Efficient Optimization Techniques for RIS-aided Wireless Systems

TL;DR

This paper introduces simple, effective optimization techniques for RIS-aided wireless systems, including channel separation and iterative algorithms, to improve uplink sum rates and MMSE performance, validated through simulations.

Contribution

It proposes novel channel separation and simple iterative algorithms for optimizing RIS phases, offering practical alternatives to complex numerical methods.

Findings

Channel separation improves understanding of RIS phase effects.

Iterative algorithms enhance uplink sum rates with discrete phases.

Closed-form solutions optimize continuous phases effectively.

Abstract

The objective of this paper is to develop simple techniques to enhance the performance of multi-user RIS aided wireless systems. Specifically, we develop a novel technique called \textit{channel separation} which provides a better understanding of how the RIS phases affect the uplink sum rate and sum rates for ZF and MMSE linear receivers. Leveraging channel separation, we propose a simple iterative algorithm to improve the uplink sum rate and the sum rates of ZF and MMSE linear receivers when discrete RIS phases are considered. For continuous RIS phases, we derive simple closed form solutions to enhance the uplink sum rate and reduce the total mean square error of the MMSE combiner. The latter metric is a tractable alternative to maximizing sum rates for ZF and MMSE. Numerical simulations are performed for all optimization techniques and the effectiveness of each technique is compared to a full numerical optimization procedure, namely an interior point (IP) algorithm.