大规模组网的集中式基站休眠算法

分析了通过基站休眠降低无线通信网络能效的集中式算法和分布式算法的原理和性能,在此基础上,针对集中式休眠算法随着网络规模的增大其计算复杂度将会异常巨大的问题,提出了一种面向大规模通信网络的集中式分簇算法。该算法首先在时域上运用多目标均衡优化对休眠时间段进行划分,随后在空域上对基站进行合理的分簇,最后通过粒子群优化算法进行了休眠组合的确定。仿真结果表明,该算法的计算复杂度要低于其他集中式算法,并且性能衰减可以忽略不计,整体的休眠部署更加合理。

A base station sleep algorithm for large-scale centralized networks

The principle and performance of the centralized base station (BS) sleeping algorithm and the distributed BS sleeping algorithm for reducing the energy consumption of wireless communication networks were analyzed , and then, a centralized clusting algorithm ( CCA) for BS sleeping was proposed for large scale wireless communication networks to solve the problem that the computational complexity of the centralized algorithm will become very large when the number of BSs increases .The CCA first formulates a bi-objective problem to divide the sleep period , and then the BSs are divided in clusters to obtain the combination of BSs ’ states through the particle swarm optimization ( PSO) .The simulation results show that the CCA significant outperforms the PSO and fast exhaustive algorithms in the computational complexity while keeping the same performance in energy saving as these algorithms ’ .