# A Primer on Cellular Network Analysis Using Stochastic Geometry

arXiv: https://arxiv.org/abs/1604.03183 · HTML: https://mlsanity.com/paper/1604.03183/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Apr 2016.

## Built on by (most cited first, 1 of 1)

- [Wireless-Enabled Asynchronous Federated Fourier Neural Network for Turbulence Prediction in Urban Air Mobility (UAM)](https://mlsanity.com/paper/2201.00626/) (2021)

## Abstract (arXiv)

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 λ, 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 λi and transmit power pi. These three baseline results have been extensively extended to many different scenarios, and we conclude with a brief summary of some of those extensions.