In this paper, we investigate an unmanned aerial vehicle (UAV)-assisted satellite-terrestrial system with simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) and rate splitting multiple access (RSMA). More specially, the satellite employs RSMA to send messages over a STAR-RIS-assisted UAV to a pair of legitimate users located on the earth in order to enable better use of spectrum resources. Serving as a mobile aerial base station, the UAV transmits information to the users through a fixed-gain amplify-and-forward (AF) or decode-and-forward (DF) relay. Also, we use the STAR-RIS to enhance the link from satellite to terrestrial. In order to evaluate the covert performance of the considered system, we derive closed-form expressions of covert performance metrics including the outage probability (OP), the covert transmission rate, and the detection error probability (DEP). Then, we analyze the impact of changes in the system parameters on the system performance, and provide some useful insights. Additionally, we present numeric simulations to validate the correctness of the theoretical results and show the considered system performs better in terms of the covert performance than the system using the non-orthogonal multiple access (NOMA) protocol.

This paper investigates a novel pinching antenna assisted multi-target integrated sensing and communication (ISAC) system. We propose a joint optimization of transmit and receive PA positions to enable the simultaneous service of multiple sensing targets and a downlink communication user. The objective of the formulated optimization problem is to maximize the minimum sensing signal-to-interference-plus-noise ratio (SINR), which addresses inter-target interference and ensures fairness across multiple targets. The design jointly considers both the transmit and receive antenna positions as well as the receive beamformer. An efficient alternating optimization framework is introduced to handle this non-convex problem. The receive beamformer is obtained in closed-form using the minimum variance distortionless response method, while the antenna position optimization is solved via the differential evolution (DE) algorithm. The DE search process is guided by a customized fitness function that incorporates both communication quality-of-service requirements and physical constraints. Numerical results demonstrate that the proposed joint optimization scheme substantially outperforms transmitter-only optimization benchmarks, receiver-only optimization, and fixed antenna placements. Furthermore, comparative studies show that the DE algorithm achieves a better trade-off between performance and complexity, it not only surpasses particle swarm optimization in terms of performance, but also outperforms element-wise search when the antenna number is small, while maintaining lower computational complexity than both alternatives.

Ensuring the secure communication of unmanned aerial vehicle-assisted reconfigurable intelligent surface (UAV-RIS) is crucial in maintaining seamless connection in next-generation Internet of Things (IoT) networks. For this purpose, intelligent beamforming is essential to ensure secure data transmission from IoT devices to UAV-RIS and optimize communication while preventing adversarial attacks. This paper proposes a novel framework of federated learning for long short-term memory-based deep deterministic policy gradient with an attention mechanism (F-DDPG-AM). The proposed algorithm aims to improve security and mitigate potential threats in UAV-RIS-assisted IoT networks. The F-DDPG-AM combines the federated LSTM’s power to capture long-term dependencies in sequential data with the attention mechanism to focus on key network states and improve decision-making efficiency. The F-DDPG-AM framework improves learning efficiency, accelerates convergence, and enhances resilience against adversarial attacks by selectively prioritizing crucial network information and focusing on insecure scenarios. In addition, federated learning in the proposal ensures secure decision-making through local training for UAV-RIS-enabled IoT networks. The F-DDPG-AM enhances system scalability, trustworthiness, and compliance with secure machine learning principles by decentralizing the training process. The simulation results demonstrate the superior performance of the proposed F-DDPG-AM framework in defending against attacks, significantly outperforming traditional security approaches and other existing reinforcement learning models.

This paper investigates covert communication in a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) assisted wireless-powered communication (WPC) system employing rate splitting multiple access (RSMA). Specifically, the communication process is divided into two stages: energy transmission (ET) and information transmission (IT). In the ET stage, the energy-constrained user (U) and the cooperative jammer (J) harvest radio-frequency (RF) energy from the power station (PS). In the IT stage, U uses the harvested energy to transmit information to the access point (AP) via the STAR-RIS, while J uses the harvested energy to reflect artificial noise through the STAR-RIS. All channels are modeled under Nakagami-mfading. To evaluate covert performance, we derive the statistical characteristics of the cascaded channels, including the probability density function (PDF) and the cumulative distribution function (CDF). Based on these results, we derive expressions for the detection error probability (DEP), outage probability (OP) and covert rate (CR), and further conduct an asymptotic analysis of the OP and derive a lower bound on the CR. Finally, we examine the impact of key parameters on system performance. The simulation results show that, compared with the baseline scheme, the proposed scheme achieves better covert performance and improved robustness against fading, providing support for secure communication in sensitive 6G scenarios.

To solve the problems of low system security and poor transmission quality in integrated satellite-terrestrial communication systems due to eavesdroppers and channel uncertainties, a robust resource allocation (RA) problem is studied. First, considering the constraints of users’ quality of service, the maximum transmit power of the satellite and the base station (BS), and the bounded channel uncertainties, an RA optimization problem is established by jointly optimizing the beamforming vectors, artificial noise (AN) vectors, and power allocation factors. Then, S-Procedure, successive convex approximation (SCA), and alternating optimization are adopted to convert the nonconvex problem with parameter perturbation into a convex one that can be solved efficiently. Finally, a robust RA algorithm based on the alternating approach is proposed to obtain the solutions. Simulation results show that the proposed algorithm has good security and robustness, and the outage probability is reduced by 9.12% compared to the traditional nonrobust algorithms without AN.

This paper investigates a secure beam-scanning framework for near-field integrated sensing and communication (ISAC) systems, driven by location division multiple access (LDMA). Specifically, an ISAC base station performs full-map robust beam-scanning within each transmission cycle, aiming to simultaneously detect potential eavesdroppers (Eves) and ensure secure communication for legitimate users (Bobs). Based on the Bobs’ channel state information (CSI) obtained at the cycle’s start and the estimated CSI of Eves sensed in the previous cycle, we formulate a robust optimization problem. This problem jointly optimizes the hybrid analog-digital precoding and time allocation for beam-scanning, with the objective of maximizing the worst-case average sum secrecy rate. To simplify the solution process, we first eliminate or relax the semi-infinite constraints caused by uncertain multipath channels from two perspectives: convex hull and bounded uncertainty. Subsequently, we design a near-field LDMA codebook in both azimuth and distance domains to construct ideal radar beampatterns for covering and partitioning the spatial scanning region. We also develop efficient analog precoders to significantly reduce computational complexity. Based on the convex hull model, we develop a low-complexity alternating optimization (AO) algorithm. In addition, for the bounded uncertainty model, we propose a semidefinite relaxation-based AO algorithm without requiring a rank-one constraint. Simulation results demonstrate that the proposed framework enables effective full-map Eves sensing while guaranteeing secure communication for Bobs. Moreover, the convex hull-based algorithm exhibits superior robustness and scalability compared to conventional bounded uncertainty approaches.

This paper investigates a near-field covert communication system enhanced by an absorptive reconfigurable intelligent surface (ARIS) and a fluid antenna system (FAS), enabling covert transmission to arbitrary receiver locations. By generating near-field spherical waves via large-scale antenna arrays at Alice and ARIS, covert transmission to Bob is enabled while evading detection by Willie. We jointly optimize Alice’s hybrid precoding, ARIS reflection coefficients, and Bob’s active port selection to maximize the worst-case covert transmission rate. We begin by evaluating ARIS’s suitability versus conventional RIS. We demonstrate the asymptotic orthogonality of near-field beam-focusing vectors in the 3D domain for uniform planar arrays, and characterize the beam-focusing behavior in cascaded ARIS-enabled covert transmissions. Additionally, we reveal the channel gain improvement owing to FAS over traditional antenna systems. To solve the coupled non-convex problem, we propose a low-complexity block coordinate descent algorithm. It incorporates Fibonacci search for hybrid precoding, three complexity-performance trade-off strategies for reflection coefficients optimization, and both exhaustive search and linear conic relaxation for active port selection. Finally, we recover precoding via an alternating minimization scheme. Numerical results show that (i) significant improvement of covert transmission is achieved only with both ARIS and FAS, when Bob and Willie are co-located; (ii) the proposed algorithm outperforms near-field and far-field beam alignment schemes without ARIS, as well as beam focusing of full-map zeroing with ARIS, when Bob and Willie share the same reception direction.

Reconfigurable intelligent surface (RIS) has emerged as a promising technology to enhance both achievable rate and energy efficiency in next-generation wireless networks. This article investigates a novel energy-efficient UAV-RIS-assisted architecture for simultaneous wireless information and power transfer (SWIPT) in integrated ground–aerial–space networks, where a satellite cooperates with multiple UAV-RISs to provide downlink wireless energy transfer (WET) and support uplink wireless information transmission (WIT) for energy-constrained IoT devices in remote environments. We formulate an alternating iterative joint optimization problem (AIJOP) that aims to maximize the system sum achievable rate while ensuring causality of device energy via jointly optimizing UAV-RIS trajectories, RIS phase shift matrices, and satellite power allocation and time allocation between WET and WIT. The problem is highly non-convex due to the strong coupling among variables. To address this challenge, we propose a trajectory–phase–power–time alternating optimization algorithm (TPPTAOA), which decomposes the original problem into four tractable subproblems and solves them iteratively. Specifically, the UAV-RIS trajectories is first optimized via using a device scheduling and TSP-based path planning approach to solve the first subproblem, followed by the proposition of a two-stage heuristic phase optimization algorithm under fixed parameters to solve the second subproblem. Subsequently, the satellite power allocation is solved using a Lagrangian dual method, while the time allocation is optimized through a two-stage strategy combining grid-based coarse search with gradient-based refinement. Simulation results under various system settings verify the fast convergence, robustness, and superior performance of the proposed TPPTAOA, showing significant improvements in both energy efficiency and uplink achievable rate compared with benchmark schemes.

