Clustering-based resource allocation algorithm in ultra dense network

Abstract

In ultra-dense network(UDN), the serious inter-cell interference has restricted the data rate of users. In view of this problem, a new coloring-based clustering resource allocation scheme is proposed in this paper. The scheme is divided into three steps: the first step uses graph-based coloring algorithm for femtocell access points (FAPs). The second step uses the amount of data to be transmitted, the queuing delay and the interference intensity of each femtocell user equipment (FUEs) in the cluster to build the corresponding priority, and then calculate the priority of each cluster. Such clusters owning high priority can received sub-channel of good channel gain first. The third step allocates power for FUEs by Karush-Kuhn-Tucker(KKT) and water-filling algorithm. Simulation results show that the proposed scheme can effectively reduce the interference among femtocells and also greatly satisfy the needs of users, while improving the throughput and spectrum efficiency. In addition, the power of each sub-channel is dynamically adjusted based on the fairness criterion of maximum power and minimum rate which further improves the fairness degree among FUEs.