Integrating Generative AI for Enhanced Network Operations, Monitoring, and Incident Management in Communication Networks

Abstract

The increasing complexity of modern communication networks has created significant challenges for traditional operational and management frameworks. This paper examines the role of Generative Artificial Intelligence (GenAI) in improving network operations, monitoring, and incident management. We present a framework that integrates large language models (LLMs) with diffusion-based synthetic data generation to support predictive maintenance, automated incident handling, and real-time network optimization. The proposed solution focuses on reducing operational delays, improving fault detection accuracy, and increasing service reliability in 5G, IoT, and emerging 6G environments. By incorporating intelligent automation, closed-loop control, and adaptive learning, GenAI emerges as a key technology for enabling more autonomous and resilient communication networks.