Modeling and analysis of ergodic capacity in network MIMO systems

Abstract

This paper studies the downlink ergodic capacity of a network multiple-input multiple-output (MIMO) system. The system model includes base-stations (BSs) randomly distributed with a fixed density, each equipped with M antennas, scheduling K single-antenna users, and forming cooperating clusters via perfect backhaul links. Intra-cluster interference is eliminated by joint transmission using zero-forcing beamforming assuming perfect channel state information (CSI), while inter-cluster interference remains. This paper shows that although coordinating a large cluster of BSs eliminates strong interferers, the coordination gain depends on the network load factor, defined as the relative ratio of M and K. In particular, we show that with M = K, increasing the coordination cluster size is only beneficial for the cluster-edge users, while degrading the ergodic capacity of the users located close to the cluster center. In contrast, when M > K, increasing the cluster size potentially improves every user's ergodic capacity. In the second part of this paper, we use tools from stochastic geometry to account for random BS locations in characterizing the performance of network MIMO systems. In this setting, we model the BS locations according to a homogeneous Poisson point process with a fixed density, and propose tractable, yet accurate, distribution functions for the signal and inter-cluster interference powers. We then derive an efficiently computable expression for the user ergodic capacity as a function of the distance between a user and the cluster center.