antennas are MRC combined. New exact closed-form expressions are derived for the cumulative distribution function (CDF), the probability density function (PDF), and the moment generating function (MGF) of the highest instantaneous end-to-end SNR. Based on these, we determine the symbol error rate with M-ary phase-shift keying. Our derived results apply to general operating scenarios with arbitrary number of antennas, arbitrary number of destinations, and distinct average SNRs.

This letter advocates the performance of a multiuser relay network (MRN) equipped with a single amplify-and-forward (AaF) relay over Rayleigh fading environments. We derive new expressions for the cumulative distribution function (CDF) of the highest instantaneous end-to-end signal-to-noise ratio (SNR) taking into consideration the two cases of fixed gain relays and variable gain relays. Relying on these statistical results, we derive new expressions for the outage probability and symbol error rate (SER), both of which are obtained in exact closed form. Furthermore, we derive simple asymptotic outage probability and SER. Our asymptotic results confirm that opportunistic scheduling has no impact on the diversity order. We further prove that the array gain is what determines the SNR advantage of opportunistic scheduling over the single user scenario.

This paper presents a comparison and analysis of selection relaying with transmit beamforming as an effective approach to combat channel impairments in relay-assisted cellular networks. We consider the downlink scenario where the base station equipped with N antennas transmits to the mobile station either directly, or indirectly via a relay station, according to the link with the strongest received signal-to-noise ratio (SNR). We compare two amplify-and-forward protocols: i) fixed gain relaying which requires partial channel state information (CSI), and ii) variable gain relaying which requires full CSI. We present new exact closed-form expressions for the generalized moments of the end-to-end SNR to characterize the higher-order statistical properties of the SNR. We derive new exact closed-form expressions for the symbol error rate (SER), which are valid for a wide variety of modulations. Furthermore, we explicitly characterize the asymptotic behavior of the SER to obtain two key performance parameters: the array gain and the diversity order. Based on these, we reveal that the SNR advantage of variable over fixed gain relaying vanishes in the large N limit.

We develop a unified framework for the symbol error rate (SER) of distributed transmit antenna selection with receiver maximal-ratio combining (TAS/MRC) in multiple-input multiple-output (MIMO) relay networks. We focus on nonregenerative relaying with NS, NR, and NDantennas at the source, relay, and destination, respectively. We consider the general fading scenario of Nakagami-m fading with distinct m fading parameters in the source-to-relay and the relay-to-destination links. We present new analytical expressions for the statistics of the end-to-end signal-to-noise ratio (SNR). Specifically, we derive exact expressions and first order expansions for the cumulative distribution function and moment generating function of the end-to-end SNR. Based on these, we derive new closed-form expressions for the asymptotic SER under M-ary phase-shift keying (M-PSK) and M-ary quadrature amplitude modulation (M-QAM). Our asymptotic solutions accurately identify the diversity order and the array gain as two key design components of the network.

In wireless mesh networks, it is desirable to utilize overlapping coverage of multiple parallel relays to assist the source-destination transmission. In this letter, we consider selection diversity (SD) to select the strongest link amongst the direct and N amplify-and-forward (AF) relay links. We derive new closed-form expressions for the symbol error rate (SER) in independent but not necessarily identically distributed (i.n.d.) Rayleigh fading relay channels. Our results are given as both lower bound and asymptotic expressions based on an accurate upper bound on the signal-to-noise ratio (SNR) of the relay links. Our asymptotic results provide key performance parameters such as the array gain and diversity order, which prove that a full N+1 diversity order is achieved. We show that SD can offer an array gain advantage over maximal-ratio combining which entails all the relays to transmit. Numerical results are shown to validate the analysis.

We propose distributed transmit antenna selection with receiver maximal-ratio combining (TAS/MRC) for use in a two-hop multiple-input multiple-output (MIMO) relay network. The network under consideration is equipped with NS, NR, and NDantennas at the source, relay, and destination, respectively. First, we derive a new closed-form expression for the exact cumulative distribution function (cdf) of the end-to-end SNR. Based on this, we present a new closed-form expression for the exact symbol error rate (SER). Our analytical results are further evaluated in the high SNR regime, leading to practical design insights. Our asymptotic expressions are concise and have the added advantage of explicitly characterizing the diversity order and the array gain of the network. Our exact and asymptotic results are valid for general operating scenarios with distinct average received SNRs in each hop.

