AI drives smarter and self-managing 6G mobile networks
Toward Fully Autonomous 6G Networks: AI-driven Operational Efficiency and Optimization
Networking and Internet Architecture
Summary
Mobile networks are becoming more complex because they support many different types of services on the same infrastructure. The authors study how future 6G networks can use artificial intelligence to manage themselves better and save energy. They focus on combining AI with new service models called Network as a Service (NaaS), which lets outside developers use network capabilities easily. Their solution is a smart system that interprets network goals and manages both outside requests and internal policies automatically. This approach aims to make 6G networks more efficient, flexible, and autonomous.
6G networksartificial intelligence (AI)Radio Access Network (RAN)Network as a Service (NaaS)network automationorchestration frameworkenergy optimizationintent-based policiesnetwork managementautonomous control
Authors
David Reiss, Oriol Sallent, Miguel Catalan-Cid, Daniel Camps-Mur
Abstract
Mobile networks evolution is characterized by a substantial increase in system complexity, driven by the need to accommodate a growing number of heterogeneous services on top of the digital infrastructure. This growth in service accommodation is expected to accelerate with the adoption of the Network as a Service (NaaS) paradigm, which has emerged as a promising approach to accelerate network innovation while enabling new revenue streams for operators. Although it is fundamental to abstract network capabilities for third-party developers, it poses significant challenges in terms of efficient network operation. To address this increased complexity, future mobile networks are envisioned to be inherently Artificial Intelligence (AI)-native. In particular, the integration of AI within the Radio Access Network (RAN) becomes a key enabler for optimizing operation, energy consumption, and autonomous network control. In this context, this research explores the convergence of AI-native RAN and NaaS ecosystems to enable autonomous 6G RAN management. We propose an Agentic-based orchestration framework capable of interpreting intent-based policies. The proposed framework becomes key to integrate external NaaS requests with internal network management policies.