Search
Main navigation
VERTICAL ENGAGEMENT TRACKER
Vertical Cartography
Vertical Engagement Charts
Vertical Associations
STANDARDS TRACKER
SNS JU Standardisation
Relevant Telco Standards
Standardisation updates
KPI RADARS
Programme Radar
Main navigation
VERTICAL ENGAGEMENT TRACKER
Vertical Cartography
Vertical Engagement Charts
Vertical Associations
STANDARDS TRACKER
SNS JU Standardisation
Relevant Telco Standards
Standardisation updates
KPI RADARS
Programme Radar
Main navigation
VERTICAL ENGAGEMENT TRACKER
Vertical Cartography
Vertical Engagement Charts
Vertical Associations
STANDARDS TRACKER
SNS JU Standardisation
Relevant Telco Standards
Standardisation updates
KPI RADARS
Programme Radar
Breadcrumb
Home
AI and machine learning for network optimisation
NGMN 5G End-to-End Architecture - Overview of the architecture for 5G End-to-End deployment
Application Type:
Green/Energy Saving Use Cases
ITU-T Y.3170 - Framework for distributed artificial intelligence in the IMT-2020 network
Application Type:
Federation-based Use Case
ETSI TR 122 934 - Study on architecture enhancements for 5G System (5GS) to support advanced V2X services
Application Type:
Slice-based URLLC
GSMA TS.45 - 5G Core Network Requirements
Application Type:
Telco Cloud
GSMA TS.44 - Open API standards for 5G
Application Type:
Telco Cloud
NGMN V2X - Vehicle-to-everything communication (V2X) for 5G
Application Type:
Networked Cloud
ITU-R M.2083-0 - IMT Vision – Framework and overall objectives of the future development of IMT for 2020 and beyond
Application Type:
Federation-based Use Case
ITU-T Y.3300 - Framework of software-defined networking
Application Type:
Telco Cloud
ITU-T Y.3173 - Framework for evaluating intelligence levels of future networks including IMT-2020
Application Type:
Federation-based Use Case
ITU-T Y.3112 - Framework of network slicing in the IMT-2020 network
Application Type:
Slice-based eMBB
Pagination
Page 1
Next page
››
Subscribe to AI and machine learning for network optimisation