In this paper, channel estimation (CE) for up-link hybrid-field communications involving multiple Internet of Things (IoT) devices assisted by an active intelligent reflecting surface (IRS) is investigated. Firstly, to reduce the complexity of near-field (NF) channel modeling and estimation between IoT devices and active IRS, a sub-blocking strategy for active IRS is proposed. Specifically, the entire active IRS is divided into multiple smaller sub-blocks, so that IoT devices are located in the far-field (FF) region of each sub-block, while also being located in the NF region of the entire active IRS. This strategy significantly simplifies the channel model and reduces the parameter estimation dimension by decoupling the high-dimensional NF channel parameter space into low dimensional FF sub channels. Subsequently, the relationship between channel approximation error and CE error with respect to the number of sub-blocks is derived, and the optimal number of sub-blocks is solved based on the criterion of minimizing the total error. In addition, considering that the amplification capability of active IRS requires power consumption, a closed-form expression for the optimal power allocation factor is derived. To further reduce the pilot overhead, a lightweight CE algorithm based on convolutional autoencoder (CAE) and multi-head attention mechanism, called CAEformer, is designed. The Cramér-Rao lower bound is derived to evaluate the proposed algorithm’s performance. Finally, simulation results demonstrate the proposed CAEformer network significantly outperforms the conventional least square and minimum mean square error scheme in terms of estimation accuracy.

In this paper, we investigate a near-field Internet of Vehicles scenario that utilizes a dual-array antenna architecture and incorporates a transmitting reconfigurable intelligent surface (T-RIS)-assisted integrated sensing and communication (ISAC) to assist driving. A high-frequency large antenna phased array constructed from low-cost energy-efficient T-RIS forms a near-field spherical wave electromagnetic environment. The vehicle communicates with a roadside small base station (SBS) while performing radar detection of the region of interest (RoI) to enhance driving safety. First, we use the kinematic behavior of the vehicle to predict the RoI. Then, we propose a unified optimization framework for all architectures aimed at maximizing the overall gains in both sensing and communication performance, investigating performance upper bounds and associated trade-offs, and proposing a fairness-enhanced scheme. Finally, we propose an integrated sensing, positioning, and communication scheme that derives the multi-objective Cramér-Rao Bound (CRB) for the joint estimation of azimuth, elevation, and range information, and we formulate and solve the problem of minimizing the CRB with guaranteed communication quality. Simulation results demonstrate that the proposed schemes effectively focus on both the RoI and SBS regions, contributing to enhanced driving safety. Additionally, our findings reveal the inherent performance trade-offs between sensing and communications in vehicular networks, and validate the energy efficiency superiority of the proposed T-RIS-aided architecture.

The rapid development of the low-altitude economy (LAE) has accelerated the deployment of cargo unmanned aerial vehicles (UAVs) for intelligent logistics and delivery services. However, large-scale UAV operations still face multiple practical challenges, including unstable communication connectivity, limited onboard battery energy, and strict customer time-window constraints. To address these issues, this paper investigates the trajectory and task scheduling optimization problem for multi-UAV cooperative cargo pick-up under joint communication, energy, and time-window constraints. We develop a collision-aware cooperative multi-UAV optimization algorithm (CACMO) that integrates a Dueling Deep Q-Network (D3QN) for communication-aware trajectory learning with a simulated annealing (SA) based global task-sequence planner and an explicit inter-UAV conflict-resolution mechanism. The D3QN module enables adaptive trajectory generation in unknown and time-varying radio environments without requiring an a priori radio map, maintaining stable connectivity while reducing flight cost, whereas the SA module determines efficient task orders and enforces safe coordination among multiple UAVs through collision-aware refinement. Simulation results demonstrate that the proposed CACMO algorithm framework achieves an optimal balance between task completion time (1,719 seconds) and user satisfaction (score of 0.9969) under typical operating conditions, delivering a 70–75% reduction in total weighted cost compared to representative baseline methods. Crucially, this substantial improvement is achieved while explicitly enforcing multi-UAV collision avoidance-a critical constraint absent in most baseline methods. The framework maintains zero communication outage and guarantees safe inter-UAV separation throughout the mission while satisfying all energy and time window constraints in realistic urban environments, confirming its robustness and scalability for cooperative multi-UAV logistics operations within the LAE.

This paper introduces the concept of wireless-powered zero-energy reconfigurable intelligent surface (zeRIS), and investigates a wireless-powered zeRIS aided communication system in terms of security, reliability and energy efficiency. In particular, we propose three new wireless-powered zeRIS modes: 1) in mode-I,Nreconfigurable reflecting elements are adjusted to the optimal phase shift design of information user to maximize the reliability of the system; 2) in mode-II,Nreconfigurable reflecting elements are adjusted to the optimal phase shift design of cooperative jamming user to maximize the security of the system; 3) in mode-III,N1andN2(N1+N2=N) reconfigurable reflecting elements are respectively adjusted to the optimal phase shift designs of information user and cooperative jamming user to balance the reliability and security of the system. Then, we propose three new metrics, i.e., joint outage probability (JOP), joint intercept probability (JIP), and secrecy energy efficiency (SEE), and analyze their closed-form expressions in three modes, respectively. The results show that under high transmission power, all the diversity gains of three modes are 1. Among three modes, mode-I achieves the best JOP, while mode-II achieves the best JIP. We exploit two security-reliability trade-off (SRT) metrics, i.e., JOP versus JIP, and normalized joint intercept and outage probability (JIOP), to reveal the SRT performance of the proposed three modes. Interestingly, mode-III achieves the lowest normalized JIOP with increasing time allocation factor, and the highest SEE with increasing transmission power. However, mode-I has the highest SEE with increasing predefined data rate. The optimal zeRIS deployment for mode-I and mode-III is near the PS, while that for mode-II is near the AP.

In this paper, we investigate a millimeter-wave secure integrated sensing and communication system assisted by the sub-connected (SC) active reconfigurable intelligent surface (SC-ARIS), where the dual-function radar and communication station (DFBS) employs a hybrid precoding structure. We formulate an optimization problem to jointly design the DFBS hybrid precoding and SC-ARIS beamforming, aiming to maximize the secure energy efficiency while ensuring communication and sensing qualities. To address the above non-convex problem, we utilize alternating optimization technique to decouple it into two subproblems, where DFBS hybrid precoding and SC-ARIS beamforming are respectively optimized. For the first one, we first propose an iterative algorithm to solve the equivalent digital precoding based on constrained concave-convex procedure, Taylor expansion, semidefinite relaxation (SDR) and fractional programming techniques. Then, the hybrid precoding is obtained rely on the manifold optimization alternating minimization technique. For the later one, we propose an iterative algorithm based on the SDR. Considering a more realistic scenario, we extend to the imperfect eavesdropping channel, and propose a robust beamforming design scheme. Finally, simulation results show the effectiveness of the proposed schemes.

This work is focused on safeguarding the security of a reconfigurable intelligent surface (RIS) based symbiotic radio (SR) system. In the considered system, a primary link coexists with an RIS-based backscatter link. For the primary link, physical layer security is used to ensure the confidentiality of the transmitted data, for which a null-space artificial noise scheme is adopted. For the RIS-based backscatter link, we design the reflection coefficients of the RIS so that it becomes covert to a third-party. Under the condition that the backscatter link is covert and its signal-to-noise ratio is above a pre-given threshold, the secrecy rate of the primary link is maximized by jointly optimizing the beamforming vector of the primary transmitter and the reflection coefficients of the RIS. The considered optimization problem is non-convex, and we present a penalty-based iterative method to handle with it, along with an alternating-optimization based initialization method. Numerical results reveal that even though the backscatter link interferes with the primary link, the secrecy rate of the primary link could still be increased as compared with the case without an RIS, which demonstrates the superiority of the RIS-SR technology.

The non-orthogonal superimposed pilot (NOSIP) scheme significantly improves the spectrum efficiency of semantic communication (SemCom) systems by effectively reducing pilot overhead. However, existing SemCom systems based on NOSIP still face challenges, including strong model-channel coupling and limited adaptability to heterogeneous channels. To address these issues, this paper proposes a flexible, channel-adaptive digital SemCom (D-SemCom) architecture based on the NOSIP scheme. Specifically, we design a lightweight semantic codec, termed ShiftViT, and a semantic receiver, termed ShiftRx, which employ time- and frequency-domain shift mechanisms to decouple pilot and data and suppress multi-user interference, thereby enabling image transmission under complex channel conditions. Furthermore, a lightweight channel adaptation algorithm based on first-order meta-learning is proposed to facilitate rapid adaptation and mitigate the strong coupling between semantic models and channel environments. Numerical results demonstrate that the proposed D-SemCom system achieves approximately 25.14% and 1.16% goodput improvements over traditional receivers and existing state-of-the-art methods, respectively, while reducing the computational complexity in terms of FLOPs by approximately 40.37%. In addition, the proposed channel adaptation algorithm is shown to rapidly adapt to diverse channel scenarios within the D-SemCom system.

This paper addresses the problem of capacity maximization in double reconfigurable intelligent surface (RIS) -aided multiple-input single-output (MISO) systems under multi-user scenarios. A system model is proposed for double RIS-aided MISO configurations, incorporating both passive RIS (PRIS) and active RIS (ARIS). The primary objective is to maximize the minimum channel capacity across all users, and a corresponding optimization problem is formulated to achieve this goal. To overcome the challenges posed by the fractional structure of the non-convex objective function, auxiliary variables are introduced, and the bisection method is utilized. Given the highly coupled and nonconvex nature of the optimization variables, a joint alternating optimization (AO) algorithm is designed based on the bisection method and successive convex approximation (SCA), enabling iterative determination of the beamforming vectors at the base station and the reflection coefficients of RISs. The results indicate that deploying double RISs substantially enhances the system’s channel capacity through reflected links. Notably, the ARIS protocols yield higher performance gains, particularly under scenarios involving high total power and large amplification factors. In multi-user environments, the double RIS configuration significantly outperforms the single RIS setup due to the increased degrees of freedom, especially when supported by ARIS protocols. These findings underscore the substantial potential and advantages of double RIS configurations in complex communication environments.

This article proposes a novel covert communication framework utilizing movable antennas (MAs) to enable covert communications in which the evading detection eavesdropper aided by a reconfigurable intelligent surface (RIS). The trajectories of the MAs over the entire time slot, transmit beamforming, and the phase shift of the RIS in each time slot are jointly optimized to improve the covert rate. Specifically, the movement trajectories of the MAs are modeled as a Markov decision process (MDP), optimized by developing a novel deep reinforcement learning (DRL) approach. Furthermore, an alternating optimization (AO) algorithm is designed to jointly optimize the beamforming and phase. In particular, penalty-based two-layer iterative algorithm is proposed to guarantee that the solution satisfies the rank-one constraints. Numerical results show that the proposed MA-assisted covert communications system significantly outperforms conventional fixed-position antenna (FPA) schemes in terms of covert rate.

