Sony · 9.1.2

Sony proposes supporting Channel Impulse Response (CIR) reporting for data collection, specifically advocating for configurable report sizes and measurement windows to mitigate signaling overhead. They require the association of data sample parts (Part A and Part B) via timing or location information and support model transfer from the LMF to UE/gNB. Regarding inference consistency, Sony proposes defining parameters for reference signal characteristics and associating these characteristics with both the trained model and the inference operation to prevent performance degradation. They further propose studying signaling procedures for this consistency and supporting AD-IE-Group2 provision for Case 1. For performance monitoring, Sony supports Options A-1, A-2, and A-3 for Case 1 label-based monitoring and requires indications of model validity to be exchanged between the LMF and NG-RAN nodes/UEs depending on the monitoring option (A or B).

Sony strongly advocates for sample-based time domain channel measurements over path-based measurements for AI/ML model input, emphasizing information richness for positioning accuracy. They push for comprehensive CIR reporting mechanisms and advocate for robust consistency mechanisms between training and inference phases, particularly supporting centralized model training at LMF with distributed inference at UE/gNB. Sony favors Option A approaches for performance monitoring where UE/gNB perform local model validity assessment.