5 papers
Resi-VidTok: An Efficient and Decomposed Progressive Tokenization Framework for Ultra-Low-Rate and Lightweight Video Transmission
Zhenyu Liu, Yi Ma, Rahim Tafazolli +1
Real-time transmission of video over wireless networks remains highly challenging, even with advanced deep models, particularly under severe channel conditions such as limited band…
Deep Learning-Based Rate-Adaptive CSI Feedback for Wideband XL-MIMO Systems in the Near-Field Domain
Zhenyu Liu, Yi Ma, Rahim Tafazolli
Accurate and efficient channel state information (CSI) feedback is crucial for unlocking the substantial spectral efficiency gains of extremely large-scale MIMO (XL-MIMO) systems i…
Leveraging Bi-Directional Channel Reciprocity for Robust Ultra-Low-Rate Implicit CSI Feedback with Deep Learning
Zhenyu Liu, Yi Ma, Rahim Tafazolli +1
Deep learning-based implicit channel state information (CSI) feedback has been introduced to enhance spectral efficiency in massive MIMO systems. Existing methods often show perfor…
ResiTok: A Resilient Tokenization-Enabled Framework for Ultra-Low-Rate and Robust Image Transmission
Zhenyu Liu, Yi Ma, Rahim Tafazolli
Real-time transmission of visual data over wireless networks remains highly challenging, even when leveraging advanced deep neural networks, particularly under severe channel condi…
Importance-Aware Source-Channel Coding for Multi-Modal Task-Oriented Semantic Communication
Yi Ma, Chunmei Xu, Zhenyu Liu +2
This paper explores the concept of information importance in multi-modal task-oriented semantic communication systems, emphasizing the need for high accuracy and efficiency to fulf…