  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.
