A Stochastic Geometry Framework for LOS/NLOS Propagation in Dense Small Cell Networks

TL;DR

This paper introduces a stochastic geometry framework for dense small cell networks that incorporates LOS/NLOS propagation models, revealing that while dense deployments can improve spectral efficiency, they also increase outage probability.

Contribution

It develops a novel stochastic geometry model accounting for LOS/NLOS effects, providing more accurate performance analysis of dense small cell networks.

Findings

Dense networks achieve significant ASE gains with LOS/NLOS models.

LOS/NLOS propagation increases outage probability in dense networks.

Performance metrics depend on base station density and LOS likelihood.

Abstract

The need to carry out analytical studies of wireless systems often motivates the usage of simplified models which, despite their tractability, can easily lead to an overestimation of the achievable performance. In the case of dense small cells networks, the standard single slope path-loss model has been shown to provide interesting, but supposedly too optimistic, properties such as the invariance of the outage/coverage probability and of the spectral efficiency to the base station density. This paper seeks to explore the performance of dense small cells networks when a more accurate path-loss model is taken into account. We first propose a stochastic geometry based framework for small cell networks where the signal propagation accounts for both the Line-of-Sight (LOS) and Non-Line-Of-Sight (NLOS) components, such as the model provided by the 3GPP for evaluation of pico-cells in Heterogeneous Networks. We then study the performance of these networks and we show the dependency of some metrics such as the outage/coverage probability, the spectral efficiency and Area Spectral Efficiency (ASE) on the base station density and on the LOS likelihood of the propagation environment. Specifically, we show that, with LOS/NLOS propagation, dense networks still achieve large ASE gain but, at the same time, suffer from high outage probability.