VIAVI’s digital twin technology lets telecom operators safely test AI in virtual networks

Digital twins are emerging as essential tools for testing AI integration in telecommunications networks, offering realistic virtual environments to validate complex technologies before deployment. VIAVI Solutions is pioneering this approach with its RAN Digital Twin, which creates a comprehensive virtual replica of radio access networks by combining synthetic traffic with real data from various sources to ensure AI algorithms make correct decisions in network environments.

The big picture: Telecom operators face increasing complexity in testing AI features within their networks, driving innovation in validation tools that can simulate real-world conditions.

• VIAVI’s RAN Digital Twin solution allows operators to create accurate virtual replicas of network elements or segments, synchronized with real-time data from the actual network.
• This builds upon the established strategy of emulation but takes it further by integrating AI and machine learning capabilities.

Key capabilities: The VIAVI RAN Digital Twin creates a virtual version of an operator’s radio access network powered by TeraVM AI RSG technology.

• The system combines synthetic traffic with real data from probes, sensors, and third-party sources like traffic and weather reports.
• It can simulate thousands of user equipment devices and cells while supporting the import of real-world maps and network configurations.

Why this matters: Digital twins enable safe experimentation in virtual environments before deploying changes to live networks.

• According to VIAVI CTO Sameh Yamany, “We’re making sure that any AI algorithms that are put into that network are actually making the right decisions.”
• The technology allows operators to test complex scenarios that aren’t suitable for simple pass/fail validation, particularly important as networks incorporate more AI features.

Future implications: The development of RAN digital twins is laying groundwork for more comprehensive network simulation capabilities.

• Yamany notes that “RAN digital twins are shaping what the overall network digital twin will look like,” suggesting a path toward potentially replicating entire networks digitally.
• The ability to generate various traffic demand profiles and radio conditions supports thorough testing of how AI will perform across different network scenarios.