Mobile Video Quality Assessment Method Based on AHP and Multiple Linear Regression

Abstract

The invention relates to a mobile video quality assessment method based on hierarchy analysis and multiple linear regressions. The method comprises the following steps: firstly, determining each layer of end-to-end performance indexes of user QoE (Quality of Experience) influencing mobile video services; dividing various end-to-end performance indexes of the QoE into a target layer, a criterion layer and an index layer by utilizing a hierarchy analysis method according to the attributes and the types of the performance indexes; respectively constructing hierarchical influence models in manners that the index layer is aligned to the criterion layer which is aligned to the target layer from bottom to top by utilizing the multiple linear regression analysis; constantly adjusting regression coefficients for influencing the models and various performance indexes of the models; and finally, establishing the influence model in the manner that the index layer is aligned to the target layer, i.e., establishing a total regression model influencing the quality of a mobile video according to various end-to-end performance indexes of QoE so as to assess the quality of the mobile video by utilizing the hierarchical total assessment model. According to the method, the subjective and objective performance indexes of the mobile video are combined with the QoE of the user, so that the method provided by the invention is a comprehensive and effective user experience quality assessment method.

Description

technical field [0001] The invention relates to a mobile video quality assessment method, more precisely, relates to a mobile video quality assessment method based on hierarchical analysis and multiple linear regression analysis, and belongs to the technical field of mobile communication. Background technique [0002] With the rise and wide application of wireless network technologies such as Wi-Fi, 3G and LTE, as well as the popularity of smart phones and tablet computers, the available wireless bandwidth of mobile terminals has increased significantly, and mobile video services have increased significantly. One of the mainstream businesses of domestic service providers. Mobile video quality has a great impact on user experience. How to evaluate its quality and truly reflect user experience is a problem that service providers pay attention to. Due to the complexity of the mobile video service itself and the lack of a complete evaluation system, it is difficult to evaluate ...

AI Technical Summary

Problems solved by technology

However, each of them has its limitations: it can only measure objective performance indicators, and cannot truly reflect the QoE (Quality of Experience) of mobile video users

However, this approach does not take into account the variability among performance metrics, which can vary greatly, resulting in increased dispersion of user quality of experience when mobile video quality is excellent or extremely poor

Therefore, it is difficult to establish an effective model when directly performing linear regression analysis by uniformly considering different types of performance indicators

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