Fast matrix inversion based on Chebyshev acceleration for linear detection in massive MIMO systems

Detalhes bibliográficos
Autor(a) principal: Berra, Salah
Data de Publicação: 2022
Outros Autores: Dinis, Rui, Shahabuddin, Shahriar
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/144423
Resumo: MASSIVE5G (SAICT‐45‐2017‐02)
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spelling Fast matrix inversion based on Chebyshev acceleration for linear detection in massive MIMO systemsElectrical and Electronic EngineeringMASSIVE5G (SAICT‐45‐2017‐02)To circumvent the prohibitive complexity of linear minimum mean square error detection in a massive multiple-input multiple-output system, several iterative methods have been proposed. However, they can still be too complex and/or lead to non-negligible performance degradation. In this letter, a Chebyshev acceleration technique is proposed to overcome the limitations of iterative methods, accelerating the convergence rates and enhancing the performance. The Chebyshev acceleration method employs a new vector combination, which combines the spectral radius of the iteration matrix with the receiver signal, and also the optimal parameters of Chebyshev acceleration have also been defined. A detector based on iterative algorithms requires pre-processing and initialisation, which enhance the convergence, performance, and complexity. To influence the initialisation, the stair matrix has been proposed as the first start of iterative methods. The performance results show that the proposed technique outperforms state-of-the-art methods in terms of error rate performance, while significantly reducing the computational complexity.DEE2010-A1 TelecomunicaçõesDEE - Departamento de Engenharia Electrotécnica e de ComputadoresRUNBerra, SalahDinis, RuiShahabuddin, Shahriar2022-09-30T22:39:20Z2022-052022-05-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article3application/pdfhttp://hdl.handle.net/10362/144423eng0013-5194PURE: 46298922https://doi.org/10.1049/ell2.12486info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:24:05Zoai:run.unl.pt:10362/144423Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:51:32.968911Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Fast matrix inversion based on Chebyshev acceleration for linear detection in massive MIMO systems
title Fast matrix inversion based on Chebyshev acceleration for linear detection in massive MIMO systems
spellingShingle Fast matrix inversion based on Chebyshev acceleration for linear detection in massive MIMO systems
Berra, Salah
Electrical and Electronic Engineering
title_short Fast matrix inversion based on Chebyshev acceleration for linear detection in massive MIMO systems
title_full Fast matrix inversion based on Chebyshev acceleration for linear detection in massive MIMO systems
title_fullStr Fast matrix inversion based on Chebyshev acceleration for linear detection in massive MIMO systems
title_full_unstemmed Fast matrix inversion based on Chebyshev acceleration for linear detection in massive MIMO systems
title_sort Fast matrix inversion based on Chebyshev acceleration for linear detection in massive MIMO systems
author Berra, Salah
author_facet Berra, Salah
Dinis, Rui
Shahabuddin, Shahriar
author_role author
author2 Dinis, Rui
Shahabuddin, Shahriar
author2_role author
author
dc.contributor.none.fl_str_mv DEE2010-A1 Telecomunicações
DEE - Departamento de Engenharia Electrotécnica e de Computadores
RUN
dc.contributor.author.fl_str_mv Berra, Salah
Dinis, Rui
Shahabuddin, Shahriar
dc.subject.por.fl_str_mv Electrical and Electronic Engineering
topic Electrical and Electronic Engineering
description MASSIVE5G (SAICT‐45‐2017‐02)
publishDate 2022
dc.date.none.fl_str_mv 2022-09-30T22:39:20Z
2022-05
2022-05-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/144423
url http://hdl.handle.net/10362/144423
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0013-5194
PURE: 46298922
https://doi.org/10.1049/ell2.12486
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
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instacron:RCAAP
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instacron_str RCAAP
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