Fairness-Based Distributed Resource Allocation in Two-Tier Heterogeneous Networks

Booming demand for mobile intelligent terminal equipment results in the exponential growth of the data flow in the fifth-generation mobile communication network. Small-cell networks have been considered as one of the possible solutions, where interference management and effective resource allocation are outstanding issues due to numerous small base stations. In this paper, the concept of cognitive small-cell networks is introduced, which combines technologies from cognitive radio with small cells. We aim to maximize the total throughput of the cognitive small-cell networks by jointly considering interference management, fairness-based resource allocation, average outage probability, and channel reuse radius. In order to make the optimization problem tractable, we decompose the original problem into three sub-problems. First, we derive the average outage probability function of the network with respect to the spectrum sensing threshold. With a given outage probability threshold, the associated range of the channel reuse radius is obtained. In addition, to maximize the total throughput, a fairness-based distributed resource allocation (FDRA) algorithm is proposed to guarantee the fairness among cognitive small-cell base stations, which defines the satisfaction degree and the traffic requirement indicators to dynamically adjust the resource allocation process. Finally, considering the time-varying traffic load and different geographical environments, an improved FDRA (IFDRA) algorithm is proposed to further improve the throughput of the hot area. The simulation results demonstrate that the proposed FDRA algorithm and IFDRA algorithm could achieve a considerable performance improvement compared with schemes in the literature while providing better fairness among cognitive small-cell base stations.