MU-Massive MIMO With Multiple RISs: SINR Maximization and Asymptotic Analysis

Abstract

In this letter, we investigate the signal-tointerference-plus-noise-ratio (SINR) maximization problem in a multi-user massive multiple-input-multiple-output (massive MIMO) system enabled with multiple reconfigurable intelligent surfaces (RISs). We examine two zero-forcing (ZF) beamforming approaches for interference management namely BS-UE-ZF and BS-RIS-ZF that enforce the interference to zero at the users (UEs) and the RISs, respectively. Then, for each case, we resolve the SINR maximization problem to find the optimal phase shifts of the elements of the RISs. Also, we evaluate the asymptotic expressions for the optimal phase shifts and the maximum SINRs when the number of the base station (BS) antennas tends to infinity. We show that if the channels of the RIS elements are independent and the number of the BS antennas tends to infinity, random phase shifts achieve the maximum SINR using the BS-UE-ZF beamforming approach. The simulation results illustrate that by employing the BS-RIS-ZF beamforming approach, the asymptotic expressions of the phase shifts and maximum SINRs achieve the rate obtained by the optimal phase shifts even for a small number of the BS antennas.

Performance of Massive MIMO aided by Reflective Intelligent Surfaces

“…There are several challenges involving beamforming and phase shift design and optimization in a RIS-aided multi-user MIMO and massive MIMO scenarios with different objectives [2]- [11], including the maximization of the system sum-rate [2], [3], spectral efficiency [4] and energy efficiency [5], [6], or minimization of the transmission power [7], MAX-MIN SINR problem [8], [9], and the exposure to electromagnetic fields [10], [11]. Moreover, a more sophisticated setup involving multiple RIS is investigated in [12]. The authors investigate the SINR maximization problem in the downlink (DL) transmission of a multi-user massive MIMO system assisted with multiple RISs.…”

“…In this scenario, they assume that the BS directly serves some of the UEs, while others have no direct channel to the BS and are served through the RISs. Each RIS serves several UEs in a specific geographic area, forming a cluster [12]. A zero-forcing (ZF) beamforming approach is deployed at the BS, completely canceling the interference, allowing the asymptotic analysis, and facilitating the RIS phase-shift matrices design.…”

“…In the multi-user scenarios, we consider the correlation coefficient between RIS elements, defined experimentally by evaluating samples of the overall massive MIMO channel for the k-th user [12]:…”

Efficiently Refining Beampattern in FDA-MIMO Radar via Alternating Manifold Optimization for Maximizing Signal-to-Interference-Noise Ratio

“…To obtain a transceiver waveform with high quality and reliability, we study the joint design of the transmit waveform and receive filter. The SINR is a fundamental metric used for evaluating the overall system performance [44][45][46]. In the FDA-MIMO radar, crucial tasks such as target detection, interference suppressing, target tracking, and synthetic aperture radar imaging necessitate a higher SINR output to facilitate the comprehensive acquisition of multi-dimensional information.…”