1 citations · 1 across the 4 of their papers we have counts for
7 papers
Generalizable Learning for Massive MIMO CSI Feedback in Unseen Environments
Haoyu Wang, Zhi Sun, Shuangfeng Han +2
Deep learning is promising to enhance the accuracy and reduce the overhead of channel state information (CSI) feedback, which can boost the capacity of frequency division duplex (F…
TREE:Token-Responsive Energy Efficiency Framework For Green AI-Integrated 6G Networks
Tao Yu, Kaixuan Huang, Tengsheng Wang +7
As wireless networks evolve toward AI-integrated intelligence, conventional energy-efficiency metrics fail to capture the value of AI tasks. In this paper, we propose a novel EE me…
Enhancing Environment Generalizability for Deep Learning-Based CSI Feedback
Haoyu Wang, Shuangfeng Han, Xiaoyun Wang +1
Accurate and low-overhead channel state information (CSI) feedback is essential to boost the capacity of frequency division duplex (FDD) massive multiple-input multiple-output (MIM…
Generalizable Learning for Frequency-Domain Channel Extrapolation under Distribution Shift
Haoyu Wang, Zhi Sun, Shuangfeng Han +2
Frequency-domain channel extrapolation is effective in reducing pilot overhead for massive multiple-input multiple-output (MIMO) systems. Recently, Deep learning (DL) based channel…
AI-driven 6G Air Interface: Technical Usage Scenarios and Balanced Design Methodology
Xiaoyun Wang, Shuangfeng Han, Zhiming Liu +3
This paper systematically analyzes the typical application scenarios and key technical challenges of AI in 6G air interface transmission, covering important areas such as performan…
Energy Optimization of Multi-task DNN Inference in MEC-assisted XR Devices: A Lyapunov-Guided Reinforcement Learning Approach
Yanzan Sun, Jiacheng Qiu, Guangjin Pan +4
Extended reality (XR), blending virtual and real worlds, is a key application of future networks. While AI advancements enhance XR capabilities, they also impose significant comput…