Chao Wang
Xidian University, China
Chao Wang (Senior Member, IEEE) received the B.S., M.S., and Ph.D. degrees in information and communication engineering from Xi’an Jiaotong University, Xi’an, China, in 2008, 2013, and 2016, respectively. He is currently an Associate Professor with the State Key Laboratory of Integrated Services Networks, School of Telecommunications Engineering, Xidian University. His current research interests include 5G&6G wireless networks and key technologies, physical-layer security, covert communications, and deep learning and its application in the optimization of wireless communications. He was a recipient of the Excellent Doctoral Dissertation Award of Shaanxi Province in 2018 and China Institute of Communications in 2016. He was a recipient of the Best Paper Awards at IEEE ICCC 2014 and IEEE SAGC 2020.
This paper investigates channel estimation for multiple-input multiple-output fluid antenna systems (MIMO-FAS). Since FAS contains a large number of candidate ports while only a small number can be activated by limited RF chains, it is difficult to acquire the complete high-dimensional CSI with limited pilot resources. To address this issue, the paper proposes a diffusion model-driven channel estimation method. During training, the diffusion model learns the prior distribution of MIMO-FAS channels from channel samples. During inference, the received pilot observations are incorporated through diffusion posterior sampling to reconstruct the complete channel matrix. Simulation results show that the proposed method achieves better channel estimation accuracy than LS, LMMSE, and MAE-based methods under limited pilot conditions.