With the development of the sixth generation wireless communication, the increasingly scarce spectrum resources limit the further increase in data rate and exacerbate the interference problem among different users and applications. To address this issue, rate-splitting multiple access (RSMA) provides a flexible framework that unifies existing orthogonal and non-orthogonal multiple access schemes. In this work, we analyze the interference scenario of RSMA-based space-terrestrial transmission systems, with multiple satellite users independently and uniformly distributed in the coverage area of the serving satellite. Specifically, the outage performance at the satellite users (resp. terrestrial base station (BS) users) is assessed while considering the interference from the BS users (resp. the satellite and the BSs of other cells). Approximate analytical expressions of the outage probability at each satellite user/BS user are derived, numerically evaluated, and verified through simulation results. The impacts of RSMA power allocation factors, fading parameters, interference severity, and satellite altitude on outage performance are thoroughly analyzed, and the trade-off between outage performance and user fairness is also illustrated.

Programmable wireless environments (PWEs) have emerged as a key paradigm for next-generation communication networks, aiming to transform wireless propagation from an uncontrollable phenomenon into a reconfigurable process that can adapt to diverse service requirements. In this framework, pinching-antenna systems (PASs) have recently been proposed as a promising enabling technology, as they allow the radiation location and effective propagation distance to be adjusted by selectively exciting radiating points along a dielectric waveguide. However, most existing studies on PASs rely on the idealized assumption that pinching-antenna (PA) positions can be continuously adjusted along the waveguide, while realistically only a finite set of pinching locations is available. Motivated by this, this paper analyzes the performance of two-state PASs, where the PA positions are fixed and only their activation state can be controlled. By explicitly accounting for the spatial discreteness of the available pinching points, closed-form analytical expressions for the outage probability and the ergodic achievable data rate are derived. In addition, we introduce the pinching discretization efficiency to quantify the performance gap between discrete and continuous pinching configurations, enabling a direct assessment of the number of PAs required to approximate the ideal continuous case. Finally, numerical results validate the analytical framework and show that near-continuous performance can be achieved with a limited number of PAs, offering useful insights for the design and deployment of PASs in PWEs.

This paper investigates the reliability and security of a hybrid double-reconfigurable intelligent surface (HDRIS) aided wireless-powered communication (WPC) system in the presence of eavesdroppers, where one active/passive RIS (RIS-1) is deployed between the power station and the information user, and the other passive/active RIS (RIS-2) is deployed between the information user and the access point. We propose two modes of HDRIS aided WPC, i.e., HDRIS-I with passive RIS-1 and active RIS-2, and HDRIS-II with active RIS-1 and passive RIS-2. Based on the two modes, we analyze the outage probability (OP) from the perspective of reliability and intercept probability (IP) from the perspective of security, and derive their accurate and asymptotic expressions, respectively. Moreover, a joint metric is proposed, i.e., reliability and security probability (RSP), to reveal the superiority of HDRIS compared to pure double-RIS (PDRIS). The results show that compared to PDRIS, the proposed HDRIS-I and HDRIS-II have better OPs than PDRIS-I with two passive RISs, but worse OPs than PDRIS-II with two active RISs. Both HDRIS-I and HDRIS-II have worse IPs than PDRIS-I, but better IPs than PDRIS-II. Interestingly, in HDRIS-I and HDRIS-II, the diversity gain for legitimate users is proportional to the number of elements of the RISs, while the diversity gain for eavesdroppers is only 1, indicating that HDRIS provide greater benefits for legitimate communications. In Particular, HDRIS-I achieves the best RSP under high transmission power, while HDRIS-II achieves the best RSP under low transmission power, demonstrating the superiority of HDRIS.

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

Wireless jamming identification, which detects and classifies electromagnetic jamming from non-cooperative devices, is crucial for emerging low-altitude wireless networks consisting of many drone terminals that are highly susceptible to electromagnetic jamming. However, jamming identification schemes adopting deep learning (DL) are vulnerable to attacks involving carefully crafted adversarial samples, resulting in inevitable robustness degradation. To address this issue, we propose a differential transformer framework for wireless jamming identification. Firstly, we introduce a differential transformer network in order to distinguish jamming signals, which overcomes the attention noise when compared with its traditional counterpart by performing self-attention operations in a differential manner. Secondly, we propose a randomized masking training strategy to improve network robustness, which leverages the patch partitioning mechanism inherent to transformer architectures in order to create parallel feature extraction branches. Each branch operates on a distinct, randomly masked subset of patches, which fundamentally constrains the propagation of adversarial perturbations across the network. Additionally, the ensemble effect generated by fusing predictions from these diverse branches demonstrates superior resilience against adversarial attacks. Finally, we introduce a novel consistent training framework that significantly enhances adversarial robustness through dual-branch regularization. Simulation results demonstrate that our proposed methodology is superior to existing methods in boosting robustness to adversarial samples.

This contribution focuses on the optimization of bit error rate (BER) performance in fluid antenna (FA)-aided wireless communication systems, which leverage the new degrees of freedom provided by positional flexibility, thus surpassing the limitations of conventional fixed-position antenna (FPA) systems. In this context, a theoretical analysis identifies key metrics for maximum likelihood (ML) and zero-forcing (ZF) detectors, specifically the minimum singular value and effective rank, as determinants of system performance. Then, for single-input single-output (SISO) channels, the optimization problem is formulated as channel gain maximization constrained by the predefined moving region and then solved using a mixed-integer linear programming (MILP) model. Furthermore, for multiple-input multiple-output (MIMO) channels, an alternating optimization (AO) algorithm incorporating the Frank-Wolfe method is proposed to optimize ML and ZF performances, targeting minimum singular value maximization for ML and singular value balancing for ZF, both subject to moving region and antenna spacing constraints. Finally, numerical results exhibit significant performance gains for the FA system over its conventional FPA alternative. In general, these findings highlight the potential of FA systems for addressing ultra-reliable communication challenges in the sixth generation (6G) wireless communications.

The growth of communication technologies has led to a corresponding increase in the need for information security. The use of covert communication techniques has the potential to significantly reduce the likelihood of the transmitted signal being intercepted by unintended receivers, thereby significantly increasing the security of the information. In this paper, we propose an energy-dispersed random time-hopping (ED-RTH) covert communication scheme. Building on existing time uncertainty schemes, this scheme further enhances time uncertainty through random time-hopping, while dispersing signal energy to achieve stronger covertness. We present a model for analyzing the covertness of the ED-RTH scheme. Given the complexity of the likelihood ratio distribution, the Kullback-Leibler (KL) divergence is used to analyze the lower bound of Willie’s detection error probability. Through constructing behavioral-level simulations for validation, we investigated the impact of the number of dispersed time slotsKon both Willie’s detection error probability and the system’s covert throughput. Finally we compared the proposed ED-RTH scheme with existing time uncertainty scheme, and the results demonstrate that the ED-RTH scheme achieves significantly enhanced covertness.

With the rapid growth of high-speed rail (HSR) networks, reliable communication is increasingly challenging due to complex terrain and coverage gaps in remote areas. Uncrewed aerial vehicles (UAVs), with their mobility and flexibility, provide aerial relay support to bridge these gaps, enhance signal strength, and improve HSR communication reliability. However, their performance in millimeter-wave (mmWave) systems is significantly degraded by mechanical jitter caused by environmental factors such as wind and turbulence, which adversely affects beam alignment and overall communication quality. To address these challenges, this work introduces a comprehensive analytical framework. We first develop a statistical model that characterizes the relationship between beam gain and jitter intensity. Subsequently, closed-form expressions are derived for the outage probability and ergodic data rate of UAV-assisted HSR mmWave systems under jitter influence, taking into account both co-located (CA) and distributed antenna (DA) configurations. Furthermore, we propose an adaptive beamwidth design that maximizes the average ergodic rate by adjusting the beamwidth according to UAV jitter severity. Numerical simulations verify that this approach significantly improves system capacity and robustness compared with conventional static beamforming, confirming its effectiveness.

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

As virtual reality (VR) and 360° video applications continue to gain traction, multi-quality tile-based 360° video streaming has emerged as a flexible and adaptive solution for delivering high-quality immersive content while optimizing bandwidth usage. However, the presence of mixed quality levels within a single 360° video frame can adversely affect users' perceived quality. In this work, we investigate the impact of spatial quality variations across tiles and within users' viewports, and provide improved perceptual quality modeling for tiled 360° videos. To realize this goal, we introduce the Subjective Tile based Assessment for 360° Videos (STAV360) dataset, which includes six source 360° videos, each encoded using twelve tile based configurations, subjective ratings from 27 participants, and corresponding viewing trajectories. Based on this dataset, we propose novel tile-based and viewport-aware 360° video quality assessment (360° VQA) models that incorporate tile-level quality information and user interaction data. Experimental results show that our models outperform conventional full-frame methods by more accurately predicting perceived quality. This work provides key insights for designing perceptually-driven quality metrics and lays the foundation for more efficient and adaptive tile-based 360° video streaming strategies.

As 6G wireless networks seek to enable robust and dynamic programmable wireless environments (PWEs), reconfigurable intelligent surfaces (RISs) have emerged as a cornerstone for controlling electromagnetic wave propagation. However, realizing the potential of RISs for demanding PWE applications depends on precise and real-time user localization, especially in scenarios with random receiver orientations and inherent hardware imperfections. To address this challenge, we propose a novel optical localization framework that integrates conventional ceiling-mounted LEDs with light-emitting reconfigurable intelligent surfaces (LeRISs). By leveraging the spatial diversity offered by the LeRIS architecture, the framework introduces robust signal paths that improve localization accuracy and reduce errors under varying orientations. To this end, we derive a system of equations for received signal strength-based localization that accounts for random receiver orientations and imposes spatial constraints on LED placement, ensuring unique and reliable solutions. Finally, our simulation results demonstrate that the proposed framework achieves precise beam control and high spectral efficiency even for RISs with large number of reflecting elements by tightly coupling the localization process with the beamforming configuration, allowing accurate direction estimation and robust PWE operation.

In response to the increasing number of devices expected in next-generation networks, a shift to over-the-air (OTA) computing has been proposed. By leveraging the superposition of multiple access channels, OTA computing enables efficient resource management by supporting simultaneous uncoded transmission in the time and frequency domains. To advance the integration of OTA computing, our study presents a theoretical analysis that addresses practical issues encountered in current digital communication transceivers, such as transmitter synchronization (sync) errors and intersymbol interference (ISI). To this end, we investigate the theoretical mean squared error (MSE) for OTA transmission under sync errors and ISI, while also exploring methods for minimizing the MSE in OTA transmission. Using alternating optimization, we also derive optimal power policies for both the devices and the base station. In addition, we propose a novel deep neural network (DNN)-based approach to design waveforms that improve OTA transmission performance under sync errors and ISI. To ensure a fair comparison with existing waveforms such as raised cosine (RC) and better-than-raised-cosine (BTRC), we incorporate a custom loss function that integrates energy and bandwidth constraints along with practical design considerations such as waveform symmetry. Simulation results validate our theoretical analysis and demonstrate performance gains of the designed pulse over RC and BTRC waveforms. To facilitate testing of our results without the need to rebuild the DNN structure, we also provide curve-fitting parameters for the selected DNN-based waveforms.

This paper presents a non-orthogonal retransmission framework for integrated satellite-terrestrial networks (ISTNs). This framework integrates hybrid automatic repeat request (HARQ) with incremental redundancy (HARQ-IR) and rate splitting multiple access (RSMA). HARQ-IR and RSMA are utilized for downlink retransmission and multi-user interference management, respectively, to address the requirements for extensive and highly reliable concurrent connections. Employing the inclusion-exclusion principle, we establish precise upper and lower bounds for the exact outage probability (OP), which function as approximations. We also examine the asymptotic OP, which yields significant insights and informs a partial HARQ-IR-RSMA scheme. We propose a joint common-private power allocation (JCPPA) algorithm based on alternating optimization (AO) to enhance the energy efficiency (EE) of the partial retransmission scheme while adhering to power and outage probability (OP) constraints. The non-convex problem is addressed effectively via asymptotic OP, which allows for the decomposition into common and private power optimization subproblems utilizing the Dinkelbach method. The common power optimization subproblem is convex and can be solved using the CVX toolbox. The private power optimization subproblem is addressed through variable substitution and the application of the Lagrangian dual algorithm. The numerical results indicate the accuracy and superiority of the proposed special scheme regarding outage performance and energy efficiency when compared to benchmarks.

This paper introduces a sensing-centric joint communication and millimeter-wave radar paradigm to facilitate collaboration among intelligent vehicles. We first propose a chirp waveform-based delay-Doppler quadrature amplitude modulation (DD-QAM) that modulates data across delay, Doppler, and amplitude dimensions. Building upon this modulation scheme, we derive its achievable rate to quantify the communication performance. We then introduce an extended Kalman filter-based scheme for four-dimensional (4D) parameter estimation in dynamic environments, enabling the active vehicles to accurately estimate orientation and tangential-velocity beyond traditional 4D radar systems. Furthermore, in terms of communication, we propose a dual-compensation-based demodulation and tracking scheme that allows the passive vehicles to effectively demodulate data without compromising their sensing functions. Simulation results underscore the feasibility and superior performance of our proposed methods, marking a significant advancement in the field of autonomous vehicles. Simulation codes are provided to reproduce the results in this paper: https://github.com/LiZhuoRan0.

The optimal solution to an optimization problem depends on the problem’s objective function, constraints, and size. While deep neural networks (DNNs) have proven effective in solving optimization problems, changes in the problem’s size, objectives, or constraints often require adjustments to the DNN architecture to maintain effectiveness, or even retraining a new DNN from scratch. Given the nature of wireless networks, which involves multiple and diverse objectives that can have conflicting requirements and constraints, we propose a multi-task learning (MTL) framework to enable a single DNN to jointly solve a range of diverse optimization problems. In this framework, optimization problems with varying dimensionality values, objectives, and constraints are treated as distinct tasks. To jointly address these tasks, we propose a conditional computation-based MTL approach with routing. The multi-task DNN consists of two components, the base DNN (bDNN), which is the single DNN used to extract the solutions for all considered optimization problems, and the routing DNN (rDNN), which manages which nodes and layers of the bDNN to be used during the forward propagation of each task. The output of the rDNN is multiplied with all bDNN’s weights during the forward propagation, creating a unique computational path through the bDNN for each task. This setup allows the tasks to either share parameters or use independent ones, with the decision controlled by the rDNN. The proposed framework supports both supervised and unsupervised learning scenarios. Based on this framework, a soft modularization and a hard parameter sharing approach of lower complexity are proposed. The numerical results demonstrate the efficiency of the proposed MTL approaches compared to several multi-task benchmarks and the single-task DNN approach.

This paper propose a two-stage quantum neural network (QNN) framework for cell-free multiple-input and multiple-output (MIMO) wireless communication systems. Cell-free MIMO, which has been regarded as a key technology for enhancing the performance of the next-generation wireless communication systems, leverages the collective capability of multiple distributed access points (APs), allowing collaboration between them. However, optimizing cell-free MIMO can pose challenges for centralized optimization schemes. In particular, complexities associated with the joint optimizations of user-transmission assignment and transmission precoding, two factors which are of much importance for determining the quality-of-service, grow with the number of APs and served users. To this end, a unified scheme employing distributed QNNs is used to optimize downlink transmitter-user assignment and transmit precoding with the goal of maximizing the achieved sum rate. Firstly, the cloud processing unit, which holds holistic information about the particular wireless communication network, employs QNN to assign each AP to its designated mobile terminal. Secondly, the edge processing units, which are computed in proximity relative to the AP in order to reduce latency, estimate transmission precoding for their corresponding APs. Moreover, numerical results are presented to showcase the performance of the proposed protocol.

Stacked intelligent metasurfaces (SIMs), which integrate multiple programmable metasurface layers, have recently emerged as a promising technology for advanced wave-domain signal processing. SIMs benefit from flexible spatial degree-of-freedom (DoF) while reducing the requirement for costly radio-frequency (RF) chains. However, current state-of-the-art SIM designs face challenges such as complex phase shift optimization and energy attenuation from multiple layers. To address these aspects, we propose incorporating meta-fibers into SIMs, with the aim of reducing the number of layers and enhancing the energy efficiency. First, we introduce a meta-fiber-connected 2-layer SIM that exhibits the same flexible signal processing capabilities as conventional multi-layer structures, and explains the operating principle. Subsequently, we formulate and solve the optimization problem of minimizing the mean square error (MSE) between the SIM channel and the desired channel matrices. Specifically, by designing the phase shifts of the meta-atoms associated with the transmitting-SIM and receiving-SIM, a non-interference system with parallel subchannels is established. In order to reduce the computational complexity, a closed-form expression for each phase shift at each iteration of an alternating optimization (AO) algorithm is proposed. We show that the proposed algorithm is applicable to conventional multi-layer SIMs. The channel capacity bound and computational complexity are analyzed to provide design insights. Finally, numerical results are illustrated, demonstrating that the proposed two-layer SIM with meta-fiber achieves over a 25% improvement in channel capacity while reducing the total number of meta-atoms by 59% as compared with a conventional seven-layer SIM.

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

Millimeter-wave (mmWave) communications, coupled with directional antenna-based Flying Ad-Hoc Networks (FANETs), have received considerable attention for their potential to provide high-speed, low-latency communications for a variety of applications. However, the high mobility of Unmanned Aerial Vehicles (UAVs) in FANETs leads to dynamic changes in relative positions, resulting in frequent link failures. Effective link maintenance in such networks has become a critical challenge. This paper addresses this issue by developing mathematical models of link disconnections in directional antenna-based FANETs. Specifically, we derive the probability density functions for link disconnections due to distance and angular misalignment in closed-form expressions. Based on these prediction models, we propose the Adaptive Link Breakage Prediction with Directionality (ALBP-D) method, which exploits the high directional gain of directional antennas to extend link lifetime and improve network performance. We compare ALBP-D with two baseline methods, the Periodic Link Maintenance (PLM) method and the Residual Path Lifetime (RPL) method, through extensive simulations. The results show that ALBP-D achieves superior performance, with approximately a 10-fold improvement in both link lifetime and network connectivity duration compared to the baseline methods. In addition, ALBP-D exhibits significant improvements in maintenance overhead efficiency, especially at higher max range adjustment count, achieving a 5 to 7-fold improvement over baseline methods. These results highlight the effectiveness of ALBP-D in directional antenna-based FANETs. We also implemented a prototype system consisting of a directional antenna node and an omnidirectional antenna node using realistic UAV trajectory data. Experimental results show that the prediction models agree well with the real link disconnection data, confirming the practical feasibility and accuracy of the proposed method.

One of the main goals of the upcoming sixth-generation (6G) wireless networks is the ability to support higher network density, while ensuring a high quality of service for each user. In this paper, we introduce distributed uplink rate-splitting multiple access (DU-RSMA), define its basic principles, and provide insights into its advantages. Specifically, a system with two remote radio heads (RRHs) and two users is investigated. To improve the performance of the system, we consider that the RRHs can communicate through a feedback link, and thus they are able to decode the received messages either independently or with the assistance of the other RRH, since the decoded information can be shared through the feedback link. It should be noted that this scheme increases the achievable capacity region compared to the known multiple access schemes, which is also evaluated by a novel metric termed “fill factor”. Both the case of adaptive transmission rates and the case of fixed transmission rates are investigated. To this end, the ergodic rate is investigated to cover the former case, while the outage probability is studied for the latter. Closed-form expressions are derived for both metrics. Finally, the analytical expressions are validated by simulation results, which explicitly show the impact of each parameter on the performance of the system, and prove that the proposed scheme outperforms the corresponding benchmarks.

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

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

Wireless federated learning (FL) facilitates collaborative training of artificial intelligence (AI) models to support ubiquitous intelligent applications at the wireless edge. However, the inherent constraints of limited wireless resources inevitably lead to unreliable communication, which poses a significant challenge to wireless FL. To overcome this challenge, we propose Sign-Prioritized FL (SP-FL), a novel framework that improves wireless FL by prioritizing the transmission of important gradient information through uneven resource allocation. Specifically, recognizing the importance of descent direction in model updating, we transmit gradient signs in individual packets and allow their reuse for gradient descent if the remaining gradient modulus cannot be correctly recovered. To further improve the reliability of transmission of important information, we formulate a hierarchical resource allocation problem based on the importance disparity at both the packet and device levels, optimizing bandwidth allocation across multiple devices and power allocation between sign and modulus packets. To make the problem tractable, the one-step convergence behavior of SP-FL, which characterizes data importance at both levels in an explicit form, is analyzed. We then propose an alternating optimization algorithm to solve this problem using the Newton-Raphson method and successive convex approximation (SCA). Simulation results confirm the superiority of SP-FL, especially in resource-constrained scenarios, demonstrating up to 9.96% higher testing accuracy on the CIFAR-10 dataset compared to existing methods.

Integrated sensing and communication (ISAC) is expected to enable the fifth-generation (5G) networks to provide ubiquitous communication and sensing. However, some high-dynamic scenarios hinder applications of conventional ISAC schemes owing to the high overhead and poor real-time performance. In this paper, we design a novel ISAC architecture and propose a large language model (LLM) based two-stage beamforming prediction scheme. Specifically, in the first stage, we develop an LLM-based approach to predict the future channel state information (CSI) according to the history echoes. Via the data preprocessing and supervised fine-tuning, the LLM can achieve effective channel prediction task with unstructured data. In the second stage, according to the predicted/estimated CSI, we formulate a beamforming optimization problem to maximize the achievable sum rate while satisfying the quality of service (QoS). Then, we propose a Primary-dual network with the unsupervised adversarial learning to handle it, facilitating the on-line beamforming. Simulation results verify that, compared with the benchmarks, our proposed beamforming prediction scheme not only enjoys a higher channel prediction accuracy but also achieves a better balance between the performance and computational complexity.

In this paper, we develop an energy minimization framework for wireless-powered multi-access edge computing (WP-MEC) networks, where two zero-energy reconfigurable intelligent surfaces (zeRISs) are employed to support energy harvesting and task offloading. In the downlink energy harvesting period, the hybrid access point (HAP) provides energy beamforming for multiple zero-energy devices and two zeRISs, where the harvested energy is used to offload tasks in the uplink period. Specifically, an optimization problem is formulated to minimize the energy consumption at the HAP, jointly considering the nonlinear energy harvesting model and cascaded RIS link. Next, an efficient iterative solution is designed to realize joint time allocation, HAP energy beamforming, and reflection coefficients for two-RIS by employing alternating optimization and semidefinite relaxation methods. Numerical results demonstrate the superiority of the algorithm. Compared to the corresponding single RIS setup, the energy consumption of HAP under the proposed two-zeRIS scheme is significantly reduced.

Free space optics (FSO) has emerged as a key technology for high-data-rate wireless communication, thanks to the availability of mature transceiver designs and unlicensed spectrum. Although FSO links are highly directive, atmospheric turbulence introduces random scintillation effects analogous to RF multipath fading, degrading system performance. Traditional models often treat turbulence as an intensity-based stochastic process, providing limited insight into phase distortions and wavefront aberrations such as beam wander. While split-step propagation methods can capture these effects accurately, their computational cost is prohibitive for large-scale simulations. In this paper, we propose a single-phase screen channel model using Zernike polynomials, effectively representing the turbulence-induced phase aberrations without resorting to full multi-screen wave propagation. Because it preserves the full complex wavefront, the proposed method captures both phase and intensity distortions, enabling evaluation of beam-shaping and adaptive optics design and providing an accurate performance baseline for coherent FSO links. Simulation results prove the value of the proposed model, as interesting insights can be derived regarding the intensity distribution at the receiver and the impact of the receiver lens.

One of the main goals of the upcoming sixthgeneration (6G) wireless networks is the ability to support higher network density, while ensuring a high quality of service for each user. To this end, we introduce distributed uplink ratesplitting multiple access (DU-RSMA), define its basic principles, and provide insights into its benefits. DU-RSMA allows multiple users to efficiently share the same resource block through message splitting and the use of remote radio heads that independently decode incoming messages and exchange the decoded information through a feedback link. It should be noted that this scheme increases the achievable capacity region, compared to the known multiple access schemes, which is also evaluated through a novel metric, termed as “fill factor”. Since adaptive transmission rates are considered, the performance of the proposed scheme is investigated in terms of the ergodic rate of both users, for which we derive closed-form expressions. Simulation results illustrate the performance gains of DU-RSMA over corresponding benchmarks and investigate the effect of system parameters on its performance.

Integrated sensing and communication (ISAC) is seen as a future solution to frequency congestion due to its excellent ability to simultaneously support target sensing and information transmission. However, it also introduces a potential security threat due to the sensing behavior. In this paper, we propose a covert ISAC scheme against collusive wardens. In particular, a dual-function base station continuously sense an aerial target while communicating with a ground receiver. First, we derive a closed-form expression of each warden's detection outage probability to obtain the global detection outage probability. Then, we jointly optimize the communication and sensing beamformings to maximize the covert transmission rate under the worst case that all wardens can collusively adjust their detection thresholds to achieve the best detection. To tackle this non-convex optimization problem, an iteration scheme is proposed. Numerical results demonstrate the validity of the proposed covert ISAC scheme.

To meet the requirements of the artificial internet of things (AIoT), decentralization is essential to provide wide coverage, trustworthiness, and low-latency communication. For this purpose, decentralized federated learning (DFL) has rapidly evolved and gained popularity in recent years by reducing reliance on a central server and promoting a more robust, scalable, and privacy-preserving system. Nevertheless, the exchange of model updates and gradients in peer-to-peer (P2P) wireless communication systems introduces new vulnerabilities that threaten both model performance and data security, while frequent P2P communication among clients can lead to high communication costs. To address these issues, in this work, we develop a communicationefficient and security-enhanced DFL algorithm, which integrates the fast incremental alternating direction method of multipliers (FI-ADMM) algorithm with parameter-selective additively homomorphic encryption. Additionally, by introducing a first-order approximation for primal updates and rearranging the update order in FI-ADMM, the proposed method is superior to the other benchmarks in terms of computational and time complexity, which is validated by theoretical analysis and simulations.

Pinching-antenna systems (PASs) have recently emerged as a flexible, cost-effective route to large-scale antenna deployments envisioned for integrated sensing and communications (ISAC). This paper establishes the fundamental sensing limits of a bistatic PAS link by deriving closed-form Cramér-Rao lower bounds for the joint estimation of range and direction when a target is illuminated by pinching antennas placed along a dielectric waveguide and observed by a uniform linear array receiver. By rigorously preserving the amplitude and phase variations of each pinching antenna, as well as exploiting their non-uniform deployment, we gain valuable insights into the performance gain of PASs over conventional antenna arrays. Numerical results validate that the PAS-based ISAC can achieve centimeter-level ranging and sub-degree angular resolution with significantly fewer hardware resources than conventional uniform linear arrays. The derived bounds provide practical design guidelines for next-generation PAS-enabled ISAC systems.

Security is emerging as a critical performance metric for next-generation wireless networks, but conventional multiple-input-multiple-output (MIMO) systems often suffer from severe path loss and are vulnerable to nearby eavesdroppers due to their fixed-antenna configurations. Pinching-antenna systems (PAS) offer a promising alternative, leveraging reconfigurable pinching antennas (PAs) positioned along low-loss dielectric waveguides to enhance channel conditions and dynamically mitigate security threats. In this paper, we propose an artificial noise (AN)-based beamforming scheme for downlink transmissions in PAS, with the goal of maximizing the secrecy rate. A closed-form solution is derived for the single-waveguide scenario, while an alternating optimization approach addresses more complex multiple waveguide setups. Numerical results show that the proposed scheme significantly outperforms conventional MIMO and existing PAS security schemes.

The evolution toward sixth-generation wireless networks introduces the concept of intelligent and reconfigurable environments designed to support advanced services. Achieving this paradigm shift requires addressing the limitations of traditional wireless systems, particularly their inability to effectively counteract path loss or adapt to diverse user scenarios. Pinching antenna systems (PASs) have emerged as a promising solution, enabling dynamic control over path loss by leveraging dielectric waveguides to support low-loss transmission at high frequencies. This work presents an analytical framework for assessing the reliability of PASs through the derivation of closed-form expressions for the outage probability under both free-space and waveguide attenuation. In addition, a rigorous formulation is provided for the optimal positioning of the pinching antennas to maximize signal reception, taking into account the trade-off between waveguide losses and spatial separation. Simulation results validate the impact of waveguide attenuation on performance and show that PASs consistently outperform conventional architectures in terms of outage behavior, confirming their suitability for next-generation wireless networks.

Accurate indoor localization is crucial for enabling 6G applications, such as smart homes, augmented reality, and advanced healthcare systems. Optical wireless systems utilizing Light-Emitting Diodes (LEDs) offer centimeter-level accuracy due to their dominant line-of-sight (LoS) characteristics. However, most existing methods assume fixed and known user orientations, limiting their practical applicability in real-world scenarios with random orientations. In this paper, we propose an LED-based visible light positioning (VLP) scheme that accurately, through closed form equations, localizes users with arbitrary orientations using optical received signal strength (RSS) measurements. The proposed method achieves high localization accuracy, without requiring hardware for orientation measurements. Finally, an analytical expression for the error is derived, while Monte Carlo simulations validate the scheme's performance, highlighting the critical role of the parameters of the system in achieving accurate localization.

One of the main applications expected to be enabled by next-generation networks is computing. The goal-oriented nature of computing allows the use of different implementation techniques, with over-the-air (OTA) computation being one of the main proposed schemes due to its effective resource management and computational efficiency. In this work, we aim at optimizing the waveform of the system in the presence of intersymbol interference (ISI) and sampling error. To this end, we propose a deep neural network (DNN) framework that generates an optimal waveform that minimizes the mean square error (MSE) of the OTA computation system. To ensure that the generated waveform exhibits the same behavior as other common waveforms, weighted energy and spectrum constraints are included in the loss function of the training phase. To better mitigate ISI, the spectrum constraint integrates the roll-off factor of the waveform, allowing for the generation of different waveforms. Simulation results verify that the desired constraints are met and show a significant performance gain over state-of-the-art waveforms.

In the rapidly advancing field of sixth generation (6G) wireless networks, where the achievement of ultra-high data rates and energy efficiency is crucial, this study introduces the concept of super constellations as a solution to meet these pressing requirements. However, when higher-order modulations are employed, the system becomes increasingly susceptible to Gaussian phase noise (GPN), resulting in significant performance degradation. To address this issue, we propose a novel modulation scheme, called super amplitude phase shift keying (SAPSK), which is specifically designed to improve resilience against GPN. Furthermore, recognizing the critical need for efficient detection methods in high-order constellations, we present a detection framework that is not only capable of mitigating the detrimental effects of GPN, but also provides a foundation for the development of low-complexity detection algorithms. Specifically, we introduce the generalized polar distance detector (GPD-D), a detection metric that approximates maximum likelihood detection (MLD) in GPN-affected channels while introducing structured decision regions. Building on the GPD-D, SAPSK formulates a hexagonal lattice that provides improved energy efficiency and is further supported by a detection algorithm with Ό (1) complexity, ensuring fast and accurate symbol detection. Finally, the superiority of SAPSK is demonstrated through extensive numerical simulations, which show that SAPSK has significant advantages in terms of symbol error probability (SEP) over other conventional modulation schemes.

Abstract Integrated sensing and communication (ISAC) is a promising technique to increase spectral efficiency and support various emerging applications by sharing the spectrum and hardware between these functionalities. However, the traditional ISAC schemes are highly dependent on the accurate mathematical model and suffer from the challenges of high complexity and poor performance in practical scenarios. Recently, artificial intelligence (AI) has emerged as a viable technique to address these issues due to its powerful learning capabilities, satisfactory generalization capability, fast inference speed, and high adaptability for dynamic environments, facilitating a system design shift from model-driven to data-driven. Intelligent ISAC, which integrates AI into ISAC, has been a hot topic that has attracted many researchers to investigate. In this paper, we provide a comprehensive overview of intelligent ISAC, including its motivation, typical applications, recent trends, and challenges. In particular, we first introduce the basic principle of ISAC, followed by its key techniques. Then, an overview of AI and a comparison between model-based and AI-based methods for ISAC are provided. Furthermore, the typical applications of AI in ISAC and the recent trends for AI-enabled ISAC are reviewed. Finally, the future research issues and challenges of intelligent ISAC are discussed.

With the recent expansion of patient data availability and storage capabilities, healthcare entities tend to store an increasing amount of medical data locally. In addition, ongoing advances in the era of healthcare industry 5.0 and Artificial Intelligence of Things can lead to more efficient use of medical data, resulting in better health monitoring at lower costs. However, due to strict privacy restrictions related to the sensitive nature of medical data, it is often only used locally and ultimately underutilized. To this end, federated learning (FL) offers a promising solution for the efficient use of medical data, facilitating the development of reliable and robust healthcare tools. This can be achieved thanks to its decentralized nature, which allows participating entities to collaborate and thus develop and train a centralized shared model without requiring data sharing. Taking this into account, we present a Pareto-front optimization framework for FL-based health monitoring that is able to mitigate false negative predictions for the required level of false positives. By applying the proposed framework to four different medical applications, it is shown that the risk of misdiagnosis is significantly reduced, providing an additional tool for medical professionals.

Optical wireless communication (OWC) systems with multiple light-emitting diodes (LEDs) have recently been benefited from the assistance of optical reflecting intelligent surface (ORIS) to support energy-limited devices via simultaneous lightweight information and power transfer (SLIPT). This article studies the application of rate splitting multiple access (RSMA) for effective interference management and enhancing the data rate of these systems. Regarding the considerable bandwidth of the OWC band and also considerable energy consumption of the multi-LED transmitter, we formulate an energy efficiency (EE) maximization problem to jointly optimize the system variables, including transmit beamforming, LED selection, rate adaptation and ORIS element association, while adhering to the system requirements. Accordingly, we propose a dynamic resource allocation mechanism, leveraging proximal policy optimization (PPO) to accommodate system dynamism and optimize its variables. Concerning the frequent obstruction of OWC Line-of-Sight (LoS) links and consequently swift system reconfiguration, we improve the adaptability and predictability of the PPO agent by integrating Meta-learning technique. Simulations reveal that the proposed Meta-PPO algorithm has superior performance compared to the PPO method in the presence of ORIS with 76% gain. Furthermore, employing an ORIS in the proposed system model improves the performance by 51% compared to a scenario without ORIS.

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

integrated sensing and communication (ISAC) is a promising paradigm to alleviate spectrum congestion and facilitate a variety of emerging Internet of Things (IoT) applications. However, the direct links from the ISAC base station (BS) to the users may be blocked due to the obstacles. In this article, we investigate the double-active reconfigurable intelligent surfaces (RISs) assisted ISAC, where two active RISs are used to establish virtual line-of-sight (LoS) links from the ISAC BS to the users. In addition, the sum of the minimum sensing signal-to-interference-plus-noise ratios (SINRs) among multiple targets during a series of time slots is maximized, subject to Quality of Service (QoS) and transmit power constraints, through the joint optimization of transmit, reflection and receive beamforming. We first transform this nonconvex optimization problem in the dynamic environment into a Markov decision process (MDP), and then propose a twin delayed deep deterministic policy gradient (TD3)-based algorithm to solve it. Moreover, to enhance the generalization and stability, we integrate the generative adversarial network (GAN) into the TD3 algorithm and propose a GAN-TD3-based algorithm to handle the beamforming optimization problem. Compared with the TD3-based algorithm, the proposed GAN-TD3-based algorithm achieves the better performance and higher stability at the cost of higher computational complexity and slower convergence speed. Simulation results are presented to verify the effectiveness of our proposed algorithms and the superiority of the active RIS over the passive counterpart.

The emergence of new application scenarios, such as mobile edge computing (MEC) and the industrial internet of things (IIoT), places new demands on next-generation communication systems to support green and sustainable machine-to-machine communications, posing new challenges for wireless network resource allocation. In this paper, the problem of time resource allocation in wireless networks with periodic packet transmission is studied to achieve collision-free transmission. Based on the Diophantine equation, the effect of initial timeslot allocation on transmission collision is analyzed, and the timeslot collision graph (TCG) is constructed. The TCG is then used for timeslot allocation in two wireless communication scenarios. First, a maximum independent set timeslot allocation (MIS-TA) algorithm is proposed for the design of pre-deployed wireless networks. Given multiple packet periods, by finding the maximum independent set in the TCG, we can obtain the number combinations of all devices without transmission collisions and the corresponding timeslot allocation scheme. In addition, for dynamic networks, a dynamic weighted collision graph timeslot allocation (DWCG-TA) scheme is proposed to minimize the number of packet collisions with the given number of devices and transmission periods. We evaluate the DWCG-TA with simulations, which show that it effectively reduces the average transmission collision compared to carrier sense multiple access.

