  Statistical characterization of the signal-to-interference-plus-noise ratio
(SINR) via its cumulative distribution function (CDF) is ubiquitous in a vast
majority of technical contributions in the area of cellular networks since it
boils down to averaging the Laplace transform of the aggregate interference, a
benefit accorded at the expense of confinement to the simplistic Rayleigh
fading. In this work, to capture diverse fading channels that appear in
realistic outdoor/indoor wireless communication scenarios, we tackle the
problem differently. By exploting the moment generating function (MGF) of the
SINR, we succeed in analytically assessing cellular networks performance over
the shadowed {\kappa}-{\mu}, {\kappa}-{\mu} and {\eta}-{\mu} fading models. The
latter offer high flexibility by capturing diverse fading channels including
Rayleigh, Nakagami-m, Rician, and Rician shadow fading distributions. These
channel models have been recently praised for their capability to accurately
model dense urban environments, future femtocells and device-to-device (D2D)
shadowed channels. In addition to unifying the analysis for different channel
models, this work integrates, for the first time, the coverage, the achievable
rate, and the bit error probability (BEP), which are largely treated separately
in the literature. The developed model and analysis are validated over a broad
range of simulation setups and parameters.
