Degeneracy estimation in interference models on wireless networks

Neal McBride, John Bulava, Carlo Galiotto, Nicola Marchetti, Irene Macaluso and Linda Doyle

Physica A: Statistical Mechanics and its Applications, 2017, vol. 469, issue C, 540-550

Abstract: We present a Monte Carlo study of interference in real-world wireless networks using the Potts model. Our approach maps the Potts energy to discrete interference levels. These levels depend on the configurations of radio frequency allocation in the network. For the first time, we estimate the degeneracy of these interference levels using the Wang–Landau algorithm. The cumulative distribution function of the resulting density of states is found to increase rapidly at a critical interference value. We compare these critical values for several different real-world interference networks and Potts models. Our results show that models with a greater number of available frequency channels and less dense interference networks result in the majority of configurations having lower interference levels. Consequently, their critical interference levels occur at lower values. Furthermore, the area under the density of states increases and shifts to lower interference values. Therefore, the probability of randomly sampling low interference configurations is higher under these conditions. This result can be used to consider dynamic and distributed spectrum allocation in future wireless networks.

Keywords: Potts model; Wang–Landau algorithm; Degeneracy; Interference modelling; Distributed spectrum allocation; Future wireless networks operation and design (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:469:y:2017:i:c:p:540-550

DOI: 10.1016/j.physa.2016.11.065

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