User Association in Massive MIMO HetNets

TL;DR

This paper explores optimal and distributed user association strategies in a 5G heterogeneous network combining massive MIMO macro cells and small cells, improving network efficiency and fairness.

Contribution

It introduces centralized and distributed algorithms for user association in massive MIMO HetNets, with proven optimality and convergence, respectively.

Findings

Optimal algorithms outperform greedy methods in simulations.

Distributed algorithms converge to Nash Equilibrium.

Enhanced network performance with proposed schemes.

Abstract

Massive MIMO and small cell are both recognized as the key technologies for the future 5G wireless systems. In this paper, we investigate the problem of user association in a heterogeneous network (HetNet) with massive MIMO and small cells, where the macro base station (BS) is equipped with a massive MIMO and the picocell BS's are equipped with regular MIMOs. We first develop centralized user association algorithms with proven optimality, considering various objectives such as rate maximization, proportional fairness, and joint user association and resource allocation. We then model the massive MIMO HetNet as a repeated game, which leads to distributed user association algorithms with proven convergence to the Nash Equilibrium (NE). We demonstrate the efficacy of these optimal schemes by comparison with several greedy algorithms through simulations.