Spreadtrum · 9.1.3

Spreadtrum argues that the 'associated ID' mechanism, previously introduced for Beam Management (AI-BM), should be reused for CSI prediction to ensure consistency of network-side additional conditions across training and inference. They present a technical case against 'performance monitoring based' approaches (Option 2), arguing that such methods require a trial-and-error process causing significant performance loss and cannot distinguish consistency issues from other degradation factors. Consequently, they prefer Option 1, where the UE assumes consistency is guaranteed if training and inference data share the same associated ID. Furthermore, they propose that the associated ID for CSI prediction should be configured within the existing CSI framework, leveraging the fact that reference resources for channel measurement are already defined there.

Spreadtrum advocates FOR reusing existing AI-BM (beam management) conclusions and associated ID mechanisms for CSI prediction to minimize workload, and pushes AGAINST performance monitoring-based approaches (option 2) which would cause significant performance loss due to trial-and-error processes and inability to determine root causes of performance degradation.