The Aarna Networks Multi-Cluster Orchestration Platform (AMCOP) performs orchestration, lifecycle management, and analytics/closed-loop automation for cloud-native 5G network services and edge computing applications. The last part of the functionality is through a component called the Aarna Analytics Platform (AAP). The AAP uses open source software from ONAP DCAE (Data Collection Analytics and Events) and the DMaaP (Data Movement as a Platform, which is based on Kafka). Aarna Analytics Platform includes both the 3GPP NWDAF and the O-RAN Non-Real-Time Radio Intelligent Controller (Non-RT RIC) functionality.
NWDAF or Network Data Analytics Function provides analytics to 5G Core Network Functions (NFs) and the OAM platform. NWDAF has 3GPP defined interfaces using which NFs can request analytics information. There can be multiple instances of NWDAF deployed in the 5G Core. Each NWDAF is identified by the NF-ID and the Analytics ID. Like other NFs, NWDAF registers itself with NRF (Network Repository Function) of the 5G Core, enabling other NFs to reach it.
Figure 1 - NWDAF Architecture
NWDAF provides statistics and predictions. For prediction, it can make use of ML models, which would be embedded into NWDAF. This ML Model can address specific use cases of 5G .
The Non-RT RIC is a component in the Service Management and Orchestration (SMO) framework specified by the O-RAN Alliance. It enhances the functionality of the RAN by communicating with the Near Real Time RIC (Near-RT RIC) which resides in the edge/remote cluster. The Non-RT RIC provides policies and enrichment information for the RAN to the Near-RT RIC over the A1 interface. The Non-RT RIC is an extensible platform and includes modular applications called rApps. These modular apps can be added in the Non-RT RIC based on specific use cases. Along with rApps, the Non-RT RIC contains A1 Policy function, A1 Enrichment Function and A1 Termination Function. The Non-RT RIC provides enrichment information and the latest A1 policies to the Near-RT RIC over the A1 interface. Using rapid closed-loop automation, the Non-RT RIC can also enable additional advanced SON use-cases. The Non-RT RIC also includes AI/ML functions.
Figure 2 - Non-RT RIC Architecture
Thus, AMCOP is capable of orchestrating NWDAF in the 5G Core and AMCOP also has the SMO functionality for O-RAN and thus includes the Non-RT RIC functionality. AMCOP utilizes ML models but is not capable of training these models or managing the lifecycle of these models as mentioned above. In order to address the gap Aarna Networks has partnered with Pradera. AMCOP along with Predera’s MLOps AIQ platform serves end-to-end use cases of NWDAF and Non-RT RIC.
AMCOP provides raw training data to Predera’s MLOps AIQ platform by sending telemetry data (metrics, logs, alarms, events) to an external datalake. AIQ uses this raw data to train ML models. These ML models are stored in a catalog such as the LF AI Acumos project. AMCOP then pickes up these MLOps models and uses them for use cases such as the Non-RT RIC, NWDAF, closed-loop automation, and more.
To learn more about Aarna Networks AMCOP, Non-RT RIC, or NWDAF offerings, please contact us. Alternatively, if you are an rAPP vendor that wants to collaborate with us, please do not hesitate to contact us.
To learn more about the AIQ platform, please contact Predera.
Figure 3 - End-to-end NWDAF Implementation
Figure 4 - End-to-end Non RT RIC Implementation