7 citations · 18 across the 12 of their papers we have counts for
12 papers
Digital Twin Aided Massive MIMO CSI Feedback: Exploring the Impact of Twinning Fidelity
Hao Luo, Shuaifeng Jiang, Saeed R. Khosravirad +1
Deep learning (DL) techniques have demonstrated strong performance in compressing and reconstructing channel state information (CSI) while reducing feedback overhead in massive MIM…
Digital Twin Assisted Beamforming Design for Integrated Sensing and Communication Systems
Shuaifeng Jiang, Ahmed Alkhateeb
This paper explores a novel research direction where a digital twin is leveraged to assist the beamforming design for an integrated sensing and communication (ISAC) system. In this…
Learnable Wireless Digital Twins: Reconstructing Electromagnetic Field with Neural Representations
Shuaifeng Jiang, Qi Qu, Xiaqing Pan +3
Fully harvesting the gain of multiple-input and multiple-output (MIMO) requires accurate channel information. However, conventional channel acquisition methods mainly rely on pilot…
Digital Twin Aided Massive MIMO: CSI Compression and Feedback
Shuaifeng Jiang, Ahmed Alkhateeb
Deep learning (DL) approaches have demonstrated high performance in compressing and reconstructing the channel state information (CSI) and reducing the CSI feedback overhead in mas…
Vision Guided MIMO Radar Beamforming for Enhanced Vital Signs Detection in Crowds
Shuaifeng Jiang, Ahmed Alkhateeb, Daniel W. Bliss +1
Radar as a remote sensing technology has been used to analyze human activity for decades. Despite all the great features such as motion sensitivity, privacy preservation, penetrabi…
Real-Time Digital Twins: Vision and Research Directions for 6G and Beyond
Ahmed Alkhateeb, Shuaifeng Jiang, Gouranga Charan
This article presents a vision where \textit{real-time} digital twins of the physical wireless environments are continuously updated using multi-modal sensing data from the distrib…
Digital Twin Based Beam Prediction: Can we Train in the Digital World and Deploy in Reality?
Shuaifeng Jiang, Ahmed Alkhateeb
Realizing the potential gains of large-scale MIMO systems requires the accurate estimation of their channels or the fine adjustment of their narrow beams. This, however, is typical…
Sensing Aided Reconfigurable Intelligent Surfaces for 3GPP 5G Transparent Operation
Shuaifeng Jiang, Ahmed Hindy, Ahmed Alkhateeb
Can reconfigurable intelligent surfaces (RISs) operate in a standalone mode that is completely transparent to the 3GPP 5G initial access process? Realizing that may greatly simplif…
Camera Aided Reconfigurable Intelligent Surfaces: Computer Vision Based Fast Beam Selection
Shuaifeng Jiang, Ahmed Hindy, Ahmed Alkhateeb
Reconfigurable intelligent surfaces (RISs) have attracted increasing interest due to their ability to improve the coverage, reliability, and energy efficiency of millimeter wave (m…
Sensing Aided OTFS Channel Estimation for Massive MIMO Systems
Shuaifeng Jiang, Ahmed Alkhateeb
Orthogonal time frequency space (OTFS) modulation has the potential to enable robust communications in highly-mobile scenarios. Estimating the channels for OTFS systems, however, i…
LiDAR Aided Future Beam Prediction in Real-World Millimeter Wave V2I Communications
Shuaifeng Jiang, Gouranga Charan, Ahmed Alkhateeb
This paper presents the first large-scale real-world evaluation for using LiDAR data to guide the mmWave beam prediction task. A machine learning (ML) model that leverages the LiDA…
Computer Vision Aided Beam Tracking in A Real-World Millimeter Wave Deployment
Shuaifeng Jiang, Ahmed Alkhateeb
Millimeter-wave (mmWave) and terahertz (THz) communications require beamforming to acquire adequate receive signal-to-noise ratio (SNR). To find the optimal beam, current beam mana…