  Recently, spatial stochastic models based on determinantal point processes
(DPP) are studied as promising models for analysis of cellular wireless
networks. Indeed, the DPPs can express the repulsive nature of the macro base
station (BS) configuration observed in a real cellular network and have many
desirable mathematical properties to analyze the network performance. However,
almost all the prior works on the DPP based models assume the Rayleigh fading
while the spatial models based on Poisson point processes have been developed
to allow arbitrary distributions of fading/shadowing propagation effects. In
order for the DPP based model to be more promising, it is essential to extend
it to allow non-Rayleigh propagation effects. In the present paper, we propose
the downlink cellular network model where the BSs are deployed according to the
Ginibre point process, which is one of the main examples of the DPPs, over
Nakagami-m fading. For the proposed model, we derive a numerically computable
form of the coverage probability and reveal some properties of it numerically
and theoretically.
