AutoNetTest: A Platform-Aware Framework for Intelligent 5G Network Test Automation and Issue Diagnosis

The rapid evolution of 5G networks introduces intricate challenges in testing and diagnosis, necessitating effective solutions for robust operation. We introduce AutoNetTest, a groundbreaking framework that streamlines test automation through intelligent, platform-aware design. This framework integrates sophisticated machine learning methodologies, allowing for automatic detection of network issues and facilitating thorough diagnostics. With its modular architecture, AutoNetTest is capable of adapting to a variety of platforms, ensuring flexibility in diverse environments. Real-time data analytics play a crucial role in the system, enabling continuous monitoring of network performance and timely anomaly detection. By utilizing both supervised and unsupervised learning techniques, the framework efficiently classifies issues and offers actionable remediation strategies, underscoring a proactive approach to network quality management.