  Keeler, Ross and Xia (2016) recently derived approximation and convergence
results, which imply that the point process formed from the signal strengths
received by an observer in a wireless network under a general statistical
propagation model can be modelled by an inhomogeneous Poisson point process on
the positive real line. The basic requirement for the results to apply is that
there must be a large number of transmitters with different locations and
random propagation effects.The aim of this note is to apply some of the main
results of Keeler, Ross and Xia (2016) in a less general but more easily
applicable form to illustrate how the results can be applied in practice. New
results are derived that show that it is the strongest signals, after being
weakened by random propagation effects, that behave like a Poisson process,
which supports recent experimental work.
