activity
20222026
most citedAn Adaptive and Robust Deep Learning Framework for THz Ultra-Massive MIMO Channel Estimation

116 citations · 142 across the 13 of their papers we have counts for

collaborators

14 papers

eess.SP2026

Low-Complexity Gridless Single-Snapshot DoA Estimation via Truncated Hankel Newton-MUSIC

Ruoxiao Cao, Wentao Yu, Yi Gong +1

Reconfigurable antenna arrays can provide enhanced spatial Degrees of Freedom (DoFs) for Integrated Sensing And Communication (ISAC) systems, enabling high-resolution Direction of…

eess.SP2026

Sensing-Assisted Channel Estimation for Flexible-Antenna Systems: A Unified Framework

Ruoxiao Cao, Wentao Yu, Zixin Wang +4

Flexible-antenna systems, which use a small number of radio frequency (RF) chains to dynamically access a large set of candidate antenna locations, have emerged as a hardware-effic…

eess.SP2025

Multimodal Mixture-of-Experts for ISAC in Low-Altitude Wireless Networks

Kai Zhang, Wentao Yu, Hengtao He +3

Integrated sensing and communication (ISAC) is a key enabler for low-altitude wireless networks (LAWNs), providing simultaneous environmental perception and data transmission in co…

eess.SP2025

Sensing for Free: Learn to Localize More Sources than Antennas without Pilots

Wentao Yu, Khaled B. Letaief, Lizhong Zheng

Integrated sensing and communication (ISAC) represents a key paradigm for future wireless networks. However, existing approaches require waveform modifications, dedicated pilots, o…

eess.SP2025

Multimodal Deep Learning-Empowered Beam Prediction in Future THz ISAC Systems

Kai Zhang, Wentao Yu, Hengtao He +3

Integrated sensing and communication (ISAC) systems operating at terahertz (THz) bands are envisioned to enable both ultra-high data-rate communication and precise environmental aw…

eess.SP2024

AI and Deep Learning for Terahertz Ultra-Massive MIMO: From Model-Driven Approaches to Foundation Models

Wentao Yu, Hengtao He, Shenghui Song +4

This study explored the transformative potential of artificial intelligence (AI) in addressing the challenges posed by terahertz ultra-massive multiple-input multiple-output (UM-MI…

eess.SP2023★ 19 cited

Bayes-Optimal Unsupervised Learning for Channel Estimation in Near-Field Holographic MIMO

Wentao Yu, Hengtao He, Xianghao Yu +4

Holographic MIMO (HMIMO) is being increasingly recognized as a key enabling technology for 6G wireless systems through the deployment of an extremely large number of antennas withi…

eess.SP2023★ 2 cited

Learning Bayes-Optimal Channel Estimation for Holographic MIMO in Unknown EM Environments

Wentao Yu, Hengtao He, Xianghao Yu +4

Holographic MIMO (HMIMO) has recently been recognized as a promising enabler for future 6G systems through the use of an ultra-massive number of antennas in a compact space to expl…

eess.SP2023★ 3 cited

Deep Learning for Near-Field XL-MIMO Transceiver Design: Principles and Techniques

Wentao Yu, Yifan Ma, Hengtao He +3

Massive multiple-input multiple-output (MIMO) has been a critical enabling technology in 5th generation (5G) wireless networks. With the advent of 6G, a natural evolution is to emp…

eess.SP2023★ 2 cited

Task-Oriented Communication with Out-of-Distribution Detection: An Information Bottleneck Framework

Hongru Li, Wentao Yu, Hengtao He +4

Task-oriented communication is an emerging paradigm for next-generation communication networks, which extracts and transmits task-relevant information, instead of raw data, for dow…

eess.SP2022★ 116 cited

An Adaptive and Robust Deep Learning Framework for THz Ultra-Massive MIMO Channel Estimation

Wentao Yu, Yifei Shen, Hengtao He +4

Terahertz ultra-massive MIMO (THz UM-MIMO) is envisioned as one of the key enablers of 6G wireless networks, for which channel estimation is highly challenging. Traditional analyti…

cs.IT2022

Lightweight and Flexible Deep Equilibrium Learning for CSI Feedback in FDD Massive MIMO

Yifan Ma, Wentao Yu, Xianghao Yu +3

In frequency-division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems, downlink channel state information (CSI) needs to be sent back to the base station (BS)…

eess.SP2022

Blind Performance Prediction for Deep Learning Based Ultra-Massive MIMO Channel Estimation

Wentao Yu, Hengtao He, Xianghao Yu +3

Reliability is of paramount importance for the physical layer of wireless systems due to its decisive impact on end-to-end performance. However, the uncertainty of prevailing deep…

eess.SP2022

Hybrid Far- and Near-Field Channel Estimation for THz Ultra-Massive MIMO via Fixed Point Networks

Wentao Yu, Yifei Shen, Hengtao He +3

Terahertz ultra-massive multiple-input multiple-output (THz UM-MIMO) is envisioned as one of the key enablers of 6G wireless systems. Due to the joint effect of its array aperture…