Power Minimization with Rate Constraints for Multi-User MIMO Systems with Large-Size RISs

TL;DR

This paper proposes an iterative optimization method for minimizing power in multi-user MIMO systems with large RISs, balancing power efficiency and signal quality constraints.

Contribution

It introduces a novel two-step alternating optimization approach that efficiently configures large RISs by partitioning them into tiles, reducing computational complexity.

Findings

The proposed method achieves lower power consumption compared to benchmarks.

It maintains user SINR constraints effectively.

The approach demonstrates good performance with limited computational complexity.

Abstract

This study focuses on the optimization of a single-cell multi-user multiple-input multiple-output (MIMO) system with multiple large-size reconfigurable intelligent surfaces (RISs). The overall transmit power is minimized by optimizing the precoding coefficients and the RIS configuration, with constraints on users' signal-to-interference-plus-noise ratios (SINRs). The minimization problem is divided into two sub-problems and solved by means of an iterative alternating optimization (AO) approach. The first sub-problem focuses on finding the best precoder design. The second sub-problem optimizes the configuration of the RISs by partitioning them into smaller tiles. Each tile is then configured as a combination of pre-defined configurations. This allows the efficient optimization of RISs, especially in scenarios where the computational complexity would be prohibitive using traditional approaches. Simulation results show the good performance and limited complexity of the proposed method in comparison to benchmark schemes.