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Fast and efficient energy-oriented cell assignment in heterogeneous networks
dc.contributor.author | Rubio Loyola, Javier |
dc.contributor.author | Aguilar Fuster, Christian |
dc.contributor.author | Díez Fernández, Luis Francisco |
dc.contributor.author | Agüero Calvo, Ramón |
dc.contributor.author | Gorricho Moreno, Juan Luis |
dc.contributor.author | Serrat Fernández, Juan |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Enginyeria Telemàtica |
dc.date.accessioned | 2019-06-21T18:39:49Z |
dc.date.available | 2020-06-11T00:25:29Z |
dc.date.issued | 2019-06-10 |
dc.identifier.citation | Rubio-Loyola, J. [et al.]. Fast and efficient energy-oriented cell assignment in heterogeneous networks. "Wireless Networks", 10 Juny 2019, vol. 2019, p. 1-19. |
dc.identifier.issn | 1572-8196 |
dc.identifier.uri | http://hdl.handle.net/2117/134952 |
dc.description | This is a post-peer-review, pre-copyedit version of an article published in Wireless Networks. The final authenticated version is available online at: http://dx.doi.org/10.1007/s11276-019-02047-x” |
dc.description.abstract | 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. |
dc.format.extent | 19 p. |
dc.language.iso | eng |
dc.publisher | Springer |
dc.subject | Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors |
dc.subject.lcsh | Wireless communication systems |
dc.subject.other | Cell assignment |
dc.subject.other | Resource allocation |
dc.subject.other | Metaheuristic |
dc.subject.other | Energy efficiency |
dc.subject.other | Cellular networks |
dc.subject.other | Heterogeneous networks |
dc.subject.other | Dense networks |
dc.title | Fast and efficient energy-oriented cell assignment in heterogeneous networks |
dc.type | Article |
dc.subject.lemac | Comunicació sense fil, Sistemes de |
dc.contributor.group | Universitat Politècnica de Catalunya. MAPS - Management, Pricing and Services in Next Generation Networks |
dc.identifier.doi | 10.1007/s11276-019-02047-x |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | http://link.springer.com/article/10.1007/s11276-019-02047-x |
dc.rights.access | Open Access |
local.identifier.drac | 25184600 |
dc.description.version | Postprint (author's final draft) |
dc.relation.projectid | info:eu-repo/grantAgreement/EC/H2020/777067/EU/Novel Enablers for Cloud Slicing/NECOS |
dc.relation.projectid | info:eu-repo/grantAgreement/MINECO//TEC2015-71329-C2-2-R/ES/APROVISIONAMIENTO DINAMICO DE CONECTIVIDAD EN ESCENARIOS INALAMBRICOS 5G DE ALTA DENSIDAD/ |
local.citation.author | Rubio-Loyola, J.; Aguilar, C.; Díez, L.; Agüero Calvo, Ramón; Gorricho, J.; Serrat, J. |
local.citation.publicationName | Wireless Networks |
local.citation.volume | 2019 |
local.citation.startingPage | 1 |
local.citation.endingPage | 19 |
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