MACHINE LEARNING FOR QOE PREDICTION AND ANOMALY DETECTION IN SELF-ORGANIZING MOBILE NETWORKING SYSTEMS

Existing mobile networking systems lack the level of intelligence, scalability, and autonomous adaptability required to optimally enable next-generation networks like 5G and beyond, which are expected to be Self -Organizing Networks (SONs). It is anticipated that machine learning (ML) will be instrumental in designingfuture “x”G SON networks with their demanding Quality of Experience (QoE) requirements. This paper evaluates a methodology that...