SWIPT in Cell-Free Massive MIMO Using Stacked Intelligent Metasurfaces

We investigate the integration of stacked intelligent metasurfaces (SIMs) into cell-free massive multiple input multiple output (CF-mMIMO) system to enhance the simultaneous wireless information and power transfer (SWIPT) performance. Closed-form expressions for the spectral efficiency (SE) of the information-decoding receivers (IRs) and the average sum of harvested energy (sum-HE) at the energy-harvesting receivers (ERs) in the novel system model are derived to subsequently formulate a maximum total average sum-HE problem under a minimum SE threshold per each IR. This problem jointly optimizes the SIM phase-shift (PS) configuration and access points' (APs) power allocation, relying on long-term statistical channel state information (CSI). This non-convex problem is then transformed into more tractable forms. Then, efficient algorithms are proposed, including a layer-by-layer heuristic method for SIMs PS configuration that prioritizes sum-HE for the ERs and a successive convex approximation (SCA)-based power allocation scheme to improve the achievable SE for the IRs. Numerical results show that our proposed algorithms achieve an almost 7-fold sum-HE gain as we increase the number of SIM layers, while the proposed power allocation (PPA) scheme often gains up to 40% in terms of the achievable minimum SE, compared to the equal power allocation.

Generalized Tensor-Aided Channel Estimation for Hardware Impaired Device Identification

In this paper, we investigate the joint generalized channel estimation and device identification problem in Internet of Things (IoT) networks {under multipath propagation}. To fully utilize the received signal, we decompose the generalized channel into three components: transmitter hardware characteristics, path gains, and angles of arrival. By modelling the received signals as parallel factor (PARAFAC) tensors, we develop alternating least squares (ALS)-based algorithms to simultaneously estimate the generalized channels and identify the transmitters. Simulation results show that the proposed scheme outperforms {both Khatri-Rao Factorization (KRF) and the conventional least squares (LS) method} in terms of channel estimation accuracy and achieves performance close to the derived Cramer-Rao lower bound.

RIS-enabled Multi-user M-QAM Uplink NOMA Systems: Design, Analysis, and Optimization

Non-orthogonal multiple access (NOMA) is widely recognized for enhancing the energy and spectral efficiency through effective radio resource sharing. However, uplink NOMA systems face greater challenges than their downlink counterparts, as their bit error rate (BER) performance is hindered by an inherent error floor due to error propagation caused by imperfect successive interference cancellation (SIC). This paper investigates BER performance improvements enabled by reconfigurable intelligent surfaces (RISs) in multi-user uplink NOMA transmission. Specifically, we propose a novel RIS-assisted uplink NOMA design, where the RIS phase shifts are optimized to enhance the received signal amplitudes while mitigating the phase rotations induced by the channel. To achieve this, we first develop an accurate channel model for the effective user channels, which facilitates our BER analysis. We then introduce a channel alignment scheme for a two-user scenario, enabling efficient SIC-based detection and deriving closed-form BER expressions. We further extend the analysis to a generalized setup with an arbitrary number of users and modulation orders for quadrature amplitude modulation signaling. Using the derived BER expressions, we develop an optimized uplink NOMA power allocation (PA) scheme that minimizes the average BER while satisfying the user transmit power constraints. It will be shown that the proposed NOMA detection scheme, in conjunction with the optimized PA strategy, eliminate SIC error floors at the base station. The theoretical BER expressions are validated using simulations, which confirms the effectiveness of the proposed design in eliminating BER floors.

Performance Analysis and Optimization of STAR-RIS-Aided Cell-Free Massive MIMO Systems Relying on Imperfect Hardware

Simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-aided cell-free massive multiple-input multiple-output (CF-mMIMO) systems are investigated under spatially correlated fading channels using realistic imperfect hardware. Specifically, the transceiver distortions, \textcolor{black}{time-varying phase noise, and RIS phase shift errors} are considered. Upon considering imperfect hardware and pilot contamination, we derive a linear minimum mean-square error (MMSE) criterion-based cascaded channel estimator. Moreover, a closed-form expression of the downlink ergodic spectral efficiency (SE) is derived based on maximum ratio (MR) based transmit precoding and channel statistics, where both a finite number of access points (APs) and STAR-RIS elements as well as imperfect hardware are considered. Furthermore, by exploiting the ergodic signal-to-interference-plus-noise ratios (SINRs) among user equipment (UE), a max-min fairness problem is formulated for the joint optimization of the passive transmitting and reflecting beamforming (BF) at the STAR-RIS as well as of the power control coefficients. An alternating optimization (AO) algorithm is proposed for solving the resultant problems, where iterative adaptive particle swarm optimization (APSO) and bisection methods are proposed for circumventing the non-convexity of the RIS passive BF and the quasi-concave power control sub-problems, respectively. Our simulation results illustrate that the STAR-RIS-aided CF-mMIMO system attains higher SE than its RIS-aided counterpart. The performance of different hardware parameters is also evaluated. Additionally, it is demonstrated that the SE of the worst UE can be significantly improved by exploiting the proposed AO-based algorithm compared to conventional solutions associated with random passive BF and equal-power scenarios.

