Avaliação de Algoritmos de Aprendizado de Máquina para Predição de QoE em Redes 6G

Felipe S. Dantas Silva, M. Lima, Charles H. F. Santos, Augusto Neto
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Abstract

This paper evaluates the performance of Machine Learning (ML) algorithms to provide Quality of Experience (QoE) user decisions in multimedia services. A specialized dataset was built for mapping network Quality of Service (QoS) Key Performance Indicators (KPIs) with video quality metrics to perform QoE predictions. An evaluation is then carried out considering the main regression models to support the development of QoE-aware systems and meet the critical requirements of applications characteristic of 6G scenarios.
6G网络中QoE预测的机器学习算法评估
本文评估了机器学习(ML)算法在多媒体服务中提供体验质量(QoE)用户决策的性能。建立了一个专门的数据集,用于将网络服务质量(QoS)关键性能指标(kpi)与视频质量指标进行映射,以执行QoE预测。为支持qos感知系统的发展,满足6G场景应用特征的关键需求,对主要回归模型进行了评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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