19 citations · 36 across the 32 of their papers we have counts for
12 papers · 1 filter
Task-Oriented Communication with Hybrid-Precision Models
Songjie Xie, Wei Guo, Shenghui Song +3
Edge inference has emerged as a promising solution for the proliferation of artificial intelligence (AI) services by deploying models at the network edge to circumvent cloud-routin…
Multi-Modal Environment-Aware Beam Management for Massive MIMO: A Geometry-Driven Virtual Base Station Framework
Yijie Bian, Wei Guo, Jie Yang +4
High-frequency massive multiple-input multiple-output (MIMO) systems promise ultra-high data rates. However, efficient beam management remains challenging due to the prohibitive be…
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…
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…
Low-Complexity CSI Feedback for FDD Massive MIMO Systems via Learning to Optimize
Yifan Ma, Hengtao He, Shenghui Song +2
In frequency-division duplex (FDD) massive multiple-input multiple-output (MIMO) systems, the growing number of base station antennas leads to prohibitive feedback overhead for dow…
Tackling Distribution Shifts in Task-Oriented Communication with Information Bottleneck
Hongru Li, Jiawei Shao, Hengtao He +3
Task-oriented communication aims to extract and transmit task-relevant information to significantly reduce the communication overhead and transmission latency. However, the unpredi…
Joint Channel Estimation and Cooperative Localization for Near-Field Ultra-Massive MIMO
Ruoxiao Cao, Hengtao He, Xianghao Yu +5
The next-generation wireless networks are envisioned to jointly support high-rate communications and ubiquitous sensing. Ultra-Massive Multiple-Input Multiple-Output (UM-MIMO) offe…
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…