This article explores the benefits of deploying simultaneously transmitting and reflecting reconfigurable intelligence surfaces (STAR-RIS) in autonomous aerial vehicle (AAV) networks with simultaneous wireless information and power transfer. In the proposed system, the AAV utilizes STAR-RIS to radiate energy-carrying information signals (ECISs) to multiple outdoor energy receivers and multiple indoor information receivers without flying over indoor no-fly zone. Based on the AAV propulsion power formula, we successively introduce fly-hover-broadcast (FHB) and path discretization (PD) protocols to minimize the total AAV energy consumption by jointly using the extended penalty function and optimization algorithm based on the expected value of channel status information, where the AAV flight constraints, no-fly constraint, minimized energy or information threshold constraints, and STAR-RIS phase-shift constraints are met. The FHB protocol, which requires the AAV to radiate the ECISs to the users at only a few hovering positions, provides a lower bound performance of AAV energy consumption, while the PD protocol is used to discuss the general situation of the ECISs during AAV flight. Simulation results demonstrate that the utilization of the STAR-RIS in AAV networks outperforms the traditional RIS in improving energy efficiency and extending AAV flight time.

This article explores the impact of source data compression on the performance of task execution at the receiver side of a communication system, and investigates the interference and impact of channel environment variations on semantic coding features. In order to further optimize the performance of the semantic communication model, a semantic communication framework (DIB-DeepSC) based on disentangled information bottleneck is proposed, which improves the inference accuracy of the model by separating and decoupling irrelevant information in the source data, thus compressing valid information related to downstream task execution to a greater extent, reduced communication overhead. Meanwhile, the influence of the Lagrange multiplier$\beta $in the classical information bottleneck (IB) framework is eliminated, which avoids the need to manually optimize$\beta $several times in the semantic communication model. And the dynamic coding method (DIB-DE) is further designed based on adaptive weights, which can dynamically adjust the coding features according to the channel conditions and enhance the robustness of the model. Numerous experiments show that the proposed DIB-DeepSC framework combined with the DIB-DE dynamic encoding communication scheme possesses better semantic extraction and task inference performance relative to the benchmark methods. This scheme is expected to realize more efficient and reliable semantic transmission in practical communication systems and provides new ideas for developing practical semantic communication systems.

We investigate the performance of an active reconfigurable intelligent surface (RIS)-assisted mixed radio frequency (RF)-terahertz (THz) relaying system, where the RF signal reaches the relay through the active RIS and is then transmitted to the user via the THz channel. Under this scenario, we analyze the system performance with the relay employing amplify-and-forward (AF) and decode-and-forward (DF) protocols. More specifically, we derive the exact expressions for the cumulative distribution function (CDF) of the end-to-end signal-to-noise ratio (SNR) for both relaying protocols. Based on this, we obtain the exact expressions for the outage probability, average bit error rate (ABER), and average channel capacity (ACC). Furthermore, to gain deeper insights, we derive the asymptotic expressions at high SNRs and obtain diversity order (DO) of the system. Moreover, we extend the analysis to the variable gain relaying scheme. The findings reveal that the DOs for both relaying protocols are determined by the THz channel parameters, and the DO under the AF relaying protocol is twice that of the DF relaying protocol. Finally, we validate that active RIS (A-RIS) can more effectively assist the performance of the mixed RF-THz relaying system compared to passive RIS.

In this work, we investigate an active reconfigurable intelligent surface (RIS)-aided non-orthogonal multiple access (NOMA)-enabled space-air-ground integrated network (SAGIN) with cognitive radio, leveraging the flexible deployment of an unmanned aerial vehicle (UAV) and the ubiquitous coverage of satellite networks. The UAV serves uplink and downlink users in the secondary network via NOMA and time division multiple access mechanisms, respectively, while satellites provide wireless backhaul for the UAV and primary users. We aim to maximize the weighted sum mean rate and energy efficiency for the secondary network by jointly the optimizing power allocation, the RIS reflection coefficients (RC), the user matching factors, and the UAV trajectory. We propose an alternating optimization framework based on the block coordinate ascent (BCA) technique, which decouples the problem into multiple variable blocks for alternating optimization until convergence. Moreover, we investigate the performance of energy-efficient active RIS with a sub-connected architecture, decoupling the RIS RC optimization into amplification factor and phase shift subproblems to be solved separately. Finally, simulation results validate the effectiveness of the proposed schemes, and demonstrate weakness of passive RIS and rationality and economics of sub-connected active RIS architecture.

In this paper, rate splitting (RS) has been applied in a mixed dual-hop radio frequency/free space optical (RF/FSO) relay system. In particular, assuming fixed-gain amplify-and-forward (AF) and decode-and-forward (DF) relay protocols, the performance of both heterodyne detection and intensity-modulated direct detection (IM-DD) has been analytically evaluated. In this framework, it is assumed that the RF channel suffers from Rayleigh fading, while the FSO channel is affected by the atmospheric turbulence-induced fading withMálaga($\mathcal {M}$) distribution and pointing errors. For the considered system, we derive expressions for the outage probability, the average bit error rate (BER), and the average channel capacity. In addition, the asymptotic performance of the system at high signal-to-noise ratios regime is analyzed, special cases are discussed, and useful insights have been extracted. Finally, numerical results are presented to verify the accuracy of the analytical and asymptotic expressions.

This paper investigates the physical layer security for a double-reconfigurable intelligent surface (DRIS) aided wireless-powered communication (WPC) system in the presence of an eavesdropper, where one RIS (termed as RIS-1) is deployed between power station (PS) and information user (U) while the other RIS (termed as RIS-2) is deployed between U and access point (AP). Moreover, an idle user acts as a cooperative jamming user (J) to emit the artificial noise to improve the transmission security of U. According to different types in energy harvesting (EH) and information transmission (IT)/noise transmission (NT) of U/J, we propose four DRIS enabled wireless-powered cooperative jamming transmission schemes based on jointly enhancing EH and IT of U (namely DRIS-1), jointly enhancing EH of U and NT of J (namely DRIS-2), jointly enhancing EH of J and IT of U (namely DRIS-3), and jointly enhancing EH and NT of J (namely DRIS-4), respectively. We analyze connection outage probability (COP), secrecy outage probability (SOP), and effective secrecy throughput (EST) of the proposed four schemes, respectively. The results show that DRIS-1 scheme has the highest diversity gain among the four schemes. Besides, the gain of the number of reflecting elements at RIS-1 has the same order as that at RIS-2 in DRIS-1 scheme and DRIS-4 scheme. In DRIS-2 scheme, the gains of the number of reflecting elements at RIS-1 and RIS-2 are two powers and one power, respectively, while the opposite is true in DRIS-3 scheme. In addition, DRIS-1 scheme achieves the best COP, while DRIS-4 scheme achieves the best SOP. DRIS-1 scheme, DRIS-3 scheme, and DRIS-4 scheme respectively achieve the best EST in the low, middle, and high region of transmission power or number of RIS elements.

In this paper, a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-assisted uplink non-orthogonal multiple access (NOMA) system with semi-grant-free (SGF) transmission in the presence of the illegal user is investigated. Particularly, with the help of SGF transmission, grant-free (GF) users omit the tedious process of requesting authorization from the base station and are able to transmit signals by sharing the resource blocks reserved for grant-based (GB) user. Among theKGF users, the one with the best channel conditions is eligible to share the resource block for GB user, which ensures the quality of service for the GB user and avoids collisions due to too many GF users. For this setup, we consider the covert performance and secrecy performance. Particularly, expressions for the outage probability (OP), detection error probability (DEP), optimal detection threshold, and secrecy outage probability (SOP) are derived to assess the system performance. In addition, we present many special cases to get more intuitive insights. Finally, the simulation results verify the correctness and validity of the theoretical calculations, and the effect of each parameter on the system performance is also investigated.

This paper investigates the covert communication performance of a radio frequency underwater acoustic communication (RF-UAC) system deploying rate-splitting multiple access (RSMA). The proposed system aims to enhance the covertness of communication signals while maintaining reliable communications for legitimate users. In this context, we model the RF link using the Rayleigh distribution and the UAC link using the κ – μ shadow distribution. Moreover, We analytically evaluate key performance metrics for the proposed system, including the detection error probability, outage probability and covert communication rate under various system parameters, such as signal-to-noise ratio thresholds and power allocation between public and private streams. Our extensive numerical investigations validate the proposed analytical expressions, demonstrating the role of key system and channel parameters on the performance of RSMA-assisted RF-UAC communications.

Given the rapid growth of diverse communication demands, future large-scale satellite-aerial-terrestrial integrated networks (SATINs) need to simultaneously provide services to users while guaranteeing spectral efficiency, secrecy and energy efficiency. This paper addresses the problem of maximising secrecy energy efficiency (SEE) in SATINs, which can accurately describe the effective trade-off between security, spectral efficiency and transmit power. Particularly, we investigate a secure beamforming (BF) scheme in cognitive SATINs that employs rate-splitting multiple access (RSMA) and reconfigurable intelligent surface (RIS) in the presence of multiple eavesdroppers (Eves) in a UAV-aided secondary network (SN). To optimize the SEE for secondary vehicle users while satisfying the constraints of primary users (PUs), we utilize deep reinforcement learning (DRL) to address the coupling between different optimized parameters based on the improved long short-term memory proximal policy optimization (LSTM-PPO) algorithm. The main innovation of this paper is to design a sophisticated reward function, action space, and state space according to each constraint to speed up the convergence. In addition, simulation results show that the proposed DRL-based optimization scheme exhibits significant advantages in terms of SEE compared with benchmark schemes, validating the effectiveness of this work.

In order to reduce the impact of obstacles and improve system performance for traditional backscatter communication (BackCom) networks, we propose a reconfigurable intelligent surface (RIS)-assisted heterogeneous BackCom network framework, where multiple backscatter clusters share the spectrum resource with macrocell users in an underlay spectrum sharing mode and achieve self-sufficient energy of each low-power-consumption backscatter device (BD) via a radio-frequency energy-harvesting way. Then, a robust resource allocation problem with imperfect channel station information is studied under the constraints of the minimum rate requirement of each BD, the minimum energy requirement of each BD, the maximum interference power of each macrocell user, the reflection coefficient of each BD, and the phase shifts of each RIS. Moreover, based on the bounded channel uncertainty model, a max-min throughput resource allocation problem of multiple backscatter clusters is formulated by jointly optimizing the time allocation factors, the reflection coefficient of each BD, and the phase shifts of each RIS. To deal with the non-convex optimization problem caused by the uncertain constraints and non-convex constraints, the worst-case approach, successive convex approximation as well as semi-definite relaxation are applied. Finally, an iteration-based robust resource allocation algorithm is proposed accordingly. Simulation results demonstrate that the proposed algorithm has good fairness and stronger robustness.

