Spatial modeling and analysis of cellular networks using the Ginibre point process: A tutorial

TL;DR

This tutorial introduces the Ginibre point process as a novel spatial model for cellular network base station deployment, highlighting its advantages over traditional Poisson models and demonstrating its application in performance analysis.

Contribution

It provides a comprehensive guide to the Ginibre point process and its variant, demonstrating their use in modeling base station deployments and analyzing cellular network performance.

Findings

Ginibre point process captures repulsive spatial configurations of base stations.

Analytical results show improved modeling accuracy over Poisson processes.

Simulation methods for Ginibre point process are efficient and practical.

Abstract

Spatial stochastic models have been much used for performance analysis of wireless communication networks. This is due to the fact that the performance of wireless networks depends on the spatial configuration of wireless nodes and the irregularity of node locations in a real wireless network can be captured by a spatial point process. Most works on such spatial stochastic models of wireless networks have adopted homogeneous Poisson point processes as the models of wireless node locations. While this adoption makes the models analytically tractable, it assumes that the wireless nodes are located independently of each other and their spatial correlation is ignored. Recently, the authors have proposed to adopt the Ginibre point process---one of the determinantal point processes---as the deployment models of base stations (BSs) in cellular networks. The determinantal point processes constitute a class of repulsive point processes and have been attracting attention due to their mathematically interesting properties and efficient simulation methods. In this tutorial, we provide a brief guide to the Ginibre point process and its variant, $\alpha$-Ginibre point process, as the models of BS deployments in cellular networks and show some existing results on the performance analysis of cellular network models with $\alpha$-Ginibre deployed BSs. The authors hope the readers to use such point processes as a tool for analyzing various problems arising in future cellular networks.