4 papers · 1 filter
Reliable Remote Inference from Unreliable Components: Joint Communication and Computation Limits
Zhenyu Liu, Yi Ma, Rahim Tafazolli
Classical information theory typically assumes reliable receiver-side processing. We study remote inference when communication is noisy and the receiver itself is built from unreli…
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…
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…