Continuous Prediction for Quality of Experience in Wireless Video Streaming

Due to the rapid development of communication technologies, the requirement of mobile video streaming services is extremely increased in recent years. However, the bandwidth limitation of the wireless network often causes video impairments, such as compression artifacts and rebuffering event, when users are watching online videos. Hence, this problem often causes the reduction of quality of experience (QoE). Predicting the QoE can provide a reference to improve resource allocation strategies, accordingly providing users with a higher quality of video streaming services. In order to predict the impact of video impairment, continuous prediction for the QoE in wireless video streaming is proposed. The input of the predicted model consists of three vectors that characterize frame quality, the state of rebuffering events, and memory effect, respectively, while the output consists of continuous predicted the QoE. The predicted model uses a block-structured nonlinear Hammerstein-Wiener model. The experimental results confirm that our proposed model can effectively predict the continuous QoE for wireless video streaming.