Modeling the Spatial Distributions of Macro Base Stations with Homogeneous Density: Theory and Application to Real Networks

Abstract

Stochastic geometry is a highly studied field in telecommunications as in many other scientific fields. In the last ten years in particular, theoretical knowledge has evolved a lot, whether for the calculation of metrics to characterize interference, coverage, energy or spectral efficiency, or exposure to electromagnetic fields. Many spatial point process models have been developed but are often left aside because of their unfamiliarity, their lack of tractability in favor of the Poisson point process or the regular lattice, easier to use. This article is intended to be a short guide presenting a complete and simple methodology to follow to infer a real stationary macro antenna network using tractable spatial models. The focus is mainly on repulsive point processes and in particular on determinantal point processes which are among the most tractable repulsive point processes. This methodology is applied on Belgian and French cell towers. The results show that for all stationary distributions in France and Belgium, the best inference model is the $\beta$-Ginibre point process.