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SINR percolation for Cox point processes with random powers

Part of: Operations research and management science Equilibrium statistical mechanics Stochastic processes Special processes

Published online by Cambridge University Press:  23 March 2022

Benedikt Jahnel  and
András Tóbiás
Benedikt Jahnel*
Affiliation:
Weierstrass Institute for Applied Analysis and Stochastics
András Tóbiás*
Affiliation:
Technical University of Berlin
*
*Postal address: Weierstrass Institute for Applied Analysis and Stochastics, Mohrenstraße 39, 10117 Berlin, Germany. Email address: Jahnel@wias-berlin.de
**Postal address: Technical University of Berlin, Institute of Mathematics, Straße des 17. Juni 136, 10623 Berlin, Germany. Email address: Tobias@math.tu-berlin.de
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Abstract

Signal-to-interference-plus-noise ratio (SINR) percolation is an infinite-range dependent variant of continuum percolation modeling connections in a telecommunication network. Unlike in earlier works, in the present paper the transmitted signal powers of the devices of the network are assumed random, independent and identically distributed, and possibly unbounded. Additionally, we assume that the devices form a stationary Cox point process, i.e., a Poisson point process with stationary random intensity measure, in two or more dimensions. We present the following main results. First, under suitable moment conditions on the signal powers and the intensity measure, there is percolation in the SINR graph given that the device density is high and interferences are sufficiently reduced, but not vanishing. Second, if the interference cancellation factor $\gamma$ and the SINR threshold $\tau$ satisfy $\gamma \geq 1/(2\tau)$, then there is no percolation for any intensity parameter. Third, in the case of a Poisson point process with constant powers, for any intensity parameter that is supercritical for the underlying Gilbert graph, the SINR graph also percolates with some small but positive interference cancellation factor.

Keywords

Signal-to-interference ratioCox point processPoisson point processcontinuum percolationSINR percolationGilbert graphBoolean modelstabilizationrandom powerdegree bound

MSC classification

Primary: 82B43: Percolation 60G55: Point processes 60K35: Interacting random processes; statistical mechanics type models; percolation theory
Secondary: 90B18: Communication networks

Information

Type
Original Article
Information
Advances in Applied Probability , Volume 54 , Issue 1 , March 2022 , pp. 227 - 253
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Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of Applied Probability Trust

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