In this paper, we propose a novel approach to minimize the inference delay in semantic segmentation using split learning (SL), tailored to the needs of real-time computer vision (CV) applications for resource-constrained devices. Semantic segmentation is essential for applications such as autonomous vehicles and smart city infrastructure, but faces significant latency challenges due to high computational and communication loads. Traditional centralized processing methods are inefficient in such scenarios, often resulting in unacceptable inference delays. SL offers a promising alternative by partitioning deep neural networks (DNNs) between edge devices and a central server, enabling localized data processing and reducing the amount of data required for transmission. Our contribution includes the joint optimization of bandwidth allocation, cut layer selection of the edge devices’ DNN, and the central server’s processing resource allocation. We investigate both parallel and serial data processing scenarios and propose low-complexity heuristic solutions that maintain near-optimal performance while reducing computational requirements. Numerical results show that our approach effectively reduces inference delay, demonstrating the potential of SL to improve real-time CV applications in dynamic, resource-constrained environments.

The combination of a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) and an unmanned aerial vehicle (UAV) can further improve channel quality and extend coverage. However, the high-quality air-to-ground link is more vulnerable to eavesdropping by adversaries. In this paper, we investigate STAR-RIS-assisted covert communication in UAV non-orthogonal multiple access (NOMA) networks with a warden Willie, where Alice intends to transmit the covert signal to a near user Bob under the cover of a far user Carol via STAR-RIS. We aim to maximize the covert transmission rate by jointly optimizing the active and passive beamforming as well as the UAV location. The error detection probability and optimal detection threshold for Willie are first derived to obtain an analytic solution for the minimum detection error probability. Then, an alternating optimization algorithm is proposed to maximize the covert transmission rate under the condition of guaranteeing the communication of Carol and satisfying the covertness constraint of Bob. Specifically, the nonconvex problem is decomposed into three sub-problems by block coordinate descent, which are then solved using semidefinite relaxation and successive convex approximation. Finally, simulation results are presented to demonstrate the effectiveness of the proposed covert communication scheme for STAR-RIS assisted UAV air-ground networks.

Near-space airship-borne communication network is recognized to be an indispensable component of the future integrated ground-air-space network thanks to airships’ advantage of long-term residency at stratospheric altitudes, but it urgently needs reliable and efficient Airship-to-X link. To improve the transmission efficiency and capacity, this paper proposes to integrate semantic communication with massive multiple-input multiple-output (MIMO) technology. Specifically, we propose a deep joint semantic coding and beamforming (JSCBF) scheme for airship-based massive MIMO image transmission network in space, in which semantics from both source and channel are fused to jointly design the semantic coding and physical layer beamforming. First, we design two semantic extraction networks to extract semantics from image source and channel state information, respectively. Then, we propose a semantic fusion network that can fuse these semantics into complex-valued semantic features for subsequent physical-layer transmission. To efficiently transmit the fused semantic features at the physical layer, we then propose the hybrid data and model-driven semantic-aware beamforming networks. At the receiver, a semantic decoding network is designed to reconstruct the transmitted images. Finally, we perform end-to-end deep learning to jointly train all the modules, using the image reconstruction quality at the receivers as a metric. The proposed deep JSCBF scheme fully combines the efficient source compressibility and robust error correction capability of semantic communication with the high spectral efficiency of massive MIMO, achieving a significant performance improvement over existing approaches.

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.

In this paper, we investigate the secure transmission design for simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-assisted multiple-input multiple-output (MIMO) systems. By considering both perfect and imperfect channel state information (CSI) scenarios, we jointly optimize the covariance matrix of the transmitter and the transmitting and reflecting coefficients of the STAR-RIS and formulate two transmit power minimization problems. For the optimization problem in the perfect CSI scenario, we develop a penalty-based alternating optimization (AO) algorithm to handle it. For the optimization problem in the imperfect CSI scenario, this paper is the first work to study the robust beamforming design for STAR-RIS-assisted secure MIMO systems. To address this challenging problem, we first use the inequalities of the determinant to transform it into an equivalent form. Then, we use the generalized S-procedure to handle the worst-case constraints. Finally, we develop a penalty-based AO algorithm. Performance evaluation results show that the two proposed optimization algorithms significantly reduce the transmit power compared to other baseline schemes.

This paper introduces Elliptic Curve Modulation (ECM), a novel modulation scheme that can be leveraged to effectively shuffle transmitted data while maintaining symbol error probability (SEP) performance equivalent to unencrypted systems. By utilizing the well-distributed elliptic curve points over the field of large primes, ECM enhances symbol obfuscation, making it a powerful foundation for physical-layer encryption (PLE). Each symbol is mapped from a predefined key while preserving a minimum Euclidean distance constraint, ensuring strong security against adversarial inference without compromising error performance. Building on ECM’s strong obfuscation capabilities, we propose ECM with dynamic rotation (ECM-DR) as a practical PLE scheme that achieves near-maximal obfuscation while balancing precomputation complexity. By leveraging a reduced subset of precomputed elliptic curve points and key-based dynamic constellation rotation, ECM-DR ensures that each transmission remains unpredictable, significantly enhancing security compared to traditional PLE schemes without additional computational cost. Security analysis confirms ECM’s resilience to brute-force attacks, while numerical results demonstrate its strong obfuscation capabilities. Furthermore, ECM-DR achieves near-maximum information entropy while preserving the SEP performance of unencrypted quadrature amplitude modulation (QAM), offering an extremely robust solution for secure wireless communications.

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

In wireless communications, the communication channel between the transmitter and receiver can be monitored by an eavesdropper. The eavesdropper uses deep learning (DL) to quickly identify the modulation parameters of signals and further disrupt legitimate communications. Since DL has been proven to be vulnerable to adversarial attacks, this paper proposes to attack the eavesdropper’s model by designing adversarial waveforms, preventing the eavesdropper from correctly identifying the modulation schemes used by legitimate users, and thereby preventing the eavesdropper from interfering with normal communications. This paper proposes an attention-based black-box attack method, which uses the prediction of different networks in the ensemble model to assign adversarial attention factors to each network. This greatly improves the transmission attack performance of the designed adversarial examples. In addition, by analysing the influence of the channel on the adversarial waveform, we further design the adversarial waveform that can be transmitted in the channel to improve the practicability of the attack algorithm. Finally, we theoretically derive the bounds of the adversarial risk increase that the attack brings to the target model. Simulation results show that the proposed method can improve the success rate of the attack on the eavesdropper’s modulation detection model, cause the model to misidentify the signal modulation type, and improve the security and reliability of legitimate transceivers in wireless communication systems.

Federated learning (FL) enables devices to collaboratively build a shared machine learning (ML) or deep learning (DL) model without exposing raw data. Its privacy-preserving nature has made it popular for intrusion detection systems (IDS) in the field of cybersecurity. However, data heterogeneity across participants poses challenges for FL-based IDS. This paper proposes statistical averaging (StatAvg) method to alleviate non-independently and identically (non-iid) distributed features across local clients’ data in FL. In particular, StatAvg allows the FL clients to share their individual local data statistics with the server. These statistics include the mean and variance of each client’s feature vector. The server then aggregates this information to produce global statistics, which are shared with the clients and used for universal data normalization, i.e., common scaling of the input features by all clients. It is worth mentioning that StatAvg can seamlessly integrate with any FL aggregation strategy, as it occurs before the actual FL training process. The proposed method is evaluated against well-known baseline approaches that rely on batch and layer normalization, such as FedBN, and address the non-iid features issue in FL. Experiments were conducted using the TON-IoT and CIC-IoT-2023 datasets, which are relevant to the design of host and network IDS, respectively. The experimental results demonstrate the efficiency of StatAvg in mitigating non-iid feature distributions across the FL clients compared to the baseline methods, offering a gain in IDS accuracy ranging from 4% to 17%.

Programmable Wireless Environments aim to render the communication environment a controllable, software-defined medium. Reconfigurable Intelligent Surfaces (RISes) are the key enabling technology, which can offer the real-time capability to manipulate impinging waves. RISes are expected to be widely deployed in B5G/6G networks to serve a large number of users simultaneously. Despite numerous analyses highlighting the benefits of utilizing previously unexploitable propagation factors through the use of RISes, there is a lack of analysis regarding their relation to the concept of network resource, their allocation to users/stakeholders and their fair pricing. Thus, this paper models RISes as networked resources. Based on this definition, the PRIME algorithm is proposed, the first algorithm for RIS resource allocation and joint pricing. PRIME strives for proportionality between the offered end-user performance level and the corresponding resource pricing, promoting fairness. The algorithm is validated via full-wave electromagnetic simulations and applies to multiple RIS functionalities and frequency bands.

In the field of constant envelope orthogonal frequency division multiplexing (CE-OFDM), the use of phase modulation heralds a paradigm with an extremely reduced peak-to-average power ratio (PAPR) of zero. However, the non-linear characteristics inherent to phase modulation pose a formidable challenge to the integration of modern channel coding strategies aimed at improved bit error rate (BER) results. To address this issue, we present an efficient low-complexity log-likelihood ratio (LLR) computation strategy based on the traditional phase receiver, anchored in an effective approximation to the phase noise variance. Furthermore, this foundation paves the way for an innovative receiver architecture, namely the near-maximum likelihood (NML) receiver, designed to improve decoding performance without incurring significant computational overhead. Comparative analyses of encoded CE-OFDM across different receiver models not only confirm the accuracy and superiority of the proposed LLR estimation, but also underscore the dual advantages of our proposed NML receiver in optimising BER and detection complexity, positioning CE-OFDM as an optimal candidate for scenarios requiring high-efficiency power amplifiers (PAs).

In this paper, we consider the downlink transmission of a multi-antenna base station (BS) supported by an active simultaneously transmitting and reconfigurable intelligent surface (STAR-RIS) to serve single-antenna users via simultaneous wireless information and power transfer (SWIPT). In this context, we formulate an energy efficiency maximisation problem that jointly optimises the gain, element selection and phase shift matrices of the active STAR-RIS, the transmit beamforming of the BS and the power splitting ratio of the users. With respect to the highly coupled and non-convex form of this problem, an alternating optimisation solution approach is proposed, using tools from convex optimisation and reinforcement learning. Specifically, semi-definite relaxation (SDR), difference of convex functions (DC), and fractional programming techniques are employed to transform the non-convex optimisation problem into a convex form for optimising the BS beamforming vector and the power splitting ratio of the SWIPT. Then, by integrating meta-learning with the modified deep deterministic policy gradient (DDPG) and soft actor-critical (SAC) methods, a combinatorial reinforcement learning network is developed to optimise the element selection, gain and phase shift matrices of the active STAR-RIS. Our simulations show the effectiveness of the proposed resource allocation scheme. Furthermore, our proposed active STAR-RIS-based SWIPT system outperforms its passive counterpart by 57% on average.

Satellite-Ground Integrated Networks (SGINs) are promising network architectures that can help reduce the load on terrestrial networks, provide mega-access capabilities and intensive task offloading functions. However, traditional resource management methods are difficult to apply directly into SGINs due to their multi-layered, heterogeneous and dynamic three-dimensional characteristics. In addition, massive multi-modal and multi-task information hinders better service performance in SGINs. Therefore, we design a multi-task integrated computation offloading model to process complex multi-modal network information, such as time-varying channel gains and dynamic Low Earth Orbit (LEO) locations, which can efficiently improve data transmission rate and privacy level. Furthermore, we propose three multi-modal based learning methods, such as centralized actor-critic (C-AC) algorithm, distributed multi-agent deep deterministic policy gradient (D-MADDPG) algorithm, and quantization-based federated learning (Q-FL) algorithm for computation-intensive, latency-critical and privacy-preserving tasks, which can further optimize the local execution or LEO offloading ratio, CPU cycle frequency and transmission power. Meanwhile, we demonstrate the quantization error upper bound between the optimal solution and the quantization scheme through massive mathematical derivations. Finally, extensive simulation results show that the proposed multi-modal based learning methods have better performance gains in terms of model convergence performance, quantization metrics, data transmission rate and number of bits processed.

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

Integrated sensing and communication (ISAC) is seen as a future solution to frequency congestion due to its excellent ability to simultaneously support target sensing and information transmission. To guarantee robust data security and privacy protection, covert communication can be employed in ISAC systems. In this paper, we propose a covert ISAC scheme against collusive wardens. In particular, a dual-function base station transmits the sensing beamforming to continuously sense an aerial target while communicating with a ground receiver with a probability of 0.5 via the communication beamforming. First, we derive a closed-form expression of the detection outage probability of each warden to obtain the global detection outage probability. Under the worst case that the wardens can collusively adjust their detection thresholds to achieve the best detection performance, we jointly optimize the communication and sensing beamformings to maximize the covert transmission rate. To tackle this non-convex problem, unitary-iteration and zero-forcing schemes are proposed to transform it into convex ones via semidefinite relaxation and successive convex approximation, respectively. Numerical results demonstrate the validity of the proposed covert ISAC scheme, which can achieve a better trade-off among communication, sensing and covertness compared to benchmarks.

Age of information (AoI) is an effective measure to quantify the information freshness in wireless status update systems. It has been further validated that the peak AoI has the potential to capture the core characteristics of the aging process, and thus the average peak AoI is widely used to evaluate the long-term performance of information freshness. However, the average peak AoI is a risk-insensitive metric and therefore may not be well suited for evaluating critical status update services. Motivated by this concern, and following the spirit of entropic value-at-risk (EVaR) in the field of risk analysis, in this paper we present a concept, termed Statistical AoI, for providing a unified framework to guarantee various requirements of risk-sensitive status-update services with the demand on the violation probability of the peak age. In particular, as the constraint on the violation probability of the peak age varies from loose to strict, the statistical AoI evolves from the average peak AoI to the maximum peak AoI. We then investigate the statistical AoI minimization problem for status updates over wireless fading channels. It is interesting to note that the corresponding optimal sampling scheme varies from step to constant functions of the channel power gain with the peak age violation probability from one to zero. We also address the maximum statistical AoI minimization problem for multi-source status updates with time division multiple access (TDMA), where longer transmission time can improve reliability but may also cause the larger age. By solving this problem, we derive the optimal transmission time allocation scheme. Numerical results show that our proposals can better satisfy the diverse requirements of various risk-sensitive status update services, and demonstrate the great potential of improving information freshness compared to baseline approaches.

The advent of sixth-generation (6G) wireless communication systems represents a transformative leap in global connectivity, moving from traditional internet of things (IoT) frameworks to an advanced artificial intelligence of things (AIoT) paradigm. This evolution presents significant challenges, primarily due to exponential growth in data volume, complexity, and latency requirements. To address these challenges, over-the-air (OTA) computation has emerged as a breakthrough approach by integrating computational processes directly into the communication framework, overcoming the inefficiencies of traditional separate designs. In this study, we explore the integration of OTA computation with reconfigurable intelligent surfaces (RISs) within multi-cell multiple-input multiple-output (MIMO) networks. RIS technology enhances signal propagation, mitigates interference, and optimizes wireless coverage, thereby complementing the OTA computation paradigm’s ability to facilitate real-time data aggregation and processing. Specifically, we propose a novel joint optimization framework aimed at minimizing the mean squared error (MSE) in multi-cell environments. This framework addresses the complexity of beamforming design through an innovative power-iteration-based majorization-minimization approach and a successive alignment technique. In addition, we perform asymptotic analysis to elucidate the performance benefits of large-scale MIMO and RIS configurations. We also consider the fairness of MSE computation throughout the multi-cell system. Finally, numerical simulations validate the effectiveness of the proposed methods and provide additional insights based on the asymptotic analysis.

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

Massive machine communication is predicted to provide widespread and unparalleled connectivity for cellular Internet of Things (IoT) applications via multiple-input multiple-output (MIMO) and grant-free random access (GF-RA) techniques. Compressed sensing (CS) has been widely advocated to support massive connectivity due to the bursty nature of traffic transmission. In this paper, the joint activity detection and channel estimation in MIMO-enabled GF-RA system is formulated as a block single measurement vector (SMV) problem and efficiently addressed by using Bayesian-based CS algorithms. First, the pattern coupled sparse Bayesian learning (PCSBL) and block sparse Bayesian learning (BSBL) algorithms are introduced to solve this problem, where the potential block sparsity properties induced by multi-antenna reception are exploited by assigning the structured hyperpriors. Then, by embedding the Generalized Approximate Message Passing (GAMP) technique into the PCSBL and BSBL frameworks to enable effective approximation of posterior distributions, we propose two computationally efficient Bayesian learning algorithms, i.e., GAMP-PCSBL and GAMP-BSBL. Fortunately, the proposed Bayesian algorithms allow automatic learning of block sparse solutions without requiring noise level and user sparsity ratio as explicit conditions. Simulation results show that the proposed algorithms provide improved performance gains over the standard CS-based methods.

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

Optical wireless communication (OWC) systems with multiple light-emitting diodes (LEDs) have recently been explored to support energy-limited devices via simultaneous lightwave information and power transfer (SLIPT). The energy consumption, however, becomes considerable by increasing the number of incorporated LEDs. This paper proposes a joint dimming (JD) scheme that lowers the consumed power of a SLIPT-enabled OWC system by controlling the number of active LEDs. We further enhance the data rate of this system by utilizing rate splitting multiple access (RSMA). More specifically, we formulate a data rate maximization problem to optimize the beamforming design, LED selection and RSMA rate adaptation that guarantees the power budget of the OWC transmitter, as well as the quality-of-service (QoS) and an energy harvesting level for users. We propose a dynamic resource allocation solution based on proximal policy optimization (PPO) reinforcement learning. In simulations, the optimal dimming level is determined to initiate a trade-off between the data rate and power consumption. It is also verified that RSMA significantly improves the data rate.

In this paper, we study the fundamental limits of simultaneous lightwave information and power transfer (SLIPT) systems over channels with path loss and lognormal fading conditions. We consider a system with a single transmitter transferring information to a photodiode-based receiver as well as transferring energy to a photovoltaic cell receiver. In particular, we study the information-energy capacity region and the optimal input distribution under (a) peak-power and average-power constraints at the transmitter, and (b) the minimum harvest energy at the energy harvesting receiver. To this end, an expression for the transition probability distribution function of the lognormal channel is derived. By extending Smith's framework and using Hermite polynomial bases, we prove that the optimal input distribution is discrete with a finite number of mass points. Information-energy capacity region for SLIPT over lognormal channel conditions is illustrated and compared with the case of additive white Gaussian noise channel.

Deep neural networks (DNNs) have demonstrated their efficacy in delivering accurate solutions to a range of optimization problems. However, in the context of wireless communications, the size of these problems may vary across adjacent time slots, due to fast changes in the networks’ architecture, e.g., the number of users. It is essential to note that this time-varying dimensionality of optimization problems in wireless networks necessitates adjustments in the DNN architecture, resulting in different numbers of input and output nodes. To address this challenge, in our paper, optimization problems of varying size are treated as distinct tasks. To tackle these tasks, a multi-task learning (MTL) approach based on modular sharing is proposed. The multi-task approach consists of a DNN, which is used to extract the solutions for all the optimization problems, and a router which manages which nodes and layers of the input and output layer of the DNN to be used during the forward propagation of each task. Consequently, all tasks share common parameters of the DNN, while the DNN dynamically adjusts to the number of nodes of its output and input layers. Numerical results demonstrate the superiority of the suggested approach over zero-padding, which is the current solution for handling resource allocation problems of varying size.

Unmanned aerial vehicles (UAVs) equipped with full-duplex relays (FDRs) are pivotal in overcoming connectivity challenges by dynamically establishing effective communication channels. However, despite their potential in network performance via trajectory optimization, integrating energy consumption models for UAV-mounted FDRs remains unexplored, crucial for trajectory design adhering to existing energy constraints. To this end, we introduce an energy-aware trajectory optimization framework to maximize network performance and user fairness within the UAV’s energy constraints. Specifically, we present a detailed energy consumption model describing the operational needs of UAV-mounted FDRs and formulate a joint time-division multiple access (TDMA) user scheduling-UAV trajectory optimization problem considering the power dynamics of UAV-mounted FDRs. Finally, our simulation results highlight the role of energy awareness in achieving optimal trajectory and scheduling, contributing to UAV-mounted FDRs’ performance in future networks.

Massive machine-type communications (mMTC) are anticipated to be supported by grant-free random access (GF-RA) and multiple-input multiple-output (MIMO) techniques. Compressed sensing (CS) is extensively advocated to accommodate massive connectivity due to bursty data transmission. In this paper, we formulate the joint activity detection and channel estimation for the MIMO-enabled GF-RA system as a block single measurement vector (SMV) problem. First, the hierarchical block sparse Bayesian learning (BSBL) framework is developed to solve this problem, where the potential block sparse properties induced by multiantenna reception are exploited by assigning the structured hyperprior. Then, by integrating the generalized approximate message passing (GAMP) approach into the BSBL formulation to effectively approximate the posterior distribution, we propose a computationally efficient Bayesian learning algorithm named GAMP-BSBL. Fortunately, the proposed Bayesian algorithms enable automatic learning of block sparse solutions without requiring noise level and user sparsity ratio as explicit conditions. Simulation results show that the proposed algorithms provide improved performance gains as compared with the standard CS methods.

Orthogonal Time-Frequency-Space (OTFS) modulation can effectively suppress the effects of Doppler shift in high-speed mobile scenarios. At the same time, the accuracy of OTFS channel estimation is an important factor that affects the performance of OTFS. In this paper, we propose a Sparse Bayesian Learning (SBL) algorithm to quickly and accurately estimate the OTFS channel by combining the pilot pattern and the sparsity of the OTFS channel. First, we propose a new pilot pattern to prevent the contamination of information symbols on pilot symbols. Since the pilot pattern uses only partial guard symbols, it can also improve the spectral efficiency. Then, we propose the Student-T prior SBL (STSBL) algorithm to improve the speed and accuracy of OTFS channel estimation by exploiting the sparsity of the OTFS channel. Simulation results show that the normalized mean squared error (NMSE), bit error rate (BER), and throughput of the proposed scheme outperform the benchmark schemes.

Grant-free non-orthogonal multiple access (GF-NOMA) based on multiple-input multiple-output (MIMO) has attracted much attention as a promising technique to support massive connectivity and bursty data transmission in massive machine-type communication. In this paper, we propose two compressed sensing based multiuser detection (MUD) algorithms for the MIMO-enabled GF-NOMA system. First, the spatially enhanced variational Bayesian inference (SE-VBI) algorithm is developed for MUD by exploiting the Gaussian mixture prior and diversity combining technique. Then, by applying the covariance-free (CoFe) strategy to the SE-VBI framework to estimate the diagonal elements of the posterior covariance, we propose a low-complexity MUD method named SE-CoFe-VBI. In particular, the proposed algorithms integrate the multivariate nature of the transmitted signal, i.e., discreteness, sparsity, and spatial correlation. Simulation results show that the proposed algorithms offer improved detection performance over the state-of-the-art spatially enhanced sparse Bayesian learning method.

One of the principal challenges anticipated for the forthcoming sixth-generation (6G) wireless networks is the imper-ative need to design advanced multiple access techniques capable of enabling massive connectivity. In this direction, rate splitting multiple access (RSMA) has been reported as a promising approach. In this work, we investigate the ergodic rate (ER) performance of an uplink RSMA network which consists of two sources. Specifically, analytical closed-form expressions for the sources' ERs and the system ergodic sum rate (ESR) are derived under the case of perfect successive interference cancellation$(\text{pSIC})$and perfect channel state information (pCSI) as well as under the more realistic scenario of imperfect SIC (ipSIC) and imperfect CSI (ipCSI). Furthermore, an asymptotic analysis for the high signal-to-noise ratio regime is presented, which provides useful insights into the sources' behavior in all considered cases. The accuracy of the provided analytical expressions is validated by simulation results, which not only explore how different system parameters affect the extracted expressions, but also reveal the detrimental impact of ipSIC and ipCSI on system performance.

Semantic communications offer a promising approach to decrease network congestion and improve reliability, leading to more sustainable and energy-efficient wireless networks. However, the design of semantic transceivers constrain their effectiveness. This paper introduces a novel multi-carrier system that combines both semantic and Shannon communications, with a focus on text transmission. We formulate an optimization problem that jointly selects the transmission method and allocates power to reduce the transmission delay. Despite the challenges of solving this non-convex problem, we employ alternating optimization techniques to address it and the closed-form solution of the power allocation is extracted. The simulation results verify that jointly selecting semantic and Shannon communications decreases the transmission delay compared to using only one of the schemes.

In sixth-generation (6G) wireless communication systems, the coexistence of enhanced mobile broadband (eMBB) and massive machine-type communications (mMTC) services requires the investigation of appropriate multiple access schemes. In this direction, this paper delves into the hybrid eMBB-mMTC policy, focusing on the implications of non-orthogonality in contention-based access schemes and combining the strengths of slotted ALOHA and successive interference cancellation to address the challenges of this hybrid policy. Closed-form expressions for the outage probability, which are crucial for deriving the throughput of the sources, are presented and integrated into a comprehensive analysis. Finally, simulation results are used to validate the provided theoretical expressions, highlighting the effects of random source deployment within the hybrid eMBB-mMTC framework and highlighting the potential and challenges of this policy in shaping the future of 6G wireless communication systems.

Future connected vehicles will require high-performance communication technologies for advanced cooperative driving applications such as maneuvering and cooperative perception. mmWave communications can meet the bandwidth requirements of such applications, but the typically harsh propagation conditions of vehicular environments hinder the broad adoption of mmWave devices on cars. Reconfigurable intelligent surfaces (RISs) can help mitigate this problem by enabling the reflection of signals in a configurable direction. In turn, this can result in more stable non-line of sight (NLoS) links whenever a LoS path is not available. RISs have recently gained attention in the vehicular domain but, while providing benefits, they also introduce a lot of research challenges. To measure their effectiveness at scale, it is necessary to develop simulation tools that can reproduce their characteristics with high fidelity and federate them with existing cooperative driving simulation frameworks. In this work we present CoopeRIS, an open-source simulation framework federated within the Plexe/Veins/SUMO ecosystem, capable of modeling and simulating RIS-based mmWave communications in a vehicular environment. We exploit CoopeRIS to perform an initial feasibility study, highlighting the challenges ahead and the performance RISs need to deliver in order to enable this type of communication. In addition we propose a method to combine multiple RIS configurations into a single one to enable multi-user service delivery, showing its performance via CoopeRIS. The insights we presents within this work show the potential of such simulation framework and thus how the community can build further research work on top if it.

In the evolving landscape of sixth-generation (6G) wireless networks, unmanned aerial vehicles (UAVs) have emerged as transformative tools for dynamic and adaptive connectivity. However, dynamically adjusting their position to offer favorable communication channels introduces operational challenges in terms of energy consumption, especially when integrating advanced communication technologies like reconfigurable intelligent surfaces (RISs) and full-duplex relays (FDRs). To this end, by recognizing the pivotal role of UAV mobility, the paper introduces an energy-aware trajectory design for UAV-mounted RISs and UAV-mounted FDRs using the decode-and-forward (DF) protocol, aiming to maximize the network’s minimum rate and enhance user fairness, while taking into consideration the available on-board energy. Specifically, this work highlights their distinct energy consumption characteristics and their associated integration challenges by developing appropriate energy consumption models for both UAV-mounted RISs and FDRs that capture the intricate relationship between key factors such as weight, and their operational characteristics. Furthermore, a joint time-division multiple access (TDMA) user scheduling-UAV trajectory optimization problem is formulated, considering the power dynamics of both systems, while assuring that the UAV energy is not depleted mid-air. Finally, simulation results underscore the importance of energy considerations in determining the optimal trajectory and scheduling and provide insights into the performance comparison of UAV-mounted RISs and FDRs in UAV-assisted wireless networks.

Recently, reconfigurable intelligent surfaces (RISs) have emerged as a highly promising technology within the realm of wireless communication systems, as they offer the potential to minimize obstructions, enhance reliability, and establish alternative paths for signal propagation. This article presents the performance of a free space optics (FSOs) system empowered by multiple optical reflecting surfaces (ORSs) over a Gamma-Gamma turbulence-induced fading channel with pointing errors by considering imperfections in channel state information (CSI). The expressions for probability density function (PDF) of the end-to-end FSO channel considering both perfect and imperfect CSI cases are derived. Further, the unified PDF and cumulative distribution function (CDF) of instantaneous signal-to-noise ratio (SNR) are determined under two detection schemes, i.e., intensity modulation/ direct detection and heterodyne detection for both perfect and imperfect CSI cases. Utilizing the derived CDFs, the closed-form expressions for outage probability and average symbol error rate (ASER) of the proposed multiple ORSs system are obtained along with performing asymptotic analysis. Finally, the numerical results indicate that the performance of ORS-assisted FSO systems is significantly degraded by severe turbulence, pointing errors, and imperfect CSI. However, the inclusion of ORSs and increasing their number improves the performance of ORS-assisted FSO systems in the presence of turbulence, pointing errors, and imperfect CSI, compared to FSO systems without ORSs.

In this paper, we investigate a sensing-enabled integrated space-air-ground (SAG) data collection network, in which an unmanned aerial vehicle (UAV) can not only work singly to sense data from multiple targets but also collaborate with a low-earth orbit (LEO) satellite to collect communication data from multiple users. Since the coverage of the UAV is much smaller than that of the LEO satellite, we first determine the set of usable users and targets for the UAV by analyzing the signal-to-noise ratios between the UAV and the users and targets. Based on this, we pose an optimization problem designed to maximize the total amount of data collected in the network while satisfying the constraints of UAV energy consumption, memory capacity, and minimum amount of sensor data per target. Moreover, considering that the network consists of three layers and the UAV has dual functions of communication and sensing, this problem is solved by jointly optimizing the scheduling of the users’ data upload scheme, the UAV trajectory, and the allocation of communication and sensing time. However, the formulated problem is a mixed integer nonlinear programming (MINLP) problem, so it is difficult to find the optimal solution. Therefore, we further design an alternating iterative optimization algorithm (AIOA) framework to find an appropriate solution. Specifically, we alternately optimize the UAV trajectory, time allocation strategy, and data upload schedule in each iteration. Finally, simulation experiments validate the effectiveness of the AIOA and its superiority over other benchmarks in terms of the amount of data collected.

This article focuses on the latest research and innovations in fundamental next-generation multiple access (NGMA) techniques and the coexistence with other key technologies for the sixth generation (6G) of wireless networks. In more detail, we first examine multiaccess edge computing (MEC), which is critical to meeting the growing demand for data processing and computational capacity at the edge of the network, as well as network slicing. We then explore over-the-air (OTA) computing, which is considered to be an approach that provides fast and efficient computation of various functions. We also explore semantic communications, identified as an effective way to improve communication systems by focusing on the exchange of meaningful information, thus minimizing unnecessary data and increasing efficiency. The interrelationship between machine learning (ML) and multiple access technologies is also reviewed, with an emphasis on federated learning (FL), federated distillation (FD), split learning (SL), reinforcement learning (RL), and the development of ML-based multiple access protocols. Finally, the concept of digital twinning and its role in network management is discussed, highlighting how virtual replication of physical networks can lead to improvements in network efficiency and reliability.

One of the main challenges that the upcoming sixth-generation (6G) wireless networks will encounter is the necessity to design sophisticated multiple access techniques that besides being capable of supporting massive connectivity, they can also fulfill the heterogeneous requirements of 6G services, namely further-enhanced mobile broadband (feMBB), extremely reliable and low-latency communication, and ultra-massive machine-type communication (umMTC). To this end, this work investigates the coexistence of multiple feMBB and umMTC wireless sources in a network. In order to enhance the achievable connectivity, each orthogonal resource block of the network is assigned to one feMBB and multiple umMTC sources. FeMBB sources are assumed to constantly transmit, while umMTC are considered to access the network in a probabilistic manner. If more than one umMTC sources attempt to access the network in a given resource block, no umMTC transmission is permitted, however, when precisely one umMTC source endeavors to access the medium, rate-splitting multiple access is employed to concurrently serve both feMBB and umMTC transmissions. For such a communication scenario, we derive novel closed-form expressions for sources’ outage probabilities (OPs), ergodic rates (ERs), system throughput, and ergodic sum rate under both the ideal case of perfect channel state information (pCSI) and perfect successive interference cancellation (pSIC) and the more realistic scenario of imperfect CSI (ipCSI) and imperfect SIC (ipSIC). Furthermore, a high signal-to-noise ratio analysis is provided revealing deeper insights for sources’ asymptotic behavior under all considered cases. Simulation results corroborate the accuracy of the derived analytical expressions, investigate the impact of different system parameters on sources’ OP and ER performance, and illustrate the detrimental impact of ipCSI and ipSIC on system performance compared to the ideal case of pCSI and pSIC.

Recently, there has been a growing interest in learning-based semantic communication because it can prioritize the preservation of meaningful semantic information over the accuracy of the transmitted symbols, resulting in improved communication efficiency. However, existing learning-based approaches still face limitations in defining semantic level loss and often struggle to find a good trade-off between preserving semantic information and preserving intricate details. In addition, the existing semantic communication approaches cannot effectively train semantic encoders and decoders without the support of downstream models. To address these limitations, this paper proposes a contrastive learning (CL)-based semantic communication system. First, inspired by practical observations, we introduce the concept of semantic contrastive loss and propose a semantic contrastive coding (SemCC) approach that treats data corruption during transmission as a form of data augmentation within the CL framework. Moreover, we propose a semantic re-encoding (SemRE) operation, which uses a duplicate of the semantic encoder deployed at the receiver to guide the entire training process when the downstream model is inaccessible. Further, we design the training procedure for SemCC and SemRE approaches, respectively, to balance the semantic information and intricate details. Finally, simulations are performed to demonstrate the superiority of the proposed approaches over competing approaches. In particular, our approaches achieve a significant accuracy improvement of up to 53% on the CIFAR-10 dataset with a bandwidth compression ratio of 1/24, and also obtain comparable image reconstruction quality as the bandwidth compression ratio is improved.

In this work, we address a novel framework for next-generation distributed radio access. In contrast with existing studies, where all remote radio heads (RRHs) in a distributed network are directly connected to a central unit (CU), an alternative architecture for advanced flexibility is proposed. In our setup, only one of the RRHs, namely the$primary$RRH, communicates directly with the CU, while the connectivity between the rest RRHs, namely$secondary$RRHs, and the CU is achieved through the primary RRH via free-space optical links. Assuming that users exploit non-orthogonal multiple access (NOMA) for their transmissions, we introduce two successive interference cancellation (SIC) cooperation schemes, depending on the one-directional or bidirectional communication between the RRHs, as well as, a four-step centralized algorithm for efficient user-RRH association and decoding order operations is proposed. The feasibility of the suggested schemes is adequately demonstrated by deriving analytical expressions for users' outage probabilities and providing valuable insights into the high signal-to-noise ratio regime. Furthermore, the performance of the proposed system under various weather conditions is investigated via simulation and analytical results. The comparison with a benchmark scheme, where all RRHs are directly connected to the CU and cooperate with each other via ideal links, is provided and it is revealed that although the performance of the proposed system model is weather dependent, in most of the practical cases it achieves similar performance with the ideal benchmark.

Semantic communications are considered a promising beyond-Shannon paradigm to reduce network traffic and increase reliability, thus making wireless networks more energy efficient, robust, and sustainable. However, the performance is limited by the efficiency of the semantic transceivers, i.e., the achievable “similarity” between the transmitted and received signals. Under strict similarity conditions, semantic transmission may not be applicable and Shannon communication is mandatory. In this paper, for the first time in the literature, we propose a multi-carrierHybrid Semantic-Shannoncommunication system where, without loss of generality, the case of text transmission is investigated. To this end, a joint semantic-Shannon transmission selection and power allocation optimization problem is formulated, aiming to minimize two transmission delay metrics widely used in the literature, subject to strict similarity thresholds. Despite their non-convexity, both problems are decomposed into a convex and a mixed linear integer programming problem by using alternating optimization, both of which can be solved optimally. Furthermore, to improve the performance of the proposed hybrid schemes, a novel association of text sentences to subcarriers is proposed based on the data size of the sentences and the channel gains of the subcarriers. We show that the proposed association is optimal in terms of transmission delay. Numerical simulations verify the effectiveness of the proposed hybrid semantic-Shannon communication scheme and the derived sentence-to-subcarrier association, and provide useful insights into the design parameters of such systems.

