Addressing the 5G Cell Switch-off Problem with a Multi-objective Cellular Genetic Algorithm

F. Luna, Rafael Marcos Luque Baena, Jesús Martínez, J. Valenzuela-Valdés, P. Padilla
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引用次数: 13

Abstract

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.
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用多目标细胞遗传算法解决5G小区关闭问题
预计5G网络的功耗将大大高于4G系统,主要是因为需要超密集的部署来满足即将到来的流量需求。本文讨论了细胞关闭(CSO)问题的多目标公式,这是在这种密集场景中节省能量的一种众所周知的有效方法,该问题通过一种精确但相当未知的多目标元启发式算法MOCell(多目标细胞遗传算法)来解决。它已经在不同的密度水平增加的网络上进行了评估。结果表明,与广泛使用的多目标算法相比,MOCell能够节省大量能源。
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