A Variable Neighborhood Search Algorithm for Massive MIMO Resource Allocation

Abstract

In this paper, we consider the problem of maximizing capacity for a Massive Multiple Input Multiple Output (MIMO) system subject to power and antenna assignment constraints. Massive MIMO technology has gained increased attention by the research community within last decade as it has become a strong candidate for 5G wireless communications. Some advantages of this new technology include better performance in terms of data rate and link reliability, transmitting in higher frequency bands which improves coverage, strong signal indoors, and the possibility of more resistant systems to intentional jamming attacks, to name a few. The optimization problem is formulated as a mixed integer nonlinear programming problem for which exact methods cannot be applied efficiently. Consequently, we propose a variable neighborhood search (VNS for short) meta-heuristic algorithm which allows to obtain significantly better solutions compared to a state of the art algorithm. Although, at a higher computational cost for most tested instances.