Joint precoding and antenna selection in massive mimo systems
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFRJ |
Texto Completo: | http://hdl.handle.net/11422/11565 |
Resumo: | This thesis presents an overview of massive multiple-input multiple-output (MIMO) systems and proposes new algorithms to jointly precode and select the antennas. Massive MIMO is a new technology, which is candidate for comprising the fifth-generation (5G) of mobile cellular systems. This technology employs a huge amount of antennas at the base station and can reach high data rates under favorable, or asymptotically favorable, propagation conditions, while using simple linear processing. However, massive MIMO systems have some drawbacks, such as the high cost related to the base stations. A way to deal with this issue is to employ antenna selection algorithms at the base stations. These algorithms reduce the number of active antennas, decreasing the deployment and maintenance costs related to the base stations. Moreover, this thesis also describes a class of nonlinear precoders that are rarely addressed in the literature; these techniques are able to generate precoded sparse signals in order to achieve joint precoding and antenna selection. This thesis proposes two precoders belonging to this class, where the number of selected antennas is controlled by a design parameter. Simulation results show that the proposed precoders reach a lower bit-error rate than the classical antenna selection algorithms. Furthermore, simulation results show that the proposed precoders present a linear relation between the aforementioned design parameter that controls the signals’ sparsity and the number of selected antennas. Such relation is invariant to the number of base station’s antennas and the number of terminals served by this base station. |
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Joint precoding and antenna selection in massive mimo systemsAntenasProcessamento de sinaisAlgoritmosMatrizes esparsasCNPQ::ENGENHARIAS::ENGENHARIA ELETRICA::TELECOMUNICACOES::TEORIA ELETROMAGNETICA, MICROONDAS, PROPAGACAO DE ONDAS, ANTENASThis thesis presents an overview of massive multiple-input multiple-output (MIMO) systems and proposes new algorithms to jointly precode and select the antennas. Massive MIMO is a new technology, which is candidate for comprising the fifth-generation (5G) of mobile cellular systems. This technology employs a huge amount of antennas at the base station and can reach high data rates under favorable, or asymptotically favorable, propagation conditions, while using simple linear processing. However, massive MIMO systems have some drawbacks, such as the high cost related to the base stations. A way to deal with this issue is to employ antenna selection algorithms at the base stations. These algorithms reduce the number of active antennas, decreasing the deployment and maintenance costs related to the base stations. Moreover, this thesis also describes a class of nonlinear precoders that are rarely addressed in the literature; these techniques are able to generate precoded sparse signals in order to achieve joint precoding and antenna selection. This thesis proposes two precoders belonging to this class, where the number of selected antennas is controlled by a design parameter. Simulation results show that the proposed precoders reach a lower bit-error rate than the classical antenna selection algorithms. Furthermore, simulation results show that the proposed precoders present a linear relation between the aforementioned design parameter that controls the signals’ sparsity and the number of selected antennas. Such relation is invariant to the number of base station’s antennas and the number of terminals served by this base station.Esta dissertação apresenta uma visão geral sobre MIMO (do termo em inglês, multiple-input multiple-output) massivo e propõe novos algoritmos que permitem a pré-codificacão de sinais e a seleção de antenas de forma simultânea. MIMO massivo é uma nova tecnologia candidata para compor a quinta geração (5G) dos sistemas celulares. Essa tecnologia utiliza uma quantidade muito grande de antenas na estação-base e, sob condições de propagação favorável ou assintoticamente favorável, pode alcançar taxas de transmissão elevadas, ainda que utilizando um simples processamento linear. Entretanto, os sistemas MIMO massivo apresentam algumas desvantagens, como por exemplo, o alto custo de implementação das estações-bases. Uma maneira de lidar com esse problema é utilizar algoritmos de seleção de antenas na estação-base. Com esses algoritmos é possível reduzir o número de antenas ativas e consequentemente reduzir o custo nas estações-bases. Essa dissertação também apresenta uma classe pouco estudada de pré-codificadores não-lineares que buscam sinais pré-codificados esparsos para realizar a seleção de antenas conjuntamente com a pré-codificação. Além disso, este trabalho propõem dois novos pré-codificadores pertencentes a essa classe, para os quais o número de antenas selecionadas é controlado por um parâmetro de projeto. Resultados de simulações mostram que os pré-codificadores propostos conseguem uma BER (do termo em inglês, bit-error rate) menor que os algoritmos clássicos usados para selecionar antenas. Além disso, resultados de simulações mostram que os pré-codificadores propostos apresentam uma relação linear com o parâmetro