A two-stage cluster-based resource management scheme in ultra-dense networks

Abstract

As the demand for mobile data services skyrockets and the scarcity of spectrum increasing, femtocell networks overlaying with macrocell networks becomes a promising solution. However, the dense and random deployment of femto-cells and their uncoordinated operations cause severe inter-cell interference. This paper studies cluster-based wireless resource management issues in ultra-dense networks (UDN). Firstly, a modified K-means algorithm is performed in the clustering process. A reasonable number of clusters is derived instead of the predefined value as the input parameter. The wireless resource management is investigated to maximize the sum-throughput in UDN. Specifically, this paper propose a two-stage resource management scheme to solve this problem. In the first stage, primary resource allocation is performed by using a greedy search algorithm in each cluster. In the second stage, a supplementary allocation algorithm (SAA) is presented to assign the remainder subchannels. Finally, numerical results show that the proposed scheme achieves a satisfying performance in terms of average SINR, the system throughput, and the spatial spectrum efficiency, which provides guidelines for the practical dense deployment of femtocells.