Abstract

Telecommunication networks are ever more frequently relying on artificial intelligence and machine learning techniques to detect specific use patterns or potential errors and to take automated decisions when these are encountered. This concept requires that methods be employed to measure the level of quality of a given telecommunication service, i.e. to verify quality of service (QoS) metrics. In a broader context, methods assessing the entire user experience (quality of experience – QoE) are required as well. In this article, various approaches to assessing QoS, QoE and the related metrics are presented, with a view to implement these at an FTTH network operator in Poland. Since this article presents the architecture of the system used to analyze QoE performance based on a number of QoS metrics collected by the operator, we also provide a comprehensive introduction to the QoS and QoE metrics used herein.

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