The evolution of mobile networks has led to great opportunities for the development of cutting-edge services. One of these is 360-Video, which is an application of VR (Virtual Reality) technology that intends for displaying immersive multimedia content. This work presents a framework that enables the estimation of Key Quality Indicators (KQI), through the use of ML (Machine Learning) mechanisms, based on Key Performance Indicators (KPI) and network configuration parameters. This methodology aims to quantify metrics that are useful for Quality of Experience evaluation using objective perspectives. The algorithms’ performance is assessed through MAE (Mean Average Error) in two estimation scenarios, per- sample and session average. The results describe the algorithms’ performance of KQI estimation for 360-video over LTE service.
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