R1-2410020
discussion
On AI/ML for CSI prediction
From Lenovo
Summary
Lenovo's document analyzes training/inference consistency challenges for UE-sided AI/ML-based CSI prediction in 5G NR, presenting 7 key proposals and 8 observations. The contribution evaluates four approaches to maintain consistency and recommends focusing on monitoring-based techniques while deprioritizing model transfer approaches.
Position
Lenovo advocates FOR monitoring-based approaches (Type 1 and Type 3) and limited NW-side additional condition indication for maintaining training/inference consistency in UE-sided CSI prediction. They push AGAINST model transfer from network to UE due to significant overhead challenges and deprioritize model identification techniques as overly implementation-dependent, favoring practical solutions that don't require complex model sharing mechanisms.
Key proposals
- Proposal 1 (Sec 2): Verify whether UE-sided AI/ML-based CSI prediction performance degradation resembles that of two-sided AI/ML-based CSI compression with respect to training/inference consistency in TXRU virtualization and electrical tilt/panning variation
- Proposal 2 (Sec 2): For UE-sided AI/ML-based CSI prediction, training the model with various UE speed values that are equal to or exceed the UE speed values associated with inference process leads to negligible performance degradation
- Proposal 3 (Sec 3.1): Maintaining consistency of training/inference via model training at the NW side followed by model transfer to UE side is not considered for the study of training/inference consistency under UE-sided CSI prediction
- Proposal 4 (Sec 3.2): Further study maintaining consistency of training/inference via indication of NW-side additional conditions, with focus on scenarios with a few number/values of NW-side additional conditions, as well as scenarios with localized/cell-specific/site-specific models
- Proposal 5 (Sec 3.3): Deprioritize model identification-based techniques for training/inference consistency for UE-sided CSI prediction
- Proposal 6 (Sec 3.4): Further study Type 1 and Type 3 performance monitoring techniques for CSI prediction for the purpose of training/inference consistency
- Proposal 7 (Sec 3.4): For training/inference consistency issues for UE-sided CSI prediction, if specified, scope is limited to additional condition associated ID techniques, as well as monitoring-based techniques