Capacity of Infrastructure-Based Cooperative Vehicular Networks

Chen, J; Mao, G; Li, C

Capacity of Infrastructure-Based Cooperative Vehicular Networks

Chen, J

Mao, G

Li, C

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Publication Type:: Conference Proceeding
Citation:: 2017 IEEE Global Communications Conference, GLOBECOM 2017 - Proceedings, 2017, 2018-January pp. 1 - 6
Issue Date:: 2017-07-01

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Field	Value	Language
dc.contributor.author	Chen, J https://orcid.org/0000-0003-3072-1872	en_US
dc.contributor.author	Mao, G https://orcid.org/0000-0002-3598-4949	en_US
dc.contributor.author	Li, C	en_US
dc.date.issued	2017-07-01	en_US
dc.identifier.citation	2017 IEEE Global Communications Conference, GLOBECOM 2017 - Proceedings, 2017, 2018-January pp. 1 - 6	en_US
dc.identifier.isbn	9781509050192	en_US
dc.identifier.uri	http://hdl.handle.net/10453/119580
dc.description.abstract	© 2017 IEEE. In this paper, we propose a cooperative communication strategy that explores the combined use of vehicle-to-infrastructure (V2I) communications, vehicle-to-vehicle (V2V) communications, mobility of vehicles and cooperation among vehicles and infrastructure to improve the achievable capacity of vehicular network. An analytical framework is developed to model the data dissemination process using this strategy, and a closed form expression of the achievable capacity is obtained, which reveals the relationship between the achievable capacity and its major performance-impacting parameters such as inter-infrastructure distance, radio ranges of infrastructure and vehicles, sensing range of vehicles, transmission rates of V2I and V2V communications, vehicular density and the proportion of vehicles with download requests. Numerical result shows that the proposed cooperative communication strategy significantly increases the capacity of vehicular networks, especially when the proportion of vehicles with download request is low. Our results provide guidance on the optimum deployment of vehicular network infrastructure and the design of cooperative communication strategy to maximize the capacity.	en_US
dc.relation.ispartof	2017 IEEE Global Communications Conference, GLOBECOM 2017 - Proceedings	en_US
dc.relation.isbasedon	10.1109/GLOCOM.2017.8254669	en_US
dc.title	Capacity of Infrastructure-Based Cooperative Vehicular Networks	en_US
dc.type	Conference Proceeding
utslib.citation.volume	2018-January	en_US
utslib.for	0913 Mechanical 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
pubs.organisational-group	/University of Technology Sydney/Students
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US
pubs.volume	2018-January	en_US

Abstract:

© 2017 IEEE. In this paper, we propose a cooperative communication strategy that explores the combined use of vehicle-to-infrastructure (V2I) communications, vehicle-to-vehicle (V2V) communications, mobility of vehicles and cooperation among vehicles and infrastructure to improve the achievable capacity of vehicular network. An analytical framework is developed to model the data dissemination process using this strategy, and a closed form expression of the achievable capacity is obtained, which reveals the relationship between the achievable capacity and its major performance-impacting parameters such as inter-infrastructure distance, radio ranges of infrastructure and vehicles, sensing range of vehicles, transmission rates of V2I and V2V communications, vehicular density and the proportion of vehicles with download requests. Numerical result shows that the proposed cooperative communication strategy significantly increases the capacity of vehicular networks, especially when the proportion of vehicles with download request is low. Our results provide guidance on the optimum deployment of vehicular network infrastructure and the design of cooperative communication strategy to maximize the capacity.

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http://hdl.handle.net/10453/119580