R1-2410380 discussion

Discussion on other aspects of AI/ML model and data

From NTT DOCOMO
Status: not treated
WI: NR_AIML_air
Agenda: 9.1.4.2
Release: Rel-19
Source: 3gpp.org ↗

Summary

NTT DOCOMO presents a comprehensive discussion on AI/ML model identification, data collection, and transfer mechanisms for 5G NR air interface, making 9 proposals and 6 observations covering scenario-specific models, model identification procedures, and standardization approaches.

Position

NTT DOCOMO strongly advocates FOR scenario/site-specific AI/ML models over generalized models, arguing they provide superior performance by learning specific environment tendencies that are difficult to mathematically model. They push FOR hybrid approaches combining multiple model identification options and standardized model transfer mechanisms. They are AGAINST deprioritizing model identification due to management complexity, and AGAINST case z1 model delivery unless clear gains are demonstrated over UE-side training approaches.

Key proposals

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