RIS-Aided Localization Under Pixel Failures

Reconfigurable intelligent surfaces (RISs) hold great potential as one of the key technological enablers for beyond-5G wireless networks, improving localization and communication performance under line-of-sight (LoS) blockage conditions. However, hardware imperfections might cause RIS elements to become faulty, a problem referred to as pixel failures, which can constitute a major showstopper especially for localization. In this paper, we investigate the problem of RIS-aided localization of a user equipment (UE) under LoS blockage in the presence of RIS pixel failures, considering the challenging single-input single-output (SISO) scenario. We first explore the impact of such failures on accuracy through misspecified Cramér-Rao bound (MCRB) analysis, which reveals severe performance loss with even a small percentage of pixel failures. To remedy this issue, we develop two strategies for joint localization and failure diagnosis (JLFD) to detect failing pixels while simultaneously locating the UE with high accuracy. The first strategy relies on $\ell _{1}$ -regularization through exploitation of failure sparsity. The second strategy detects the failures one-by-one by solving a multiple hypothesis testing problem at each iteration, successively enhancing localization and diagnosis accuracy. Simulation results show significant performance improvements of the proposed JLFD algorithms over the conventional failure-agnostic benchmark, enabling successful recovery of failure-induced performance degradations.

I. Introduction

Reconfigurable intelligent surfaces (RISs) are envisaged as a key enabling technology towards 6G to reduce the vulnerability of mmWave and sub-THz systems to signal blockages, providing improved communication rate and coverage [1], [2], [3]. Through their dynamic ability to engineer the propagation environment, reconfigurable intelligent surfaces (RISs) can be optimized in terms of various performance metrics, such as energy efficiency [4], [5] and sum-rate [6], [7]. While a great deal of papers has been devoted to RIS for communication, especially for overcoming line-of-sight (LoS) blockages [1], [8], RISs enjoy several properties that make them attractive for localization as well [9], [10]. The large aperture of RISs enables high resolution in angle-of-arrival (AoA) and angle-of-departure (AoD) estimation, while their functioning over large bandwidths supports high delay resolution (in addition to high data rates) [11]. When user equipments (UEs) are close to the RIS, wavefront curvature (also known as near-field (NF)) allows direct relative localization, even when the LoS between the UE and base station (BS) is blocked [12], [13], [14]. When the RIS has a known location and orientation, this relative location can be transformed into global coordinates, effectively rendering the RIS into an additional analog BS [11].