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Revolutionizing Connectivity: the power of AI in intelligent networks

Technology
Networks and Connectivity Artificial Intelligence
  • At Discovery – Future Network Labs, we are developing an exciting project called NAAS6G as part of the UNICO 5G program. This initiative will apply new concepts and methodologies for operating 5G+/6G networks across four use cases. Additionally, we have developed an internal OpenNWDAF, equipped with the capability to handle new events, thereby covering a broader range of use cases and complementing the capabilities of existing NWDAF solutions provided by current market vendors.

    1) Deployment of new network elements. In this use case, OpenNWDAF will analytically and predictively identify congestion scenarios, facilitating the deployment of new network elements to address load issues. This predictive analysis capability not only optimizes network resources but also intelligently manages their deployment, automating the provisioning task (Zero Touch Provisioning, ZTP).

    2) Identification of QoS Loss. Quality of Service (QoS) loss can be critical, especially for services sensitive to security and performance, such as autonomous vehicles. Using NWDAF events, performance patterns can be detected and analyzed in real-time, allowing operators to quickly identify any decrease in QoS. This enables proactive solutions to be implemented before end-users are affected, ensuring a consistent and high-quality network experience.

    3) Network congestion identification and prediction.
    Network congestion can significantly degrade performance and user satisfaction. By leveraging NWDAF, networks can predict potential congestion points before they occur. Analyzing real-time data and historical patterns, NWDAF helps in effectively redistributing traffic, avoiding bottlenecks, and maintaining efficient data flow. 

    4) High traffic event detection. Unexpected high traffic events, such as live sports broadcasts or popular product launches, can challenge network capacity. NWDAF allows operators to detect these traffic spikes in real-time and adjust network resources accordingly. This rapid response capability ensures the network can handle sudden demand increases without sacrificing service quality. 

    Throughout these use cases, we will see how NWDAF not only optimizes network management but also anticipates issues before they become problems, ensuring a more robust and efficient network for all users. 
NWDAF Usage Architecture

NWDAF Usage Architecture

Link to NAAS6G project https://www.linkedin.com/company/naas6g/about/

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