Special Session 7

Topic: AI-Driven Intelligent Spectrum Analysis and Management

Intelligent Electromagnetic Spectrum Analysis and Management has emerged as a critical research direction in response to the rapid growth of wireless systems and the increasing scarcity of spectrum resources. With the widespread deployment of 5G/6G networks, the Internet of Things (IoT), unmanned systems, and advanced radar and sensing technologies, the electromagnetic environment has become highly dynamic, complex, and heterogeneous. Conventional rule-based or static spectrum management approaches are no longer sufficient to address these challenges.
By incorporating artificial intelligence, machine learning, and data-driven techniques, intelligent spectrum analysis and management enables adaptive perception, modeling, cognition, prediction, and decision-making in complex electromagnetic environments, offering new solutions for efficient spectrum utilization, interference mitigation, and spectrum security.
This special session aims to solicit original research contributions on the theories, methodologies, and applications of intelligent electromagnetic spectrum analysis and management. Topics of interest span from fundamental modeling and algorithm design to system implementation and experimental validation, with the goal of advancing intelligent spectrum technologies in communications, radar, electronic warfare, and spectrum regulation.

Topics of interest include, but are not limited to:
1. AI-driven spectrum sensing and signal recognition
2. Electromagnetic spectrum situational awareness and environment modeling
3. AI-driven radio frequency resource allocation and dynamic spectrum management
4. Deep learning and reinforcement learning for spectrum decision-making and optimization
5. Cognitive radio networks
6. Electromagnetic interference detection, localization, and suppression
7. Spectrum security
8. Electromagnetic spectrum map construction

 Submission Link: https://easychair.org/conferences/?conf=icccas2026
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Special Session Chair

 

Zan Li

Jilin University, China

Biography: Zan Li is currently a full Professor and Ph.D. Supervisor at the College of Communication Engineering, Jilin University, and a Tang Aoqing Young Scholar. He leads the Information Science Laboratory and has been selected for the Jilin Provincial Young Scientist Development Program as well as awarded the Jilin University Outstanding Young Faculty.
He received his Ph.D. degree from the University of Bern, Switzerland, in 2016, graduating summa cum laude, and was awarded the Fritz Kutter Award for the Best Ph.D. Dissertation in Computer Science, as the sole recipient that year.
His research interests include intelligent wireless sensing and positioning, intelligent spectrum sensing and management. He has published over 40 papers in leading international journals and conferences, including IEEE JSAC, TWC, TII, and IoT-J. He has led multiple projects funded by the National Natural Science Foundation of China and the Jilin Provincial Department of Science and Technology, and has also undertaken several industry-sponsored research projects.