collaborators

7 papers

eess.SY2026

Executor-Side Progressive Risk-Gated Actuation for Agentic AI in Wireless Supervisory Control

Zhenyu Liu, Yi Ma, Rahim Tafazolli

Agentic artificial intelligence (AI) shows promise for automating O-RAN wireless supervisory control, but translated intents still require an executor-side decision before live net…

cs.IT2026

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…

cs.IT2025

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…

cs.IT2025

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…

eess.SP2025

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…

cs.IT2025

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…