This paper introduces delay-alignment modulation (DAM) for secure integrated sensing and communication (ISAC). Due to the broadcast nature of multi-user downlinks, communications are vulnerable to eavesdropping. DAM applies controlled per-path symbol delays at the transmitter to coherently align the multipath components at the intended user, enhancing the received signal power, while simultaneously creating delay misalignment at the eavesdropper (Eve). To mitigate sensing degradation caused by multipath propagation, we propose a two-stage protocol that first estimates the angle and then the delay of the line-of-sight (LoS) path after suppressing multipath interference. We derive the secrecy spectral efficiency (SSE) and the Cramer–Rao bound (CRB) of the target delay. Finally, we develop a path-based zero-forcing (ZF) precoding framework and formulate a max–min SSE design under CRB and power constraints. Simulation results show DAM significantly outperforms the strongest-path (SP) benchmark in terms of SSE, while meeting sensing requirements, since intentional delay alignment at legitimate users degrades Eve’s reception.

This paper proposes a distributed continuous aperture array (D-CAPA) to support simultaneous wireless information and power transfer (SWIPT) to multiple information users (IUs) and energy users (EUs). Each metasurface supports continuous surface currents that radiate electromagnetic (EM) waves for information and energy transmission to the users. These waves propagate through continuous EM channels characterized by the dyadic Green’s function. We formulate a system power consumption (PC) minimization problem subject to spectral efficiency and energy harvesting quality-of-service (QoS) requirements, where the QoS requirements are derived under the equal power allocation (EPA) scheme. An efficient two-layer optimization algorithm is developed to solve this problem by optimizing the power allocation subject to the QoS violation penalties using augmented Lagrangian transformation. Our numerical results show that well-optimized current distributions over each metasurface in the proposed D-CAPA achieve up to 65% and 61% reductions in overall system PC compared to the EPA and co-located CAPA (C-CAPA) cases, while maintaining the same total aperture size and transmission power.

This paper proposes a novel optimization framework for enhancing the security resilience of cell-free massive multiple-input multiple-output (CF-mMIMO) networks with multi-antenna access points (APs) and protective partial zero-forcing (PPZF) under active eavesdropping. Based on the main principles of absorption, adaptation, and recovery, we formulate a security aware resilience metric to quantify the system performance during and after a security outage. A multi-user service priority-aware power allocation problem is formulated to minimize the mean squared error (MSE) between real-time and desired security efficiency, thereby enabling a trade-off between the target user’s secrecy performance and multi-user quality of service (QoS). To solve this non-convex problem, a security-aware iterative algorithm based on the successive convex approximation (SCA) is employed. The proposed algorithm determines the optimal power allocation strategy by balancing solution quality against recovery time. At each iteration, it evaluates the overall resilience score and selects the strategy that achieves the highest value. Simulation results confirm that the proposed framework significantly improves the resilience of CF-mMIMO networks, allowing flexible adaptation between rapid recovery and high-quality recovery, depending on system requirements.

This paper examines the power consumption (PC) efficiency of a mixed near- and far-field (MF) simultaneous wireless information and power transfer (SWIPT) system underpinned by a hybrid beamforming (HB)-based modular extra-large multiple-input-multiple output (XL-MIMO) array. Multiple information decoding (ID) and energy harvesting (EH) users are served by multiple constituent subarrays in both the near-field (NF) and far-field (FF) region of the transmit array. A novel decision method is proposed for accurate classification of different field users using Frobenius norm-based frequency correlation of the least square (LS) channel estimates. The NF spatial non-stationarities (SnS) effects entail distinct electromagnetic (EM) visibility regions (VRs), which can be customized to employ strategic activation of the constituent XL-MIMO subarrays. We formulate a two-tier joint optimization problem to minimize the overall PC, considering the power allocation (PA) for both ID and EH users in addition to the subarray activation (SA). This challenging mixed-integer problem is transformed into computationally tractable formulations, accompanied by the development of well-optimized algorithms. Our simulation results demonstrate an overall PC reduction for our proposed PA-SA-HB scheme by up to 93% against the equal PA with full array (FA) and up to 18% with respect to the PA-FA-HB case.

Driven by diverse applications in the emerging low-altitude economy, modern aerial networks must inherently cater for highly heterogeneous environments, characterized by communication services under mixed service delay constraints and diverse user equipment (UE) mobility. However, such heterogeneity leads to resource allocation conflicts and imbalances, which undermine communication reliability and may result in network unavailability. To address this, we investigate resource management in uplink low-altitude heterogeneous networks. Specifically, we propose a flying access point (FAP)-coordinated multi-point packet delivery mechanism with a unified resource allocation (URA) scheme to efficiently manage spatial, frequency, and temporal resources. This includes subchannel allocation, time slot partitioning, and pilot length design. Then, we derive a lower bound (LB) on network availability (NA) and reveal that extended heterogeneity significantly degrades the LB due to: (a) resource reduction under URA and (b) the independence in ensuring services under heterogeneity. To mitigate this degradation, we derive a closed-form condition on the required number of FAPs by relaxing the LB, thereby ensuring sufficient spatial resources to achieve the target NA. Meanwhile, we derive closed-form expressions for jointly approximating the optimal number of UEs sharing time-frequency resources and the pilot length. This optimization improves resource efficiency for NA by balancing the post-processing signal-to-noise ratio and its associated thresholds to satisfy reliability requirements under heterogeneous conditions. Numerical results validate the analysis and demonstrate that the proposed resource management strategy achieves the target NA under increased heterogeneity, thereby outperforming existing approaches.

