R1-2410259
discussion
Discussion on specification support for CSI prediction
From ETRI
Summary
ETRI discusses specification support for CSI prediction using AI/ML models, focusing on ensuring consistency between training and inference phases to prevent performance degradation. The document contains 3 proposals and 1 observation, advocating for associated ID support similar to beam management solutions.
Position
ETRI advocates FOR extending the already-agreed associated ID support from AI/ML beam management to CSI prediction to reduce specification workload and ensure training/inference consistency. They push FOR leveraging existing CSI framework configurations (CSI report configuration or CSI resource configuration) to implement associated ID, arguing this approach minimizes new specification requirements while addressing the critical issue of model performance degradation when network conditions change between training and inference phases.
Key proposals
- Observation 1: Ensuring the consistency between training and inference of UE-sided AI/ML model is essential for preventing non-negligible performance degradation
- Proposal 1: For consistency of training/inference of UE sided model in CSI prediction, support associated ID
- Proposal 2: In CSI prediction, UE may assume the same NW-side additional conditions of DL RS associated with the same associated ID
- Proposal 3: For consistency of UE sided model in CSI prediction, RAN1 to study the method for configuration of associated ID