部分信道状态信息下簇规模均匀的基站群快速分簇方案

在获取的信道状态信息(CSI)失真且信道快变的情况下，现有分簇方案需要获取全部基站的CSI且不能快速得到簇结构。针对以上问题，提出了一种基于近邻传播(AP)聚类思想的基站群快速分簇方案。该方案只需获取近邻基站间（部分）的CSI，通过近邻基站间协同的平均信干比(SIR)增益来构成稀疏化的相似度矩阵；然后，在近邻基站间进行协同信息的交互、更新，快速生成多个协同簇；最后，以簇合并带来的平均信干比增益大小为依据合并较小规模的簇，从而达到簇规模均匀的目的。仿真结果表明，与完全CSI下的现有分簇方案相比，所提方案不但收敛速度快，而且簇规模较均匀。

Fast clustering scheme of base station group based on partial CSI and uniform cluster size

In the case of Channel State Information(CSI) distortion and channel fast changing,the existing clustering scheme needs to get CSI of all the base stations and generates cluster structure slowly.Concerning the problem,a fast clustering scheme based on Affinity Propagation(AP) algorithm was proposed in this paper.The scheme just needs CSI of neighboring base stations.Firstly,sparse similarity matrix was formed by the average Signal to Interfere Ratio(SIR) of cooperation between neighboring base stations.Then,among neighboring base stations,the interaction and update of collaborative information was done to quickly generate multiple clusters.Finally,the average SIR of cooperation between clusters was normal when the smaller clusters were combined to achieve the purpose of uniform cluster size.The simulation results show that the performance of the proposed scheme is better than the existing scheme in terms of convergence and cluster size uniformity.