Summary: Reconfigurable Intelligent Surface (RIS) is an emerging technology for reconfiguring wireless propagation environments through passive and tunable signal controls. It has potential applications to improve received signal strengths, reduce the transmit power consumption, and combat eavesdropping in wireless communication scenarios. However, due to the “multiplicative” fading effects, it is not trivial to acquire channel state information as the foundation of constructing and designing RIS-assisted wireless networks. As a key enabler for many intelligent solutions, Artificial Intelligent (AI) / Machine Learning (ML) could be integrated into RIS to alleviate the massive control and signaling overhead and simplify the design of RIS-assisted communications, leading to a more autonomous and self-adaptive configuration for future 6G systems.
This special workshop is aimed to introduce the state‐of‐the‐art researches on performance analysis, algorithm design, systematic design and implementation, to accelerate the development of AI-empowered RISs for practical applications in wireless communications and networks. Suitable topics for this workshop include, but are not limited to, the following areas:
AI-enabled aerial RIS for wireless networks
Learning based active and passive beamforming design in RIS transmissions
AI-empowered RIS aided localization and sensing
AI-assisted design for robust and secure communications in RIS-assisted wireless networks
Joint design of RIS-based communication and channel estimation in the AI framework
Keywords：AI-enabled RIS, Learning based design, RIS aided localization and sensing, AI-assisted design for robust and secure communications, RIS-based communication and channel estimation
Chair 1: Prof. Gang Wang，Ningbo University, China
Gang Wang received the B.Eng. degree in electronic engineering from Shandong University, Jinan, China, in 2006, and the Ph.D. degree in electronic engineering from Xidian University, Xi’an, China, in 2011. He joined Ningbo University, Ningbo, China, in January 2012, where he is currently a full Professor. From June 2018 to June 2019, he was a Visiting Scholar with the University of Missouri, Columbia, MO, USA. His research interests include the area of target localization and tracking in wireless networks.
Dr. Wang was the recipient of the Natural Science Funds for Outstanding Young Scholars from the National Natural Science Foundation of China and the Natural Science Funds for Distinguished Young Scholars from Zhejiang Provincial Natural Science Foundation. He is an elected member of the Sensor Array and Multichannel Technical Committee of the IEEE Signal Processing Society. He serves as the Associate Editor for IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, and the Handling Editor for Signal Processing (Elsevier).
Chair 2: Assoc. Juan Liu，Ningbo University, China
Juan Liu received the Ph.D. degree in electronic engineering from Tsinghua University, Beijing, China, in 2011. From March 2012 to June 2014, she was a Postdoc Research Scholar in Department of Electrical and Computer Engineering, NC State University (NCSU), Raleigh, NC, USA. From February 2015 to February 2016, she was a Research Associate in Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology (HKUST), Hong Kong. Since March 2016, she has been with Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, China, where she is an Associate Professor. Now she is focusing on the research topics on UAV communications, wireless caching and edge computing, and deep learning for large-scale wireless networks.
Chair 3: Assoc. Yangong Zheng，Ningbo University, China
Yangong Zheng is an Associate Professor in the Faculty of Electrical Engineering and Computer Science, Ningbo University, China. He received his PhD from the School of Electronic Science and Technology of Dalian University of Technology in 2014. During 2011-2013, he worked as a visiting scholar in Chemistry Department of The Ohio State University in USA. Currently, his research interests focus on electronic nose and neural networks.