Hybrid Non-Reference QoE Prediction Model for 3D Video Streaming Over Wireless Networks

With the rapid growth in mobile device users, and increasing demand for video applications, the traffic from 2D/3D video services is expected to account the largest proportion of internet traffics. User’s perceived quality of experience (QoE) and quality of service (QoS) are the most important key factors for the success of video delivery. In this regard, predicting the QoE attracts high importance for provisioning of 3D video services in wireless domain due to limited resources and bandwidth constraints. This study presents a cross-layer no-reference quality prediction model for the wireless 3D video streaming. The model is based on fuzzy inference systems (FIS), and exploits several QoS key factors that are mapped to the QoE. The performance of the model was validated with unseen datasets and even shows a high prediction accuracy. The result shows a high correlation between the objectivley measured QoE and the predicted QoE by the FIS model.

@article{Alsukayti2018,
  title     = {Hybrid Non-Reference QoE Prediction Model for 3D Video Streaming Over Wireless Networks},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {9},
  number    = {11},
  year      = {2018},
  publisher = {The Science and Information Organization},
  author    = {Ibrahim Alsukayti and Mohammed Alreshoodi},
  doi       = {10.14569/IJACSA.2018.0911100},
  url       = {https://doi.org/10.14569/IJACSA.2018.0911100}
}