Joint User-Centric Clustering and Frequency Allocation in Ultra-Dense C-RAN

Abstract

This paper considers the downlink ultra-dense cloud radio access network (C-RAN), which employs multiple radio remote head (RRH) cooperation to guarantee the minimum achievable transmission rate for each user equipment (UE). However, due to the limited orthogonal frequency resources, it is difficult to achieve this goal. To maximize the coverage probability of the system, we focus on the joint user-centric clustering and frequency allocation problem. To reduce the computational complexity, this problem is split into two sub-problems: user-centric clustering and frequency allocation. Firstly, we propose a novel binary user-centric clustering strategy, which includes serving clusters and silent clusters. This strategy determines the acceptable combination of serving clusters and silent clusters to guarantee the minimum transmission rate for each UE and simplify the complexity of the subsequent frequency allocation. Then based on the generated clusters, a new graph generation method is proposed. The advantage of this graph is that we can allocate frequency resources by simply judging the relationship between the serving clusters in the graph without complicated calculations. Numerical simulation results show that the joint binary user-centric clustering and location-based frequency allocation scheme is superior to the benchmark solutions in terms of the coverage probability.