A Clustering-Based Spectrum Resource Allocation Algorithm for Dense Small Cell Networks

Abstract

This paper considers the spectrum resource allocation problem for dense small cell networks, and focuses on a system scenario where small cells are non-uniformly distributed in a macro cell. A clustering-based spectrum resource allocation (CSRA) algorithm is proposed to perform resource allocation for both macro-cell user equipments and small cell user equipments with the objective to maximize the system capacity. To minimize both intra-tier and inter-tier interferences in the system, the concept of clusters is introduced into spectrum resource allocation, and a few principles are correspondingly set for clustering. Moreover, an upper limit for the cluster size is set in for clustering to avoid the formation of a too large cluster, which otherwise would consume a large number of physical resource blocks (PRBs) and thus affect the system capacity. To increase spectrum utilization, all PRBs are allowed to be used by all users in the system. Simulation results show that the proposed CSRA algorithm can significantly increase the system capacity as compared with an existing CDRA algorithm.