Coverage Analysis of Cloud Radio Networks With Finite Clustering

Abstract

Cloud radio networks coordinate transmission among base stations (BSs) to reduce the interference effects, particularly for the cell-edge users. In this paper, we analyze the performance of a cloud network with static clustering where geographically close BSs form a cloud network of cooperating BSs. Due to finite cooperation, the interference in a practical cloud radio cannot be removed, and in this paper, the distance-based interference is taken into account in the analysis. In particular, we consider centralized zero forcing equalizer and dirty paper precoding for canceling the interference. Bounds are developed on the signal-to-interference ratio distribution and achievable rate with full and limited channel feedback from the cluster users. The adverse effect of finite clusters on the achievable rate is quantified. We show that the number of cooperating BSs is more crucial than the cluster area when full channel state information from the cluster is available for precoding. Also, we study the impact of limiting the channel state information on the achievable rate. We show that even with a practically feasible feedback of about five to six channel states from each user, significant gain in mean rate and cell edge rate compared with conventional cellular systems can be obtained.