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Utilizing Multi-Dimensional MmWave MIMO Channel Features for Location Verification

In this paper, we address the problem of authenticating transmitters in millimeter-wave (mmWave) multiple-input multiple-output (MIMO) communication systems, and propose a location verification scheme based on multi-dimensional mmWave MIMO channel features. In particular, we first examine the mmWave...

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Detalles Bibliográficos
Autores principales: Zhang, Pinchang, Liu, Yangyang, He, Ji
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9739151/
https://www.ncbi.nlm.nih.gov/pubmed/36501903
http://dx.doi.org/10.3390/s22239202
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author Zhang, Pinchang
Liu, Yangyang
He, Ji
author_facet Zhang, Pinchang
Liu, Yangyang
He, Ji
author_sort Zhang, Pinchang
collection PubMed
description In this paper, we address the problem of authenticating transmitters in millimeter-wave (mmWave) multiple-input multiple-output (MIMO) communication systems, and propose a location verification scheme based on multi-dimensional mmWave MIMO channel features. In particular, we first examine the mmWave MIMO channel features in terms of azimuth angle of arrival (AAoA), elevation angle of arrival (EAoA), and path gain, and then extract these fine-grained channel features through the maximum-likelihood (ML) estimation method. Based on the extracted feature parameters, authentication validation is cast in the framework of hypothesis testing theory. We also derive the analytical expressions for the typical false alarm and detection rates by using the likelihood ratio test and thus the statistical performance is analytically established. Finally, extensive numerical results are provided to demonstrate the performance of the proposed authentication scheme.
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spelling pubmed-97391512022-12-11 Utilizing Multi-Dimensional MmWave MIMO Channel Features for Location Verification Zhang, Pinchang Liu, Yangyang He, Ji Sensors (Basel) Article In this paper, we address the problem of authenticating transmitters in millimeter-wave (mmWave) multiple-input multiple-output (MIMO) communication systems, and propose a location verification scheme based on multi-dimensional mmWave MIMO channel features. In particular, we first examine the mmWave MIMO channel features in terms of azimuth angle of arrival (AAoA), elevation angle of arrival (EAoA), and path gain, and then extract these fine-grained channel features through the maximum-likelihood (ML) estimation method. Based on the extracted feature parameters, authentication validation is cast in the framework of hypothesis testing theory. We also derive the analytical expressions for the typical false alarm and detection rates by using the likelihood ratio test and thus the statistical performance is analytically established. Finally, extensive numerical results are provided to demonstrate the performance of the proposed authentication scheme. MDPI 2022-11-26 /pmc/articles/PMC9739151/ /pubmed/36501903 http://dx.doi.org/10.3390/s22239202 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhang, Pinchang
Liu, Yangyang
He, Ji
Utilizing Multi-Dimensional MmWave MIMO Channel Features for Location Verification
title Utilizing Multi-Dimensional MmWave MIMO Channel Features for Location Verification
title_full Utilizing Multi-Dimensional MmWave MIMO Channel Features for Location Verification
title_fullStr Utilizing Multi-Dimensional MmWave MIMO Channel Features for Location Verification
title_full_unstemmed Utilizing Multi-Dimensional MmWave MIMO Channel Features for Location Verification
title_short Utilizing Multi-Dimensional MmWave MIMO Channel Features for Location Verification
title_sort utilizing multi-dimensional mmwave mimo channel features for location verification
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9739151/
https://www.ncbi.nlm.nih.gov/pubmed/36501903
http://dx.doi.org/10.3390/s22239202
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