SPECIAL SESSION
Special Session 1: Towards 6G and Future Wireless Networks: Terahertz Ultra-Massive MIMO and Network-Wide Distributed Intelligence
The evolution of 6G and future networked systems is driven by two highly interdependent cornerstones: the leap to the Terahertz (THz) band with ultra-massive multiple-input multiple-output (UM-MIMO) arrays, and the network-wide integration of distributed intelligence. Together, they promise to reshape wireless communications, offering terabit-per-second data rates and fast, responsive intelligence at the point of demand.
Overcoming immense THz path loss requires integrating thousands of antennas to synthesize highly directional beams. This introduces unique electromagnetic challenges: extremely short wavelengths shift the operational environment into the radiating near-field (Fresnel) region, necessitating spherical wavefront models instead of conventional far-field plane wave assumptions. Furthermore, multi-antenna THz systems face severe hardware impairments, wideband beam squint, and complex subarray architectures.
Simultaneously, integrating artificial intelligence with advanced networking—including edge computing, IoT mesh networks, and Integrated Sensing and Communication (ISAC)—enables large-scale collaborative inference across heterogeneous devices. While this distributed intelligence supports emerging applications like autonomous systems and AI-native network optimization, it faces practical hurdles in communication-computation co-design, cross-layer optimization, and severe security vulnerabilities, such as model poisoning and privacy leakage. This special session brings together leading researchers and industry experts to address these critical cross-layer challenges and share recent advances in 6G connectivity.
Related Topics for this Session （but not limited to）:
- Scientific advances in THz UM-MIMO: Channel modeling, transceiver architectures, and spherical wavefront signal processing for the near-field (Fresnel) region.
- Hardware-aware 6G designs: Coping with THz hardware impairments, high power consumption, wideband beam squint, and hybrid subarray architectures.
- Distributed learning for network optimization: Topology-aware learning, AI-native network management, and real-time model sharing across heterogeneous devices.
- Communication-computation co-design: Cross-layer optimization and dynamic resource allocation for massive collaborative inference and edge computing.
- Integrated Sensing and Communication (ISAC): Synergies between high-resolution THz sensing and distributed intelligence.
- Trustworthy & Secure 6G AI: Privacy-preserving distributed intelligence, defenses against model/data poisoning, adversarial attacks, and privacy leakage in ultra-dense deployments.
- Hardware prototyping & system design: Bridging the gap between THz high-frequency operations and scalable distributed learning frameworks.
Short Biography of Organizers
Hongwei WANG is an Associate Professor at the University of Electronic Science and Technology of China (UESTC). He received his B.S. degree in 2013 and Ph.D. degree in 2019, both from Northwestern Polytechnical University (NPU), Xi'an, China. During his doctoral studies, he was a joint Ph.D. student at Nanyang Technological University, Singapore, and Stevens Institute of Technology, USA. From December 2019 to July 2024, he worked as a postdoctoral researcher at UESTC, and subsequently joined the faculty as an Associate Professor. In recent years, he has published more than 30 academic papers, led or participated in over 10 projects funded by the National Natural Science Foundation of China (NSFC) and other agencies, and serves as a member of the CIGRE D2 China Committee. His research interests include statistical signal processing, compressive sensing and sparse theory, THz communications.
Shuai Wang received the PhD degree from the School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, China, in 2021. He is currently an associated professor at the University of Electronic Science and Technology of China. Before that, he was a postdoctoral research fellow with the Information Systems Technology and Design Pillar, Singapore University of Technology and Design, Singapore. His current primary research interests include optimization algorithms for signal processing, machine learning and communication systems, distributed optimization and federated learning (FL), data security and privacy protection in distributed systems, integrated sensing and communication (ISAC), etc. He has published more than 30 academic papers and serves as the Youth Editorial Board Member of two journals, and the session chair of ICCT 2025.
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