Channel Estimation for RIS Assisted Wireless Communications: Part II -- An Improved Solution Based on Double-Structured Sparsity

TL;DR

This paper introduces a novel channel estimation method for RIS-assisted wireless systems that leverages double-structured sparsity to significantly reduce pilot overhead, improving efficiency in multi-user scenarios.

Contribution

It proposes the double-structured orthogonal matching pursuit (DS-OMP) algorithm that jointly estimates common sparsity patterns across users, a novel approach in RIS channel estimation.

Findings

Reduced pilot overhead compared to existing methods

Effective exploitation of double-structured sparsity in channels

Improved accuracy in multi-user channel estimation

Abstract

Reconfigurable intelligent surface (RIS) can manipulate the wireless communication environment by controlling the coefficients of RIS elements. However, due to the large number of passive RIS elements without signal processing capability, channel estimation in RIS assisted wireless communication system requires high pilot overhead. In the second part of this invited paper, we propose to exploit the double-structured sparsity of the angular cascaded channels among users to reduce the pilot overhead. Specifically, we first reveal the double-structured sparsity, i.e., different angular cascaded channels for different users enjoy the completely common non-zero rows and the partially common non-zero columns. By exploiting this double-structured sparsity, we further propose the double-structured orthogonal matching pursuit (DS-OMP) algorithm, where the completely common non-zero rows and the partially common non-zero columns are jointly estimated for all users. Simulation results show that the pilot overhead required by the proposed scheme is lower than existing schemes.