User Association and Interference Management in Massive MIMO HetNets

TL;DR

This paper investigates how massive MIMO can enhance user association and interference management in 5G HetNets, proposing joint transmission and resource blanking strategies to significantly improve cell-edge user rates.

Contribution

It introduces a unified framework leveraging massive MIMO channel hardening for joint optimization of user association and interference management in HetNets.

Findings

Over 2x rate improvement for 10th percentile users

Effective dual subgradient algorithm for network utility maximization

Significant gains with interference mitigation strategies

Abstract

Two key traits of 5G cellular networks are much higher base station (BS) densities - especially in the case of low-power BSs - and the use of massive MIMO at these BSs. This paper explores how massive MIMO can be used to jointly maximize the offloading gains and minimize the interference challenges arising from adding small cells. We consider two interference management approaches: joint transmission (JT) with local precoding, where users are served simultaneously by multiple BSs without requiring channel state information exchanges among cooperating BSs, and resource blanking, where some macro BS resources are left blank to reduce the interference in the small cell downlink. A key advantage offered by massive MIMO is channel hardening, which enables to predict instantaneous rates a priori. This allows us to develop a unified framework, where resource allocation is cast as a network utility maximization (NUM) problem, and to demonstrate large gains in cell-edge rates based on the NUM solution. We propose an efficient dual subgradient based algorithm, which converges towards the NUM solution. A scheduling scheme is also proposed to approach the NUM solution. Simulations illustrate more than 2x rate gain for 10th percentile users vs. an optimal association without interference management.