MSE Minimization in RIS-Aided MU-MIMO with Discrete Phase Shifts and Fronthaul Quantization

TL;DR

This paper addresses the challenge of optimizing MU-MIMO systems aided by RIS with practical constraints like limited fronthaul capacity and discrete phase shifts, proposing an SESD-based algorithm for MSE minimization.

Contribution

It introduces a novel SESD-based optimization algorithm for joint precoding and RIS configuration under realistic system constraints.

Findings

SESD-based method achieves near-optimal MSE performance.

The proposed approach effectively handles discrete phase shifts and fronthaul limitations.

Numerical results confirm significant performance improvements.

Abstract

In this paper, we consider a downlink multi-user multiple-input multiple-output (MU-MIMO) communication assisted by a reconfigurable intelligent surface (RIS) and study the precoding and RIS configuration design under practical system constraints. These constraints include the limited-capacity fronthaul at the transmitter side and the finite resolution of RIS elements. We investigate the sum mean squared error (MSE) minimization problem and propose an algorithm based on the block coordinate descent method to optimize the precoding, RIS configuration, and receiver gains. We compute the precoding vectors and RIS configuration using the Schnorr-Euchner sphere decoding (SESD) method which delivers the optimal MSE-minimizing solution. We numerically evaluate the performance of the proposed SESD-based methods and corroborate their effectiveness in improving the system performance.