We consider a reconfigurable intelligent surface (RIS)-assisted extremely large-scale multiple-input multiple-output (XL-MIMO) downlink system, where an XL-MIMO array serves two groups of single-antennas users, namely near-field users (NFUEs) and far-field users (FFUEs). FFUEs are subject to blockage, and their communication is facilitated through the RIS. We consider three precoding schemes at the XL-MIMO array, namely central zero-forcing (CZF), local zero-forcing (LZF) and maximum ratio transmission (MRT). Closed-form expressions for the spectral efficiency (SE) of all users are derived for MRT precoding, while statistical-form expressions are obtained for CZF and LZF processing. A heuristic visibility region (VR) selection algorithm is also introduced to help reduce the computational complexity of the precoding scheme. Furthermore, we devise a two-stage phase shifts design and power control algorithm to maximize the sum of weighted minimum SE of two groups of users with CZF, LZF and MRT precoding schemes. The simulation results indicate that, when equal priority is given to NFUEs and FFUEs, the proposed design improves the sum of the weighted minimum SE by 31.9%, 37.8%, and 119.2% with CZF, LZF, and MRT, respectively, compared to the case with equal power allocation and random phase shifts design. CZF achieves the best performance, while LZF offers comparable results with lower complexity. When prioritizing NFUEs or FFUEs, LZF achieves strong performance for the prioritized group, whereas CZF ensures balanced performance between NFUEs and FFUEs.

Cell-free massive multiple-input multiple-output is a potential candidate for future networks with pervasive connectivity by utilizing coherent joint transmission and distributed antenna arrays. This paper studies the exploitation of full-duplex communication for a distributed antenna array. Specifically, we derive a closed-form expression for the uplink and downlink ergodic spectral efficiency (SE) for a network where the APs can flexibly operate in either the full-duplex or half-duplex mode with linear processing and Rayleigh fading channels. A long-term total SE maximization problem is formulated subject to a network operation model and individual SE requirements with limited power budget. Due to the intrinsic nonconvexity and infeasible circumstances where some UEs might not be able to achieve the rate requirements, we adapt differential evolution to design a low computational complexity algorithm that can attain good power allocation and network operation mode in polynomial time. Numerical results demonstrate the effectiveness of our system design and proposed algorithm over state-of-the-art benchmarks with satisfactory service to the majority of UEs, although several ones may be unscheduled under harsh conditions.

This study explores a next-generation multiple access (NGMA) framework for cell-free massive MIMO (CF-mMIMO) systems enhanced by stacked intelligent metasurfaces (SIMs), aiming to improve simultaneous wireless information and power transfer (SWIPT) performance. A fundamental challenge lies in optimally selecting the operating modes of access points (APs) to jointly maximize the received energy and satisfy spectral efficiency (SE) quality-of-service constraints. Practical system impairments, including a non-linear harvested energy model, pilot contamination (PC), channel estimation errors, and reliance on long-term statistical channel state information (CSI), are considered. We derive closed-form expressions for both the achievable SE and the average sum harvested energy (sum-HE). A mixed-integer non-convex optimization problem is formulated to jointly optimize the SIM phase shifts, APs mode selection, and power allocation to maximize average sum-HE under SE and average harvested energy constraints. To solve this problem, we propose a centralized training, decentralized execution (CTDE) framework based on deep reinforcement learning (DRL), which efficiently handles high-dimensional decision spaces. A Markovian environment and a normalized joint reward function are introduced to enhance the training stability across on-policy and off-policy DRL algorithms. Additionally, we provide a two-phase convex-based solution as a theoretical robust performance. Numerical results demonstrate that the proposed DRL-based CTDE framework achieves SWIPT performance comparable to convexification-based solution, while significantly outperforming baselines.

We propose a hybrid simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) architecture with dynamically switched active and passive elements to support joint localization, communication, and wireless power transfer (WPT). We first pursue a parallel factor analysis with the alternating least squares (PARAFAC-ALS)-based tensor decomposition approach that decouples the base station (BS)-reconfigurable intelligent surface (RIS) and RIS-user channels, thereby enabling low-overhead channel acquisition. Based on this, we formulate a system energy efficiency (EE) maximization problem, subject to the spectral efficiency (SE) requirements of communication users, sensing signal-to-interference-plus-noise ratio constraints, and the nonlinear energy harvesting requirements of energy-harvesting users. The optimization problem is nonconvex since the transmit power allocation, STAR-RIS coefficients, and active/passive mode assignments are tightly coupled in both the objective and constraints. We address this issue by alternating between two subproblems, and solving them via fractional programming, successive convex approximation and a multi-seed greedy strategy employed as an initialization step. Numerical results demonstrate that selectively activating a small, well-chosen subset of STAR-RIS elements achieves 1.5 to 3 times EE improvements compared with fully passive/active architectures, while satisfying communication, sensing, and power-transfer requirements.

This paper presents an application of differential evolution in optimizing the exploitation of full-duplex communication for Cell-Free Massive Multiple Input Multiple Output (CF-mMIMO), a potential candidate for 6G networks. This paper proposes a new dynamic network-assisted full-duplex CF-mMIMO network, where access points can operate in either half-duplex or full-duplex mode, and each full-duplex access point can serve uplink and downlink users simultaneously. A long-term total spectral efficiency maximization problem is formulated subject to a network operation model and individual spectral efficiency requirements with a limited power budget. Due to the intrinsic nonconvexity and infeasible circumstances where some users might not achieve the rate requirements, we adapt differential evolution to design a low computational complexity algorithm, attaining good power allocation and network operation mode in polynomial time. We further analytically investigate the number of generations required to reach the optimal solution. Numerical results demonstrate the effectiveness of our system design and proposed algorithm over state-of-the-art benchmarks. The network can offer satisfactory service to most users, although several may be unscheduled under harsh conditions.

In this paper, we propose a hybrid beamforming design for multiple target detection in an orthogonal time frequency space (OTFS)-based integrated sensing and communication (ISAC) multiple-input multiple-output (MIMO) system. The proposed hybrid beamformer allows spatial separation of the beams for communication and sensing, thereby eliminating inter-beam interference (IBI), while reducing the number of required radio frequency (RF) chains. More specifically, in addition to the beams allocated for communication users, multiple beams are assigned for target scanning and detection. By applying a combiner to the received echo signals, information about the target's existence, along with its angular, range, and Doppler characteristics, can be directly obtained across different RF chains. To shed light on the system performance, we analyze the signal-to-interference-plusnoise ratio (SINR) and discuss the effect of the beamformer in the on-grid and off-grid cases, respectively. Our simulation results indicate that accurate sensing can be achieved with integer delay and Doppler indices; however, in the cases of fractional delay and Doppler, the sensing accuracy depends on the resolution of these parameters.

