GA based optimal resource allocation and user matching in device to device underlaying network

Abstract

Device-to-Device (D2D) communication is expected to play a pivotal role in the next generation of LET/LTE-A network, which is able to improve the system throughput by reusing the cellular resource. However, the caused intra-cell interference is quite a challenging issue in D2D underlaying cellular network. In this paper, we propose a Genetic Algorithm (GA) based joint resource allocation and user matching scheme (GAAM) to minimize the intra-cell interference while maximize the system throughput. With the proposed scheme, we firstly analyze and formulate the user matching scheme in mathematical model, during which resources are allocated to cellular user equipments (CUE) and further be shared by D2D UEs (DUE) in a coordinated manner. Secondly, GA is used to globally search the optimal user matching solution to maximize the system throughput. Furthermore, with some innovations, the more efficient GAAM can be applied to a much wider scope in D2D underlying network. Simulation results show that GAAM achieves nearly the same system throughput comparing to the exhaustive method, which is 30 Mbps bigger than the traditional greedy algorithm based allocation and matching scheme (GreedyAM).