  This paper develops a stochastic geometry-based approach for the modeling and
analysis of single- and multi-cluster wireless networks. We first define finite
homogeneous Poisson point processes to model the number and locations of the
transmitters in a confined region as a single-cluster wireless network. We
study the coverage probability for a reference receiver for two strategies;
closest-selection, where the receiver is served by the closest transmitter
among all transmitters, and uniform-selection, where the serving transmitter is
selected randomly with uniform distribution. Second, using Matern cluster
processes, we extend our model and analysis to multi-cluster wireless networks.
Here, the receivers are modeled in two types, namely, closed- and open-access.
Closed-access receivers are distributed around the cluster centers of the
transmitters according to a symmetric normal distribution and can be served
only by the transmitters of their corresponding clusters. Open-access
receivers, on the other hand, are placed independently of the transmitters and
can be served by all transmitters. In all cases, the link distance distribution
and the Laplace transform (LT) of the interference are derived. We also derive
closed-form lower bounds on the LT of the interference for single-cluster
wireless networks. The impact of different parameters on the performance is
also investigated.