Integrated sensing and communication (ISAC) systems enable communication and sensing functions via three protocols, including ($\text{TP}_{1}$) concurrently using the same time-frequency resources, ($\text{TP}_{2}$) scheduling them independently, or ($\text{TP}_{3}$) a hybrid technique that combines both. Nevertheless, all existing studies rely on the first approach, and none provide a comprehensive performance evaluation of all three protocols. Thus, this paper offers an extensive performance evaluation of these protocols, emphasizing their advantages, limitations, and trade-offs. Specifically, we maximize the sum communication and/or sensing rate for all protocols in a full-duplex ISAC system with multiple users and targets. Numerical results reveal that protocols ($\text{TP}_{1}$) and ($\text{TP}_{3}$) necessitate a sensing metric considering both transmit and receiver beams to ensure adequate sensing performance. In contrast, although protocol ($\text{TP}_{2}$) can utilize more straightforward sensing metrics and avoid communication-sensing interference, it may not achieve high communication performance.

Cell-free (CF) integrated sensing and communication (ISAC) combines CF architecture with ISAC. CF employs distributed access points, eliminates cell boundaries, and enhances coverage, spectral efficiency, and reliability. ISAC unifies radar sensing and communication, enabling simultaneous data transmission and environmental sensing within shared spectral and hardware resources. CF-ISAC leverages these strengths to improve spectral and energy efficiency while enhancing sensing in wireless networks. As a promising candidate for next-generation wireless systems, CF-ISAC supports robust multi-user communication, distributed multi-static sensing, and seamless resource optimization. However, a comprehensive survey on CF-ISAC has been lacking. This paper fills that gap by first revisiting CF and ISAC principles, covering cooperative transmission, radar cross-section, target parameter estimation, ISAC integration levels, sensing metrics, and applications. It then explores CF-ISAC systems, emphasizing their unique features and the benefits of multi-static sensing. State-of-the-art developments are categorized into performance analysis, resource allocation, security, and user/target-centric designs, offering a thorough literature review and case studies. Finally, the paper identifies key challenges such as synchronization, multi-target detection, interference management, and fronthaul capacity and latency. Emerging trends, including next-generation antenna technologies, network-assisted systems, near-field CF-ISAC, integration with other technologies, and machine learning approaches, are highlighted to outline the future trajectory of CF-ISAC research.

We consider a downlink (DL) massive multiple-input multiple-output (MIMO) system, where different users have different mobility profiles. To support this system, we categorize the users into two disjoint groups according to their mobility profile and implement a hybrid orthogonal time frequency space (OTFS)/orthogonal frequency division multiplexing (OFDM) modulation scheme. Building upon this framework, two precoding designs, namely full-pilot zero-forcing (FZF) precoding and partial zero-forcing (PZF) precoding are considered. To shed light on the system performance, the spectral efficiency (SE) with a minimum-mean-square-error (MMSE)-successive interference cancellation (SIC) detector is investigated. Closed-form expressions for the SE are obtained using some tight mathematical approximations. To improve fairness among different users, we consider max-min power control for both precoding schemes based on the closed-form SE expression. However, by noting the large performance gap for different groups of users with PZF precoding, the per-user SE will be compromised when pursuing overall fairness. Therefore, we propose a weighted max-min power control scheme. By introducing a weighting coefficient, the trade-off between the per-user performance and fairness can be enhanced. Our numerical results confirm the theoretical analysis and reveal that with mobility-based grouping, the proposed hybrid OTFS/OFDM modulation significantly outperforms the conventional OFDM modulation for high-mobility users.

Cell-free (CF) architectures and full-duplex (FD) communication are leading candidates for next-generation wireless networks. The CF framework removes cell boundaries in traditional cell-based systems, thereby mitigating the inter-cell interference and improving the coverage probability. In contrast, FD communication allows simultaneous transmission and reception on the same frequency-time resources, effectively doubling the spectral efficiency (SE). The integration of these technologies, known as CF FD communication, leverages the advantages of both approaches to enhance the spectral and energy efficiency in wireless networks. CF FD communication is particularly promising due to the low-power and cost-effective FD-enabled access points (APs), which are ideal for short-range transmissions between APs and users. Despite its potential, a comprehensive survey or tutorial on CF FD communication has been notably absent. This paper aims to address this gap in the literature. It begins with an overview of FD communication fundamentals, self-interference cancellation techniques, and CF technology principles, including their implications for current wireless networks. The discussion then moves to the integration and compatibility of CF and FD technologies, focusing on channel estimation, performance analysis, and resource allocation in CF FD massive multiple-input multiple-output (mMIMO) networks, supported by an extensive literature review and case studies. The potential of combining a sub-category of CF architecture—network-assisted CF technology—with FD technology is also explored, including a detailed case study on fundamentals, performance analysis, AP operation, and mode assignments. Finally, emerging CF FD paradigms, like millimeter-wave communications, unmanned aerial vehicles, and reconfigurable intelligent surfaces, are discussed, highlighting existing contributions and unresolved issues.

We investigate the integration of beyond-diagonal reconfigurable intelligent surfaces (BD-RISs) into cell-free massive multiple-input multiple-output (CF-mMIMO) systems to enhance simultaneous wireless information and power transfer (SWIPT). To simultaneously support two groups of users—energy receivers (ERs) and information receivers (IRs)— without sacrificing time-frequency resources, a subset of access points (APs) is dedicated to serving ERs with the aid of a BD-RIS, while the remaining APs focus on supporting IRs. A protective partial zero-forcing precoding technique is implemented at the APs to manage the non-coherent interference between the ERs and IRs. Subsequently, closed-form expressions for the spectral efficiency of the IRs and the average sum of harvested energy (HE) at the ERs are leveraged to formulate a comprehensive optimization problem. This problem jointly optimizes the AP selection, AP power control, and scattering matrix design at the BD-RIS, all based on long-term statistical channel state information. This challenging problem is then effectively transformed into more tractable forms. To solve these sub-problems, efficient algorithms are proposed, including a heuristic search for the scattering matrix design, as well as successive convex approximation and deep reinforcement learning methods for the joint AP mode selection and power control design. Numerical results show that a BD-RIS with a group- or fully-connected architecture achieves significant EH gains over the conventional diagonal RIS, especially delivering up to a 7-fold increase in the average sum of HE when a heuristic-based scattering matrix design is employed.

