The 6G-Cloud project has published a new article on Medium detailing the technological breakthroughs driving its approach to next-generation network design. Written by Dr. Nikos Dimitriou (NCSRD), Technical Manager of 6G-Cloud, the piece outlines how the project is shaping a cloud-native, AI-driven architecture for 6G networks. This architecture places intelligence, flexibility and service composition at the core of future network infrastructures.
Cloud-Native RAN and Core for Dynamic Service Provisioning
At the heart of 6G-Cloud’s vision lies a fully elastic, cloud-native architecture for both RAN and Core networks. Built on a service-based model, the project introduces a dynamic control fabric for RAN that enables scalable and resilient deployment of Control Plane Network Functions (CP NFs). These functions interact flexibly across domains with diverse latency and reliability requirements, ensuring fine-grained, real-time control of network services.
Through a smart discovery, selection, and placement process, the most suitable NFs are automatically orchestrated to meet end-to-end service demands. This includes the definition of service descriptors and AI-assisted deployment across the cloud continuum — paving the way for highly adaptable and efficient network operation.
Intelligent Exposure with 6C-nApps and 6CEL
The project also introduces 6C-nApps, intelligent, AI/ML-driven applications deployed within the RAN and Core that enable secure exposure of network data and control to third parties, verticals and external frameworks. These components support programmability, configuration and interworking between systems like MEC and O-RAN, unlocking new avenues for external innovation and application-aware networking.
Supporting this is the 6G-Cloud Exposure Layer (6CEL), a comprehensive framework that governs how network insights are exposed, integrating exposure servers, client components and compatibility with existing standards such as SEAL, CAPIF and EES.
Network Digital Twins for Reliable AI-Driven Networks
To validate and optimise AI/ML integration, 6G-Cloud leverages Network Digital Twins (NDTs) — real-time virtual representations of network components. These enable predictive analysis, anomaly detection and simulation-based training of AI models without impacting live systems. Embedded within the AI/ML Framework (AIMLF), NDTs support intelligent decision-making across the management and orchestration layers, from service scaling and routing to dynamic function placement.
Towards a Sustainable, Programmable 6G Future
The Medium article underscores how 6G-Cloud’s architecture supports flexibility, ultra-low latency, and seamless integration across heterogeneous infrastructures. By embedding native AI capabilities, the system offers real-time adaptation, energy efficiency and self-optimisation — all crucial for a sustainable and programmable 6G ecosystem.
📖 Read the full article here: Technological Advances for 6G Networks: The 6G-Cloud approach
