R1-2410654
discussion
Discussion on AI/ML for CSI prediction
From Huawei
Huawei's prior position on
9.1.3
at
RAN1#118bis
· AI-synthesized, paraphrased
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Strongly advocates against introducing associated IDs or network-side indications for CSI prediction consistency, arguing they are unnecessary and create privacy risks. Proposes UE-side performance monitoring as a sufficient implementation-based solution instead.
Summary
Huawei argues against introducing associated IDs for ensuring training/inference consistency in CSI prediction for AI/ML-enhanced NR air interface, presenting 5 observations and 2 proposals. The document demonstrates through simulation results that generalized AI/ML models can achieve satisfactory performance using mixed datasets without network-side indications.
Position
Huawei advocates AGAINST introducing network-side associated IDs or explicit indications for CSI prediction consistency, arguing that such mechanisms are both infeasible (due to massive impacting factors and network burden) and unnecessary (since generalized models work well with mixed datasets). They push FOR UE-side performance monitoring as an implementation-based solution, distinguishing CSI prediction from beam management and positioning use cases where associated IDs were deemed necessary.
Key proposals
- Proposal 1 (Sec 2.2): No need to introduce indications from NW (e.g., explicit indication or associated ID) for ensuring consistency between training/inference for CSI prediction
- Proposal 2 (Sec 2.3): The consistency can be achieved by performance monitoring at UE side with an implementation manner
Revision chain
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Discussion on AI/ML for CSI prediction
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R1-2410654 ← you are here discussion not treated Final