Home

Main navigation

  • VERTICAL ENGAGEMENT TRACKER
    • Vertical Cartography
      • Vertical Engagement Charts
    • Vertical Associations
  • STANDARDS TRACKER
    • SNS JU Standardisation
      • Standard Contribution Charts
    • Relevant Telco Standards
    • Standardisation updates
  • KPI RADARS
    • Technical Radar
    • Programme Radar
Home Home

Main navigation

  • VERTICAL ENGAGEMENT TRACKER
    • Vertical Cartography
      • Vertical Engagement Charts
    • Vertical Associations
  • STANDARDS TRACKER
    • SNS JU Standardisation
      • Standard Contribution Charts
    • Relevant Telco Standards
    • Standardisation updates
  • KPI RADARS
    • Technical Radar
    • Programme Radar

Main navigation

  • VERTICAL ENGAGEMENT TRACKER
    • Vertical Cartography
      • Vertical Engagement Charts
    • Vertical Associations
  • STANDARDS TRACKER
    • SNS JU Standardisation
      • Standard Contribution Charts
    • Relevant Telco Standards
    • Standardisation updates
  • KPI RADARS
    • Technical Radar
    • Programme Radar

Breadcrumb

  1. Home

AI and machine learning for network optimisation

ITU-T Y.3172 - Framework for machine learning in future networks including IMT-2020
Application Type:
Federation-based Use Case
ETSI EN 302 637-2 - Intelligent Transport Systems (ITS); Vehicular Communications
Application Type:
Slice-based URLLC
"ETSI TS 129 520 5G System; Network Data Analytics Services; Stage 3"
Application Type:
Telco Cloud
3GPP TS 23.501 - System Architecture for the 5G System
Application Type:
Federation-based Use Case
3GPP TS 28.530 V15.3.0 Management and orchestration; Concepts, use cases and requirements
Application Type:
Federation-based Use Case
ITU Recommendation ITU-R M.2150-1
Application Type:
Telco Cloud
ETSI An Architectural Reference Model for Autonomic Networking
Application Type:
Federation-based Use Case

Pagination

  • Previous page ‹‹
  • Page 3
Subscribe to AI and machine learning for network optimisation

Hosted by sns-ju.eu