We present an overview of ongoing research endeavors focused on in-band full-duplex (IBFD) massive multiple-input multiple-output (MIMO) systems and their applications. In response to the unprecedented demands for mobile traffic in concurrent and upcoming wireless networks, a paradigm shift from conventional cellular networks to distributed communication systems becomes imperative. Cell-free massive MIMO (CF-mMIMO) emerges as a practical and scalable implementation of distributed/network MIMO systems, serving as a crucial physical layer technology for the advancement of next-generation wireless networks. This architecture inherits benefits from co-located massive MIMO and distributed systems and provides the flexibility for integration with the IBFD technology. We delineate the evolutionary trajectory of cellular networks, transitioning from conventional half-duplex multi-user MIMO networks to IBFD CF-mMIMO. The discussion extends further to the emerging paradigm of network-assisted IBFD CF-mMIMO (NAFD CF-mMIMO), serving as an energy-efficient prototype for asymmetric uplink and downlink communication services. This novel approach finds applications in dual-functionality scenarios, including simultaneous wireless power and information transmission, wireless surveillance, and integrated sensing and communications. We highlight various current use case applications, discuss open challenges, and outline future research directions aimed at fully realizing the potential of NAFD CF-mMIMO systems to meet the evolving demands of future wireless networks.

We investigate reconfigurable intelligent surface (RIS)-assisted simultaneous wireless information and power transfer (SWIPT) Internet of Things (IoT) networks, where energy-limited IoT devices are overlaid with cellular information users (IUs). IoT devices are wirelessly powered by a RIS-assisted massive multiple-input multiple-output (MIMO) base station (BS), which is simultaneously serving a group of IUs. By leveraging a two-timescale transmission scheme, precoding at the BS is developed based on the instantaneous channel state information (CSI), while the passive beamforming at the RIS is adapted to the slowly-changing statistical CSI. We derive closed-form expressions for the achievable spectral efficiency of the IUs and average harvested energy at the IoT devices, taking the channel estimation errors and pilot contamination into account. Then, a non-convex max-min fairness optimization problem is formulated subject to the power budget at the BS and individual quality of service requirements of IUs, where the transmit power levels at the BS and passive RIS reflection coefficients are jointly optimized. Our simulation results show that the average harvested energy at the IoT devices can be improved by 132% with the proposed resource allocation algorithm. Interestingly, IoT devices benefit from the pilot contamination, leading to a potential doubling of the harvested energy in certain network configurations.

We propose a distributed implementation of integrated sensing and communication (ISAC) underpinned by a massive multiple input multiple output (CF-mMIMO) architecture without cells. Distributed multi-antenna access points (APs) simultaneously serve communication users (UEs) and emit probing signals towards multiple specified zones for sensing. The APs can switch between communication and sensing modes, and adjust their transmit power based on the network settings and sensing and communication operations’ requirements. By considering local partial zero-forcing and maximum-ratio-transmit precoding at the APs for communication and sensing, respectively, we first derive closed-form expressions for the spectral efficiency (SE) of the UEs and the mainlobe-to-average-sidelobe ratio (MASR) of the sensing zones. Then, a joint operation mode selection and power control design problem is formulated to maximize the SE fairness among the UEs, while ensuring specific levels of MASR for sensing zones. The complicated mixed-integer problem is relaxed and solved via a successive convex approximation approach. We further propose a low-complexity design, where the AP mode selection is designed through a greedy algorithm and then power control is designed based on this chosen mode. Our findings reveal that the proposed scheme can consistently ensure a sensing success rate of 100% for different network setups with a satisfactory fairness among all UEs.

This paper studies cell-free massive multiple-input multiple-output (CF-mMIMO) systems that underpin simultaneous wireless information and power transfer (SWIPT) for separate information users (IUs) and energy users (EUs) in Internet of Things (IoT) networks. We propose a joint access point (AP) operation mode selection and power control design, wherein certain APs are designated for energy transmission to EUs, while others are dedicated to information transmission to IUs. The performance of the system, from both a spectral efficiency (SE) and energy efficiency (EE) perspective, is comprehensively analyzed. Specifically, we formulate two mixed-integer nonconvex optimization problems for maximizing the average sum-SE and EE, under realistic power consumption models and constraints on the minimum individual SE requirements for individual IUs, minimum HE for individual EUs, and maximum transmit power at each AP. The challenging optimization problems are solved using successive convex approximation (SCA) techniques. The proposed framework design is further applied to the average sum-HE maximization and energy harvesting fairness problems. Our numerical results demonstrate that the proposed joint AP operation mode selection and power control algorithm can achieve EE performance gains of up to 4-fold and 5-fold over random AP operation mode selection, with and without power control respectively.

This paper explores a discrete energy state transition model for energy harvesting (EH) in cell-free massive multiple-input multiple-output (CF-mMIMO) networks. Multiple-antenna access points (APs) provide wireless power and information to single-antenna UE equipment (UEs). The harvested energy at the UEs is used for both uplink (UL) training and data transmission. We investigate the energy transition probabilities based on the energy differential achieved in each coherence interval. A Markov chain-based stochastic process is introduced to characterize the evolving UE energy status. A detailed statistical model is developed for a non-linear EH circuit at the UEs, using the derived closed-form expressions for the mean and variance of the harvested energy. More specifically, simulation results confirm that the proposed Gamma distribution approximation can accurately capture the statistical behavior of the harvested energy. Furthermore, the energy state transitions are evaluated using the proposed Markov chain-based framework, while mathematical expressions for the self, positive and negative transition probabilities of the discrete energy states are also presented. Our numerical results depict that increasing the number of APs with a constant number of service antennas provides significant improvement in the positive energy state transition and reduces the negative transition probabilities of the overall network.

