Research

We conduct advanced research on next-generation wireless communication systems with a particular focus on 6G, non-terrestrial networks (NTN), and intelligent spectrum sharing. Our work integrates communication theory, signal processing, and machine learning to design robust, sustainable, and spectrum-efficient radio access networks (RAN).

From a methodological perspective, we leverage mathematical tools such as linear algebra, probability and statistics, optimization theory, and information theory to rigorously analyze system performance and develop theoretically grounded yet practically viable solutions. Increasingly, we incorporate machine learning techniques to enable autonomous and adaptive wireless networks.

Our research interests include 6G mobile communications, space-air-ground integrated networks (SAGIN), physical-layer security, space-time coding, interference management, spectrum sharing, intelligent resource management, and AI-driven RAN (AI-RAN) design.