AI-Driven Automation and Self-Healing Mechanisms in 5G Core Networks for Reliable Telecom Operations under Vision 2030
The study presents an overview of automation technologies that are self-healing methods applied in stand-alone 5G Core telecommunications systems required for providing reliable communications in Saudi Vision 2030 conditions. Literature surveys covering the period 2020-2025 have been done in research domains like cloud-native 5G Core design, SBA, NDAF roles, closed-loop assurance, AI-based anomalies detection and localization, root cause analysis, policy management, edge computing, and automation. It is shown in the paper that the 5G Core is much more than a pure packet router and, in fact, represents a state-of-the-art platform which allows predicting network performance degradation, localize faults, and execute repair processes without any impact on user services and industrial operations. The focus of the review is on Saudi Arabia, where the country's oil and gas industry, mining sector, transport, manufacturing industries, smart city initiatives, and giga projects require reliable connectivity, deterministic performance, and secure digital infrastructure. Based on the findings of the literature survey, it is possible to conclude that the self-healing feature of stand-alone 5G Core can be achieved with the help of the following three capabilities being implemented jointly: telemetry trustworthiness, explainable AI for decision-making, and automation policies enforcement. In the proposed Saudi Arabia-specific solution, the relationship between NWDAF, cloud-native NFs, MEC, slicing assurance, and operation management will be discussed.