Low-Altitude Wireless Networks: A Comprehensive Survey
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Abstract (arXiv)
The rapid development of the low-altitude economy has imposed unprecedented demands on wireless infrastructure to accommodate large-scale drone deployments and facilitate intelligent services in dynamic airspace environments. However, unlocking its full potential in practical applications presents significant challenges. Traditional aerial systems predominantly focus on air-ground communication services, often neglecting the integration of sensing, computation, control, and energy-delivering functions, which hinders the ability to meet diverse mission-critical demands. Besides, the absence of systematic low-altitude airspace planning and management exacerbates issues regarding dynamic interference in three-dimensional space, coverage instability, and scalability. To overcome these challenges, a comprehensive framework, termed low-altitude wireless network (LAWN), has emerged to seamlessly integrate communication, sensing, computation, control, and air traffic management into a unified design. This article provides a comprehensive overview of LAWN systems, introducing LAWN system fundamentals and the evolution of functional designs. Subsequently, we delve into performance evaluation metrics and review critical concerns surrounding privacy and security in the open-air network environment. Finally, we present the cutting-edge developments in airspace structuring and air traffic management, providing insights to facilitate the practical deployment of LAWNs.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 15 Sep 2025.
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Citing papers per year: 2026: 4.
4 papers.
- 2026Bridging Visual and Wireless Sensing via a Unified Radiation Field for 3D Radio Map Constructioncited by 4
- 2026TRUAV: Distributed Multi-Agent Reinforcement Learning for Trajectory Planning and Routing Enhancement in UAV-Aided IoT-Enabled VANETscited by 0
- 2026Low-Altitude Fluid Antenna Network with Multi-Agent Reinforcement Learningcited by 0
- 2026Agentic AI Networking for Heterogeneous Unmanned Aerial Systems in Low-Altitude Wireless Networkscited by 0
- 2026Agentic AI Networking for Heterogeneous Unmanned Aerial Systems in Low-Altitude Wireless Networks17 Sep 2026
- 2026Low-Altitude Fluid Antenna Network with Multi-Agent Reinforcement Learning28 Aug 2026
- 2026TRUAV: Distributed Multi-Agent Reinforcement Learning for Trajectory Planning and Routing Enhancement in UAV-Aided IoT-Enabled VANETs26 Jul 2026
- 2026Bridging Visual and Wireless Sensing via a Unified Radiation Field for 3D Radio Map Construction27 Jan 2026