Rank-One Tensor Modeling Approach to Joint Channel and Symbol Estimation in Two-Hop MIMO Relaying Systems
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , |
Tipo de documento: | Artigo de conferência |
Idioma: | por |
Título da fonte: | Repositório Institucional da Universidade Federal do Ceará (UFC) |
Texto Completo: | http://www.repositorio.ufc.br/handle/riufc/60023 |
Resumo: | This paper proposes two semi-blind receives for joint channel and symbol estimation in MIMO relay-based communication systems. These receivers are developed for a two-hop system, assuming a tensor coding at the source and relay nodes. The central idea of the proposed approach is on the rank-one tensor modeling of the received signal, which allows the use of efficient estimation algorithms. The first receiver utilizes an iterative solution based on the alternating least squares (ALS) algorithm, while the second provides closed-form estimations of the channel and symbol matrices from a truncated higher order singular value decomposition (T-HOSVD). The proposed approach has a lower complexity compared to the receiver developed in a previous work, while providing remarkable performance. |
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Repositório Institucional da Universidade Federal do Ceará (UFC) |
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Rank-One Tensor Modeling Approach to Joint Channel and Symbol Estimation in Two-Hop MIMO Relaying SystemsMIMO systemsCooperative communicationsTensor decompositionsSemi-blind receiverThis paper proposes two semi-blind receives for joint channel and symbol estimation in MIMO relay-based communication systems. These receivers are developed for a two-hop system, assuming a tensor coding at the source and relay nodes. The central idea of the proposed approach is on the rank-one tensor modeling of the received signal, which allows the use of efficient estimation algorithms. The first receiver utilizes an iterative solution based on the alternating least squares (ALS) algorithm, while the second provides closed-form estimations of the channel and symbol matrices from a truncated higher order singular value decomposition (T-HOSVD). The proposed approach has a lower complexity compared to the receiver developed in a previous work, while providing remarkable performance.This paper proposes two semi-blind receives for joint channel and symbol estimation in MIMO relay-based communication systems. These receivers are developed for a two-hop system, assuming a tensor coding at the source and relay nodes. The central idea of the proposed approach is on the rank-one tensor modeling of the received signal, which allows the use of efficient estimation algorithms. The first receiver utilizes an iterative solution based on the alternating least squares (ALS) algorithm, while the second provides closed-form estimations of the channel and symbol matrices from a truncated higher order singular value decomposition (T-HOSVD). The proposed approach has a lower complexity compared to the receiver developed in a previous work, while providing remarkable performance.https://www.sbrt.org.br/sbrt20172021-08-18T18:26:57Z2021-08-18T18:26:57Z2017info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjectapplication/pdfSOKAL, Bruno; ALMEIDA, André Lima Férrer de; HAARDT, Martin. Rank-one tensor modeling approach to joint channel and symbol estimation in two-hop MIMO relaying systems. In: SIMPÓSIO BRASILEIRO DE TELECOMUNICAÇÕES E PROCESSAMENTO DE SINAIS – SbrT, XXXV., 3 a 6 set. 2017. São Pedro-SP. Anais[…], São Pedro-SP, 2017.p.37-41.http://www.repositorio.ufc.br/handle/riufc/60023Sokal, BrunoAlmeida, André Lima Férrer deHaardt, Martin Haardtporreponame:Repositório Institucional da Universidade Federal do Ceará (UFC)instname:Universidade Federal do Ceará (UFC)instacron:UFCinfo:eu-repo/semantics/openAccess2021-08-18T18:26:57Zoai:repositorio.ufc.br:riufc/60023Repositório InstitucionalPUBhttp://www.repositorio.ufc.br/ri-oai/requestbu@ufc.br || repositorio@ufc.bropendoar:2024-09-11T18:42:24.961977Repositório Institucional da Universidade Federal do Ceará (UFC) - Universidade Federal do Ceará (UFC)false |