Extremely large-scale multiple-input multiple-output (XL-MIMO) is a transformative technology to achieve spectral-efficient and energy-saving wireless communication. However, XL-MIMO leads to the near-field propagation becoming dominant. In this paper, we examine a reconfigurable intelligent surface (RIS)-assisted XL-MIMO communication system to serve two distinct groups of users, namely near-field users (NFUEs), directly served by the XL-MIMO, and far-field users (FFUEs), served with the assistance of a RIS. We derive the signal-to-interference-plus-noise ratio (SINR) expressions for whole-array-based precoders, including maximum-ratio transmission (MRT), and zero-forcing (ZF). Moreover, we take into account the spatially, non-stationary channel characteristics, indicating that user terminals may only have visibility of a specific portion of the array, referred to as the visibility region (VR). To further leverage the VR for complexity reduction, we propose a heuristic algorithm designed to determine the VR, while also guaranteeing the individual SINR requirements for both NFUEs and FFUEs. Simulation results indicate that utilizing VR with our proposed heuristic algorithm yields performance comparable to a benchmark utilizing the whole-array, albeit with a notable reduction in the number of antennas and computational complexity.

This paper investigates the integration of beyond-diagonal reconfigurable intelligent surfaces (BD-RISs) into cell-free massive multiple-input multiple-output (CF-mMIMO) systems, focusing on applications involving simultaneous wireless information and power transfer (SWIPT). The system supports concurrently two user groups: information users (IUs) and energy users (EUs). A BD-RIS is employed to enhance the wireless power transfer (WPT) directed towards the EUs. To comprehensively evaluate the system's performance, we present an analytical framework for the spectral efficiency (SE) of IUs and the average harvested energy (HE) of EUs in the presence of spatial correlation among the BD-RIS elements and for a non-linear energy harvesting circuit. Our findings offer important insights into the transformative potential of BD- RIS, setting the stage for the development of more efficient and effective SWIPT networks. Finally, incorporating a heuristic scattering matrix design at the BD-RIS results in a substantial improvement compared to the scenario with random scattering matrix design.

We explore the potential of a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) to enhance the performance of wireless surveillance systems. The STAR-RIS is deployed between a full-duplex (FD) multi-antenna legitimate eavesdropper (E) and a suspicious communication pair. It reflects the suspicious signal towards the suspicious receiver (SR), while simultaneously transmitting the same signal to E for interception purposes. Additionally, it enables the forwarding of a jamming signal from E to SR, which is located on the back side of the STAR-RIS. To enhance the eavesdropping non-outage probability, we formulate a non-convex joint optimization problem to design the beamforming vectors at E and reflection/transmission phase shift matrices at the STAR-RIS. We adopt the block coordinate descent (BCD) algorithm and propose an approach, mainly based on semi-definite relaxation (SDR) and successive convex approximation (SCA), for solving the resulting decoupled sub-problems. Finally, we compare the performance of the proposed design against low-complexity zero-forcing (ZF)-based beamforming designs.

To meet the unprecedented mobile traffic demands of future wireless networks, a paradigm shift from conventional cellular networks to distributed communication systems is imperative. Cell-free massive multiple-input multiple-output (CF-mMIMO) represents a practical and scalable embodiment of distributed/network MIMO systems. It inherits not only the key benefits of co-located massive MIMO systems but also the macro-diversity gains from distributed systems. This innovative architecture has demonstrated significant potential in enhancing network performance from various perspectives, outperforming co-located mMIMO and conventional small-cell systems. Moreover, CF-mMIMO offers flexibility in integration with emerging wireless technologies such as full-duplex (FD), nonorthogonal transmission schemes, millimeter-wave (mmWave) communications, ultrareliable low-latency communication (URLLC), unmanned aerial vehicle (UAV)-aided communication, and reconfigurable intelligent surfaces (RISs). In this article, we provide an overview of current research efforts on CF-mMIMO systems and their promising future application scenarios. We then elaborate on new requirements for CF-mMIMO networks in the context of these technological breakthroughs. We also present several current open challenges and outline future research directions aimed at fully realizing the potential of CF-mMIMO systems in meeting the evolving demands of future wireless networks.

In this paper, we consider a downlink (DL) massive multiple-input multiple-output (MIMO) system, where different users have different mobility profiles. To support this system, we propose to use a hybrid orthogonal time frequency space (OTFS)/orthogonal frequency division multiplexing (OFDM) modulation scheme, where OTFS is applied for high-mobility users and OFDM is used for low-mobility users. Two precoding designs, namely full zero-forcing (FZF) precoding and partial zero-forcing (PZF) precoding, are considered and analyzed in terms of per-user spectral efficiency (SE). With FZF, interference among users is totally eliminated at the cost of high computational complexity, while PZF can be used to provide a trade-off between complexity and performance. To apply PZF precoding, users are grouped into two disjoint groups according to their mobility profile or channel gain. Then, zero-forcing (ZF) is utilized for high-mobility or strong channel gain users to completely cancel the inter-group interference, while maximum ratio transmission (MRT) is applied for low-mobility users or users with weak channel gain. To shed light on the system performance, the SE for high-mobility and low-mobility users with a minimum-mean-square-error (MMSE)-successive interference cancellation (SIC) detector is investigated. Our numerical results reveal that the PZF precoding with channel gain grouping can guarantee a similar quality of service for all users. In addition, with mobility-based grouping, the hybrid OTFS/OFDM modulation outperforms the conventional OFDM modulation for high-mobility users.

