DOA estimation via shift-invariant matrix completion

This paper presents a method to estimate the direction of arrival (DOA) of multiple sources received by a uniform linear array (ULA) with a reduced number of radio-frequency (RF) chains. The receiving array relies on antenna switching so that at every time instant only the signals received by a rand...

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Autores: Garg, Vaibhav, Giménez Febrer, Pedro Juan, Pagès Zamora, Alba Maria|||0000-0002-7087-7014, Santamaria Caballero, Ignacio
Tipo de documento: artigo
Data de publicação:2021
País:España
Recursos:Universitat Politècnica de Catalunya (UPC)
Repositório:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglês
OAI Identifier:oai:upcommons.upc.edu:2117/344839
Acesso em linha:https://hdl.handle.net/2117/344839
https://dx.doi.org/10.1016/j.sigpro.2021.107993
Access Level:Acceso aberto
Palavra-chave:MIMO systems
Direction of arrival (DOA)
Uniform linear array
Massive MIMO
Matrix Completion Shift invariance
Sistemes MIMO
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació
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oai_identifier_str oai:upcommons.upc.edu:2117/344839
network_acronym_str ES
network_name_str España
repository_id_str
spelling DOA estimation via shift-invariant matrix completionGarg, VaibhavGiménez Febrer, Pedro JuanPagès Zamora, Alba Maria|||0000-0002-7087-7014Santamaria Caballero, IgnacioMIMO systemsDirection of arrival (DOA)Uniform linear arrayMassive MIMOMatrix Completion Shift invarianceSistemes MIMOÀrees temàtiques de la UPC::Enginyeria de la telecomunicacióThis paper presents a method to estimate the direction of arrival (DOA) of multiple sources received by a uniform linear array (ULA) with a reduced number of radio-frequency (RF) chains. The receiving array relies on antenna switching so that at every time instant only the signals received by a randomly selected subset of antennas are downconverted to baseband and sampled. Low-rank matrix completion (MC) techniques are then used to reconstruct the missing entries of the signal data matrix to keep the angular resolution of the original large-scale array. The proposed MC algorithm exploits not only the low- rank structure of the signal subspace, but also the shift-invariance property of ULAs, which results in a better estimation of the signal subspace. Further, the effect of MC on DOA estimation is discussed under the perturbation theory framework. The simulation results suggest that the proposed method provides accurate DOA estimates even in the small-sample regime with a significant reduction in the number of RF chains required for a given spatial resolution.This work was supported by the Ministerio de Ciencia e Innovación (MICINN) of Spain, and AEI/FEDER funds of the E.U., under grants TEC2016-75067-C4-4-R /2-R (CARMEN), PID2019-104958RB-C43/C41 (ADELE) and BES-2017-080542.Peer Reviewed20212021-06-0120212021-04-29journal articlehttp://purl.org/coar/resource_type/c_6501AMhttp://purl.org/coar/version/c_ab4af688f83e57aainfo:eu-repo/semantics/articleapplication/pdfapplication/pdfhttps://hdl.handle.net/2117/344839https://dx.doi.org/10.1016/j.sigpro.2021.107993reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/3448392026-05-27T15:37:01Z
dc.title.none.fl_str_mv DOA estimation via shift-invariant matrix completion
title DOA estimation via shift-invariant matrix completion
spellingShingle DOA estimation via shift-invariant matrix completion
Garg, Vaibhav
MIMO systems
Direction of arrival (DOA)
Uniform linear array
Massive MIMO
Matrix Completion Shift invariance
Sistemes MIMO
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació
title_short DOA estimation via shift-invariant matrix completion
title_full DOA estimation via shift-invariant matrix completion
title_fullStr DOA estimation via shift-invariant matrix completion
title_full_unstemmed DOA estimation via shift-invariant matrix completion
title_sort DOA estimation via shift-invariant matrix completion
dc.creator.none.fl_str_mv Garg, Vaibhav
Giménez Febrer, Pedro Juan
Pagès Zamora, Alba Maria|||0000-0002-7087-7014
Santamaria Caballero, Ignacio
author Garg, Vaibhav
author_facet Garg, Vaibhav
Giménez Febrer, Pedro Juan
Pagès Zamora, Alba Maria|||0000-0002-7087-7014
Santamaria Caballero, Ignacio
author_role author
author2 Giménez Febrer, Pedro Juan
Pagès Zamora, Alba Maria|||0000-0002-7087-7014
Santamaria Caballero, Ignacio
author2_role author
author
author
dc.subject.none.fl_str_mv MIMO systems
Direction of arrival (DOA)
Uniform linear array
Massive MIMO
Matrix Completion Shift invariance
Sistemes MIMO
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació
topic MIMO systems
Direction of arrival (DOA)
Uniform linear array
Massive MIMO
Matrix Completion Shift invariance
Sistemes MIMO
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació
description This paper presents a method to estimate the direction of arrival (DOA) of multiple sources received by a uniform linear array (ULA) with a reduced number of radio-frequency (RF) chains. The receiving array relies on antenna switching so that at every time instant only the signals received by a randomly selected subset of antennas are downconverted to baseband and sampled. Low-rank matrix completion (MC) techniques are then used to reconstruct the missing entries of the signal data matrix to keep the angular resolution of the original large-scale array. The proposed MC algorithm exploits not only the low- rank structure of the signal subspace, but also the shift-invariance property of ULAs, which results in a better estimation of the signal subspace. Further, the effect of MC on DOA estimation is discussed under the perturbation theory framework. The simulation results suggest that the proposed method provides accurate DOA estimates even in the small-sample regime with a significant reduction in the number of RF chains required for a given spatial resolution.
publishDate 2021
dc.date.none.fl_str_mv 2021
2021-06-01
2021
2021-04-29
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
AM
http://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/344839
https://dx.doi.org/10.1016/j.sigpro.2021.107993
url https://hdl.handle.net/2117/344839
https://dx.doi.org/10.1016/j.sigpro.2021.107993
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,198674

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