An active simultaneously transmitting and reflecting reconfigurable intelligent surface (ASTAR-RIS)-aided rate-splitting multiple access (RSMA) system is investigated in this paper. Specifically, a multi-antenna base station (BS) employs the RSMA protocol to communicate with a covert user and a public user with the help of an ASTAR-RIS in the presence of hardware impairments. For this setup, the outage probability (OP) and the detection error probability (DEP) of the warden are derived to characterize the covert communication performance. The covert transmission rate ($C_{R}$) in high signal-to-noise ratio (SNR) regions is also taken into consideration, for which an accurate approximate expression is presented. Based on the analytical results, the influences of the number of ASTAR-RIS elements, the RSMA factors, and the reflection coefficient of the ASTAR-RIS elements are analyzed. Finally, numeric simulations validate the correctness of the theoretical results presented in this paper.

The communication security and covertness of legitimate vehicles in the sixth-generation (6G) mobile communication intelligent automatic transportation systems (IATS) face significant challenges, as the communication equipment and wireless signals are complex and susceptible to information leakage. To address the above issues, this paper proposes a novel IATS that integrates simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) with rate-splitting multiple access (RSMA). Concurrently, an eavesdropping vehicle, capable of monitoring and eavesdropping information from legitimate vehicles, is introduced to explore the joint security and covertness performance. A roadside device is also introduced to improve security and covertness performance by transmitting artificial noise. The closed-form expressions for outage probability (OP), detection error probability (DEP), and intercept probability (IP) are derived to characterize the reliability, covertness, and security of the proposed system. The impact of various system parameters on system performance has also been extensively conducted, including transmitted signal-to-noise ratio (SNR), interference power, the power allocation coefficients, and the number of elements in STAR-RIS. The simulation results reveal several key insights: 1) The OPs and IPs of the RSMA-IATS network gradually decrease and increase with the transmitted SNR, respectively; 2) Achieving an optimal balance in power allocation between monitoring and eavesdropping proves essential for effective eavesdropper management; 3) The energy efficiency (EE) of the proposed system exhibits dual peaks at higher STAR-RIS element numbers, contrasting with a single peak at lower element counts, underscoring the strategic deployment of STAR-RIS technology in RSMA-IATS network.

In this paper, we consider a cargo autonomous aerial vehicle (AAV)-aided multi-parcel pick-up and delivery network, where the communication ability of the AAV is provided by the ground base stations (GBSs). For such a system setup, our goal is to optimize the trajectory of the cargo AAV while minimizing the combined impact of total energy consumption and total outage time. Simultaneously, we aim to maximize overall user satisfaction throughout the entire flight duration. More specifically, we propose a pick-up and delivery of AAV (PDU) framework to address this problem and this framework consists of two parts. First, a simulated annealing (SA) algorithm is used to obtain the pick-up and delivery (P&D) order of parcels. On the basis of obtaining the P&D order through SA, we further use deep reinforcement learning (DRL) to optimize the flight trajectory of the AAV to ensure the expected communication quality between the AAV and GBSs. To verify the effectiveness of our proposed algorithms, we design three baseline strategies for comparison, and also investigate the effect of using the PDU framework with different weights. Finally, numerical results show that the performance of PDU strategy is improved by about 5%-30% compared with other strategies in solving the performance tradeoff of AAV energy consumption, communication quality, and user satisfaction.

Vehicle Edge Computing (VEC) assists vehicles in performing latency-sensitive tasks by deploying resources near the vehicle. Designing an incentive mechanism for vehicles and VEC is crucial for realizing an intelligent transmission system. Considering the rationality of resource allocation, we model the utility functions of the VEC and the vehicle, which are used as optimization objectives. Specifically, the VEC allocates resources through pricing to maximize revenue under resource-constrained conditions, and the vehicle weighs payments against energy consumption to determine offloading and resource allocation. Given the vehicle movement and the variable channel state, we use the Deep Reinforcement Learning (DRL) algorithm to solve these optimization problems. To reduce the learning difficulty of the DRL algorithm in complex VEC scenarios with multiple optimization variables, we propose a Pricing-Driven Resource Allocation (PDRA) algorithm that performs mobility-aware task offloading and calculates the optimal values of the optimization variables in the utility function of the vehicle to reduce the decision dimension. Furthermore, we also propose a DRL-based Pricing-Driven Dynamic Resource Allocation (DPDDRA) algorithm to achieve efficient resource allocation. Extensive experimental results show that the proposed algorithms can reduce the learning difficulty while maximizing VEC and vehicle revenue in complex VEC scenarios.

In this paper, we propose a novel architecture for a multi-layer active-passive cascade transmitting reconfigurable intelligent surface (RIS)-aided receiver. We aim at enhancing the scalability of antenna dimensions and energy efficiency for user equipment (UE), as well as improving the amplitude freedom of antenna gain. This architecture integrates reflecting RIS for applications in both jamming and anti-jamming scenarios. We formulate a problem to maximize the worst-case spectral efficiency (SE) of the UE, based on imperfect channel state information (CSI) of the malicious device, thereby ensuring the SE of our UE while disrupting the signal reception of the illegal UE. To address the inherently non-convex nature of the formulated problem, we propose an alternating optimization framework, which decomposes the main problem into several subproblems. Specifically, we uniformly discretize the uncertain domains to obtain robust CSI, allowing us to determine an optimal receiver vector. To balance computational complexity and performance, we propose solutions for the subproblems of base station beamforming and coefficients with different patterns of RIS. Furthermore, to effectively disrupt malicious inter-device communication while avoiding detection and localization, we develop a collaborative interference pattern incorporating silent interference and non-interference protocols. Importantly, the pattern carefully balances performance with the overhead of CSI acquisition. Finally, simulation results validate the efficiency of the proposed algorithms, demonstrating that the proposed architecture achieves better jamming and anti-jamming performance.

This paper proposes a secrecy enhancement scheme for the space shift keying (SSK) assisted multiple-input single-output (MISO) visible light communications (VLC) system in a complex indoor environment, where the line-of-sight (LoS) link of the transmitter and legitimate user can be blocked or exist. By leveraging a properly arranged mirror array as an optical intelligent reflecting surface (ORIS), a legitimate user can access confidential information, while an eavesdropping user cannot intercept the confidential message. To achieve this goal, an optical artificial noise (OAN) assisted secrecy enhancement strategy is introduced. In this strategy, the transmitter transmits both the desired signal and the OAN signal simultaneously while adhering to power and amplitude constraints. The average mutual information (AMI) and achievable secrecy rate (ASR) are employed to analyze the secrecy performance of the ORIS aided SSK VLC system. Furthermore, to adapt to different environments, four system configuration scenarios are presented, and the corresponding secrecy performance is analyzed. To clarify the theoretical results of the OAN assisted indoor MISO SSK VLC system with an ORIS, extensive simulation results are performed.

In this paper, we investigate covert communication in rate-splitting multiple access (RSMA)-assisted ambient backscatter communication (AmBC) systems. Specifically, in the presence of illegitimate users, a base station applies RSMA to the downlink transmission of covert users and common users in the the primary system of ambient backscatter. To evaluate the covertness of the system, we derive closed-form expressions for the detection error probability (DEP), outage probability (OP), and covert rate (CR), where the DEP is applied to evaluate the ability of the warden to detect the presence or absence of communication behaviors between the base station and the covert user. Based on these expressions, we also conduct an asymptotic analysis of the outage probability, an upper bound analysis of the covert rate, and an analysis of the impact of the power allocation factor on system performance. Numerical results show that the RSMA scheme has a higher covert rate and a higher minimum DEP value compared to the non-orthogonal multiple access (NOMA) scheme, but it may reduce its outage performance. Additionally, an appropriate use of the power allocation factor can enhance the covertness of the system. Furthermore, we find that the co-channel interference between the primary and secondary systems in the ambient backscatter system can degrade the covert performance of the primary system.

DNA storage is a promising data storage method with high density, durability, and easy maintenance, ideal for data archiving. However, wide-scale adoption is hindered by challenges like high synthesis costs, data loss, and I/O complexities. Addressing robustness is a primary concern in advancing DNA storage. Traditional strategies for robustness rely on increasing redundancy, replicas, and error-correction codes (ECC) for each DNA sequence strand. Given the unpredictable errors in DNA storage and the associated costs of absolute accuracy, we’ve embraced an error-tolerance approach. This paper introduces an innovative method utilizing the residual Convolutional Neural Network (CNN) during image decoding in DNA storage to combat noise and enhance robustness. We simulated compressed images in DNA sequences and restored them using our network, achieving commendable peak signal-to-noise ratios (PSNR) even with lower-quality images. Our method offers a balance between redundancy and image quality in DNA storage.

In this article, we consider an active reconfigurable intelligent surface (ARIS)-aided nonorthogonal multiple access (NOMA) and rate-splitting (RS)-enabled communication system, in which a base station applies RS and NOMA to the downlink transmission of a hidden user and a public user with the assistance of an ARIS in the presence of an illegal user. More specifically, the closed expressions for the outage probability (OP), covert rate, and detection error probability (DEP) are derived. Also, we present the analysis for the secrecy OP (SOP), and analyse the effects of detection threshold, total power consumption, reconfigurable intelligent surface (RIS) deployment distance, and power allocation factors on the system performance. The numerical results show that under the same total power consumption, the ARIS has a lower OP value than the passive RIS (PRIS), which can effectively overcome the “multiplicative fading” effect. Moreover, applying the ARIS can result in a larger covert rate and a higher minimum DEP value at the optimal detection threshold, and can reduce the SOP values of hidden and public users by reducing the power allocation factors. In addition, at the same minimum DEP value, the RS-NOMA scheme has a higher covert rate than the NOMA scheme.

