6G enabled UAV traffic management models using deep learning algorithms
Author:
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Information Systems
Link
https://link.springer.com/content/pdf/10.1007/s11276-023-03485-4.pdf
Reference47 articles.
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2. Alharbi, A., Petrunin, I., & Panagiotakopoulos, D. (2023). Deep learning architecture for UAV traffic-density prediction. Drones, 7(2), 78.
3. Samir Labib, N., Danoy, G., Musial, J., Brust, M. R., & Bouvry, P. (2019). Internet of unmanned aerial vehicles—A multilayer low-altitude airspace model for distributed UAV traffic management. Sensors, 19(21), 4779.
4. Bogaerts, T., Masegosa, A. D., Angarita-Zapata, J. S., Onieva, E., & Hellinckx, P. (2020). A graph CNN-LSTM neural network for short and long-term traffic forecasting based on trajectory data. Transp. Res. Part C Emerg. Technol, 112, 62–77.
5. Li, B., Zhang, M., Rong, Y., & Han, Z. (2021). Transceiver optimization for wireless powered time-division duplex MU-MIMO systems: Non-robust and robust designs. IEEE Transactions on Wireless Communications, 21(6), 4594–4607.
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