This paper studies cell-free massive multiple-input multiple-output (CF-mMIMO) systems incorporating simultane-ous wireless information and power transfer (SWIPT) for separate information users (IUs) and energy users (EUs) in Internet of Things (IoT) networks. To optimize both the spectral efficiency (SE) of IUs and harvested energy (HE) of EUs, we propose a joint access point (AP) operation mode selection and power control design, wherein certain APs are designated for energy transmission to EUs, while others are dedicated to information transmission to IUs. We investigate the problem of maximizing the total HE for EUs, considering constraints on SE for individual IUs and minimum HE for individual EUs. Our numerical results showcase that the proposed AP operation mode selection algorithm can provide up to 76% and 130% performance gains over random AP operation mode selection with and without power control, respectively,

We consider a reflecting intelligent surface (RIS)-assisted massive multiple-input multiple-output (MIMO) system to facilitate simultaneous wireless information and power transfer (SWIPT) towards two groups of information users (IUs) and energy users (EUs) over Rician fading channels. By considering partial zero-forcing (PZF) precoding at the base station (BS), we derive closed-from expressions for the achievable downlink spectral efficiency (SE) of the IUs and average harvested energy at the EUs. Our results rigorously demonstrate the impact of various system parameters on the actual performance. We next propose a maxmin fairness transmit power allocation which seeks to maximize the minimum harvested power by EUs, subject to quality-of-service constraints at all IUs, relying on statistical channel state information (CSI) and a realistic non-linear energy harvesting (EH) model for the EUs. Our numerical results reveal that the interplay between the RIS and massive MIMO can significantly boost the performance of SWIPT in wireless networks.

We consider network-assisted full-duplex (NAFD) cell-free massive multiple-input multiple-output (CF-mMIMO) systems, where full-duplex (FD) transmission is virtually realized via half-duplex (HD) hardware devices. The HD access points (APs) operating in uplink (UL) mode and those operating in downlink (DL) mode simultaneously serve DL and UL user equipments (UEs) in the same frequency bands. We comprehensively analyze the performance of NAFD CF-mMIMO from both a spectral efficiency (SE) and energy efficiency (EE) perspectives. Specifically, we propose a joint optimization approach that designs the AP mode assignment, power control, and large-scale fading (LSFD) weights to improve the sum SE and EE of NAFD CF-mMIMO systems. We formulate two mixed-integer nonconvex optimization problems of maximizing the sum SE and EE, under realistic power consumption models, and the constraints on minimum individual SE requirements, maximum transmit power at each DL AP and UL UE. The challenging formulated problems are transformed into tractable forms and two novel algorithms are proposed to solve them using successive convex approximation techniques. More importantly, our approach can be applied to jointly optimize power control and LSFD weights for maximizing the sum SE and EE of HD and FD CF-mMIMO systems, which, to date, has not been studied. Numerical results show that: (a) our joint optimization approach significantly outperforms the heuristic approaches in terms of both sum SE and EE; (b) in CF-mMIMO systems, the NAFD scheme can provide approximately 30% SE gains, while achieving a remarkable EE gain of up to 200% compared with the HD and FD schemes.

We provide a performance evaluation of orthogonal time frequency space (OTFS) modulation in cell-free massive MIMO (multiple-input multiple-output) systems. By leveraging the inherent sparsity of the delay-Doppler (DD) representation of time-varying channels, we apply the embedded pilot-aided channel estimation method with reduced guard intervals and derive the minimum mean-square error estimate of the channel gains from received uplink pilots at the access points (APs). Each AP applies conjugate beamforming to transmit data to the users. We derive a closed-form expression for the individual user downlink throughput as a function of the numbers of APs, users and DD channel estimate parameters. We compare the OTFS performance with that of orthogonal frequency division multiplexing (OFDM) at high-mobility conditions. Our findings reveal that with uncorrelated shadowing, cell-free massive MIMO with OTFS modulation achieves up to 35% gain in 95%-likely per-user throughput, compared with the OFDM counterpart. Finally, the increase in the per user throughput is more pronounced at the median rates over the correlated shadowing scenarios.

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

We provide the first-ever performance evaluation of orthogonal time frequency space (OTFS) modulation in cell-free massive multiple-input multiple-output (MIMO) systems. To investigate the trade-off between performance and overhead, we apply embedded pilot-aided and superimposed pilot-based channel estimation methods. We then derive a closed-form expression for the individual user downlink and uplink spectral efficiencies (SEs) as a function of the numbers of APs, users and delay-Doppler domain channel estimate parameters. Based on these analytical results, we also present new scaling laws that the AP’s and user’s transmit power should satisfy, to sustain a desirable quality of service. It is found that when the number of APs,$M_{a}$, grows without bound, we can reduce the transmit power of each user and AP proportionally to$1/M_{a}$and$1/M_{a}^{2}$, respectively, during the uplink and downlink phases. We compare the OTFS performance with that of orthogonal frequency division multiplexing (OFDM) at high-mobility conditions. Our findings reveal that, OTFS modulation with embedded pilot-based channel estimation provides up to 20-fold gain over the OFDM counterpart in terms of 95%-likely per-user downlink SE. Finally, with superimposed pilot-based channel estimation, the increase in the uplink sum SE is more pronounced when the channel delay spread is increased.

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

This paper investigates the application of full-duplex (FD) multi-antenna transceivers in proactive eavesdropping systems. To this end, we jointly optimize the transmit and receive beamformers at the legitimate FD monitor to maximize the eavesdropping non-outage probability of the system. The resulting non-convex problem is solved using two-layer decomposition technique. The inner layer problem is formulated as a semidefinite relaxation problem, and the outer problem is solved by one-dimensional line search. We further propose sub-optimum beamforming designs, where the beamformers are obtained using zero-forcing, and maximum ratio transmission. To archive a low-complexity implementation, we study the antenna selection problem as an alternative for performance optimization. Particularly, based on the system's eavesdropping non-outage probability, several antenna selection schemes are proposed to choose single transmit and single receive antenna at the FD monitor. For each scheme, we derive closed-form expressions of the eavesdropping non-outage probability. Our findings reveal that proposed antenna selection schemes can achieve the performance close to that of the proposed optimum/sub-optimum beamforming design, but with much lower implementation complexity.

