RT Conference Proceedings
T1 Addressing the 5G cell switch-off problem with a multi-objective cellular genetic algorithm
A1 Luna, Francisco
A1 Luque-Baena, Rafael Marcos
A1 Martínez, Jesús
A1 Padilla, Pablo
A1 Valenzuela-Valdés, Juan Francisco
K1 Algoritmos genéticos - Congresos
AB The power consumption foreseen for 5G networks is expected to be substantially greater than that of 4G systems, mainly because of the ultra-dense deployments required to meet the upcoming traffic demands. This paper deals with a multi- objective formulation of the Cell Switch-Off (CSO) problem, a well-known and effective approach to save energy in such dense scenarios, which is addressed with an accurate, yet rather unknown multi-objective metaheuristic called MOCell (multi- objective cellular genetic algorithm). It has been evaluated over a different set of networks of increasing densification levels. The results have shown that MOCell is able to reach major energy savings when compared to a widely used multi-objective algorithm.
YR 2018
FD 2018-07-16
LK https://hdl.handle.net/10630/16274
UL https://hdl.handle.net/10630/16274
LA eng
NO © 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
NO TIN2016-75097-PUniversidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026