Zeroing Unknown Terms: A Novel Clustering Architecture for Low Network Overhead in Distributed Massive MIMO

Abstract

We propose a novel user-centric clustering architecture for distributed massive multiple-input-multiple-output networks. We examine the uplink of a general multi-cell scenario in which a cluster of base stations (BSs) with large antenna arrays detect the signals of multiple users simultaneously. As opposed to traditional clustering schemes, where the channel coefficients of all the users within the cooperating cluster are learned at the BSs, in the proposed approach, BSs in the network learn the channels of only the strongest users based on the received signal-to-noise ratio. We consider two linear receivers, namely, zero forcing and linear minimum mean squared error receivers at the central..