Communication Systems in Unmanned Aerial Vehicles

Dear Colleagues,

The rapid proliferation of unmanned aerial vehicles (UAVs) has ushered in a new paradigm for aerial communication, sensing, and computation. From disaster response and surveillance to enhanced cellular coverage and Internet of Things (IoT) connectivity, UAVs are increasingly envisioned as agile, on-demand platforms. However, the unique characteristics of UAV-based communication—high mobility, dynamic channel conditions, stringent energy constraints, and complex three-dimensional spatial dynamics—present significant challenges that conventional terrestrial network optimization methods are ill-equipped to handle.

This Special Issue, “Communication Systems in Unmanned Aerial Veihicles,” aims to explore the transformative role of intelligent optimization in overcoming these challenges. The focus is on the intersection of advanced optimization techniques (e.g., machine learning, deep reinforcement learning, meta-heuristics) and UAV communication system design. The scope encompasses a broad range of topics, including but not limited to: trajectory and path planning for spectral and energy efficiency; joint optimization of communication, sensing, and computation; resource allocation and interference management in UAV-aided networks; decentralized and federated learning for swarm-based UAV coordination; and the integration of UAVs as aerial base stations, relays, or edge computing nodes in 5G/6G infrastructures.

The purpose of this collection is to bring together cutting-edge research that leverages intelligent optimization to move beyond traditional model-driven approaches. By embracing data-driven, adaptive, and predictive methodologies, this Special Issue seeks to highlight solutions that can operate effectively in the highly dynamic and uncertain environments inherent to UAV operations.

While the existing literature has separately addressed aspects of UAV control and communication system design, a holistic treatment of their synergistic optimization through intelligent algorithms remains fragmented. This collection will supplement the current body of work by providing a dedicated platform that bridges the gap between theoretical optimization, artificial intelligence, and practical UAV deployment. It will serve as a comprehensive reference for researchers and practitioners aiming to build truly autonomous, efficient, and resilient aerial communication networks for next-generation wireless systems.

We invite original research articles and comprehensive reviews that push the boundaries of intelligent optimization in this rapidly evolving field.

Dr. Xin Fan
Dr. Xuehan Li
Dr. Yu Zhang
Guest Editors

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• unmanned aerial vehicles (UAVs)
• intelligent optimization
• machine learning for communications
• UAV-aided wireless networks
• 6G aerial communications
• deep reinforcement learning
• swarm intelligence
• edge intelligence
• resource allocation