7 papers · 1 filter
Full-Domain Coupler: A Wireless Native Neural Backbone for Channel Representation and Deduction
Zirui Chen, Ziqing Xing, Zhaoyang Zhang +5
Data representation is a fundamental issue in deep learning. However, as wireless data scales and deeply couples across many physical domains such as time, space, and frequency, ex…
Synergizing Global Pattern Learning and Time Order Characterization in Mobile Channel Prediction: An RWKV-Based Approach
Zili Wang, Zirui Chen, Ridong Li +2
Owing to the potential to reduce pilot overhead and mitigate channel aging, channel prediction is emerging as an important research topic in wireless communications. Meanwhile, dee…
Geometry-Aided Channel Deduction: A Robust Channel Acquisition Framework Utilizing Coarse Scenario Prompt
Hongning Ruan, Zhaoyang Zhang, Zirui Chen +2
Channel state information (CSI) is critical for multi-input multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) system. Pilot-based channel estimation methods suf…
Multi-View Wireless Sensing via Conditional Generative Learning: Framework and Model Design
Ziqing Xing, Zhaoyang Zhang, Zirui Chen +3
In this paper, we incorporate physical knowledge into learning-based high-precision target sensing using the multi-view channel state information (CSI) between multiple base statio…
Towards Wireless Native Big AI Model: The Mission and Approach Differ From Large Language Model
Zirui Chen, Zhaoyang Zhang, Chenyu Liu +1
Research on leveraging big artificial intelligence model (BAIM) technology to drive the intelligent evolution of wireless networks is emerging. However, breakthroughs in generaliza…
VBIM-Net: Variational Born Iterative Network for Inverse Scattering Problems
Ziqing Xing, Zhaoyang Zhang, Zirui Chen +3
Recently, studies have shown the potential of integrating field-type iterative methods with deep learning (DL) techniques in solving inverse scattering problems (ISPs). In this art…