2026-05-29T23:31:43Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/162742026-02-03T12:25:05Zcom_10630_2254col_10630_37959

Luna, Francisco Luque-Baena, Rafael Marcos Martínez, Jesús Padilla, Pablo Valenzuela-Valdés, Juan Francisco 2018-07-16T11:17:17Z 2018-07-16T11:17:17Z 2018-07-16 https://hdl.handle.net/10630/16274 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. eng http://creativecommons.org/licenses/by-nd/4.0/ open access Attribution-NonCommercial-NoDerivatives 4.0 Internacional Attribution-NoDerivatives 4.0 Internacional Algoritmos genéticos - Congresos Addressing the 5G cell switch-off problem with a multi-objective cellular genetic algorithm conference output