DocumentCode :
3541622
Title :
No-Reference QoE Prediction Model for Video Streaming Service in 3G Networks
Author :
Xin Yu ; Huifang Chen ; Wendao Zhao ; Lei Xie
Author_Institution :
Dept. of Inf. Sci. & Electron. Eng., Zhejiang Univ., Hangzhou, China
fYear :
2012
fDate :
21-23 Sept. 2012
Firstpage :
1
Lastpage :
4
Abstract :
User experience becomes a most crucial factor for the application and promotion of a new technology. Traditional quality of service (QoS) can only measure the objective quality of services and networks, while the quality of experience (QoE), which has become a hot topic in recent years, can reflect subjective feelings more directly from users´ perspective. In this paper, we investigate the QoE evaluation method of video streaming service in 3G networks, and propose a no-reference QoE prediction model of video streaming service based on the gradient boosting machine. Our proposed QoE prediction model considered comprehensive parameters from the network layer, the application layer, decoded videos and the user equipment. Simulation results show that the performance of our proposed QoE prediction model outperforms the G.1070 model, in terms of accurate predicted mean opinion score, small root mean squared error, and low time-consuming.
Keywords :
3G mobile communication; decoding; mean square error methods; quality of experience; quality of service; video coding; video streaming; 3G networks; G.1070 model; QoE evaluation method; QoS; application layer; gradient boosting machine; network layer; no-reference QoE prediction model; objective quality of services; predicted mean opinion score; quality-of-experience; root mean squared error; user equipment; user experience; video decoding; video streaming service; Computational modeling; Packet loss; Predictive models; Quality assessment; Quality of service; Streaming media;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Wireless Communications, Networking and Mobile Computing (WiCOM), 2012 8th International Conference on
Conference_Location :
Shanghai
ISSN :
2161-9646
Print_ISBN :
978-1-61284-684-2
Type :
conf
DOI :
10.1109/WiCOM.2012.6478588
Filename :
6478588
Link To Document :
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