  Despite coverage enhancement in rural areas is one of the main requirements
in next generations of wireless networks (i.e., 5G and 6G), the low expected
profit prevents telecommunication providers from investing in such sparsely
populated areas. Hence, it is required to design and deploy cost efficient
alternatives for extending the cellular infrastructure to these regions. A
concrete mathematical model that characterizes and clearly captures the
aforementioned problem might be a key-enabler for studying the efficiency of
any potential solution. Unfortunately, the commonly used mathematical tools
that model large scale wireless networks are not designed to capture the
unfairness, in terms of cellular coverage, suffered by exurban and rural areas.
In big cities, in fact, cellular deployment is essentially capacity driven and
thus cellular base station densities are maximum in the town centers and
decline when getting far from them. In this paper, a new stochastic
geometry-based model is implemented in order to show the coverage spatial
variation among urban, suburban, and exurban settlements. Indeed, by
implementing inhomogeneous Poisson point processes (PPPs) it is possible to
study the performance metrics in a realistic scenario where terrestrial base
stations (TBSs) are clustered around the urban center while outer aerial base
stations (ABSs) are uniformly distributed outside an urban exclusion zone.
Based on this, our simulation results can quantify the improvement, in terms of
coverage probability, that even a surprisingly low density of ABSs can bring to
peripheral regions depending on the extension of the exclusion zone, enabling
us to draw insightful considerations.
