Reconfigurable intelligent surface (RIS): Eigenvalue Decomposition-Based Separate Channel Estimation

TL;DR

This paper introduces an eigenvalue decomposition-based method for separate channel estimation in RIS-MIMO systems, effectively modeling the channel as a keyhole MIMO system to reduce estimation time and error.

Contribution

It proposes a novel disassembled channel estimation framework for RIS-MIMO using EVD, enabling separate link estimation and improved efficiency.

Findings

Low estimation time overhead

Reduced estimation error

Effective modeling of RIS-MIMO as keyhole MIMO

Abstract

Reconfigurable intelligent surface (RIS) has recently drawn significant attention in wireless communication technologies. However, identifying, modeling, and estimating the RIS channel in multiple-input multiple-output (MIMO) systems are considered challenging in recent studies. In this paper, a disassembled channel estimation framework for the RIS-MIMO system is proposed based on the eigenvalue decomposition (EVD) concept to separate the cascaded channel links and estimate each link separately. This estimation is based on modeling the RIS-MIMO channel as a keyhole MIMO system model. Numerical results show that the proposed estimation method has a low estimation time overhead while providing less estimation error.