Large Deviations, Sharron-McMillan-Breiman Theorem for Super-Critical Telecommunication Networks
E. Sakyi-Yeboah, P. S. Andam, L. Asiedu, K. Doku-Amponsah

TL;DR
This paper establishes large deviation principles and asymptotic properties for supercritical SINR telecommunication networks modeled via Poisson point processes, providing new insights into network connectivity and stochastic behavior.
Contribution
It introduces joint large deviation principles for empirical measures in SINR networks and proves an asymptotic equipartition property and a local large deviation principle.
Findings
Derived joint LDPs for empirical power and connectivity measures.
Proved an asymptotic equipartition property for SINR networks.
Established a local large deviation principle and a classical MacMillian theorem for network processes.
Abstract
In this article we obtain large deviation asymptotics for supercritical communication networks modelled as signal-interference-noise ratio networks. To do this, we define the empirical power measure and the empirical connectivity measure, and prove joint large deviation principles(LDPs) for the two empirical measures on two different scales i.e. and where is the intensity measure of the poisson point process (PPP) which defines the SINR random network.Using this joint LDPs we prove an asymptotic equipartition property for the stochastic telecommunication Networks modelled as the SINR networks. Further, we prove a Local large deviation principle(LLDP) for the SINR Network. From the LLDP we prove the a large deviation principle, and a classical MacMillian Theorem for the stochastic SNIR network processes. Note, for tupical empirical…
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Taxonomy
TopicsStochastic processes and statistical mechanics · Complex Network Analysis Techniques · Topological and Geometric Data Analysis
