Active and Passive Beamforming Designs for SER Minimization in RIS-Assisted MIMO Systems

TL;DR

This paper develops a joint active and passive beamforming strategy for RIS-assisted MIMO systems to minimize symbol error rate, using differential evolution optimization and local search, validated by simulations.

Contribution

It introduces a novel SER minimization framework for RIS-MIMO systems, incorporating a differential evolution algorithm with local search to optimize beamforming under practical constraints.

Findings

Joint beamforming significantly reduces SER compared to benchmarks.

The proposed optimization approach effectively handles non-convexity of the problem.

Simulation results confirm the analytical SER and the superiority of the method.

Abstract

This research exploits the applications of reconfigurable intelligent surface (RIS)-assisted multiple input multiple output (MIMO) systems, specifically addressing the enhancement of communication reliability with modulated signals. Specifically, we first derive the analytical downlink symbol error rate (SER) of each user as a multivariate function of both the phase-shift and beamforming vectors. The analytical SER enables us to obtain insights into the synergistic dynamics between the RIS and MIMO communication. We then introduce a novel average SER minimization problem subject to the practical constraints of the transmitted power budget and phase shift coefficients, which is NP-hard. By incorporating the differential evolution (DE) algorithm as a pivotal tool for optimizing the intricate active and passive beamforming variables in RIS-assisted communication systems, the non-convexity of the considered SER optimization problem can be effectively handled. Furthermore, an efficient local search is incorporated into the DE algorithm to overcome the local optimum, and hence offer low SER and high communication reliability. Monte Carlo simulations validate the analytical results and the proposed optimization framework, indicating that the joint active and passive beamforming design is superior to the other benchmarks.