Model-Free Optimization for Reconfigurable Intelligent Surface with Statistical CSI

TL;DR

This paper introduces two model-free algorithms to optimize reconfigurable intelligent surfaces in wireless communication systems using statistical CSI, significantly improving performance over random schemes especially in low channel randomness scenarios.

Contribution

The paper proposes novel model-free algorithms for RIS phase shift optimization based on statistical CSI, applicable under any channel assumptions.

Findings

Algorithms outperform random phase schemes

Performance improves with lower channel randomness

Applicable to various statistical channel models

Abstract

In this paper, a single user multiple input single output downlink wireless communication system is investigated, in which multiple reconfigurable intelligent surfaces (RISs) are deployed to improve the propagation condition. Our objective is to optimize the phase shift matrices of all the RISs by exploiting the statistical channel state information (CSI). In particular, two model-free algorithms are proposed, which are applicable for any channel statistical assumptions. Numerical results show that the proposed algorithms significantly outperform the random phase shift scheme, especially when the channel randomness is low.