A survey of intelligent and content-aware aerial networks' capabilities, challenges, and future directions

초록

Unmanned Aerial Vehicles (UAVs) have emerged as a prominent technology across several contemporary application domains, evolving from large, remotely controlled drone platforms into decentralized networks of small-scale, autonomous UAVs. Integrating AI capabilities with UAV networks makes the system more autonomous, intelligent, and capable of realtime data-driven decision-making, improving task execution, resource utilization, and network responsiveness for end users. In recent years, Information-Centric Networking (ICN) has become a promising solution for UAV networks, which introduces novel approaches such as name-based routing and in-network caching. These features contribute to decentralizing network utilization and improving performance. This survey explores the integration of AI and ICN into UAV networks to address challenges in trajectory and routing optimization, energy efficiency, dynamic topology management, content distribution, quality of service, latency reduction, and intelligent resource allocation. In addition to individual performance dimensions, this work systematically evaluates joint optimization frameworks that address systemic trade-offs among communication overhead, onboard computational limitations, and information freshness under highly dynamic mobility constraints. Moreover, the survey outlines how other emerging techniques further improve UAV network performance, including AI-driven and quantum-inspired solutions. Finally, the paper outlines future research directions and challenges in UAV communication networks.

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