Enhancing Quality of Experience (QoE) assessment models for video applications

Video applications are becoming the key services in today's networks (both fixed networks and mobile networks). Consideration of video service quality has become essential to provide the end users with satisfying Quality of Experience (QoE). In order to evaluate and manage the video quality, methods for QoE assessment are desired to estimate the service quality perceived by the end users. In this paper, we study a number of existing objective quality assessment models for assessing the QoE of video applications, and compare their performance with simulations to find out their individual advantages and limitations to use in practice. To overcome the shortcomings of the existing models, this paper proposes an enhanced QoE model which considers a wide range of codec rates and video formats, and moreover considers the packet losses and video content dependence in quality assessment. Simulation results show that the proposed QoE model can be applied for evaluating the quality of different video sources in the Long Term Evolution (LTE) networks, considering the lossy property of mobile networks. In addition to the objective QoE methods, we also plan to carry out subjective tests in the lab as well as in the real system for the subjective evoluation of QoE.