An artificial neural network based cell switch-off algorithm in cellular system

With the increasing usage of wireless devices, the power consumption and energy efficiency of cellular networks have been receiving much attention in wireless network in recent years. One way of saving energy is to switch off some underutilized small cells in light traffic conditions. In existing researches, the number of the base stations (BSs) that can be switched off in a network is take as the the optimization object. However, under many circumstances, it would be acceptable if the energy efficiency increases with less cells switched off. In this paper, we take the energy efficiency as the optimization object and suppose that each user equipment (UE) has a minimum rate requirement and the bandwith is uniformly shared by UEs in a cell. Under this assumption, the problem of optimizing cell switch-off for maximum energy efficiency is still NP-hard. We present an artificial neural network based small cell switch-off algorithm followed by flip-over method in omnidirectional cell deployment which offers a good result with linear complexity in on-line system and the Quality of Service (QoS) of the UEs can be met. Numerical results are presented through system level simulations.