A statistical approach to interference reduction in distributed large-scale antenna systems

This paper considers the problem of interference control in networks where base stations signals are coherently combined (aka network MIMO). Building on an analogy with so-called massive MIMO, we show how second-order statistical properties of channels can be exploited when the massive MIMO array corresponds in fact to many antennas randomly spread over a two-dimensional network. Based on the classical one-ring model, we characterize the low-rankness of channel covariance matrices and show the rank is related to the scattering radius. The application of the low-rankness property to channel estimation's denoising and low complexity interference filtering is highlighted.