Factor Graph-based Message Passing Technique for Distributed Resource Allocation in 5G Networks

Abstract

Next generation 5G cellular networks are intended to provide higher data rates, excellent user coverage, low latency, and low power consumption. Since 5G is expected to have a multitier architecture consisting of macro cells, small cells and Device-to-Device communication altogether but the reported works so far have considered either one of these but not all in resource allocation (RA) in heterogeneous interference model. Moreover, heterogeneous systems using centralized schemes are not scalable with respect to different constraints including interference. We propose a distributed scheme for RA in Orthogonal Frequency Division Multiple Access (OFDMA) based multi-tier cellular network for maximizing the user’s data rate by keeping all kinds of interference constraints into mind. The formulated problem is an NP-hard non-convex non-linear optimization problem. The proposed algorithm solves RA problem through a distributed message passing approach which uses factor graph to model the decision making nodes. We prove the convergence of the proposed algorithm and analyze its time complexity. Through simulation experiments, we show the effect of the different parameter on RA and compared it with the existing work.