A framework for radio resource allocation and SDMA grouping in massive MIMO systems

Detalhes bibliográficos
Autor(a) principal: Mauricio, Weskley Vinicius Fernandes
Data de Publicação: 2021
Outros Autores: Araújo, Daniel Costa, Maciel, Tarcísio Ferreira, Lima, Francisco Rafael Marques
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da Universidade Federal do Ceará (UFC)
Texto Completo: http://www.repositorio.ufc.br/handle/riufc/67210
Resumo: This work proposes a framework for multiuser massive Multiple Input Multiple Output (MIMO) systems which is composed of three parts - clustering , grouping , and scheduling - and aims at maximizing the total system data rate considering Quality of Service (QoS) constraints. We firstly use a clustering algorithm to create clusters of spatially correlated Mobile Stations (MSs). Secondly, in the grouping part, we select a set of Space-Division Multiple Access (SDMA) groups from each cluster. These groups are used as candidate groups to receive Scheduling Unit (SU) in the scheduling part. In order to compose a group, we employ a metric that takes into account the trade-off between the spatial channel correlation and channel gain of MSs. In this context, it is proposed a suboptimal solution to avoid the high complexity required by the optimal solution. Thirdly and finally, we use the candidate SDMA groups from the grouping part to solve the data rate maximization problem considering QoS requirements. The scheduling part can be solved by our proposed optimal solution based on Branch and Bound (BB). However, since it has high computational complexity, we propose a suboptimal scheduling algorithm that presents a reduced complexity. In the simulation results, we evaluate the performance of both optimal and suboptimal solutions, as well as an adaptation of the Joint Satisfaction Maximization (JSM) scheduler to a massive MIMO scenario. Although the suboptimal solution presents a performance loss compared to the optimal one, it is more suitable for practical settings as it is able to obtain a good performance-complexity trade-off. Furthermore, we show that the choice of a suitable trade-off between the spatial channel correlation and channel gain improves the system performance. Finally, for a low number of available SDMA groups, the suboptimal solution presents near optimal outage and a throughput loss of only 10% in comparison to the high-complexity optimal solution while it outperforms the JSM solution in terms of outage and system throughput.
id UFC-7_613f1b92bc9d733f6bcfe50bce5ca291
oai_identifier_str oai:repositorio.ufc.br:riufc/67210
network_acronym_str UFC-7
network_name_str Repositório Institucional da Universidade Federal do Ceará (UFC)
repository_id_str
spelling A framework for radio resource allocation and SDMA grouping in massive MIMO systemsMassive MIMOChannel hardeningSDMA groupingRadio resource allocationQuality of serviceThis work proposes a framework for multiuser massive Multiple Input Multiple Output (MIMO) systems which is composed of three parts - clustering , grouping , and scheduling - and aims at maximizing the total system data rate considering Quality of Service (QoS) constraints. We firstly use a clustering algorithm to create clusters of spatially correlated Mobile Stations (MSs). Secondly, in the grouping part, we select a set of Space-Division Multiple Access (SDMA) groups from each cluster. These groups are used as candidate groups to receive Scheduling Unit (SU) in the scheduling part. In order to compose a group, we employ a metric that takes into account the trade-off between the spatial channel correlation and channel gain of MSs. In this context, it is proposed a suboptimal solution to avoid the high complexity required by the optimal solution. Thirdly and finally, we use the candidate SDMA groups from the grouping part to solve the data rate maximization problem considering QoS requirements. The scheduling part can be solved by our proposed optimal solution based on Branch and Bound (BB). However, since it has high computational complexity, we propose a suboptimal scheduling algorithm that presents a reduced complexity. In the simulation results, we evaluate the performance of both optimal and suboptimal solutions, as well as an adaptation of the Joint Satisfaction Maximization (JSM) scheduler to a massive MIMO scenario. Although the suboptimal solution presents a performance loss compared to the optimal one, it is more suitable for practical settings as it is able to obtain a good performance-complexity trade-off. Furthermore, we show that the choice of a suitable trade-off between the spatial channel correlation and channel gain improves the system performance. Finally, for a low number of available SDMA groups, the suboptimal solution presents near optimal outage and a throughput loss of only 10% in comparison to the high-complexity optimal solution while it outperforms the JSM solution in terms of outage and system throughput.IEEE Acess2022-07-18T18:54:57Z2022-07-18T18:54:57Z2021info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfMACIEL, T. F. et al. A framework for radio resource allocation and SDMA grouping in massive MIMO systems. IEEE Acess, vol. 9, p. 61680-61696, 20212169-3536http://www.repositorio.ufc.br/handle/riufc/67210Mauricio, Weskley Vinicius FernandesAraújo, Daniel CostaMaciel, Tarcísio FerreiraLima, Francisco Rafael Marquesengreponame:Repositório Institucional da Universidade Federal do Ceará (UFC)instname:Universidade Federal do Ceará (UFC)instacron:UFCinfo:eu-repo/semantics/openAccess2022-07-21T12:21:15Zoai:repositorio.ufc.br:riufc/67210Repositório InstitucionalPUBhttp://www.repositorio.ufc.br/ri-oai/requestbu@ufc.br || repositorio@ufc.bropendoar:2024-09-11T18:41:58.082913Repositório Institucional da Universidade Federal do Ceará (UFC) - Universidade Federal do Ceará (UFC)false
