With continuous cost reduction and device miniaturization, small UAVs are now more easily accessible to the public, hence, numerous new applications in the civilian and commercial domains have emerged, such as weather monitoring, forest fire detection, traffic control, cargo transport, emergency search and rescue, communication relays, and others. Among the various applications, UAVs can help achieve high-speed wireless communications to play an important role in future communication systems. UAV-aided wireless communication offers one promising solution to provide wireless connectivity for devices without infrastructure coverage, due to severe shadowing by urban or mountainous terrain, or damage to the communication infrastructure caused by natural disasters. On the other hand, deep learning has been shown as a powerful algorithm in exploiting the system communication resources to enhance transmission performance.

The integration of deep learning into UAV communication systems has become a hot research topic in the field of wireless communication. However, several critical challenges remain unsolved for deep learning in UAV communications. One critical challenge is the complicated channel estimation due to the mobility of the UAVs, therefore, some deep learning-based algorithms should be developed. Another challenge is the transmission scheme design, where some intelligent algorithms should be devised to utilize the system communication resource efficiently. Specifically, the transmission scheme design should jointly consider the mobility and flexibility of the UAVs, in order to guarantee the system performance. Another challenge is the integration of UAV with some other techniques including caching, MIMO, OFDM, and edge computing, where deep learning-based resource management should be developed.

In this Special Issue, researchers from academia and practitioners from the industry are invited to submit their cutting-edge original research and review articles on deep learning-based methods and techniques for UAV technologies in wireless antenna propagation. This Special Issue aims to address advances in deep learning techniques for UAV technologies and improve services based on data analytics, covering topics ranging from enabling technologies to emerging applications and, importantly, industrial experiences.

Potential topics include but are not limited to the following:

• Deep UAV technologies
• Deep learning-based channel estimation
• Advanced transmission schemes
• Intelligent resource management
• UAV with caching
• MIMO with UAV
• Edge computing with UAV
• Physical-layer security of UAV
• Deep learning and federated learning
• Internet of things and traffic control
• UAV-aided cloud computing
• Channel state feedback for UAV systems