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7th International Conference on Communications and Networking in China

Research Article

PNN-Based QoE Measuring Model for Video Applications over LTE System

Cite
BibTeX Plain Text
  • @INPROCEEDINGS{10.1109/ChinaCom.2012.6417448,
        author={Yuan He and Chao Wang and Hang Long and Kan Zheng},
        title={PNN-Based QoE Measuring Model for Video Applications over LTE System},
        proceedings={7th International Conference on Communications and Networking in China},
        publisher={IEEE},
        proceedings_a={CHINACOM},
        year={2012},
        month={9},
        keywords={quality of experience (qoe) video applications pnn lte},
        doi={10.1109/ChinaCom.2012.6417448}
    }
    
  • Yuan He
    Chao Wang
    Hang Long
    Kan Zheng
    Year: 2012
    PNN-Based QoE Measuring Model for Video Applications over LTE System
    CHINACOM
    IEEE
    DOI: 10.1109/ChinaCom.2012.6417448
Yuan He1,*, Chao Wang1, Hang Long1, Kan Zheng1
  • 1: Beijing University of Posts and Telecommunications
*Contact email: heyuan06622917@gmail.com

Abstract

Users’ quality of experience (QoE) is a key factor in the success of video applications over the Long Term Evolution (LTE) networks. Thus, evaluating the QoE of video applications is of tremendous importance in design and optimization of wireless video processing and transmission systems. In this paper, we propose a QoE measuring model for the quality of video applications by using probabilistic neural network (PNN). We conduct a subjective test, in which OPNET modeler is employed to build a system level simulation platform for the wireless network and distortion is added into original video sequences when transmitting on the platform. A subject pool is utilized to evaluate the distorted videos. Based on the subjective test, we create a distorted-video database. PNN is used to train the mapping function between the corresponding parameters and QoE. The results demonstrate the effectiveness of the proposed model and show that it can provide a high correlation rate with human perception.

Keywords
quality of experience (qoe) video applications pnn lte
Published
2012-09-13
Publisher
IEEE
http://dx.doi.org/10.1109/ChinaCom.2012.6417448
Copyright © 2012–2025 IEEE
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