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无线网络中的视频丢失预测模型。

Video loss prediction model in wireless networks.

机构信息

Department of Computation, Federal University of South and Southeast of Pará, Marabá, Pará, Brazil.

Department of Computation, Federal University of Pará, Belém, Pará, Brazil.

出版信息

PLoS One. 2019 Mar 6;14(3):e0212407. doi: 10.1371/journal.pone.0212407. eCollection 2019.

Abstract

This work discusses video communications over wireless networks (IEEE 802.11ac standard). The videos are in three different resolutions: 720p, 1080p, and 2160p. It is essential to study the performance of these media in access technologies to enhance the current coding and communications techniques. This study sets out a video quality prediction model that includes the different resolutions that are based on wireless network terms and conditions, an approach that has not previously been adopted in the literature. The model involves obtaining Service and Experience Quality Metrics, such as PSNR (Peak Signal-to-Noise Ratio) and packet loss. This article outlines a methodology and mathematical model for video quality loss in the wireless network from simulated data and its accuracy is ensured through the use of performance metrics (RMSE and Standard Deviation). The methodology is based on two mathematical functions, (logarithmic and exponential), and their parameters are defined by linear regression. The model obtained RMSE values and standard deviation of 2.32 dB and 2.2 dB for the predicted values, respectively. The results should lead to a CODEC (Coder-Decoder) improvement and contribute to a better wireless networks design.

摘要

本文讨论了通过无线网络(IEEE 802.11ac 标准)进行视频通信。视频有三种不同的分辨率:720p、1080p 和 2160p。研究这些媒体在接入技术中的性能对于增强当前的编码和通信技术至关重要。本研究提出了一种视频质量预测模型,该模型包括基于无线网络条件的不同分辨率,这在文献中尚未采用过。该模型涉及获取服务和体验质量指标,如 PSNR(峰值信噪比)和数据包丢失。本文概述了一种从模拟数据中评估无线网络中视频质量损失的方法和数学模型,并通过使用性能指标(RMSE 和标准差)来确保其准确性。该方法基于两个数学函数(对数和指数),其参数通过线性回归定义。该模型获得的 RMSE 值和预测值的标准差分别为 2.32dB 和 2.2dB。研究结果应有助于提高编解码器(Coder-Decoder)性能,并有助于设计更好的无线网络。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/663e/6402757/a66b672c5c26/pone.0212407.g001.jpg

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