Unified stochastic geometry analysis of downlink cellular networks

摘要

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, namely the achievable rate and and the bit error probability (BEP), over the shadowed κ-μ, κ-μ and η-μ fading models. These models offer higher flexibility to capture diverse and more realistic fading environments than the classical Rayleigh, Nakagami-m, and Rician ones.