摘要
该文针对协同基站群分簇算法缺乏通用模型的问题,提出了一种协同度分簇模型,将系统和容量最大化简化为协同度最大化。在该模型的指导下,将分簇问题建模为有向带权连通图的利益树生成问题,设计了一种利益树动态分簇算法。该算法能够并行生成多个规模动态变化的协同簇,克服了传统顺序分簇导致的系统性能受限的问题;且分簇结果的协同度之和最大,可获得近似最优的分簇性能。仿真结果表明,该算法与传统贪婪搜索算法相比,系统频谱利用率提高了约0.4 bit/Hz,且算法复杂度只与基站个数呈线性关系。
As the existing clustering algorithms are lack of effective guidable clustering model,an Degree of Wiliness to Cooperate（DWC） based clustering model is proposed,in which the clustering objective of maximizing the system sum rate is approximately to maximizing the sum of DWC between every two Base Stations（BS） in system.Based on this,the clustering issue is modeled as constructing benefit-trees of a connected graph with edge costs.Then a benefit-tree dynamic clustering algorithm is proposed.This algorithm simultaneously generates several clusters of dynamic size which could solve the limited-capacity problem caused by conventional orderly clustering scheme.Besides,the maximum sum of DWC in clustering results offers the approximately best system clustering capacity.Simulation results show that compared to the conventional greedy clustering algorithm,the system spectrum efficiency in this algorithm increases about 0.4 bit/Hz and the computational complexity is directly proportional to system size.
出处
《电子与信息学报》
EI
CSCD
北大核心
2012年第6期1469-1475,共7页
Journal of Electronics & Information Technology
基金
国家科技重大项目(2008ZX03003-004)
国家973计划项目(2007CB310608)资助课题
关键词
无线通信
分簇
多基站协同
小区间干扰
信道状态信息
Wireless communication
Cluster
Base Stations（BS） cooperation
Inter-Cell Interference（ICI）
Channel State Information（CSI）
