Near-Field RIS-Assisted Localization Under Mutual Coupling

TL;DR

This paper investigates the detrimental effects of mutual coupling in near-field RIS-assisted localization systems and proposes a joint estimation method to mitigate these effects, significantly improving localization accuracy.

Contribution

It introduces a novel joint localization and mutual coupling parameter estimation method that accounts for mutual coupling effects in near-field RIS systems.

Findings

Mutual coupling severely degrades localization accuracy if ignored.

The proposed JLMC method outperforms classical approaches that neglect mutual coupling.

Simulation results confirm the effectiveness of the joint estimation approach.

Abstract

Reconfigurable intelligent surfaces (RISs) have the potential to significantly enhance the performance of integrated sensing and communication (ISAC) systems, particularly in line-of-sight (LoS) blockage scenarios. However, as larger RISs are integrated into ISAC systems, mutual coupling (MC) effects between RIS elements become more pronounced, leading to a substantial degradation in performance, especially for localization applications. In this paper, we first conduct a misspecified and standard Cram\'er-Rao bound analysis to quantify the impact of MC on localization performance, demonstrating severe degradations in accuracy, especially when MC is ignored. Building on this, we propose a novel joint user equipment localization and RIS MC parameter estimation (JLMC) method in near-field wireless systems. Our two-stage MC-aware approach outperforms classical methods that neglect MC, significantly improving localization accuracy and overall system performance. Simulation results validate the effectiveness and advantages of the proposed method in realistic scenarios.