摘要
现有的动态分簇算法大多假设系统知道完全的信道状态信息(CSI),但这在实际系统中较难实现。针对这一问题,提出了一种部分CSI下的近邻传播动态分簇算法。在每个基站已知一定地理区域内基站CSI的情况下,利用协同度设计输入矩阵,通过近邻传播的方式在全网内传播吸引度及归属度;然后,通过协作证据积累过程,生成多个协同簇。仿真结果表明,该算法的分簇性能接近于完全CSI下的利益树分簇算法,算法的收敛速度受系统内基站数的影响较小,收敛速度快,适用于实际系统。
The precondition of whole channel state information（CSI） is impractical in realistic systems.To deal with this problem,this paper proposed a partial CSI based affinity propagation dynamic clustering algorithm.This algorithm used degree of wiliness to cooperate（DWC） to design the input matrix and introduced a cooperation fact to adjust the number of clusters in clustering results.Assuming every BS had the partial CSI information of whole system,during every iteration rounds,it propagated the messages of responsibility and availability to accumulate the coordination incidences among BSs.After that,it constructed several clusters of dynamic size.Simulation results show that the capability of this scheme is almost as same as the whole CSI based benefit-tree clustering algorithm.And the convergence iteration rounds increase slowly as the system size enlarging.This exhibits high convergence speed and is well suited for implementation in realistic system.
出处
《计算机应用研究》
CSCD
北大核心
2013年第4期1136-1139,1151,共5页
Application Research of Computers
基金
国家自然科学基金资助项目(61171108)
关键词
协同度
动态分簇
信道状态信息
近邻传播
degree of wiliness to cooperate（DWC）
dynamic clustering
channel state information（CSI）
affinity propagation（AP）
