8 citations · 15 across the 7 of their papers we have counts for
7 papers · 1 filter
Geometry-Aided Channel Deduction with Partial Channel Estimates and Uncalibrated Digital Twin
Hongning Ruan, Zhaoyang Zhang, Zirui Chen +3
The acquisition of high-dimensional channel state information (CSI) in wireless MIMO-OFDM communications usually requires high pilot overhead, or relies on accurate and complete po…
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…
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…
Physics-Inspired Target Shape Detection and Reconstruction in mmWave Communication Systems
Ziqing Xing, Zhaoyang Zhang, Xin Tong +2
The integration of sensing and communication (ISAC) is an essential function of future wireless systems. Due to its large available bandwidth, millimeter-wave (mmWave) ISAC systems…
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…