Over-the-air computing (AirComp) has recently attracted considerable attention as an efficient method of data fusion by integrating uncoded communication transmissions with computation thanks to the signal superposition offered by the multiple access channels. However, appropriate processing is required to neutralize the wireless channel effect. As, internet-of-things (IoT) applications through low-cost devices is the main target of AirComp, perfect availability of channel state information (CSI) is not always practical, there is the need to investigate the effect of imperfect CSI on AirComp. Specifically, we present novel closed-form expressions for tight approximations that can be used to design and evaluate AirComp systems. Furthermore, we design a general optimization framework that takes into account both magnitude and phase errors in the CSI. Finally, a pilot retransmission policy is designed, that offers trade-off between resources cost and the gain in the accuracy of the computations. In order to validate its application, a utility function of the cost of retransmission is introduced, namely,Retransmission Policy Cost (RPC), which can incorporate the power or throughput cost opposing to the expected gain of the selected policy. Simulations show the deterioration caused by the imperfect CSI and highlight the added value of the proposed policy under various system conditions.

This paper investigates an unconventional superposition scheme, i.e., rate-splitting multiple access (RSMA) to maximize the overall user fairness and high system performance gain for ultra-reliable low-latency communication (URLLC), enhanced mobile-broadband (eMBB) traffic coexistence in uplink scenarios. In particular, we focus on maximizing the worst-case performance of uplink eMBB and URLLC users when multiplexed in a given resource block using an effective rate-splitting approach among multiple sub-messages. Subsequently, a multi-objective optimization problem (MOOP) is formulated to jointly maximize the worst-case rate and minimize the worst-case packet-error probability (PEP) for eMBB and URLLC users, respectively, using effective power splitting and successive interference cancellation (SIC) decoding of the sub-messages. To solve the non-convexity of the formulated MOOP, we adopt a priori articulation scheme combined with the weighted product approach to transforming the MOOP into a single objective optimization problem (SOOP) and later, solve it using a low complex differential evolution (DE)-based meta-heuristic algorithm. We derive an optimal decoding strategy for sub-messages to ensure better user fairness among eMBB-URLLC traffic. Numerical simulations demonstrate the superiority of the considered RSMA-based superposition for hybrid eMBB-URLLC traffic over conventional slicing and superposition techniques. Moreover, the adopted weighted product method-based DE algorithm outperforms the state-of-art solutions.

A primary objective of the forthcoming sixth generation (6G) of wireless networking is to support demanding applications, while ensuring energy efficiency. Programmable wireless environments (PWEs) have emerged as a promising solution, leveraging reconfigurable intelligent surfaces (RISs), to control wireless propagation and deliver exceptional quality-of-service. In this paper, we analyze the performance of a network supported byzero-energy RISs (zeRISs), which harvest energy for their operation and contribute to the realization of PWEs. Specifically, we investigate joint energy-data rate outage probability and the energy efficiency of a zeRIS-assisted communication system by employing three harvest-and-reflect (HaR) methods, i) power splitting, ii) time switching, and iii) element splitting. Furthermore, we consider two zeRIS deployment strategies, namely BS-side zeRIS and UE-side zeRIS. Simulation results validate the provided analysis and examine which HaR method performs better depending on the zeRIS placement. Finally, valuable insights and conclusions for the performance of zeRIS-assisted wireless networks are drawn from the presented results.

Since the unmanned aerial vehicle (UAV) network and intelligent reflecting surface (IRS) technology can flexibly change wireless network links signal, the UAV-IRS network system is a potential solution to increase the communication performance gain. Motivated by the practicality of UAV-IRS networks, a non-orthogonal multiple access (NOMA) heterogeneous UAV communication system with simultaneous wireless information and power transfer (SWIPT) is considered, which consists of multiple UAV base stations (UBSs), a macro base station (MBS), and multiple IRSs for auxiliary communications. This paper pursues a goal to receive the system energy efficiency (EE) maximization by resource allocation and reflecting design of IRSs. Due to the strong coupling among multiple parameters in the original problem, this complex non-convex problem is decomposed into three stages. In the first stage, this paper decouples the problem into two subproblems of NOMA subchannel assignment and SIC decoding order to find the optimal solution separately. For the second stage, under the constraints of UAV’s maximum transmit power, users’ quality of service (QoS) requirements, user energy harvesting threshold and cross-layer interference constraints, a beamforming design based on Lagrangian duality is exploited. For the third stage, the power splitting (PS) factors and the reflecting phases of the IRS are jointly optimized using the penalty-SDR algorithm to approximate the suboptimal solution. Finally, the simulation curves exhibit the validity and excellent performance of the co-design scheme in improving the system EE.

A core vision of the future sixth-generation wireless networks is to serve, in the most spectral and energy efficient way, a massive number of devices and/or Internet-of-Things (IoT) sensors, plenty of which are expected to be low-powered or even battery-free. In this direction, non-orthogonal multiple access (NOMA) and ambient backscatter communications (AmBC) are considered as two key promising technologies. In this work, we present a novel analytical framework for studying the performance of uplink NOMA-based AmBC systems. Specifically, analytical expressions for both NOMA-users’ and IoT backscatter device’s (BD) outage probabilities (OPs) are derived under both perfect and the more realistic case of imperfect successive interference cancellation (SIC). Likewise, system’s performance at the high signal-to-noise ratio (SNR) regime is investigated as well as expressions for the system’s overall average throughput are also derived. A performance comparison between the proposed setup and a conventional orthogonal multiple access (OMA)-based AmBC system is provided as well as it is proved that the proposed system’s average throughput is equal or even greater compared to a conventional uplink NOMA system with two NOMA-users and no BDs.

In this paper, we propose and evaluate a hybrid visible light communication (VLC)/radio-frequency (RF) network architecture, where a VLC access point serves two user equipments (UEs), which also act as RF relays in order to extend the network’s coverage to a third UE outside the VLC cell. The proposed protocol is inspired by uplink rate-splitting multiple access to efficiently route the messages to the UEs. In more detail, the proposed protocol utilizes the nuances of the specific network architecture to efficiently utilize the wireless resource blocks for both coverage and throughput. The protocol is then optimized by maximizing the minimum achievable rate. Simulation results show that the proposed method achieves superior results compared with a more conventional benchmark scheme, that is also optimized under the same constraints.

For future networks, it is highly demanding to satisfy a wide range of time-sensitive and computation-intensive services. This is a very challenging task, since it requires a combination of aspects from information, communication and computation in order to establish a digital representation of the real network environment. This paper introduces a fairness-aware latency minimisation (FALM) framework in the digital twin (DT) aided edge computing with ultra-reliable and low latency communications (URLLC), which jointly optimises various communication and computation parameters, namely, bandwidth allocation, transmission power, task offloading portions, and processing rate of user equipments (UEs) and edge servers (ESs). The formulated problem is highly complicated, due to non-convex constraints and strong coupling among optimisation variables. To deal with this problem, we develop both centralised and distributed optimisation approaches. In particular, we first resort to successive convex approximation (SCA) method to develop a low-complexity iterative algorithm and solve the problem in a centralised manner. Combining tools from SCA and alternating direction method of multipliers (ADMM), we develop an efficient distributed solution with parallel computation processing at ESs under global consensus in each iteration and strong theoretical performance guaranteed. Numerical results are provided to validate the proposed solutions in terms of convergence speed and overall latency as well as improving fairness among all UEs.

Many real-time application scenarios are developed in 6G communications. Driven by the low-latency data processing requirements, multi-tier computing has become an important technology to improve user experience and reduce network overhead. In this paper, we consider a multi-tier computation offloading network structure for 6G applications, in which the cloud computing center and the nearby vehicle edge server (VES) are able to partially calculate the tasks offloaded from the user equipment (UE), and the remaining task is processed locally in the UE. By jointly optimizing user scheduling, cloud offloading ratio, VES offloading ratio, and VES mobility, the objective function is to minimize the delay of the system transmission and computation under the constraints of discrete variables and energy consumption. To solve the problem, a primal-dual deep deterministic policy gradient (PD-DDPG) algorithm based on multi-tier computation offloading is proposed. Simultaneously, compared with baseline algorithms, PD-DDPG algorithm has an obvious advantage in both the speed of convergence and the system delay.

Grant-Free (GF) access has been recognized as a promising candidate for Ultra-Reliable and Low-Latency Communications (URLLC). However, even with GF access, URLLC still may not effectively gain high reliability and millimeter-level latency, simultaneously. This is because the network load is typically time-varying and not known to the base station (BS), and thus, the resource allocated for GF access cannot well adapt to variations of the network load, resulting in low resource utilization efficiency under light network load and leading to severe collisions under heavy network load. To tackle this problem, we propose a multi-tier-driven computing framework and the associated algorithms for URLLC to support users with different QoS requirements. Especially, we concentrate on$K $- repetition GF access in light of its simplicity and well-balanced performance for practical systems. In particular, our framework consists of three tiers of computation, namely network-load learning, network-load prediction, and adaptive resource allocation. In the first tier, the BS can learn the network-load information from the states (success, collision, and idle) of random-access resources in terms of resource blocks (RB) and time slots. In the second tier, the network-load variation is effectively predicted based on estimation results from the first tier. Finally, in the third tier, by deriving and weighing the failure probabilities of different groups of users, their QoS requirements, and the predicted network loads, the BS is able to dynamically allocate sufficient resources accommodating the varying network loads. Simulation results show that our proposed approach can estimate the network load more accurately compared with the baseline schemes. Moreover, with the assistance of network-load prediction, our adaptive resource allocation offers an effective way to enhance the QoS for different URLLC services, simultaneously.

Recently, federated learning (FL) has sparked widespread attention as a promising decentralized machine learning approach which provides privacy and low delay. However, communication bottleneck still constitutes an issue, that needs to be resolved for an efficient deployment of FL over wireless networks. In this paper, we aim to minimize the total convergence time of FL, by quantizing the local model parameters prior to uplink transmission. More specifically, the convergence analysis of the FL algorithm with stochastic quantization is firstly presented, which reveals the impact of the quantization error on the convergence rate. Following that, we jointly optimize the computing and communication resources as well as the number of quantization bits, in order to guarantee minimized convergence time, subject to energy and quantization error requirements. The impact of the quantization error on the convergence time is evaluated and the trade-off among model accuracy and timely execution is revealed. Moreover, the proposed method is shown to result in faster convergence compared with baseline schemes. Finally, useful insights for the selection of the quantization error tolerance are provided.

In this paper, we study a relay-assisted federated edge learning (FEEL) network under latency and bandwidth constraints. In this network,$N$users collaboratively train a global model assisted by$M$intermediate relays and one edge server. We firstly propose partial aggregation and spectrum resource multiplexing at the relays in order to improve the communication of the relay-assisted FEEL system. Furthermore, we derive analytical and asymptotic expressions of the system outage probability and convergence rate. For the purpose of improving the system performance, we further optimize the relay-assisted FEEL network by maximizing the number of users who participate in each round of federated learning, through allocation of the wireless bandwidth among users and relays. Specifically, two bandwidth allocation (BA) schemes have been proposed, assuming either instantaneous or statistical channel state information (CSI). Simulations show the advantages of the proposed BA schemes over other benchmarks, regarding the accuracy and convergence rate of the considered relay-assisted FEEL network.

Distributed optimization is ubiquitous in emerging applications, such as robust sensor network control, smart grid management, machine learning, resource slicing, and localization. However, the extensive data exchange among local and central nodes may cause a severe communication bottleneck. To overcome this challenge, over-the-air computing (AirComp) is a promising medium access technology, which exploits the superposition property of the wireless multiple access channel (MAC) and offers significant bandwidth savings. In this work, we propose an AirComp framework for general distributed convex optimization problems. Specifically, a distributed primal-dual (DPD) subgradient method is utilized for the optimization procedure. Under general assumptions, we prove that DPD-AirComp can asymptotically achieve zero expected constraint violation. Therefore, DPD-AirComp ensures the feasibility of the original problem, despite the presence of channel fading and additive noise. Moreover, with proper power control of the users’ signals, the expected non-zero optimality gap can also be mitigated. Two practical applications of the proposed framework are presented, namely, smart grid management and wireless resource allocation. Finally, numerical results confirm DPD-AirComp’s excellent performance, while it is also shown that DPD-AirComp converges an order of magnitude faster compared to two digital orthogonal multiple access schemes, specifically, time-division multiple access (TDMA), and orthogonal frequency-division multiple access (OFDMA).

Optimizing the energy efficiency (EE) of wireless networks is one of the key priorities in the design of beyond 5G mobile technologies. In this pursuit, the use of new frequency bands, in combination with advanced multiple access protocols and cooperative communications strategies, has recently shown promising results. To this end, this paper investigates an indoor wireless network that aggregates communication resources in visible light and radio-frequency (RF) bands, taking advantage of the complementary aspects of the two technologies. More specifically, a non-orthogonal multiple access (NOMA) scheme is introduced for the visible light communication (VLC) downlink, such that cell-edge users experiencing a weak VLC signal enhance their aggregated data rate with the aid of cooperative communications over RF sidelinks (i.e., device-to-device links). The optimal resource allocation strategy over both VLC and RF bands is derived aiming at EE maximization based on the Dinkelbach’s algorithm and successive convex approximation. Additionally, for the sake of flexibility, a weighted EE metric is proposed for the characterization of the aggregated VLC/RF network performance. Simulation results are provided to validate the proposed analysis, revealing the impact of various design and system parameters, such as the weighting factors, quality of service requirements, and channel conditions.

Data collection in massive Internet of Things networks requires novel and flexible methods. Unmanned aerial vehicles (UAVs) are foreseen as a means to collect data rapidly even in remote areas without static telecommunication infrastructure. In this direction, UAV-mounted reconfigurable intelligent surfaces (RISs) aid in reducing the hardware requirements and signal processing complexity at the UAV side, while increasing the network’s energy efficiency and coverage. Hence, in this paper, we propose the utilization of a UAV-mounted RIS for data collection and study the coverage probability in such networks. Additionally, we propose a novel medium access control protocol based on slotted ALOHA and Code Combining to handle the communication of multiple sensors. To account for the crucial energy issue in UAVs, we devise an energy model that considers both the UAV and the RIS weight, as well as the environmental conditions and the UAV’s velocity. Finally, we characterize the performance of the proposed data collection scheme by analyzing the average throughput and the average collected data per flight, while providing useful insights for the design of such networks.

Recently, the use of reconfigurable intelligent surfaces (RIS) has gained popularity and is emerging as a promising technique to provide improved link reliability and enhanced coverage area. In this paper, we propose an optical reflecting surface (ORS)-assisted free space optics (FSO) communication system, which is based on optical space shift keying (OSSK) technique. Specifically, the closed-form expression for probability density function (PDF) of the ORS-assisted FSO channel is derived over Malaga turbulence model. Further, we have obtained the moment generating function (MGF) of the instantaneous signal-to-noise ratio (SNR) of the overall OSSK-based multiple-input multiple-output (MIMO)-FSO system. Using the derived channel statistics, an upper bound expression for the average bit error rate (BER) and a lower bound for the ergodic capacity are derived. Further, the asymptotic BER is utilized to calculate the diversity gain of the system. Numerical results are provided to corroborate the theoretical analysis of the system, along with insightful discussions. It is observed from the numerical results that the atmospheric turbulence and pointing errors have a negligible effect on the performance of the proposed system. Finally, a trade-off is noticed with respect to the average BER performance versus the spectral efficiency of the proposed system.

Coded caching is the distribution of content across a communication system using techniques from coding theory in order to create multicasting opportunities among the users receiving the content. This enables a multiplicative improvement over the classic uncoded caching with respect to the transmission rates required in the delivery phase of the content. Since its introduction, coded caching has eliceted significant research interest as a result of which several different schemes have been proposed over the last few years. This work focuses on the fundamental case of coded caching with uncoded prefetching. In this case, the users’ caches are filled with uncoded content during a prefetching phase in order to best serve the request made by each user during a subsequent delivery phase. This important case has recently received a complete information-theoretic characterization. However, reaching the information-theoretic optimality imposes a significant computational imbalance among the users. To mitigate this imbalance, we perform a complete computational analysis of the two major forms of coded caching with uncoded prefetching, namely centralized and decentralized. Furthermore, we propose a new information-theoretically optimal method for the delivery phase that achieves a significant computational improvement compared to the state of the art.

In the past few years, satellite communications have greatly affected our daily lives, and the integrated terrestrial-satellite network can combine the advantages of satellite and base stations (BSs) to provide wider coverage and lower cost. Because the resources of terrestrial-satellite network are limited, how to allocate resources of terrestrial-satellite network through effective methods has become a major challenge. This paper proposes a framework for resource allocation of terrestrial-satellite network based on non-orthogonal multiple access (NOMA). Then, a deployment method of local cache pools is given to achieve lower time delay and maximize energy efficiency in terrestrial-satellite network. In the proposed framework, we adopt a multi-agent deep deterministic policy gradient (MADDPG) method to obtain the maximum energy efficiency by user association, power control, and cache design. The MADDPG algorithm is divided into two stages, users and BSs are set as agents to complete the optimization problem in the framework. Finally, the simulation results show that the proposed method has better optimized performance compared with the traditional single-agent deep reinforcement learning algorithm and can efficiently solve the problems of resource allocation and cache design in the integrated terrestrial-satellite network.

Reconfigurable Intelligent Surfaces (RIS) constitute a promising technology that could fulfill the extreme performance and capacity needs of the upcoming 6G wireless networks, by offering software-defined control over wireless propagation phenomena. Despite the existence of many theoretical models describing various aspects of RIS from the signal processing perspective (e.g., channel fading models), there is no open platform to simulate and study their actual physical-layer behavior, especially in the multi-RIS case. In this paper, we develop an open simulation platform, aimed at modeling the physical-layer electromagnetic coupling and propagation between RIS pairs. We present the platform by initially designing a basic unit cell, and then proceeding to progressively model and simulate multiple and larger RISs. The platform can be used for producing verifiable stochastic models for wireless communication in multi-RIS deployments, such as vehicle-to-everything (V2X) communications in autonomous vehicles and cybersecurity schemes, while its code is freely available to the public.

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

Massive IoT deployments in smart cities pose a significant challenge to the data collection due to the harsh wireless channel conditions of dense urban environments. Aerial reconfigurable intelligent surfaces (RIS) carried by Unmanned Aerial Vehicles (UAVs) can improve the communication thanks to their high mobility that provides line-of-sight propagation. In this paper, we investigate the impact of the aerial RIS in the data collection by deriving the outage probability of the randomly-deployed devices, while taking into account the imperfect channel state and the UAV fluctuations. Furthermore, we study the effects on the network reliability of two hybrid automatic repeat request protocol types, i.e., incremental redundancy and code combining, as well as on the average throughput. Finally, we provide useful insights regarding the RIS characteristics that guarantee the optimal network performance.

The integration of Radio Frequency (RF) and Visible Light Communication (VLC) technologies has been considered an enabler to achieving the Key Performance Indicators (KPIs) in Beyond 5G (B5G). Apart from higher data rates for enhanced Mobile Broadband applications, Ultra-Reliable and Low-Latency Communications and massive Machine-Type Communications must be also supported. This poses notable challenges in the design of a mobile communication system that relies exclusively on the use of licensed RF spectrum. In order to cope with the requirements of B5G services, the complementary benefits that RF and VLC bands have in terms of communication bandwidth, signal propagation characteristics, and ultra-densification feasibility, can be exploited. For this purpose, this paper studies the performance of two integration approaches, namely RF - VLC selection (Layer-3 or network-layer) and RF-VLC aggregation (Layer-2 or MAC-layer). Based on the obtained simulation results, it is possible to conclude that RF - VLC aggregation outperforms RF - VLC selection in terms of data rate performance, especially when ultra-reliable communication services are required to connect a large number of user terminals placed in an indoor scenario.

Over-the-air Computation (AirComp) has attracted significant attention as an efficient way of data fusion by inte-grating uncoded communication transmissions with computation thanks to the superposition offered by the multiple access channels. However, proper pre-processing and post-processing is required to neutralize the wireless channel effect, in order for AirComp to function successfully. Since, internet-of-things (IoT) type of devices with limited capabilities are the target de-mographic of AirComp, having perfect channel state information (CSI) available is not always a practical assumption. In this work, we examine the effect of imperfect CSI on the AirComp system and we design a general optimization framework that takes into account both magnitude and phase errors in CSI. On top of that, a pilot retransmission policy is designed that offers a trade-off between cost of retransmissions and gain in the accuracy of the computations. Simulation results show the deterioration caused by the imperfect CSI and also the value of the proposed policy under various system conditions.

Federated Learning is a promising decentralized machine learning approach, which has the potential to realize the vision of next-generation internet-of-things (NGIoT), by offering intelligent services and meeting the privacy and low latency requirements. By leveraging the combination of edge servers, as intermediate model aggregators, and the central cloud server, as global model aggregator, the concept of Hierarchical Federated Learning (HFL) has recently emerged. In this paper, we aim to minimize the delay of a global HFL round, under user energy requirements. We jointly optimize the computation and communication resources, as well as the user-edge assignment, in order to minimize the overall delay. The formulated non-convex combinatorial problem, is optimally solved by being decomposed into two disjoint subproblems, namely the resource allocation and user-edge assignment. Finally, the simulation results demonstrate the effectiveness of the proposed methods in terms of delay reduction, compared to selected benchmarks, while insights for the networks' behavior are provided.

The Pearson type III and the log Pearson type III distributions have been considered in several scientific fields, as in hydrology and seismology. In this article, we present new results for these distributions and we utilize them, for the first time in the literature, to investigate the statistical behavior of wireless power transfer, which can prolong the lifetime of Internet of Things networks, considering the nonlinear relationship between the received and harvested power, which can be precisely modeled by using the logistic function. Specifically, we present new closed-form expressions for the statistical properties of a general form of the Pearson type III and the log Pearson type III distributions and we utilize them to introduce a new member of the Pearson type III family, the logit Pearson type III distribution, through which the logit gamma and the logit exponential distributions are also defined. Moreover, we derive closed-form expressions for the probability density function, the cumulative distribution function and moments of the distributions of the sum, the log sum, and the logit sum of Pearson type III random variables. Furthermore, taking into account that the Pearson type III family of distributions is closely related to the considered nonlinear energy harvesting model the statistical properties of the distribution of the harvested power are derived, for both single input single output and multiple input single output scenarios with or without channel state information at the transmitter.

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

In this paper, an uplink non-orthogonal multiple access (NOMA) terrestrial-satellite network is investigated, where the terrestrial base stations (BSs) communicate with satellite by backhaul link, and user equipments (UEs) share spectrum resource of access link. Firstly, a utility function which consists of the achieved terrestrial user rate and cross-tier interference caused by terrestrial BSs to satellite is design. Thus, the optimization problem can be modeled by maximizing the system utility function while satisfying the varying backhaul rate and UEs’ quality of service (QoS) constraints. The optimization problem is highly non-convex and can not be solved directly. Thus, we decouple the original problem into user association sub-problem, bandwidth assignment sub-problem, and power allocation sub-problem. In user association sub-problem, an enhanced-caching, preference relation, and swapping based algorithm is proposed, where the satellite UEs are selected by the channel coefficient ratio. The terrestrial UEs association considers the both caching state and backhaul link. Then we derive the closed-form expression of the bandwidth assignment. In power allocation sub-problem, we convert the non-convex term of the target function into the convex one by the Taylor expansion, and solve the transformed convex problem by an iterative power allocation algorithm. Finally, a three-stages iterative resource allocation algorithm by joint considering the three sub-problems is proposed. Simulation results are discussed to show the effectiveness of the proposed algorithms.

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

We investigate the optimal signal detection problem in large-scale multiple-input multiple-output (MIMO) system with the generalized spatial modulation (GSM) scheme, which can be formulated as a closest lattice point search (CLPS). To identify invalid signals, an efficient pruning strategy is needed while searching on the GSM decision tree. However, the existing algorithms have exponential complexity, whereas they are infeasible in large-scale GSM-MIMO systems. In order to tackle this problem, we propose a memory-efficient pruning strategy by leveraging the combinatorial nature of the GSM signal structure. Thus, the required memory size is squared to the number of transmit antennas. We further propose an efficient memory-bounded maximum likelihood (ML) search (EM-MLS) algorithm by jointly employing the proposed pruning strategy and the memory-bounded best-first algorithm. Theoretical and simulation results show that our proposed algorithm can achieve the optimal bit error rate (BER) performance, while its memory size can be bounded. Moreover, the expected time complexity decreases exponentially with increasing the signal-to-noise ratio (SNR) as well as the system’s excess degree of freedom, and it often converges to squared time under practical scenarios.

This paper investigates the optimal signal detection problem with a particular interest in large-scale multiple-input multiple-output (MIMO) systems. The problem is NP-hard and can be solved optimally by searching the shortest path on the decision tree. Unfortunately, the existing optimal search algorithms often involve prohibitively high complexities, which indicates that they are infeasible in large-scale MIMO systems. To address this issue, we propose a general heuristic search algorithm, namely, hyper-accelerated tree search (HATS) algorithm. The proposed algorithm employs a deep neural network (DNN) to estimate the optimal heuristic, and then use the estimated heuristic to speed up the underlying memory-bounded search algorithm. This idea is inspired by the fact that the underlying heuristic search algorithm reaches the optimal efficiency with the optimal heuristic function. Simulation results show that the proposed algorithm reaches almost the optimal bit error rate (BER) performance in large-scale systems, while the memory size can be bounded. In the meanwhile, it visits nearly the fewest tree nodes. This indicates that the proposed algorithm reaches almost the optimal efficiency in practical scenarios, and thereby it is applicable for large-scale systems. Besides, the code for this paper is available athttps://github.com/skypitcher/hats.

In this paper, we investigate a secure mobile edge computing (MEC) network in the presence of multiple eavesdroppers, where multiple users can offload parts of their tasks to the computational access point (CAP). The multiple eavesdroppers may overhear the confidential task offloading, which leads to information leakage. In order to address this issue, we present the minimization problem of the secrecy outage probability (SOP), by jointly taking into account the constraints from the latency and energy consumption. With the aim to improve the system secrecy performance, we then introduce three user selection criteria to choose the best user among multiple ones. Specifically,criterion Imaximizes the locally computational capacity, whilecriterion IIandIIImaximize the secrecy capacity and data rate of main links, respectively. For these criteria, we further analyze the system secrecy performance by deriving analytical and asymptotic expressions for the SOP, from which we can conclude important insights for the system design. Finally, simulation and analytical results are provided to verify the proposed analysis. The results show that the three criteria can efficiently safeguard the MEC networks, compared to the traditional local computing and fully offloading, especially with a large value of user number.

The convergence of radar sensing and communication applications in the millimeter-wave (mmWave) and low terahertz (THz) bands has been envisioned as a promising technology, since it incorporates high-rate data transmission of hundreds of gigabits per second (Gbps) and mm-level radar sensing in a spectrum- and cost-efficient manner, by sharing both the frequency and hardware resources. However, the joint radar sensing and communication (JRC) system faces considerable challenges in the mmWave and low-THz scale, due to the peculiarities of the propagation channel and radio-frequency (RF) front ends. To this end, the waveform design for the JRC systems in mmWave and low-THz bands with ultra-broad bandwidth is investigated in this paper. Firstly, by considering the JRC design based on the co- existence concept, where both functions operate in a time-domain duplex (TDD) manner, a novel multi-subband quasi-perfect (MS-QP) sequence, composed of multiple perfect subsequences on different subbands, is proposed for target sensing, which achieves accurate target ranging and velocity estimation, whilst only requiring cost-efficient low-rate analog-to-digital converters (A/Ds) for sequence detection. Furthermore, the root index of each perfect subsequence is designed to eliminate the influence of strong Doppler shift on radar sensing. Finally, a data-embedded MS-QP (DE-MS-QP) waveform is constructed through time-domain extension of the MS-QP sequence, generating null frequency points on each subband for data transmission. Unlike the co- existence-based JRC system in TDD manner, the proposed DE-MS-QP waveform enables simultaneous interference-free sensing and communication, whilst inheriting all the merits from MS-QP sequences. Numerical results validate the superiority of the proposed waveforms regarding the communication and sensing performances, hardware cost as well as flexibility of the resource allocation between the dual functions.

The cell-free massive multiple-input multiple-output (CFmMIMO) aims to provide uniform quality of service (QoS) for all users, and can be used in small-area scenarios such as indoor industrial networks. This paper studies the CFmMIMO system for indoor industrial scenarios. Firstly, an access point (AP) grouping based hierarchical network topology is proposed. Based on this, we propose an effective AP selection method. To reduce pilot contamination, a pilot assignment scheme based on inspection robot (IR) location is proposed. Considering the high reliability requirement of industrial data transmission, the power control and backhaul combining are jointly optimized to maximize the minimum signal to interference plus noise ratio (SINR). The scalability of the proposed CFmMIMO system is analyzed, and a scalable power control method is proposed. The simulations demonstrate the effectiveness of the AP selection method, pilot assignment scheme, and the joint optimization algorithm for power control and backhaul combining. Moreover, the impact of network scale and network load on system performance is evaluated and analyzed in the simulations.

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

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

The advent of Internet of Things (IoT) has bring a new era in communication technology by expanding the current inter-networking services and enabling the machine-to-machine communication. IoT massive deployments will create the problem of optimal power allocation. The objective of the optimization problem is to obtain a feasible solution that minimizes the total power consumption of the WSN, when the error probability at the fusion center meets certain criteria. This work studies the optimization of a wireless sensor network (WNS) at higher dimensions by focusing to the power allocation of decentralized detection. More specifically, we apply and compare four algorithms designed to tackle Large scale global optimization (LSGO) problems. These are the memetic linear population size reduction and semi-parameter adaptation (MLSHADE-SPA), the contribution-based cooperative coevolution recursive differential grouping (CBCC-RDG3), the differential grouping with spectral clustering-differential evolution cooperative coevolution (DGSC-DECC), and the enhanced adaptive differential evolution (EADE). To the best of the authors knowledge, this is the first time that LSGO algorithms are applied to the optimal power allocation problem in IoT networks. We evaluate the algorithms performance in several different cases by applying them in cases with 300, 600 and 800 dimensions.

Terahertz (THz) technology and non-orthogonal multiple access (NOMA) technology have shown a high potential to enhance the spectrum efficiency of wireless communications. This paper aims to study the resource scheduling problem by maximizing energy efficiency (EE) of NOMA two-tier heterogeneous network in THz frequency band, taking a full account of the influence of subchannel and power allocation on the downlink of THZ-NOMA network. In order to achieve the research goal better, it's the first time that a subchannel allocation method and power allocation scheme based on improved Whale Optimization Algorithm (WOA) is proposed in this system. The simulation results indicate that, compared with the existing methods, the proposed scheme has faster convergence speed and has certain advantages in performance.

In the vision of the next generation communications, the wireless devices may work on different transmission media, such as microwave and visible light. In this case, how to bridge these different devices remains an open challenge. Following the framework of [1], we consider a cross-media base station (BS) for supporting devices working on different media, as visible light and radio frequency (RF). Specifically, we conceive two criteria for power allocation toward enhanced performance, by maximizing the sum and minimum rates. Furthermore, we also analyze the impact of the position of BS to the system performance. Finally, the theoretical results are verified by simulations for supporting the effectiveness of the developed power allocation schemes in cross-media communications.

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

One of the main challenges in wireless powered networks (WPNs) is the doubly near-far problem, i.e., the twofold degradation of the users' performance due to different path-loss values that affects both the energy harvesting and the information transmission efficiency. To this end, we propose and optimize the application of decentralized power transfer and radio access in WPNs, which is implemented by using multiple remote radio heads (RRHs) with the capability to both transfer energy and receive information. More specifically, the use of non-orthogonal multiple access (NOMA) and time division multiple access (TDMA) is investigated, while two novel schemes are proposed, hereinafter termed as partially and fully asynchronous transmission TDMA (AT-TDMA). According to the proposed schemes, the users harvest energy and transmit information to the RRHs in different portions of time. Furthermore, the sum and minimum throughput among users are jointly maximized by obtaining the Pareto optimal solutions for the scheduling of power transfer and information transmission. To evaluate the performance of the decentralized architecture compared to the centralized one, we solve the aforementioned optimization problem for both architectures, taking also into account the circuit power consumption. Simulations show that the use of multiple RRHs improves spectral efficiency compared to the centralized implementation, since it can tackle more efficiently the doubly near-far problem. In addition, the proposed AT-TDMA schemes increase the achievable data rate.

This paper aims to devise a generalized maximum likelihood (ML) estimator to robustly detect signals with unknown noise statistics in multiple-input multiple-output (MIMO) systems. In practice, there is little or even no statistical knowledge on the system noise, which in many cases is non-Gaussian, impulsive and not analyzable. Existing detection methods have mainly focused on specific noise models, which are not robust enough with unknown noise statistics. To tackle this issue, we propose a novel ML detection framework to effectively recover the desired signal. Our framework is a fully probabilistic one that can efficiently approximate the unknown noise distribution through a normalizing flow. Importantly, this framework is driven by an unsupervised learning approach, where only the noise samples are required. To reduce the computational complexity, we further present a low-complexity version of the framework, by utilizing an initial estimation to reduce the search space. Simulation results show that our framework outperforms other existing algorithms in terms of bit error rate (BER) in non-analytical noise environments, while it can reach the ML performance bound in analytical noise environments.

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

A hybrid downlink system that simultaneously uses visible light communication (VLC) and radio frequency (RF) is investigated, assuming that only one of the two considered users is capable of receiving information over the optical band. In order to facilitate information transmissions from the VLC access point to the RF user, mixed VLC/RF relaying and simultaneous lightwave information and power transfer (SLIPT) are utilized. Moreover, a cognitive-based resource allocation policy and tractable bounds for the harvested energy are introduced. Furthermore, by taking into account the random location of the VLC and RF user terminals, the closed-form outage probability for the VLC user is given, while for the RF user, the outage probability is derived in terms of infinite-series, which is also approximated by a tractable closed-form expression. In addition, the outage probability of the RF user is minimized by optimizing the direct current (DC) component. Finally, simulations are provided to verify the accuracy of the theoretical analysis and demonstrate the effectiveness of the proposed optimization framework.

The$\kappa $-$\mu $/ inverse gamma and$\eta $-$\mu $/ inverse gamma composite fading models are presented and extensively investigated in this paper. We derive closed-form expressions for the fundamental statistics of the$\kappa $-$\mu $/ inverse gamma composite fading model, such as the probability density function (PDF), cumulative distribution function (CDF). Additionally, we solve the associated integral that is commonly used to obtain the moment generating function (MGF) of statistical distributions to provide an MGF-type function which is valid for performance analysis over the specified parameter space. Analytic expressions for the PDF, higher order moments and AF are also derived for the$\eta $-$\mu $/ inverse gamma composite fading model, while infinite series expressions are obtained for the corresponding CDF and MGF-type function. The suitability of the new models for characterizing composite fading channels is demonstrated through a series of extensive field measurements for wearable, cellular, and vehicular communications. For all of the measurements, two propagation geometry problems with special relevance to the two new composite fading models, namely the line-of-sight (LOS) and non-LOS (NLOS) channel conditions, are considered. It is found that both the$\kappa $-$\mu $/ inverse gamma and$\eta $-$\mu $/ inverse gamma composite fading models provide an excellent fit to fading conditions encountered in the field. The goodness-of-fit of these two composite fading models is also evaluated and compared using the resistor-average distance. As a result, it is shown that the$\kappa $-$\mu $/ inverse gamma composite fading model provides a better fit compared to the$\eta $-$\mu $/ inverse gamma composite fading model when strong dominant signal components exist. On the contrary, the$\eta $-$\mu $/ inverse gamma composite fading model outperforms the$\kappa $-$\mu $/ inverse gamma composite fading model when there is no strong dominant signal component and/or the parameter$\eta $is not equal to unity, indicating that the scattered wave power of the in-phase and quadrature components of each cluster of multipath are not identical.

