AI-Enabled UAV Communications: Challenges and Future Directions
IEEE Access • 2022
Publication Information
Authors
AMIRA O. HASHESH, SHERIEF HASHIMA , ROKAIA M. ZAKI,
MOSTAFA M. FOUDA , KOHEI HATANO AND ADLY S. TAG ELDIEN
Keywords
Unmanned aerial vehicles (UAVs), artificial intelligence (AI), deep learning (DL), metalearning, federated learning (FL), reinforcement learning (RL)
Journal
IEEE Access
Publisher
IEEE
Volume
10
Issue
Not Available
Pages
92048-92066
publication.type
International
Paper Link
Open Link
Supplementary Materials
Not Available
Abstract
Recently, unmanned aerial vehicles (UAVs) communications gained significant concentration as a talented technology for future wireless communications using its remarkable advantages and broad applicability. Furthermore, UAV networks’ high complex configurations and designs encourage researchers to leverage relevant artificial intelligence (AI) techniques for better beyond fifth-generation (B5G)/sixthgeneration (6G) services. This article summarizes AI-aided UAV solutions designated for forthcoming wireless networks. Besides, we deliver a comprehensive summary of machine learning (ML) approaches,
including their applications and valuable contributions towards effective UAV network implementations,
particularly advanced ML ones like bandits, federated learning (FL), meta-learning, etc. Finally, detailed
UAV communication-related future research scopes and challenges is highlighted.
including their applications and valuable contributions towards effective UAV network implementations,
particularly advanced ML ones like bandits, federated learning (FL), meta-learning, etc. Finally, detailed
UAV communication-related future research scopes and challenges is highlighted.
Staff Members - Benha University