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Video Quality Prediction Model for H.264 Video over UMTS Networks and Their Application in Mobile Video Streaming

Universal Mobile Telecommunication System (UMTS) is a third generation mobile communication systems that supports wireless wideband multimedia applications. The objective of this paper is to present a new model for non-intrusive prediction of H.264 encoded video quality over UMTS networks and to illustrate their application to video quality monitoring and adaptation in mobile wireless streaming services. First, we present an efficient regression model for predicting video quality non-intrusively for all content types. The model is predicted from a combination of a set of objective parameters in the application and physical layer in terms of the Mean opinion Score (MOS). The application layer parameters considered are the content type, sender bitrate and frame rate and the physical layer parameters are the block error rate modeled with 2-state Markov model for a mean burst length of 1.75. The performance of the proposed metric is evaluated with unseen dataset with good prediction accuracy. Second, we illustrate the application of the model in mobile streaming services by presenting a new Sender Bitrate (SBR) adaptation scheme at pre-encoding stage that is Quality of Experience (QoE) driven. The scheme was tested and evaluated in the NS2 based UMTS simulation network. Extensive simulation results demonstrate the effectiveness of the proposed adaptation scheme in terms of the MOS and especially at the UMTS network bottleneck access where perceived video quality is most affected. The proposed scheme was responsive to available network bandwidth and congestion and adapted the SBR accordingly maintaining acceptable quality in terms of the MOS. The proposed scheme has applications in network planning and content provisioning for network/service providers.