In this paper, non-orthogonal multiple access (NOMA) networks assisted by multiple intelligent reflecting surfaces (IRSs) with discrete phase shifts are investigated, in which each user device (UD) is served by an IRS to improve the quality of the received signal. Two scenarios are considered according to whether there is a direct link between the base station (BS) and each UD, and the outage performance is analyzed for each of them. Specifically, the asymptotic expressions for the upper and lower bounds of the outage probability in the high signal-to-noise ratio (SNR) regime are derived. Following that, the diversity order is obtained. It is shown that the use of discrete phase shifts does not degrade diversity order. More importantly, simulation results reveal that a 3-bit resolution for discrete phase shifts is sufficient to achieve near-optimal outage performance. Simulation results also imply the superiority of IRSs over full-duplex decode-and-forward relays.

In this paper, we investigate simultaneous lightwave information and power transfer (SLIPT) for underwater visible light communication systems. We consider three SLIPT methods namely time switching (TS), power splitting (PS) and time switching-power splitting (TS-PS) where the splitting/switching factors are defined as optimization parameters. For each of these methods, we derive closed-form expressions for the average harvested energy, bit error rate and spectral efficiency in the presence of underwater turbulence modeled by lognormal statistics. Using these expressions, we determine the optimal splitting factors to maximize the harvested energy while satisfying a given bit error rate value and a given threshold spectral efficiency value. Our results reveal that, if not optimized, SLIPT methods under consideration are outperformed by the simple AC-DC separation (ADS) method which provides the largest harvested energy versus spectral efficiency (HE-SE) region. Optimization of splitting/switching factors extends the HE-SE regions; hence, optimized versions of TS, PS and TS-PS methods are able to significantly outperform ADS for most cases. We further investigate the effect of various channel and system parameters such as water type, turbulence level, beam divergence, receiver aperture size on the harvested energy and quantify the improvements in battery lifetime through the use of SLIPT methods.

In this paper, we investigate a mobile edge computing (MEC) network with two computational access points (CAPs), where the source is equipped with multiple antennas and it has some computational tasks to be accomplished by the CAPs through Nakagami-m distributed wireless links. Since the MEC network involves both communication and computation, we first define the outage probability by taking into account the joint impact of latency and energy consumption. From this new definition, we then employ receiver antenna selection (RAS) or maximal ratio combining (MRC) at the receiver, and apply selection combining (SC) or switch-and-stay combining (SSC) protocol to choose a CAP to accomplish the computational task from the source. For both protocols along with the RAS and MRC, we further analyze the network performance by deriving new and easy-to-use analytical expressions for the outage probability over Nakagami-m fading channels, and study the impact of the network parameters on the outage performance. Furthermore, we provide the asymptotic outage probability in the low regime of noise power, from which we obtain some important insights on the system design. Finally, simulations and numerical results are demonstrated to verify the effectiveness of the proposed approach. It is shown that the number of transmit antenna and Nakagami parameter can help reduce the latency and energy consumption effectively, and the SSC protocol can achieve the same performance as the SC protocol with proper switching thresholds of latency and energy consumption.

Secure communication for the primitive relay wiretap channel under the decode-and-forward protocol, is considered. A polar coding-based technique is proposed and we show that is suitable to provide reliability and a level of information-theoretic security. We focus on the strong secrecy criterion where in order to satisfy it we implement a double-chaining construction to overcome the obstacle of misaligned bits.

A new queue-length aware online scheduling scheme is proposed for a buffer-aided wireless-powered communication network (WPCN) with non-orthogonal multiple access (NOMA). The throughput of the considered network is maximized by designing the optimal resource allocation scheme, while preserving the stability of both energy and data queues. The formulated optimization problem is particularly challenging, since it is a long-term mixed-integer optimization problem. In order to solve it efficiently, we first transform the long-term optimization problem into a series of short-term ones at each time slot by taking advantage of the Lyapunov optimization framework, which can be efficiently solved. The analytical expression of the rate allocation reveals that in contrast to the case of WPCN without buffering, the optimal decoding order depends on the length of data buffer. Simulation results show that the proposed scheme outperforms the non-buffering scheme in terms of the long-term time-average sum rate.

In this paper, we investigate a secure relaying network with simultaneous wireless information and power transfer (SWIPT). It is assumed that Alice wants to send confidential information to Bob under the existence of a passive eavesdropper (Eve), while the relay is equipped with a data buffer and an energy storage device. More specifically, we aim at achieving higher secrecy throughput, while retaining the stability of the data and energy queues. To achieve this with acceptable complexity, we transform the original long-term stochastic optimization problem into a series of online subproblems using the framework of Lyapunov optimization. The proposed scheme shows that the optimal time switching factor is 0 or 1, which is different from the conventional secure relaying network with SWIPT. In addition, simulation results verify that the proposed scheme can improve the secrecy throughput compared with the baseline scheme.

Unmanned aerial vehicle (UAV)-enabled communications have been proposed as a critical part of the beyond fifth-generation (5G) cellular networks. This type of communications is frequently characterized by line-of-sight (LoS) and dynamic propagation conditions. However, in various scenarios, the presence of large obstacles in the LoS path is unavoidable, resulting in shadowed fading environments. In this paper, a new channel model is proposed, in which the effects of mobility and shadowing are simultaneously considered. In particular, the performance of a UAV-based communication system operating in a shadowed double-scattering channel is analyzed. The new channel model is generic, since it models various fading/shadowing conditions, while it is in terms of easy-to-evaluate mathematical functions. Moreover, a low complexity UAV selection policy is proposed, which exploits shadowing-related information. The proposed scheme offers a reduction of the signal processing complexity, without any important degradation on the performance, as compared to alternatives approaches. In this context, a new analytical framework has been developed for investigating the performance of the new strategy. Finally, the main outcomes of this paper are also validated by empirical data, collected in an air-to-ground measurement campaign.

Ambient backscatter devices (tags and readers) use existing radio frequency (RF) signals to transmit data. Most prior works consider single-antenna tags, but this paper investigates the case of multiple-antenna tags, which are capable of simultaneous energy harvesting and data transmission. However, the multi-antenna channel between the tag and the reader, and the unpredictable nature of RF signals due to uncontrollable RF sources (e.g., location and transmit power), make signal detection highly challenging. Thus, the detection process becomes a hypothesis testing problem with unknown parameters. Consequently, we design a blind detector based on the generalized likelihood ratio test (GLRT) without using channel state information (CSI), signal power and noise variance. The decision threshold and detection probability of it are also analyzed in detail. Furthermore, to maximize its detection performance, we develop the optimal backscatter antenna selection scheme. Interestingly, we show that the detector performs best when only two backscatter antennas are selected. Finally, extensive simulation results validate the analysis and illustrate the effectiveness of the proposed detector.

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

Cooperative non-orthogonal multiple access (C-NOMA) and buffering are promising techniques to improve spectrum efficiency in the next generation of wireless networks. In this article, a buffer-aided cooperative NOMA network with direct links is studied. The throughput maximization problem is firstly formulated under the assumption of fixed power allocation and optimally solved by designing a mode selection policy. In order to further improve system throughput, the problem is extended into the case that power allocation and mode selection are jointly optimized. An optimal solution is obtained, while a sub-optimal one is also provided in order to decrease the implementation complexity. Furthermore, considering the case where the buffer has finite size and the users are delay-sensitive, a throughput-delay aware strategy is also presented. Moreover, it is shown that the proposed schemes outperform the baseline one in terms of throughput. Finally, simulations demonstrate that the sub-optimal solution achieves similar performance to the optimal one, while significantly reduces the implementation complexity.

In this paper, we investigate the statistics of the free space optics (FSO) communication channel between a hovering unmanned aerial vehicle (UAV) and a central unit. Two unique characteristics make UAV-based FSO systems significantly different from conventional FSO systems with static transceivers. First, for UAV-based FSO systems, the incident laser beam is not always orthogonal to the receiver lens plane. Second, both position and orientation of the UAV fluctuate over time due to dynamic wind load, inherent random air fluctuations in the atmosphere around the UAV, and internal vibrations of the UAV. On the contrary, for conventional FSO systems, the laser beam is always perpendicular to the receiver lens plane and the relative movement of the transceivers is limited. In this paper, we develop a novel channel model for UAV-based FSO systems by quantifying the corresponding geometric and misalignment losses (GML), while taking into account the non-orthogonality of the laser beam and the random fluctuations of the position and orientation of the UAV. In particular, for diverse weather conditions, we propose different fluctuation models for the position and orientation of the UAV and derive corresponding statistical models for the GML. We further analyze the performance of a UAV-based FSO link in terms of outage probability and ergodic rate and simplify the resulting analytical expressions for the high signal-to-noise ratio (SNR) regime. Finally, simulations validate the accuracy of the presented analysis and provide important insights for system design. For instance, we show that for a given variance of the fluctuations, the beam width should be properly adjusted to minimize the outage probability.

Random access (RA) has recently been revisited and considered as a key technology for the medium access control layer of the Internet of Things applications. Compared to other RA protocols, slotted ALOHA (SA) has the advantages of low complexity and elimination of partially overlapping transmissions, reducing the number of collisions, however it may suffer from congestion as the traffic load and the number of devices increase. To this end, two RA protocols based on SA and uplink non-orthogonal multiple access are proposed and applied to wireless sensor networks and wireless powered sensor networks. More specifically, to reduce the number of collisions and increase the throughput of SA, while maintaining low complexity, two detection techniques are used to mitigate the interference, when two sources transmit information in the same time slot, namely successive interference cancellation (SIC) with optimal decoding order policy and joint decoding (JD). To evaluate the performance of the proposed protocols, the outage probability of SIC and JD is derived, which is used to express the average throughput attained by each protocol in closed-form. Finally, both the analytical results and the simulations verify that the proposed protocols substantially increase the throughput and the number of connected devices compared to SA.

In this paper, the end-to-end performance of a mixed radio frequency (RF)/free space optical (FSO) affected by co-channel interference (CCI), is studied. We consider that the RF link experiences η - μ fading and the FSO link is subjected to atmospheric turbulence, which is modeled by the α - μ distribution. Also, the statistics of the FSO link is presented for the case of zero and non-zero boresight pointing errors. Furthermore, we assume intensity modulation with direct detection (IM/DD) and coherent demodulation. In particular, we present a closed-form expression for the probability density function of the FSO link, which is then used to obtain a closedform and an asymptotic expression for the outage probability. In order to quantify the system performance, we utilize this asymptotic result to yield the system's coding gain and diversity order. Moreover, we have presented analytical expressions for the average bit error rate (BER) and ergodic capacity for the system design. In order to gain more insights, high signal-to-noise ratio (SNR) approximations expressions for the BER and ergodic capacity, are also derived. Finally, the analytical results presented in the paper are validated through computer simulations.

Fuel-powered UAVs have long endurance of flight, heavy payload and adaptation to extreme environment. The mechanical operation and communication power are supported independently by fuel and batteries. In the paper, we study the energy efficiency of the communication system with a fuel-powered UAV relay. We consider a three-node communication network, consisting of a mobile relay, a source node, and a destination node. The UAV relay is able to change its 3-D trajectory to maintain high probability of LoS channels, receiving information from the fixed source node and transmitting it to the fixed destination node. The power allocation scheme and UAV's trajectory are designed to maximize the system energy efficiency, considering the constraints of speeds, UAV's altitudes, communication and mechanical energy consumption, the required data rates of the destination node and information-causality. We solve the power allocation sub-problem by splitting the domain of variables and transforming it into a convex optimization problem. And then a suboptimal scheme is provided to design the trajectory based on successive convex approximation method. Numerical results show the convergence of the proposed schemes and the performance of the proposed algorithms. The influences of time slots, constraints of fuel, communication power and required data rates are discussed.

High-speed train (HST) communications in tunnels have attracted more and more research interests recently, especially within the framework of the fifth generation (5G) wireless networks. In this paper, based on cuboid-shape, three-dimensional (3D) non-stationary wideband geometry-based stochastic models (GBSMs) for HST tunnel scenarios are proposed. By considering the influence of the tunnel walls, a theoretical channel model is first established, which assumes clusters with an infinite number of scatterers randomly distributed on the tunnel walls. The corresponding simulation model is then developed and the method of equal areas is employed to obtain the discrete parameters, such as the azimuth and elevation angles. We derive and investigate the most important channel statistical properties of the proposed 3D GBSMs, including the time-variant autocorrelation function, spatial cross-correlation function, and Doppler power spectrum density. It is indicated that all statistical properties of the simulation model, verified by simulation results, can match very well with those of the theoretical model. Furthermore, a validation is presented by comparing the stationary regions of our proposed tunnel channel model to those of relevant measurement data.

We propose an indoor lightwave downlink wireless communication network with the non-orthogonal multiple access (NOMA) technology, that consists of one visible light communication (VLC) access point (AP) and a pair of randomly located users. Although both users can directly receive information from the AP, the performance of the far user is degraded compared to the near one due to the asymmetrical channel gains. Thus, the user cooperation strategy is proposed to improve the performance of the far user by using mixed VLC/RF relaying technique in parallel with the wireless optical direct link. To efficiently exploit the available heterogeneous links, the concept of cross-band selection combining (CBSC) is introduced, according to which the far user is continuously served by either the mixed VLC/RF or the direct VLC link. Meanwhile, the performance of the proposed scheme is thoroughly investigated and compared to appropriate baselines. To this end, we derive closed-form expressions for the outage probability of each user as well as the system sum throughput. Finally, simulation results are provided to verify the effectiveness of the proposed scheme and the accuracy of the corresponding analysis.

Non-orthogonal multiple access (NOMA) in heterogeneous network (HetNet) is a very promising scheme to meet the exponential growth of mobile data expected in the coming years. However, since wireless networks are becoming denser, the energy consumption of such networks is increasingly severe. Therefore, it is necessary to design novel energy efficiency (EE) maximization technologies under the constraint of limited energy supply. This paper investigates the resource optimization problem of NOMA heterogeneous small cell networks with simultaneous wireless information and power transfer (SWIPT). By decoupling subchannel allocation and power control, a low-complexity subchannel matching algorithm is designed. Furthermore, to maximize the energy efficiency, a power optimization algorithm is proposed using Langrangian duality. Aiming at the power allocation problem, the original non-convex and non-linear energy efficiency optimization problem is transformed into a more tractable one. Simulation results demonstrate the effectiveness and convergence of the proposed optimization scheme in terms of system energy efficiency.

In this paper, we present a novel low cost and low complexity platform for the provisional diagnosis of vessels abnormalities, such as artery stenosis, aneurysms, etc. The proposed system is based on a low cost lightwave wearable device and advanced machine learning techniques to reduce the computational load and improve the accuracy of diagnosis. Specifically, in this work we focus on the image reconstruction in the case of an artery stenosis due to atheromatic plaque, where we briefly present the method and some preliminary results. The proposed platform can automatically provide a provisional diagnosis which can then be followed-up with further detailed and/or established imaging methods (e.g., Doppler ultrasound, Magnetic Resonance Angiography, etc) and treated promptly in order to minimize their likelihood of progression to higher levels of severity. This method may act as an adjunct to existing established screening programmes (e.g., arterial stenosis and aneurysm screening) or be used for new forms of population screening in the future.

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

Non-orthogonal multiple access (NOMA) has recently attracted the academic and industrial interest, due to offering higher spectral efficiency and connectivity compared to conventional orthogonal multiple access schemes. In this paper, buffer-aided relaying for a downlink NOMA system with direct links is proposed, while in order to take advantage the extra degrees of freedom, appropriate transmission modes are presented. Targeting at the throughput maximization, the corresponding optimization problem is formulated and solved and theoretical expressions are derived for the optimal mode selection policy and maximum throughput. Finally, simulation results illustrate the efficiency of the proposed scheme and its superiority compared with a previously presented baseline scheme.

Visible light communication (VLC) has emerged as a high-capacity connectivity solution for underwater sensor networks. Since water is relatively transparent to blue or green light, visible light lasers or LEDs can be used as transmitters for underwater wireless connectivity with data rates up to hundreds of Mbps. In underwater networks, a critical system design issue is the network lifetime which highly depends on the battery capacity. Since recharging in underwater scenarios is typically very costly and impractical, energy harvesting can be considered as a promising alternative. In this paper, we explore simultaneous lightwave information and power transfer (SLIPT) for VLC-based USNs. We adopt time splitting method where the receiver switches in time between the modes of energy harvesting (EH) and information decoding (ID). We derive a closed-form expression for the average harvested energy over log-normal model underwater turbulence channel. Using this expression, we determine the splitting factor between EH and ID operation modes to maximize the harvested energy while satisfying a given bit error rate value.

Non-orthogonal multiple access (NOMA) has attracted both academic and industrial interest since it has been considered as one of the promising 5G technologies in order to increase connectivity and spectral efficiency. In this paper, we focus on a downlink NOMA network, where a single base station serves a set of users through multiple subchannels. The goal is to jointly optimize energy efficiency (EE) and fairness among users with respect to the subcarrier and power allocation parameters. To achieve this with acceptable complexity, we propose a novel greedy subcarrier assignment scheme. Due to the fractional form of the EE expression and the existence of interference, the power allocation problem is non-convex. To this end, we first transform this into an equivalent subtractive form, which is then solved by using fractional programming with sequential optimization of the power allocation vectors. Simulation results reveal the effectiveness of the proposed scheme in terms of EE and fairness among users compared to baseline schemes. Finally, the proposed algorithms are of fast convergence, low complexity, and insensitive to the initial values.

The F composite fading model was recently proposed as an accurate and tractable statistical model for the characterization of the composite fading conditions encountered in realistic wireless communication scenarios. In the present contribution we capitalize on the distinct properties of this composite model to evaluate the achievable effective rate over F composite fading channels. To this end, we derive an exact closed-form expression for the effective rate, which is subsequently used as a benchmark for the derivation of tight upper and lower bounds, as well as of an accurate approximation. The derived analytic expressions are provided in closed-form and benefit from being tractable both analytically and numerically. This enables the development of meaningful insights on the effect of fading conditions and/or latency on the overall system performance. Also, it allows the accurate quantification of the signal to noise ratio required in target quality of service requirements under different composite fading conditions.

Non-orthogonal multiple access (NOMA) has attracted both academic and industrial interest since it has been considered as one of the promising 5G technologies in order to increase connectivity and spectral efficiency. In this paper, we focus on a downlink multicarrier (MC) NOMA network, where a single base station serves a set of users through multiple subchannels. The goal is to jointly optimize energy efficiency (EE) and fairness among users with respect to the subcarrier and power allocation parameters. To achieve this with acceptable complexity, a novel greedy subcarrier assignment scheme based on the worst-user first principle is proposed. Due to the fractional form of the EE expression and the existence of interference, the power allocation problem is non-convex and NP-hard. To this end, we first transform this into an equivalent subtractive form, which is then solved by using fractional programming with sequential optimization of the inter/intra-subchannel power allocation vectors. Simulation results reveal the effectiveness of the proposed scheme in terms of EE and fairness among users compared to baseline schemes. Finally, the proposed algorithms are of fast convergence, low complexity, and insensitive to the initial values.

One of the major goals of emerging wireless systems is to prolong the lifetime of wireless communication devices. To this end, this contribution evaluates and optimizes the performance of simultaneous wireless information and power transfer (SWIPT) with an integrated energy and information receiver, which has the advantage of low complexity and energy cost. A tractable expression for the achievable rate is first derived, which is subsequently used to quantify the achievable harvested energy-rate region for the two fundamental SWIPT protocols, namely, power-splitting (PS) and time-switching (TS). In this context, the joint harvested energy-rate outage probability is then defined and minimized for a point-to-point and multicasting system, determining the optimal PS and TS factors for both linear and nonlinear energy harvesting models. In addition, a TS-based broadcasting system is dynamically optimized by maximizing the energy harvested by all users under an achievable rate threshold for each user. The formulated optimization problem is, in fact, particularly challenging due to the non-convex form of the expression for the achievable rate. Yet, an effective solution is ultimately achieved by converting this problem into a convex one. Also, respective computer simulation results corroborate the effectiveness of the proposed framework. Overall, it is shown that the offered results provide meaningful theoretical and practical insights that will be useful in the design and efficient operation of wireless powered systems. Indicatively, unlike the trend in common separated receivers, a region has been identified, where TS outperforms PS.

This paper investigates a hybrid radio frequency (RF)/visible light communication (VLC) ultra-small cell network consisting of multiple optical angle-diversity transmitters, one multi-antenna RF access point (AP) and multiple terminal devices. In the network, the optical transmitters play the primary role and are responsible for delivering information and power over the visible light while the RF AP acts as a complementary power transfer system. Thus, we propose a novel collaborative RF and lightwave resource allocation scheme for hybrid RF/VLC ultra-small cell networks. The proposed scheme aims to maximize the communication quality-of-service provided by the VLC under a constraint of total RF and light energy harvesting performance while keeping illumination constant and ensuring health safety. This scheme leads to the formulation of two optimization problems that correspond to the resource allocation at the optical transmitters and the RF AP. Both problems are optimally solved by appropriate algorithms. Moreover, we propose a closed-form suboptimal solution with high accuracy to tackle the optical transmitters' resource allocation problem, as well as an efficient semi-decentralized method. Finally, simulation results illustrate the achievable performance of the investigated system and the effectiveness of the proposed solutions.

We investigate the performance of mixed free-space optical (FSO)/millimeter-wave (mmWave) relay networks with interference at the destination. The FSO/mmWave channels are assumed to follow Málaga-M/generalized-K fading models with pointing errors in the FSO link. The H-transform theory, wherein integral transforms involve Fox's H-functions as kernels, is embodied to unifying the performance analysis framework that encompasses closed-form expressions for the outage probability, the average bit error rate (BER), and the average capacity. By virtue of some H-transform asymptotic expansions, the high signal-to-interference-plus-noise ratio (SINR) analysis reduces to easy-to-compute expressions for the outage probability and BER, which reveals inside information for the system design. We finally investigate the optimal power allocation strategy that minimizes the outage probability.

In this paper, we investigate the security of a cache-aided multi-relay communication network in the presence of multiple eavesdroppers, where each relay can pre-store a part of the requested files in order to assist secure data transmission from source to destination. If the relays have cached the requested file, then they can directly send it to the destination; otherwise, traditional dual-hop data transmission is used. For both cases, relay selection is performed to assist the secure data transmission. We analyze the network secrecy performance in both scenarios ofnon-colludingandcolludingeavesdroppers, and obtain a closed-form expression for the average secrecy outage probability (SOP), as well as an asymptotic expression for the high main-to-eavesdropper ratio (MER). Through minimizing the network SOP, we further optimize the cache placement by proposing a stochastic sampling based cache learning (SacLe) strategy, which can be implemented in parallel and thus reduces the implementation latency substantially. Numerical and simulation results are finally presented to verify the proposed analysis, and show that the caching strategy has a significant impact on the network secrecy performance through affecting the caching diversity gain and signal cooperation gain at the relays. The proposed SacLe strategy is shown to be able to achieve the optimal performance obtained by the brute force (BF) algorithm.

For unmanned aerial vehicle (UAV) aided millimeter wave (mmWave) networks, we propose a unified three-dimensional (3D) spatial framework in this paper to model a general case that uncovered users send messages to base stations via UAVs. More specifically, the locations of transceivers in downlink and uplink are modeled through the Poisson point processes and Poisson cluster processes (PCPs), respectively. For PCPs, Matern cluster and Thomas cluster processes, are analyzed. Furthermore, both 3D blockage processes and 3D antenna patterns are introduced for appraising the effect of altitudes. Based on this unified framework, several closed-form expressions for the coverage probability in the uplink and downlink, are derived. By investigating the entire communication process, which includes the two aforementioned phases and the cooperative transmission between them, tractable expressions of system coverage probabilities are derived. Next, three practical applications in UAV networks are provided as case studies of the proposed framework. The results reveal that the impact of thermal noise and non-line-of-sight mmWave transmissions is negligible. In the considered networks, mmWave outperforms sub-6 GHz in terms of the data rate, due to the sharp direction beamforming and large transmit bandwidth. Additionally, there exists an optimal altitude of UAVs, which maximizes the system coverage probability.

In this paper, we investigate the performance of energy detection-based spectrum sensing over F composite fading channels. To this end, an analytical expression for the average detection probability is first derived. This expression is then extended to account for collaborative spectrum sensing, square-law selection diversity reception, and noise power uncertainty. The corresponding receiver operating characteristics (ROC) are analyzed for different conditions of the average signal-to-noise ratio (SNR), noise power uncertainty, time-bandwidth product, multipath fading, shadowing, number of diversity branches, and number of collaborating users. It is shown that the energy detection performance is sensitive to the severity of the multipath fading and the amount of shadowing, whereby even small variations in either of these physical phenomena can significantly impact the detection probability. As a figure of merit to evaluate the detection performance, the area under the ROC curve (AUC) is derived and evaluated for different multipath fading and shadowing conditions. Closed-form expressions for the differential entropy and cross entropy are also formulated and assessed for different average SNR, multipath fading, and shadowing conditions. Then, the relationship between the differential entropy of F composite fading channels and the corresponding ROC/AUC is examined where it is shown that the average number of bits required for encoding a signal becomes small (i.e., low differential entropy) when the detection probability is high or when the AUC is large. The difference between composite fading and traditional small-scale fading is emphasized by comparing the cross entropy for Rayleigh and Nakagami-m fading. A validation of the analytical results is provided through a careful comparison with the results of some simulations.

In this paper, we consider a radio-frequency identification (RFID) backscatter system with two scenarios: single input multiple output (SIMO) and multiple input single output (MISO). We investigate the impact of channel correlation between the forward and backscatter links on the symbol error rate (SER), and we compare the performance of SIMO and MISO RFID systems with maximum ratio combining reception over arbitrarily correlated Nakagami-m fading channels. In order to gain an insight for the system design, closed-form expressions for the asymptotic SER and an upper bound are derived for M-ary phase-shift keying and quadrature amplitude modulation. The diversity order in the fully correlated cases, revealed from these expressions, is half of that in the partially correlated and uncorrelated cases. Finally, simulations are performed to validate the theoretical analysis.

A full-duplex ultra-dense network (FDUDN) has been envisioned as a promising network paradigm for spectrum efficiency enhancement. This paper presents a novel joint spectrum and power management scheme, which maximizes the total capacity of the FDUDN, under given quality-of-service and cross-tier interference constraints. The proposed scheme is decomposed into inter-cell and intra-cell allocation. A novel approach, which performs initial capacity-maximization allocation and successive adjustment based on the constraints, is proposed for the allocation of the inter-cell subchannels. The inter-cell power control is formulated as a non-convex optimization problem, and variable substitution is used to transform it into a convex one. Furthermore, we solve this problem through a low-complexity heuristic scheme, which utilizes the water-filling theorem in inter-cell power allocation. Finally, a time-sharing relaxation method is adopted to solve the intra-cell subchannel allocation problem and reduce the computation complexity. The Computer simulation demonstrates the enhancement effect of the proposed scheme in terms of the capacity, spectrum efficiency, and power efficiency.

In this paper, we study decode-and-forward relaying networks in the presence of direct links, where they are used by the eavesdropper to overhear the confidential message from the source and relay. The secure data transmission can go through from either the direct or the relaying branch, and we focus on the practical communication scenarios, where the main and eavesdropper channels are correlated. Although traditional opportunistic selection techniques can choose one better branch to ensure the secure performance, it needs to continuously know the channel state information (CSI) of both branches and may result in a high branch switching rate. To overcome these limitations, we propose a distributed secure switch-and-stay combining (DSSSC) protocol, where only one between direct and relaying branches is activated to assist the secure data transmission, and the switching occurs when the branch cannot support the secure communication any longer. The DSSSC protocol uses either the instantaneous or the statistics of the eavesdropping CSI. For both cases, we quantify the impact of correlated fading on secure communication by deriving an analytical expression for the secrecy outage probability (SOP) as well as an asymptotic expression for the high main-to-eavesdropper ratio region. From the asymptotic SOP, we can conclude that the DSSSC can achieve the optimal secure performance of opportunistic selection with less implementation complexity, and the channel correlation can further enhance the transmission security.

Radio frequency identification (RFID) backscatter communication systems play an important part in the future Internet of Things (IoT) applications. In this paper, we consider a multiple input single output (MISO) backscatter system, where the reader is equipped with multiple antennas and the tag is equipped with single antenna. The impact of the channel correlation between the forward and backscatter links on the symbol error rate (SER) is investigated. Then, we derive expressions for asymptotic SER and an upper bound, assuming M-ary phase-shift keying (M-PSK) and quadrature amplitude modulation (M-QAM) with maximum ratio combining (MRC) reception, over arbitrarily correlated Nakagami-m fading channels. From these expressions, we can directly obtain the diversity order. Finally, numerical results and simulations are provided to demonstrate the accuracy of the theoretical expressions.

Airborne radio access networks (A-RANs) is a particularly promising technology due to its ability to offer fast, cost-efficient, and on-demand enhancement of the existing telecommunication infrastructure. The main challenges of ARANs are the energy sustainability of the aerial platforms (APs) and the establishment of reliable links with the ground nodes. To this direction, we propose a novel approach, which is based on mixed free-space optical (FSO)/radio frequency (RF) relaying protocol and simultaneous lightwave information and power transfer (SLIPT). In this context, we also formulate and optimally solve the max-min fairness problem, which regulates the trade-off between the energy and information transfer to the AP and allocates the available resources to multiple endusers. Finally, the impact of the number of users and weather conditions on system's optimal configuration and performance is investigated through simulations. The offered results provide meaningful theoretical and practical insights on the capabilities of the proposed scheme.

Recently, it was shown that non-orthogonal multiple access (NOMA) became a hot topic due to its capacity for ameliorating spectral efficiency. In this paper, power allocation in heterogeneous NOMA networks with multiple users are formulated as a Stackelberg game. The competition between the leaders and followers is considered as the energy efficiency (EE) maximization between the small base stations (SBSs) and macro base stations (MBSs). We propose an algorithm to obtain optimal power allocation in MBSs layer and SBSs layer, respectively. Then, Stackelberg iteration is used among MBSs and SBSs to reach the equilibrium point during the game. Simulation results demonstrate the effectiveness of proposed algorithms.

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

To evaluate the system-level performance of clustered unmanned aerial vehicle (UAV) networks, we apply stochastic geometry in order to establish a tractable analytical framework. The users' locations are modeled as Poisson cluster processes (PCPs) and the UAVs are assumed to hover above cluster centers at a fixed altitude. In order to enhance the generality of the analysis, two typical patterns of PCPs, namely Thomas cluster process and Matern cluster process, are analyzed. Based on this spatial framework, a unified expression for the coverage probability is derived, for both millimeter wave (mmWave) and sub-6 GHz scenarios. Theoretical and numerical results demonstrate that mmWave outperforms sub-6 GHz, and an optimal altitude of UAVs exists, which maximizes the coverage probability. This result indicates that in most cases UAVs perform better than traditional terrestrial base stations, due to their mobility.

This paper investigates the performance of energy detection-based spectrum sensing over Fisher-Snedecor F fading channels. To this end, an analytical expression for the corre- sponding average detection probability is firstly derived and then this is extended to account for collaborative spectrum sensing. The complementary receiver operating characteristics (ROC) are analyzed for different conditions of the average signal-to- noise ratio (SNR), time-bandwidth product, multipath fading, shadowing and number of collaborating users. It is shown that the energy detection performance is strongly linked to the severity of the multipath fading and amount of shadowing, whereby even small variations in either of these physical phenomena significantly impact the detection probability. Also, the versatile modeling capability of the Fisher-Snedecor F distribution is verified in the context of energy detection based spectrum sensing as it provides considerably more accurate characterization than the conventional Rayleigh fading model. To confirm the validity of the analytical results presented in this paper, we compare them with the results of some simulations.

Non-orthogonal multiple access (NOMA) and heterogeneous networks are promising candidate technologies to meet the exponential growth of mobile data. However, because the wireless network is becoming more and more dense, the energy consumption problem has become increasingly prominent and severe. This paper studies the resource allocation problem of NOMA heterogeneous small cell networks with energy harvesting. By decoupling subchannel allocation and power control, a low complexity subchannel matching algorithm is designed, and a power optimization algorithm is proposed based on Lagrange dual method. The simulation results demonstrated the convergence and effectiveness of the proposed algorithms in terms of the system energy efficiency.

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

We consider a drone-based communication network, where several drones hover above an area and serve as mobile remote radio heads for a large number of mobile users. We assume that the drones employ free space optical (FSO) links for fronthauling of the users' data to a central unit. The main focus of this paper is to quantify the geometric loss of the FSO channel arising from random fluctuation of the position and orientation of the drones. In particular, we derive upper and lower bounds, corresponding approximate expressions, and a closed-form statistical model for the geometric loss. Simulation results validate our derivations and quantify the FSO channel quality as a function of the drone's instability, i.e., the variation of its position and orientation.

Full duplex ultra-dense network (FDUDN) has been envisioned as a promising network paradigm for spectrum efficiency enhancement. This paper presents a novel power management scheme, which maximizes the total capacity of FDUDN, under given Quality-of-Service (QoS) and cross-tier interference constraints. The inter-cell power control is formulated as a non-convex optimization problem and variable substitution is used to transform it into a convex one. Furthermore, we solve this problem through a low-complexity heuristic scheme, which utilizes the water-filling theorem in inter-cell power allocation. Simulation demonstrates the enhancement effect of the proposed scheme in terms of the capacity and the power efficiency.

The explosive growth of connected devices and the increasing number of broadband users have led to an unprecedented growth in traffic demand. To this effect, the next generation wireless systems are envisioned to meet this growth and offer a potential data rate of 10 Gbps or more. In this context, an attractive solution to the current spectrum crunch issue is to exploit the visible light spectrum for the realization of high-speed commutation systems. However, this requires solutions to certain challenges relating to visible light communications (VLC), such as the stringent requirements of VLC-based intensity modulation and direct detection (IM/DD), which require signals to be real and unipolar. The present work proposes a novel power-domain multiplexing based optical asymmetric modulation (OAM) scheme for indoor VLC systems, which is particularly adapted to transmit high-order modulation signals using linear real and unipolar constellations that fit into the restrictions of IM/DD systems. It is shown that the proposed scheme provides improved system performance that outperforms alternative modulation schemes, at no extra complexity.

In-phase/quadrature-phase Imbalance (IQI) is considered a major performance-limiting impairment in direct-conversion transceivers. Its effects become even more pronounced at higher carrier frequencies such as the millimeter-wave frequency bands considered for 5G systems. In this work, we quantify the effects of IQI on the performance of different modulations under multipath fading channels. This is realized by developing a comprehensive framework for the symbol error rate (SER) analysis of coherent phase shift keying (PSK), noncoherent differential phase shift keying (DPSK) and noncoherent frequency shift keying (FSK) under IQI effects. In this context, the moment generating function of the signal-to-interference-plus-noise-ratio is first derived for single-carrier systems suffering from transmitter (TX) IQI only, receiver (RX) IQI only and joint TX/RX IQI. Capitalizing on this, we derive analytic expressions for the SER of the different modulation schemes considered. These expressions are corroborated with simulation results and they provide insights into the dependence of IQI on the system parameters. We further demonstrate that, while in some cases, IQI can cause a slight degradation of the SER performance and, hence, it can be neglected, in other cases it should be compensated in order to achieve a reliable communication link.

Novel composite fading models were recently proposed based on inverse gamma distributed shadowing conditions. These models were extensively shown to provide remarkable modeling of the simultaneous occurrence of multipath fading and shadowing phenomena in emerging wireless scenarios such as cellular, off-body and vehicle-to-vehicle communications. Furthermore, the algebraic representation of these models is rather tractable, which renders them convenient to handle both analytically and numerically. Based on this, the present contribution analyzes the ergodic capacity over the recently proposed $\kappa-\mu$ / inverse gamma composite fading channels, which were shown to characterize excellently multipath fading and shadowing in line-of-sight communication scenarios, including realistic vehicular communications. Novel analytic expressions are derived which are subsequently used in the analysis of the corresponding system performance. In this context, the offered results are compared with respective results from cases assuming conventional fading conditions, which leads to the development of numerous insights on the effect of the multipath fading and shadowing severity on the achieved capacity levels. It is expected that these results will be useful in the design of timely and demanding wireless technologies such as wearable, cellular and inter-vehicular communications.