Nonregenerative relaying in MIMO multi-relay networks is analyzed under the general operating scenario of independent but not necessarily identically distributed (i.n.d.) Rayleigh fading. Exact closed-form expressions are derived for the moment generating function of the end-to-end signal-to-noise ratio (SNR) with distinct average received SNRs in each link. Our analysis applies to arbitrary L number of relays, each equipped with arbitrary N transmit/receive antennas. Based on the derived results, we determine the symbol error rate with M-ary phase-shift keying. In addition, we carry out a high SNR analysis of the error performance. We explicitly reveal that the diversity order is equal to LN+1.

In this contribution, we propose an antenna selection scheme in dual-hop amplify-and-forward (AaF) multiple-input multiple-output (MIMO) relaying in Nakagami-m fading channels. In each hop, the transmit and receive antenna pair that maximizes the instantaneous signal-to-noise ratio (SNR) at the receiver is selected for transmission. We derive new closed-form expressions for the exact outage probability and the exact symbol error rate (SER), relying on the cumulative distribution function (CDF) of the instantaneous end-to-end SNR. Furthermore, we derive simple closed-form expressions for the asymptotic outage probability and the asymptotic SER, revealing the diversity order of the proposed scheme. Specifically, the diversity order is equal to the minimum of two parameters: first, the product of the number of source and relay antennas and the first hop fading parameter, and second, the product of the number of relay and destination antennas and the second hop fading parameter. Our derived results apply to general operating scenarios with distinct Nakagami-m fading parameters and average SNRs in each hop.

Cooperative diversity is a promising solution in wireless distributed networks where integrating multiple antennas onto small mobile devices is practically impossible due to size and cost constraints. As such, we consider a cooperative diversity network where the source and the destination user-pair are equipped with single antennas while the relay is a wireless access point equipped with N antennas. For such networks, we focus on cooperative selection diversity (CSD) to select a single link with the highest instantaneous received signal-to-noise ratio (SNR) between the direct link and the multiple-input multiple-output (MIMO) relay link. We present new closed-form expressions for the exact outage probability and the exact symbol error rate (SER) based on the cumulative distribution function (cdf) of the instantaneous received SNR. Our expressions are valid for arbitrary N antennas and apply to general operating scenarios with distinct average received SNRs in each link. Furthermore, we present a high SNR analysis of the outage probability and SER to explicitly characterize the diversity order and array gain. We show that the diversity order increases with the number of antennas according to N + 1.

Multiple amplify-and-forward (AF) relays with receive diversity is analyzed over unbalanced hops with independent but not necessarily identically distributed Rayleigh fading. Exact closed-form expressions are derived for the moment generating function of the end-to-end signal-to-noise ratio (SNR) at the destination. Our analysis apply to arbitrary numbers of relays and arbitrary numbers of antennas at the destination. Based on the derived results, we determine the symbol error rate with M-ary phase-shift keying. In addition, we carry out an asymptotic analysis in the high SNR regime. Our results provide fundamental insights into the impact of the number of antennas on the performance of multiple AF relaying. We explicitly reveal that the diversity order is equal to the sum of the number of relays and the number of antennas. Theoretical analysis is verified by simulation.

This paper analyzes the performance of wireless multiuser relay networks (MRN) in unbalanced Nakagami-m fading channels. For such networks, we consider a single channel state information (CSI)-based amplify-and-forward (AaF) relay. We derive a new exact expression for the symbol error rate (SER), which is in closed-form and applies to a wide variety of modulations. Subsequently we present a simplified asymptotic expression for the SER in the high signal-to-noise ratio (SNR) regime to identify key performance metrics such as the diversity order and array gain. Our asymptotic result explicitly reveals the direct relationship between the diversity order and both the number of destinations and the per-hop fading parameters. Moreover, we highlight the effect of the number of destinations on the optimal relay location aiming at minimizing the SER. The validity of our analysis is substantiated by numerical results.

This paper analyzes selection diversity as an effective tool to combat channel impairments in relay-assisted cellular systems. We consider the downlink scenario where the base station equipped with N antennas transmits to the mobile station either directly, or indirectly via a relay station, according to the link with the strongest received signal-to-noise ratio (SNR). For this system, we analyze the performance of fixed gain amplify-and-forward relaying that does not require full channel-state-information (CSI) at the relay. We derive new exact closed-form expressions for the outage probability and symbol error rate (SER) based on new statistical properties of the end-to-end SNR. Furthermore, we quantify the asymptotic behavior of the outage probability and SER. We explicitly reveal the impact of multiple antennas with relay selection diversity, on the array gain and the diversity order. Our new asymptotic results prove that the maximum diversity order of N+1 is achieved.

