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dc.contributor.authorGarg, Vaibhav 
dc.contributor.authorGiménez Febrer, Pedro Juan
dc.contributor.authorPagès Zamora, Alba
dc.contributor.authorSantamaría Caballero, Luis Ignacio 
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2021-02-09T15:26:19Z
dc.date.available2023-06-30T00:19:37Z
dc.date.issued2021-06
dc.identifier.issn0165-1684
dc.identifier.issn1872-7557
dc.identifier.otherTEC2016-75067-C4-4-Res_ES
dc.identifier.otherTEC2016-75067-C4-2-Res_ES
dc.identifier.otherPID2019-104958RB-C43es_ES
dc.identifier.otherPID2019-104958RB-C41es_ES
dc.identifier.urihttp://hdl.handle.net/10902/20676
dc.description.abstractThis 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.es_ES
dc.description.sponsorshipThis 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.es_ES
dc.format.extent21 p.es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.rights© 2021. This manuscript version is made available under the CC-BY-NC-ND 4.0 licensees_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.sourceSignal Processing, 2021, 183, 107993es_ES
dc.subject.otherDirection of arrival (DOA)es_ES
dc.subject.otherUniform linear arrayes_ES
dc.subject.otherMassive MIMOes_ES
dc.subject.otherMatrix completiones_ES
dc.subject.otherShift invariancees_ES
dc.titleDOA estimation via shift-invariant matrix completiones_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherVersionhttps://doi.org/10.1016/j.sigpro.2021.107993es_ES
dc.rights.accessRightsopenAccesses_ES
dc.identifier.DOI10.1016/j.sigpro.2021.107993
dc.type.versionacceptedVersiones_ES


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© 2021. This manuscript version is made available under the CC-BY-NC-ND 4.0 licenseExcepto si se señala otra cosa, la licencia del ítem se describe como © 2021. This manuscript version is made available under the CC-BY-NC-ND 4.0 license