超密集网络中基于分簇的干扰管理算法

CLUSTERING-BASED INTERFERENCE MANAGEMENT ALGORITHM IN ULTRA-DENSE NETWORKS

  • 摘要: 针对超密集网络拓扑结构复杂而导致的干扰愈加严重问题,提出一种改进的基于干扰图的分簇干扰管理算法。基于干扰关系定义簇权重值并构建干扰图;根据分簇算法将微微基站分簇,设置分簇阈值,避免顶点无限制地加入一个簇内;分簇完成后,根据用户数据速率值的大小依次为用户分配信道,结合功率分配算法,减轻簇内干扰。仿真结果显示,与不分簇的算法比,所提算法可以减少微微基站之间的干扰,同时,结合能效函数辅助的功率分配迭代算法可以得到更高的系统吞吐量。

     

    Abstract: Aiming at the increasingly serious problem of interference caused by the complex topology of ultra-dense networks, the paper proposes an improved interference graph-based clustering interference management algorithm. The cluster weight value was defined based on the interference relationship and the interference graph was constructed. The pico base station was divided into clusters according to the clustering algorithm, and the clustering threshold was set to avoid the vertices being added into a cluster indefinitely. After the clustering was completed, channels were assigned to users according to their data rate values. Combined with the power allocation algorithm, interference in the cluster can be reduced. The simulation results show that the proposed algorithm can reduce the interference between pico base stations compared with the non-clustering algorithms, and the power allocation iterative algorithm assisted by the energy efficiency function can obtain higher system throughput.

     

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