Distributed multi-antenna relaying is analyzed in nonregenerative cooperative networks with unbalanced hops and independent but not necessarily identically distributed Rayleigh fading. Exact closed-form expressions are derived for the moment generating function of the end-to-end signal-to-noise ratio (SNR) at the destination. Our analysis applies to arbitrary N number of antennas at the relay and arbitrary average received SNRs. Based on the derived results, we determine the symbol error rate with M-ary phase-shift keying. In addition, we carry out an asymptotic analysis in the high SNR regime. Our results provide fundamental insights into the impact of the number of antennas on the performance of nonregenerative relaying. We explicitly reveal that the diversity order is equal to N + 1. Theoretical analysis is verified by simulation.

This paper proposes and analyzes selection diversity as an effective tool to combat channel impairments in relay-assisted cellular systems. We consider the uplink scenario where the base station equipped with N antennas receives from the mobile station either directly, or indirectly via a relay station, according to the link with the strongest received signal-to-noise ratio (SNR). For this system, we analyze the performance of fixed gain amplify-and-forward relaying that does not require full channel-state-information (CSI) at the relay. We derive new exact closed-form expressions for the outage probability and symbol error rate (SER) based on new statistical properties of the end-to-end SNR. Furthermore, we quantify the asymptotic behavior of the outage probability and SER. We explicitly reveal the impact of multiple antennas with relay selection diversity, on the array gain and the diversity order. Our new asymptotic results prove that the maximum diversity order of N + 1 is achieved.

Multiple fixed gain amplify-and-forward (AF) relays with receive diversity is analyzed for the practical case of unbalanced hops with independent but non-identically distributed (i.n.d.) Rayleigh fading channels. We derive a new exact closed-form expression for the moment generating function (mgf) of the end-to-end signal-to-noise ratio (SNR). Our mgf is valid for the general case of arbitrary numbers of relays and arbitrary numbers of antennas at the destination. Based on this, we determine the exact and approximate symbol error rate (SER) for M-ary phase-shift keying. Our results provide new important insights into the joint impacts of the number of relays and the number of receive antennas on the system performance. Theoretical analysis is verified by simulation.

This paper advocates the performance of wireless multiuser relay networks (MRNs) equipped with a single amplify-and-forward (AaF) relay. For such networks, we focus on opportunistic scheduling, in which the destination with the highest instantaneous end-to-end signal-to-noise ratio (SNR) is scheduled for transmission. The scheduled destination can receive either directly from the source or indirectly through the relay, based on cooperative selection diversity (CSD). Assuming Rayleigh fading channels, we first derive a new expression for the cumulative distribution function (CDF) of the received instantaneous end-to-end SNR. Then, relying on this statistical result, we present new exact expressions for the outage probability and symbol error rate (SER), both of which are obtained in closed-form. Furthermore, we derive simple yet valuable closed-form asymptotic expressions for the outage probability and SER in the high SNR regime. Our results explicitly reveal the impacts of CSD and opportunistic scheduling on the diversity order and array gain. Numerical results are presented to validate the analysis.

We derive new exact closed-form expressions for the symbol error rate (SER) of cooperative selection diversity (CSD) with amplify-and-forward (AF) transmission using channel-state-information (CSI)-based gain relaying. We consider the general fading condition of independent but not necessarily identically distributed (i.n.d.) Nakagami-m fading. We also present a closed-form expression for i.n.d. Rayleigh fading as a special case. We highlight the impact of the m fading parameter on the SER performance in unbalanced fading conditions. Numerical results substantiate the validity of our analysis.

Decentralized multiple access networks require dynamic spectrum allocation to efficiently and fairly allocate resources among multiple users. In this paper, we consider the problem of spectrum allocation from the standpoint of diversity combining, and in particular as an explicit case of selection combining (SC). General order selection allocation (GOSA) was previously proposed by the authors as a low-complexity spectrum allocation scheme for decentralized multiple access networks. In this paper, noting that previous analytical results on the error performance of GOSA are for independent identically distributed (i.i.d.) Rayleigh fading, we carry out a thorough and exact analysis of GOSA for the i.i.d. Nakagami-m fading scenario. In particular, based on new results on the exact and asymptotic average error probability of the r-th order statistic, we obtain exact and asymptotic closed-form expressions for the error performance of GOSA. Numerical results show that the performance of the algorithm is close to that of the highly complex optimal search method.

