Fast and efficient energy-oriented cell assignment in heterogeneous networks

The cell assignment problem is combinatorial, with increased complexity when it is tackled considering resource allocation. This paper models joint cell assignment and resource allocation for cellular heterogeneous networks, and formalizes cell assignment as an optimization problem. Exact algorithms...

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Autores: Rubio-Loyola, Javier, Aguilar-Fuster, Christian, Díez Fernández, Luis Francisco, Agüero Calvo, Ramón||| 0000-0002-9620-3990, Luis-Gorricho, Juan, Serrat Fernández, Joan
Formato: artículo
Fecha de publicación:2020
País:España
Recursos:Universidad de Cantabria (UC)
Repositorio:UCrea Repositorio Abierto de la Universidad de Cantabria
Idioma:inglés
OAI Identifier:oai:repositorio.unican.es:10902/18620
Acesso em linha:http://hdl.handle.net/10902/18620
Access Level:acceso abierto
Palavra-chave:Cell assignment
Resource allocation
Metaheuristic
Energy efficiency
Cellular networks
Heterogeneous networks
Dense networks
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spelling Fast and efficient energy-oriented cell assignment in heterogeneous networksRubio-Loyola, JavierAguilar-Fuster, ChristianDíez Fernández, Luis FranciscoAgüero Calvo, Ramón||| 0000-0002-9620-3990Luis-Gorricho, JuanSerrat Fernández, JoanCell assignmentResource allocationMetaheuristicEnergy efficiencyCellular networksHeterogeneous networksDense networksThe cell assignment problem is combinatorial, with increased complexity when it is tackled considering resource allocation. This paper models joint cell assignment and resource allocation for cellular heterogeneous networks, and formalizes cell assignment as an optimization problem. Exact algorithms can find optimal solutions to the cell assignment problem, but their execution time increases drastically with realistic network deployments. In turn, heuristics are able to find solutions in reasonable execution times, but they get usually stuck in local optima, thus failing to find optimal solutions. Metaheuristic approaches have been successful in finding solutions closer to the optimum one to combinatorial problems for large instances. In this paper we propose a fast and efficient heuristic that yields very competitive cell assignment solutions compared to those obtained with three of the most widely-used metaheuristics, which are known to find solutions close to the optimum due to the nature of their search space exploration. Our heuristic approach adds energy expenditure reduction in its algorithmic design. Through simulation and formal statistical analysis, the proposed scheme has been proved to produce efficient assignments in terms of the number of served users, resource allocation and energy savings, while being an order of magnitude faster than metaheuritsic-based approaches.This paper has been supported by the National Council of Research and Technology (CONACYT) through Grant FONCICYT/272278 and the ERANetLAC (Network of the European Union, Latin America, and the Caribbean Countries) Project ELAC2015/T100761. This paper is partially supported also by the ADVICE Project, TEC2015-71329 (MINECO/FEDER) and the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 777067 (NECOS Project).Springer NetherlandsUniversidad de Cantabria20202020-07-01journal articlehttp://purl.org/coar/resource_type/c_6501NAhttp://purl.org/coar/version/c_be7fb7dd8ff6fe43info:eu-repo/semantics/articlehttp://hdl.handle.net/10902/18620Wireless Networks, 2020, 26(5), 3119-3137reponame:UCrea Repositorio Abierto de la Universidad de Cantabriainstname:Universidad de Cantabria (UC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:repositorio.unican.es:10902/186202026-06-02T12:39:31Z
dc.title.none.fl_str_mv Fast and efficient energy-oriented cell assignment in heterogeneous networks
title Fast and efficient energy-oriented cell assignment in heterogeneous networks
spellingShingle Fast and efficient energy-oriented cell assignment in heterogeneous networks
Rubio-Loyola, Javier
Cell assignment
Resource allocation
Metaheuristic
Energy efficiency
Cellular networks
Heterogeneous networks
Dense networks
title_short Fast and efficient energy-oriented cell assignment in heterogeneous networks
title_full Fast and efficient energy-oriented cell assignment in heterogeneous networks
title_fullStr Fast and efficient energy-oriented cell assignment in heterogeneous networks
title_full_unstemmed Fast and efficient energy-oriented cell assignment in heterogeneous networks
title_sort Fast and efficient energy-oriented cell assignment in heterogeneous networks
dc.creator.none.fl_str_mv Rubio-Loyola, Javier
Aguilar-Fuster, Christian
Díez Fernández, Luis Francisco
Agüero Calvo, Ramón||| 0000-0002-9620-3990
Luis-Gorricho, Juan
Serrat Fernández, Joan
author Rubio-Loyola, Javier
author_facet Rubio-Loyola, Javier
Aguilar-Fuster, Christian
Díez Fernández, Luis Francisco
Agüero Calvo, Ramón||| 0000-0002-9620-3990
Luis-Gorricho, Juan
Serrat Fernández, Joan
author_role author
author2 Aguilar-Fuster, Christian
Díez Fernández, Luis Francisco
Agüero Calvo, Ramón||| 0000-0002-9620-3990
Luis-Gorricho, Juan
Serrat Fernández, Joan
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Universidad de Cantabria
dc.subject.none.fl_str_mv Cell assignment
Resource allocation
Metaheuristic
Energy efficiency
Cellular networks
Heterogeneous networks
Dense networks
topic Cell assignment
Resource allocation
Metaheuristic
Energy efficiency
Cellular networks
Heterogeneous networks
Dense networks
description The cell assignment problem is combinatorial, with increased complexity when it is tackled considering resource allocation. This paper models joint cell assignment and resource allocation for cellular heterogeneous networks, and formalizes cell assignment as an optimization problem. Exact algorithms can find optimal solutions to the cell assignment problem, but their execution time increases drastically with realistic network deployments. In turn, heuristics are able to find solutions in reasonable execution times, but they get usually stuck in local optima, thus failing to find optimal solutions. Metaheuristic approaches have been successful in finding solutions closer to the optimum one to combinatorial problems for large instances. In this paper we propose a fast and efficient heuristic that yields very competitive cell assignment solutions compared to those obtained with three of the most widely-used metaheuristics, which are known to find solutions close to the optimum due to the nature of their search space exploration. Our heuristic approach adds energy expenditure reduction in its algorithmic design. Through simulation and formal statistical analysis, the proposed scheme has been proved to produce efficient assignments in terms of the number of served users, resource allocation and energy savings, while being an order of magnitude faster than metaheuritsic-based approaches.
publishDate 2020
dc.date.none.fl_str_mv 2020
2020-07-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
NA
http://purl.org/coar/version/c_be7fb7dd8ff6fe43
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10902/18620
url http://hdl.handle.net/10902/18620
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Springer Netherlands
publisher.none.fl_str_mv Springer Netherlands
dc.source.none.fl_str_mv Wireless Networks, 2020, 26(5), 3119-3137
reponame:UCrea Repositorio Abierto de la Universidad de Cantabria
instname:Universidad de Cantabria (UC)
instname_str Universidad de Cantabria (UC)
reponame_str UCrea Repositorio Abierto de la Universidad de Cantabria
collection UCrea Repositorio Abierto de la Universidad de Cantabria
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,301629

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