Affiliation:
1. Facultad de Ingeniería - Universidad de la República
2. Conicet - IMAS - Universidad de Buenos Aires
3. Laboratoire de Mathèmatiques Appliquées (LMAC) - Université de Technologie de Compiègne
Abstract
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.
Funder
Comisión Sectorial de Investigación Científica
Agencia Nacional de Investigación e Innovación
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Networks and Communications,Hardware and Architecture,Safety, Risk, Reliability and Quality,Media Technology,Information Systems,Software,Computer Science (miscellaneous)
Reference26 articles.
1. Stochastic Geometry and Wireless Networks: Volume I Theory
2. Stochastic Geometry and Wireless Networks: Volume II Applications
3. Paola Bermolen Matthieu Jonckheere and Pascal Moyal. 2013. The Jamming Constant of Random Graphs. (2013). http://arxiv.org/abs/1310.8475 Submitted. Paola Bermolen Matthieu Jonckheere and Pascal Moyal. 2013. The Jamming Constant of Random Graphs. (2013). http://arxiv.org/abs/1310.8475 Submitted.
4. Performance analysis of the IEEE 802.11 distributed coordination function
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