In this paper, we investigate the joint subcarrier (SC) assignment and power allocation problem for non-orthogonal multiple access (NOMA) amplify-and- forward two-way relay wireless networks. We aim to maximize the achievable secrecy energy efficiency by jointly designing the SC assignment, user pair scheduling and power allocation. Assuming the perfect knowledge of the channel state information (CSI) at the relay station, we propose a low-complexity subcarrier assignment scheme (SCAS-1), which is equivalent to many-to-many matching games, and then SCAS-2 is formulated as a secrecy energy efficiency maximization problem. The secure power allocation problem is modeled as a convex geometric programming (GP) problem, and then solved by interior point methods. Simulation results demonstrate that the effectiveness of the proposed SSPA algorithms.

We consider a free space optical (FSO) backhauling system which consists of two base stations (BSs) and one central unit (CU). We propose to employ non-orthogonal multiple access (NOMA) for FSO backhauling where both BSs transmit at the same time and in the same frequency band to the same photodetector at the CU. We develop a dynamic NOMA scheme which determines the optimal decoding order as a function of the channel state information at the CU and the quality of service requirements of the BSs, such that the outage probabilities of both BSs are jointly minimized. Moreover, we analyze the performance of the proposed NOMA scheme in terms of the outage probability over Gamma-Gamma FSO turbulence channels. We further derive closed-form expressions for the outage probability for the high signal-to-noise ratio regime. Our simulation results confirm the analytical derivations and reveal that the proposed dynamic NOMA scheme significantly outperforms orthogonal transmission and existing NOMA schemes.

Visible light communication (VLC)-also known as light fidelity (Li-Fi)-networks will play an important role in the near future, since they will provide full coverage and improved data rates for indoor wireless applications. In this paper, the coexistence of Li-Fi and Wi-Fi networks is investigated for the multi-user scenario, under the practical assumption that both of them are served by the same backhaul network (e.g., optical fiber). More specifically, we study the resource allocation and coordination problems by maximizing the proportional fairness of all users. To do so, we formulate and solve an optimization problem for the power allocation of the hybrid Li-Fi/Wi-Fi scenario, under the constraint of the common backhaul. Computer simulation results are provided to illustrate the effectiveness of the proposed analysis.

Non-orthogonal multiple access (NOMA) has been recently proposed as a viable technology that has the potential to improve the spectral efficiency of fifth generation (5G) wireless networks and beyond. However, in practical communication scenarios, transceiver architectures inevitably suffer from radio-frequency (RF) front-end related impairments that can lead to non-negligible degradation of the overall system performance. In this context, in-phase/quadrature-phase imbalance (IQI) constitutes a major impairment in direct-conversion transceivers. Based on this, the present contribution quantifies the effects of IQI on the performance of NOMA based systems under multipath fading conditions. This is realized by first deriving novel analytic expressions for the signal-to-interference-plus-noise ratio and the outage probability of NOMA systems subject to IQI at the transmitter and/or the receiver sites. Capitalizing on these results, we demonstrate that the effects of IQI differ considerably between the different NOMA users and depending on the considered system's parameters.

The η-μ / inverse gamma and κ-μ / inverse gamma distributions were recently introduced as particularly flexible and tractable composite fading models that provide accurate characterization of multipath and shadowing effects, which are encountered simultaneously during wireless transmission in emerging communication scenarios such as off-body, cellular and vehicular-to-vehicular communications. The present contribution analyzes the symbol error rate performance of digital communications over these fading channels. To this end, we derive novel analytic expressions for the symbol error rate of multiple amplitude based modulated systems under these fading conditions, which are subsequently used in the analysis of the corresponding system performance. In this context, numerous insights are developed on the effect of different fading conditions on the corresponding error rate, which are expected to be useful in the design of timely and demanding wireless technologies such as wearable, cellular and vehicular communication systems.

The authors study the performance of an amplify‐and‐forward dual‐hop, switch‐and‐stay combining receiver, used in free space optical communications over non‐identical fading channels. One path is characterised by the generalised Málaga (or M distribution), whereas the other is influenced by the combined effects of Gamma–Gamma distributed atmospheric turbulence, pointing error and path loss. Novel closed‐form expressions for the end‐to‐end moment generating function, probability density function, and cumulative distribution function are derived in terms of Meijer's G function. Furthermore, the performance of the system is analysed, and closed‐form expressions are presented for the end‐to‐end outage probability and channel capacity.

Secure communication is a promising technology for wireless networks because it ensures secure transmission of information. In this paper, we investigate the joint subcarrier (SC) assignment and power allocation problem for non-orthogonal multiple access amplify-and-forward two-way relay wireless networks, in the presence of eavesdroppers. By exploiting cooperative jamming (CJ) to enhance the security of the communication link, we aim to maximize the achievable secrecy energy efficiency by jointly designing the SC assignment, user pair scheduling and power allocation. Assuming the perfect knowledge of the channel state information at the relay station, we propose a low-complexity subcarrier assignment scheme (SCAS-1), which is equivalent to many-to-many matching games, and then SCAS-2 is formulated as a secrecy energy efficiency maximization problem. The secure power allocation problem is modeled as a convex geometric programming problem, and then, solved by interior point methods. Simulation results demonstrate that the effectiveness of the proposed SSPA algorithms under scenarios of using and not using CJ, respectively.

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

Buffer-aided relays can improve the diversity of multi-hop networks, however, they increase packet delays. Thus, various delay-aware protocols have been developed, but without considering the transmission diversity. Moreover, most works adopt ideal assumptions, such as symmetric links, perfect channel state information (CSI), and error-free feedback channels. So, we propose a low-complexity (LoCo) link selection algorithm, herein called LoCo-Link. The proposed algorithm may experience delays during CSI updates, and hence, by using outdated CSI its performance may deteriorate. To alleviate this issue, we next propose a distributed version of LoCo-Link (d-LoCo-Link) dealing with outdated CSI. In both algorithms, the source performs broadcasting toward multiple relays; when the packets are transmitted by a relay to the destination, they are discarded from all other relays. This coordination relies on feedback channels. For non error-free feedback channels, we propose a scheme in which the relays listen to the transmission of the best relay and drop duplicate packets. Results show that LoCo-Link surpasses other algorithms, by decreasing the delay in asymmetric networks. Moreover, d-LoCo-Link avoids diversity losses due to outdated CSI, while the effect of non error-free feedback channels is mitigated by taking advantage of the inter-relay channels.

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

In this paper, we consider a point-to-point multi-input multi-output wireless-powered communication system, where the source S is powered by a dedicated power beacon (PB) with multiple antennas. Employing the time splitting protocol, the energy constrained source S first harvests energy through the radio-frequency signals sent by the PB and then uses this energy to transmit information to the destination D. Unlike several prior works, we assume that the energy transfer link is subjected to Rician fading, which is a real fading environment, due to relatively short range power transfer distance and the existence of a strong line of sight path. We present a comprehensive analysis of the achievable ergodic capacity in two scenarios, depending on the availability of channel state information (CSI) at PB, namely, the absence of CSI and partial CSI. For the former case, equal power allocation is used, while for the later one, energy beamforming is used to enhance the energy transfer efficiency. For both the cases, closed-form expressions for the upper and lower bounds of the ergodic capacity are derived. Furthermore, the optimal time split is discussed, and the capacity in the low and high signal-to-noise ratio regimes is studied through simple closed-form expressions. Numerical results and simulations are provided to validate the theoretical analysis. The results show that the Rician factor K has a significant impact on the ergodic capacity performance, and this impact strongly depends on the availability of the CSI at the PB.

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

We present the concept of Simultaneous Lightwave Information and Power Transfer (SLIPT) for indoor Internet-of-Things (IoT) applications. Specifically, we propose novel and fundamental SLIPT strategies, which can be implemented through Visible Light or Infrared communication systems, equipped with a simple solar panel-based receiver. These strategies are performed at the transmitter or at the receiver, or at both sides, named Adjusting transmission, Adjusting reception, and Coordinated adjustment of transmission and reception, correspondingly. Furthermore, we deal with the fundamental trade-off between harvested energy and quality-of-service (QoS), by maximizing the harvested energy, while achieving the required user's QoS. To this end, two optimization problems are formulated and optimally solved. Computer simulations validate the optimum solutions and reveal that the proposed strategies considerably increase the harvested energy, compared to SLIPT with fixed policies.

Visible light communication (VLC) systems are expected to provide remarkably high speed indoor communications and effective ubiquitous connectivity. However, the key limitation of such systems is the narrow modulation bandwidth of the light sources. Based on this, non-orthogonal multiple access (NOMA) has been recently proposed as an effective method that can enhance considerably the spectral efficiency of indoor downlink VLC systems. In this context, the present work is devoted to the evaluation of the bit-error-rate (BER) performance of NOMA-based VLC systems. Specifically, a novel closed-form expression is first derived for the BER of the considered set up, by also taking into account the realistically incurred cancellation errors and interference terms. The validity of the derived expressions is verified through extensive comparisons with respective results from Monte Carlo simulations, while their algebraic representation is relatively simple, which renders them convenient to handle both analytically and numerically. This leads to meaningful insights on the behavior and performance gains achieved, thanks to the adoption of NOMA, which are particularly useful in future design and deployment of VLC systems.

In this paper, we propose a cooperative approach to improve the security of both primary and secondary systems in cognitive radio multicast communications. During their access to the frequency spectrum licensed to the primary users, the secondary unlicensed users assist the primary system in fortifying security by sending a jamming noise to the eavesdroppers, while simultaneously protect themselves from eavesdropping. The main objective of this work is to maximize the secrecy rate of the secondary system, while adhering to all individual primary users' secrecy rate constraints. In the case of passive eavesdroppers and imperfect channel state information knowledge at the transceivers, the utility function of interest is nonconcave and involved constraints are nonconvex, and thus, the optimal solutions are troublesome. To address this problem, we propose an iterative algorithm to arrive at a local optimum of the considered problem. The proposed iterative algorithm is guaranteed to achieve a Karush-Kuhn-Tucker solution.

While buffer-aided relaying improves the diversity of a multi-hop network, its deployment introduces time-delays, thus rendering buffering unreliable for delay-intolerant applications. To alleviate excessive delays, various studies propose delayaware protocols, but at the expense of reduced diversity, and consequently, increased outage probability. Attempts to maintain the diversity of the system while trying to reduce delays, however, may lead to even higher delays, especially in asymmetric topologies. In this work, we propose a Low-Complexity (LoCo) link selection algorithm, herein called LoCo - Link, that aims at reducing packet delays and enhancing the performance of practical asymmetric two-hop networks. The complexity of LoCo - Link is derived and compared with other state-of-the-art relay selection policies. The performance of the proposed algorithm is evaluated in terms of outage probability, average throughput and average delay, focusing on scenarios with asymmetric links.

Coherent detection requires exact knowledge of the channel state information, which is often a challenging task in demanding practical applications. Based on this, non-coherent detection of differentially modulated signals can be considered as an alternative method. The present paper investigates the effects of in-phase/quadrature-phase imbalance (IQI), which are known to degrade the performance of wireless communication systems. Specifically, we evaluate the effects of IQI on the bit error rate (BER) performance of differential quadrature phase shift keying (dQPSK) for ideal receiver (RX) with transmitter (TX) IQI, ideal TX with RX IQI and joint TX/RX IQI. Explicit analytic expressions are derived for the BER of both single-carrier and multi-carrier systems suffering from IQI at the TX and/or RX. Extensive Monte-Carlo simulation as well as offered analytic results show that realistic TX/RX IQI values can degrade the corresponding BER by over 30%. Likewise, it is shown that the detrimental effects of IQI are more considerable on DQPSK than on QPSK.

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

Welcome to the third one in the sequel of three IEEE JSAC special issues on Spectrum Sharing and Aggregation for Future Wireless Networks. In recognition of the fact that a substantial number of submissions have been received in response to the call for papers, the decision has been made to publish three issues on the cutting-edge advances in spectrum sharing and aggregation. The first two issues were published in October 2016 with 20 papers and November 2016 with 19 papers, respectively. This is the third issue with 17 papers, covering a feast of hot research topics as follows.

Millimeter wave (mmWave) communications have recently attracted large research interest, since the huge available bandwidth can potentially lead to the rates of multiple gigabit per second per user. Though mmWave can be readily used in stationary scenarios, such as indoor hotspots or backhaul, it is challenging to use mmWave in mobile networks, where the transmitting/receiving nodes may be moving, channels may have a complicated structure, and the coordination among multiple nodes is difficult. To fully exploit the high potential rates of mmWave in mobile networks, lots of technical problems must be addressed. This paper presents a comprehensive survey of mmWave communications for future mobile networks (5G and beyond). We first summarize the recent channel measurement campaigns and modeling results. Then, we discuss in detail recent progresses in multiple input multiple output transceiver design for mmWave communications. After that, we provide an overview of the solution for multiple access and backhauling, followed by the analysis of coverage and connectivity. Finally, the progresses in the standardization and deployment of mmWave for mobile networks are discussed.

For the potential of providing rates of multiple Giga-bps in a single channel, millimeter wave (mmWave) communications have recently attracted substantial research interest. While mmWave technology is already being used in stationary scenarios such as indoor hotspots or backhaul, it is challenging to use mmWave frequencies in mobile networks, where transmitting/receiving nodes may be moving, channels may have a complicated structure, and the coordination among multiple nodes is difficult. To fully exploit the high potential rates of mmWave in mobile networks, many significant technical challenges must be tackled. The main objective of this IEEE JSAC Special Issue on “Millimeter wave communications for future mobile networks” is to collect the most recent technical advances in mmWave for future mobile networks. The response from the community to the call has been overwhelming. We received 96 submissions with a call period short than 4 months. Many of the submissions are from the most well known research groups in the field. After a strict review process, we decided to accept 38 papers, which will be published in two issues. The papers were selected based on the technical relevance and merits. Unfortunately, due to space limitations, a number of interesting papers were not selected, despite the merits that they had. We sincerely hope those papers can find other publishing venues.

Millimeter wave (mmWave) wireless networks can operate in single-cell point-to-multipoint mode to provide local multicast services efficiently. In this paper, the performance of multicast mmWave wireless networks is studied, through stochastic geometry. Then, the use of power domain non-orthogonal multiple access (NOMA) for enhancing mmWave multicasting is also investigated. Furthermore, we study multicasting in two-tier mmWave heterogeneous networks, and propose a novel cooperative NOMA multicast scheme. Analytical expressions for the signal-to-interference-plus-noise ratio coverage probability, the average number of served users, and the sum multicast rate are derived, in order to assess the performance of these schemes. Finally, we discuss the maximum sum multicast rates, by formulating them as optimization problems, and also develop efficient golden section search algorithms to solve them. The offered solutions reveal the impact of data transmission rate and power allocation on the sum multicast rate. Both analytical and numerical results demonstrate that NOMA can significantly improve the mmWave multicasting, while the proposed cooperative NOMA mmWave multicast scheme can further improve the NOMA mmWave multicasting.

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

We investigate the error performance of multidimensional constellations in the multiple access and broadcast channels. More specifically, we provide closed-form expressions for the pairwise error probability (PEP) of the joint maximum likelihood detection, for multiuser signaling in the presence of additive white Gaussian noise and Rayleigh fading. Arbitrary numbers of users and multidimensional signal sets are assumed, while the provided formula for the PEP is a function of the dimension-wise distances of the multidimensional constellation. Furthermore, a useful upper bound on the average symbol error probability is also obtained through the union bound. The analysis is applied to the sparse code multiple access systems. The analytical results are validated successfully through simulations, and show their importance in the multidimensional constellation design.

We propose techniques for optimizing transmit beamforming in a full-duplex multiple-input-multiple-output wireless-powered communication system, which consists of two phases. In the first phase, the wireless-powered mobile station (MS) harvests energy using signals from the base station (BS), whereas in the second phase, both MS and BS communicate to each other in a full-duplex mode. When complete instantaneous channel state information (CSI) is available, the BS beamformer and the time-splitting (TS) parameter of energy harvesting are jointly optimized in order to obtain the BS-MS rate region. The joint optimization problem is non-convex, however, a computationally efficient optimum technique, based upon semidefinite relaxation and line-search, is proposed to solve the problem. A sub-optimum zero-forcing approach is also proposed, in which a closed-form solution of TS parameter is obtained. When only the second-order statistics of transmit CSI is available, we propose to maximize the ergodic information rate at the MS while maintaining the outage probability at the BS below a certain threshold. An upper bound for the outage probability is also derived and an approximate convex optimization framework is proposed for efficiently solving the underlying non-convex problem. Simulations demonstrate the advantages of the proposed methods over the sub-optimum and half-duplex ones.

This paper quantifies the impact of correlated fading on secure communication of multiple amplify-and-forward (AF) relaying networks. In such a network, the base station (BS) is equipped with multiple antennas and communicates with the destination through multiple AF relays, while the message from the relays can be overheard by an eavesdropper. We focus on the practical communication scenario, where the main and eavesdropper's channels are correlated. In order to enhance the transmission security, transmit antenna selection is performed at the BS, and the best relay is chosen according to the full- or partial-relay selection criterion, which relies on the dual-hop relay channels or the second-hop relay channels, respectively. For these criteria, we study the impact of correlated fading on the network secrecy performance, by deriving an analytical approximation for the secrecy outage probability and an asymptotic expression for the high main-to-eavesdropper ratio. From these results, it is concluded that the channel correlation is always beneficial to the secrecy performance of full relay selection. However, it deteriorates the secrecy performance if partial-relay selection is used, when the number of antennas at the BS is less than the number of relays.

Visible light communication (VLC) has been proposed as a promising and efficient solution to indoor ubiquitous broadband connectivity. In this paper, non-orthogonal multiple access, which has been recently introduced as an effective scheme for fifth generation (5G) wireless networks, is considered in the context of VLC systems under different channel uncertainty models. To this end, we first derive a novel closed-form expression for the bit-error-rate (BER) under perfect channel state information (CSI). Capitalizing on this, we then quantify the effect of noisy and outdated CSI by deriving a simple and accurate approximation for the former and a tight upper bound for the latter. The offered results are corroborated by respective results from extensive Monte Carlo simulations and assist in developing useful insights on the effect of imperfect CSI knowledge on the overall system performance. Furthermore, it was shown that while noisy CSI leads to slight degradation in the BER performance, outdated CSI can cause considerable performance degradation, if the order of the users' channel gains change due to the involved mobility.

This paper studies the error performance of free-space optical (FSO) systems, employing subcarrier intensity modulation (SIM) with M-ary differential phase-shift keying (MDPSK). Novel analytical expressions for the symbol error probability are derived, based on the Fourier series approach. The irradiance fluctuations of the received optical signal are modeled by considering both Gamma-Gamma atmospheric turbulence and pointing errors. In addition, hardware imperfections of DPSK demodulator, as the phase noise of local oscillator at the receiver, are considered. It is illustrated that the phase noise significantly degrades the system performance, especially when the optical signal transmission is impaired by weak atmospheric turbulence and weak pointing errors effect. Furthermore, the phase noise results in an unrecoverable error-rate floor, which is an important limiting factor for SIM-DPSK FSO systems.

This paper is devoted to the end-to-end performance analysis, optimal power allocation (OPA), and energy-efficiency (EE) optimization of decode-and-forward (DF)-based full-duplex relaying (FDR) and half-duplex relaying (HDR) systems. Unlike existing analyses and works that assume simplified transmission over symmetric fading channels, we consider the more realistic case of asymmetric multipath fading and shadowing conditions. To this end, exact and asymptotic analytic expressions are first derived for the end-to-end outage probabilities (OPs) of the considered DF-FDR set ups. Based on these expressions, we then formulate the OPA and EE optimization problems under given end-to-end target OP and maximum total transmit power constraints. It is shown that OP in FDR systems is highly dependent upon the different fading parameters and that OPA provides substantial performance gains, particularly, when the relay self-interference (SI) level is strong. Finally, the FDR is shown to be more energy-efficient than its HDR counterpart, as energy savings beyond 50% are feasible even for moderate values of the SI levels, especially at larger link distances, under given total transmit power constraints and OP requirements.

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

Efficient demand side management through dynamic power pricing is an important application in the smart grids. However, in the absence of a detailed user consumption model, it is difficult to set an optimal power price. In this paper, we propose to efficiently capture the user consumption behavior through a user-dependent acceptance price. Each rational user will decide its own acceptance price based on its desire to get served. Then, we model the selfish interaction between operator and users as a Stackelberg game, where the operator aims to maximize its profit, while the individual users try to pay the lowest price and be served in time. After each user selfishly declares its own acceptance price, the operator sets an optimal power price, based on the user feedback and taking into account the random output of the renewable power sources. Simulation results confirm that the operator can maximize its profit and the users get served in time, while the proposed scheme leads to the optimal usage of the renewable power production.

In this paper, we investigate the secrecy performance of dual-hop amplify-and-forward (AF) multi-antenna relaying systems over Rayleigh fading channels by taking into account the direct link between the source and destination. To improve the secrecy performance, two linear processing schemes at relay and maximal ratio combining (MRC) at destination are proposed, namely, Zero-forcing/MRC (ZF/MRC) and Maximal ratio transmission/MRC (MRT/MRC). For these schemes, we present new tight analytical expressions of the secrecy outage probability. In addition, we examine the performance in high signal-to-noise ratio (SNR) regimes, and present simple secrecy outage approximations for all schemes. The results reveal that: 1) The MRT/MRC scheme achieves a full diversity order of M+1, while the ZF/MRC scheme achieves a diversity order ofM, where M is the number of antennas at relay. 2) The ZF/MRC scheme outperforms the MRT/MRC scheme in the low SNR regime, while becomes inferior to the MRT/MRC scheme in the high SNR regime.

In this paper, we analyze the secrecy performance of multi-antenna cognitive wiretap network, where the secondary transmitter (Alice) communicates with the secondary receiver (Bob) in the presence of an eavesdropper (Eve). Specifically, we investigate the cases of maximal-ratio combining (MRC) with half-duplex (HD) and selection combining/Zero forcing beamforming (SC/ZFB) scheme with full-duplex (FD) operation, respectively. Assuming the Rayleigh fading, closed-form expressions for the secrecy outage probability of cognitive wiretap channels with MRC and SC/ZFB are derived. Furthermore, we provide simple asymptotic approximations for the secrecy outage probability and find that both schemes achieve full diversity. In addition, simulation results reveal that MRC outperforms SC/ZBF in the low interference threshold regime, while the opposite holds in the high interference threshold regime.

Direct-conversion radio transceivers can offer reprogrammable and low-cost hardware solutions for full-duplex (FD) cognitive radio (CR) devices. However, they are susceptible to radio frequency (RF) impairments, such as in-phase (I) and quadrature (Q) imbalance (IQI), which can significantly constrain the spectrum sensing capabilities. This paper is devoted to quantify and evaluate the effects of IQI in the context of spectrum sensing in FD CR systems, in which self-interference suppression (SIS) techniques are employed. Specifically, closed form expressions are derived for the false alarm and detection probabilities, under three different scenarios: imperfect SIS with joint transmitter (TX) and receiver (RX) IQI, imperfect SIS and ideal TX/RX RF front-end, and perfect SIS and ideal TX/RX RF front-end. The derived analytical results are validated through extensive simulations, which reveal that IQI has a detrimental impact on the spectrum sensing performance of the FD CR transceiver, which brings significant losses in the spectrum utilization.

In this paper, we investigate joint relay selection and optimal power allocation, as a means to maximize the achievable rate of an underlay cooperative cognitive radio with carrier aggregation, taking into account the availability of multiple carrier components in two different bands and primary users (PUs) with specific average outage probability requirements. For the acquisition of the interference thresholds, which are set by the PUs on the secondary user (SU), we incorporate a minimum feedback strategy into the problem formulation, based on the minimization of the PUs outage probabilities. The resulting non-convex optimization problem is transformed into a convex one and optimally solved using dual decomposition and an efficient iterative method with closed-form power policies. Simulation results illustrate that the proposed configuration exploits the available degrees of freedom in an efficient way which maximizes the SU throughput while the average outage probability of the PUs is kept at acceptable levels.

We present a new multiple input multiple output (MIMO) technique, based on Walsh Hadamard Transform (WHT) precoding, to improve the robustness of space-frequency block coded orthogonal frequency division multiplexing (SFBC-OFDM) systems. The WHT is applied to the data symbols prior the Alamouti encoder at the transmitter and to the output of the Alamouti decoder at the receiver. The computational complexity of the proposed system is evaluated in terms of complex additions and multiplications where the numerical results show that the proposed system has a lower complexity as compared to other precoded OFDM systems. Moreover, the proposed system is highly robust to the channel time and frequency selectivity as compared to conventional SFBC, space time block coded (STBC) and other precoded OFDM systems.

The authors study the design of cooperative beamforming for an underlay cognitive relay network over frequency selective fading channels. The network under consideration consists of one primary link, one secondary link and relay nodes that assist the communication. It is assumed imperfect blind channel estimation, i.e. only the second order statistics – with uncertainty – of the channel gain between the primary transmitter‐relay and relay‐primary receiver, is available. To mitigate the channel's frequency selectivity, each relay is equipped with a finite impulse response filter, which performs filter and forward relaying. The authors consider two different scenarios: in the first, the objective is to minimise the total transmit power of the relays subject to a constraint on the interference induce on the primary receiver. Furthermore, a constraint is also considered on the received signal‐to‐interference plus noise ratio (SINR) in the secondary receiver. In the second scenario, the objective is to maximise SINR in the secondary receiver, subject to constraints on the sum power of the relays and also on the noise and interference power in the primary receiver. Simulation results show how total power of relay varies with the uncertainty in the blind channel estimation in the first scenario. In addition, the achievable SINR deteriorates in the second scenario when the uncertainty increases.

Welcome to the IEEE JSAC special issue on Spectrum Sharing and Aggregation for Future Wireless Networks. The conception of this special issue is motivated by the following observations: the ever-increasing penetration of both the mobile Internet and of the Internet-of-things is gradually clogging up the most valuable spectral bands available in the sub-2 GHz frequency range for future wireless networks. Hence there is an urgent need for improved spectrum exploitation to satisfy this demand. It is expected that the wireless tele-traffic will continue to grow quite dramatically in the ensuing years, hence further widening the spectrum-supply versus demand gap. In order to mitigate this gap, spectrum sharing and aggregation have been well recognized as promising approaches, which led to rapid advances by harnessing a large cross-section of the research community. Nonetheless, there are numerous unsolved technical challenges. This special issue aims for reporting on some of these cutting-edge advances in spectrum sharing and aggregation, whilst opening new avenues of research in this area.

The papers in this special issue represent the second one in the sequel of three special issues on spectrum sharing and aggregation for future wirelessn networks.

A direct-conversion architecture can offer highly integrated low-cost hardware solutions to communication transceivers. However, it has been demonstrated that radio frequency impairments, such as amplifier nonlinearities, phase noise, and in-phase/quadrature-phase imbalances (IQI), can lead to a severe degradation in the performance and fairness. To this end, we study the power allocation (PA) problem in an orthogonal frequency-division multiple access system, when the served user equipment (UE) suffers from different levels of IQI. Additionally, we present a novel low-complexity solution with directly calculated PA policies, given the Lagrange multiplier, which mitigates the impact of IQI and achieves fairness in terms of capacity for the served UE, by maximizing the minimum achievable capacity of the UE. The effectiveness of the offered solution is validated through simulation results, which reveal that it can drastically increase the minimum achievable UE's capacity.

In this letter, we consider wireless powered communication networks which could operate perpetually, as the base station (BS) broadcasts energy to the multiple energy harvesting (EH) information transmitters. These employ “harvest then transmit” mechanism, as they spend all of their energy harvested during the previous BS energy broadcast to transmit the information towards the BS. Assuming time division multiple access (TDMA), we propose a novel transmission scheme for jointly optimal allocation of the BS broadcasting power and time sharing among the wireless nodes, which maximizes the overall network throughput, under the constraint of average transmit power and maximum transmit power at the BS. The proposed scheme significantly outperforms “state of the art” schemes that employ only the optimal time allocation. If a single EH transmitter is considered, we generalize the optimal solutions for the case of fixed circuit power consumption, which refers to a much more practical scenario.

The present work quantifies the effects of asymmetric fading conditions on differentially modulated amplify-and-forward relaying systems. To this end, novel bit error rate expressions are derived for the case that the source-relay and relay-destination links experience non-line-of-sight multipath fading whilst the source-destination link is subject to: multipath fading, shadowing, and composite fading. Simple and tight approximate and asymptotic expressions are also derived, leading to useful insights into the system design. It is shown that the incurred performance variations range from one to few orders of magnitude compared to the standard case of symmetric Rayleigh scenarios, which verifies the importance to account for fading conditions realistically. In addition, differential phase-shift keying is shown to provide adequate performance in severe fading conditions in the moderate and high-signal-to-noise ratio regimes.

Direct-conversion radio (DCR) receivers can offer highly integrated low-cost hardware solutions for spectrum sensing in cognitive radio (CR) systems. However, the DCR receivers are susceptible to radio frequency (RF) impairments, such as in-phase and quadrature-phase imbalance, low-noise amplifier nonlinearities, and phase noise, which limit the spectrum sensing capabilities. In this paper, we investigate the joint effects of RF impairments on energy detection-based spectrum sensing for CR systems in multi-channel environments. In particular, we provide the novel closed-form expressions for the evaluation of the detection and false alarm probabilities, assuming Rayleigh fading. Furthermore, we extend the analysis to the case of CR networks with cooperative sensing, where the secondary users suffer from different levels of RF imperfections, considering both scenarios of error free and imperfect reporting channel. Numerical and simulation results demonstrate the accuracy of the analysis as well as the detrimental effects of RF imperfections on the spectrum sensing performance, which bring significant losses in the spectrum utilization.

In this paper, we study a two-phase underlay cognitive relay network, where there exists an eavesdropper who can overhear the message. The secure data transmission from the secondary source to secondary destination is assisted by two decode-and-forward (DF) relays. Although the traditional opportunistic relaying technique can choose one relay to provide the best secure performance, it needs to continuously have the channel state information (CSI) of both relays, and may result in a high relay switching rate. To overcome these limitations, a secure switch-and-stay combining (SSSC) protocol is proposed where only one out of the two relays is activated to assist the secure data transmission, and the secure relay switching occurs when the relay cannot support the secure communication any longer. This security switching is assisted by either instantaneous or statistical eavesdropping CSI. For these two cases, we study the system secure performance of SSSC protocol, by deriving the analytical secrecy outage probability as well as an asymptotic expression for the high main-to-eavesdropper ratio (MER) region. We show that SSSC can substantially reduce the system complexity while achieving or approaching the full diversity order of opportunistic relaying in the presence of the instantaneous or statistical eavesdropping CSI.

Cooperative communication has been shown to provide significant increase of transmission reliability and network capacity while expanding coverage in cellular networks. The present work is devoted to the investigation of the end-to-end performance and power allocation of a maximum-ratio-combining based regenerative multi-relay cooperative network over non-homogeneous scattering environment, which is the realistic case in many practical wireless communication scenarios. Novel analytic expressions are derived for the end-to-end symbol-error-rate of both M-ary phase-shift keying and M-ary quadrature amplitude modulation over independent and non-identically distributed generalized fading channels are given by exact analytic expressions that involve the Lauricella function and can be readily evaluated with the aid of a proposed computing algorithm. Simple analytic expressions are also derived for the corresponding symbol-error-rate at asymptotically high signal-to-noise ratios. The derived expressions are corroborated with respective results from computer simulations and are subsequently employed in formulating a sum-power optimization problem that enhances the system performance under total sum-power constraint within the multi-relay cooperative system. It is also shown that asymptotically optimum power allocation provides substantial performance gains over the corresponding equal power allocation, particularly, when the source-relay and relay-destination paths are highly unbalanced.

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

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

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

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

In several wireless communication systems, low complexity channel selection schemes are required, as power efficient mechanisms to improve performance. In this context, the best selection scheme, in terms of performance, comes at the cost of increased complexity, since it necessitates a continuous monitoring of all available channels. In this paper, a new threshold-based channel selection strategy is proposed, which decreases the system complexity, without considerably affecting the system performance. Assuming independent but nonidentically distributed channel conditions, a generic analytical framework is first presented, based on the Markov chain theory. Then, the proposed selection scheme is applied to three specific communication scenarios, namely multichannel reception, transmit antenna selection with diversity reception, and cooperative relay selection. In all three cases, closed-form results are obtained and used to analyze the performance of the systems under consideration. It is shown that based on the proposed scheme, computational complexity is reduced and thus important energy savings can be achieved, without a significant loss in performance.

In this paper, we present a novel low-complexity technique, which improves the performance of single-antenna multi-carrier communication systems, suffering from in-phase and quadrature (I/Q)-imbalance (IQI) at the receiver. We refer to the proposed scheme as I/Q-imbalance self-interference coordination (IQSC). This technique not only mitigates the detrimental effects of IQI, but, through appropriate signal processing, also coordinates the self-interference terms produced by IQI in order to achieve second-order frequency diversity. However, these benefits come at the expense of a reduction in transmission rate. More specifically, IQSC is a simple transmit diversity scheme that improves the signal quality at the receiver by elementary signal processing operations across symmetric (mirror) pairs of subcarriers. Thereby, the proposed transmission protocol has a similar complexity as Alamouti's space-time block coding scheme and does not require extra transmit power nor any feedback. To evaluate the performance of IQSC, we derive closed-form expressions for the resulting outage probability and symbol-error rate. Interestingly, IQSC outperforms not only existing IQI compensation schemes but also the ideal system without IQI for the same spectral efficiency and practical target error rates, while it achieves almost the same performance as ideal (i.e., IQI-free) equal-rate repetition coding. Our findings reveal that IQSC is a promising low-complexity technique for significantly increasing the reliability of low-cost devices that suffer from high levels of IQI.

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

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

We investigate the secrecy performance of dual-hop amplify-and-forward multi-antenna relaying systems over Rayleigh fading channels, considering the direct link between the source and the destination. In order to exploit the available direct link and the multiple antennas for secrecy improvement, different linear processing schemes at the relay and different diversity combining techniques at the destination are proposed, namely: 1) zero-forcing/maximal ratio combining (ZF/MRC); 2) ZF/selection combining (ZF/SC); 3) maximal ratio transmission/MRC (MRT/MRC); and 4) MRT/SC. For all these schemes, we present new closed-form approximations for the secrecy outage probability. Moreover, we investigate a benchmark scheme, i.e., cooperative jamming/ZF (CJ/ZF), where the secrecy outage probability is obtained in exact closed-form. In addition, we present asymptotic secrecy outage expressions for all the proposed schemes in the high signal-to-noise ratio (SNR) regime, in order to characterize key design parameters, such as secrecy diversity order and secrecy array gain. The outcomes of this paper can be summarized as follows: 1) MRT/MRC and MRT/SC achieve a full diversity order of M + 1, ZF/MRC and ZF/SC achieve a diversity order of M, while CJ/ZF only achieves unit diversity order, where M is the number of antennas at the relay; 2) ZF/MRC (ZF/SC) outperforms the corresponding MRT/MRC(MRT/SC) in the low SNR regime, while becomes inferior to the corresponding MRT/MRC (MRT/SC) in the high SNR; and 3) all the proposed schemes tend to outperform the CJ/ZF with moderate number of antennas, and linear processing schemes with MRC attain better performance than those with SC.

This paper proposes a novel power beacon-assisted wiretap channel, where an energy constrained source, powered by a dedicated power beacon, aims to establish secure communications with a legitimate user in the presence of an eavesdropper. The power beacon and the source are assumed to have multiple antennas, while the legitimate user and the eavesdropper are equipped with a single antenna each. Considering a time-switching protocol, the power beacon first charges the source through wireless power transfer, and then acts as a friendly jammer to assist the source for secure communication. Depending on the available channel state information (CSI) at the power beacon, we propose several different jamming schemes for secrecy performance enhancement. Closed-form expressions are derived for the achievable secrecy outage probability of the proposed schemes. In addition, simple and accurate approximations are obtained at the high signal-to-noise ratio regime. The outcomes suggest that jamming is an effective approach to improve the secrecy performance: with full CSI available at the power beacon, employing simple zero-forcing scheme attains significant secrecy diversity gain and without the CSI of the eavesdropper link, jamming provides only some array gain. Moreover, we show that the proposed limited feedback-based random beamforming is an effective approach, which may outperform the antenna selection scheme. Furthermore, numerical results reveal that there exists a unique time switching ratio that maximizes the effective secrecy throughput.

