Continuous Predictive Model for Quality of Experience in Wireless Video Streaming

  • Wenjuan ShiEmail author
  • Jinqiu Pan
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 302)


Because of bandwidth and buffer limitation in wireless network, rebuffering events and bitrate drop often cause video impairments, e.g. compression artifacts and video stalling. Hence, these problems often make a loss of the quality of experience (QoE). For making a prediction about the impact of video impairments on QoE, a continuous predictive model for QoE in wireless video streaming is proposed. In this paper, the inputs are composed of three vectors that are the quality of video frame, rebuffering events state and human memory effect, and the output represents the predicted continuous QoE. We build the predictive model by a Hammerstein-Wiener model. Experimental results show that the proposed model can accurately make a prediction about continuous subjective QoE.


Quality of experience (QoE) Continuous QoE Frame quality Rebuffering event Memory effect 


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Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2019

Authors and Affiliations

  1. 1.College of Physics and Electronical EngineeringYancheng Teachers UniversityYanchengChina
  2. 2.College of Telecommunications and Information EngineeringNanjing University of Posts and TelecommunicationsNanjingChina

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