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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Detalles Bibliográficos
Autores: Garg, Vaibhav, Giménez Febrer, Pedro Juan, Pagès Zamora, Alba Maria|||0000-0002-7087-7014, Santamaria Caballero, Ignacio
Tipo de recurso: artículo
Fecha de publicación:2021
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/344839
Acceso en línea:https://hdl.handle.net/2117/344839
https://dx.doi.org/10.1016/j.sigpro.2021.107993
Access Level:acceso abierto
Palabra clave: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
Descripción
Sumario: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.