Hao Xu
Southeast University, China
Hao Xu (S'15-M'19-SM'25) received the B.S. degree in communication engineering from Nanjing University of Science and Technology, Nanjing, China, in 2013, and the Ph.D. degree in information and communication engineering with the National Mobile Communications Research Laboratory, Southeast University, Nanjing, China, in 2019. From 2019 to 2021, he worked as an Alexander von Humboldt (AvH) Post-Doctoral Research Fellow at the Faculty of Electrical Engineering and Computer Science, Technical University of Berlin, Germany. From 2021 to 2025, he worked as a Marie Skłodowska-Curie Actions (MSCA) Individual Fellow at the Department of Electronic and Electrical Engineering, University College London, UK. He is currently a professor with the National Mobile Communications Research Laboratory, Southeast University, Nanjing, China. His research interests mainly include communication theory, information theory, mathematical optimization, MIMO systems, and privacy and security. He has been serving as an Associate Editor for IEEE Transactions on Communications since August 2024 and IET Communications since August 2021. He was the recipient of the 2026 IEEE ComSoc Asia-Pacific Outstanding Young Researcher Award, the 2026 IEEE Communications Society Heinrich Hertz Award, and the 2024 IEEE ISTT Best Paper Award.
Recently, fluid antenna system (FAS) has emerged as a promising technology to obtain spatial diversity. By switching the antenna’s position, a transmitter or receiver is able to access the ups and downs of the fading channel, providing additional degrees of freedom and significant communication gains. A lot of studies on FAS have focused on the analysis and optimization of its communication performance, which relies heavily on the acquisition of channel state information (CSI). In FAS, the antenna can often change its position discretely or continuously in a given area, which means that to realize its full potential, the CSI of a large number of preset ports or any position at a FAS, has to be known, and conventional channel estimation schemes developed for fixed-antenna systems are no longer suitable. In this talk, I will introduce how to estimate and reconstruct the CSI of the FAS-assisted systems using the sparsity of the channel and AI approaches, and show how to evaluate the estimation performance.