超密集网络中小区分簇的资源分配仿真  

Resource Allocation Simulation of Cell Clustering in Ultra-Ense Network

作　　者：刘亚非 滕得阳 王琼[1] 周朋光 LIU Ya-fei;TENG De-yang;WANG Qiong;ZHOU Peng-guang(School of Communication and Information Engineering,Chongqing University of Posts and Telecommunications,Chongqing 400065,China)

机构地区：[1]重庆邮电大学通信与信息工程学院,重庆400065

出　　处：《计算机仿真》2018年第11期259-263,共5页Computer Simulation

基　　金：国家科技重大专项(2016ZX03002010-003)

摘　　要：对超密集网络中小区分簇进行资源分配,可以抑制小区间的干扰,满足用户速率需求,有效提升网络频谱效率。基于小区分簇的资源分配方案,需要对超密集网络中毫微微小区(femtocell)动态分簇,分簇之后再进行子信道和功率分配。传统资源分配算法仅仅考虑了毫微微小区(femtocell)之间同层干扰问题,而忽略了小区跨层干扰,并且小区分簇方案容易陷入局部最优解,导致网络性能提升不明显。提出基于小区分簇的资源分配方法,考虑了小区同层干扰以及毫微微小区与宏小区(Macrocell)之间跨层干扰问题,根据毫微微小区之间的干扰权值大小,利用改进的蚁群优化算法(EACO)设定信息素浓度范围来对FAPs分簇,有效避免传统资源分配算法陷入局部最优解的问题;其次利用启发式信道分配算法为簇内FUEs分配子信道,采用KKT条件为用户分配功率。仿真表明,所提方法能够满足用户速率需求,提升网络频谱效率。In the ultra-dense network,the resource allocation based on cell clustering can suppress the inter-cell interference,meet the user rate requirements,and improve the network spectrum efficiency. The method of resource allocation based on cell clustering was proposed,which considered the interference of the same layer and the crosslayer interference between the femto-cell and the macrocell. Firstly,according to the size of interference weights between femtocells,the improved ant colony optimization algorithm set the pheromone concentration range to cluster FAPs,which effectively avoided the traditional resource allocation algorithm into the local optimal solution. Secondly,the heuristic channel allocation algorithm was used to allocate sub-channels for intra-cluster FUEs,and KKT conditions were used to allocate power to users. Simulation results show that the proposed algorithm can effectively meet the user rate requirements and improve the network spectrum efficiency.

关 键 词：超密集网络 分簇 干扰 资源分配 毫微微小区 

分 类 号：TN929.5[电子电信—通信与信息系统]