NWDAF Use Cases
Operational Intelligence for 5G Standalone Networks
The Network Data Analytics Function (NWDAF) is defined by the 3GPP as a standard for using network data analytics in the 5G Core to drive network automation and service orchestration.
As mobile network operators (MNOs) scale out 5G standalone networks, the adoption of NWDAF will be guided by the operational requirements for achieving their business objectives.
MNOs need to know – in real time – how users and applications are impacting the 5G network, or how adverse network conditions or unusual device behavior is impacting users and applications. They also need to constantly monitor service experience metrics for each type of 5G service.
Guavus 5G-IQ NWDAF supports all of the 3GPP use cases.
5G-IQ NWDAF offers an open, multi-vendor, full-featured NWDAF that will interoperate with all 3GPP-compliant 5G Core components.
NWDAF Operational Intelligence
Performing statistical or predictive analytics on collected data and applying AI/ML algorithms, NWDAF generates real-time insights into the critical business values for MNOs:
- Network Conditions
- Device Behavior
- Service Experience
NWDAF Use Cases
Here is a quick run-down of the types of monitoring and analytics that NWDAF will perform. These use cases have been identified by the 3GPP in release 16, which was frozen in 2020.
Network Conditions
Real-time network monitoring is typically per slice and involves generating performance metrics such as throughput, latency, and connection setups, measuring network load and detecting congestion or other types of network performance anomalies.
Use cases:
- Network slice instance load level computation and prediction
- Load analytics information and prediction for a specific NF
- Network performance computation and prediction
- Congestion information – current and predicted for a specific location
- Quality of service (QoS) sustainability reporting and predicting QoS change
Device Behavior
Both human users and machines will be connected to the 5G network. 5G operations require monitoring device connectivity, mobility and communications patterns. Abnormal device usage or unanticipated behavior by human users or smart machines could have a negative impact on network performance.
Use cases:
- User equipment (UE) mobility analytics and expected behavior prediction
- UE abnormal behavior / anomaly detection
- UE communication analytics and pattern prediction
Service Experience
MNOs need to measure and track service experience to ensure that the 5G network is meeting user expectations and Service-Level Agreements (SLAs). NWDAF generated metrics will measure the current service experience by user, application type, device group or geographic location, and predict future changes.
Use cases:
- Service experience computation and prediction for an application or UE group
- Application service experience computation and prediction