A rule-based solution search methodology for self-optimization in cellular networks

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dc.contributor	Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
dc.contributor	Universitat Politècnica de Catalunya. GRCM - Grup de Recerca en Comunicacions Mòbils
dc.contributor.author	Sánchez González, Juan
dc.contributor.author	Pérez Romero, Jordi
dc.contributor.author	Sallent Roig, José Oriol
dc.date	2014-12-12
dc.identifier.citation	Sanchez, J.; Perez, J.; Sallent, J. A rule-based solution search methodology for self-optimization in cellular networks. "IEEE communications letters", 12 Desembre 2014, vol. 18, núm. 12, p. 2189-2192.
dc.identifier.citation	1089-7798
dc.identifier.citation	10.1109/LCOMM.2014.2363670
dc.identifier.uri	http://hdl.handle.net/2117/26062
dc.language.iso	eng
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Comunicacions mòbils
dc.subject	Mobile communication systems
dc.subject	Self-optimization
dc.subject	Self-organizing networks (SON)
dc.subject	Cellular networks
dc.subject	Cell coverage
dc.subject	Cell overlap
dc.subject	Comunicacions mòbils, Sistemes de
dc.title	A rule-based solution search methodology for self-optimization in cellular networks
dc.type	info:eu-repo/semantics/publishedVersion
dc.type	info:eu-repo/semantics/article
dc.description.abstract	This letter presents a rule-based solution search (RBSS) algorithm for self-optimization in a cellular network. It improves the solution search process of classical optimization methodologies by including a set of rules that capture the knowledge of how a given problem can be solved. The results obtained in a scenario using measurements from a real network reveal that including the RBSS algorithm achieves reductions of up to 60% and 90% in the convergence time of Particle Swarm and Genetic Algorithms, respectively.
dc.description.abstract	Peer Reviewed

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