A case study on regularity in cellular network deployment

This paper aims to validate the \(\beta\)-Ginibre point process as a model for the distribution of base station locations in a cellular network. The \(\beta\)-Ginibre is a repulsive point process in which repulsion is controlled by the \(\beta\) parameter. When \(\beta\) tends to zero, the point process converges in law towards a Poisson point process. If \(\beta\) equals to one it becomes a Ginibre point process. Simulations on real data collected in Paris (France) show that base station locations can be fitted with a \(\beta\)-Ginibre point process. Moreover we prove that their superposition tends to a Poisson point process as it can be seen from real data. Qualitative interpretations on deployment strategies are derived from the model fitting of the raw data.