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Machine Learning for Disseminating Cooperative Awareness Messages in Cellular V2V Communications

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posted on 22.09.2021, 00:36 by Luca LusvarghiLuca Lusvarghi, Maria Luisa Merani
This paper develops a novel Machine Learning (ML)-based strategy to distribute aperiodic Cooperative Awareness Messages (CAMs) through cellular Vehicle-to-Vehicle (V2V) communications. According to it, an ML algorithm is employed by each vehicle to forecast its future CAM generation times; then, the vehicle autonomously selects the radio resources for message broadcasting on the basis of the forecast provided by the algorithm. This action is combined with a wise analysis of the radio resources available for transmission, that identifies subchannels where collisions might occur, to avoid selecting them.
Extensive simulations show that the accuracy in the prediction of the CAMs’ temporal pattern is excellent. Exploiting this knowledge in the strategy for radio resource assignment, and carefully identifying idle resources, allows to outperform the legacy LTE-V2X Mode 4 in all respects.

History

Email Address of Submitting Author

luca.lusvarghi5@unimore.it

Submitting Author's Institution

University of Modena and Reggio Emilia

Submitting Author's Country

Italy