A Primer on Cellular Network Analysis Using Stochastic Geometry

TL;DR

This tutorial introduces stochastic geometry methods for modeling and analyzing cellular network performance, focusing on SINR distribution and coverage probability across various network configurations.

Contribution

It provides a rigorous, accessible foundation for modeling cellular networks using Poisson point processes and derives key SINR distribution results for multiple network scenarios.

Findings

Derived SINR distribution for downlink, uplink, and multi-tier networks.

Established coverage and outage probability formulas.

Extended baseline models to various network configurations.

Abstract

This tutorial is intended as an accessible but rigorous first reference for someone interested in learning how to model and analyze cellular network performance using stochastic geometry. In particular, we focus on computing the signal-to-interference-plus-noise ratio (SINR) distribution, which can be characterized by the coverage probability (the SINR CCDF) or the outage probability (its CDF). We model base stations (BSs) in the network as a realization of a homogeneous Poisson point process of density $\lambda$, and compute the SINR for three main cases: the downlink, uplink, and finally the multi-tier downlink, which is characterized by having $k$ tiers of BSs each with a unique density $\lambda_i$ and transmit power $p_i$. These three baseline results have been extensively extended to many different scenarios, and we conclude with a brief summary of some of those extensions.