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Sensors 2018, 18(4), 1183; https://doi.org/10.3390/s18041183

Crowdsourcing-Assisted Radio Environment Database for V2V Communication

1,‡,* , 2,‡
and
1,‡
1
Advanced Wireless and Communication Research Center (AWCC), The University of Electro-Communications, 1-5-1 Chofugaoka, Chofu-shi, Tokyo 182–8585, Japan
2
Department of Electrical Engineering, Faculty of Engineering, Tokyo University of Science, 6-3-1 Niijuku, Katsushika-ku, Tokyo 125-8585, Japan
This paper is an extended version of our paper published in Katagiri, K.; Sato, K; Fujii, T. Crowdsourcing-assisted Radio Environment Maps for V2V Communication Systems. In Proceedings of the 2017 IEEE 86th the Vehicular Technology Conference (VTC-Fall), 24–27 September 2017, Tronto, Canada; doi:10.1109/VTCFall.2017.8287980.
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Received: 28 February 2018 / Revised: 9 April 2018 / Accepted: 9 April 2018 / Published: 12 April 2018
(This article belongs to the Special Issue Smart Vehicular Mobile Sensing)
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Abstract

In order to realize reliable Vehicle-to-Vehicle (V2V) communication systems for autonomous driving, the recognition of radio propagation becomes an important technology. However, in the current wireless distributed network systems, it is difficult to accurately estimate the radio propagation characteristics because of the locality of the radio propagation caused by surrounding buildings and geographical features. In this paper, we propose a measurement-based radio environment database for improving the accuracy of the radio environment estimation in the V2V communication systems. The database first gathers measurement datasets of the received signal strength indicator (RSSI) related to the transmission/reception locations from V2V systems. By using the datasets, the average received power maps linked with transmitter and receiver locations are generated. We have performed measurement campaigns of V2V communications in the real environment to observe RSSI for the database construction. Our results show that the proposed method has higher accuracy of the radio propagation estimation than the conventional path loss model-based estimation. View Full-Text
Keywords: wireless distributed networks; spectrum database; radio propagation wireless distributed networks; spectrum database; radio propagation
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Katagiri, K.; Sato, K.; Fujii, T. Crowdsourcing-Assisted Radio Environment Database for V2V Communication. Sensors 2018, 18, 1183.

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