Journal article
Throughput of Infrastructure-Based Cooperative Vehicular Networks
IEEE transactions on intelligent transportation systems, Vol.18(11), pp.2964-2979
11/2017
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Source: InCites
Abstract
In this paper, we provide the detailed analysis of the achievable throughput of infrastructure-based vehicular network with a finite traffic density under a cooperative communication strategy, which explores the combined use of vehicle-toinfrastructure (V2I) communications, vehicle-to-vehicle (V2V) communications, the mobility of vehicles, and cooperations among vehicles and infrastructure to facilitate the data transmission. A closed form expression of the achievable throughput is obtained, which reveals the relationship between the achievable throughput and its major performance-impacting parameters, such as distance between adjacent infrastructure points, the radio ranges of infrastructure and vehicles, the transmission rates of V2I and V2V communications, and vehicular density. Numerical and simulation results show that the proposed cooperative communication strategy significantly increases the throughput of vehicular networks, compared with its non-cooperative counterpart, even when the traffic density is low. Our results shed insight on the optimum deployment of vehicular network infrastructure and the optimum design of cooperative communication strategies in vehicular networks to maximize the throughput.
Details
- Title
- Throughput of Infrastructure-Based Cooperative Vehicular Networks
- Creators
- Jieqiong Chen - University of Technology SydneyGuoqiang Mao - University of Technology SydneyChangle Li - Xidian UniversityAmmar Zafar - University of Technology SydneyAlbert Y. Zomaya - University of Sydney
- Publication Details
- IEEE transactions on intelligent transportation systems, Vol.18(11), pp.2964-2979
- Publisher
- IEEE
- Number of pages
- 16
- Grant note
- 61571350; 61401334 / National Natural Science Foundation of China; National Natural Science Foundation of China (NSFC)
- Identifiers
- 991013101613802368
- Academic Unit
- School of Business and Tourism
- Language
- English
- Resource Type
- Journal article