Cell-free wireless networks have attracted significant interest for their ability to eliminate cell-edge effects and deliver uniformly high service quality through macro-diversity. In this paper, we develop an algorithm to jointly optimize uplink transmit powers and dynamic user-centric access point (AP) clusters in a centralized cell-free network. This approach aims to efficiently mitigate inter-user interference and achieve higher max-min signal-to-interference-plus-noise ratio (SINR) targets for users. To this end, we re-purpose an iterative power control algorithm based on non-linear Perron-Frobenius theory and prove its convergence for the maximum ratio combiner (MRC) receiver under various AP subset selection schemes. We further provide analytical results by framing the joint optimization as a conditional eigenvalue problem with power and AP association constraints, and leveraging Perron-Frobenius theory on a centrally constructed matrix. The numerical results highlight that optimizing each user’s serving AP cluster is essential to achieving higher max-min SINR targets with the simple MRC receiver.

Recent developments in Multiple-Input-Multiple-Output (MIMO) technology include packing a large number of antenna elements in a compact array to access the bandwidth benefits provided by higher mutual coupling (MC). The resulting super-wideband (SW) systems require a circuit-theoretic framework to handle the MC and channel models which span extremely large bands. Hence, in this paper, we make two key contributions. First, we develop a physically-consistent Rician channel model for use with SW systems. Secondly, we express the circuit-theoretic models in terms of a standard MIMO model, so that insights into the effects of antenna layouts, MC, and bandwidth can be made using standard communication theory. For example, we show the bandwidth widening resulting from the new channel model. In addition, we show that MC distorts line-of-sight paths which has beamforming implications. We also highlight the interaction between spatial correlation and MC and show that tight coupling reduces spatial correlations at low frequencies.

Cell-free wireless networks have garnered significant interest within the research community due to their potential to eliminate cell-edge effects and exploit macro-diversity. In this paper, we design algorithms to jointly optimize uplink transmit powers and dynamic user-centric clusters within a cell-free network. This strategy aims to effectively mitigate inter-user interference and attain spectral efficiency targets for users in a scalable manner. To serve this goal, we re-purpose a classic iterative algorithm and prove its convergence for both the maximum ratio combiner (MRC) and linear minimum mean square error (LMMSE) receivers. We present several access point (AP) subset selection schemes of varying complexity and demonstrate how clustering requirements differ according to receiver capabilities. In particular, we show that optimizing the serving cluster for each user is crucial when using the simple MRC receiver.

This paper considers multiuser millimeter wave (mmWave) MIMO communication systems where both the base station (BS) and the user equipments (UEs) use analog beamforming (BF). We propose a beam acquisition approach to find the best directions for the narrow beams, required to achieve BS-UE links above a minimum signal-to-noise ratio (SNR) threshold. The multiple UEs first select their beams simultaneously, based on signals transmitted from the BS on wide training beams. The BS then switches to a beam acquisition mode in order to select the best beam direction for each UE, based on training signals the UEs send on the uplink. We propose a novel parallel beam acquisition scheme for this uplink phase. We also propose a user rejection policy, in which weak UEs that do not satisfy a target SNR threshold, equivalent to a certain bit error rate, are rejected. To do so, we derive the posterior probability that a BS beam has a resultant SNR below the target SNR threshold. We also propose a generalized likelihood ratio test (GLRT) to reduce the computational burden. We derive closed-form error probability expressions for the proposed GLRT approach, and examine the trade-off between the beam acquisition time and accuracy in selecting the beams. We show that the beam acquisition time of our proposed approach is as low as 3% of existing approaches.

Building on recent trends in multiple-input multiple-output and reconfigurable intelligent surfaces, where densely spaced element arrays are considered, this paper focuses on con-tinuous antenna systems where the receive antenna is modelled as a continuous line (in the one-dimensional case) or a continuous surface (in the two-dimensional case). Considering a spatially-correlated Rayleigh process for the communication channel, we conduct an analytical investigation based on matched filtering. More specifically, we derive an approximated distribution for the instantaneous received signal-to-noise ratio (SNR) at the continuous surface. Furthermore, we derive approximations to the achievable rate, average symbol error rate for Mary phase shift keying (MPSK) and an upper bound for the achievable rate. We use extensive numerical examples to illustrate the accuracy of our approximation to the SNR distribution as well as the performance analysis.

This paper considers the implementation of compressive sensing (CS) approaches for beam alignment (BA) in multiuser millimeter wave (mmWave) MIMO systems. We particularly consider wideband time-varying channels in the practical low SNR regime. We examine two different time scales for beam-switching in the BA training phase at both the base station (BS) and the user equipment (UE). We also compare different time scales for running the CS algorithm at the UE, with their corresponding overhead and complexity. We propose an overarching trial-based protocol that re- initializes the BA process at particular times. We also propose a new approach to designing the CS sensing matrix (SM), based on a deterministic construction. Rows of our proposed SM are Kronecker product decomposable, making it ideal for the BA problem. We show that when block-based beam switching is employed in combination with running the CS algorithm Every Epoch (CS-EE), our proposed SM gives superior performance compared to the other approaches. Moreover, our proposed overarching trial-based protocol enhances the performance even further. We also show that running the CS algorithm Every Block (CS-EB) outperforms CS-EE at the cost of higher complexity and overhead.

This study concerns maximising the minimum achievable secrecy rate (ASR) of a two‐way relay network in the presence of an eavesdropper, in which two nodes aim to exchange messages in two hops, using a multi‐antenna relay. Throughout the first hop, the two nodes simultaneously transmit their messages to the relay. In the second hop, the relay broadcasts a combination of the received information to the users such that the transmitted signal lies in the null space of the eavesdropper's channel; this is called null space beamforming (NSBF). The best NSBF matrix for maximising the minimum ASR is studied, showing that the problem is not convex in general. To address this issue, the problem is divided into three sub‐problems: a close‐to‐optimal solution is derived by using the semi‐definite relaxation technique. Simulation results demonstrate the superiority of the proposed method w.r.t. the most well‐known method addressed in the literature.