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

Opportunistic relaying scheme (ORS), where the best relay is selected for dual-hop communication, has been widely considered as the global optimum relaying technique. However, due to the requirement of acquiring the full channel state information (CSI) of all links, ORS has increased the system's complexity and might be harmful to the network stability, especially for the large-scale networks. In this paper, we therefore proposed an alternative scheme, namely, secure switch-and-stay combining (SSSC) protocol for providing the best secure performance. In particular, a two-phase underlay cognitive relay network, where one out of two decode-and-forward (DF) is activated to assist the secure data transmission. The secure relay switching occurs when the relay cannot support the secure communication any longer. We study the system secure performance of SSSC protocol by deriving an analytical secrecy outage probability as well as an asymptotic expression in the high main-to-eavesdropper ratio (MER) region. It is shown that SSSC can substantially reduce the switching rate with lower channel estimation complexity, and approach the full diversity meanwhile.

This work is devoted to the outage probability analysis of full-duplex (FD) regenerative relay systems over multipath fading channels. Unlike the majority of analyses that assume basic symmetric fading conditions, the present work considers asymmetric generalized fading conditions, which are more realistic in practical communications scenarios. To this end, we assume that the source-relay path is subject to κ - μ multipath fading conditions, that can also account for line-of-sight communications, whereas the source-to-destination and relay-to-destination paths are subject to η-μ fading conditions that typically hold for non-line-of-sight communications. Novel analytic expressions are derived for the outage probability (OP) of the considered FD as well as for the corresponding half-duplex (HD) relay case for comparisons. These expressions are given in closed-form and have a tractable algebraic representation which renders them convenient to handle both analytically and numerically. Based on this, they are subsequently employed in analyzing the corresponding performance for different communication scenarios. It is shown that the OP of the FD relay system is highly dependent upon the severity of fading and that its performance outperforms significantly the spectral efficiency increases.

This paper investigates the impact of the multiple antenna and co-channel interference (CCI) on the outage performance of a dual-hop amplify-and-forward energy harvesting relaying network. The energy constrained relay is powered by radio frequency signals and employs the power splitting receiver architecture. To exploit the benefit of multiple antennas, two different linear processing schemes are investigated, namely, Maximum ratio combining/maximal ratio transmission (MRC/ MRT) and Minimum mean-square error/MRT (MMSE/MRT). For both schemes, a new closed-form outage lower bound and a simple high signal-to-noise ratio outage approximation are derived, respectively. Also, the achievable diversity order is quantified. In addition, we study the optimal power splitting ratio which minimizes the outage probability. Our results show that, by increasing the energy harvesting capability, the implementation of multiple antennas significantly improves the systems performance. Moreover, CCI could be potentially exploited to boost the performance, while how much performance gain can be obtained depends on the choice of the linear processing scheme.

Radio frequency (RF) front-ends constitute a fundamental part of both conventional and emerging wireless communication systems. However, in spite of their importance they are often assumed ideal, although they are practically subject to certain detrimental impairments, such as amplifier nonlinearities, phase noise and in phase and quadrature (I/Q) imbalance (IQI). The present work is devoted to the quantification and evaluation of the RF IQI effects in the context of realistic wireless vehicle-to-vehicle (V2V) communications over double-Nakagami-m fading channels. Novel closed form expressions are derived for the corresponding outage probability for the case of ideal transmitter (TX) and receiver (RX), ideal TX and I/Q imbalanced RX, I/Q imbalanced TX and ideal RX, and joint I/Q imbalanced TX/RX. The offered analytic results have a relatively convenient algebraic representation and their validity is extensively justified through comparisons with respective results from computer simulations. Based on these, it is shown that cascaded fading results to considerable degradations in the system performance and that assuming ideal RF front-ends at the TX and RX induces non-negligible errors in the outage probability evaluation that can exceed 20% in several V2V communication scenarios.

This work is devoted to the error rate and energy-efficiency analysis of regenerative cooperative networks in the presence of multipath fading and spatial correlation. To this end, exact analytic expressions are firstly derived for the symbol-error-rate of M-ary quadrature amplitude modulation in a dual-hop decode-and-forward relay system under spatially correlated Nakagami-m fading channels and maximum ratio combining at the destination. The derived expressions are subsequently employed in quantifying the energy consumption of the considered system, incorporating both transmit energy and the energy consumed by the transceiver circuits. The overall energy consumption is also minimized for certain quality-of-service requirements and it is shown that depending on the degree of spatial correlation, severity of fading, transmission distance, and relay location, a substantial overall energy reduction is sought when compared to conventional direct transmission.

The present work is devoted to the analytic performance evaluation of cooperative spectrum sensing (CSS) over generalized fading channels. The proposed analysis is based on the efficient Gaussian-Finite-Mixture (GFM) that allows the derivation of a simple and accurate closed-form expression for the average probability of energy detection (ED) under different fading environments. Capitalizing on this, we derive generalized closed-form expressions for the global probabilities of detection for the CSS with two main hard centralized fusion rules, namely, the AND and the OR rules. The efficiency and usefulness of the proposed expressions is justified by comparing the corresponding complementary receiver operating characteristic (ROC) curves for both multipath and composite multipath/shadowing fading channels, which are otherwise particularly difficult to obtain. The offered analytic results are corroborated by respective results from computer simulations and it is shown that the corresponding performance depends significantly on both the severity of fading and the involved number of users in the collaborative network.

Statistical distributions have been extensively used in modeling fading effects in conventional and modern wireless communications. In the present work, we propose a novel κ - μ composite shadowed fading model, which is based on the valid assumption that the mean signal power follows the inverse gamma distribution instead of the lognormal or commonly used gamma distributions. This distribution has a simple relationship with the gamma distribution, but most importantly, its semi heavy-tailed characteristics constitute it suitable for applications relating to modeling of shadowed fading. Furthermore, the derived probability density function of the κ - μ / inverse gamma composite distribution admits a rather simple algebraic representation that renders it convenient to handle both analytically and numerically. The validity and utility of this fading model are demonstrated by means of modeling the fading effects encountered in body centric communications channels, which have been known to be susceptible to the shadowing effect. To this end, extensive comparisons are provided between theoretical and respective real-time measurement results. It is shown that these comparisons exhibit accurate fitting of the new model for various measurement set ups that correspond to realistic communication scenarios.

In this paper we propose a new composite fading model which assumes that the mean signal power of an η — μ signal envelope follows an inverse gamma distribution. The inverse gamma distribution has a simple relationship with the gamma distribution and can be used to model shadowed fading due to its semi heavy-tailed characteristics. To demonstrate the utility of the new η — μ / inverse gamma composite fading model, we investigate the characteristics of the shadowed fading behavior observed in body centric communications channels which are known to be susceptible to shadowing effects, particularly generated by the human body. It is shown that the η — μ / inverse gamma composite fading model provided an excellent fit to the measurement data. Moreover, using Kullback-Leibler divergence, the η — μ / inverse gamma composite fading model was found to provide a better fit to the measured data than the k — μ / inverse gamma composite fading model, for the communication scenarios considered here.

The analysis of composite fading channels, which are typically encountered in wireless channels due to multipath and shadowing is quite involved, as the underlying fading distributions do not lend themselves to analysis. An example of such channels are the Nakagami/Rayleigh-Lognormal fading channels. Several simplified expressions have been proposed in the literature. In this paper, a generalized fading model for composite and non-composite fading models, based on the so-called Mixture of Gaussians (MoG) distribution, is proposed. The well-known expectation-maximization algorithm is utilized to estimate the parameters of the MoG model. Furthermore, relying on the proposed MoG model, we derive closed form expressions for several performance metrics used in wireless communication systems, including the raw moments, the amount of fading, the outage probability, the average channel capacity, and the moment generating function. In addition, the symbol error rate of L-branch maximum ratio combining diversity receiver is studied for linear coherent signaling schemes. Monte Carlo simulations are presented to corroborate the analytical results and to assess the accuracy of the MoG model.

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

The present paper is devoted to the evaluation of energy detection based spectrum sensing over different multipath fading and shadowing conditions. This is realized by means of a unified and versatile approach that is based on the particularly flexible mixture gamma distribution. To this end, novel analytic expressions are firstly derived for the probability of detection over MG fading channels for the conventional single-channel communication scenario. These expressions are subsequently employed in deriving closed-form expressions for the case of square-law combining and square-law selection diversity methods. The validity of the offered expressions is verified through comparisons with results from respective computer simulations. Furthermore, they are employed in analyzing the performance of energy detection over multipath fading, shadowing and composite fading conditions, which provides useful insighs on the performance and design of future cognitive radio based communication systems.

This paper is devoted to the analytic investigation of a maximum-ratio-combining based regenerative multi-relay cooperative wireless network over non-homogeneous scattering environments. Such propagation conditions are rather realistic as they are encountered often in practical wireless transmission scenarios. Novel analytic expressions are derived for the symbol-error-rate of M-ary phase shift keying (M-PSK) over independently and non-identically distributed fading channels. The derived expressions are based on the moment-generating-function (MGF) approach and are given in closed-form in terms of the generalized Lauricella series. A simple algorithm for computing this special function is also proposed while the offered results are validated extensively through comparisons with respective results from computer simulations. Based on this, they are particularly useful in the analytic performance evaluation of such cooperative systems. To this end, it is shown that the performance of the cooperative system is significantly affected, as expected, by the number of employed relays as well as by the value of the involved fading parameters η and μ.

The present paper analyzes the outage probability of full-duplex (FD) regenerative relay systems over multipath fading channels. Unlike the majority of investigations that assume basic symmetric fading conditions, this analysis considers asymmetric generalized fading conditions, which are more realistic as they are encountered more often in practical wireless transmissions. To this end, it is assumed that the source-relay and source-destination links are subject to k -μ multipath fading conditions, which can represent generalized line-of-sight communication scenarios; on the contrary, the relay-to-destination link is subject to η-μ fading conditions that typically represent generalized non-line-of-sight communication scenarios. Novel analytic expressions are derived for the outage probability (OP) of the considered FD relaying system. These expressions are given in closed-form and have a relatively tractable algebraic form which renders them convenient to handle both analytically and numerically. To this effect, they are subsequently employed in analyzing the corresponding performance for various communication scenarios. It is shown that the OP of the FD relay system is, as expected, highly dependent upon the severity of fading, the relay self-interference and the interference from the direct link. Furthermore, it is shown that at relatively high average signal-to-noise ratio values, the outage probability at low fading severity and at high relay self interference outperforms the respective performance for the case of high fading severity, but with low relay self-interference. Based on this, the offered results can be useful in the design and deployment of future full-duplex based cooperative communication systems.

The aim of this paper is to develop link layer transmission schemes for hybrid optical wireless (OW)/radio frequency (RF) systems, with constraints on both per-link and total average power consumption at the transmitter. In this context, we adopt a timeslot structure with a queue for storing the data packets for transmission and model the hybrid channel as an erasure channel with parameters varying along the time-slots according to a Markov chain. Then, a stochastic optimization problem is formulated, where intelligent decisions regarding the number of the packets admitted in the queue and the power levels used in every link, are taken by the hybrid transmitter in each slot. The objective of this formulation is to design a control policy that maximizes the transmitter throughput, while satisfying the power constraints as well. A solution is offered by using the Lyapunov optimization framework and an on-line transmission algorithm is developed. The proposed transmission algorithm takes decisions based only on the status of the queue and the statistical parameters of the OW/RF channel in each time-slot, without requiring any knowledge of the underlying Markov chain of the channel process, or the statistics of the packet arrival process. Furthermore, in order to alleviate the requirement for full feedback at the transmitter, i.e., feedback for every successfully received packet, which is critical for the accurate queue update, we extend our analysis and incorporate reduced-feedback coding schemes. The proposed transmission policy in this scenario still meets the throughput objective and satisfies the power consumption constraints, while a tradeoff between transmission delays and feedback requirements is revealed.

We investigate the outage probability and the average bit error rate (BER) performance of a dual-hop amplify-and-forward (AF) relaying system, composed of a mixed radio frequency (RF)/free-space optical (FSO) link, when simultaneously outdated channel state information (CSI) is assumed at the relay and there is a misalignment between transmitter and receiver apertures in FSO link. In contrast to the majority of works on CSI-assisted AF relays, in this paper, we assume that the estimated CSI is outdated, when the relay amplifies the transmitted signal. The RF link experiences Rayleigh fading, while the FSO link is under the influence of atmospheric turbulence, modeled by the Gamma-Gamma distribution. Novel analytical expressions for the outage probability and the average BER are derived in a power series form, which in some special cases are simplified to offer engineering insight into the effects of important transceiver and channel parameters on the system performance. Numerical and simulation results show that there is an optimal value of the transmitter beam waist, which minimizes the overall outage probability. This optimal value strongly depends on the pointing errors standard deviation. Furthermore, the outage probability varies for several orders of magnitude depending on the transmitter beam waist.

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

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

Novel analytic solutions are derived for integrals that involve the generalized Marcum Q-function, exponential functions and arbitrary powers. Simple closed-form expressions are also derived for specific cases of the generic integrals. The offered expressions are both convenient and versatile, which is particularly useful in applications relating to natural sciences and engineering, including wireless communications and signal processing. To this end, they are employed in the derivation of the average probability of detection in energy detection of unknown signals over multipath fading channels as well as of the channel capacity with fixed rate and channel inversion in the case of correlated multipath fading and switched diversity.

Accurate fading characterization and channel capacity determination are of paramount importance in both conventional and emerging communication systems. The present work addresses the non-linearity of the propagation medium and its effects on the channel capacity. Such fading conditions are first characterized using information theoretic measures, namely, Shannon entropy, cross entropy and relative entropy. The corresponding effects on the channel capacity with and without power adaptation are then analyzed. Closed-form expressions are derived and validated through computer simulations. It is shown that the effects of nonlinearities are significantly larger than those of fading parameters such as the scattered-wave power ratio, and the correlation coefficient between the in-phase and quadrature components in each cluster of multipath components.

This letter maximizes the achievable throughput of a relay-assisted wirelessly powered communications system, where an energy constrained source, assisted by an energy constrained relay and both powered by a dedicated power beacon (PB), communicates with a destination. Considering the time splitting approach, the source and relay first harvest energy from the PB, which is equipped with multiple antennas, and then transmits the information to destination. Simple closed-form expressions are derived for the optimal PB energy beamforming vector and time split for energy harvesting and information transmission. Numerical results and simulations demonstrate the superior performance compared with some intuitive benchmark beamforming scheme. Also, it is found that placing the relay at the middle of the source-destination path is no longer optimal.

This paper investigates the average throughput of a wireless-powered communications system, where an energy constrained source, powered by a dedicated power beacon (PB), communicates with a destination. It is assumed that the PB is capable of performing channel estimation, digital beamforming, and spectrum sensing as a communication device. Considering a time-splitting approach, the source first harvests energy from the PB equipped with multiple antennas, and then transmits information to the destination. Assuming Nakagami-m fading channels, analytical expressions for the average throughput are derived for two different transmission modes, namely, delay tolerant and delay intolerant. In addition, closed-form solutions for the optimal time split, which maximize the average throughput are obtained in some special cases, i.e., high-transmit power regime and large number of antennas. Finally, the impact of cochannel interference is studied. Numerical and simulation results have shown that increasing the number of transmit antennas at the PB is an effective tool to improve the average throughput and the interference can be potentially exploited to enhance the average throughput, since it can be utilized as an extra source of energy. Also, the impact of fading severity level of the energy transfer link on the average throughput is not significant, especially if the number of PB antennas is large. Finally, it is observed that the source position has a great impact on the average throughput.

In this paper, an energy harvesting dual-hop relaying system without/with the presence of co-channel interference (CCI) is investigated. Specifically, the energy constrained multi-antenna relay node is powered by either the information signal of the source or via the signal receiving from both the source and interferer. In particular, we first study the outage probability and ergodic capacity of an interference free system, and then extend the analysis to an interfering environment. To exploit the benefit of multiple antennas, three different linear processing schemes are investigated, namely, 1) Maximum ratio combining/maximum ratio transmission (MRC/MRT), 2) Zero-forcing/MRT (ZF/MRT) and 3) Minimum mean-square error/MRT (MMSE/MRT). For all schemes, both the systems outage probability and ergodic capacity are studied, and the achievable diversity order is also presented. In addition, the optimal power splitting ratio minimizing the outage probability is characterized. Our results show that the implementation of multiple antennas increases the energy harvesting capability, hence, significantly improves the systems performance.

-We study a cloud network with M distributed receiving antennas and L users, which transmit their messages towards a centralized decoder (CD), where M ≥ L. We consider that the cloud network applies the Compute-and-Forward (C&F) protocol, where L antennas/relays are selected to decode integer equations of the transmitted messages. In this work, we focus on the best relay selection and the optimization of the Physical-Layer Network Coding (PNC) at the relays, aiming at the throughput maximization of the network. Existing literature optimizes PNC with respect to the maximization of the minimum rate among users. The proposed strategy maximizes the sum rate of the users allowing non-symmetric rates, while the optimal solution is explored with the aid of the Pareto frontier. The problem of relay selection is matched to a coalition formation game, where the relays and the CD cooperate to maximize their profit. Efficient coalition formation algorithms are proposed, which perform joint relay selection and PNC optimization. Simulation results show that a considerable improvement is achieved compared to existing results, both in terms of the network sum rate and the players' profits.

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

In this paper, the application of radio over fiber (RoF) based wireless communications for smart metering and power distribution is introduced. A RoF based network has the potential to enhance both the coverage and spectral efficiency of smart grid wireless networks since its major benefit is adaptability to temporal and spatial traffic variations. A clustered architecture is presented which provides signal diversity to enhance the coverage and capacity of smart grid communications. Examples are presented to illustrate the improvement in coverage and latency of a smart grid wireless network when RoF is used instead of a conventional wireless network.

This work is devoted to the analysis of the performance of energy detection based spectrum sensing in the presence of enriched fading conditions which are distinct for the large number of multipath components and the lack of a dominant components. This type of fading conditions are characterized efficiently by the well known Nakagami-q or Hoyt distribution and the proposed analysis is carried out in the context of the area under the receiver operating characteristics (ROC) curve (AUC). Unlike the widely used probability of detection metric, the AUC is a single metric and has been shown to be rather capable of evaluating the performance of a detector in applications relating to cognitive radio, radar systems and biomédical engineering, among others. Based on this, novel analytic expressions are derived for the average AUC and its complementary metric, average CAUC, for both integer and fractional values of the involved time-bandwidth product. The derived expressions have a tractable algebraic representation which renders them convenient to handle both analytically and numerically. Based on this, they are employed in analyzing the behavior of energy detection based spectrum sensing over enriched fading conditions for different severity scenarios, which demonstrates that the performance of energy detectors is, as expected, closely related to the value of the fading parameter q.

This paper investigates link layer transmission schemes for hybrid optical wireless (OW)/radio frequency (RF) systems with constraints on both per-link and total power consumption at the transmitter. Assuming timeslot structure and using a queue for storing the random data packet arrivals, we formulate a stochastic optimization problem where intelligent control decisions are taken by the hybrid transmitter in each slot, regarding the number of the packets admitted in its queue and the power levels used in each link. The aim of this formulation is to design a control policy that maximizes the transmitter throughput, while satisfying its power constraints as well. A solution is offered by using the Lyapunov optimization framework. An on-line transmission algorithm is derived, which takes control decisions based only on the status of the transmitter queue and the erasure probabilities of the OW and RF links. The proposed algorithm meets the desired throughput objective by efficiently exploiting both links, while provides explicit power consumption guarantees.

The performance of multiuser dual-hop relaying over mixed radio frequency/free-space optical (RF/FSO) links is investigated. RF links are used for the simultaneous data transmission from m single-antenna sources to the relay, which is equipped with n ≥ m receive antennas and a photo-aperture transmitter. The relay operates under the decode-and-forward protocol and utilizes the popular ordered V-BLAST technique to successively decode each user's transmitted stream. A common norm-based ordering approach is adopted, where the streams are decoded in an ascending order. After the V-BLAST decoding, the relay retransmits the initial information to the destination, which is equipped with a photo-detector, via a point-to-point FSO link in m consecutive timeslots. Analytical expressions for the end-to-end outage probability and average symbol error probability of each user are derived. Some engineering insights are manifested, such as the diversity order, the impact of the pointing error displacement on the FSO link and the severity on the turbulence-induced channel fading.

Heterogeneous cellular networks can improve network capacity by co-deployment of macro and femto base stations (BSs). The capacity improvement comes with a higher power consumption. This paper proposes a method to minimize the power consumption without compromising the quality-of-service demand which is measured in terms of packet delay. First, we derive a closed-form expression for the packet delay as a function of macro and femto BS densities. Then, we determine the BS densities that minimize the network power consumption under a packet delay constraint. Evaluation results show that heterogeneous networks always outperforms a homogeneous network in terms of power-delay characteristics. With the optimal BS densities for a given packet delay requirement, the minimum power consumption of a heterogeneous network is always lower than that of a homogeneous network.

Motivated by the cooperative game theory, we propose an efficient physical layer network coding technique for compute-and-forward (C&F) relaying systems, which jointly optimizes the sum and the minimum transmission rate, while minimizing the total transmitting power. Specifically, we show that relay selection in C&F networks leads to an increase of both rates. We also propose an algorithmic approach for the rates' further optimization and we illustrate that its implementation can offer the same or even greater gain than adding an extra relay. Furthermore, the tradeoff between the minimum and the sum rate is explained by utilizing the concept of Pareto frontier. Simulations and numerical results show that a combination of relay selection and the proposed algorithms offers a considerable increase in the sum rate for the same transmitting power, without reducing the system's Quality of Service.

We present a novel low-complexity technique that obtains the Physical-Layer Network Coding (PNC) equation coefficient vectors for the two-way relay channel when Compute-and-Forward is employed. The proposed method is based on pre-computed look-up tables that are used for all channel realizations. It is shown that the size of the look-up tables can be made small by taking into account the statistics of the channel coefficients as well as power and performance specifications. Moreover, a low-complexity algorithm is developed for efficient real-time selection of the equation coefficient vectors using the instantaneous channel coefficients and the look-up tables. Although the method may at times exclude some candidate vectors from the search space, simulation results indicate that the effect on the achievable computation rate at the relay is very small. Hence, significant complexity reduction is achieved, while the computation rate remains extremely close to the optimal value.

In this study, the outage performance of a multi‐relay cooperative network operating in a spectrum sharing environment is analysed. Focusing on the secondary communication process, a relay selection procedure is performed prior to the communication process, where the selected relay is the one maximising the instantaneous end‐to‐end signal‐to‐noise ratio (SNR) and, at the same time, satisfying the power restrictions imposed by the primary receivers. The secondary destination employs a selection combining strategy, selecting the best path (direct link or relaying link) with the highest instantaneous SNR. Two kinds of relaying protocols are considered: decode‐and‐forward and amplify‐and‐forward. For the former, an exact closed‐form expression for the outage probability (OP) is derived, whereas for the latter an accurate approximation for the OP is obtained. Then, an asymptotic analysis is carried out and reveals that the system diversity order is N + 1 for both relaying protocols, with N denoting the number of relays. Monte Carlo simulations assess the accuracy of the authors’ results.

Block error rate performance of subcarrier intensity modulation based optical wireless communication systems is analysed over Gamma–Gamma and lognormal atmospheric turbulence channels. The analysis is applicable to non‐coherent binary modulations and coherent binary phase shift keying. The special cases of K ‐distributed strong turbulence channel and negative exponential turbulence channel are also considered. The closed‐form expressions of block error rate in the Gamma–Gamma turbulence channels are derived using a series expansion of the modified Bessel function. For the lognormal turbulence channels, the Gauss–Laguerre quadrature method can be used to estimate the block error rate accurately.

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

A multiuser dual-hop relaying system over mixed radio frequency/free-space optical (RF/FSO) links is investigated. Specifically, the system consists of m single-antenna sources, a relay node equipped with n≥ m receive antennas and a single photo-aperture transmitter, and one destination equipped with a single photo-detector. RF links are used for the simultaneous data transmission from multiple sources to the relay. The relay operates under the decode-and-forward protocol and utilizes the popular V-BLAST technique by successively decoding each user's transmitted stream. Two common norm-based orderings are adopted, i.e., the streams are decoded in an ascending or a descending order. After V-BLAST, the relay retransmits the decoded information to the destination via a point-to-point FSO link in m consecutive timeslots. Analytical expressions for the end-to-end outage probability and average symbol error probability of each user are derived, while closed-form asymptotic expressions are also presented. Capitalizing on the derived results, some engineering insights are manifested, such as the coding and diversity gain of each user, the impact of the pointing error displacement on the FSO link and the V-BLAST ordering effectiveness at the relay.

We study the outage performance of orthogonal frequency-division multiplexing dual-hop opportunistic amplify-and-forward relaying in the presence of I/Q imbalance (IQI) in all nodes. We derive a closed-form expression for the end-to-end outage probability for the general case where each node suffers from a different IQI level and assuming that the distance between source and relay is not the same for all relays. Furthermore, we consider the more general case where there is a direct link between the source and the destination and we derive a closed-form expression for the end-to-end outage probability for both maximum-ratio and selection combining at the destination. To gain more insights, we analyze a special case where all relays lie on the perpendicular line midway between source and destination and all nodes experience the same IQI level. Our simulations show excellent match to the analytical results and both demonstrate that uncompensated IQI can be detrimental but it can also be effectively mitigated using a few opportunistic relays. In summary, the main contributions of this paper are analyzing the effect of IQI on the outage probability of an opportunistic relaying system and determining the number of relays needed to effectively mitigate uncompensated IQI.

Two closed-form expressions for the end-to-end cumulative distribution function (CDF) and outage probability of two-way interference-limited amplify-and-forward (AF) relaying were recently presented in Equations (19) and (24) in the above titled paper (ibid., vol. 61, no. 8 pp. 3156-3169, Aug. 2013). However, the expressions contain a notational error. A correction is presented here.

This paper is devoted to the derivation of novel analytic expressions and bounds for a family of special functions that are useful in wireless communication theory. These functions are the well-known Nuttall Q-function, incomplete Toronto function, Rice Ie-function, and incomplete Lipschitz-Hankel integrals. Capitalizing on the offered results, useful identities are additionally derived between the above functions and Humbert, Φ1, function as well as for specific cases of the Kampé de Fériet function. These functions can be considered as useful mathematical tools that can be employed in applications relating to the analytic performance evaluation of modern wireless communication systems, such as cognitive radio, cooperative, and free-space optical communications as well as radar, diversity, and multiantenna systems. As an example, new closed-form expressions are derived for the outage probability over nonlinear generalized fading channels, namely, α-η-μ, α-λ-μ, and α-κ-μ as well as for specific cases of the η-μ and λ-μ fading channels. Furthermore, simple expressions are presented for the channel capacity for the truncated channel inversion with fixed rate and corresponding optimum cutoff signal-to-noise ratio for single-antenna and multiantenna communication systems over Rician fading channels. The accuracy and validity of the derived expressions is justified through extensive comparisons with respective numerical results.

Distributed switch-and-stay combining (DSSC) has been envisioned as an effective transmission technique to achieve spatial diversity in a distributed fashion, with low implementation complexity. In this paper, we take a step further to incorporate DSSC into spectrum-limited environment, where the operating nodes have to share the frequency radio spectrum with licensed users. In particular, by deploying DSSC scheme in cognitive radio networks, we have shown that the low transmit power at unlicensed users, inflicted by the peak interference power constraint at licensed users, can be alleviated. We present closed-form expressions for outage probability and spectral efficiency, enabling us to evaluate and optimize the considered network performance. Numerical and simulation results show that when the switching threshold is below the outage threshold the full diversity order can be guaranteed at the secondary networks.

Reducing the power consumption of base transceiver stations (BTSs) in mobile communications networks is typically achieved through energy saving techniques, where they can also be combined with local power generators to create a hybrid power system (HPS). Such a system has reduced power consumption and operational cost, without taking the advantage of real-time energy management. In this paper, we introduce the smart HPS that can facilitate energy consumption scheduling (ECS) via an intelligent connection to the power grid. In doing so, we first develop sensor control and communication systems with an embedded smart ECS unit for the HPS. Then, we propose a real-time energy management algorithm to reduce the operational cost of BTS, according to real-time pricing and estimating demand and supply. The numerical results presented show a significant reduction in the BTS operational costs. We also develop a techno-economic and sizing analysis to describe the total cost of the smart HPS taking the real-time energy pricing into account. Since the lifetime of the operating system can be quite long, our results show that there is possibility to make a profit.

Previous works on cognitive relay networks (CRNs) considered only symmetric fading channels. However, in practical wireless propagation scenarios, it is likely that the channels of the secondary user (SU) and primary user (PU) may undergo different fading characteristics. In this paper, we assume that the channels of the secondary network (SU-source→SU-relay→SU-destination) are subject to Rician fading, whereas the channels of the link from the SU to the PU experience Rayleigh fading. Based on this framework, the end-to-end outage probability (OP) of CRNs is investigated for two different relaying schemes: i) in the absence of the direct link with decode-and-forward (DF) protocol and ii) in the presence of the direct link with incremental DF protocol. In particular, we derive both exact and asymptotic OP expressions for the considered CRNs. Our analysis reveals important insights into the impact of fading parameters on the CRN performance under distinct fading distributions.

This paper proposes a novel and efficient algorithm for space-time block code (STBC) classification, when a single antenna is employed at the receiver. The algorithm exploits the discriminating features provided by the discrete Fourier transform (DFT) of the fourth-order lag products (FOLPs) of the received signal. It does not require estimation of the channel, signal-to-noise ratio (SNR), and modulation of the transmitted signal. Computer simulations are conducted to evaluate the performance of the proposed algorithm. The results show the validity of the algorithm, its robustness to carrier frequency offset, and low sensitivity to timing offset.

We study the outage performance of orthogonal frequency-division multiplexing dual-hop opportunistic amplify-and-forward relaying in the presence of I/Q imbalance in all of the nodes' transceivers. We derive a closed-form expression for the end-to-end outage probability for the general case, where each node suffers from a different I/Q imbalance level and under the assumption that the distance between source and relay is not the same for all relays. Our simulation results show excellent match to our analysis and both demonstrate that uncompensated I/Q imbalance can be detrimental but it can also be effectively mitigated using a few relays. This result has a significant impact on relay deployment in future wireless communication networks.

We investigate the performance of two-way interference-limited amplify-and-forward relaying systems over independent but non-identically distributed (i.n.i.d.) Nakagami-m fading channels. A tight closed-form lower bound on the outage probability of the system is derived, along with a simplified expression in the asymptotically low outage regime. Some special cases of practical interest (e.g., no interference power and interference-limited case) are also examined. The theoretical and numerical results provide important physical insights into the implications of the model parameters on the system performance.

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

We investigate the performance of two-way interference-limited amplify-and-forward (AF) relaying systems with selection-combining (SC) over Nakagami-m fading channels. In particular, a tight lower bound on the end-to-end outage probability (OP) is derived in closed-form, while a useful expression is presented for the asymptotically low outage regime. Some special cases of practical interest (e.g., no interference power and Rayleigh fading channels) are also studied. The numerical results provide important physical insights into the implications of model parameters on the system performance.

Cooperative spectrum sharing systems (CSSSs) have recently received considerable attention from the wireless community due to their performance gains and spectrum utilization improvement when compared to traditional communication systems. Owing to this fact, we investigate the outage performance of CSSSs in the presence of multiple primary users (PUs). The secondary user (SU) network is composed by one source node, N decode-and-forward (DF) relays, and one destination. A best relay selection strategy is performed where the selected relay is that which maximizes the end-to-end signal-to-noise ratio (SNR) and, simultaneously, satisfies the interference constraint imposed by the MPU receivers. The communication between the SU source and SU destination is carried out through the help of one out of N DF relays and also via direct link. Afterwards, the SU destination selects the best path between the direct and the relaying path by using selection combining technique. A closed-form expression for the outage probability (OP) is derived, and an asymptotic analysis is carried out which reveals that the diversity order of the considered system equals N +1, showing that it is not affected neither by the number of PU receivers nor by the interference threshold. The presented analytical expressions are corroborated by means of Monte Carlo simulations and insightful discussions are provided.

We employ the theory of multidimensional lattice constellations in order to evaluate the maximum-likelihood (ML) performance of a general multiple-input multiple-output MIMO system. We show that the lattice representation of the equivalent system model enables a mapping of the received signal set to a single point in a multidimensional constellation, with the generator matrix being equal to the equivalent channel matrix. With the aid of this geometrical interpretation, we derive a performance limit for a general MIMO system in terms of the symbol error probability, which can be written in closed form for various designs. Application of the proposed analysis to popular MIMO schemes reveals the tractability of the approach and validates that designs exploiting the available degrees of freedom in a better way approach the proposed performance limit.

The Gallager's random coding error exponent for space-time block codes (STBC) over multiple-input multiple-output (MIMO) block-fading channels, with Gaussian input distribution, is investigated. Gallager's error exponent can be used to determine the required codeword length to achieve a prescribed error probability at a given rate below the channel capacity. We first provide new, analytical expressions for Gallager's exponent of STBC systems over η-μ fading channels. The Shannon capacity and cutoff rate, which can be directly derived from Gallager's exponent, are further examined. In order to get additional insights, a high signal-to-noise ratio analysis is pursued to investigate the effects of coherence time and codeword length on the error probability. For the sake of completeness, we provide the link to previous known results on Rayleigh and Nakagami-m fading channels.

We investigate the sensitivity of Compute-and-Forward (C&F) to channel estimation errors. More specifically, a general formula for the computation rate region of a C&F relay, suffering from imperfect channel estimation, is derived, which is then tightly approximated for Gaussian distributed channel estimation errors. Furthermore, a closed-form expression for the distribution of the C&F rate loss is presented, which can be efficiently used to compute relevant statistical parameters, such as the mean rate loss. Numerical and simulation results highlight the high sensitivity of the overall network performance to channel estimation errors.

Several key exchange methods for wireless channels have been proposed in the literature. They are referred to as physical‐layer security techniques and are usually based on the channel's fading characteristics and the principle of channel reciprocity. In this study, the authors present key exchange algorithms for wireless fading channels whose operation is based on channel estimation. Specifically, the authors present a complete key exchange scheme that includes channel sampling, thresholding and error reconciliation. Two error reconciliation methods are proposed. The first one is based on neural networks and the second one is based on linear block coding. Simulations of the proposed methods’ performances and levels of security are presented and conclusions are drawn regarding their overall utility.

The papers in this special issue focus on large-scale multiple antenna wireless systems and services.

Blind signal classification, a major task of intelligent receivers, has important civilian and military applications. This problem becomes more challenging in multi-antenna scenarios due to the diverse transmission schemes that can be employed, e.g., spatial multiplexing (SM) and space-time block codes (STBCs). This paper presents a class of novel algorithms for blind classification of SM and Alamouti STBC (AL-STBC) transmissions. Unlike the prior art, we show that signal classification can be performed using a single receive antenna by taking advantage of the space-time redundancy. The first proposed algorithm relies on the fourth-order moment as a discriminating feature and employs the likelihood ratio test for achieving maximum average probability of correct classification. This requires knowledge of the channel coefficients, modulation type, and noise power. To avoid this drawback, three algorithms have been further developed. Their common idea is that the discrete Fourier transform of the fourth-order lag product exhibits peaks at certain frequencies for the AL-STBC signals, but not for the SM signals, and thus, provides the basis of a useful discriminating feature for signal classification. The effectiveness of these algorithms has been demonstrated in extensive simulation experiments, where a Nakagami-m fading channel and the presence of timing and frequency offsets are assumed.

Multidimensional lattice constellations which present signal space diversity (SSD) have been extensively studied for single-antenna transmission over fading channels, with focus on their optimal design for achieving high diversity gain. In this two-part series of papers we present a novel combinatorial geometrical approach based on parallelotope geometry, for the performance evaluation of multidimensional finite lattice constellations with arbitrary structure, dimension and rank. In Part I, we present an analytical expression for the exact symbol error probability (SEP) of multidimensional signal sets, and two novel closed-form bounds, named Multiple Sphere Lower Bound (MLSB) and Multiple Sphere Upper Bound (MSUB). Part II extends the analysis to the transmission over fading channels, where multidimensional signal sets are commonly used to combat fading degradation. Numerical and simulation results show that the proposed geometrical approach leads to bounds that can be used for the performance evaluation and the design of multidimensional lattice constellations, both in Additive White Gaussian Noise (AWGN) and fading channels.

