Agentic AI for self-deployable 6G networks in the edge-cloud continuum

Research Project, 2025 – 2027

The rollout of 6G networks presents significant challenges due to their disaggregated nature, requiring the deployment and meticulous configuration of heterogeneous software entities and applications across diverse, different operator and edge-cloud environments. Current methods, reliant on fixed rules, struggles with this complexity and the difficulty of fully understanding target environments in advance. This makes traditional, human-centric deployment too slow and costly for the scale of 6G. This project proposes an innovative agentic AI system capable of autonomously deploying these 6G software entities and applications in edge-cloud environments. The system will feature AI agents, powered by locally run Large Language Models (LLMs), designed to discover current environmental conditions, probe on-demand for more information, and execute necessary deployment actions (e.g., software installation). These agents will operate online or offline depending on the case, crucial for private operator environments. A knowledge base will provide details about the 6G entities and applications, while a comprehensive test suite will validate successful deployment. By intelligently navigating unknown environments and automating complex configurations and optimization objectives, this solution enables faster, more reliable, performant, and cost-effective 6G rollouts, significantly reducing human intervention and paving the way for self-deploying networks and applications.