A natural way to capture the inevitable uncertainty and heterogeneity in the
current cellular networks is by using random spatial models. In this research,
we use random spatial models to develop a comprehensive downlink model for
heterogeneous cellular networks, where the base stations across tiers may
differ
in terms of transmit power, deployment density, supported data rate, number of
transmit antennas, transmission technique and the number of users served.
Using
tools from stochastic geometry, we derive simple closed form expressions for
coverage and average downlink rate. Besides other key design guidelines, our
analysis provides a simple way to compare different transmission techniques
and
shows that deploying small cells always improve coverage.