The rapid proliferation of the Internet of Things (IoT), cloud-native applications, an‎d the deployment of 5G/6G cellular networks have introduced unprecedented complexity into modern communication infrastructures. Traditional network management paradigms, reliant on manual configuration an‎d static policies, struggle to cope with the volume, velocity, an‎d variety of emerging network traffic. This seminar provides a comprehensive review of the paradigm shift from reactive, script-based automation to proactive, AI-driven autonomous systems. We analyze the architectural frameworks, specifically focusing on the progression from manual operation (Level 0) to fully autonomous networks (Level 5). Furthermore, we explore core Artificial Intelligence (AI) techniques, including Machine Learning (ML), Deep Reinforcement Learning (DRL), an‎d Explainable AI (XAI), as key enablers for self-managing, self-healing, an‎d self-optimizing networks. The role of Intent-Based Networking (IBN) an‎d Network Digital Twins in bridging the gap between business objectives an‎d network operations is also critically examined. Finally, we address the security implications of zero-touch networks, offering a roadmap for future research in intelligent infrastructure..

2/18/2026 12:00:00 AM

89717

1404/11/29

A Review of AI-Driven Mobile Network Management: From Automation to Autonomous Systems

Autonomous Networks, , 5G/6G , AI-Driven Management, , Deep Reinforcement Learning (DRL) , Intent-Based Networking (IBN), , Zero-Touch Service Management (ZSM) , Explainable AI (XAI), , Network Digital Twins.