Company

NVIDIA

5 contributions across 1 work items
5
Tdocs
1
Work items

Recent contributions

R1-2409780 RAN1_119 NR_AIML_air
Specification support for AI-enabled beam management
NVIDIA presents a comprehensive framework for AI/ML-enabled beam management in 5G-Advanced, focusing on spatial (BM-Case 1) and temporal (BM-Case 2) downlink beam prediction. The document contains 11 proposals and 1 observation, advocating…
R1-2409781 RAN1_119 NR_AIML_air
Specification support for AI-enabled positioning
NVIDIA presents a comprehensive framework for AI/ML-enabled positioning in 5G-Advanced, focusing on specification support for measurements, model lifecycle management, and data consistency. The document contains 1 observation and 9…
R1-2409782 RAN1_119 NR_AIML_air
Specification support for AI-enabled CSI prediction
NVIDIA presents a technical contribution on specification support for AI-enabled CSI prediction, highlighting four key proposals and two observations regarding inference location, training/inference consistency, and post-deployment…
R1-2409783 RAN1_119 NR_AIML_air
Additional study on AI-enabled CSI compression
NVIDIA argues that stochastic channel models are insufficient for demonstrating AI/ML CSI compression gains, proposing instead the use of site-specific models trained on data generated via ray tracing in defined reference scenarios. The…
R1-2409784 RAN1_119 NR_AIML_air
Additional study on other aspects of AI model and data
NVIDIA argues for the necessity of deterministic, physics-based propagation modeling (specifically ray tracing) for accurate AI/ML data generation in 5G-Advanced and 6G. The document proposes concluding the need for model identification in…