Vehicle road cooperation systems are the vital components of intelligent transportation systems, destined to play an irreplaceable role in the future smart cites. Such systems are mandated to achieve elevated data rates, ultralow latency, and enhanced reliability. To meet these requirements, we incorporate full-duplex (FD) and rate splitting multiple access (RSMA) into vehicle road cooperation systems and propose a downlink FD RSMA vehicle road cooperation system. More importantly, we introduce a crucial metric to evaluate the influence of the delay constraints on the system performance. Specifically, analytical expressions for the effective capacity of the nearby vehicle and the distant pedestrian are derived. We also provide the approximate expressions for the effective capacity at the low and high-signal-to-noise ratios (SNRs) and the upper bound on the effective capacity to gain further insights. Furthermore, we expand our evaluation to include both throughput and energy efficiency for the FD RSMA vehicle road cooperation system. Results illustrate that: the effective capacity of the nearby vehicle increases with the increasing transmitted power at low SNRs and stabilizes at a constant level at high SNRs. Conversely, the effective capacity of the distant pedestrian increases continuously with the higher transmitted power. The effective capacities of the vehicle and pedestrian are influenced by various factors, such as the transmitted power, power allocation coefficients, and Quality-of-Service exponent.

A mixed multi-user underwater acoustic communication/free space optical (MU-UAC/FSO) air-to-sea heterogeneous relaying system is analyzed in this work, where multiple UAC channels aggregate into a FSO channel to obtain maximum capacity. The UAC channels experience κ-μ shadowed fading and the FSO channel obeys double generalized Gamma fading with the non-zero boresight pointing error. Utilizing the amplify-and-forward protocol, we obtain the approximate statistical distribution of the end-to-end signal-to-noise radio. The expressions of the outage probability (OP), average bit error rate (BER), and average channel capacity (ACC) are derived. Moreover, asymptotic expressions of the OP and average BER are obtained. Relying on the asymptotic results, our findings emphasize that the diversity gain of the MU-UAC/FSO relaying system is determined as the number of users, fading parameters of the UAC and FSO channels, pointing error parameters, and detection types. The results can be simplified to the single-user case. It is shown that the multi-user scheme provides significant diversity gain compared to the single-user scheme. Furthermore, considering the characteristics of UAC channels, such as the Doppler effect, we investigate the performance of a MU-UAC/FSO relaying system in time-varying scenarios.

In this work, we study the performance of an unmanned aerial vehicle (UAV)-aided mixed radio frequency (RF)/underwater acoustic communication (MRFUAC) transmission system, where the UAV transmits signals to an underwater node through the amplify-and-forward (AF) relay, such as a buoy located on the sea surface. In particular, the UAV-relay RF channel follows a Rician distribution, while κ-μ shadowed fading distribution is applied to model the UAC link. For this considered system with the fixed-gain AF relay, we obtain the statistical distributions of the end-to-end signal-to-noise ratio. To demonstrate the performance of the MRFUAC system, formulae for the outage probability and average bit-error rate are further obtained in closed form. Moreover, to obtain some interesting insights, we present the asymptotic analyses of these performance metrics. To show the validity of our analysis, the truncation error analysis is also provided and the results show that our proposed method has a smaller error than that in the previous literature. In addition, we present the analysis of the optimal height of the UAV at different horizontal distances. In addition to the fixed-gain analysis, we also provide few results for the variable-gain AF relaying MRFUAC system. Finally, the validity of the theoretical analysis is confirmed by Monte Carlo simulations.

In this article, we investigate covert communication in simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-assisted networks with rate-splitting multiple access (RSMA). Specifically, a legitimate transmitter employs RSMA to send messages over the STAR-RIS to a pair of legitimate users located on both sides of the STAR-RIS, where the user on the transmitting surface is equipped with a full-duplex (FD) receiver with two antennas. In particular, one of the receiver’s antennas is used to receive signals and the other is used to transmit jamming signals to confuse the warden’s detection. In order to evaluate the covert performance of the considered system, we derive closed-form expressions for the detection error probability (DEP), the outage probability, and the covert rate. Then, the effects of the maximum signal interference power of the FD, the power distribution coefficient, and the reflection coefficient of the STAR-RIS elements on the covert performance are presented. The numerical results indicate that increasing the maximum signal interference power of the FD enhances the value of DEP, but reduces its outage performance. Additionally, it is observed that the impact of the reflection coefficient of the STAR-RIS elements on the covert performance is related to the transmit power, and the DEP is a monotonically increasing function of the reflection coefficient when the transmit power is sufficiently high.

In this paper, we study the performance of a cooperative underwater acoustic communication/free-space optical communication (UAC-FSO) transmission system supported by a fixed-gain amplify-and-forward (AF) relay, where an underwater source transmits signals to a satellite through the help of a buoy functioning as a relay located on the sea surface. In particular,Kand κ - μ shadowed fading distribution models are used to characterize the UAC link, while the FSO channel follows a unified Málaga distribution existing pointing errors. Based on the above considerations, we calculate the cumulative distribution function (CDF) and probability density function (PDF) of the end-to-end (e2e) signal-to-noise ratio (SNR). To assess the system performance, expressions for the outage probability (OP) and average bit-error rate (BER) are further obtained in closed-form. Furthermore, driven by a desire for more explicit insights, the high SNR analyses of the OP and average BER, and upper and lower bounds on the average capacity are presented. Finally, through Monte Carlo simulations, the correctness of the theoretical analysis is verified.

The location information of cars contains great value, but the uncontrollable characteristics of public data and the difficulty in distributing benefits derived from the potential value of the data greatly reduces the enthusiasm for data owners to share their data. In addition, the current selective disclosure schemes based on merkle tree still require large costs when there are many data items. To solve these problems, a blockchain-based framework for sharing cars’ location information applicable to the online car hailing industry is proposed in this paper, enabling the sharing of cars’ location information while protecting passengers’ privacy through selective disclosure. The combination of homomorphic encryption and probabilistic verification enables a faster batch data verification compared to other blockchain-based data sharing schemes, as well as ensures the authenticity of the data uploaded to the blockchain. The experimental results show that the proposed selective disclosure mechanism based on hash exclusive or tree has lower costs than the baseline for cases with many data items. Moreover, the proposed framework meets both security and feasibility requirements. Specifically speaking, under the constraint of 128-bits security level, the costs of time and space on the location information during one drive are at microsecond level and kilobyte level, respectively. Finally, the scheme is suitable for scenarios with higher throughput.

In this paper, we consider a simultaneously transmitting and reflecting reconfigurable intelligent surface (STARRIS)-assisted Internet of Vehicles non-orthogonal multiple access network. For practical considerations, the impacts of residual hardware impairments and imperfect channel state information are investigated. For such a setup with three different protocols, including time switching (TS), energy splitting, and mode switching (MS), we present the outage probability (OP) analysis for the network. Moreover, the probability of signal-to-noise ratio (SNR) gain and the delayed outage probability are further investigated. Compared with the traditional relaying scheme, the obtained results show that the STARRIS-assisted system achieves better delay performance. Furthermore, for the STARRIS-assisted system, the TS protocol achieves the best performance, while the MS protocol has the worst performance. In addition, considering the base station with multiple antennas, the expression for the OP is derived and error floors at high SNRs due to imperfect channel state information constraints exist. Finally, one can readily observe that increasing the number of STARRIS elements and antennas of the source can improve the outage performance.

We take the viewpoint of wireless attackers, and investigate the use of the reconfigurable intelligent surface (RIS) in degrading the communications performance of a time-division duplex system, in which a multiple-antenna base station (BS) transmits independent data streams to multiple user terminals (UTs). Each channel coherent time block consists of a channel training (CT) phase followed by a data transmission (DT) phase. During the CT phase, the UTs broadcast pilots to enable the BS to estimate the wireless channels, and the RIS manipulates the wireless environment so that the channel estimations obtained by the BS are incorrect. During the DT phase, the BS generates beamforming vectors, which are based on the channel estimations obtained during the CT phase, to transmit data to the UTs, and the RIS adopts a randomly time-varying reflection pattern to distort the signals received by the UTs. The mean square errors (MSEs) of the UTs are used as the performance metric, for which, analytical expressions are derived in large system limit. Based on the theoretic results, an efficient method is proposed to optimize the time-varying reflection pattern of the RIS to enhance the attack performance. Numerical simulations are presented to validate our theoretical results and to demonstrate the superiority of the proposed attack scheme over an existing attack scheme wherein the reflection pattern is time-invariant.

In this work, a mixed underwater acoustic/optical wireless transmission system under both amplify-and-forward (AF) and decode-and-forward (DF) relaying protocols is proposed. Assuming pointing errors and both heterodyne detection (HD) as well as intensity modulation/direct detection (IM/DD) techniques in the underwater optical link, we deduce the exact analytical formulas for the outage probability (OP), average bit error rate (ABER), and average capacity of the system under consideration. Also, we further derive the corresponding asymptotic expressions to gain intuitive physical insights about the system and channel models under consideration. Additionally, we extend the analysis to a more general multi-sensor system. Finally, we check the analytical results by Monte Carlo simulations.

Intelligent reflecting surface (IRSs) have recently played a crucial role for numerous application associated with unmanned aerial vehicle (UAV) communications. To provide good quality of service (QoS) for the users, it is necessary to study the IRS-aided UAV communication system with performance analysis. Thus, in this paper, a three-dimensional (3D) geometry-based stochastic multiple-input multiple-output (MIMO) channel model is developed to characterize the IRS-aided air-to-ground (A2G) propagation environments, which takes into account the multipath fading and height-dependent path loss effects. Based on the proposed channel model, the impact of some important system parameters on the outage probability (OP) is numerically investigated. One key insight from our analysis is the AIRS operating on mmWave frequencies is more suitable for high mobility scenarios. The obtained results can provide guidance for achieving better system performance optimization.

In this paper, we investigate joint optimization of secure AirComp and reliable multicasting assisted by a multiple-input multiple-output untrusted two-way relay, where artificial noise is employed at the access point (AP) to interfere the relay for ensuring secure AirComp. We aim to minimize the computation distortion at the AP by jointly designing the transmit variables of all the nodes and the aggregation variables at the AP and relay, under the secure AirComp constraint, the reliable multicasting constraint, and the transmit power constraints of all the nodes. We consider two scenarios that perfect and imperfect channel state information (CSI) are available. For the former, the formulated optimization problem is highly nonconvex, and we propose an effective block coordinate descent (BCD)-penalty successive convex approximation (penaltySCA) method to solve the nonconvex problem. For the latter, we model the imperfect CSI by using worst-case criterion and the formulated robust optimization problem is much more challenging than its counterpart with perfect CSI. To solve the robust problem effectively, we first transform it to a deterministic optimization problem by employing some powerful mathematical lemmas, and then apply the proposed BCD-penaltySCA method to solve the reformulated deterministic problem. The proposed methods are shown by simulations to significantly reduce the computation distortion compared with other benchmarks under considering secure AirComp and reliable multicasting.

