RIS-aided Localization under Pixel Failures

Fuente: arXiv
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Autores principales: Ozturk, Cuneyd, Keskin, Musa Furkan, Sciancalepore, Vincenzo, Wymeersch, Henk, Gezici, Sinan
Formato: Preprint
Publicado: 2023
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author Ozturk, Cuneyd
Keskin, Musa Furkan
Sciancalepore, Vincenzo
Wymeersch, Henk
Gezici, Sinan
author_facet Ozturk, Cuneyd
Keskin, Musa Furkan
Sciancalepore, Vincenzo
Wymeersch, Henk
Gezici, Sinan
contents 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 Cramer-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 l_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.
format Preprint
id arxiv_https___arxiv_org_abs_2302_04436
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle RIS-aided Localization under Pixel Failures
Ozturk, Cuneyd
Keskin, Musa Furkan
Sciancalepore, Vincenzo
Wymeersch, Henk
Gezici, Sinan
Signal Processing
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 Cramer-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 l_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.
title RIS-aided Localization under Pixel Failures
topic Signal Processing
url https://arxiv.org/abs/2302.04436