Deadline Date: 01 December 2026
The burgeoning low-altitude economy is unlocking new frontiers for economic and technological innovation. UAVs, as a critical infrastructure, are at the heart of this revolution, enabling applications from smart logistics to urban air mobility. The reliability of these services is fundamentally dependent on robust, efficient, and intelligent communication networks. This creates an urgent need for advanced algorithms to solve complex challenges in real-time trajectory optimization, dynamic resource allocation, and large-scale swarm coordination under uncertain environments.
This Special Issue aims to compile the latest breakthroughs in applying Artificial Intelligence (AI) to address these critical challenges in UAV-assisted communications. It will highlight how AI methodologies—including Evolutionary Computation, Deep Reinforcement Learning, Federated Learning, and other machine learning paradigms—provide innovative, scalable, and self-adaptive solutions. The focus is on leveraging AI's powerful learning and optimization capabilities to build the cognitive and decision-making core for next-generation autonomous UAV networks, thereby accelerating the sustainable growth of the low-altitude economy.
- AI-driven 3D path planning and collision avoidance in dense airspace.
- Deep reinforcement learning for dynamic spectrum management and interference mitigation.
- Federated and distributed learning for privacy-preserving and collaborative swarm intelligence.
- AI-based solutions for robust network operation under uncertainties and security threats.
- Multi-agent AI systems for heterogeneous UAV swarm coordination and control.
Deadline Date: 01 December 2026
The burgeoning low-altitude economy is unlocking new frontiers for economic and technological innovation. UAVs, as a critical infrastructure, are at the heart of this revolution, enabling applications from smart logistics to urban air mobility. The reliability of these services is fundamentally dependent on robust, efficient, and intelligent communication networks. This creates an urgent need for advanced algorithms to solve complex challenges in real-time trajectory optimization, ... show more
Editorial board
