A Primer on Cellular Network Analysis Using Stochastic Geometry

April 12, 2016 Β· Declared Dead Β· πŸ› arXiv.org

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Authors Jeffrey G. Andrews, Abhishek K. Gupta, Harpreet S. Dhillon arXiv ID 1604.03183 Category cs.IT: Information Theory Cross-listed cs.NI Citations 305 Venue arXiv.org Last Checked 3 months ago
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 $Ξ»$, 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 $Ξ»_i$ 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.
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