Wireless energy harvesting, physical-layer security, and full-duplex wireless are important, emerging fifth generation (5G) technologies. In this paper, we thus investigate a source-destination link with an energy-harvesting full-duplex relay and a jammer (to degrade the eavesdropper channel) in the presence of an eavesdropper. Thus, to exploit energy harvesting and to improve security, we propose a full-duplex jammer (FDJ) protocol and its half-duplex version (HDJ). Two cases for availability of the eavesdropper channel state information (ECSI) are considered: complete ECSI and incomplete ECSI. For both FDJ and HDJ protocols and for complete ECSI, we derive the instantaneous and average secrecy rates and compute optimal time split for energy harvesting. To gain more insights, we consider a practical interference-limited scenario and derive closed-form cumulative distribution function of the signal-to-interference plus noise ratio at the destination and eavesdropper nodes. Comparatively, we show that FDJ improves instantaneous secrecy rate over HDJ. However, the degree of improvement is highly dependent on time split for energy harvesting, amount of self-interference, the channel gains, and locations of the nodes. Our findings reveal that FDJ increases the average secrecy rate 150% over HDJ and 260% over HD relaying without jammer. For incomplete ECSI scenario, we derive asymptotic secrecy outage and show that FDJ performs better for small-to-medium values of source powers; otherwise, HDJ yields a higher gain.

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

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

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

In this paper, a joint relay selection and power allocation (JRP) scheme is proposed to enhance the physical layer security of a cooperative network, where a multiple antennas source communicates with a single-antenna destination in the presence of untrusted relays and passive eavesdroppers (Eves). The objective is to protect the data confidentially while concurrently relying on the untrusted relays as potential Eves to improve both the security and reliability of the network. To realize this objective, we consider cooperative jamming performed by the destination while the JRP scheme is implemented. With the aim of maximizing the instantaneous secrecy rate, we derive a new closed-form solution for the optimal power allocation and propose a simple relay selection criterion under two scenarios of non-colluding Eves (NCE) and colluding Eves (CE). For the proposed scheme, a new closed-form expression is derived for the ergodic secrecy rate (ESR) and the secrecy outage probability as security metrics, and a new closed-form expression is presented for the average symbol error rate as a reliability measure over Rayleigh fading channels. We further explicitly characterize the high signal-to-noise ratio slope and power offset of the ESR to highlight the impacts of system parameters on the ESR. In addition, we examine the diversity order of the proposed scheme to reveal the achievable secrecy performance advantage. Finally, the secrecy and reliability diversity-multiplexing tradeoff of the optimized network are provided. Numerical results highlight that the ESR performance of the proposed JRP scheme for NCE and CE cases is increased with respect to the number of untrustworthy relays.

This paper considers a cloud radio access network, where full-duplex (FD) users communicate with remote radio heads (RRHs) that are spatially distributed. We consider all participate RRH association (ARA) and single nearest RRH association (SRA) policies with optimal, maximum ratio combining/maximal ratio transmission (MRT), and zero-forcing/MRT (ZF/MRT) processing schemes and derive analytical expressions useful to compare the average uplink/downlink (UL/DL) sum rate among association schemes as a function of the number of RRHs antennas and UL/DL RRH density. We also study a dense network setting with multiple FD users and derive exact expressions for the average UL/DL rates, where a user-centric clustering technique is adopted and each user is served by its nearest UL and DL RRHs. Furthermore, by maximizing the instantaneous sum rate, we develop an optimum power allocation scheme for the single-user case. We observe that ARA results in a rate region that is strongly biased toward the UL or DL, but using SRA results in a more balanced rate region. Moreover, SRA policy with ZF/MRT processing achieves up to 32% and 42% average sum rate gains as compared with the HD SRA and FD ARA counterparts, respectively.

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

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

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

In this paper, we consider two fundamental full-duplex (FD) architectures, two-node and three-node, in the context of cellular networks where the terminals employ directional antennas. The simultaneous transmission and reception of data in non-orthogonal channels makes FD radio a potential solution for the currently limited spectrum. However, its implementation generates high levels of interference either in the form of loopback interference (LI) from the output to the input antenna of a transceiver or in the form of co-channel interference in large-scale multicell networks due to the large number of active links. Using a stochastic geometry model, we investigate how directional antennas can control and mitigate the co-channel interference. Furthermore, we provide a model which characterizes the way directional antennas manage the LI in order to passively suppress it. Our results show that both architectures can benefit significantly by the employment of directional antennas. Finally, we consider the case where both architectures are employed in the network and derive the optimal values for the density fraction of each architecture, which maximize the success probability and the network throughput.

This paper considers a cloud radio access network (C-RAN) where spatially distributed remote radio heads (RRHs) communicate with a full-duplex user. In order to reflect a realistic scenario, the uplink (UL) and downlink (DL) RRHs are assumed to be equipped with multiple antennas and distributed according to a Poisson point process. We consider all participate and nearest RRH association schemes with distributed beam-forming in the form of maximum ratio combining/maximal ratio transmission (MRC/MRT) and zero-forcing/MRT(ZF/MRT) processing. We derive analytical expressions useful to compare the average sum rate among association schemes as a function of the number of RRHs antennas and density of the UL and DL RRHs. Numerical results show that significant performance improvements can be achieved by using the full-duplex mode as compared to the half-duplex mode, while the choice of the beamforming design as well as the RRH association scheme plays a critical role in determining the full-duplex gains.

The authors consider a cellular wireless system where multiple antenna full‐duplex base stations (BSs) communicate with single antenna half‐duplex spatially random users to support simultaneous uplink/downlink transmissions. Leveraging recent applications of stochastic geometry to analyse cellular systems, this study proposes to study the antenna selection problem for full‐duplex BSs. In particular, they investigate max–max antenna selection (MM‐AS) and loopback‐interference antenna selection (LI‐AS) schemes to select a single transmit and receive antenna at BSs. They develop new outage probability expressions for both downlink and uplink transmissions of the proposed antenna selection schemes to investigate network throughput. The authors’ analysis shows interesting performance comparisons of the proposed antenna selection schemes for different system parameters. The LI‐AS scheme outperforms the MM‐AS scheme at uplink, whereas the opposite trend is observed at downlink direction. Moreover, it is demonstrated that the LI‐AS scheme can ensure a balance between maximising the network throughput and maintaining an acceptable uplink/downlink transmission fairness level.

