AI/ML Standardization in 3GPP Release 19: Progress and Gaps
Dr. Yusuf Ozturk, 3GPP RAN1 Delegation
Samsung Research / 3GPP
Abstract
This paper provides a comprehensive analysis of AI/ML standardization progress in 3GPP Release 19, covering air interface enhancements, network automation, and management. We catalog all AI-related study items and work items, assess their completion status, and identify critical gaps that remain for Release 20 and beyond. Key findings indicate that while basic AI framework specifications are maturing, critical areas including model lifecycle management, federated learning support, and real-time inference specifications still require significant work before 6G.
AI Summary
- Comprehensive analysis of AI/ML progress in 3GPP Release 19.
- Catalogs all AI study items and work items with completion status.
- Identifies critical gaps for Release 20 and 6G standardization.
- Covers air interface, network automation, and management AI features.
Key Findings
- 1Basic AI/ML framework for NR is 80% complete in Release 19.
- 2Model lifecycle management specifications are only 30% defined.
- 3Federated learning lacks standardized interfaces between network nodes.
Industry Implications
Release 20 must accelerate AI standardization to prepare for 6G.
Vendors should implement Release 19 AI features to gain deployment experience.
Research community should focus on the identified gaps for maximum standards impact.
Read the Original Paper
Access the full paper on arXiv for complete methodology, results, and references.
Open on arXivRelated Papers
3GPP 6G Vision and Requirements: Technical Report Summary and Analysis
3GPP / Ericsson — 56 citations
Standards/Policy PapersSpectrum Policy for 6G: Upper Mid-Band and Sub-THz Allocation Strategies
London School of Economics — 18 citations
Standards/Policy PapersEthical AI in 6G Networks: A Framework for Responsible Deployment
Umea University / Oxford Internet Institute — 25 citations