Unified Stochastic Geometry Modeling and Analysis of Cellular Networks in LOS/NLOS and Shadowed Fading

Abstract

Statistical characterization of the signal-to-interference-plus-noise ratio (SINR) via its cumulative distri- bution function 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 paper, to capture diverse fading channels that arise in realistic outdoor/indoor wireless communication scenarios, we tackle the problem differently. By exploiting the moment generating function of the SINR, we succeed in analytically assessing cellular networks performance over the shadowed $\kappa$ – $\mu$ , $\kappa$ – $\mu$ , and $\eta$ – $\mu$ fading models. These channel models offer high flexibility by capturing diverse fading channels, including Rayleigh, Nakagami- $m$ , Rician, and Rician shadow fading distributions. These channel models have been recently promoted for their capability to accurately model dense urban environments, future femtocells, and device-to-device shadowed channels. In addition to unifying the analysis for different channel models, this paper integrates the coverage, the achievable rate, and the bit error probability, which are largely treated separately in the literature. The developed model and analysis are validated over a broad range of simulation setups and parameters.