Modular Arrays (MAs) are a promising architecture to enable multi-user communications in next-generation multiple-input multiple-output (MIMO) systems based on extra-large (XL) or gigantic MIMO (gMIMO) deployments, trading off improved spatial resolution with characteristic interference patterns associated with grating lobes. In this work, we analyze whether MAs can outperform conventional collocated deployments, in terms of achievable sum-spectral efficiency (SE) and served users in a multi-user downlink set-up. First, we provide a rigorous analytical characterization of the inter-user interference for modular gMIMO systems operating in the near field. Then, we leverage these results to optimize the user selection and precoding mechanisms, designing two algorithms that largely outperform existing alternatives in the literature, with different algorithmic complexities. Results show that the proposed algorithms yield over 70% improvements in achievable sum-spectral efficiencies compared to the state of the art. We also illustrate how MAs allows us to serve a larger number of users thanks to their improved spatial resolution, compared to the collocated counterpart.

This paper analyzes the key differences between the plane-wave (PW) and the spherical-wavefront (SW) models in the context of physical layer security (PLS) for extra-large (XL)-multiple-input multiple-output (MIMO) systems with multiple eavesdroppers. Both colluding and non-colluding strategies are considered for the different eavesdroppers. Results show that the propagation features associated to the SW model allow to reach higher secrecy rates, and to reduce the areas where an eavesdropper makes secure communication unfeasible.

This paper jointly addresses user scheduling and precoder/combiner design in the downlink of a wideband millimeter-wave communications system. We consider the orthogonal frequency-division multiplexing modulation to overcome the channel frequency selectivity and obtain a number of equivalent narrowband channels. Hence, the main challenge is that the analog preprocessing network is frequency flat and common to all the users at the transmitter side. Moreover, the effect of the signal bandwidth over the uniform linear array steering vectors has to be taken into account to design the hybrid precoders and combiners. The proposed algorithmic solution is based on the linear successive allocation, which greedily allocates streams to different users and computes the corresponding precoders and combiners. By taking into account the rank limitations imposed by the hardware at transmission and reception, the performance loss in terms of achievable sum rate for the hybrid approach is negligible. The numerical experiments show that the proposed method exhibits excellent performance with reasonable computational complexity.

This paper focuses on distributed linear precoding when users transmit correlated information over a fading multiple-input and multiple-output multiple access channel. The precoders are optimized in order to minimize the sum-mean square error (MSE) between the source and the estimated symbols. When sources are correlated, minimizing the sum-MSE results in a non-convex optimization problem. The precoders for an arbitrary number of users and transmit and receive antennas are thus obtained via a projected steepest-descent algorithm and a low-complexity heuristic approach. For the more restrictive case of two single-antenna users, a closed-form expression for the minimum sum-MSE precoders is derived. Moreover, for the scenario with a single receive antenna and any number of users, a solution is obtained by means of a semi-definite relaxation. Finally, we also consider precoding schemes where the precoders are decomposed into complex scalars and unit norm vectors. Simulation results show a significant improvement when source correlation is exploited at precoding, especially for low signal-to-noise ratios and when the number of receive antennas is lower than the number of transmitting nodes.

In this work we consider the problem of designing the precoders and combiners in a multiuser hybrid frequency selective millimeter wave (mmWave) system. We propose two methods to design the hybrid analog-digital filters when only an estimate of the channel is available at both the base station (BS) and the users. The first one is a projected gradient method that factorizes the all-digital solution, while the second approach is based on an alternating minimization (AM) iterative strategy. The channel is estimated using an algorithm that takes into account the hardware limitations of the hybrid architecture and leverages the sparse structure of mmWave channels. The proposed methods are evaluated in terms of achievable sum rate, outperforming the state of the art solutions. The negligible impact of the hybrid structure and the imperfect channel knowledge on the system performance are shown via numerical experiments.

We address the evaluation of low-complexity analog Joint Source Channel Coding (JSCC) methods for the transmission of discrete-time analog symbols over Multiple-Input Multiple-Output (MIMO) Multiple Access Channels (MAC). Analog JSCC is employed to encode the source information at each transmitter prior to be directly input to the MAC access scheme. Three channel access methods are considered to ensure the receiver is able to recover the user information: Code Division Multiple Access (CDMA), linear MMSE access codes and opportunistic access. CDMA allows the orthogonal transmission of the user data requiring only Channel State Information (CSI) at reception. On the other hand, linear MMSE access codes exploit CSI knowledge at transmission and exhibit better performance. Finally, opportunistic access also exploits CSI at transmission and allocates all MAC resources to the user with the strongest channel. This latter access scheme exhibits the best performance in terms of sum distortion although it may lead to unfair rate distributions among users.

The aim of this work is to jointly achieve individual rate requirements and minimum total transmit power in the vector Broadcast Channel (BC). Data streams are transmitted from a multi-antenna base station to several non-cooperative single-antenna receivers having perfect Channel-State-Information (CSI). Partial CSI, e.g., obtained via feedback, is used for the design of linear transmit filters at the transmitter. Employing a duality between Multiple Access Channel (MAC) and BC rate regions and the so-called standard interference functions, we propose an algorithmic joint solution for the transmit filter design and the power allocation in this work.