dc.title.none.fl_str_mv A framework for radio resource allocation and SDMA grouping in massive MIMO systems
title A framework for radio resource allocation and SDMA grouping in massive MIMO systems
spellingShingle A framework for radio resource allocation and SDMA grouping in massive MIMO systems
Mauricio, Weskley Vinicius Fernandes
Massive MIMO
Channel hardening
SDMA grouping
Radio resource allocation
Quality of service
title_short A framework for radio resource allocation and SDMA grouping in massive MIMO systems
title_full A framework for radio resource allocation and SDMA grouping in massive MIMO systems
title_fullStr A framework for radio resource allocation and SDMA grouping in massive MIMO systems
title_full_unstemmed A framework for radio resource allocation and SDMA grouping in massive MIMO systems
title_sort A framework for radio resource allocation and SDMA grouping in massive MIMO systems
author Mauricio, Weskley Vinicius Fernandes
author_facet Mauricio, Weskley Vinicius Fernandes
Araújo, Daniel Costa
Maciel, Tarcísio Ferreira
Lima, Francisco Rafael Marques
author_role author
author2 Araújo, Daniel Costa
Maciel, Tarcísio Ferreira
Lima, Francisco Rafael Marques
author2_role author
author
author
dc.contributor.author.fl_str_mv Mauricio, Weskley Vinicius Fernandes
Araújo, Daniel Costa
Maciel, Tarcísio Ferreira
Lima, Francisco Rafael Marques
dc.subject.por.fl_str_mv Massive MIMO
Channel hardening
SDMA grouping
Radio resource allocation
Quality of service
topic Massive MIMO
Channel hardening
SDMA grouping
Radio resource allocation
Quality of service
description This work proposes a framework for multiuser massive Multiple Input Multiple Output (MIMO) systems which is composed of three parts - clustering , grouping , and scheduling - and aims at maximizing the total system data rate considering Quality of Service (QoS) constraints. We firstly use a clustering algorithm to create clusters of spatially correlated Mobile Stations (MSs). Secondly, in the grouping part, we select a set of Space-Division Multiple Access (SDMA) groups from each cluster. These groups are used as candidate groups to receive Scheduling Unit (SU) in the scheduling part. In order to compose a group, we employ a metric that takes into account the trade-off between the spatial channel correlation and channel gain of MSs. In this context, it is proposed a suboptimal solution to avoid the high complexity required by the optimal solution. Thirdly and finally, we use the candidate SDMA groups from the grouping part to solve the data rate maximization problem considering QoS requirements. The scheduling part can be solved by our proposed optimal solution based on Branch and Bound (BB). However, since it has high computational complexity, we propose a suboptimal scheduling algorithm that presents a reduced complexity. In the simulation results, we evaluate the performance of both optimal and suboptimal solutions, as well as an adaptation of the Joint Satisfaction Maximization (JSM) scheduler to a massive MIMO scenario. Although the suboptimal solution presents a performance loss compared to the optimal one, it is more suitable for practical settings as it is able to obtain a good performance-complexity trade-off. Furthermore, we show that the choice of a suitable trade-off between the spatial channel correlation and channel gain improves the system performance. Finally, for a low number of available SDMA groups, the suboptimal solution presents near optimal outage and a throughput loss of only 10% in comparison to the high-complexity optimal solution while it outperforms the JSM solution in terms of outage and system throughput.
publishDate 2021
dc.date.none.fl_str_mv 2021
2022-07-18T18:54:57Z
2022-07-18T18:54:57Z
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 MACIEL, T. F. et al. A framework for radio resource allocation and SDMA grouping in massive MIMO systems. IEEE Acess, vol. 9, p. 61680-61696, 2021
2169-3536
http://www.repositorio.ufc.br/handle/riufc/67210
identifier_str_mv MACIEL, T. F. et al. A framework for radio resource allocation and SDMA grouping in massive MIMO systems. IEEE Acess, vol. 9, p. 61680-61696, 2021
2169-3536
url http://www.repositorio.ufc.br/handle/riufc/67210
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.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv IEEE Acess
publisher.none.fl_str_mv IEEE Acess
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_ 1813028911093645312