Resource Allocation scheme for Multi - hop D2D communication in 5G Networks

Abstract

Multi-hop D2D communications increases proximity and an efficient capacity scaling technique for 5G networks. In this letter, we proposed a novel resource allocation scheme for multi-hop D2D communication for 5G networks. This scheme comprises in three phases: in first phase, a Q learning mechanism is used for finding the best routing path between multi-hop D2D communication. In second phase, mean-max distance (MMF) resource allocation scheme is proposed for best routing path. In the last phase, we proposed a hybrid optimization technique by using particle swarm optimization (PSO) and grey wolf optimization (GWO) technique (HPSOGWO). The analysis framework and the results guarantee that the proposed schemes improve the system throughput.