We consider a full-duplex (FD) decode-and-forward system in which the time-switching protocol is employed by the multiantenna relay to receive energy from the source and transmit information to the destination. The instantaneous throughput is maximized by optimizing receive and transmit beamformers at the relay and the time-split parameter. We study both optimum and suboptimum schemes. The reformulated problem in the optimum scheme achieves closed-form solutions in terms of transmit beamformer for some scenarios. In other scenarios, the optimization problem is formulated as a semidefinite relaxation problem and a rank-one optimum solution is always guaranteed. In the suboptimum schemes, the beamformers are obtained using maximum ratio combining, zero-forcing, and maximum ratio transmission. When beamformers have closed-form solutions, the achievable instantaneous and delay-constrained throughput are analytically characterized. Our results reveal that beamforming increases both the energy harvesting and loop interference suppression capabilities at the FD relay. Moreover, simulation results demonstrate that the choice of the linear processing scheme as well as the time-split plays a critical role in determining the FD gains.

We consider a wireless system with a full-duplex (FD) access point (AP) that transmits to a scheduled user in the downlink (DL) channel, while receiving data from an user in the uplink (UL) channel at the same time on the same frequency. In this system, loopback interference (LI) at the AP and inter user interference between the uplink (UL) user and downlink (DL) user can cause performance degradation. In order to characterize the effects of LI and inter user interference, we derive closed-form expressions for the outage probability and achievable sum rate of the system. In addition an asymptotic analysis that reveals insights into the system behavior and performance degradation is presented. Our results indicate that under certain conditions, FD transmissions yield performance gains over half-duplex (HD) mode of operation.

A full-duplex (FD) multiple antenna access point (AP) communicating with single antenna half-duplex (HD) spatially random users to support simultaneous uplink (UL)/downlink (DL) transmissions is investigated. Since FD nodes are inherently constrained by the loopback interference (LI), we study precoding schemes for the AP based on maximum ratio combining (MRC)/maximal ratio transmission (MRT), zero-forcing, and the optimal scheme for UL and DL sum rate maximization using tools from stochastic geometry. In order to shed insights into the systems performance, simple expressions for single antenna/perfect LI cancellation/negligible internode interference cases are also presented. We show that FD precoding at AP improves the UL/DL sum rate and hence a doubling of the performance of the HD mode is achievable. In particular, our results show that these impressive performance gains remain substantially intact even if the LI cancellation is imperfect. Furthermore, relative performance gap between FD and HD modes increases as the number of transmit/receive antennas becomes large, while with the MRC/MRT scheme, increasing the receive antenna number at FD AP, is more beneficial in terms of sum rate than increasing the transmit antenna number.

This study investigates the performance of two‐way decode‐and‐forward (DF) relaying networks, considering transmissions over independent but not necessarily identically distributed (i.n.i.d.) Rayleigh fading channels, in the presence of multiple co‐channel interferers at both the relay and end‐source nodes. Both asymmetrical and symmetrical cases, of whether the channels from source terminals to the relay are identically distributed or not, are considered. Specifically, closed‐form expressions for the cumulative distribution function of the equivalent signal‐to‐interference‐plus‐noise ratio (SINR) in different cases are derived, based on which the exact symbol error probability (SEP) and the systems’ achievable rate are derived and analysed. Based on the analytic results, the authors study the impacts of system parameters, such as interference power and number of interferers on the performance of the system. Furthermore, the system behavior at high signal‐to‐noise ratio (SNR) values is studied via deriving the asymptotic SEP. The results of this study are attested through Monte Carlo simulations.

We study information rate penalties for single-relay amplify and forward (AF) cooperative communication in the presence of unknown and time-varying fading. The penalty is defined as the gap between the information rate with perfect channel state information and that when the source-destination, source-relay and relay-destination channels are unknown at the receiving nodes. We prove that this gap in the cooperative system is the sum of gaps in the source-destination (single-hop) and source-relay-destination (dual-hop) channels. Under the assumption that the source and destination are mobile and the relay is stationary, we derive a closed-form accurate approximation for the asymptotic penalty of the mobile-to-mobile single-hop channel, which can also be used in computing asymptotic penalties for the mobile-fixed-mobile dual-hop channel. AF relaying induces non-Gaussian noise at the destination and hence, the penalty of the dual-hop channel is computed semi-analytically. We discuss a numerical technique for evaluation of destination noise entropy. One main observation of this paper is that non-negligible amplified relay noise can increase the cooperation information rate penalty of up to 1.5 times, as compared to non-relayed transmission. We provide extensive simulation results that characterize the behavior of penalty and include other mobility models for the source, relay and destination.

In this paper, we analyze the performance of cooperative transmissions in wireless ad hoc networks with random node locations. According to a contention probability for message transmission, each source node can either transmits its own message signal or acts as a potential relay for others. Hence, each destination node can potentially receive two copies of the message signal, one from the direct link and the other from the relay link. Taking the random node locations and interference into account, we derive closed-form expressions for the outage probability with different combining schemes at the destination nodes. In particular, the outage performance of optimal combining, maximum ratio combining, and selection combining strategies are studied and quantified.

Motivated by the fact that full diversity order is achieved using the “best-relay” selection technique, we consider opportunistic amplify-and-forward and decode-and-forward relaying systems. We focus on the outage probability of such a systems and then derive closed-form expressions for the outage probability of these systems over independent but non-identical imperfect Log-normal fading channels. We consider the error of channel estimation as a Gaussian random variable. As a result the estimated channels distribution are not Log-normal either as would be in the case of the Rayleigh fading channels. This is exactly the reason why our simulation results do not exactly matched with analytical results. However, this difference is negligible for a wide variety of situations.