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This is a collective workspace for exploring how to apply open source processes to the development of AI/ML models for use in the operations of intelligent networks.


Ideas on data sharing

Ideas on specific use cases to lead the exploration

  • If you are an operator or vendor that would like to propose a use case - please add it to the table
  • If you are an operator or vendor that is interested in one of the listed use cases - please add your name to the table together with proposed contributions, if any
Use CaseDescriptionInterested DeveloperInterested Operator
<sample use case><In this use case ML is used to predict lightning strikes on cell towers> 

Company 1: <Acme Inc.>

Contact person1 : <Dr. Emmett Brown>

Proposed contribution1:<models, algorithms. etc>

Company 2: <Hooli Inc.>

Contact person2 : <Gavin Belson>

Proposed contribution2:<models, algorithms. etc>

Company 1: <Western Union>

Contact person 1: <Marty McFly>

Proposed contribution 1:<access to lab, data lake, anonymized data set, etc.>

Congestion Prediction & Mitigation

This use case will demonstrate how AI/ML may be used to predict congestion and perform closed loop automation for executing configuration changes to mitigate.

Company 1: Samsung

Contact person 1: Ranny Haiby

Proposed contribution 1:O-RAN-SC xApp, non-RT RIC, rAPP & AI server

Company 2:

Contact person2 :

Proposed contribution2:


Sleeper Cell DetectionPredict a cell going to "sleep" and handover a critical UE (e.g. ambulance) to another cell.

Company 1: Samsung

Contact person 1: Ranny Haiby

Proposed contribution 1:O-RAN-SC Non-RT-RIC rApp 2020 October Virtual Technical Event Topic Proposals#2020OctoberVirtualTechnicalEventTopicProposals-ONAP:A1PolicyenforcementwithNon-RTRIC

Company 2:

Contact person2 :

Proposed contribution2:


Traffic Steering Improve Quality of Experience (QoE) by steering UE traffic among multiple cells.

Company 1: Samsung

Contact person 1: Ranny Haiby

Proposed contribution 1:O-RAN-SC xApp

Company 2:

Contact person2 :

Proposed contribution2:


Soft fault detection and resolutionDetect "soft" faults that are not often caught because they are hidden by the redundant systems.  Example, would be faults that bounce for a short time, so are ignored by service assurance.  We want to use AI/ML to detect patterns of faults to uncover the ones that might not have an immediate impact on network performance, but will over time as the network degrades.

Company 1: Verizon

Contact person 1: Beth Cohen


Deterministic  Predictive capacity planningAbility to detect usage patterns so that the network can be used more efficiently, don't need to built to peak.

Company 1: Verizon

Contact person 1: Beth Cohen










Ideas on managing privacy of data and models

Background data

Results from the EUAG "Intelligent Networks" survey Data_All_210106.pdf

Notes from  EUAG/TAC discussion


Notes from   EUAG/TAC discussion

Telecom Italia Big Data Challenge

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  1. The Broadband Forum currently has work underway that may be of interest to these use case descriptions as well. For 2020, an application note was developed to show how closed loop monitoring and adjustment of Wi-Fi could be made, using the Cloud CO and USP projects.  Similarly, there is ongoing work for a top level automation and intelligence architecture for Broadband TR-436: Access & Home Network O&M
    Automation/Intelligence (https://www.broadband-forum.org/technical/download/TR-436.pdf).  The work area is now working on the definition of the interfaces within that architecture, including the information models that would be used over those interfaces.  That work is part of the WT-486 "Interfaces for Automated Intelligent Management (AIM)"  It might make sense to coordinate this work, as the BBF work would likely highlight many of the use cases being outlined above.