Performance Evaluation of Beyond Diagonal RIS under Hardware Impairments

TL;DR

This paper assesses how hardware imperfections in beyond diagonal RIS affect system performance, revealing conditions where traditional RIS may outperform BD-RIS due to impairments.

Contribution

It introduces three hardware impairment models for BD-RIS and evaluates their impact on channel estimation accuracy, highlighting the importance of hardware quality.

Findings

Impairments significantly degrade channel estimation accuracy.

Certain impairments can cause traditional RIS to outperform BD-RIS.

Performance degradation varies with impairment type and severity.

Abstract

Beyond diagonal reconfigurable intelligent surface (BD-RIS) improves the traditional reconfigurable intelligent surface (RIS) architecture functionality by interconnecting elements for advanced wave control. However, real-world implementations face hardware imperfections, such as impedance mismatches and varactor nonidealities, which can degrade overall system performance. In this paper, we propose three hardware impairment models that directly affect the BD-RIS scattering matrix structure and evaluate their impact on the channel estimation accuracy using the normalized mean square error (NMSE) as a performance metric. The proposed impairment models consider imperfections affecting self-impedances, mutual impedances, or both. Our results reveal how each impairment type degrades the system performance, allowing us to identify scenarios where the traditional RIS can outperform the BD-RIS.