In this paper, a rate-splitting multiple access (RSMA) scheme is proposed to aid a mobile edge computing (MEC) system where multiple randomly deployed users offload their computation tasks to a MEC server. Considering that users are divided into the center and edge groups, a cognitive radio (CR)-inspired rate-splitting is designed to enable the paired users to simultaneously offload to MEC server. Under the CR principles, the rate-splitting parameters are jointly designed to attain the maximum achievable rate for the secondary user, meanwhile maintaining the primary user’s offloading performance same as in orthogonal multiple access. For the case of the paired users with fixed locations, we derive a closed-form expression for the successful computation probability (SCP) achieved by the RSMA-aided MEC (RSMA-MEC) scheme and formulate a SCP maximization problem to obtain the optimal offloading parameters. To reveal the impact of the user locations on the offloading performance of the RSMA-MEC system, various distance-based user pairing schemes are investigated by invoking stochastic geometry techniques. We provide closed-form expressions for the SCPs achieved by the user pairing schemes to characterize the offloading performance. Pros and cons of the user locations to maximize the SCP are highlighted. Simulation results verify the accuracy of the analytical results and clarify the superior offloading performance achieved by the RSMA-MEC scheme, which attains a higher SCP than the existing schemes.

In millimeter wave (mmWave) communication systems with massive multiple-input multiple-output (MIMO) architecture, selecting the antennas contributing most from the candidate array to transmit/receive signals is one of the effective solutions to reduce hardware cost and power consumption while maintaining high spectral efficiency. In this paper, for the communication systems where the base station (BS) equipped with massive MIMO antenna array communicates with multiple single-antenna users, the impact of limited-resolution analog-to-digital converters (ADCs) and digital-to-analog converters (DACs) on system capacity is investigated, and two antenna selection (AS) algorithms, namely quantization-aware greedy with square maximum-volume (QAG-SMV) and group-selection (GS) schemes, are proposed to enhance system capacity for the uplink and downlink transmission, respectively. Specifically, after the quantization noise caused by limited-resolution ADCs/DACs is converted to independent additive noise, the problem of maximizing system capacity is formulated. Then, two novel AS schemes are proposed to improve system capacity. Simulation results show that the proposed AS algorithms can obtain higher average system capacity, and the computational complexity is reduced as well.

In this article, the performance of a dual-hop relaying terahertz (THz) wireless communication system is investigated. In particular, the behaviors of the two THz hops are determined by three factors, such as the deterministic path loss, fading effects, and pointing errors. Assuming that both THz links are subject to the$\alpha $-$\mu $fading with pointing errors, we derive exact expressions for the cumulative distribution function (CDF) and probability density function (PDF) of the end-to-end signal-to-noise ratio (SNR). With these statistical expressions, some important performance metrics are evaluated, such as the outage probability (OP), average bit error rate (BER), and average channel capacity (ACC). Moreover, the asymptotic analyses are presented to obtain more insights. The results show that the dual-hop relaying scheme has better performance than the single THz link. Furthermore, the system diversity order depends on the fading parameters and pointing errors of both THz links. In addition, we extend the analysis to a multirelay cooperative diversity system and derive the asymptotic symbol error rate (SER) expressions. Finally, the derived analytical expressions are verified by the Monte Carlo simulation.

In this article, we analyze the performance of a mixed dual-hop power line communication/free-space optical communication (PLC-FSO) transmission system supporting both decode-and-forward (DF) and fixed-gain amplify-and-forward (AF) relaying protocols. Further, it is assumed that the PLC link experiences log-normal fading under the effects of additive background and impulsive noise, while the free-space optical (FSO) channel obeys an exponentiated Weibull distribution with pointing errors. On this basis, we derive the probability density function (PDF) and cumulative distribution function (CDF) of the end-to-end (e2e) signal-to-noise ratio (SNR). To evaluate the system performance, the closed-form expressions for the outage probability (OP) and average bit-error rate (BER) are derived. Additionally, to gain more insights, the asymptotic analysis of OP and average BER, and the upper bound of the average capacity are presented.

In this paper, the performance of a mixed Terahertz/free-space optical (THz/FSO) wireless transmission system is studied, where the joint effects of channel fading and pointing errors are considered for both THz and FSO links. Employing the semi-blind amplify-and-forward protocol, we derive the cumulative distribution function and probability density function of the end-to-end signal-to-noise ratio. By applying the derived statistics, exact expressions for the outage probability (OP), average bit error rate (BER), and average channel capacity are obtained. In order to attain useful physical insights, asymptotic OP and average BER expressions are also presented. Based on them, the diversity gain is determined, which is shown to depend on channel fading and pointing errors of both links. In addition, by taking into account the hardware impairments, the OP of the non-ideal hardware system is derived. Moreover, the analysis is extended to multi-antenna scenarios and the asymptotic OP is obtained. Finally, illustrative numerical results are plotted and it can be observed that the path loss, channel fading, pointing errors and hardware impairments lead to a considerable degradation in system performance.

In this paper, we investigate the secure beamforming design in multiple-input multiple-output (MIMO) nonorthogonal multiple access (NOMA) en-abled Internet of Things (IoT) networks, where a controller transmits confidential messages to multiple actuators and a cooperative controller acts as a jammer to prevent a potential eavesdropper from wiretapping the information. Our goal is to maximize achievable secrecy sum rate subject to the successful successive interference cancellation constraint and transmit power constraints of the controller and jammer. When channel state information (CSI) is perfect, we design the secure beamforming by developing an iterative optimization algorithm based on minimum mean square error (MMSE) method. When perfect CSI is not available, we model the channel errors as deterministically-bounded, and propose a robust secure beamforming design algorithm based on weighted MMSE and cutting-set method. The effectiveness of the proposed algorithms is verified by the simulation results.

In this paper, secure beamforming design in cooperative cognitive radio networks for Internet of Things (IoT) is investigated, where we maximize the secrecy sum rate for the IoT devices (IoDs) to protect their communication and employ the nonorthogonal multiple access scheme at the cognitive access point (AP) to serve the cognitive users. The formulated secure beamforming optimization problem is a non-convex problem and its global optimal solution is very hard to find. To overcome this difficulty, we propose an iterative algorithm based on semidefinite programming and monotonic optimization method to obtain the global optimal solution, which has high computational complexity and is suitable for the case that the cognitive AP has a powerful computing ability. For some application scenarios in which the cognitive AP has a lower computing ability, we propose suboptimal solutions based on zero-forcing scheme, which have much lower computational complexity. Furthermore, we derive the limit value of the secrecy sum rate for the IoDs when the transmit power of the cognitive AP goes to infinity, which can serve as an upper bound for our proposed solutions. Numerical results are also provided to verify the effectiveness of our proposed solutions.

Abstract In this work, the authors consider the security performance for the mixed radio frequency link and visible‐light link cooperative relaying system, where the relay has the energy collection ability and can extract the direct current part existing in the visible‐light signal. Then, the relay uses the collected energy to demodulate the received visible‐light signal and retransmit it through the radio frequency link. With this equipment, some analytical expressions of the average secrecy capacity and the secrecy outage probability are derived. Furthermore, the asymptotic expression is also derived to examine the influence of the various configuration parameters on the secrecy performance of the mixed relaying system. At last, some numerical and simulation results are given to verify the theoretical analysis.

Existing WiFi recognition schemes are capable of discovering patterns of indoor semantics, such as human activity, identity, indoor environment, and so on. We note that channel state information (CSI) presents an opportunity for hackers to learn indoor privacy, however, currently there is a lack of security research on CSI. In this article, we are the first to discuss and define the security problem of CSI signals, which is further extended to the problems of nontargeted protection and targeted protection. To solve them, we present two types of adversarial autoencoder networks (AAENs). Through replacing the original signals with the generated adversarial ones, the protected semantic features are modified, and the significant features of the other semantics required to be recognized are reserved. Intensive evaluations demonstrate that with the proposed AAENs, the recognition accuracy of the protected semantic can be significantly decreased, while still maintaining the other semantics to be identified correctly.

In this paper, we investigate the performance of a mixed radio-frequency-underwater wireless optical communication (RF-UWOC) system where an unmanned aerial vehicle (UAV), as a low-altitude mobile aerial base station, transmits information to an autonomous underwater vehicle (AUV) through a fixed-gain amplify-and-forward (AF) or decode-and-forward (DF) relay. The analysis accounts for the main factors that affect the system performance, such as the UAV height, air bubbles, temperature gradient, water salinity variations, detection techniques, and pointing errors. Employing the fixed-gain AF and DF relays, expressions for some key performance metrics are derived, e.g., outage probability (OP), average bit error rate (ABER), and average channel capacity. Moreover, in order to get further insights, asymptotic analyses for the OP and ABER are also carried out. Additionally, for the two relaying systems, we derive analytical expressions for the optimal UAV altitude that minimizes the OP. Simulation results show that the UAV altitude influences the system performance and there is an optimal altitude which ensures a minimum OP. Furthermore, it is demonstrated that the diversity order of the fixed-gain AF relaying depends on the RF link and pointing errors, while the diversity order of the DF relaying depends on the detection techniques and pointing errors.

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

In this work, we study a low altitude platform (LAP)-aided dual-hop relaying system combined with non-orthogonal multiple access (NOMA) and free-space optical (FSO) communication technology. More specifically, we assume that a LAP is served as a relay with decode-and-forward (DF) protocol, where the link between the source and the relay is assumed to adopt the FSO scheme, and the links between the relay and the two NOMA users are supposed to be radio frequency (RF). Based on this system model, we analyze the outage probability. To obtain the diversity order information, we also develop the asymptotic analysis. Our results show that the altitude of the LAP affects the system performance significantly. In addition, the system's performance is dependent on the parameters of the FSO channel.

In this paper, we consider the physical layer security for unmanned aerial vehicles communication systems, where a unmanned aerial vehicle works as an aerial base station and an emergency communication vehicle serves as a terrestrial relay. More specifically, we present the analytical results for the secrecy outage probability, strictly positive secrecy capacity, and average secrecy capacity. Finally, Monte-Carlo simulations are provided to verify the correctness of the analytical results.

