5 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…
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…
Path Evolution Model for Endogenous Channel Digital Twin towards 6G Wireless Networks
Haoyu Wang, Zhi Sun, Shuangfeng Han +3
Massive Multiple Input Multiple Output (MIMO) is critical for boosting 6G wireless network capacity. Nevertheless, high dimensional Channel State Information (CSI) acquisition beco…