Estimating the Transmission Probability in Wireless Networks with Configuration Models

Authors
Bermolen, P.; Jonckheere, Matthieu Thimothy Samson; Larroca, F.; Moyal, P.
Publication Year
2016
Language
English
Format
article
Status
Published version
Description
We propose a new methodology to estimate the probability of successful transmissions for random access scheduling in wireless networks, in particular those using Carrier Sense Multiple Access (CSMA). Instead of focusing on spatial configurations of users, we model the interference between users as a random graph. Using configuration models for random graphs, we show how the properties of the medium access mechanism are captured by some deterministic differential equations when the size of the graph gets large. Performance indicators such as the probability of connection of a given node can then be efficiently computed from these equations. We also perform simulations to illustrate the results on different types of random graphs. Even on spatial structures, these estimates get very accurate as soon as the variance of the interference is not negligible.
Fil: Bermolen, P.. Universidad de la Republica. Facultad de Ingeniería; Uruguay
Fil: Jonckheere, Matthieu Thimothy Samson. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigaciones Matemáticas "Luis A. Santaló". Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Matemáticas "Luis A. Santaló"; Argentina
Fil: Larroca, F.. Universidad de la Republica. Facultad de Ingeniería; Uruguay
Fil: Moyal, P.. Universite de Technologie de Compiegne; Francia
Subject
Random graphs
Wireless networks
Probability of connection
Estadística y Probabilidad
Matemáticas
CIENCIAS NATURALES Y EXACTAS
Access level
Restricted access
License
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repository
CONICET Digital (CONICET)
Institution
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identifier
oai:ri.conicet.gov.ar:11336/18996