Mobile-edge computing (MEC) has been witnessed as a promising solution for the vehicular task offloading. Due to the limited computing resource of individual MEC servers, it faces challenges when higher requirements are put forward for timely task processing of a large amount of computations in the emerging vehicular applications. In this article, we strive to realize the efficient vehicular task offloading via heat-aware MEC cooperation from the game theory perspective. Here, the heat indicates the vehicle density and is tightly related to the requests of vehicle users when they drive through the hot zones. Specifically, a deep learning-based prediction method is proposed, capturing the dynamic time-varying heat value of the hot zones based on the analysis of the real-world private car trajectory data. To identify the role of MEC in the cooperation, we take the time-delay constraint into consideration for the task offloading. To realize MEC grouping for task offloading in MEC cooperation, we formulate the MEC grouping as a utility maximization problem via designing a noncooperative game-theoretic strategy selection based on regret-matching. Furthermore, we derive the correlated equilibrium and prove that the fast convergence can be achieved. Extensive simulation results validate the effectiveness of the proposed vehicular task offloading approach under various system parameters, such as computation workload, time slots, and MEC servers number. The proposed method outperforms the existing methods, which is able to significantly reduce the task complete delay, and in the meantime enhance the MEC energy efficiency with end users' quality-of-experience guaranteed.

To provide high data rate for high-speed trains (HSTs), it is required to use emerging wireless communication systems, such as the fifth generation (5G). An asymmetric 5G mobile relay system is investigated for HSTs, where the mobile relay is deployed at the HST to avoid high penetration loss of the direct link between the base station (BS) and the users (TIE) inside carriages. The sub-6GHz frequency is utilized for the BS-relay link while the relay-TIE link adopts the millimeter wave frequency. Therefore, the BS-relay link experiences κ-μ fading and the relay-TIE link experiences static fluctuating two-ray fading. Moreover, the channel aging effect is considered due to the mobility of HST. For the considered system, we first study the exact statistical characterizations of the end-to-end signalto-noise ratios. Then, we derive exact closed-form expressions for key performance metrics, such as outage probability, average bit-error rate, and average achievable rate per unit bandwidth. The significant effects of channel aging, system and channel parameters on the mobile relay system are revealed from theoretical analysis and are further illustrated by simulation results. Our investigation reveals that the mobile relay system is a promising network architecture for HST communications and can provide steady and high-speed data provisioning to HST passengers against the significant bottleneck of channel aging.

In this paper, we investigate beamforming design for cooperative secure transmission in cognitive two-way relay networks, where the cognitive transmitter (CT) with multiple antennas helps to forward the signals of two primary transmitters (PTs) and tries to protect the PTs from wiretapping by a single-antenna eavesdropper. With the objective of maximizing the secrecy sum rate (SSR) for PTs, we jointly design the beamforming matrix for the PTs' signals, the beamforming vector for the cognitive receiver (CR)'s signal, and the artificial noise (AN)'s beamforming matrix, under the quality of service constraint at the CR and the transmit power constraint at the CT. We propose the monotonic optimization-based algorithm to obtain the global optimal solution to the SSR maximization problem, which is a double-layer iterative algorithm and has very high complexity. To balance the complexity and the performance, we also propose a sequential parametric convex approximation-based single-layer iterative algorithm and a zero-forcing-based closed-form algorithm, the latter of which has the lowest complexity. Furthermore, we derive the asymptotic achievable secrecy sum rate when the CT transmit power goes to infinity. We present the numerical results to verify the effectiveness of our proposed algorithms.

In this paper, we jointly explore random caching and cooperative transmission based on cooperative radius in HetNets. Using tools from stochastic geometry, we obtain the tractable expression of the average successful transmission probability (STP) under our proposed scheme. By maximizing the average STP, we formulate the optimization problem to find the optimal policy. Given the existence of popularity prediction errors in practice, we then examined two types of errors: errors in file popularity prediction and errors in file library size estimation. By comparing with several existing caching policies in the literature (e.g., the most popular caching and the uniform caching), we demonstrated the robustness of our proposed scheme in the presence of errors.

In this paper, we analyze the performance of a NOMA-based cooperative relaying network with the Nth best relay selection scheme over Rayleigh fading channels. In addition, the simultaneous wireless information and power transfer (SWIPT) technique is applied to prolong the work time of the relay. Some closed-form expressions as well as the asymptotic analysis for the outage probability are derived. These analysis reveals that the diversity order achieved by the Nth best relay selection scheme is M -N +1, where M is the number of all the relays and N is the order number. Monte Carlo simulation results verify our theoretical analysis and demonstrate the impact of the number of the relays, the order number, and the power-splitting ratio on the outage performance of our considered system.

In this article, we study the secure beamforming design for a two-way cognitive radio (CR) Internet of Things (IoT) network aided with the simultaneous wireless information and power transfer (SWIPT). Located at the center of secondary network, the IoT controller helps to provide relay assistance and cooperative physical layer security (PLS) for two primary users (PUs) against an eavesdropper, while transmitting information and power to the other IoT devices (IoDs) with primary spectrum. To enhance the information security, we aim to maximize the secrecy sum rate (SSR) for PUs by jointly designing the beamforming matrix and vectors at the central controller. To efficiently solve the nonconvex problem, we first propose the branch-reduce-and-bound (BRB)-based algorithm to obtain an upper bound for the SSR and offer a feasible solution by Gaussian randomization, which demands two-level iteration and thus has high complexity. To strike a balance between the complexity and the performance, we then propose iterative algorithm based on constrained-convex-concave programming (CCCP) and a zero forcing (ZF)-based noniterative algorithm, the latter of which with lowest complexity is suitable for the central controller with limited-power supply. The simulation results are provided to demonstrate the effectiveness of our proposed optimization algorithms in comparison to the traditional schemes.

In this paper, we analyze the secrecy performance of the decode-and-forward (DF) relay system in generalized-K fading channels. In a typical four-node communications model, a source (S) sends confidential information to a destination (D) via a relay (R) using DF strategy in two time slots, while an eavesdropper (E) wants to overhear the information from S to D over generalized-K fading channels. To be more realistic, we assume that E can receive the signals of two time slots, and there is no direct link between S and D because of heavy fading. Based on those assumptions, we derive closed-form expressions for the secrecy outage probability (SOP) and ergodic secrecy capacity (ESC) by using a tight approximate probability density function of the generalized-K model. Furthermore, asymptotic expressions for the SOP and ESC are also derived in the high signal-to-noise ratio region, not only because we can get some insights about SOP and ESC, but also because expressions for SOP and ESC can be simplified significantly. The single relay system is subsequently extended into a multi-relay system, where the asymptotic SOP analysis of three proposed relay selection strategies is investigated. Moreover, the security-reliability tradeoff analysis in the multi-relay system is also presented given that S adopts a constant code rate. Finally, the Monte-Carlo simulation is used to demonstrate the accuracy of the derived closed-form expressions.

In this paper, we consider the average secrecy capacity of a single-input multiple-output (SIMO) system with channel estimation error over generalized fading channels in the presence of co-channel interference and an eavesdropper. More specifically, we assume that selection combining is applied at both the receiver and eavesdropper. We first present statistical analysis for the signal-to-interference plus noise ratio (SINR). Then, closed-form expressions for the average secrecy capacity are derived for two special cases: Rayleigh fading and no interference. For the general case, we focus on the asymptotic secrecy capacity analysis. Finally, numerical results are provided for average secrecy capacity with with different values of NDand NE. Results show that the scaling law of the secrecy capacity is 1/L log2(ND/NE).

Physical-layer secure is an important issue for untrusted relay systems. In this paper, we investigate secure precoding design for non-regenerative multiple-input multiple-output untrusted two-way relay systems, where artificial noise (AN) is applied at the source and the relay is untrusted. We aim to maximize the secrecy sum rate by jointly designing the source's signal and AN precoders and the relay's precoder, under the sources and relay transmit power constraints. We consider two scenarios that perfect and imperfect channel state information of all the channels is available. For the former, we convert the secure precoding problem to a difference of convex programming and develop a constrained concave convex procedure based iterative algorithm which can obtain a local optimal solution. We also provide asymptotic analysis on the maximum secrecy sum rate when the relay transmit power approaches infinity, and propose alternating optimization method to compute asymptotic optimal precoders. For the latter, we model the channel uncertainties by using worst-case criterion and propose the weighted minimum mean square error based method to solve the robust secure precoding problem. Numerical simulations are presented to show the effectiveness of our proposed schemes.

In this paper, we consider a mixed free-space optical (FSO) communication scheme with the help of a fixed relay. We assume that the links from the source to the relay are radio-frequency links with multiuser diversity operating in η-μ fading channels while the link between the relay and the destination is a FSO link with M-distribution. We first derive expressions for the cumulative distribution function of the end-to-end signal-to-noise ratio for the considered system with pointing errors and then use them to evaluate the outage probability and bit-error rate performance. We further present asymptotic performance expressions to investigate the diversity order. Finally some selected numerical results are given to verify our analytical results.

A mixed free-space optical (FSO) communication scheme is considered with the help of a fixed gain relay. We assume that the links from the source to the relay are radio frequency links with multiuser diversity operating in η-μ fading channels, while the link between the relay and the destination is a FSO link with M-distribution. We first derive expressions for the cumulative distribution function of the end-to-end signal-tonoise ratio for the considered system with pointing errors, and then use them to derive some exact closed-form expressions for the outage probability, bit-error rate performance, and ergodic capacity. To investigate the diversity order and effects of different system and channel parameters on the system performance, we further present the asymptotic performance expressions. On the other hand, we also present the performance analysis for a mixed RF/FSO system with variable-gain relaying and multiuser diversity. Results show that the system diversity orders for both fixed and variable gains systems are min{2Kμ, g2/2, α/2, k/2}, where K is the number of users, g represents the pointing error, and α and k are the channel parameters. Finally, some selected numerical results are given to corroborate the derived analytical results.

