Model-free Optimization and Experimental Validation of RIS-assisted Wireless Communications under Rich Multipath Fading

TL;DR

This paper introduces a model-free optimization method for RIS-assisted wireless systems that enhances signal quality without requiring detailed channel models, validated through simulations and real-world experiments.

Contribution

It proposes a novel cross-entropy algorithm for binary RIS configuration optimization that operates without channel state information, simplifying practical implementation.

Findings

The CE algorithm effectively improves SNR in RIS-assisted systems.

Experimental validation confirms the channel hardening effect under rich multipath fading.

The method reduces computational complexity compared to traditional optimization techniques.

Abstract

Reconfigurable intelligent surface (RIS) devices have emerged as an effective way to control the propagation channels for enhancing the end-users' performance. However, RIS optimization involves configuring the radio frequency response of a large number of radiating elements, which is challenging in real-world applications due to high computational complexity. In this paper, a model-free cross-entropy (CE) algorithm is proposed to optimize the binary RIS configuration for improving the signal-to-noise ratio (SNR) at the receiver. One key advantage of the proposed method is that it only requires system performance indicators, e.g., the received SNR, without the need for channel models or channel state information. Both simulations and experiments are conducted to evaluate the performance of the proposed CE algorithm. This study provides an experimental demonstration of the channel hardening effect in a multi-antenna RIS-assisted wireless system under rich multipath fading.