R1-2500618 LS out

[Draft] Reply LS on LMF-based AI/ML Positioning for Case 2b

From ZTE
Status: not treated
WI: NR_AIML_air-Core, AIML_CN
Agenda: 5
Release: Rel-19
Source: 3gpp.org ↗

Summary

This document is a Liaison Statement reply from RAN1 to SA2 regarding LMF-based AI/ML Positioning for Case 2b in Release 19. It outlines current agreements on data types (timing, power, phase) and measurement alternatives (sample-based vs. path-based), as well as procedures for model training data collection and performance monitoring. The document contains no new proposals but summarizes existing RAN1 agreements and future work plans across data types, training procedures, and monitoring.

Position

ZTE, representing RAN1, confirms that for AI/ML positioning Case 2b, the supported data types include timing information and paired timing/power information, with phase information still under investigation. They propose studying two alternatives for time domain channel measurements: sample-based measurements (defined by Nt' samples with granularity T=2kxTc) and path-based measurements (based on existing Rel-18 reporting). For model training, they define data samples comprising Part A (channel measurements with NR-TimingQuality indicators) and Part B (ground truth labels), assuming these parts correspond to the same UE and location. They require that power measurements use DL PRS-RSRPP and UL SRS-RSRPP as starting points. Regarding model monitoring, they propose studying the necessity of assistance information from UE/PRU/gNB to LMF, while noting that monitoring metric calculation is out of RAN1 scope.

Key proposals

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