Channel Estimation for Reconfigurable Intelligent Surface-Aided Multiuser Communication Systems Exploiting Statistical CSI of Correlated RIS-User Channels

TL;DR

This paper proposes a new channel estimation method for RIS-assisted multi-user systems that exploits channel correlation to reduce pilot overhead and improve estimation accuracy.

Contribution

It introduces a beam domain channel model and an eigenspace projection algorithm leveraging correlated RIS-user channels, reducing pilot overhead in multi-user RIS systems.

Findings

Achieves accurate channel estimation with lower pilot overhead.

Outperforms existing schemes in simulation.

Effectively exploits channel correlation for improved estimation.

Abstract

Reconfigurable intelligent surface (RIS) is a promising candidate technology for the upcoming Sixth Generation (6G) communication system for its ability to manipulate the wireless communication environment by controlling the coefficients of reflection elements (REs). However, since the RIS usually consists of a large number of passive REs, the pilot overhead for channel estimation in the RIS-aided system is prohibitively high. In this paper, the channel estimation problem for a RIS-aided multi-user multiple-input-single-output (MISO) communication system with clustered users is investigated. First, to describe the correlated feature for RIS-user channels, a beam domain channel model is developed for RIS-user channels. Then, a pilot reuse strategy is put forward to reduce the pilot overhead and decompose the channel estimation problem into several subproblems. Finally, by leveraging the correlated nature of RIS-user channels, an eigenspace projection (EP) algorithm is proposed to solve each subproblem respectively. Simulation results show that the proposed EP channel estimation scheme can achieve accurate channel estimation with lower pilot overhead than existing schemes.