User Association and Interference Management in Massive MIMO HetNets

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 small cells. A key advantage of massive MIMO is that the instantaneous rates do not depend on small scale fading, and can be predicted a priori. This allows us to develop a unified network utility maximization (NUM) problem for JT and blanking, which optimizes resource allocations to improve the rate of cell-edge users. 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 the 10th percentile users vs. an optimal association without interference management.