RADCOM Closed Loop Automation

RADCOM Closed-Loop Automation delivers a standards-compliant, vendor-agnostic solution that enables telecom operators to automate operations seamlessly across the 5G Core and RAN. It can also be deployed as a Management Data Analytics Function (MDAF), supporting 3GPP-defined use cases from Releases 17 and 18, as well as extended, advanced use cases tailored to operator needs.

“By deploying RADCOM, we can automatically
prevent a drop in service quality or connectivity issues to ensure
our customers receive top-quality services.”

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RADCOM Closed Loop Automation is fully containerized and integrated with the Network Repository Function (NRF), which streamlines the production and consumption of network data. It generates insights and triggers closed-loop actions to enhance the customer experience.

RADCOM Closed-Loop Automation provides all the use cases defined in Rel. 17 and 18, as well as offering customer-driven use cases such as analytics as a service, predicted coverage QoE impact, mass call event optimization, automated disaster recovery, and more.

RADCOM Closed-Loop Automation is designed to help accelerate efficient operations and transition to autonomous networks and closed-loop automation. Its centralized analytics system provides a distinctive value proposition, lowering the total cost of operations, creating new closed-loop automation opportunities, and driving superior customer experiences. RADCOM’s integrated artificial intelligence and machine learning (AI/ML) capabilities are at the heart of the solution, facilitating predictive analytics to enhance real-time network operations and deliver unparalleled customer experiences.

Flexible solution architecture

RADCOM can provide the following deployment options to operators:

A 3GPP-defined architecture that includes standard APIs and network interfaces.
An extended solution that includes closed-loop options, additional interfaces, and probe data ingestion.
A lightweight NWDAF deployment with a front-end NWDAF deployed in the core. While the heavy lifting is performed outside the core via a centralized back-end.

Advanced-built AI

RADCOM Closed-Loop Automation also extends beyond the 3GPP-defined AI framework, which focuses on predictive analytics. With RADCOM NWDAF powered by RADCOM AIM (AI module), the operator also benefits from additional artificial intelligence (AI) and machine learning (ML) driven use cases such as AI-powered anomaly detection and automated root cause analysis.

RADCOM AIM provides this without any need to configure thresholds. So, once RADCOM’s solution is deployed on the network, it learns baseline behavior and automatically creates thresholds. If an anomaly is detected a closed-loop task is activated by sending a notification to third party network functions or the operations, administration, and maintenance (OAM), which facilitates corrective action using a zero-touch process with no human interaction.