T1 – AI RAN: Artificial Intelligence for Radio Access Networks
Co-organizer: Hongliang Zhang, Peking University, China
Co-organizer: Qingyu Liu, Peking University, China
Co-organizer: Shuhang Zhang, Peking University, China
Abstract: With the rapid growth of the demands in modern wireless applications, the limitations of conventional radio access networks (RAN) in handling the complexity, scalability, and performance demands of wireless networks have become apparent. Recent advancements in generative artificial intelligence (AI) and large foundation models lead to a significant shift in how wireless networks are designed, managed, and optimized. The integration of AI and RAN heralds a transformative era, enabling the development of more adaptive, intelligent, high-performing, efficient, and versatile network systems. AI RAN is a key enabler for next-generation networks like 6G, where the complexity and demand for high performance require advanced automation and intelligent management. This tutorial will present the basic concepts/theories for addressing the research advances of AI RAN.
Co-organizer Bios:
Hongliang Zhang
Hongliang Zhang received B.S. and Ph.D. degrees at the School of Electrical Engineering and Computer Science at Peking University, in 2014 and 2019, respectively, where he is currently an
Endowed Boya Young Fellow Assistant Professor with School of Electronics. His current research interests include intelligent surfaces, aerial access networks, and Internet of Things. He received the best doctoral thesis award from Chinese Institute of Electronics in 2019. He is also the recipient of 2024 IEEE GLOBECOM Best Paper Award, 2024 IEEE/CIC ICCC Best Demo Award, 2023 IEEE
ComSoc Asia-Pacific Outstanding Young Researcher Award, 2021 IEEE Comsoc Heinrich Hertz Award for Best Communications Letters, and 2021 IEEE ComSoc Asia-Pacific Outstanding Paper
Award. He is currently an Editor for IEEE Transactions on Cognitive Communications and Networking, IEEE Internet of Things Journal, IEEE Transactions on Vehicular Technology, IEEE
Communications Letters, and IET Communications. He is an exemplary editor for IEEE Communications Letters in 2023.
Qingyu Liu
Qingyu Liu received the Ph.D. degree in computer engineering from Virginia Tech, Blacksburg, VA, USA, in 2019. He is currently an Assistant Professor with the School of Electronic and Computer
Engineering, Peking University, where he joined in June 2023. Prior to joining Peking University, he was a Postdoc and then a Research Assistant Professor of electrical and computer engineering with Virginia Tech, from September 2019 to May 2023. His research interests include wireless networking, mobile networking, edge AI, and the Internet of Things. He received the best paper award candidate of MILCOM 2022, and the best paper award finalist of ACM e-Energy 2018. He has been serving on TPC of IEEE INFOCOM since 2021, and was awarded as a Distinguished Member of the INFOCOM TPC in 2023. He now serves as the Secretary for the IEEE ComSoc Asia/Pacific Region Board.
Shuhang Zhang
Shuhang Zhang received the Ph. D degree and B.S. degree in electronic engineering from the School of Electrical Engineering and Computer Science, Peking University, Beijing, China, in 2021 and 2016, respectively. Since 2023, he has worked in Peng Cheng Laboratory as a research scientist and doctoral supervisor. Before joining Peng Cheng Laboratory, he worked in Huawei Technology Co. Ltd. from 2021 to 2023 as a senior engineer. His current research interests include space-air-ground integrated network, artificial intelligence, signal processing, etc. His first-author papers have won the 2021 IEEE ComSoc Heinrich Hertz Award, and the 2021 IEEE ComSoc Asia-Pacific Outstanding Paper Award. He has also won the First Prize of 2019 IEEE ComSoc Student Competition, and the Silver Prize of 2019 ACM SIGCOMM Student Research Competition. He has published over 20 papers in IEEE/ACM Journals, including multiple ESI hot papers and ESI highly cited papers. He has served as the TPC member of over 10 IEEE conferences.