R1-2410414 discussion

Discussion on specification support for AI-ML based positioning accuracy enhancement

From Baicells
Status: not treated
WI: NR_AIML_air
Agenda: 9.1.2
Release: Rel-19
Source: 3gpp.org ↗

Summary

Baicells presents their views on AI/ML-based positioning accuracy enhancement for R19, covering model input/output, training data collection, quality indicators, and model monitoring across positioning sub-use cases. The document contains 11 proposals and 9 observations addressing technical aspects from sample-based measurements to model monitoring approaches.

Position

Baicells strongly advocates FOR sample-based measurements over path-based measurements, arguing that sample-based provides superior positioning accuracy (1.06-1.62x better performance) and avoids algorithm inconsistencies between vendors. They push FOR phase information support in Case 3b despite overhead concerns, and advocate FOR minimizing specification impact by reusing existing IEs and procedures wherever possible rather than defining new mechanisms.

Key proposals

Your notes

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