In recent years, Inter Vehicle Communication (IVC) has become an intensive research area, as part of Intelligent Transportation Systems. It supposes that all, or a subset of the vehicles is equipped with radio devices, enabling communication between them. IEEE 802.11p (standardized for vehicular communication) shows a great deal of promise. By using ad hoc mode, this radio technology allows vehicles to extend their scopes of communication and thus forming a Multi-hop wireless Ad-hoc NETwork, also called Vehicular Ad-hoc NETwork (VANET). This thesis addresses a fundamental problem of VANET: the network capacity. Two simple theoretical models to estimate this capacity have been proposed: a packing model and a Markovian point process model. They offer simple and closed formulae on the maximum number of simultaneous transmitters, and on the distribution of the distance between them. An accurate upper bound on the maximum capacity had been derived. An analytical formula on distribution of the transmitters had been presented. This distribution allows us to optimize Clear Channel Assessment (CCA) parameters that leads to an optimization of the network capacity.In order to validate the approach of this thesis, results from the analytical models are compared to simulations performed with the network simulator NS-3. Simulation parameters was estimated from real experimentation. Impact of different traffic distributions (traffic of vehicles) on the network capacity is also studied. This thesis also focuses on extended perception map applications, which use information from local and distant sensors to offer driving assistance (autonomous driving, collision warning, etc.). Extended perception requires a high bandwidth that might not be available in practice in classical IEEE 802.11p ad hoc networks. Therefore, this thesis proposes an adaptive power control algorithm optimized for this particular application. It shows through an analytical model and a large set of simulations that the network capacity is then significantly increased.
Identifer | oai:union.ndltd.org:CCSD/oai:tel.archives-ouvertes.fr:tel-00989836 |
Date | 18 April 2014 |
Creators | Giang, Anh Tuan |
Publisher | Université Paris Sud - Paris XI |
Source Sets | CCSD theses-EN-ligne, France |
Language | English |
Detected Language | English |
Type | PhD thesis |
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