de projeto que controla a quantidade de antenas selecionadas; tal relação independe do número de antenas na estação-base e do número de terminais servidos por essa estação.Universidade Federal do Rio de JaneiroBrasilInstituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de EngenhariaPrograma de Pós-Graduação em Engenharia ElétricaUFRJMartins, Wallace Alveshttp://lattes.cnpq.br/5359708806116816Campos, Marcello Luiz Rodrigues deSampaio Neto, RaimundoChaves, Rafael da Silva2020-03-20T21:42:18Z2023-12-21T03:00:47Z2018-03info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesishttp://hdl.handle.net/11422/11565enginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRJinstname:Universidade Federal do Rio de Janeiro (UFRJ)instacron:UFRJ2023-12-21T03:00:47Zoai:pantheon.ufrj.br:11422/11565Repositório InstitucionalPUBhttp://www.pantheon.ufrj.br/oai/requestpantheon@sibi.ufrj.bropendoar:2023-12-21T03:00:47Repositório Institucional da UFRJ - Universidade Federal do Rio de Janeiro (UFRJ)false |
dc.title.none.fl_str_mv |
Joint precoding and antenna selection in massive mimo systems |
title |
Joint precoding and antenna selection in massive mimo systems |
spellingShingle |
Joint precoding and antenna selection in massive mimo systems Chaves, Rafael da Silva Antenas Processamento de sinais Algoritmos Matrizes esparsas CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA::TELECOMUNICACOES::TEORIA ELETROMAGNETICA, MICROONDAS, PROPAGACAO DE ONDAS, ANTENAS |
title_short |
Joint precoding and antenna selection in massive mimo systems |
title_full |
Joint precoding and antenna selection in massive mimo systems |
title_fullStr |
Joint precoding and antenna selection in massive mimo systems |
title_full_unstemmed |
Joint precoding and antenna selection in massive mimo systems |
title_sort |
Joint precoding and antenna selection in massive mimo systems |
author |
Chaves, Rafael da Silva |
author_facet |
Chaves, Rafael da Silva |
author_role |
author |
dc.contributor.none.fl_str_mv |
Martins, Wallace Alves http://lattes.cnpq.br/5359708806116816 Campos, Marcello Luiz Rodrigues de Sampaio Neto, Raimundo |
dc.contributor.author.fl_str_mv |
Chaves, Rafael da Silva |
dc.subject.por.fl_str_mv |
Antenas Processamento de sinais Algoritmos Matrizes esparsas CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA::TELECOMUNICACOES::TEORIA ELETROMAGNETICA, MICROONDAS, PROPAGACAO DE ONDAS, ANTENAS |
topic |
Antenas Processamento de sinais Algoritmos Matrizes esparsas CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA::TELECOMUNICACOES::TEORIA ELETROMAGNETICA, MICROONDAS, PROPAGACAO DE ONDAS, ANTENAS |
description |
This thesis presents an overview of massive multiple-input multiple-output (MIMO) systems and proposes new algorithms to jointly precode and select the antennas. Massive MIMO is a new technology, which is candidate for comprising the fifth-generation (5G) of mobile cellular systems. This technology employs a huge amount of antennas at the base station and can reach high data rates under favorable, or asymptotically favorable, propagation conditions, while using simple linear processing. However, massive MIMO systems have some drawbacks, such as the high cost related to the base stations. A way to deal with this issue is to employ antenna selection algorithms at the base stations. These algorithms reduce the number of active antennas, decreasing the deployment and maintenance costs related to the base stations. Moreover, this thesis also describes a class of nonlinear precoders that are rarely addressed in the literature; these techniques are able to generate precoded sparse signals in order to achieve joint precoding and antenna selection. This thesis proposes two precoders belonging to this class, where the number of selected antennas is controlled by a design parameter. Simulation results show that the proposed precoders reach a lower bit-error rate than the classical antenna selection algorithms. Furthermore, simulation results show that the proposed precoders present a linear relation between the aforementioned design parameter that controls the signals’ sparsity and the number of selected antennas. Such relation is invariant to the number of base station’s antennas and the number of terminals served by this base station. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-03 2020-03-20T21:42:18Z 2023-12-21T03:00:47Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/11422/11565 |
url |
http://hdl.handle.net/11422/11565 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Universidade Federal do Rio de Janeiro Brasil Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia Programa de Pós-Graduação em Engenharia Elétrica UFRJ |
publisher.none.fl_str_mv |
Universidade Federal do Rio de Janeiro Brasil Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia Programa de Pós-Graduação em Engenharia Elétrica UFRJ |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da UFRJ instname:Universidade Federal do Rio de Janeiro (UFRJ) instacron:UFRJ |
instname_str |
Universidade Federal do Rio de Janeiro (UFRJ) |
instacron_str |
UFRJ |
institution |
UFRJ |
reponame_str |
Repositório Institucional da UFRJ |
collection |
Repositório Institucional da UFRJ |
repository.name.fl_str_mv |
Repositório Institucional da UFRJ - Universidade Federal do Rio de Janeiro (UFRJ) |
repository.mail.fl_str_mv |
pantheon@sibi.ufrj.br |
_version_ |
1815456005314576384 |