Xiaoyan Hu
Xi'an Jiaotong University, China
Xiaoyan Hu (Senior Member, IEEE) received the Ph.D. degree in Electronic and Electrical Engineering from University College London (UCL), London, U.K., in 2020. From 2019 to 2021, she was a Research Fellow with the Department of Electronic and Electrical Engineering, UCL, U.K. She is currently an Associate Professor with the School of Information and Communications Engineering, Xi'an Jiaotong University, Xi'an, China. Her research interests are in the areas of 5G\&6G wireless communications, including topics such as edge computing, reconfigurable intelligent surface, UAV communications, integrated sensing and communications (ISAC), secure\&covert communications, and learning-based communications. She is the recipient of the IEEE Communication Society Big Data 2023 Best Influential Paper Award. From 2020 to 2023, she served as the Assistant to the Editor-in-Chief of IEEE Wireless Communications Letters, and she is currently serving as an Associate Editor for IEEE Wireless Communications Letters. She has also served as a Guest Editor for China Communications Blue Ocean Forum on MAC and Networks.
Owing to its flexible and intelligent electromagnetic signal manipulation, the technology of RIS has attracted widespread attention. However, the potential of current RIS can only be partly unlocked due to their fixed geometry and element patterns. Motivated by the concept of the fluid antenna system (FAS), a novel RIS framework, termed fluid RIS (FRIS), has been developed. In contrast to traditional RIS architectures, FRIS introduces additional reconfigurability in the spatial or electromagnetic domain by enabling the element positions or radiation patterns to be dynamically adjusted according to the propagation environment. Such “fluid” characteristics provide additional degrees of freedom for beamforming and environmental adaptability. In this presentation, we introduce our recent research progress on FRIS and discuss its potential for future wireless communications. We first present the fundamental concept, main architectures, and key characteristics of FRIS, with particular emphasis on the differences between FRIS and conventional RISs. We then present two cases to demonstrate its potential performance gains. Finally, we highlight several open challenges and promising research directions, including practical hardware implementation, channel acquisition and the integration of FRIS into next-generation wireless networks.