Multi-hop connectivity probability in infrastructure-based vehicular networks

Zhang, W; Chen, Y; Yang, Y; Wang, X; Zhang, Y; Hong, X; Mao, G

Multi-hop connectivity probability in infrastructure-based vehicular networks

Zhang, W Chen, Y Yang, Y Wang, X Zhang, Y Hong, X Mao, G

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Publication Type:: Journal Article
Citation:: IEEE Journal on Selected Areas in Communications, 2012, 30 (4), pp. 740 - 747
Issue Date:: 2012-05-01

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Field	Value	Language
dc.contributor.author	Zhang, W	en_US
dc.contributor.author	Chen, Y	en_US
dc.contributor.author	Yang, Y	en_US
dc.contributor.author	Wang, X	en_US
dc.contributor.author	Zhang, Y	en_US
dc.contributor.author	Hong, X	en_US
dc.contributor.author	Mao, G https://orcid.org/0000-0002-3598-4949	en_US
dc.date.issued	2012-05-01	en_US
dc.identifier.citation	IEEE Journal on Selected Areas in Communications, 2012, 30 (4), pp. 740 - 747	en_US
dc.identifier.issn	0733-8716	en_US
dc.identifier.uri	http://hdl.handle.net/10453/28432
dc.description.abstract	Infrastructure-based vehicular networks (consisting of a group of Base Stations (BSs) along the road) will be widely deployed to support Wireless Access in Vehicular Environment (WAVE) and a series of safety and non-safety related applications and services for vehicles on the road. As an important measure of user satisfaction level, uplink connectivity probability is defined as the probability that messages from vehicles can be received by the infrastructure (i.e., BSs) through multi-hop paths. While on the system side, downlink connectivity probability is defined as the probability that messages can be broadcasted from BSs to all vehicles through multi-hop paths, which indicates service coverage performance of a vehicular network. This paper proposes an analytical model to predict both uplink and downlink connectivity probabilities. Our analytical results, validated by simulations and experiments, reveal the trade-off between these two key performance metrics and the important system parameters, such as BS and vehicle densities, radio coverage (or transmission power), and maximum number of hops. This insightful knowledge enables vehicular network engineers and operators to effectively achieve high user satisfaction and good service coverage, with necessary deployment of BSs along the road according to traffic density, user requirements and service types. © 2012 IEEE.	en_US
dc.relation.ispartof	IEEE Journal on Selected Areas in Communications	en_US
dc.relation.isbasedon	10.1109/JSAC.2012.120508	en_US
dc.subject.classification	Networking & Telecommunications	en_US
dc.title	Multi-hop connectivity probability in infrastructure-based vehicular networks	en_US
dc.type	Journal Article
utslib.citation.volume	4	en_US
utslib.citation.volume	30	en_US
utslib.for	0805 Distributed Computing	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
utslib.for	1005 Communications Technologies	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CRIN - Realtime Information Networks
utslib.copyright.status	closed_access
pubs.issue	4	en_US
pubs.publication-status	Published	en_US
pubs.volume	30	en_US

Abstract:

Infrastructure-based vehicular networks (consisting of a group of Base Stations (BSs) along the road) will be widely deployed to support Wireless Access in Vehicular Environment (WAVE) and a series of safety and non-safety related applications and services for vehicles on the road. As an important measure of user satisfaction level, uplink connectivity probability is defined as the probability that messages from vehicles can be received by the infrastructure (i.e., BSs) through multi-hop paths. While on the system side, downlink connectivity probability is defined as the probability that messages can be broadcasted from BSs to all vehicles through multi-hop paths, which indicates service coverage performance of a vehicular network. This paper proposes an analytical model to predict both uplink and downlink connectivity probabilities. Our analytical results, validated by simulations and experiments, reveal the trade-off between these two key performance metrics and the important system parameters, such as BS and vehicle densities, radio coverage (or transmission power), and maximum number of hops. This insightful knowledge enables vehicular network engineers and operators to effectively achieve high user satisfaction and good service coverage, with necessary deployment of BSs along the road according to traffic density, user requirements and service types. © 2012 IEEE.

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http://hdl.handle.net/10453/28432