Bi-Objective Power Optimization of Radio Stripe Uplink Communications
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10316/100532 https://doi.org/10.3390/electronics11060876 |
Resumo: | The radio stripe (RS) system is a practical implementation of cell-free mMIMO, in which a set of multi-antenna access points (APs) serves at the same time-frequency resources the user equipment (UE) in the network. The APs are sequentially connected in a stripe, sharing the same fronthaul link to the central processing unit. This work considers an uplink power optimization problem that aims to enhance the network spectral efficiency (SE) by considering two metrics—the max–min fairness and the max–sum rate. We employ a meta-heuristic based on the differential evolution algorithm to solve the bi-objective optimization problem. The SE performances of the full power along with the single-objective and multiple-objective scenarios are analyzed and compared for the optimal sequential linear processing detection scheme. The bi-objective approach is able to unveil the trade-offs to identify solution balancing the SE distribution resulting from the optimization of the max–min fairness and the max–sum rate objective functions. |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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7160 |
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Bi-Objective Power Optimization of Radio Stripe Uplink CommunicationsCell-free (CF)Differential evolution (DE)Massive MIMO (mMIMO)Max–min; Max–sumMulti-objective (MO)Power optimizationRadio stripe (RS)The radio stripe (RS) system is a practical implementation of cell-free mMIMO, in which a set of multi-antenna access points (APs) serves at the same time-frequency resources the user equipment (UE) in the network. The APs are sequentially connected in a stripe, sharing the same fronthaul link to the central processing unit. This work considers an uplink power optimization problem that aims to enhance the network spectral efficiency (SE) by considering two metrics—the max–min fairness and the max–sum rate. We employ a meta-heuristic based on the differential evolution algorithm to solve the bi-objective optimization problem. The SE performances of the full power along with the single-objective and multiple-objective scenarios are analyzed and compared for the optimal sequential linear processing detection scheme. The bi-objective approach is able to unveil the trade-offs to identify solution balancing the SE distribution resulting from the optimization of the max–min fairness and the max–sum rate objective functions.2022info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10316/100532http://hdl.handle.net/10316/100532https://doi.org/10.3390/electronics11060876eng2079-9292Conceição, FilipeGomes, MarcoSilva, VitorDinis, RuiAntunes, Carlos Henggelerinfo: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:RCAAP2022-06-29T20:37:35Zoai:estudogeral.uc.pt:10316/100532Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T21:17:54.096071Repositório 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 |
Bi-Objective Power Optimization of Radio Stripe Uplink Communications |
title |
Bi-Objective Power Optimization of Radio Stripe Uplink Communications |
spellingShingle |
Bi-Objective Power Optimization of Radio Stripe Uplink Communications Conceição, Filipe Cell-free (CF) Differential evolution (DE) Massive MIMO (mMIMO) Max–min; Max–sum Multi-objective (MO) Power optimization Radio stripe (RS) |
title_short |
Bi-Objective Power Optimization of Radio Stripe Uplink Communications |
title_full |
Bi-Objective Power Optimization of Radio Stripe Uplink Communications |
title_fullStr |
Bi-Objective Power Optimization of Radio Stripe Uplink Communications |
title_full_unstemmed |
Bi-Objective Power Optimization of Radio Stripe Uplink Communications |
title_sort |
Bi-Objective Power Optimization of Radio Stripe Uplink Communications |
author |
Conceição, Filipe |
author_facet |
Conceição, Filipe Gomes, Marco Silva, Vitor Dinis, Rui Antunes, Carlos Henggeler |
author_role |
author |
author2 |
Gomes, Marco Silva, Vitor Dinis, Rui Antunes, Carlos Henggeler |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Conceição, Filipe Gomes, Marco Silva, Vitor Dinis, Rui Antunes, Carlos Henggeler |
dc.subject.por.fl_str_mv |
Cell-free (CF) Differential evolution (DE) Massive MIMO (mMIMO) Max–min; Max–sum Multi-objective (MO) Power optimization Radio stripe (RS) |
topic |
Cell-free (CF) Differential evolution (DE) Massive MIMO (mMIMO) Max–min; Max–sum Multi-objective (MO) Power optimization Radio stripe (RS) |
description |
The radio stripe (RS) system is a practical implementation of cell-free mMIMO, in which a set of multi-antenna access points (APs) serves at the same time-frequency resources the user equipment (UE) in the network. The APs are sequentially connected in a stripe, sharing the same fronthaul link to the central processing unit. This work considers an uplink power optimization problem that aims to enhance the network spectral efficiency (SE) by considering two metrics—the max–min fairness and the max–sum rate. We employ a meta-heuristic based on the differential evolution algorithm to solve the bi-objective optimization problem. The SE performances of the full power along with the single-objective and multiple-objective scenarios are analyzed and compared for the optimal sequential linear processing detection scheme. The bi-objective approach is able to unveil the trade-offs to identify solution balancing the SE distribution resulting from the optimization of the max–min fairness and the max–sum rate objective functions. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022 |
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/10316/100532 http://hdl.handle.net/10316/100532 https://doi.org/10.3390/electronics11060876 |
url |
http://hdl.handle.net/10316/100532 https://doi.org/10.3390/electronics11060876 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2079-9292 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799134074847100928 |