Energy-Efficient Federated Learning-enabled Digital Twin in UAV-aided Vehicular Networks
Author:
Affiliation:
1. The University of Aizu,Computer Communications Laboratory,Japan
2. Shizuoka University,Department of Mathematical and Systems Engineering,Japan
3. Hanoi University of Science and Technology,School of Electrical and Electronic Engineering,Vietnam
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10460591/10460598/10460747.pdf?arnumber=10460747
Reference17 articles.
1. Digital Twin: Values, Challenges and Enablers From a Modeling Perspective
2. Survey on Digital Twin Edge Networks (DITEN) Toward 6G
3. Driver Digital Twin for Online Prediction of Personalized Lane-Change Behavior
4. Federated Learning for Digital Twin-Based Vehicular Networks: Architecture and Challenges
5. Federated Learning Assisted Multi-UAV Networks
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