Adaptive Small Cells Clustering based on Many-to-Many Swap Matching for Ultra-Dense Networks

Abstract

Ultra-dense networks (UDN) play an important role in 5G, which significantly supports the network foundation for ultra-high density device connection and ultra-high speed data demand in future mobile network. However, the increasing density of small cell in UDN brings greater challenge to resource allocation in wireless networks. In order to achieve efficient resource allocation, a many-to-many swap matching (M-MSM) based algorithm of adaptive small cells clustering in ultra-dense networks is proposed in the paper. The many-to-many matching algorithm is utilized to divide the user-centric small cells into different clusters. Meanwhile the matching effect is further optimized by the swap matching algorithm. Simulation results show that the proposed M-MSM algorithm can effectively improve the maximum achievable rate of the UDN.