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Random transceiver networks

Part of: Equilibrium statistical mechanics Special processes

Published online by Cambridge University Press:  01 July 2016

Paul Balister ,
Béla Bollobás  and
Mark Walters
Paul Balister*
Affiliation:
University of Memphis
Béla Bollobás*
Affiliation:
University of Memphis
Mark Walters*
Affiliation:
University of Cambridge
*
∗ Postal address: University of Memphis, Department of Mathematics, Dunn Hall, 3725 Noriswood, Memphis, TN 38152, USA.
∗∗ Current address: Department of Pure Mathematics and Mathematical Statistics, University of Cambridge, Cambridge, CB3 0WB, UK.
∗∗∗ Current address: School of Mathematical Sciences, Queen Mary, University of London, Mile End Road, London E1 4NS, UK. Email address: m.walters@qmul.ac.uk
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Abstract

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Consider randomly scattered radio transceivers in ℝd, each of which can transmit signals to all transceivers in a given randomly chosen region about itself. If a signal is retransmitted by every transceiver that receives it, under what circumstances will a signal propagate to a large distance from its starting point? Put more formally, place points {xi} in ℝd according to a Poisson process with intensity 1. Then, independently for each xi, choose a bounded region Axi from some fixed distribution and let be the random directed graph with vertex set whenever xj ∈ xi + Axi. We show that, for any will almost surely have an infinite directed path, provided the expected number of transceivers that can receive a signal directly from xi is at least 1 + η, and the regions xi + Axi do not overlap too much (in a sense that we shall make precise). One example where these conditions hold, and so gives rise to percolation, is in ℝd, with each Axi a ball of volume 1 + η centred at xi, where η → 0 as d → ∞. Another example is in two dimensions, where the Axi are sectors of angle ε γ and area 1 + η, uniformly randomly oriented within a fixed angle (1 + ε)θ. In this case we can let η → 0 as ε → 0 and still obtain percolation. The result is already known for the annulus, i.e. that the critical area tends to 1 as the ratio of the radii tends to 1, while it is known to be false for the square (l∞) annulus. Our results show that it does however hold for the randomly oriented square annulus.

Keywords

Random networkrandom geometric graphpercolation

MSC classification

Primary: 60K35: Interacting random processes; statistical mechanics type models; percolation theory
Secondary: 82B43: Percolation
Type
Stochastic Geometry and Statistical Applications
Information
Advances in Applied Probability , Volume 41 , Issue 2 , June 2009 , pp. 323 - 343
Copyright
Copyright © Applied Probability Trust 2009 

Footnotes

Research supported by NSF grant EIA-0130352.

Research supported in part by NSF grants DMS-0505550, CNS-0721983, CCF-0728928, and EIA-0130352, and an ARO grant W911NF-06-1-0076.

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