W15: International Workshop on Low-Altitude Intelligent Network (LAIN 2025)

Co-Organizer: Shuai Ma, PengCheng Laboratory, China
Co-Organizer: Lingyang Song, Peking University, China
Co-Organizer: Ke Chen, PengCheng Laboratory, China

Abstract: The Low-Altitude Intelligent Networking (LAIN) Workshop aims to explore the cutting-edge developments in low-altitude communication technologies that support efficient and secure operations for drones, low-altitude vehicles, and air-ground systems. With the rapid growth of the low-altitude economy, there is a growing need for intelligent communication solutions to enable real-time, low-latency communication across various applications, including urban air transport, emergency response, environmental monitoring, and logistics.

The workshop will cover key topics such as LAIN system architecture and network design, AI-enabled intelligent networks, and the role of semantic communication in enhancing the efficiency and flexibility of low-altitude networks. It will also explore new frontiers in radiation source identification, distributed detection systems, and heterogeneous data fusion to improve situational awareness and decision-making. Localization and path planning, space-air-ground collaborative networks, and ensuring communication quality of service (QoS), reliability, and security will be crucial focal points for discussion.

The event will bring together experts from academia, industry, and government to foster collaboration and advance the development of LAIN technologies. Participants will have the opportunity to present their research, discuss technical challenges, and propose innovative solutions to overcome the barriers in deploying effective low-altitude networks. This workshop will serve as a platform for thought leadership, networking, and collaboration in shaping the future of low-altitude intelligent networking.

Program:

Sunday, 19 October 2025 14:00 – 17:30 Shu Jin

W15: International Workshop on Low-Altitude Intelligent Network (LAIN 2025)

1  Air-Ground Model Collaboration for Low-Altitude Intelligent Network with Heterogeneous Computational Resources
14:00–14:20 Lu Cheng, Peking University Shenzhen Graduate School; Shuhang Zhang, Peking University; Hongliang Zhang, Peking University; Qingyu Liu, Peking University; Mohammed Karmoose, Nile University; Kangjun Liu, Pengcheng Laboratory; Yaowei Wang, Pengcheng Laboratory

2 Automatic Modulation Recognition Based on Feature Fusion in Impulsive Noise Environment
14:20–14:40 Pengwu Wan, Xi’an University of Posts and Telecommunications

3 Client Selection Strategies for Federated Semantic Communications in Heterogeneous IoT Networks
14:40–15:00 Samer Lahoud, Dalhousie University, Canada; Kinda Khawam, Université de Versailles, France

4 Optimal Distance-Constrained Path Planning for Sparse Radio Map Recovery
16:00–16:20 Feng Qiu, Xidian University; Kangjun Liu, Pengcheng Laboratory; Longkun Zou, Pengcheng Laboratory; Jing Liu, Xidian University; Ke Chen, Pengcheng Laboratory

15:30 – 16:00 Break

5 GenRadio: A Generative Framework for Fine-Grained 3D Radio Map Estimation
15:00–15:20 Zhiyuan Liu, Peking University; Qingyu Liu, Peking University; Shuhang Zhang, Peking University; Hongliang Zhang, Peking University; Kangjun Liu, Pengcheng Laboratory; Yaowei Wang, Pengcheng Laboratory

6 RadioPix2pix: A GAN-based Style Transfer Model for 2D Radio Map Estimation
16:20–16:40 Zhiyuan Liu, Peking University; Shuai Shao, Peking University

7 Trajectory Planning for UAVs with Multiple Service Options
16:40–17:00 Sonali Chaudhari, North Carolina State University; Rudra Dutta, North Carolina State University

8 UAV-Assisted Low AoI Data Collection Strategy Based on Hierarchical Optimization
17:00–17:20 Jing Wei, Northwest Normal University; Mangang Xie, Northwest Normal University; Baozhen An, Northwest Normal University; Wenpeng Dong, Northwest Normal University; Hui Zhang, Northwest Normal University; Xiwen Wang, Northwest Normal University

End

Co-Organizer’s Bios:

Shuai Ma

Shuai Ma received the B.S. and Ph.D. degrees in communication and information systems from Xidian University, Xi’an, China, in 2009 and 2016, respectively. From 2014 to 2015, he was a Visiting Scholar with the Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA. He has been an Associate Professor with the School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China. His research interests include visible light communication, wireless communications, and network information theory.

Lingyang Song

Lingyang Song (lingyang.song@pku.edu.cn) received his Ph.D. from the University of York, UK, in 2007, where he received the K. M. Stott Prize for excellent research. In May 2009, he joined the
School of Electronics Engineering and Computer Science, Peking University, China, as a full Professor. His main research interests include cooperative and cognitive communications, physical layer security, and wireless ad hoc/sensor networks. He was a recipient of the IEEE Leonard G. Abraham Prize in 2016 and the IEEE Asia Pacific (AP) Young Researcher Award in 2012. He has been an IEEE Distinguished Lecturer since 2015.

Ke Chen

Ke Chen (Member, IEEE) received the B.E. degree in automation and the M.E. degree in software engineering from Sun Yat-sen University, in 2007 and 2009, respectively, and the Ph.D. degree in
computer vision from Queen Mary University of London in 2013. He is currently an Associate Research Fellow with the Peng Cheng Laboratory (PCL). Before joining PCL, he was an Associate
Professor with the School of Electronic and Information Engineering, South China University of Technology, China; and a Post-Doctoral Research Fellow with the Department of Signal Processing, Tampere University of Technology, Finland. His research interests include computer vision, pattern recognition, and spectrum perception