Method for measuring QoE

Abstract

The invention relates to a method for measuring a QoE (quality of experience), which comprises the following steps: establishing a neural network of cascade structure according to a QoE evaluation model and training the neural network according to a tested and acquired sample database; judging whether the training output of the neural network meets the requirement, if not, updating the speed and position of particles by a PSO (particle swarm optimization) way, adjusting the weight of the neural network, and judging whether the test error of the QoE meets a preset value, and if so, completing the establishment of the QoE evaluation model and finally completing the measurement of the QoE. According to the method, a neural network model of cascade structure is adopted and whether to start a PSO algorithm is determined according to the training result of the neural network, so that the computing complexity of the model is minimized and the fitting precision is improved; and furthermore, the problems that the conventional neural network is slow in convergence speed, liable to fall into local minimum, too complicated in model and poor in precision are solved.

Description

technical field [0001] The invention relates to the field of wireless communication, in particular to a method for measuring user service experience quality. Background technique [0002] User service quality of experience or user perception (QoE) is the user's subjective experience of the service performance provided by the wireless network or the user's overall recognition of the service or service used in a certain objective environment. It can express the end user's experience and feelings on the service and network through a quantitative method, and reflect the gap between the current service and network quality and user expectations. The ultimate goal of wireless communication network services is to provide users with the best quality of service experience. [0003] Existing research on QoE generally focuses on audio and video services. According to whether there are users directly participating in the evaluation and whether the correlation model between QoE and its ...

AI Technical Summary

Problems solved by technology

[0007] The technical problem to be solved by the present invention is to provide a method for measuring the quality of user service experience, which solves the problem that the neural network in the current solution has a slow convergence speed and is easy to fall into a local minimum, which leads to an overly complicated model in the modeling process and the problem of low precision

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