Active and Passive Beamforming Designs for SER Minimization in RIS-Assisted MIMO Systems

This research exploits the applications of reconfigurable intelligent surface (RIS)-assisted multiple input multiple output (MIMO) systems, specifically addressing the enhancement of communication reliability with modulated signals. Specifically, we first derive the analytical downlink symbol error rate (SER) of each user as a multivariate function of both the phase-shift and beamforming vectors. The analytical SER enables us to obtain insights into the synergistic dynamics between the RIS and MIMO communication. We then introduce a novel average SER minimization problem subject to the practical constraints of the transmitted power budget and phase shift coefficients, which is NP-hard. By incorporating the differential evolution (DE) algorithm as a pivotal tool for optimizing the intricate active and passive beamforming variables in RIS-assisted communication systems, the non-convexity of the considered SER optimization problem can be effectively handled. Furthermore, an efficient local search is incorporated into the DE algorithm to overcome the local optimum, and hence offer low SER and high communication reliability. Monte Carlo simulations validate the analytical results and the proposed optimization framework, indicating that the joint active and passive beamforming design is superior to the other benchmarks.

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.

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.

Energy Harvesting Characterization in Cell-Free Massive MIMO Using Markov Chains

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.

Hybrid OTFS/OFDM Design in Massive MIMO

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.

Next Generation Multiple Access with Cell-Free Massive MIMO

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), non-orthogonal transmission schemes, millimeter-wave (mmWave) communications, ultra-reliable low-latency communication (URLLC), unmanned aerial vehicle (UAV)-aided communication, and reconfigurable intelligent surfaces (RISs). In this paper, 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.

RIS-Assisted Cell-Free Massive MIMO Relying on Reflection Pattern Modulation

We propose reflection pattern modulation-aided reconfigurable intelligent surface (RPM-RIS)-assisted cell-free massive multiple-input-multiple-output (CF-mMIMO) schemes for green uplink transmission. In our RPM-RIS-assisted CF-mMIMO system, extra information is conveyed by the indices of the active RIS blocks, exploiting the joint benefits of both RIS-assisted CF-mMIMO transmission and RPM. Since only part of the RIS blocks are active, our proposed architecture strikes a flexible energy \emph{vs.} spectral efficiency (SE) trade-off. We commence with introducing the system model by considering spatially correlated channels. Moreover, we conceive a channel estimation scheme subject to the linear minimum mean-square error (MMSE) constraint, yielding sufficient information for the subsequent signal processing steps. Then, upon exploiting a so-called large-scale fading decoding (LSFD) scheme, the uplink signal-to-interference-and-noise ratio (SINR) is derived based on the RIS ON/OFF statistics, where both maximum ratio (MR) and local minimum mean-square error (L-MMSE) combiners are considered. By invoking the MR combiner, the closed-form expression of the uplink SE is formulated based only on the channel statistics. Furthermore, we derive the total energy efficiency (EE) of our proposed RPM-RIS-assisted CF-mMIMO system. Additionally, we propose a chaotic sequence-based adaptive particle swarm optimization (CSA-PSO) algorithm to maximize the total EE by designing the RIS phase shifts. Finally, our simulation results demonstrate that the proposed RPM-RIS-assisted CF-mMIMO architecture strikes an attractive SE \emph{vs.} EE trade-off, while the CSA-PSO algorithm is capable of attaining a significant EE performance gain compared to conventional solutions.

Cell-Free Massive MIMO Surveillance of Multiple Untrusted Communication Links

A cell-free massive multiple-input multiple-output (CF-mMIMO) system is considered for enhancing the monitoring performance of wireless surveillance, where a large number of distributed multi-antenna aided legitimate monitoring nodes (MNs) proactively monitor multiple distributed untrusted communication links. We consider two types of MNs whose task is to either observe the untrusted transmitters or jam the untrusted receivers. We first analyze the performance of CF-mMIMO surveillance relying on both maximum ratio (MR) and partial zero-forcing (PZF) combining schemes and derive closed-form expressions for the monitoring success probability (MSP) of the MNs. We then propose a joint optimization technique that designs the MN mode assignment, power control, and MN-weighting coefficient control to enhance the MSP based on the long-term statistical channel state information knowledge. This challenging problem is effectively transformed into tractable forms and efficient algorithms are proposed for solving them. Numerical results show that our proposed CF-mMIMO surveillance system considerably improves the monitoring performance with respect to a full-duplex co-located massive MIMO proactive monitoring system. More particularly, when the untrusted pairs are distributed over a wide area and use the MR combining, the proposed solution provides nearly a thirty-fold improvement in the minimum MSP over the co-located massive MIMO baseline, and forty-fold improvement, when the PZF combining is employed.

Analysis and Optimization of RIS-Assisted Cell-Free Massive MIMO NOMA Systems

We consider a reconfigurable intelligent surface (RIS) assisted cell-free massive multiple-input multiple-output non-orthogonal multiple access (NOMA) system, where each access point (AP) serves all the users with the aid of the RIS. We practically model the system by considering imperfect instantaneous channel state information (CSI) and employing imperfect successive interference cancellation at the users end. We first obtain the channel estimates using linear minimum mean square error approach considering the spatial correlation at the RIS and then derive a closed-form downlink spectral efficiency (SE) expression using the statistical CSI. We next formulate a joint optimization problem to maximize the sum SE of the system. We first introduce a novel successive Quadratic Transform (successive-QT) algorithm to optimize the transmit power coefficients using the concept of block optimization along with quadratic transform and then use the particle swarm optimization technique to design the RIS phase shifts. Note that most of the existing works on RIS-aided cell-free systems are specific instances of the general scenario studied in this work. We numerically show that i) the RIS-assisted link is more advantageous at lower transmit power regions where the direct link between AP and user is weak, ii) NOMA outperforms orthogonal multiple access schemes in terms of SE, and iii) the proposed joint optimization framework significantly improves the sum SE of the system.