  We propose a new cellular network model that captures both deterministic and
random aspects of base station deployments. Namely, the base station locations
are modeled as the superposition of two independent stationary point processes:
a random shifted grid with intensity $\lambda_g$ and a Poisson point process
(PPP) with intensity $\lambda_p$. Grid and PPP deployments are special cases
with $\lambda_p \to 0$ and $\lambda_g \to 0$, with actual deployments in
between these two extremes, as we demonstrate with deployment data. Assuming
that each user is associated with the base station that provides the strongest
average received signal power, we obtain the probability that a typical user is
associated with either a grid or PPP base station. Assuming Rayleigh fading
channels, we derive the expression for the coverage probability of the typical
user, resulting in the following observations. First, the association and the
coverage probability of the typical user are fully characterized as functions
of intensity ratio $\rho_\lambda = \lambda_p/\lambda_g$. Second, the user
association is biased towards the base stations located on a grid. Finally, the
proposed model predicts the coverage probability of the actual deployment with
great accuracy.
