Demo: Enhancing Network Performance based on 5G Network Function and Slice Load Analysis

The Fifth Generation Mobile Networks has transformed the paradigm of mobile network communications. In Beyond Fifth Generation Networks networks, Machine Learning (ML) and Artificial Intelligence (AI) are crucial components, optimizing network resource management to improve the network performance as well as end-users Quality of Service while lowering the network operating costs. This work makes use of an End-to-End 5G architecture to validate three demonstrations: 1) Radio Access Network monitoring using a Flexible RIC’s xApp; 2) 5G Core Network’s metrics collection via Capgemini Engineering’s Network Data Analytics Function; 3) Analysis of the Core Network’s collected data to predict Network Function load and Network Slice Instance load through the Capgemini Engineering’s NetAnticipate AI/ML engine.