GreenRAN : GenAI-Powered Autonomous Network with Self-Healing, enhanced Energy Efficiency and Climate Resilience
Project companies
Telecom operators face increasing challenges in maintaining reliable networks, especially amid environmental disruptions, natural disasters, and rising customer demands. To address these, this Phase II Catalyst is developing an AI-powered system that will transform network management by integrating fault, performance, and alarm management into a unified, automated framework.
This AI-powered system will:
- Swiftly diagnose faults by correlating data from network logs and user reports, significantly improving response times and reducing network downtime.
- Continuously monitor key performance indicators (KPIs) through machine learning algorithms, to identify patterns, predict potential performance issues, and recommend proactive measures to ensure network efficiency.
- Stremline alarm management by intelligently prioritizing alerts based on their severity and impact on service quality, enabling faster resolution and preventing service disruptions.
This Phase II Catalyst project builds on the Architectural Framework introduced in its previous phase. It aims to create a Knowledge Graph that maps relationships between network elements, topology, faults, and inventory data. This will enable predictive fault correlation, proactive decision-making, and closed-loop automation. We will also integrate TM Forum APIs into end-to-end service assurance workflows, automating manual processes and aligning with the principles of an Autonomous Network.
Moreover, the solution will focus on enabling intent-based RAN self-healing and optimization using event-driven automation and a Mixture-of-Agents approach. The AI system will leverage the Knowledge Graph to determine the next best actions, issue service requests, and manage network configuration autonomously, driving closed-loop operations.
The ultimate vision is to empower telecom operators with AI-driven intelligence to not only meet current demands but also anticipate future challenges. By employing machine learning, advanced analytics, and automation, we aim to create a smarter, more resilient telecom infrastructure that can thrive in the face of both environmental and operational challenges.
Resources
1. Project Submission
C24.5.750 - Project Presentation
2. Explore Previous Phases
GenAI Powered toolkit for network & service management - Phase I
3. Scope and Implementation Details
C24.5.750 - Orchestration layer architecture
C24.5.750 - RAN domain ontology
4. Articles, Brochures and Whitepapers
Waylay LLM-based Network Topology Traversal & Event Correlation Agent
Panamax Hybrid RAG Approach
5. Videos
C24.5.750 - Event correlation
C24.5.750 - AI-driven Unsupervised Event Handling
Contact team
Email the members of the Catalyst team to request more details.