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Telecom news: Cirrus360, Vodafone, Pegatron, Wind River, Open RAN

Today’s telecom news includes announcements on Cirrus360, Vodafone, Pegatron, Wind River, Open RAN, among others.

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AI Revolution in RAN: Cirrus360 and Vodafone Unveil Smart Digital Twin for Faster Network Deployment

Cirrus360 and Vodafone have unveiled an AI reasoning-driven declarative digital twin platform aimed at transforming radio access network (RAN) integration and testing. The solution creates a virtual model of real-world network systems to predict potential failures, optimize configurations, and improve alignment between Open RAN software and hardware before deployment. Powered by Cirrus360’s cloud-based Gabriel platform, it leverages AI and domain-specific models of 5G and emerging 6G protocols to automate system validation and forecast performance and resource issues.

Pegatron Ignites the ‘IQ Era’ with AI-Driven 5G Breakthroughs at MWC 2026

At Mobile World Congress 2026, Pegatron highlighted its vision for the “IQ Era,” blending advanced connectivity with embedded intelligence. The company introduced a portfolio of AI-powered 5G and edge computing solutions designed to enable real-time data processing and smarter enterprise operations. Key showcases included the PR2850 macro radio supporting wide-area Open RAN deployments and the PS2400 “network-in-a-box,” built for rapid setup in remote or emergency scenarios. Pegatron also presented its AI-RAN approach, integrating artificial intelligence directly into network architecture to deliver low-latency, resilient connectivity tailored for demanding industrial and enterprise environments.

Wind River and Vodafone Power the Future of AI-Driven Open RAN

Wind River and Vodafone have announced a strategic collaboration to scale AI-driven Radio Access Network (AI-RAN) operations for Open RAN environments, with demonstrations planned at MWC Barcelona 2026. The partnership integrates Vodafone’s 5G O-Cloud platform with Wind River’s Cloud Platform and advanced analytics to process large volumes of real-time network data. By applying AI models to understand normal network behavior, the solution can rapidly detect anomalies and predict potential issues faster than conventional systems.

SHAFANA FAZAL

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