Extending 5G capacity planning through advanced subscriber behavior-centric clustering

Detalhes bibliográficos
Autor(a) principal: Gonçalves, L.
Data de Publicação: 2019
Outros Autores: Sebastião, P., Souto, N., Correia, A.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10071/20215
Resumo: his work focuses on providing enhanced capacity planning and resource management for 5G networks through bridging data science concepts with usual network planning processes. For this purpose, we propose using a subscriber-centric clustering approach, based on subscribers’ behavior, leading to the concept of intelligent 5G networks, ultimately resulting in relevant advantages and improvements to the cellular planning process. Such advanced data-science-related techniques provide powerful insights into subscribers’ characteristics that can be extremely useful for mobile network operators. We demonstrate the advantages of using such techniques, focusing on the particular case of subscribers’ behavior, which has not yet been the subject of relevant studies. In this sense, we extend previously developed work, contributing further by showing that by applying advanced clustering, two new behavioral clusters appear, whose traffic generation and capacity demand profiles are very relevant for network planning and resource management and, therefore, should be taken into account by mobile network operators. As far as we are aware, for network, capacity, and resource management planning processes, it is the first time that such groups have been considered. We also contribute by demonstrating that there are extensive advantages for both operators and subscribers by performing advanced subscriber clustering and analytics.
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spelling Extending 5G capacity planning through advanced subscriber behavior-centric clustering5GAdvanced clusteringBehavior ModellingCapacity planningIntelligent 5GSubscriber centricitySubscriber clustersResource managementhis work focuses on providing enhanced capacity planning and resource management for 5G networks through bridging data science concepts with usual network planning processes. For this purpose, we propose using a subscriber-centric clustering approach, based on subscribers’ behavior, leading to the concept of intelligent 5G networks, ultimately resulting in relevant advantages and improvements to the cellular planning process. Such advanced data-science-related techniques provide powerful insights into subscribers’ characteristics that can be extremely useful for mobile network operators. We demonstrate the advantages of using such techniques, focusing on the particular case of subscribers’ behavior, which has not yet been the subject of relevant studies. In this sense, we extend previously developed work, contributing further by showing that by applying advanced clustering, two new behavioral clusters appear, whose traffic generation and capacity demand profiles are very relevant for network planning and resource management and, therefore, should be taken into account by mobile network operators. As far as we are aware, for network, capacity, and resource management planning processes, it is the first time that such groups have been considered. We also contribute by demonstrating that there are extensive advantages for both operators and subscribers by performing advanced subscriber clustering and analytics.MDPI2020-03-25T16:59:16Z2019-01-01T00:00:00Z20192020-03-25T16:58:20Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10071/20215eng2079-929210.3390/electronics8121385Gonçalves, L.Sebastião, P.Souto, N.Correia, A.info: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:RCAAP2023-11-09T17:57:02Zoai:repositorio.iscte-iul.pt:10071/20215Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:29:23.212900Repositório 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 Extending 5G capacity planning through advanced subscriber behavior-centric clustering
title Extending 5G capacity planning through advanced subscriber behavior-centric clustering
spellingShingle Extending 5G capacity planning through advanced subscriber behavior-centric clustering
Gonçalves, L.
5G
Advanced clustering
Behavior Modelling
Capacity planning
Intelligent 5G
Subscriber centricity
Subscriber clusters
Resource management
title_short Extending 5G capacity planning through advanced subscriber behavior-centric clustering
title_full Extending 5G capacity planning through advanced subscriber behavior-centric clustering
title_fullStr Extending 5G capacity planning through advanced subscriber behavior-centric clustering
title_full_unstemmed Extending 5G capacity planning through advanced subscriber behavior-centric clustering
title_sort Extending 5G capacity planning through advanced subscriber behavior-centric clustering
author Gonçalves, L.
author_facet Gonçalves, L.
Sebastião, P.
Souto, N.
Correia, A.
author_role author
author2 Sebastião, P.
Souto, N.
Correia, A.
author2_role author
author
author
dc.contributor.author.fl_str_mv Gonçalves, L.
Sebastião, P.
Souto, N.
Correia, A.
dc.subject.por.fl_str_mv 5G
Advanced clustering
Behavior Modelling
Capacity planning
Intelligent 5G
Subscriber centricity
Subscriber clusters
Resource management
topic 5G
Advanced clustering
Behavior Modelling
Capacity planning
Intelligent 5G
Subscriber centricity
Subscriber clusters
Resource management
description his work focuses on providing enhanced capacity planning and resource management for 5G networks through bridging data science concepts with usual network planning processes. For this purpose, we propose using a subscriber-centric clustering approach, based on subscribers’ behavior, leading to the concept of intelligent 5G networks, ultimately resulting in relevant advantages and improvements to the cellular planning process. Such advanced data-science-related techniques provide powerful insights into subscribers’ characteristics that can be extremely useful for mobile network operators. We demonstrate the advantages of using such techniques, focusing on the particular case of subscribers’ behavior, which has not yet been the subject of relevant studies. In this sense, we extend previously developed work, contributing further by showing that by applying advanced clustering, two new behavioral clusters appear, whose traffic generation and capacity demand profiles are very relevant for network planning and resource management and, therefore, should be taken into account by mobile network operators. As far as we are aware, for network, capacity, and resource management planning processes, it is the first time that such groups have been considered. We also contribute by demonstrating that there are extensive advantages for both operators and subscribers by performing advanced subscriber clustering and analytics.
publishDate 2019
dc.date.none.fl_str_mv 2019-01-01T00:00:00Z
2019
2020-03-25T16:59:16Z
2020-03-25T16:58:20Z
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/10071/20215
url http://hdl.handle.net/10071/20215
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2079-9292
10.3390/electronics8121385
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 MDPI
publisher.none.fl_str_mv MDPI
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
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