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A Joint Approach for Low-Complexity Channel Estimation in 5G Massive MIMO Systems

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A Joint Approach for Low-Complexity Channel Estimation in 5G Massive MIMO Systems

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dc.contributor.author Bangash, kifayatullah es_ES
dc.contributor.author Khan, Imran es_ES
dc.contributor.author Lloret, Jaime es_ES
dc.contributor.author León Fernández, Antonio es_ES
dc.date.accessioned 2020-05-07T05:56:54Z
dc.date.available 2020-05-07T05:56:54Z
dc.date.issued 2018-10 es_ES
dc.identifier.uri http://hdl.handle.net/10251/142677
dc.description.abstract [EN] Traditional Minimum Mean Square Error (MMSE) detection is widely used in wireless communications, however, it introduces matrix inversion and has a higher computational complexity. For massive Multiple-input Multiple-output (MIMO) systems, this detection complexity is very high due to its huge channel matrix dimension. Therefore, low-complexity detection technology has become a hot topic in the industry. Aiming at the problem of high computational complexity of the massive MIMO channel estimation, this paper presents a low-complexity algorithm for efficient channel estimation. The proposed algorithm is based on joint Singular Value Decomposition (SVD) and Iterative Least Square with Projection (SVD-ILSP) which overcomes the drawback of finite sample data assumption of the covariance matrix in the existing SVD-based semi-blind channel estimation scheme. Simulation results show that the proposed scheme can effectively reduce the deviation, improve the channel estimation accuracy, mitigate the impact of pilot contamination and obtain accurate CSI with low overhead and computational complexity. es_ES
dc.description.sponsorship This research was funded by Ministerio de Economia, Industria y Competitividad, Gobierno de Espana grant number BIA2017-87573-C2-2-P. es_ES
dc.language Inglés es_ES
dc.publisher MDPI AG es_ES
dc.relation.ispartof Electronics es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Massive MIMO es_ES
dc.subject Computational complexity es_ES
dc.subject Channel estimation es_ES
dc.subject Low-rank matrix completion es_ES
dc.subject Singular Value Decomposition es_ES
dc.subject.classification INGENIERIA TELEMATICA es_ES
dc.title A Joint Approach for Low-Complexity Channel Estimation in 5G Massive MIMO Systems es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/electronics7100218 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/BIA2017-87573-C2-2-P/ES/DESARROLLO Y APLICACION DE ENSAYOS NO DESTRUCTIVOS BASADOS EN ONDAS MECANICAS PARA LA EVALUACION Y MONITORIZACION DE REOLOGIA Y AUTOSANACION EN MATERIALES CEMENTANTES/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions es_ES
dc.description.bibliographicCitation Bangash, K.; Khan, I.; Lloret, J.; León Fernández, A. (2018). A Joint Approach for Low-Complexity Channel Estimation in 5G Massive MIMO Systems. Electronics. 7(10). https://doi.org/10.3390/electronics7100218 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3390/electronics7100218 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 7 es_ES
dc.description.issue 10 es_ES
dc.identifier.eissn 2079-9292 es_ES
dc.relation.pasarela S\377136 es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES
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