116 citations · 142 across the 13 of their papers we have counts for
13 papers · 1 filter
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…