Simultaneous wireless information and power transfer (SWIPT) is a potential technique to solve the energy scarcity problem in wireless communication networks. Information transmission security is one of the key issues to be addressed in SWIPT. In this study, the authors consider guaranteeing the information transmission security of a multiple‐input multiple‐output non‐regenerative relay system with SWIPT in the physical layer by designing source and relay beamforming to maximise the security rate of the system. The problem is to design the source signal and artificial noise (AN) beamforming and the relay forwarding beamforming jointly, which is highly non‐convex. They first propose an alternating optimisation‐based algorithm, which designs the beamforming matrices at the source and relay separately and alternately. Next, they propose a joint design algorithm which designs the source signal and AN beamforming and the relay beamforming together. Finally, they propose a non‐iterative design algorithm with low complexity. The performances of the proposed design algorithms have been verified by computer simulations.

For conventional subcarrier pairing scheme in cooperative orthogonal frequency division multiplexing decode‐and‐forward multi‐relay networks, to avoid interference, each subcarrier pair (SP) is assigned to a single relay. Over a specific subcarrier, the destination receives signals transmitted from the relay. In this study, to better exploit the degrees of spatial freedom, the authors propose to assign each SP to multiple relays. Thus, over a specific subcarrier, the destination receives signals transmitted from multiple relays. Under the total network power constraint, to maximise the sum transmission rate, they propose a joint resource allocation scheme, in which they jointly optimised the four types of resources: assisting relays selection, transmission mode selection, subcarrier pairing and power allocation. They further propose a suboptimal algorithm which can significantly reduce the computational complexity of the aforementioned optimal allocation scheme with sacrificing little on the performance. It is shown from simulation results that the author's proposed schemes have significant performance improvement over the resource allocation schemes in the literature.

Cognitive radio is a potential technique to solve the spectrum shortage problem in wireless communications. Integrating wireless relaying into the cognitive radio networks can further improve the spectrum efficiency. In this study, a multiple‐input multiple‐output cognitive relay network is considered, where the primary network (PN) consists of one transmitter‐receiver pair and the secondary network consists of multiple active source‐destination pairs and non‐regenerative relays. All nodes in the networks are deployed with multiple antennas. How to avoid interference to the PN is an important task in the secondary network design. The precoders of the secondary sources and the receivers of the secondary destinations are designed in a well‐known zero‐forcing way. The secondary relays forward signals for the secondary source‐destination pairs by beamforming. With interference cancellation constraints and individual transmit power constraints, a relay beamforming scheme is proposed to maximise the total signal‐to‐interference‐plus‐noise ratio (SINR) at the secondary destinations. Then a maximising minimum SINR relay beamforming scheme is further proposed to provide max–min fairness among the secondary source‐destination pairs. The beamforming problems are formulated into the quadratically constrained quadratic fractional programming problems, and are solved by the semi‐definite relaxation technique. The performances of these beamforming schemes have been verified by computer simulations.

In this paper, we consider a free-space optical (FSO) communication scheme with the help of a variable gain relay where the links from the source to the relay are radio-frequency (RF) links while the links between the relay and the destination are FSO links with M-distribution. To mitigate the effects of multipath fading and atmospheric turbulence, we apply transmit diversity at the source and selection combining (SC) at the destination, while the relay is only equipped with single RF receive antenna for receiving signal and one aperture for relaying the information. With this setup, we first derive expressions for the outage probability, bit-error rate, and the average capacity. We further investigate the effect of pointing errors on the system performance.

In this paper, we consider an amplify-and-forward hybrid satellite-terrestrial co-operative network in the presence of cochannel interference (CCI). More specifically, we assume that both the satellite-destination and the satellite-relay links undergo the shadowed-Rician fading and the relay-destination link follows the Nakagami-m fading. By applying the amplify-and-forward (AF) protocol at the terrestrial relay, both the relay and the destination are corrupted by cochannel interference from the terrestrial network. Based on this setup, we first derive the approximate statistical distributions signal-to-interference-plus noise ratio (SINR) and then analyze the system performance. To obtain more insights into the system performance, some asymptotical bit-error rate (BER) results are provided. Moreover, we extend our analysis to a multiple-relay network and analyze the asymptotic performance. Finally, some numerical results are provided to verify our analysis.

In this work, we consider a relay-assisted free-space optical (FSO) communication scheme in which the relay services multiple users and only the best user is selected so that the channel fluctuations can be effectively exploited to produce a selection diversity gain. We assume that the link from the source to the relay is a radio-frequency (RF) link while the link between the relay and the destination is an FSO link. More specifically, we first present a statistical analysis for the systems under consideration over both weak and strong atmospheric turbulence channels. Based on these results, the capacity of these systems with and without adaptive transmission is analyzed.

In this paper, we consider the performance of a two-way amplify-and-forward relaying network (AF TWRN) in the presence of unequal power co-channel interferers (CCI). Specifically, we consider AF TWRN with an interference-limited relay and two noisy-nodes with channel estimation error and CCI. We derive the approximate signal-to-interference plus noise ratio expressions and then use these expressions to evaluate the outage probability and error probability. Numerical results show that the approximate closed-form expressions are very close to the exact ones.

In this paper, we consider the performance of a two-way amplify-and-forward relaying network (AF TWRN) in the presence of unequal power co-channel interferers (CCI). Specifically, we first consider AF TWRN with an interference-limited relay and two noisy-nodes with channel estimation errors and CCI. We derive the approximate signal-to-interference plus noise ratio expressions and then use them to evaluate the outage probability, error probability, and achievable rate. Subsequently, to investigate the joint effects of the channel estimation error and CCI on the system performance, we extend our analysis to a multiple-relay network and derive several asymptotic performance expressions. For comparison purposes, we also provide the analysis for the relay selection scheme under the total power constraint at the relays. For AF TWRN with channel estimation error and CCI, numerical results show that the performance of the relay selection scheme is not always better than that of the all-relay participating case. In particular, the relay selection scheme can improve the system performance in the case of high power levels at the sources and small powers at the relays.

In this paper, we consider a distributed beamforming scheme (DBF) in a spectrum sharing system where multiple secondary users share the spectrum with the licensed primary users under an interference temperature constraint. We assume that DBF is applied at the secondary users. We first consider optimal beamforming and compare it with the user selection scheme in terms of the outage probability and bit-error rate performance. Since perfect feedback is difficult to obtain, we then investigate a limited feedback DBF scheme and develop an outage probability analysis for a random vector quantization (RVQ) design algorithm. Numerical results are provided to illustrate our mathematical formalism and verify our analysis.

In this paper, taking into account realistic propagation conditions, namely, spatial correlation, keyhole channels, and unequal-power co-channel interference, we investigate the performance of a wireless relay network where all the nodes are equipped with multiple antennas. Considering channel state information assisted amplify-and-forward protocol, we present analytical expressions for the symbol error rate (SER) and outage probability. More specifically, we first derive the SER expressions of a relay system with orthogonal space-time block coding (OSTBC) over correlated/keyhole fading channels. We also analyze the outage probability of interference corrupted relay systems with maximal ratio combing (MRC) at the receiver as well as multiple-input multiple-output MRC (MIMO MRC). Numerical results are given to illustrate and verify the analytical results.

Abstract In this paper, we investigate the performance of a multiuser wireless relay network with each of its nodes equipped with N antennas and transmit beamforming at its source and relay, where multiuser diversity (MD) is exploited to further improve the system performance. In the first part of this paper, by deriving the approximate error performance expression for a single‐relay MD system without the direct link, we obtain the maximum diversity order achievable by the CSI‐assisted amplify‐and‐forward (CAF) protocol. Then, by taking the direct link into consideration, we propose a sub‐optimal transmit beamforming scheme and show the performance loss is very small. Copyright © 2010 John Wiley & Sons, Ltd.

In this paper, we investigate the effect of channel estimation error on the capacity and bit-error rate (BER) of a multiple-input multiple-output (MIMO) transmit maximal ratio transmission (MRT) and receive maximal ratio combining (MRC) systems over uncorrelated Rayleigh fading channels. We first derive the ergodic (average) capacity expressions for such systems when power adaptation is applied at the transmitter. The exact capacity expression for the uniform power allocation case is also presented. Furthermore, to investigate the diversity order of MIMO MRT-MRC scheme, we derive the BER performance under a uniform power allocation policy. We also present an asymptotic BER performance analysis for the MIMO MRT-MRC system with multiuser diversity. The numerical results are given to illustrate the sensitivity of the main performance to the channel estimation error and the tightness of the approximate cutoff value.

Abstract In this paper, we present a comprehensive capacity analysis of the downlink of multiuser diversity (MD) systems with adaptive transmission over Rayleigh fading channels. First, the exact capacity of the single‐input single‐output (SISO) systems with MD and adaptive transmission technique is derived. The optimal power allocation scheme for such a system is shown to be a water‐filling algorithm. Next, we derive the exact closed‐form capacity expressions for different multiple‐input multiple‐output (MIMO) schemes, including the selective combining (SC), maximum ratio combining (MRC) and space‐time block codes (STBC). In order to avoid the cumbersome numerical root finding techniques in solving the optimal cutoff SNR level below which the channel is not used, we also provide the approximate expressions for the cutoff level. For the MD MIMO systems, it is observed that the optimal power allocation strategy is to focus transmit power on a single transmit antenna (e.g. Tx‐MRC/Rx‐MRC scheme) or selecting the best transmit antennas (e.g. Tx‐SC/Rx‐MRC scheme). Copyright © 2007 John Wiley & Sons, Ltd.

Abstract In this paper, we present a comprehensive performance analysis for multiple‐input multiple‐output (MIMO) systems with multiuser diversity over Rayleigh fading channels. We derive exact closed‐form expressions of the outage probability and the average bit error rate (BER) for different MIMO schemes, including the selective combining (SC), maximum ratio combining (MRC) and space‐time block codes (STBC). We also provide the explicit upper bounds on the BER performance. Finally, the mathematical formalism is verified by numeric results that study the interaction between the antenna diversity and the multiuser diversity. It is observed that the system performance is deteriorated as the number of transmit antennas increases in multiuser scenario, which is unlike the case in single‐user systems. Copyright © 2007 John Wiley & Sons, Ltd.

In this letter, we present a comprehensive performance analysis of orthogonal space-time block codes (STBCs) with transmit antenna selection under uncorrelated Rayleigh fading channels. Two best transmit antennas that maximize the instantaneous received signal-to-noise (SNR) are selected. Using the well-known moment generating function-based analysis approach, we derive the exact average symbol error rate (SER) for M-ary signals. Furthermore, we provide tight upper bounds on the SER for any number of transmit antennas and receive antennas. The tightness is verified by simulation results. It is shown that the diversity order, with antenna selection, is maintained as that of the full complexity systems