超密集网中一种基于人工蜂群的节能分簇算法

超密集网络中,密集部署的低功率基站将会加大系统的能耗,并且造成紧缺频谱资源的浪费.探寻干扰协调和系统节能的可行性方法在超密集网络架构下提出基站的休眠—唤醒—活跃机制,减小了休眠基站直接转为活跃状态的开启时间;另外,提出一种基于人工蜂群染色分簇算法,尽可能使用最少的颜色给拓扑图中的小区染色,并对簇内活跃基站进行优化功率分配.经仿真表明,休眠—唤醒—活跃机制能够提升系统的能源效率,染色分簇算法也可以改善用户的频谱效率和吞吐量.

An energy saving clustering algorithm based on artificial bee colony in ultra dense network

In ultra dense network (UDN),the dense deployment of low power base station (BS) will increase the system's energy consumption and cause the waste of the scarce spectrum resources.Aiming to explore the feasible method of energy saving system and interference coordination,BS sleeping-waking-active mechanism in UDN was proposed,which would reduce the opening time of the sleeping BS.Also an adjusted artificial bee colony algorithm was proposed which used the least colors to dye the BS in topology,then power allocation of active BS in different cluster was optimized.Simulations show that the sleeping-waking-active mechanism can improve the energy efficiency of the system,and the clustering algorithm can promote the spectrum efficiency and throughput.