Stochastic geometry and random graphs for the analysis and design of wireless networks
Abstract
Wireless networks are fundamentally limited by the intensity of the received signals and by their interference. Since both of these quantities depend on the spatial location of the nodes, mathematical techniques have been developed in the last decade to provide communication-theoretic results accounting for the networks geometrical configuration. Often, the location of the nodes in the network can be modeled as random, following for example a Poisson point process. In this case, different techniques based on stochastic geometry and the theory of random geometric graphs -including point process theory, percolation theory, and probabilistic combinatorics-have led to results on the connectivity, the capacity, the outage probability, and other fundamental limits of wireless networks. This tutorial article surveys some of these techniques, discusses their application to model wireless networks, and presents some of the main results that have appeared in the literature. It also serves as an introduction to the field for the other papers in this special issue.
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Breakthroughs in mathematics often result in a new research boom in wireless communications, as exemplified by stochastic geometry and graph theory applied for wireless network modelling.
“The breakthrough in mathematics would often result in a new research boom in wireless communications, and one example is the stochastic geometry and graph theory applied for wireless network modelling [55].”
From What should 6G be? (2020) · cites this paper as [55]
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- Authors
- Haenggi, M., Andrews, J. G., Baccelli, F., Dousse, O., & Franceschetti, M.
- Affiliations
- University of Notre Dame (US)
- The University of Texas at Austin (US)
- Institut national de recherche en sciences et technologies du numérique (FR)
- Nokia (Finland) (FI)
- University of California San Diego (US)
- Venue
- IEEE Journal on Selected Areas in Communications
- Published
- 2009-09
- Volume
- 27
- Issue
- 7
- Pages
- 1029-1046
- ISSN
- 0733-8716 (ISSN-L)
- OpenAlex
- W2145873277
- Cited by
- 1,719
- References
- 142
- Citations by year
- 2026: 22 · 2025: 36 · 2024: 34 · 2023: 46 · 2022: 51 · 2021: 76 · 2020: 103 · 2019: 121 · 2018: 140 · 2017: 178 · 2016: 162 · 2015: 171 · 2014: 170 · 2013: 157 · 2012: 123
- FWCI
- 127.90
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Journal on Selected Areas in Communications (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Applied Mathematics › Point processes and geometric inequalities
- Physical Sciences › Computer Science › Computer Networks and Communications › Mobile Ad Hoc Networks
- Physical Sciences › Computer Science › Computer Networks and Communications › Wireless Communication Networks Research
- Keywords
- wireless networks, stochastic geometry, random geometric graphs, Poisson point process, percolation theory, network connectivity, channel capacity, outage probability, interference, probabilistic combinatorics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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