Holographic MIMO Communications: Fundamental Limits, Signal Processing, and Learning-Aided Design

About this Topic:

Holographic multiple-input multiple-output (HMIMO) is a promising paradigm for future wireless systems, enabling unprecedented spatial resolution through densely integrated electromagnetic apertures. Realizing the potential of HMIMO, however, requires advances in channel modeling, signal processing, and learning algorithms.

This webinar presents our presenters recent research on HMIMO communications from three complementary perspectives. First, they investigate the fundamental limits of non-centered and non-separable channels, developing analytical characterizations of mutual information and outage performance that capture key propagation features of HMIMO systems. Second, they address the practical challenge of mutual coupling in densely packed arrays through a vector-factorization framework that jointly estimates wireless channels and coupling effects. Third, they present a score-based unsupervised learning approach for near-field HMIMO channel estimation, which learns channel distributions directly from noisy pilot observations and achieves Bayes-optimal performance without requiring labeled training data or explicit channel priors. 

Together, these results provide a unified perspective on how to model, estimate, and learn HMIMO channels. They conclude with key system-level insights and discuss how the proposed methodologies extend beyond HMIMO to a broad range of large-scale MIMO systems.

About the Presenters:

Wentao Yu received the B.Eng. degree in electronic science and engineering from Nanjing University, Nanjing, China and the Ph.D. degree in electronic and computer engineering from the Hong Kong University of Science and Technology (HKUST), Hong Kong, in 2021 and 2025 respectively.

He is currently a Postdoctoral Research Fellow with the department of electrical and computer engineering, the University of British Columbia (UBC), Vancouver, BC, Canada. From Sept. 2024 to Jul. 2025, he was a visiting researcher with the Research Laboratory of Electronics, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA. His research interests lie in signal processing and machine learning for wireless communications, including next-generation MIMO technologies, integrated sensing and communication, analog RF computing, and edge AI.

Dr. Yu was a recipient of the NSERC Canada Postdoctoral Research Award in 2026, the Hong Kong Ph.D. Fellowship Scheme (HKPFS) in 2021, and the China National Scholarship in 2018. He was also recognized as an Exemplary Reviewer of the IEEE Wireless Communications Letters in 2024.

Shenghui Song received the Ph.D. degree in electrical engineering from the City University of Hong Kong, Hong Kong, China.

He is currently an Associate Professor jointly appointed by the Division of Integrative Systems and Design (ISD) and the Department of Electronic and Computer Engineering (ECE) at the Hong Kong University of Science and Technology (HKUST). His research is primarily in the areas of Wireless Communications and Machine Learning with current focus on Information Theory, Integrated Sensing and Communication, Distributed Intelligence, and Semantic Communications.

Dr. Song is an editorial board member of Entropy. He served as the Tutorial Program Co-Chairs of the 2022 IEEE MeditCom, and the Workshop Technical Program Chairs for the IEEE GlobeCom 2026 and ICMLCN 2026. He was named the Exemplary Reviewer for IEEE Communications Letter. He is also interested in the research on Engineering Education and served as an Associate Editor for the IEEE Transactions on Education. He has won several teaching awards at HKUST, including the Michael G. Gale Medal for Distinguished Teaching in 2018, the Best Ten Lecturers in 2013, 2015, and 2017, the School of Engineering Distinguished Teaching Award in 2012, the Teachers I Like Award in 2013, 2015, 2016, and 2017, and the MSc (Telecom) Teaching Excellent Appreciation Award for 2020-21 and 2022-23. Dr. Song was one of the honorees of the Third Faculty Recognition at HKUST in 2021.