两层网络中基于聚类算法的分簇干扰对齐研究

Interference alignment method based on clustering algorithm in two-tier networks

由Femtocell和Macrocell构成两层网络可以提高系统容量,但也会引起严重的共道干扰.干扰对齐是一种避免干扰的有效方式,但对密集部署的两层网络全网实行干扰对齐是不现实的,也是没有必要的,但有必要对网络进行分簇,以减小干扰管理复杂度.为此,提出基于聚类思想分簇的干扰对齐算法.文中首先对实际场景的Femtocell网络模型进行研究,然后基于K-Medoids算法对三维泊松点过程分布的Femtocell网络进行分簇,最后对确定的簇利用干扰对齐技术进行干扰消除,以达到降低系统干扰对齐复杂度的目的.仿真结果表明,所提算法在实现系统有效分簇的同时,提高了系统的信道容量,适用于实际通信系统.

A two-tier network consisting of Femtocell and Macrocell can increase system capacity, and it can also cause severe co-channel interference. Interference alignment is an effective way to avoid interference, but it is unrealistic and unnecessary to impose interference alignment on a dense network of two-tier networks. It is necessary to divide the network into some clusters to reduce interference management complexity. In this paper, we propose an interference alignment algorithm with the idea of clustering. Firstly, the Femtocell network model in actual scene is studied, and then the Femtocell network which distributes in three-dimensional Poisson point process is divided into clusters based on the K-Medoids algorithm. Finally, the interference is eliminated by using the interference alignment technique to realize the purpose of reducing the system complexity. The simulation results show that the proposed algorithm can achieve effective system clustering, improve the channel capacity of the system, and is suitable for the actual communication system.