Abstract
In this book, we first propose a PHY-layer authentication scheme based on ambient radio signals and the RSSI of packets that usually ignored in VANETs. The problem of network selection in VANETs is considered, taking into account the rapid changes in signal strength brought about by high-speed movement of the vehicle. In addition, we propose a hotbooting PHC-based UAV relay strategy to resist smart jamming without the knowledge of the UAV channel model and the jamming model. A learning-based task offloading framework using the multi-armed bandit theory is developed, which enables vehicles to learn the potential task offloading performance of its neighboring vehicles with excessive computing resources and minimizes the average offloading delay [1].
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Xiao, L., Zhuang, W., Zhou, S., Chen, C. (2019). Conclusion and Future Work. In: Learning-based VANET Communication and Security Techniques. Wireless Networks. Springer, Cham. https://doi.org/10.1007/978-3-030-01731-6_6
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DOI: https://doi.org/10.1007/978-3-030-01731-6_6
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