A QoE Prediction Model Combining Network Parameters and Video Quality

Jinfan Zhao, Shufeng Li, Feng Hu
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Abstract

The advent of the 5G era and the theater performing arts market woes caused by Corona Virus Disease 2019 (COVID- 2019) epidemic have accelerated the emergence and growth of the cloud performing arts business. To improve the quality of service for cloud performing arts and live performances, it is critical to develop a predictive model that accurately and timely reflects the Quality of Experience (QoE). In this paper, we first filter three of the seven recognized application layer Quality of Service (QoS) parameters that represent the input network quality in this QoE prediction model. Then one of the four different video quality evaluation methods is selected as the most effective method to represent the video quality. The purpose of combining network quality and video quality is to build a more accurate and effective QoE prediction model.
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结合网络参数和视频质量的QoE预测模型
5G时代的到来和2019冠状病毒病(COVID- 2019)疫情引发的剧场演艺市场低迷,加速了云演艺事业的出现和发展。为了提高云表演艺术和现场表演的服务质量,开发准确及时反映体验质量(QoE)的预测模型至关重要。在本文中,我们首先过滤了七个公认的应用层服务质量(QoS)参数中的三个,这些参数代表了该QoS预测模型中的输入网络质量。然后从四种不同的视频质量评价方法中选择一种作为最有效的视频质量评价方法。将网络质量与视频质量相结合的目的是为了建立更准确有效的QoE预测模型。
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