2026-06-01T07:52:08Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/249882026-02-03T12:00:56Zcom_10630_2254col_10630_37959

00925njm 22002777a 4500 dc Peñaherrera-Pulla, Oswaldo Sebastián author Baena-González, José Carlos author Fortes-Rodríguez, Sergio author Baena-Martínez, Eduardo author Barco-Moreno, Raquel author 2022-09 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. https://hdl.handle.net/10630/24988 Realidad virtual - Congresos Sistemas multimedia - Congresos Estimación de KQIs para servicio de Vídeo - 360