Chip-Level Modulated Binary Pulse Position Modulation (CLM-BPPM) is proposed as a modulation scheme for Fiber-Optic Code Division Multiple Access (FO-CDMA) systems using Optical Orthogonal Code (OOC) for time domain signal spreading. The proposed scheme provides better synchronization and source activity detection at the receiver side as compared to On-Off Keying (OOK). A mathematical expression is derived for the BER of CLM-BPPM using a combinatorial interference pattern analysis approach. The mathematical model is verified using simulation. Numerical results demonstrate that CLM-BPPM has a BER that is very close to OOK. Moreover, increasing the average source activity causes the performance of the CLM-BPPM to approach that of the OOK system with an asymptotic BER equal to the BER of OOK at full user activity.

In this paper, we consider the performance of downlink multiuser relay networks (MRN) equipped with a single amplify-and-forward (AaF) relay. We present exact analysis in closed-form for the outage probability of MRN with channel state information (CSI)-based gain relaying in Nakagami-m fading channels. In doing so, we derived a new expression for the cumulative distribution function (CDF) of the highest end-to-end signal-to-noise ratio (SNR) associated with the strongest destination terminal. We demonstrate the impact of the fading severity m and the number of destination terminals on the system performance in unbalanced fading conditions. Numerical results substantiate the validity of our analysis.

We present new exact closed-form expressions for the symbol error rate (SER) of cooperative selection diversity (CSD) with a single fixed gain amplify-and-forward (AF) relay. We consider the general fading condition of independent but not necessarily identically distributed (i.n.d.) Nakagami-m fading. We also present a closed-form expression for i.n.d. Rayleigh fading as a special case. We highlight the performance improvements provided by CSD with fixed gain relaying in unbalanced fading conditions. Numerical results substantiate the validity of our analysis.

A procedure for determining the probability distribution of the rth order statistic, Gr:L, r=1, 2, , L, among a set of L correlated Nakagami diversity branch gains G1, G2, , GL has been described in David and Nagaraja (2003) and Elkashlan et al. (2008). The results are used to evaluate the bit error rate (BER) of general order selection (GOS), a diversity method in which the rth order branch is selected for transmission, over correlated Nakagami fading branches. GOS can be used to improve system throughput and provide various levels of services, both of which are highly desirable in high-speed communication systems. Numerical and simulation results are presented and used to illustrate the effects of fading correlation on the BER associated with the rth order gain branch.

In this letter, the cumulative distribution function (and hence outage probability) of the r-th order signal-to-noise ratio from a set of n correlated Nakagami fading branches is studied. Numerical results are presented to illustrate the effect of fading correlation and the fading severity parameter. The accuracy of a simple exchangeable approximation is also examined.

A new adaptive multiple access scheme based on the theory of order statistics is introduced. Because the proposed low-complexity method requires relatively small channel information overhead and processing delays, it can be feasible in fast-fading environments and systems with large number of users. Numerical results reveal significant system performance improvement over conventional approaches.

In this paper, we propose a novel simplified mathematical analysis technique for modeling and calculating the effect of multiple access interference on bit error rate in optical code division multiple access (OCDMA) systems. Our technique applies to OCDMA systems using optical orthogonal codes (OOC) with optical time-domain spreading. The proposed analysis uses combinatorial methods on the combined signal at the output of the optical correlator decoder to derive a mathematical expression for the bit error rate.

A channel aware multiple access scheme based on slow frequency-hopping code-division multiple-access (SFH/CDMA) is proposed for a cellular communication system. In contrast to conventional FH, which uses a channel state independent hopping sequence, a transmitter in the proposed scheme hops to an available frequency subband with the highest transmission gain. It is shown that the proposed scheme can offer large performance gains over the conventional FH scheme.

This paper examines the bit error rate (BER) performance of a frequency-hopping multicarrier code division multiple-access (FH-MC-CDMA) system in frequency-selective slow fading channels. The performance of FH-MC-CDMA is compared to that of MC-CDMA on an uplink with a tapped delay line (TDL) correlated channel model. FH-MC-CDMA with performance enhancement techniques is proposed as an access technique for future generation broadband wireless networks. It is found that FH-MC-CDMA generally has a much better performance than conventional frequency hopping. In addition, the performance of FH-MC-CDMA with a much smaller number of subcarriers may outperform that of MC-CDMA.