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AI-Enabled UAV Communications: Challenges and Future Directions

IEEE Access • 2022
العودة
معلومات البحث
المؤلفون AMIRA O. HASHESH, SHERIEF HASHIMA , ROKAIA M. ZAKI, MOSTAFA M. FOUDA , KOHEI HATANO AND ADLY S. TAG ELDIEN
الكلمات المفتاحية Unmanned aerial vehicles (UAVs), artificial intelligence (AI), deep learning (DL), metalearning, federated learning (FL), reinforcement learning (RL)
المجلة العلمية IEEE Access
الناشر IEEE
المجلد 10
العدد Not Available
الصفحات 92048-92066
publication.type International
رابط البحث Open Link
المواد المرفقة Not Available
الملخص
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.