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Link to original content: https://doi.org/10.48550/arXiv.1604.03183
[1604.03183] A Primer on Cellular Network Analysis Using Stochastic Geometry
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Computer Science > Information Theory

arXiv:1604.03183 (cs)
[Submitted on 12 Apr 2016 (v1), last revised 5 Oct 2016 (this version, v2)]

Title:A Primer on Cellular Network Analysis Using Stochastic Geometry

Authors:Jeffrey G. Andrews, Abhishek K. Gupta, Harpreet S. Dhillon
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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.
Subjects: Information Theory (cs.IT); Networking and Internet Architecture (cs.NI)
Cite as: arXiv:1604.03183 [cs.IT]
  (or arXiv:1604.03183v2 [cs.IT] for this version)
  https://doi.org/10.48550/arXiv.1604.03183

Submission history

From: Harpreet S. Dhillon [view email]
[v1] Tue, 12 Apr 2016 00:23:36 UTC (637 KB)
[v2] Wed, 5 Oct 2016 17:59:41 UTC (714 KB)
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