A Stochastic Geometry Approach to Analyzing Cellular Networks with Semi-Static Clustering

Static base-station clustering allows clustered transmitters to jointly serve a group of users and thus eliminate the intra-cluster interference. The network performance is then bottlenecked by the cluster-edge users. Semi-static clustering can help improve the performance along the cluster edges by time-sharing between different clustering patterns. We propose a simple clustering and user scheduling algorithm to gauge the performance gain of semi-static clustering. Under a stochastic geometry framework, we derive analytical expressions for the coverage and rate of a user at a given location. As the cluster size goes to infinity, we show that the outage probability of semi-static clustering decays at the same order as that of static clustering. Thus, in the asymptotic regime, the performance gain provided by semi- static clustering can be characterized by a linear factor. Numerical results demonstrate the gain of semi-static clustering in the non-asymptotic regime.