This is the second part of a two-part series of papers, where the error performance of multidimensional lattice constellations with signal space diversity (SSD) is investigated. In Part I, following a novel combinatorial geometrical approach which is based on parallelotope geometry, we have presented an exact analytical expression and two closed-form bounds for the symbol error probability (SEP) in Additive White Gaussian Noise (AWGN). In the present Part II, we extend the analysis and present a novel analytical expression for the Frame Error Probability (FEP) of multidimensional lattice constellations over Nakagami-m fading channels. As the FEP of infinite lattice constellations is lower bounded by the Sphere Lower Bound (SLB), we propose the Sphere Upper Bound (SUB) for block fading channels. Furthermore, two novel bounds for the FEP of multidimensional lattice constellations over block fading channels, named Multiple Sphere Lower Bound (MSLB) and Multiple Sphere Upper Bound (MSUB), are presented. The expressions for the SLB and SUB are given in closed form, while the corresponding ones for MSLB and MSUB are given in closed form for unitary block length. Numerical and simulation results illustrate the tightness of the proposed bounds which can be efficiently used to set the performance limits on the FEP of lattice constellations of arbitrary structure, dimension and rank.

In this paper, we investigate the performance of two-way interference-limited amplify-and-forward relaying systems over independent, non-identically distributed Nakagami-m fading channels. Our analysis generalizes several previous results, since it accounts for interference affecting all network nodes. In particular, tight lower bounds on the end-to-end outage and symbol error probability are derived in closed-form, while a useful expression is presented for the asymptotically low outage regime. Some special cases of practical interest (e.g., no interference power and interference-limited case) are also studied. Using the derived lower bounds as a starting point and for the case of Rayleigh fading, we formulate and solve analytically three practical optimization problems, namely, power allocation under fixed location for the relay, optimal relay position with fixed power allocation, and joint optimization of power allocation and relay position under a transmit power constraint. The numerical results provide important physical insights into the implications of model parameters on the system performance; for instance, it is demonstrated that relay position optimization offers significant performance enhancement over the non-optimized case for an asymmetric interference power profile, whilst the optimization gains are marginal for a symmetric one.

In this paper, we analytically investigate Gallager's exponent for space-time block codes over multiple-input multiple-output block-fading channels with Gaussian input distribution. As a suitable metric of the fundamental tradeoff between communication reliability and information rate, Gallager's exponent can be used to determine the required codeword length to achieve a prescribed error probability at a given rate below the channel capacity. We assume that the receiver has full channel state information (CSI), while the transmitter has no CSI and performs equal power allocation across all transmit antennas. In the following, novel exact expressions for Gallager's exponent are derived for two well-known channel fading models, namely η-μ and κ-μ fading models. More importantly, the implications of fading parameters and channel coherence time on Gallager's exponent are investigated. In addition, we present new expressions for the Shannon capacity, cutoff rate and expurgated exponent for the above mentioned fading models, while in the high signal-to-noise ratio regime, simplified closed-form expressions are also derived. Finally, we highlight the fact that the presented analysis encompasses all previously known results on Nakagami-m, Rician, Rayleigh and Hoyt fading channels, as special cases.

For the conventional three-node amplify-and-forward (AF) relaying setup, we investigate the effect of imperfect channel state information (CSI) at the relay on the overall performance. In particular, we consider variable gain (a.k.a, CSI-assisted) AF relaying and derive expressions for the outage and the error probability for the case where the relay gain is adjusted based on outdated estimates of the source-relay channel, when operating over Nakagami-m fading. For the case of Rayleigh fading in the source-relay link, we show that the results can be extended to the versatile case of imperfect CSI, where the estimation error is caused either by additive white Gaussian noise or by quantization noise. The obtained expressions are functions of the correlation coefficient between the actual source-relay channel and its corresponding estimate. We also optimize the power allocation for minimization of the outage probability under a total transmit power constraint. Numerical results reveal a considerable degradation of the overall performance, when CSI acquisition is not perfect. Moreover, it is shown that the average relay transmit power is affected when the CSI is outdated, a fact which impacts the design of variable gain relaying in practice. Since outdated CSI leads to fluctuations of the relay transmit power, we derive expressions for the complementary cumulative distribution function (CCDF) of the peak-to-average-power ratio (PAPR) at the relay. By comparing the error probability and the CCDF of the PAPR of variable gain relaying with those of fixed gain relaying, we shed some light onto the following question: How reliable has the instantaneous CSI at the relay to be for variable gain relaying to be preferable over fixed gain relaying, which requires only statistical CSI?

We investigate the diversity order of decode-and-forward relay selection in Nakagami-m fading, in cases where practical channel estimation techniques are applied. In this respect, we introduce a unified model for the imperfect channel estimates, where the effects of noise, time-varying channels, and feedback delays are jointly considered. Based on this model, the correlation between the actual and the estimated channel values, ρ, is expressed as a function of the signal-to-noise ratio (SNR), yielding closed-form expressions for the overall outage probability as a function of ρ. The resulting diversity order and power gain reveal a high dependence of the performance of relay selection on the high SNR behavior of ρ, thus shedding light onto the effect of channel estimation on the overall performance. It is shown that when the channel estimates are not frequently updated in applications involving time-varying channels, or when the amount of power allocated for channel estimation is not sufficiently high, the diversity potential of relay selection is severely degraded. In short, the main contribution of this paper lies in answering the following question: How fast should ρ tend to one, as the SNR tends to infinity, so that relay selection does not experience any diversity loss?

With reference to the typical three-node amplify-and-forward (AF) relaying setup, where a single relay assists the communication between a source terminal and a destination terminal, we investigate the effect of outdated channel state information (CSI) at the relay on the overall performance. In particular, we consider CSI-assisted (i.e., variable-gain) AF relaying and derive expressions for the outage and the error probability for the case where the relay gain is adapted based on outdated estimates of the source-relay channel, when operating over Nakagami-m fading. The obtained expressions are functions of the scale and shape fading parameters, as well as the correlation coefficient between the actual source-relay channel and its corresponding estimate. Numerical results reveal a considerable degradation of the overall performance, when CSI acquisition is not perfect.

A novel analytical framework for evaluating the statistics of the products of independent random variables is proposed. Compared with other methods which use either an infinite series or a special function, the new method provides simple and efficient closed-form approximations in terms of elementary functions, such as powers and exponentials, and therefore, is very easy to implement. The accuracy of the new approximation is examined. Numerical results show that it is quite accurate in most regions of interest. As an application, these new approximations are used in wireless communications theory to derive novel closed-form expressions for the outage probability of cascaded fading channels. Numerical examples show that the newly derived closed-form expressions provide insights on the behavior of important performance metrics as the outage probability, the bit error rate and the channel capacity.

We propose a generalized framework for handling Multiple-Input Multiple-Output (MIMO) schemes defined within the context of the Third Generation Partnership Project (3GPP) physical layer specifications. A detailed review of all the multi-antenna transmission techniques adopted by the 3GPP so far is firstly presented, starting from the Global System for Mobile (GSM) communications and passing through the High-Speed Packet Access (HSPA) releases to the very recent Long Term Evolution (LTE)-Advanced standard. Motivated by the outcome of this overview, we introduce the Transmit Matrix (TRAM) concept, that can include as special cases several MIMO systems (e.g. transmit diversity, spatial-multiplexing, etc.) regardless of the presence or not of a feedback channel. Our approach is based on the adoption of a novel measure called Necessary Transmit Information (NTI) and on its one-to-one correspondence with the TRAM. The last allows for a convenient alternative representation of a TRAM-based MIMO system model and serves the straightforward construction of NTI-codebooks for a wide range of transmission schemes. The indicative applications provided reveal the universal nature of the proposed methodology.

We present a novel combinatorial geometrical approach for evaluating the performance of multidimensional finite lattice constellations in Additive White Gaussian Noise (AWGN). More specifically, we present an analytical expression for the exact symbol error probability (SEP) of multidimensional signal sets, which is then used to derive a tight closed-form lower bound of the SEP, named Multiple Sphere Lower Bound (MLSB). Simulations are used to compare the proposed bound with the performance of various lattice constellations. It is clearly demonstrated that the MSLB can be efficiently used in finite lattice constellations, with arbitrary structure, dimension and rank. Furthermore, it can be easily extended to the case of fading channels, where multidimensional signal sets are commonly used to combat fading degradation.

We study the effect of outdated channel state information on the outage and error rate performance of amplify-and-forward (AF) relay selection, where only one out of the set of available relays is activated. We consider two variations of AF relay selection, namely best relay selection and partial relay selection, when the selection is based upon outdated channel estimates. For both these variations, closed-form expressions for the outage probability are obtained, along with approximate expressions for the symbol error rate in the medium to high signal-to-noise-ratio (SNR) regime. The diversity gain and coding gain of the above schemes are also explicitly derived. Numerical results manifest that the outage performance of AF relay selection is highly dependent on the level of correlation between the actual channel conditions and their corresponding (outdated) estimates. This result has a significant impact on the deployment of relay selection in practical applications, implying that a high feedback rate may be required in practice in order to attain the full benefits of relay selection. It is further shown that it may be preferable, in terms of outage and symbol error probability, not to include links in the relay selection process that experience a sufficiently high maximum Doppler shift, since in those cases partial relay selection outperforms best relay selection.

We investigate transmission protocols for relay-assisted free-space optical (FSO) systems, when multiple parallel relays are employed and there is no direct link between the source and the destination. As an alternative to all-active FSO relaying, where all the available relays transmit jointly, we propose a scheme which selects only a single relay to participate in the communication between the source and the destination in each transmission slot, based on the channel state information (CSI) obtained from all FSO links. Thus, the need for synchronizing the relays' transmission is avoided, while the slowly varying nature of the atmospheric channel is exploited. For both relay selection and all-active relaying, novel analytical closed-form expressions for their outage performance are derived, assuming the Gamma-Gamma channel model. Numerical results are provided for equal and non-equal length FSO links, which clearly demonstrate the significant performance gains offered by relay selection compared to all-active relaying.

The performance of relay selection is degraded when the channel estimates used for relay selection are imperfect. Considering that the channel estimates are obtained via practical channel estimation techniques, we quantify the effects of imperfect channel state information (CSI) on the diversity order of relay selection. The analysis involves combining the effects of noise, time-varying channels, and feedback delays on the CSI used for relay selection into a unified model. Based on this model, the correlation between the actual and the estimated channel values, n, is expressed as a function of the signal-to-noise ratio (SNR), providing interesting insight into the behavior of the outage probability in high SNR. The resulting expression for the diversity order reveals that the behavior of the correlation in high SNR crucially affects the asymptotic performance of relay selection. In summary, based upon expressing n as a function of the SNR, we answer the following question: How fast should n tend to one, as the SNR tends to infinity, so that relay selection does not experience any diversity loss?

This paper presents a detailed sum rate investigation of Zero-Forcing (ZF) detectors over composite multiple-input multiple-output (MIMO) channels. To this end, we consider the generic K distribution (Rayleigh/gamma distribution) to model the composite fading fluctuations and also assume the general case of semi-correlated small-scale fading. Novel exact analytical expressions are derived for the achievable sum rate followed by asymptotic expressions in the low Signal to-Noise ratio (SNR) regime. In parallel, new, closed-form upper and lower bounds on the sum rate are derived that re main tight for all SNRs. The theoretical analysis is validated via a set of Monte-Carlo simulations.

We present a novel architecture for hybrid radio frequency (RF)/ free space optical (FSO) wireless systems without feedback or channel state information (CSI) at the transmitter. Under the assumption that 60 GHz RF and FSO systems support the same data rates, the proposed implementation transmits the same data over both links, using phase shift keying (PSK) as a common modulation scheme, and combines the signals from each individual link at the receiver on a symbol-by-symbol basis. Two popular diversity combining schemes are considered, namely, selection combining (SC) and maximal ratio combining (MRC), while tractable analytical approximations for the bit error rate (BER) are obtained. Investigations over various weather conditions and link distances revealed that the proposed implementation fully exploits the complementary nature of RF and FSO channels, even when one of the two available links fails. Furthermore, the comparison of the combining schemes demonstrates MRC as the optimum combining scheme, offering link distance gains compared to SC.

We study the effect of outdated channel estimates on decode-and-forward relay selection, when operating over Nakagami-m fading channels. Closed-form expressions for the exact outage probability are derived, as function of the correlation between the actual and the estimated channel values. The diversity and coding gain are also studied, revealing a high dependence of diversity order on the aforementioned correlation coefficient. It is shown that when the channel estimates are not perfectly updated, the performance of relay selection is equivalent, in terms of diversity order, to the scheme where only a single relay is available.

We investigate the outage probability and the average bit error rate (BER) of a dual-hop fixed gain relaying system in the presence of co-channel interference and thermal noise at the relay and the destination. Our analysis assumes Rayleigh fading for the source-relay and relay-destination channels and Rician fading for the interfering channels. We present new closed-form/series expressions for the outage probability and the average BER. The achievable diversity order is also studied. It is further shown through numerical results that the Rician K-factor of the interfering channel has a negative effect on the overall outage probability and BER, yet this effect is very small.

A complete evaluation of the benefits of cooperative diversity schemes should not only include the outage and error rate performance but also the second-order statistics of the achievable information-theoretic capacity. In a non-ergodic fading channel, the system is said to be in outage when the destination cannot decode the fixed-rate transmitted signal with negligible error probability. Because of the Doppler effect, which is induced by the mobility of the wireless nodes, these outage capacity events are correlated. In this paper, we derive the average outage rate (AOR) and the average outage duration (AOD) of two well-known cooperative diversity protocols, decode-and-forward relaying and selection decode-and-forward relaying, operating in slow Rayleigh fading channels. We also analyze the asymptotic behavior of these statistical parameters for high SNRs, where it is shown that the AOR exhibits a similar behavior as the outage probability.

Several key exchange methods for wireless channels have been proposed in the literature. They are referred to as PHY-layer security techniques and are usually based on the channel's fading characteristics and the principle of reciprocity. In this paper, we present a novel PHY-layer security algorithm whose function is based on neural networks. Specifically, we present a full key exchange scheme which includes channel sampling and thresholding and neural network based error reconciliation. The proposed method's performance and offered security are studied through simulations and interesting conclusions are drawn about its overall utility.

We present a novel and analytical lower bound on the ergodic capacity of distributed multiple-input multiple-output (D-MIMO) systems operating in composite Rayleigh/lognormal (RLN) fading and assuming double-sided spatial correlation. The proposed lower bound is applicable for finite number of antennas and remains tight across the entire Signal-to-Noise (SNR) regime. In addition, we perform a detailed low-SNR analysis that provides useful insights into the implications of the system parameters on MIMO capacity.

The Gamma-Gamma (Γ Γ ) distribution has recently attracted the interest of the research community due to its involvement in various communication systems. In the context of RF wireless communications, Γ Γ distribution accurately models the power statistics in composite shadowing/fading channels as well as in cascade multipath fading channels, while in optical wireless (OW) systems, it describes the fluctuations of the irradiance of optical signals distorted by atmospheric turbulence. Although Γ Γ channel model offers analytical tractability in the analysis of single input single output (SISO) wireless systems, difficulties arise when studying multiple input multiple output (MIMO) systems, where the distribution of the sum of independent Γ Γ variates is required. In this paper, we present a novel and simple closed-form approximation for the distribution of the sum of independent, but not necessarily identically distributed Γ Γ variates. It is shown that the probability density function (PDF) of the Γ Γ sum can be efficiently approximated either by the PDF of a single Γ Γ distribution, or by a finite weighted sum of PDFs of Γ Γ distributions. To reveal the importance of the proposed approximation, the performance of RF wireless systems in the presence of composite fading, as well as MIMO OW systems impaired by atmospheric turbulence, are investigated. Numerical results and simulations illustrate the accuracy of the proposed approach.

We propose an adaptive transmission technique for free space optical (FSO) systems, operating in atmospheric turbulence and employing subcarrier phase shift keying (S-PSK) intensity modulation. Exploiting the constant envelope characteristics of S-PSK, the proposed technique offers efficient utilization of the FSO channel capacity by adapting the modulation order of S-PSK, according to the instantaneous state of turbulence induced fading and a pre-defined bit error rate (BER) requirement. Novel expressions for the spectral efficiency and average BER of the proposed adaptive FSO system are presented and performance investigations under various turbulence conditions, turbulence models, and target BER requirements are carried out. Numerical results indicate that significant spectral efficiency gains are offered without increasing the transmitted average optical power or sacrificing BER requirements, especially in moderate-to-strong turbulence conditions. Furthermore, the proposed variable rate transmission technique is applied to multiple input multiple output (MIMO) FSO systems, providing additional improvement in the achieved spectral efficiency as the number of the transmit and/or receive apertures increases.

This paper provides a systematic characterization of Zero-Forcing (ZF) detectors over multiple-input multiple-output (MIMO) channels that experience both small and large-scale fading. In particular, we consider the generic K distribution (Rayleigh/gamma distribution) to model the composite fading fluctuations and also assume the general case of semi-correlated small-scale fading. In the following, novel exact analytical expressions for the achievable sum rate are derived, followed by asymptotic expressions in the high and low Signal-to-Noise ratio (SNR) regimes. In these limiting cases, two common and insightful affine expansions are studied followed by new, closed-form upper and lower bounds on the sum rate that remain tight for all SNRs. In the second part of the paper, we present exact tractable expressions along with first-order expansions for the symbol error rate (SER) and outage probability; we also quantify the performance of ZF detectors in terms of diversity order and array (or coding) gain. The implications of the model parameters on the ZF detector performance are investigated via Monte-Carlo simulations which also validate the theoretical analysis.

The outage probability is an important performance measure for cooperative diversity schemes. However, in mobile environments, the outage probability does not completely describe the behavior of cooperative diversity schemes since the mobility of the involved nodes introduces variations in the channel gains. As a result, the capacity outage events are correlated in time and second-order statistical parameters of the achievable information-theoretic capacity such as the average capacity outage rate (AOR) and the average capacity outage duration (AOD) are required to obtain a more complete description of the properties of cooperative diversity protocols. In this paper, assuming slow Rayleigh fading, we derive exact expressions for the AOR and the AOD of three well-known cooperative diversity protocols: variable-gain amplify-and-forward, decode-and-forward, and selection decode-and-forward relaying. Furthermore, we develop asymptotically tight high signal-to-noise ratio (SNR) approximations, which offer important insights into the influence of various system and channel parameters on the AOR and the AOD. In particular, we show that on a double-logarithmic scale, similar to the outage probability, the AOR asymptotically decays with the SNR with a slope that depends on the diversity gain of the cooperative protocol, whereas the AOD asymptotically decays with a slope of -1/2 independent of the diversity gain.

We propose an adaptive transmission technique for optical wireless (OW) systems, operating in atmospheric turbulence and employing subcarrier phase shift keying (S-PSK) intensity modulation. Exploiting the constant envelope characteristics of S-PSK, the proposed technique offers efficient utilization of the OW channel capacity by adapting the modulation order of S-PSK, according to the instantaneous state of turbulence induced fading and a pre-defined bit error rate (BER) requirement. Novel expressions for the spectral efficiency and average BER of the proposed adaptive OW system are presented and performance investigations under various turbulence conditions and target BER requirements are carried out. Numerical results indicate that significant spectral efficiency gains are offered without increasing the transmitted average optical power or sacrificing BER requirements in moderate-to-strong turbulence conditions.

Due to higher peak-to-average power ratio and higher power backing-off in OFDM relaying systems, a cyclic prefixed single-carrier cooperative diversity system is considered in this paper. Under the transmission power constraint, the joint optimal power allocation to the source and relay node is investigated. For a two-hop decode-and-forward relaying protocol, the optimal power allocation is first obtained in the considered system, and then the opportunistic destination terminal selection is applied to improve the achievable average spectral efficiency (ASE). Based on the proposed QR decomposition (QRD)-based receiver in the destination terminal, closed-form expressions for the maximum achievable ASE are derived. Simulation results verify the derived closed-form analytical expressions.

We study the effect of outdated channel estimation on the outage performance of amplify-and-forward (AF) relay selection, where only one out of the set of available relays is activated. In particular, we derive closed-form expressions for the outage probability of two variations of AF relay selection, namely best relay selection and partial relay selection, when the selection is based upon outdated channel estimates. Numerical results manifest that the outage performance of both schemes under consideration is highly dependent on the level of imperfection of the channel estimates. It is further shown that it may be preferable, in terms of outage probability, not to include links in the relay selection process that experience high maximum Doppler shifts.

In this paper, we propose the Inverse Gaussian (IG) distribution, as a less complex alternative to Log-normal (LN), to describe turbulence-induced fading in free-space optical (FSO) systems operating in weak turbulence conditions and/or in the presence of a large amount of aperture averaging. By conducting goodness of fit tests, we define the range of values of the scintillation index, where the two distributions approximate each other, with a certain significance level. The efficiency of the new model is pointed out by deriving analytical expressions for the calculation of the bit-error rate of two typical FSO systems; an intensity-modulation/direct detection FSO system with M-ary pulse position modulation and a heterodyne FSO system with differential phase shift keying. Numerical examples are provided to clearly illustrate the accuracy of the proposed approach in the weak turbulence regime.

In this paper, a closed-loop wireless communication system employing Quasi-Orthogonal Space-Time Block Codes (QOSTBCs) is presented, where the total available power can be suitably allocated to the four transmit antennas, considering a very low-complexity decoding scheme at the receiver side. After deriving a particular optimization problem concerning the optimal choice of the power weights, we prove that the best strategy in terms of error probability is to switch-off three out of the four transmit antennas under the requirement of symbol-by-symbol maximum-likelihood decoding (MLD). Our proposed scheme requires a very low-data rate dedicated feedback link, since just one or two bits per block are sufficient for outperforming other existing closed-loop systems. The technique applies to all the well-known QOSTBCs with arbitrary number of receive antennas, while some special cases are taken indicatively for illustration purposes.

In this paper, several performance analysis metrics for the cyclic prefix-based single-carrier (CP-SC) opportunistic cooperative diversity systems are presented. After the statistical evaluation of the end-to-end signal-to-noise-ratio of a two-hop relaying transmission, we derive tight upper bounds for the maximum achievable average rate and lower bounds for the outage probability in closed form. Further, asymptotic analysis on the outage probability reveals that the diversity gain is determined by both the number of relay nodes in the system and the number of channel taps being supported by the CP length. Simulation results verify the derived closed-form analytical expressions and also the diversity gains. Asymptotic performance is also verified via Monte Carlo simulations.

In selective cooperative relaying only a single relay out of the set of available relays is activated at a time, hence the available power and bandwidth resources are efficiently utilized. However, implementing selective cooperative relaying in time-varying channels may cause frequent relay switchings that deteriorate the overall performance. In this paper, we study the rate at which a relay switching occurs in selective cooperative relaying applications with two available relays, operating over time-varying fading channels. In particular, we derive closed-form expressions for the relay switching rate (measured in Hz) of opportunistic relaying (OR) and distributed switch and stay combining (DSSC). Numerical results manifest that DSSC yields a considerably lower relay switching rate than OR.

In this paper, the performance of a dual-hop Amplify-and-Forward (AF) multi-antenna relay network, with end-to-end (e2e) best antenna selection, is investigated. To investigate the performance of this system, we first derive the exact outage probability in closed-form. It is then used to obtain expressions for e2e SNR moments and the average symbol/bit error rate (SER/BER) valid for a large class of practical modulation schemes. A simple and accurate BER approximation is also derived to quantify the performance at high SNR. Our analytical results, show that the e2e antenna pair selection scheme achieves the same diversity order as for the case where all antennas are used. To further confirm the validity of our analysis, Monte Carlo simulation results are also presented.

We investigate detection methods for on-off keying (OOK) photon-counting Free Space Optical (FSO) systems in the presence of turbulence-induced fading, assuming no channel state information at the receiver. To recover the performance loss which is associated with symbol-by-symbol detection in such a scenario, we consider sequence detection techniques, exploiting the temporal correlation of the FSO channel. Due to its high complexity in the calculation of its metric, optimal maximum likelihood sequence detection (MLSD) is infeasible for most practical purposes. Hence, we propose a suboptimal low-complexity detection rule, which is based on the generalized maximum-likelihood sequence estimation. The proposed scheme allows the detection of sequence lengths that are prohibitive for conventional MLSD, without using any kind of channel knowledge. Monte Carlo simulation results show its performance to be very close to the optimum for large sequence lengths and various fading models.

Channel estimation at the receiver side is essential to adaptive modulation schemes, prohibiting low complexity systems from using variable rate and/or variable power transmissions. Towards providing a solution to this problem, we introduce a variable-rate (VR) M-PSK modulation scheme, for communications over fading channels, in the absence of channel gain estimation at the receiver. The choice of the constellation size is based on the signal-plus-noise (S+N) sampling value rather than on the signal-to-noise ratio (S/N). It is analytically shown that S+N can serve as an attractive simpler criterion, alternative to S/N, for determining the modulation order in VR systems. In this way, low complexity transceivers can use VR transmissions in order to increase their spectral efficiency under an error performance constraint. As an application, we utilize the proposed VR modulation scheme in equal gain combining (EGC) diversity receivers.

This paper provides a systematic mutual information (MI) and multichannel beamforming (MBF) characterization of optimized multiple-input multiple-output (MIMO) communication systems operating in Ricean fading. These optimized configurations are of high practical importance since, contrary to the common belief, benefit from the presence of direct Line-of-Sight (LoS) components and deliver maximum multiplexing gains, by deploying specifically designed antenna arrays at both ends. In the following, using elements from random matrix theory, novel analytical expressions are derived for the exact and asymptotic MI statistics while the prevalent Gaussian approximation is examined. Moreover, new explicit expressions for the marginal eigenvalues are deduced which are thereafter used to analyze the BF performance of the associated eigenmodes in terms of Signal-to-Noise ratio (SNR) outage probability. We note that all derived formulas are given in tractable determinant form and therefore allow for fast and efficient computation and also yield an excellent match with Monte-Carlo simulations, under different fading scenarios and model parameters.

We argue for incorporating Space Division Multiple Access (SDMA) into cooperative relaying, in order to bypass orthogonal relaying transmissions and thus achieve diversity gain without any cost on the available degrees of freedom. In particular, we propose a cooperative relaying scheme that utilizes two single-antenna relays and multiple antennas at the destination terminal, in order to spatially separate the concurrently arriving signals. The whole concept is based upon two key elements: a) To combat the half-duplex constraint by having two relays transmitting alternatively, i.e., the one receiving while the other transmitting and vice versa, and b) to spatially separate the signals arriving concurrently at the destination using the well-known optimum combining technique. Closed-form expressions for the average capacity and outage probability are provided. Numerical results manifest that the proposed model outperforms orthogonal relaying as well as distributed space-time coding in terms of average capacity and outage probability, owing to the former's advantage of higher spectral efficiency.

In selective cooperative relaying only a single relay out of the set of available relays is activated, hence the available power and bandwidth resources are efficiently utilized. However, implementing selective cooperative relaying in time-varying channels may cause frequent relay switchings that deteriorate the overall performance. In this paper, we study the rate at which a relay switching occurs in selective cooperative relaying applications in time-varying fading channels. In particular, we derive closed-form expressions for the relay switching rate (measured in Hz) for opportunistic relaying (OR) and distributed switch and stay combining (DSSC). Additionally, expressions for the average relay activation time for both of the considered schemes are also provided, reflecting the average time that a selected relay remains active until a switching occurs. Numerical results manifest that DSSC yields considerably lower relay switching rates than OR, along with larger average relay activation times, rendering it a better candidate for implementation of relay selection in fast fading environments.

We study a parametric quadrature amplitude modulation (QAM) family, called θ-QAM, which includes other known constellations, such as square QAM (SQAM) and triangular QAM (TQAM), as special cases. The versatile structure of the θ-QAM signal constellation, which occurs from the varying angle between the signal points, results in achieving the minimum symbol error rate (SER) or bit error rate (BER), under an average power constraint. The theoretical study aims at providing insight into the trade-off between error performance and complexity of this parametric modulation scheme. Exact analytical expressions are obtained for the SER in additive white Gaussian Noise (AWGN) and Nakagami-m fading channels, while highly accurate BER approximations are presented. Finally, we find the optimum angles, in a minimal SER or BER sense, for a specific signal-to-noise ratio (SNR) and modulation order, M. This serves as an indicator for the appropriate constellation with respect to channel conditions and SER or BER requirements. The presented theoretical analysis is validated via extensive computer simulations.

There are several cases in wireless communications theory where the statistics of the sum of independent or correlated Nakagami-m random variables (RVs) is necessary to be known. However, a closed-form solution to the distribution of this sum does not exist when the number of constituent RVs exceeds two, even for the special case of Rayleigh fading. In this paper, we present an efficient closed-form approximation for the distribution of the sum of arbitrary correlated Nakagami-m envelopes with identical and integer fading parameters. The distribution becomes exact for maximal correlation, while the tightness of the proposed approximation is validated statistically by using the Chi-square and the Kolmogorov-Smirnov goodness-of-fit tests. As an application, the approximation is used to study the performance of equal-gain combining (EGC) systems operating over arbitrary correlated Nakagami-m fading channels, by utilizing the available analytical results for the error-rate performance of an equivalent maximal-ratio combining (MRC) system.

We present a novel approach for the accurate approximation, via closed-form expressions, of the distribution of the sum of independent and not necessarily identically distributed Gamma-Gamma (GG) variates. It is shown that the probability density function (PDF) of the GG sum can be efficiently approximated either by the PDF of a single GG distribution, or by a finite weighted sum of PDFs of GG distributions. Ascertaining on this result, the performance of multiple input multiple output (MIMO) optical wireless (OW) systems is investigated and approximative closed-form expressions for important performance metrics are derived. Numerical results and simulations illustrate the accuracy of the proposed approach.

We introduce a variable-rate (VR) M-PSK modulation scheme, for communications over fading channels, in the absence of channel gain estimation at the receiver. The choice of the constellation size is based on the signal-plus-noise (S+N) sampling value rather than on the signal-to-noise ratio (S/N). It is analytically shown that S+N can serve as an excellent simpler criterion, alternative to S/N, for determining the modulation order in VR systems. In this way, low complexity transceivers can use VR transmissions in order to increase their spectral efficiency under an error performance constraint.

In relay networks, partial channel state information at the transmitter due to feedback delay can severely degrade the beamforming performance. In this paper, the decremental effect of transmit beamforming with feedback delay on the downlink performance of a two hop Amplify-and-Forward (AF) relay network over Rayleigh fading channels is investigated. The source is equipped with multiple antennas while the relay and the destination has a single antenna. We have derived closed-form expressions for the outage probability, probability density function of the received signal-to-noise ratio (SNR) at the destination and the average bit error rate (BER). To gain further insights, outage probability and average BER approximations at high SNR are also presented. Numerical results supported by simulations are provided to illustrate the decremental effects feedback delay on the performance of the considered AF relay system.

In this paper, we explore the concept of inner and outer functions to come up with two novel parametric families of Nyquist pulses. Aside from requiring only two design parameters, the proposed pulses yield an enhanced performance compared to the sophisticated flipped-inverse hyperbolic secant (asech) pulse, that was recently presented in the literature. While the construction of parametric families originates from the work of Beaulieu and Damen, the usage of inner and outer functions guarantees a higher flexibility in the choice of the composite family members. The proposed pulses may have a slower decay rate than the well-known raised-cosine (RC) pulse, but exhibit a more pronounced decrease in the amplitudes of the two largest sidelobes and this accounts for their improved robustness to error probabilities. In the following, it is clearly demonstrated that a lower bit error rate (BER), compared to the existing pulses, can be achieved for different values of the roll-off factor and timing jitter. Moreover, a smaller maximum distortion along with a more open eye diagram are attained as well.

A major performance-limiting factor in terrestrial optical wireless (OW) systems is turbulence-induced fading. Exploiting the additional degrees of freedom in the spatial dimension, multiple laser transmitters combined with multiple receiver apertures provide an effective solution for fading mitigation. Although MIMO (multiple-input multiple-output) OW systems have been extensively studied in recent years, most of these works are mainly limited to symbol-by-symbol decoding. Maximum likelihood sequence detection (MLSD) exploits the temporal correlation of turbulence-induced fading and promises further performance gains. In this paper, we investigate MLSD for IM/DD (intensity-modulation/direct-detection) MIMO OW systems over log-normal atmospheric turbulence channels. Even with a low-order modulation scheme such as on-off keying which is typically used in OW systems, the complexity of MLSD might be prohibitive. We therefore present an iterative sequence detector based on the expectation-maximization (EM) algorithm. The complexity of the proposed algorithm is much smaller than a direct evaluation of the log-likelihood function. The Monte-Carlo simulation results demonstrate that the EM-based algorithm outperforms the symbol-by-symbol decoder and achieves a performance which lies within 0.5 dB of that of the optimal MLSD.

We present a novel and accurate approximation for the distribution of the sum of equally correlated Nakagami-m variates. Ascertaining on this result we study the performance of Equal Gain Combining (EGC) receivers, operating over equally correlating fading channels. Numerical results and simulations show the accuracy of the proposed approximation and the validity of the mathematical analysis.

We study the performance of unbalanced partially coherent uncoded and low-density parity-check (LDPC)-coded equal gain combining (EGC) receiver operating over generalized a-mu fading channels, when the binary phase-shift keying (BPSK) and quaternary phase-shift keying (QPSK) are used. We determine the bit-error ratio (BER) performance degradation due to the imperfect reference signal recovery, receiver unbalancing and fading. Furthermore, we design large girth quasi-cyclic LDPC code with high code rate, suitable for use in communications over generalized fading channels. The proposed LDPC code does not exhibit the error floor phenomena, in the region of interest, even in the presence of imperfect cophasing and receiver unbalances.

We study the performance of a parametric quadrature amplitude modulation (QAM) family, called thetas-QAM, which includes other known constellations, such as square QAM (SQAM) and triangular QAM (TQAM), as special cases. The versatile structure of the thetas-QAM signal constellation, which occurs from the varying angle between the signal points, results in achieving the minimum symbol error rate (SER) or bit error rate (BER), under an average power constraint. Exact analytical expressions are obtained for the SER performance of thetas-QAM in additive white Gaussian noise (AWGN) and Nakagami-m fading channels, while highly accurate approximations for the BER are presented. The theoretical study aims at providing insight into the tradeoff between error performance and complexity of this parametric modulation scheme. The presented theoretical analysis is validated via extensive computer simulations.

Over the last two decades, wireless communications has gained enormous popularity, offering attractive options for many personal and organizational communication needs due to major intrinsic characteristics such as flexibility, cost effectiveness, and mobility.

Second order statistics provides a dynamic representation of a fading channel and plays an important role in the evaluation and design of the wireless communication systems. In this paper, we present a novel analytical framework for the evaluation of important second order statistical parameters, as the level crossing rate (LCR) and the average fade duration (AFD) of the amplify-and-forward multihop Rayleigh fading channel. More specifically, motivated by the fact that this channel is a cascaded one and can be modeled as the product of N fading amplitudes, we derive novel analytical expressions for the average LCR and the AFD of the product of N Rayleigh fading envelopes (or of the recently so-called NRayleigh channel). Furthermore, we derive simple and efficient closed-form approximations to the aforementioned parameters, using the multivariate Laplace approximation theorem. It is shown that our general results reduce to the corresponding ones of the specific dual-hop case, previously published. Numerical and computer simulation examples verify the accuracy of the presented mathematical analysis and show the tightness of the proposed approximations.

Monotonicity criteria are established for the generalized MarcumQ-function,QM(alpha,beta), the standard NuttallQ-function,QM,N(alpha,beta) , and the normalized NuttallQ-function,QM,N(alpha,beta), with respect to their real order indicesM,N. Besides, closed-form expressions are derived for the computation of the standard and normalized NuttallQ-functions for the case whenM,Nare odd multiples of 0.5 andMgesN. By exploiting these results, novel upper and lower bounds forQM,N(alpha,beta) andQM,N(alpha,beta) are proposed. Furthermore, specific tight upper and lower bounds forQM(alpha,beta), previously reported in the literature, are extended for real values ofM. The offered theoretical results can be efficiently applied in the study of digital communications over fading channels, in the information-theoretic analysis of multiple-input multiple-output systems and in the description of stochastic processes in probability theory, among others.

