Google · 9.1.3
Specification support for CSI prediction ·
RAN1#120 · Source verification
Claude's delta
shifted
vs RAN1#119
Google shifted from proposing specific associated ID management to supporting the reuse of the broader Beam Management inference and monitoring frameworks. They added a new specific metric proposal: CQI offset between predicted and ground-truth CSI. They refined their resource configuration proposal by specifying separate CSI-RS resource sets for inference and monitoring. They also added a preference for NW-triggered reports via UCI while deprioritizing event-triggered reports.
AI-synthesized from contributions · all text is paraphrased
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Contributions at RAN1#120 · 1 doc
AI/ML based CSI Prediction
Position extracted by Claude
Google supports reusing the inference configuration procedure for AI/ML based BM for AI/ML based CSI prediction to maintain consistency of training and inference. They support reusing the framework for performance monitoring configuration, specifically requiring the NW to configure one CSI report configuration for inference and another linked configuration for monitoring. Google supports using the CQI offset between predicted and ground-truth CSI as the performance monitoring metric. They support the NW configuring separate CSI-RS resource sets for inference and monitoring, applicable to periodic, semi-persistent, or aperiodic CSI-RS. Google supports NW-triggered performance monitoring results reports and deprioritizes event-triggered reports. Finally, they support reporting performance monitoring results via UCI to manage latency.
Summary
Google proposes reusing the inference configuration and performance monitoring frameworks established for AI/ML-based Beam Management (BM) to ensure consistency for AI/ML-based CSI prediction. The document outlines six specific proposals covering configuration reuse, CQI offset metrics, separate CSI-RS resource sets, and NW-triggered reporting via UCI.
Prior contributions at RAN1#119 · 1 doc · Nov 18, 2024
AI/ML based CSI Prediction
Position extracted by Claude
Google advocates FOR UE-side only CSI prediction models with UE-reported preferred CSI-RS configurations to avoid configuration mismatches, and FOR associated ID management per CSI report configuration to maintain training/inference consistency. They push FOR dynamic activation/deactivation capabilities to enable network energy saving while maintaining model performance.
Summary
Google proposes enhancements for AI/ML based CSI prediction in NR air interface, focusing on UE-side model consistency between training and inference. The document contains 2 main proposals addressing CSI-RS configuration reporting and associated ID management for CSI report configurations.
How this was derived
Claude extracted the "position extracted" field above directly from each Tdoc during summarization.
For the delta summary at the top, Claude compared Google's consolidated stance at RAN1#120
against their stance at RAN1#119 and classified the change as
shifted.
Always verify critical claims against the original Tdocs linked above.