TP4a.3

SamplerUNet: Data Efficient Pathloss Map Prediction

Omer Gokalp Serbetci, Pradeep Mathiyarasu, Andreas F. Molisch, USC, United States
Session:
TP4a: AI-Driven Wireless Channel Modeling and Prediction Lecture
Track:
Communication Systems
Location:
Nautilus
Presentation Time:
Tue, 28 Oct, 14:20 - 14:45 PT (UTC -7)
Presentation
Discussion
Resources
No resources available.
Session TP4a
TP4a.1: Learning Ray-Tracing for Radio Propagation via Cross-Attention-Based Diffusion Models
Juseong Park, Taekyun Lee, The University of Texas at Austin, United States; Yunchou Xing, Jie Chen, Amitava Ghosh, Nokia, United States; Jeffrey Andrews, The University of Texas at Austin, United States
TP4a.2: Adaptive MIMO CSI Prediction Using Neural Networks
Moritz Benedikt Fischer, University of Stuttgart, Germany; Takayuki Shimizu, Chinmay Mahabal, Toyota Motor North America, United States; Stephan ten Brink, University of Stuttgart, Germany
TP4a.3: SamplerUNet: Data Efficient Pathloss Map Prediction
Omer Gokalp Serbetci, Pradeep Mathiyarasu, Andreas F. Molisch, USC, United States
TP4a.4: CSI-Based User Positioning, Channel Charting, and Device Classification with an NVIDIA 5G Testbed
Reinhard Wiesmayr, Frederik Zumegen, Sueda Taner, ETH Zurich, Switzerland; Chris Dick, NVIDIA, United States; Christoph Studer, ETH Zurich, Switzerland
Contacts