Combinatorial resource allocation in D2D assisted heterogeneous relay networks

Abstract

Exponential increase in wireless capacity demands innovative network designs. Heterogeneous networks (HetNets) have been considered as a promising solution to ever increasing wireless capacity demand and efficient spectrum utilization. However severe interference scenarios exist in HetNets which hinder overall network performance. It is necessary to find optimal resource allocation strategies which can maximize capacity by mitigating interference to harvest the benefits of HetNets. This article formulates the problem of capacity maximization in device-to-device (D2D) assisted heterogeneous relay networks, using mixed integer nonlinear programming (MINLP). MINLP problems are NP-hard in general. Exhaustive search cannot be applied as search space of problem increases exponentially with number of users. Outer approximation algorithm (OAA) is proposed to solve capacity maximization problem. Proposed algorithm is evaluated by extensive simulation work which show that proposed approach is effective in terms of major key performance indicators (KPIs). KPIs considered for algorithm evaluation include user throughput (sum rate) and capacity in terms of number of users accommodated.