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Leveraging AI and machine learning to develop fully automated network operations which can self-optimise, adapt, and heal or configure themselves in specific contexts.

As we move into the 5G era and beyond, AI will play an increasingly essential role in future communication networks. It will be central to delivering the vision of a user-centric, cost-effective, energy-efficient network capable of meeting the needs of tomorrow’s connected society and digital economy. In particular, AI can enable fully automated network operations, improved control and management, and self-evolved intelligence that enables optimised resource utilisation and assured Quality of Experience (QoE) in dynamic environments, with minimal human intervention.

Intent based networking

Another area being explored is intent based networking (IBN): The realisation of an intelligent network management system that can automatically translate high-level intent expressed by network operators to actual machine-configurable solutions. Empowered by AI, IBN is expected to revolutionise traditional network management operations by replacing complex, error-prone human-oriented network configuration jobs with fully-automated network configurations.

As 5G technologies develop, greater data rates are demanded from limited radio spectrum resources, which is leading to an increased complexity in the design of network architecture. This makes configuring and managing a network very challenging. 5GIC is applying machine learning techniques in order to automatically identify malfunctioning of a network operation and provide meaningful information about the issues and root cause of the problem. The aim of this work is to give engineers access to rapid and useful information when unseen faults are found in the network.

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University of Surrey