MA1a.2

Latent-Consistent Temporal Compression for Incremental CSI Feedback in Time-Varying Massive MIMO

Efstathios Chatziloizos, Linköping University / Ericsson Research, Sweden; Konstantinos Vandikas, Aneta Vulgarakis Feljan, Ericsson Research, Sweden; Zheng Chen, Nikolaos Pappas, Linköping University, Sweden
Session:
MA1a: Predictive Intelligence for Next Generation Wireless Networks Lecture
Track:
Communication Systems
Location:
Room 1
Presentation Time:
Mon, 26 Oct, 08:40 - 09:05 PT (UTC -7)
Session Co-Chairs:
Khac-Hoang Ngo, Linköpings Universitet, Sweden and Alejandro Lando Serrano, Universidad Carlos III de Madrid, Spain and Giuseppe Durisi, Chalmers University of Technology, Sweden
Presentation
Discussion
Resources
No resources available.
Session MA1a
MA1a.1: Predictive Signal Strength from 3D Urban Images: Can Diffusion Models Replace Ray Tracing?
Arpan Das, Department of Electrical and Computer Engineering, The University of Texas at Austin, United States; Amitava Ghosh, Nokia, United States; Kaushik Chowdhury, Jeffrey Andrews, Department of Electrical and Computer Engineering, The University of Texas at Austin, United States
MA1a.2: Latent-Consistent Temporal Compression for Incremental CSI Feedback in Time-Varying Massive MIMO
Efstathios Chatziloizos, Linköping University / Ericsson Research, Sweden; Konstantinos Vandikas, Aneta Vulgarakis Feljan, Ericsson Research, Sweden; Zheng Chen, Nikolaos Pappas, Linköping University, Sweden
MA1a.3: Real-Time Text Transmission via LLM-Based Entropy Coding over Fixed-Rate Channels
Vishnu Teja Kunde, Jean-Francois Chamberland, Krishna Narayanan, Texas A&M University, United States; Jamison Ebert, Brigham Young University, United States
MA1a.4: Adaptive Rate-Splitting under Channel Uncertainty and Interference
David Garrido, Universidad Carlos III de Madrid, Spain; Marcos M. Vasconcelos, Florida State University, Spain; Borja Peleato, Universidad Carlos III de Madrid, Spain
Contacts