In real wireless communication environments, it is highly likely that different channels associated with a relay network could experience different fading phenomena. In this paper, we investigate the end-to-end performance of a dual-hop fixed gain relaying system when the source-relay and the relay-destination channels experience Rayleigh/Rician and Rician/Rayleigh fading scenarios respectively. Analytical expressions for the cumulative distribution function of the end-to-end signal-to-noise ratio are derived and used to evaluate the outage probability and the average bit error probability of M-QAM modulations. Numerical and simulation results are presented to illustrate the impact of the Rician factor on the end-to-end performance. Furthermore, these results confirm that the system exhibits an improved performance in a Rician/Rayleigh (source-relay link/relay-destination link) environment compared to a Rayleigh/Rician environment.

Optical wireless, also known as free-space optics, has received much attention in recent years as a cost-effective, license-free and wide-bandwidth access technique for high data rates applications. The performance of free-space optical (FSO) communication, however, severely suffers from turbulence-induced fading caused by atmospheric conditions. Multiple laser transmitters and/or receivers can be placed at both ends to mitigate the turbulence fading and exploit the advantages of spatial diversity. Spatial diversity is particularly crucial for strong turbulence channels in which single-input single-output (SISO) link performs extremely poor. Atmospheric-induced strong turbulence fading in outdoor FSO systems can be modeled as a multiplicative random process which follows the K distribution. In this paper, we investigate the error rate performance of FSO systems for K-distributed atmospheric turbulence channels and discuss potential advantages of spatial diversity deployments at the transmitter and/or receiver. We further present efficient approximated closed-form expressions for the average bit-error rate (BER) of single-input multiple-output (SIMO) FSO systems. These analytical tools are reliable alternatives to time-consuming Monte Carlo simulation of FSO systems where BER targets as low as 10-9are typically aimed to achieve.

We present a novel analytical framework for the evaluation of important second order statistical parameters, as the level crossing rate (LCR) and the average fade duration (AFD) of the amplify-and-forward multihop Rayleigh fading channel. More specifically, motivated by the fact that this channel is a cascaded one, which can be modelled as the product of N fading amplitudes, we derive novel analytical expressions for the average LCR and AFD of the product of N Rayleigh fading envelopes, or of the recently so-called N*Rayleigh channel. Furthermore, we derive simple and efficient closed-form approximations to the aforementioned parameters, using the multivariate Laplace approximation theorem. It is shown that our general results reduce to the specific dual-hop case, previously published. Numerical and computer simulation examples verify the accuracy of the presented mathematical analysis and show the tightness of the proposed approximations.

We propose a communication system that utilizes two relays and multiple receiving antennas, in order to spatially separate the signals arriving concurrently at the destination and thus avoid the need for orthogonal transmissions in either the frequency or the time domain. The whole concept is based upon two key elements: a) To combat the half-duplex constraint by having two relays transmitting alternatively, i.e., the one receiving while the other transmitting and vice versa, and b) to separate the signals arriving concurrently at the destination using the well-known space division multiple access (SDMA) technique. Numerical results manifest that the proposed model outperforms conventional relaying in terms of outage probability, due to the former's advantage of higher spectral efficiency.

We propose a low-complexity amplify and forward relaying scheme that avoids channel amplitude estimations by combining the signals associated with the individual relays into an equal gain combiner (EGC). An approximate performance analysis of such scheme is conducted using the well-known moments-based approach. Additionally, motivated by the so-called EGC's combining loss, we propose an algorithmic method that sorts out the weakest relayed branches (in a long-term sense), aiming at activating only the relays that substantially contribute to the overall system performance.

Free-space optical (FSO) communication has received much attention in recent years as a cost-effective, license-free and wide-bandwidth access technique for high data rates applications. The performance of FSO communication, however, severely suffers from turbulence-induced fading caused by atmospheric conditions. Multiple laser transmitters and/or receivers can be placed at both ends to mitigate the turbulence fading and exploit the advantages of spatial diversity. Spatial diversity is particularly crucial for strong turbulence channels in which single-input single-output (SISO) link performs extremely poor. Atmospheric-induced strong turbulence fading in outdoor FSO systems can be modeled as a multiplicative random process which follows the K distribution. In this paper, we investigate the error rate performance of FSO systems for K-distributed atmospheric turbulence channels and potential advantages of spatial diversity deployments at the transmitter and/or receiver. Our results demonstrate significant diversity gains of multiple transmitter/receivers deployment in FSO channels. We further present efficient approximated closed-form expressions for the average bit-error rate (BER) of multiple-input single-output (MISO) and single-input multiple-output (SIMO) FSO systems. These analytical tools are reliable alternatives to time-consuming Monte Carlo simulation of FSO systems where BER targets as low as 10-9are typically aimed to achieve.

Recently, Multi-User Selection Diversity (MUSDiv) for single-carrier systems has been under extensive study on account of the enhancement it provides to system performance with minimum feedback requirements. However, its application to multichannel systems is considered straightforward and thus, it has not been thoroughly examined. In this paper, the performance of MUSDiv is investigated when applied to the spread-spectrum multi-carrier multiple-access system, where the scheduling has to be performed for all the available channels and self interference must also be considered. Specifically, based on the absolute and normalized Signal-to-Noise-Ratio (SNR) scheduling algorithms, two algorithms are presented, modified and optimized, so that they can be applied on a subband instead of a single-channel basis. Moreover, we propose a new scheduling scheme which constitutes a trade-off between the previous schemes, concerning fairness and capacity performance. The new algorithms are related to the symbol Signal-to-Noise-plus-Interference-Ratio (SNIR) instead of SNR and two interference models were devised to this end. Closed-form expressions for the system capacity are extracted for each case, which are compared with simulation results. The research is also extended to the case of non-identical user power profiles among the available subcarriers. The channel state information required to utilize multi-user selection diversity is already necessary for the most common combining schemes, so no more feedback is actually needed.

We study a distributed version of switch-and-stay combining (DSSC) for systems that utilize two relays. In particular, four different scenarios are considered, depending on a) whether or not the source-destination channel is taken into account, and b) the type of relaying, i.e., decode and forward or amplify and forward. A performance analysis in terms of outage and bit error probability is presented, when operating over Rayleigh fading channels. Numerical results demonstrate that two-relay DSSC achieves the same diversity gain and outage performance as if the best relay is selected for each transmission slot, albeit simpler.

We introduce an adaptive generalized selection combining (A-GSC) receiver that can be efficiently applied in diversity rich fading environments such as in ultra-wideband applications. The branches that participate in the combining process are selected taking into account the quality of both the total combining output signal-to-noise ratio (SNR) and the individual SNR of each branch. The proposed scheme achieves better adaptation to channel conditions compared to other competing schemes such as normalized threshold GSC (NT-GSC), minimum selection GSC (MS-GSC) or minimum estimation and combining GSC (MEC-GSC), with no further complexity. The A-GSC receiver compromises between the power consumption, hardware complexity and performance gain that each additional diversity branch induces, resulting in significant savings in power and computational resources.

We deal with the concept of physical-layer fairness in amplify and forward cooperative diversity systems, which reflects the need for equally allocating the consumed power among the relays. To this end, we propose a method which utilizes knowledge on both the instantaneous and average channel conditions in order to encompass this concept, by attributing a weight coefficient to each relay depending on its average channel state and then selecting the relay with the best instantaneous "weighted" channel conditions. We also provide a performance analysis of the proposed scheme that includes an analytical expression for the outage probability, together with a closed form one in the high signal-to-noise-ratio (SNR) regime. Through the latter expression, the average symbol error probability (ASEP) for high SNRs is also derived. Numerical results demonstrate that, for small number of available relays or for high SNRs, the performance of the proposed scheme resembles that of the "best relay selection" scheme, in terms of outage probability and ASEP, despite maintaining the average power consumptions equal.

We provide closed-form expressions for the outage and bit error probability (BEP) of uncoded, threshold-based opportunistic relaying (OR) and selection cooperation (SC), at arbitrary signal to noise ratios (SNRs) and number of available relays, assuming decode-and-forward relays and Rayleigh fading channels. Numerical results demonstrate that SC performs slightly better in terms of outage probability; in terms of BEP, both systems may outperform one another, depending on the SNR threshold that determines the set of relays that participate in the forwarding process.

Motivated by the transmit antenna selection (TAS) concept, used in Multiple-Input-Multiple-Output systems, we argue fordistributedtransmitantennaselection(DTAS), which corresponds to a method of selecting a subset of available relays in cooperative diversity systems. Assuming amplify and forward relays, the proposed selection method represents a low-complexity tool for determining the optimum relaying set. Two optimization problems are studied: the error probability minimization subject to total energy consumption constraints, and the dual one, the total energy consumption minimization under error performance constraints. Numerical examples verify the advantage of the proposed method in adapting the number of relaying terminals to the desired performance-consumption tradeoff.

We introduce the concept of fairness at the physical- layer in amplify and forward cooperative diversity systems, which reflects the need for equally allocating the consumed power among the relays. To this end, we propose a relay-selection method, which utilizes knowledge on both the instantaneous and average channel conditions in order to encompass this concept. We also provide a closed-form expression for the outage probability in the high signal to noise ratio (SNR) regime. Numerical results show that the outage performance of the proposed scheme resembles closely the performance of the "best relay selection" scheme, albeit maintaining the average power consumptions equal.

Motivated by the well-known knapsack problem, we propose an efficient algorithmic method that minimizes and optimally allocates the total transmitting power in transmitter diversity systems, provided that the instantaneous bit-error- rate (BER) is not greater than a predetermined value. We also provide closed-form expressions for the average total transmitted power for the case of two transmitting antennas operating in Rayleigh fading, and the average number of active antennas at the transmitter assuming Nakagami-m fading channels. Simulations and numerical results show that, compared to the conventional equi-power scheme, the proposed model offers a considerable reduction in the total transmitting power and the average number of active antennas, without loss in error performance.

Analytical expressions concerning the capacity and bit error rate (BER) of multiple-input multiple-output systems with space-time block coding (STBC) are derived. Two fading environments are examined, log-normal and Rician channels. A tight closed-form upper bound is presented for the BER of systems operating in log-normal fading environments in addition to an upper bound for the capacity of this type of systems. The latter bound applies to systems that operate under Rician fading as well. The analytical results were validated against ample numerical simulations for three STBC schemes and three phase-shift-keying modulations. The proposed bounds proved to be a tractable way to evaluate the system performance when no closed-form expression for the probability density function or the moment generating function is known.

We examine the performance of a dual-hop nonregenerative system with adjustable relay gain, subject to power constraints. An optimization problem is formulated and solved algorithmically for the binary phase-shift keying bit-error rate utility. The model allows for arbitrary channel statistics. Emphasis is placed on the relation between the optimal solutions obtained when observing the channels of either the first or both hops, as well as the comparison with easily implementable heuristic policies. Numerical results indicate that simple heuristics perform well for a wide range of signal-to-noise ratio (SNR), except for certain high-SNR cases. Finally, the effect of independent channel assumption on system performance is evaluated.

A generic and novel distribution, referred to as Nakagami, constructed as the product ofNstatistically independent, but not necessarily identically distributed, Nakagami-mrandom variables (RVs), is introduced and analyzed. The proposed distribution turns out to be a very convenient tool for modelling cascaded Nakagami-mfading channels and analyzing the performance of digital communications systems operating over such channels. The moments-generating, probability density, cumulative distribution, and moments functions of theN*Nakagami distribution are developed in closed form using the Meijer's G -function. Using these formulas, generic closed-form expressions for the outage probability, amount of fading, and average error probabilities for several binary and multilevel modulation signals of digital communication systems operating over theN*Nakagami fading and the additive white Gaussian noise channel are presented. Complementary numerical and computer simulation performance evaluation results verify the correctness of the proposed formulation. The suitability of theN*Nakagami fading distribution to approximate the lognormal distribution is also being investigated. Using Kolmogorov--Smirnov tests, the rate of convergence of the central limit theorem as pertaining to the multiplication of Nakagami-mRVs is quantified.

We present an optimum diversity receiver called blind ratio combining (BRC), which minimizes the average symbol error probability or maximizes the average output signal-to-noise ratio, where the channels' time delays and the random phases are known while the fading amplitudes are unknown. In contrast to previous works where efforts were made to finda posterioriprobabilities at the receiver, the BRC simply calculates the optimum weights, which depend on the channel's statistics, avoiding continuous channel estimation, and thus, it significantly reduces the system's complexity. In nonidentical multipath fading channels with power delay profile (PDP), the BRC receiver performs between maximal ratio combining (MRC) and equal gain combining (EGC), and attains to keep its performance comparable—and in some cases superior—to that of generalized selection combining (GSC), while for large values of the decay factor it approaches MRC. Moreover, in the important practical case of exponential PDP—common in RAKE receivers modeling and adopted for the Universal Mobile Telecommunications System (UMTS) spatial channel modeling by the European Telecommunications Standards Institute-Third Generation Partnership Project (ETSI-3GPP)—the optimum weights can be accurately approximated by simple elementary functions. Furthermore, it is proved that the utilization of these weights ensures an error performance improvement over EGC for arbitrary PDPs. The proposed BRC receiver can be efficiently applied in wireless wideband communication systems, where a large number of diversity branches exists, due to the strong multipath effects.

We present an optimum diversity receiver called blind ratio combining (BRC) that minimizes the average symbol error probability or maximizes the average output SNR, where the channels' time delays and the random phases are known, while the fading amplitudes are unknown. In contrast to previous works, where efforts were made to find a posteriori probabilities at the receiver, the BRC simply calculates the optimum weights, which depend on the channel's statistics, avoiding continuous channel estimation, and thus, it significantly reduces the system's complexity. In nonidentical multipath fading channels with power delay profile (PDP), the BRC receiver performs between maximal ratio combining (MRC) and equal gain combining (EGC), and keeps its performance comparable - and in some cases superior - to that of generalized selection combining, while for large values of the decay factor, it approaches MRC. Moreover, in the important practical case of exponential PDP - common in RAKE receivers modeling and adopted for the Universal Mobile Telecommunications System spatial channel modeling by the European Telecommunications Standards Institute-3GPP - the optimum weights can be accurately approximated by simple elementary functions. Furthermore, it is proved that the utilization of these weights ensures an error performance improvement over EGC for arbitrary PDPs. The proposed BRC receiver can be efficiently applied in wireless wideband communication systems, where a large number of diversity branches exists, due to the strong multipath effects.

We introduce the channel quality estimation index (CQEI) as an alternative improved long-term performance criterion for wireless communications systems operating over fading channels. CQEI is simple to evaluate, since it depends on the channel statistics which vary much more slowly than the channel state itself, and thus can be obtained at the initialization state using a long training sequence and afterwards continuously improved during the whole communication period. Considering generalized fading channels (Nakagami-m, Nakagami-n, Nakagami-q) and a variety of modulations, we show that CQEI assesses the average error performance of a communication system more efficiently, compared to other long- term performance criteria such as the average signal to noise ratio (ASNR) and the amount of fading (AoF). As an application, we utilize CQEI to present a new class of equal gain combining (EGC) receivers operating over non-identical independent fading channels, called selection-EGC (S-EGC). This kind of receivers reduces or eliminates the combining loss by rejecting the weak branches that contribute more to increasing the noise than the signal during the combining stage. S-EGC could be efficiently applied in the emerging broadband communication systems (e.g., ultra-wideband), where the number of diversity paths can be considerably large due to the strong multipath effects. Numerical results show that the new proposed selection-EGC (S-EGC) receiver outperforms the classical one, when fading with non- identically distributed diversity branches is assumed.

To compute the optimal bias in equal-gain combining (EGC) receivers with unequal energy constellations such as M-ary pulse amplitude modulation (M-PAM) and M-ary square quadrature amplitude modulation (M-QAM), the estimation of the instantaneous fading gain magnitude in each diversity branch is needed, thus defeating the usefulness of EGC. In this paper, we present an exact analytical equation, which can be efficiently used to compute a suboptimal value for the bias, both for M-PAM and M-QAM constellations. The proposed suboptimal bias minimizes the symbol error probability, and depends on the statistics of the fading gain magnitudes and not on their instantaneous values. For the case of large number of branches, where the central limit theorem can be applied, the proposed equation for the computation of the suboptimal bias is derived hi closed-form. Moreover, an approximate simple closed-form expression for the suboptimal bias is obtained, suitable for the high signal-to-noise ratio region. Numerical results verify the correctness and the accuracy of the proposed analytical formulation

Multi-user cooperative diversity is a recent technique promising great improvement of the performance of wireless communication systems operating in fading environments. Based on combinatorial optimization theory and specifically on the so-called knapsack problem, this paper presents a method of optimizing the selection among the potential cooperating users, when amplify-and-forward relays are used. In particular, two optimization problems are studied: the error probability minimization subject to total energy consumption constraints, and the dual one, the energy consumption minimization under error performance constraints. Depending on the frequency of repeating this selection, the above problems are categorized into short-term and long-term node selection. Numerical examples verify the expected knapsack scheme's advantage of adapting the number of cooperating users, depending on the desired performance-consumption tradeoff. Moreover, long-term node selection seems to lead to similar error or consumption performance compared to the short-term one, despite its simplicity.

This paper examines the performance of a dualhop, noise-limited, non-regenerative system where the relay gain is allowed to vary as an unknown deterministic function of the channel states, subject to instantaneous (i.e. peak) and average power constraints, the latter directly affecting battery lifetime in wireless systems. A convex optimization problem, in terms of a generic performance metric, is formulated and solved algorithmically for the Signal-to-Noise Ratio (SNR), Shannon rate and BPSK Bit-Error-Rate (BER) utilities. The presented model allows for arbitrary statistics of the fading channels, including correlation between them. Special emphasis is placed on the relation between the optimal solutions obtained when observing the channels of either the first or both hops. The regions in channel state space where zero and full power is allocated are determined in closed form, with numerical results being presented for the Shannon rate and BER utilities. It is observed that, for sufficiently high first hop SNR, monitoring both channels instead of just the first hop can lead to a significant performance increase.

In this paper, we study the performance of multihop free-space optical (FSO) wireless systems over turbulence-induced fading channels. The analysis is carried out for systems employing amplify-and-forward (AF) or decode-and-forward (DF) relays and for turbulence channels which can be modeled by the Gamma-Gamma distribution. An exact analytical expression for the end-to-end outage probability of AF systems is obtained, while a closed-form expression of DF systems is derived. The average bit-error probability of a dual-hop FSO system employing a DF relay is studied as a special case. Numerical examples are also presented to illustrate the proposed analysis and to further investigate the effects of the turbulence severity on the multihop FSO systems' performance.

The end-to-end performance of a dual-hop relaying system operating over independent, non-identical Nakagami-m fading channels, is analyzed and evaluated. Closed-form expressions for the cumulative distribution function, the probability density function, the moments and the moment generating function of the end-to-end signal-to-noise ratio (SNR), are derived. Using these results, closed-form expressions for the outage probability are presented for both channel state information and fixed-gain relays. Furthermore, for the case of fixed-gain relay, the average end-to-end SNR, the amount of fading and the average bit-error rate are also expressed in closed-form. The proposed mathematical analysis is complemented by numerical examples, including the effects on the overall performance of the SNRs unbalancing as well as the fading severity

The symbol error probability (SEP) performance of time-hopping (TH) ultra-wideband (UWB) systems in the presence of multiuser interference (MUI) and timing jitter is considered without making the usual Gaussian approximation (GA). Contrary to previous studies restricted to binary modulation formats, we analyze and evaluate the performance of such multiuser TH-UWB systems employing M-ary pulse position modulation (PPM) and a correlation receiver. Using the Gaussian quadrature rules (GQR) method and by considering the correlator outputs to be statistically independent, a semi-analytical method for the SEP evaluation is proposed. Furthermore, by modeling the timing jitter as a Gaussian process, we study the degradation it causes on the overall system performance (SEP and capacity). The accuracy of the proposed approach has been verified by means of computer simulations. Furthermore, a comparison with equivalent performance results obtained using the GA has provided precise conditions where this approximation should not be used.

We present closed-form expressions for the probability density function (PDF) and the cumulative distribution function (CDF) of the sum of non-identical squared Nakagami-m random variables (RVs) with integer-order fading parameters. As it is shown, they can be written as a weighted sum of Erlang PDFs and CDFs, respectively, while the analysis includes both independent and correlated sums of RVs. The proposed formulation significantly improves previously published results, which are either in the form of infinite sums or higher order derivatives of the fading parameter m. The obtained formulas can be applied to the performance analysis of diversity combining receivers operating over Nakagami-m fading channels

We present closed-form lower bounds for the performance of multihop transmissions with nonregenerative relays over not necessarily identically distributed Nakagami-m fading channels. The end-to-end signal-to-noise ratio is formulated and upper bounded by using an inequality between harmonic and geometric means of positive random variables (RVs). Novel closed-form expressions are derived for the moment generating function, the probability density function, and the cumulative distribution function of the product of rational powers of statistically independent Gamma RVs. These statistical results are then applied to studying the outage probability and the average bit-error probability for phase- and frequency-modulated signaling. Numerical examples compare analytical and simulation results, verifying the tightness of the proposed bounds.

The authors reply to the comment by Simon (IEEE Trans. Commun., vol.54, no.8, p.1511-12, 2006 August) on their original paper (Zogas and Karagiannidis, IEEE Trans. Commun., vol.53, no.11, p.1970-4, 2005 November)

In this letter, efficient performance bounds for multihop wireless communications systems with non-regenerative blind relays over non-identical Nakagami-n (Rice), Nakagami-m and Nakagami-q (Hoyt) generalized fading channels, are presented. More specifically, the end-to-end signal-to-noise ratio (SNR) is formulated and upper bounded by using the well-known inequality between harmonic and geometric mean of positive random variables. This bound is used to study important system's performance metrics: i) the moments of the end-to-end SNR which are obtained in closed-forms, and ii) the outage probability and the average error probability for coherent and non-coherent modulations, which are accurately approximated using the moments-based approach. Furthermore, new analytical formulae are derived for the gain of previously proposed semi-blind relays in generalized fading environments. These kind of relays are used in numerical examples and computer simulations to verify the accuracy and to show the tightness of the proposed bounds.

This paper presents a new approach in analyzing the reverse link capacity performance of cellular CDMA systems employing successive interference cancellation (SIC). Due to the controlled power disparity present in such systems previous methods cannot precisely model their inter-cell interference. We first introduce a novel model which allows the accurate analysis and evaluation of the inter-cell interference of cellular CDMA systems with controlled power disparity. Its validity is verified by means of theoretical analysis and computer simulations. Secondly, by using this new inter-cell interference model, a theoretical analysis of the CDMA reverse link capacity is presented. In terms of evaluation results, we focus on the performance improvements SIC offers as compared to single user detection (SUD). Analytical results complemented by equivalent computer simulated performance evaluation results have shown that SIC significantly increases the reverse link capacity of cellular CDMA systems operating in realistic controlled power disparity environments.

A versatile envelope distribution which generalizes many commonly used models for multipath and shadow fading is the so-called generalized Gamma (GG) distribution. By considering the product of N GG random variables (RV)s, novel expressions for its moments-generating, probability density, and cumulative distribution functions are obtained in closed form. These expressions are used to derive a closed-form union upper bound for the distribution of the sum of GG distributed RVs. The proposed bound turns out to be an extremely convenient analytical tool for studying the performance of TV-branch equal-gain combining receivers operating over GG fading channels. For such receivers, first the moments of the signal-to-noise (SNR) at the output, including average SNR and amount of fading, are obtained in closed form. Furthermore, novel union upper bounds for the outage and the average bit error probability are derived and evaluated in terms of Meijer's G-functions. The tightness of the proposed bounds is verified by performing comparisons between numerical evaluation and computer simulations results

We present closed-form bounds for the performance of multihop transmissions with non-regenerative relays over Nakagami-m fading channels. The end-to-end signal-to-noise ratio (SNR) is formulated and upper bounded by using the inequality between harmonic and geometric mean of positive random variables (RVs). Novel closed-form expressions are derived for the moment generating function, the probability density function, and the cumulative distribution function of the product of arbitrary powers of statistically independent Gamma RVs in terms of the Meijer's G-function. Using these theoretical results, closed-form lower bounds are obtained for the outage and average bit error probability of phase or frequency modulated signallings, while simple asymptotic expressions are also given for the bounds at high SNRs. Numerical results are compared to computer simulations, to show the tightness of the proposed bounds.

Analytical expressions for the evaluation of the bivariate Rician cumulative distribution function (CDF), the covariance, and the characteristic function (CHF) are not known, despite their usefulness in wireless communications systems analysis. In this letter, motivated by the ability of the Rician model to describe fading in wireless communications, we derive infinite-series representations for the probability density function, the CDF, the covariance, and the CHF of two correlated Rician random variables. It is shown that the presented infinite-series expressions converge rapidly, and can be efficiently used to study several performance criteria for dual-diversity receivers operating over correlated Rician fading channels.

Ascertaining on the suitability of the Weibull distribution to model fading channels, a theoretical framework for a class of multivariate Weibull distributions, originated from Gaussian random processes, is introduced and analyzed. Novel analytical expressions for the joint probability density function (pdf), moment-generating function (mgf), and cumulative distribution function (cdf) are derived for the bivariate distribution of this class with not necessarily identical fading parameters and average powers. Two specific distributions with arbitrary number of correlated variates are considered and studied: with exponential and with constant correlation where their pdfs are introduced. Both cases assume equal average fading powers, but not necessarily identical fading parameters. For the multivariate Weibull distribution with exponential correlation, useful corresponding formulas, as for the bivariate case, are derived. The presented theoretical results are applied to analyze the performance of several diversity receivers employed with selection, equal-gain, and maximal-ratio combining (MRC) techniques operating over correlated Weibull fading channels. For these diversity receivers, several useful performance criteria such as the moments of the output signal-to-noise ratio (SNR) (including average output SNR and amount of fading) and outage probability are analytically derived. Moreover, the average symbol error probability for several coherent and noncoherent modulation schemes is studied using the mgf approach. The proposed mathematical analysis is complemented by various evaluation results, showing the effects of the fading severity as well as the fading correlation on the diversity receivers performance.

We study the performance of L-branch equal-gain combining (EGC) and maximal-ratio combining (MRC) receivers operating over nonidentical Weibull-fading channels. Closed-form expressions are derived for the moments of the signal-to-noise ratio (SNR) at the output of the combiner and significant performance criteria, for both independent and correlative fading, such as average output SNR, amount of fading and spectral efficiency at the low power regime, are studied. We also evaluate the outage and the average symbol error probability (ASEP) for several coherent and noncoherent modulation schemes, using a closed-form expression for the moment-generating function (mgf) of the output SNR for MRC receivers and the Pade/spl acute/ approximation to the mgf for EGC receivers. The ASEP of dual-branch EGC and MRC receivers is also obtained in correlative fading. The proposed mathematical analysis is complimented by various numerical results, which point out the effects of fading severity and correlation on the overall system performance. Computer simulations are also performed to verify the validity and the accuracy of the proposed theoretical approach.

In mobile radio systems, antenna diversity is used to combat fading and reduce the impact of cochannel interference. In this paper, we analyze the performance of L-branch equal-gain combining receivers over correlated nonidentically distributed Nakagami-m fading channels, in the presence of multiple identical cochannel interferers and additive white Gaussian noise. The performance criterion considered is the average output signal-to-interference-plus-noise ratio, which is obtained in closed form for both independent and correlative fading. Due to the simple form of the derived expressions, they readily allow numerical evaluation for cases of practical interest.

Motivated by the importance of Nakagami-n (Rice) and Nakagami-q (Hoyt) statistical models to describe channel fading in land, mobile, terrestrial, and satellite telecommunications, we present an alternative moments-based approach to the performance analysis of equal-gain combining (EGC) receivers over independent, not necessarily identically distributed Rice- and Hoyt-fading channels. Exact closed-form expressions for the moments of the signal-to-noise ratio (SNR) at the output of the combiner are derived and significant performance criteria such as, the average output SNR, the amount of fading and the spectral efficiency at the low power regime, are studied. Moreover, using Pade rational approximation to the moment-generating function of the output SNR, the average symbol error probability and the outage probability are evaluated. We also study the suitability of modeling a Hoyt-fading environment by a properly chosen Nakagami-m model, as far as the error performance of the EGC is concerned.

Efficient performance bounds for multihop wireless communications systems with non-regenerative fixed-gain relays operating over non-identical generalized fading channels, are presented. More specifically, the end-to-end signal-to-noise ratio (SNR) is formulated and upper bounded by using the well-known inequality between harmonic and geometric mean of positive random variables. Based on this bound, the moments of the end-to-end SNR for Rayleigh, Nakagami-m, and Rice fading channels, are obtained in simple closed-forms. Furthermore, the outage performance and the average error probability for coherent and non-coherent modulation schemes are also studied using the moment-generating function (MGF) approach. The proposed method for the evaluation of the MGF is based on the Pade approximants theory. Moreover, new expressions are derived for the gain of previously proposed "semi-blind" relays. These expressions are used in numerical and computer simulations examples, to verify the accuracy and to show the tightness of the proposed bounds.

Motivated by the suitability of the Weibull distribution to model multipath fading channels, the performance of L-branch selection combining (SC) receivers, with non-identical statistics, is presented. Deriving a useful expression for the probability density function of the SC output signal-to-noise ratio (SNR), important performance metrics are studied. More specifically, a closed-form expression is derived for the moments of the combiner output SNR, which is used to study the average output SNR and the amount of fading. The average symbol error probability for several coherent and non-coherent, binary and multilevel modulation schemes is also obtained in closed-form.

The performance of dual-branch SC receivers over correlated Weibull fading channels is studied in this paper. Exact closed-form expressions are derived for the probability/cumulative density functions and the moments of the output signal-to-noise ratio (SNR). Important performance criteria, such as average output SNR, amount of fading (AoF), outage probability and average bit error probability (ABEP) for several modulation schemes, are studied and novel closed-form analytical expressions are derived. The proposed analysis is complemented by various performance evaluation results, including the effects of input SNRs unbalancing, fading severity and fading correlation on the overall system performance. Computer simulations results verify the validity and the accuracy of the proposed analysis.

Motivated by the suitability of the Weibull distribution to model multipath fading channels, the second order statistics and the spectral efficiency (SE) of L-branch SC receivers are studied. Deriving a novel closed-form expression for the probability density function (pdf) of the SC output SNR, the average level crossing rate (LCR), the average fade duration (AFD) and the Shannon's average SE, at the output of the SC, are derived in closed-forms. Our results are sufficiently general to handle arbitrary fading parameter and dissimilar branch powers.

In this letter, an alternative moments-based approach for the performance analysis of an L-branch predetection equal gain combiner (EGC) over independent or correlated Nakagami-m fading channels is presented. Exact closed-form expressions are derived for the moments of the EGC output signal-to-noise ratio (SNR), while the corresponding moment-generating function (MGF) is accurately approximated with the aid of Pade/spl acute/ approximants theory. Important performance criteria are studied; the average output SNR, which is expressed in closed form both for independent and correlative fading and for arbitrary system parameters, the average symbol-error probability for several coherent, noncoherent, and multilevel modulation schemes, and the outage probability, which are both accurately approximated using the well-known MGF approach. The proposed mathematical analysis is illustrated by various numerical results, and computer simulations have been performed to verify the validity and the accuracy of the theoretical approach.

In this letter, an approach to the evaluation of the error performance in dual predetection equal-gain combining (EGC) systems over correlated Nakagami-m fading channels is presented. Deriving an infinite series representation for the characteristic function of the sum of two correlated Nakagami-m variables, a closed-form formula is extracted for binary phase-shift keying and coherent binary frequency-shift keying, while several other modulation schemes are studied, capitalizing on a Parsevals's theorem-based approach, previously published. Numerical results and simulations are also presented to illustrate the proposed mathematical analysis and to point out the effect of the input signal-to-noise ratio unbalancing, the fading severity, and the fading correlation on the system's error performance.

Ascertaining the importance of the dual selection combining (SC) receivers and the suitability of the Weibull model to describe mobile fading channels, we study the performance of a dual SC receiver over correlated Weibull fading channels with arbitrary parameters. Exact closed-form expressions are derived for the probability density function, the cumulative distribution function, and the moments of the output signal-to-noise ratio (SNR). Important performance criteria, such as average output SNR, amount of fading, outage probability, and average bit-error probability for several modulation schemes are studied. Furthermore, for these performance criteria, novel closed-form analytical expressions are derived. The proposed analysis is complemented by various performance evaluation results, including the effects of the input SNR's unbalancing, fading severity, and fading correlation on the overall system's performance. Computer simulation results have verified the validity and accuracy of the proposed analysis.

Previous studies have addressed with the performance analysis of L-branch equal gain combining (EGC) systems over independent Rayleigh- or Nakagami-m fading channels. In this paper, important statistical parameters, such as the /spl kappa/-moment, the /spl kappa/-central moment, the skewness, and the kurtosis of the output signal-to-noise ratio (SNR), in predetection EGC systems operating over correlated Nakagami-m fading channels are studied. Simple closed-form expressions for the mean and variance of the output SNR are presented and it is shown that our general results reduce to the specific noncorrelative fading case previously published. Moreover, significant performance criteria such as the amount of fading and the spectral efficiency in the low power regime, are investigated. Numerical results and simulations are presented to check the validity of the proposed mathematical analysis and to point out the impact of the fading correlation, the input SNRs unbalancing as well as the fading severity, on the EGC performance.

An exact and rapidly converging infinite series for the average output signal-to-noise ratio in a triple selection diversity system, over correlated Nakagami-m fading channels, is presented. Numerical results are presented to illustrate the proposed approach and to point out the effect of the fading correlation to the performance of the combiner, as well as the improvement achieved by the triple selection combining compared to the dual diversity case.

In this paper, important statistical parameters, such as the k-moment and the k-central moment, of the output signal-to-noise ratio (SNR), in predetection equal-gain combining (EGC) systems operating over correlated Nakagami-m fading channels are studied. Simple closed-form expressions for the mean and variance of the output SNR are presented. Furthermore, it is shown that our general results reduce to the specific noncorrelative fading case previously published. Moreover, significant performance criteria for the EGC such as amount of fading (AoF) and spectral efficiency in the low power regime are investigated. Numerical and simulation results are presented validating the proposed mathematical analysis. These results also point out the impact of the fading correlation, the input SNRs unbalancing as well as the fading severity, on the EGC performance.

Capitalizing on the proof of a theorem presented by L.E. Blumenson and K.S. Miller (see Ann. Math. Statist., vol.34, p.903-10, 1963), we propose a useful closed formula for the exponentially correlated n-variate Nakagami-m probability density function. Moreover, an infinite series approach for the corresponding cumulative distribution function is presented. Bounds on the error resulting from the truncation of the infinite series are also derived. Finally, in order to check the accuracy of the proposed formulation, numerical results are presented.

An approach to the performance analysis of a triple selection-diversity system over exponentially correlated Nakagami-m fading channels is presented. Closed-form expressions of converged sums for both outage and average error probabilities are derived. Numerical results are presented to point out the effect of the fading correlation, the fading severity, as well as the improvement achieved by the triple selection combining compared with the corresponding dual diversity case.

An efficient approach for the evaluation of the Nakagami-m (1960) multivariate probability density function (PDF) and cumulative distribution function (CDF) with arbitrary correlation is presented. Approximating the correlation matrix with a Green's matrix, useful closed formulas for the joint Nakagami-m PDF and CDF, are derived. The proposed approach is a significant theoretical tool that can be efficiently used in the performance analysis of wireless communications systems operating over correlative Nakagami-m fading channels.

A useful formulation for the multivariate Rayleigh probability density function (PDF) with an exponential form for its correlation matrix is presented. Furthermore, the corresponding multivariate Rayleigh cumulative distribution function (CDF) is derived in a nested infinite series representation, which converges rapidly and can be efficiently used in many wireless applications with diversity reception. Finally, bounds on the error resulting from truncation of the infinite series are also derived.