dc.title.none.fl_str_mv |
Rank-One Tensor Modeling Approach to Joint Channel and Symbol Estimation in Two-Hop MIMO Relaying Systems |
title |
Rank-One Tensor Modeling Approach to Joint Channel and Symbol Estimation in Two-Hop MIMO Relaying Systems |
spellingShingle |
Rank-One Tensor Modeling Approach to Joint Channel and Symbol Estimation in Two-Hop MIMO Relaying Systems Sokal, Bruno MIMO systems Cooperative communications Tensor decompositions Semi-blind receiver |
title_short |
Rank-One Tensor Modeling Approach to Joint Channel and Symbol Estimation in Two-Hop MIMO Relaying Systems |
title_full |
Rank-One Tensor Modeling Approach to Joint Channel and Symbol Estimation in Two-Hop MIMO Relaying Systems |
title_fullStr |
Rank-One Tensor Modeling Approach to Joint Channel and Symbol Estimation in Two-Hop MIMO Relaying Systems |
title_full_unstemmed |
Rank-One Tensor Modeling Approach to Joint Channel and Symbol Estimation in Two-Hop MIMO Relaying Systems |
title_sort |
Rank-One Tensor Modeling Approach to Joint Channel and Symbol Estimation in Two-Hop MIMO Relaying Systems |
author |
Sokal, Bruno |
author_facet |
Sokal, Bruno Almeida, André Lima Férrer de Haardt, Martin Haardt |
author_role |
author |
author2 |
Almeida, André Lima Férrer de Haardt, Martin Haardt |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Sokal, Bruno Almeida, André Lima Férrer de Haardt, Martin Haardt |
dc.subject.por.fl_str_mv |
MIMO systems Cooperative communications Tensor decompositions Semi-blind receiver |
topic |
MIMO systems Cooperative communications Tensor decompositions Semi-blind receiver |
description |
This paper proposes two semi-blind receives for joint channel and symbol estimation in MIMO relay-based communication systems. These receivers are developed for a two-hop system, assuming a tensor coding at the source and relay nodes. The central idea of the proposed approach is on the rank-one tensor modeling of the received signal, which allows the use of efficient estimation algorithms. The first receiver utilizes an iterative solution based on the alternating least squares (ALS) algorithm, while the second provides closed-form estimations of the channel and symbol matrices from a truncated higher order singular value decomposition (T-HOSVD). The proposed approach has a lower complexity compared to the receiver developed in a previous work, while providing remarkable performance. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017 2021-08-18T18:26:57Z 2021-08-18T18:26:57Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
SOKAL, Bruno; ALMEIDA, André Lima Férrer de; HAARDT, Martin. Rank-one tensor modeling approach to joint channel and symbol estimation in two-hop MIMO relaying systems. In: SIMPÓSIO BRASILEIRO DE TELECOMUNICAÇÕES E PROCESSAMENTO DE SINAIS – SbrT, XXXV., 3 a 6 set. 2017. São Pedro-SP. Anais[…], São Pedro-SP, 2017.p.37-41. http://www.repositorio.ufc.br/handle/riufc/60023 |
identifier_str_mv |
SOKAL, Bruno; ALMEIDA, André Lima Férrer de; HAARDT, Martin. Rank-one tensor modeling approach to joint channel and symbol estimation in two-hop MIMO relaying systems. In: SIMPÓSIO BRASILEIRO DE TELECOMUNICAÇÕES E PROCESSAMENTO DE SINAIS – SbrT, XXXV., 3 a 6 set. 2017. São Pedro-SP. Anais[…], São Pedro-SP, 2017.p.37-41. |
url |
http://www.repositorio.ufc.br/handle/riufc/60023 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
https://www.sbrt.org.br/sbrt2017 |
publisher.none.fl_str_mv |
https://www.sbrt.org.br/sbrt2017 |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da Universidade Federal do Ceará (UFC) instname:Universidade Federal do Ceará (UFC) instacron:UFC |
instname_str |
Universidade Federal do Ceará (UFC) |
instacron_str |
UFC |
institution |
UFC |
reponame_str |
Repositório Institucional da Universidade Federal do Ceará (UFC) |
collection |
Repositório Institucional da Universidade Federal do Ceará (UFC) |
repository.name.fl_str_mv |
Repositório Institucional da Universidade Federal do Ceará (UFC) - Universidade Federal do Ceará (UFC) |
repository.mail.fl_str_mv |
bu@ufc.br || repositorio@ufc.br |
_version_ |
1813028914419728384 |