Cell-Free Full-Duplex Communication -- An Overview

Cell-free (CF) architecture 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 inter-cell interference and improving 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.

Differential Evolution-Based End-Fire Realized Gain Optimization of Active and Parasitic Arrays

We propose a novel approach for boosting the realized gain in enhanced directivity arrays with both active and parasitic dipoles as radiating elements. The optimization process involves two main objectives: maximizing the end-fire gain and minimizing the reflection coefficient to ensure high realized gain. In the first step, the current excitation vector of the fully driven array is selected to maximize the end-fire gain. Then, all but one of the dipoles are reactively loaded according to their input impedance. Following that, the optimization focuses on the inter-element distance, computing the one that offers a favorable balance between the gain and the total efficiency. This multi-objective optimization leverages the differential evolution (DE) algorithm and utilizes a simple wire dipole as the unit element. Full-wave simulations further confirm the accuracy of our theoretical results. Our two- and three-element parasitic arrays achieve realized gain comparable to state-of-the-art designs, without relying on intricate unit elements or resource-intensive simulations. Moreover, our four- and five-element parasitic arrays deliver the highest realized gain values reported in the literature. The simplicity of our approach is validated by significant time savings, with theoretical models completing optimizations much faster than full-wave simulations. Additionally, a sensitivity analysis confirms the robustness of the proposed optimization algorithm, demonstrating that the optimized design parameters remain effective even under small deviations in loads and element positions. Finally, the proposed parasitic arrays are well-suited for base station antennas due to their compact design, reduced power consumption, and simplified hardware requirements, making them ideal for modern communication systems.

Anti-Malicious ISAC Using Proactive Monitoring

In this paper, we investigate proactive monitoring to mitigate malicious activities in integrated sensing and communication (ISAC) systems. Our focus is on a scenario where a cell-free massive multiple-input multiple-output (CF-mMIMO) architecture is exploited by malicious actors. Malicious actors use multiple access points (APs) to illegally sense a legitimate target while communicating with users (UEs), one of which is suspected of illegal activities. In our approach, a proactive monitor overhears the suspicious UE and simultaneously sends a jamming signal to degrade the communication links between the APs and suspicious UE. Simultaneously, the monitor sends a precoded jamming signal toward the legitimate target to hinder the malicious sensing attempts. We derive closed-form expressions for the sensing signal-to-interference-noise ratio (SINR), as well as the received SINR at the UEs and overheard SINR at the monitor. The simulation results show that our anti-malicious CF-mMIMO ISAC strategy can significantly reduce the sensing performance while offering excellent monitoring performance.

CSI Acquisition in Cell-Free Massive MIMO Surveillance Systems

We consider a cell-free massive multiple-input multiple-output (CF-mMIMO) surveillance system, in which multiple multi-antenna monitoring nodes (MNs) are deployed in either observing or jamming mode to disrupt the communication between a multi-antenna untrusted pair. We propose a simple and effective channel state information (CSI) acquisition scheme at the MNs. Specifically, our approach leverages pilot signals in both the uplink and downlink phases of the untrusted link, coupled with minimum mean-squared error (MMSE) estimation. This enables the MNs to accurately estimate the effective channels to both the untrusted transmitter (UT) and untrusted receiver (UR), thereby yielding robust monitoring performance. We analyze the spectral efficiency (SE) performance of the untrusted links and of the monitoring system, taking into account the proposed CSI acquisition and successive MMSE cancellation schemes. The monitoring success probability (MSP) is then derived. Simulation results show that the CF-mMIMO surveillance system, relying on the proposed CSI acquisition scheme, can achieve monitoring performance close to that achieved by having perfect CSI knowledge of the untrusted link (theoretical upper bound), especially when the number of MNs is large.

Analysis of Cross-Domain Message Passing for OTFS Transmissions

In this paper, we investigate the performance of the cross-domain iterative detection (CDID) framework with orthogonal time frequency space (OTFS) modulation, where two distinct CDID algorithms are presented. The proposed schemes estimate/detect the information symbols iteratively across the frequency domain and the delay-Doppler (DD) domain via passing either the a posteriori or extrinsic information. Building upon this framework, we investigate the error performance by considering the bias evolution and state evolution. Furthermore, we discuss their error performance in convergence and the DD domain error state lower bounds in each iteration. Specifically, we demonstrate that in convergence, the ultimate error performance of the CDID passing the a posteriori information can be characterized by two potential convergence points. In contrast, the ultimate error performance of the CDID passing the extrinsic information has only one convergence point, which, interestingly, aligns with the matched filter bound. Our numerical results confirm our analytical findings and unveil the promising error performance achieved by the proposed designs.

Ten Years of Research Advances in Full-Duplex Massive MIMO

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.