Abstract:
As the global demand for intelligent aerial services continues to grow, researchers have turned their attention to the low-altitude airspace (typically ranging from 100 to 3,000 meters above ground) as a new frontier for digital infrastructure. A common vision in this evolving landscape is that the low-altitude airspace would not merely serve as an aerial extension of traditional communication networks, but would actually become a fully integrated, mission-aware platform that supports seamless connectivity, real-time sensing, distributed control, and onboard intelligence. Inspired by recent advances in wireless communications, robotics, and autonomous control, the concept of Low-Altitude Wireless Networks (LAWN) has emerged as a promising framework to meet these requirements. Unlike conventional aerial communication systems that treat unmanned aerial vehicles (UAVs) primarily as flying relays or base stations, LAWN envisions a tightly coupled cyber-physical system where drones, ground nodes, and edge computing resources collaboratively support highly dynamic, service-driven aerial operations. In this architecture, communication, sensing, and control are jointly optimized to deliver critical services such as real-time situational awareness, cooperative navigation, and autonomous mission execution.
Realizing LAWN poses significant challenges. A fundamental question arises: How can we design a unified network architecture capable of supporting such diverse and stringent demands? A natural starting point is the development of layered functional planes (data, control, sensing, and computing) that can adapt to mission requirements while maintaining operational safety and efficiency. However, achieving this integration is far from trivial. LAWN must cope with highly dynamic topologies, strict latency and reliability constraints, limited onboard energy, and complex regulatory environments. These challenges call for new cross-layer design methodologies that bridge communication theory, control systems, edge AI, and spectrum policy.
The importance of LAWN is reinforced by several large-scale industrial, regulatory, and standardization efforts already under way worldwide. Aviation authorities and technology companies are developing Unmanned Aircraft Systems Traffic Management (UTM) platforms specifically for low-altitude corridors, while 3GPP has begun standardizing aerial user equipment connectivity in 5G-Advanced and early 6G releases. Despite growing research interest from academia, industry, as well as the government, there has been no dedicated effort to systematically consolidate the advances in this emerging area. This workshop aims to bring together academic and industrial researchers from the fields of communications, signal processing, robotics, and aerospace to identify, investigate, and advance the design of robust, intelligent, and mission-aware LAWN systems. Special attention will be given to the physical and MAC layer challenges, network architecture, semantic-aware data processing, and system-level integration with Unmanned Traffic Management (UTM), Remote ID, and cyber-physical security protocols. Topics of interest include but are not limited to:
- Waveforms and signal processing for high-mobility LAWN nodes
- Architectural frameworks for agentic LAWNs and 3D network fabrics
- Cross-layer optimization and co-design of multi-functions in aerial networks
- Air-to-ground, air-to-air, and air-to-space channel modeling and measurement campaigns
- Spectrum management, sharing, and coexistence strategies for 3D airspace
- Intelligent network management, edge computing, and distributed AI for aerial platforms
- Integrated sensing and communication (ISAC) tailored for low-altitude operations
- Semantic and split inference for edge-based control and perception
- Cooperative sensing, swarm coordination, and real-time situational awareness
- Ultra-reliable and low-latency communication (URLLC) for command and control
- Remote ID, UTM compliance, and regulatory-aligned LAWN protocol stacks
- Cyber-physical security for aerial links under spoofing, jamming, and node failures
- Experimental platforms, simulation environments, and open-source LAWN benchmarks
Organizers:
- Dusit Niyato, Nanyang Technological University, Singapore
- Weijie Yuan, Southern University of Science and Technology, China
- Eirini Eleni Tsiropoulou, Arizona State University, US
- Geng Sun, Jilin University, China
- Jiacheng Wang, Nanyang Technological University, Singapore
- Baha Eddine Youcef Belmekki, Heriot-Watt University, UK