On the BER vs. Bandwidth-Efficiency Trade-offs in Windowed OTSM Dispensing with Zero-Padding

An orthogonal time sequency multiplexing (OTSM) scheme using practical signaling functions is proposed under strong phase noise (PHN) scenarios. By utilizing the transform relationships between the delay-sequency (DS), time-frequency (TF) and time-domains, we first conceive the DS-domain input-output relationship of our OTSM system, where the conventional zero-padding is discarded to increase the spectral efficiency. Then, the unconditional pairwise error probability is derived, followed by deriving the bit error ratio (BER) upper bound in closed-form. Moreover, we compare the BER performance of our OTSM system based on several practical signaling functions. Our simulation results demonstrate that the upper bound derived accurately predicts the BER performance in the case of moderate to high signal-to-noise ratios (SNRs), while harnessing practical window functions is capable of attaining an attractive out-of-band emission (OOBE) vs. BER trade-off.

Cell-Free Massive MIMO SWIPT with Beyond Diagonal Reconfigurable Intelligent Surfaces

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.

Joint Power Optimization and AP Selection for Secure Cell-Free Massive MIMO

In this paper, we investigate joint power control and access point (AP) selection scheme in a cell-free massive multiple-input multiple-output (CF-mMIMO) system under an active eavesdropping attack, where an eavesdropper tries to overhear the signal sent to one of the legitimate users by contaminating the uplink channel estimation. We formulate a joint optimization problem to minimize the eavesdropping spectral efficiency (SE) while guaranteeing a given SE requirement at legitimate users. The challenging formulated problem is converted into a more tractable form and an efficient low-complexity accelerated projected gradient (APG)-based approach is proposed to solve it. Our findings reveal that the proposed joint optimization approach significantly outperforms the heuristic approaches in terms of secrecy SE (SSE). For instance, the $50\%$ likely SSE performance of the proposed approach is $265\%$ higher than that of equal power allocation and random AP selection scheme.

Ultra-Dense Cell-Free Massive MIMO for 6G: Technical Overview and Open Questions

Ultra-dense cell-free massive multiple-input multiple-output (CF-MMIMO) has emerged as a promising technology expected to meet the future ubiquitous connectivity requirements and ever-growing data traffic demands in 6G. This article provides a contemporary overview of ultra-dense CF-MMIMO networks, and addresses important unresolved questions on their future deployment. We first present a comprehensive survey of state-of-the-art research on CF-MMIMO and ultra-dense networks. Then, we discuss the key challenges of CF-MMIMO under ultra-dense scenarios such as low-complexity architecture and processing, low-complexity/scalable resource allocation, fronthaul limitation, massive access, synchronization, and channel acquisition. Finally, we answer key open questions, considering different design comparisons and discussing suitable methods dealing with the key challenges of ultra-dense CF-MMIMO. The discussion aims to provide a valuable roadmap for interesting future research directions in this area, facilitating the development of CF-MMIMO MIMO for 6G.

Joint Power Allocation and User Scheduling in Integrated Satellite-Terrestrial Cell-Free Massive MIMO IoT Systems

Both space and ground communications have been proven effective solutions under different perspectives in Internet of Things (IoT) networks. This paper investigates multiple-access scenarios, where plenty of IoT users are cooperatively served by a satellite in space and access points (APs) on the ground. Available users in each coherence interval are split into scheduled and unscheduled subsets to optimize limited radio resources. We compute the uplink ergodic throughput of each scheduled user under imperfect channel state information (CSI) and non-orthogonal pilot signals. As maximum-radio combining is deployed locally at the ground gateway and the APs, the uplink ergodic throughput is obtained in a closed-form expression. The analytical results explicitly unveil the effects of channel conditions and pilot contamination on each scheduled user. By maximizing the sum throughput, the system can simultaneously determine scheduled users and perform power allocation based on either a model-based approach with alternating optimization or a learning-based approach with the graph neural network. Numerical results manifest that integrated satellite-terrestrial cell-free massive multiple-input multiple-output systems can significantly improve the sum ergodic throughput over coherence intervals. The integrated systems can schedule the vast majority of users; some might be out of service due to the limited power budget.

