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Vehicular visible light networks with full duplex communications

Authors :
Alessandro Bazzi
Barbara M. Masini
Alberto Zanella
Masini B.M.
Bazzi A.
Zanella A.
Source :
MT-ITS, IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS), 2017-06-26, pp. 98–103, Napoli (Italy), 26-28/06/2017, info:cnr-pdr/source/autori:Masini B.M.; Bazzi A.; Zanella A./congresso_nome:IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS), 2017-06-26,/congresso_luogo:Napoli (Italy)/congresso_data:26-28%2F06%2F2017/anno:2017/pagina_da:98/pagina_a:103/intervallo_pagine:98–103
Publication Year :
2017
Publisher :
IEEE, 2017.

Abstract

Direct connectivity between vehicles will let a variety of new applications become a reality, from safety to traffic management and infotainment. Different wireless access technologies can enable this kind of connections, from mobile-fi IEEE 802.11p in the US and ETSI G5 in Europe, to the more recent 3GPP long term evolution (LTE) for vehicle-to-vehicle (V2V) communications. To integrate the capabilities and performance of these radio access technologies, light emitting diodes (LEDs) operating in the front and rear vehicles' lights, can introduce a further degree of connectivity through the so called visible light communication (VLC), by setting up direct links between vehicles in visibility and between vehicles and the road side (such as traffic lights and variable message panels). This paper investigates the performance of vehicular visible light networks (VVLNs) in terms of message delivery rate when full-duplex (FD) capabilities are exploited. Specifically, instead of considering carrier sensing multiple access with collision avoidance (CSMA/CA) as foreseen by the IEEE 802.15.7 standard for VLC, we here propose a CSMA with collision detection (CSMA/CD) protocol exploiting the reverse link made available by the concurrent use of LEDs as transmitters and photodiodes as receivers for an immediate feedback during decoding. Results show an increase of up to 10% in the delivered data thanks to FD in realistic urban scenarios and give guidelines to network designers.

Details

Database :
OpenAIRE
Journal :
2017 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS)
Accession number :
edsair.doi.dedup.....22574ad40cd88a4f9696677ffebec3b8
Full Text :
https://doi.org/10.1109/mtits.2017.8005646