Joint User Association and Power Control for Cell-Free Massive MIMO

This work proposes novel approaches that jointly design user equipment (UE) association and power control (PC) in a downlink user-centric cell-free massive multiple-input multiple-output (CFmMIMO) network, where each UE is only served by a set of access points (APs) for reducing the fronthaul signalling and computational complexity. In order to maximize the sum spectral efficiency (SE) of the UEs, we formulate a mixed-integer nonconvex optimization problem under constraints on the per-AP transmit power, quality-of-service rate requirements, maximum fronthaul signalling load, and maximum number of UEs served by each AP. In order to solve the formulated problem efficiently, we propose two different schemes according to the different sizes of the CFmMIMO systems. For small-scale CFmMIMO systems, we present a successive convex approximation (SCA) method to obtain a stationary solution and also develop a learning-based method (JointCFNet) to reduce the computational complexity. For large-scale CFmMIMO systems, we propose a low-complexity suboptimal algorithm using accelerated projected gradient (APG) techniques. Numerical results show that our JointCFNet can yield similar performance and significantly decrease the run time compared with the SCA algorithm in small-scale systems. The presented APG approach is confirmed to run much faster than the SCA algorithm in the large-scale system while obtaining an SE performance close to that of the SCA approach. Moreover, the median sum SE of the APG method is up to about 2.8 fold higher than that of the heuristic baseline scheme.

Protecting Massive MIMO-Radar Coexistence: Precoding Design and Power Control

This paper studies the coexistence between a downlink multiuser massive multi-input-multi-output (MIMO) communication system and MIMO radar. The performance of the massive MIMO system with maximum ratio ($\MR$), zero-forcing ($\ZF$), and protective $\ZF$ ($\PZF$) precoding designs is characterized in terms of spectral efficiency (SE) and by taking the channel estimation errors and power control into account. The idea of $\PZF$ precoding relies on the projection of the information-bearing signal onto the null space of the radar channel to protect the radar against communication signals. We further derive closed-form expressions for the detection probability of the radar system for the considered precoding designs. By leveraging the closed-form expressions for the SE and detection probability, we formulate a power control problem at the radar and base station (BS) to maximize the detection probability while satisfying the per-user SE requirements. This optimization problem can be efficiently tackled via the bisection method by solving a linear feasibility problem. Our analysis and simulations show that the $\PZF$ design has the highest detection probability performance among all designs, with intermediate SE performance compared to the other two designs. Moreover, by optimally selecting the power control coefficients at the BS and radar, the detection probability improves significantly.

Cell-Free Massive MIMO Surveillance Systems

Wireless surveillance, in which untrusted communications links are proactively monitored by legitimate agencies, has started to garner a lot of interest for enhancing the national security. In this paper, we propose a new cell-free massive multiple-input multiple-output (CF-mMIMO) wireless surveillance system, where a large number of distributed multi-antenna aided legitimate monitoring nodes (MNs) embark on either observing or jamming untrusted communication links. To facilitate concurrent observing and jamming, a subset of the MNs is selected for monitoring the untrusted transmitters (UTs), while the remaining MNs are selected for jamming the untrusted receivers (URs). We analyze the performance of CF-mMIMO wireless surveillance and derive a closed-form expression for the monitoring success probability of MNs. We then propose a greedy algorithm for the observing vs, jamming mode assignment of MNs, followed by the conception of a jamming transmit power allocation algorithm for maximizing the minimum monitoring success probability concerning all the UT and UR pairs based on the associated long-term channel state information knowledge. In conclusion, our proposed CF-mMIMO system is capable of significantly improving the performance of the MNs compared to that of the state-of-the-art baseline. In scenarios of a mediocre number of MNs, our proposed scheme provides an 11-fold improvement in the minimum monitoring success probability compared to its co-located mMIMO benchmarker.

Cell-Free Massive MIMO for ISAC: Access Point Operation Mode Selection and Power Control

This paper considers a cell-free massive multipleinput multiple-output (MIMO) integrated sensing and communication (ISAC) system, where distributed MIMO access points (APs) are used to jointly serve the communication users and detect the presence of a single target. We investigate the problem of AP operation mode selection, wherein some APs are dedicated for downlink communication, while the remaining APs are used for sensing purposes. Closed-form expressions for the individual spectral efficiency (SE) and mainlobe-to-average-sidelobe ratio (MASR) are derived, which are respectively utilized to assess the communication and sensing performances. Accordingly, a maxmin fairness problem is formulated and solved, where the minimum SE of the users is maximized, subject to the per-AP power constraints as well as sensing MASR constraint. Our numerical results show that the proposed AP operation mode selection with power control can significantly improve the communication performance for given sensing requirements.

Cell-free Massive MIMO and SWIPT: Access Point Operation Mode Selection and Power Control

This paper studies cell-free massive multiple-input multiple-output (CF-mMIMO) systems incorporating simultaneous 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.