QoE model for video delivered over an LTE network using HTTP adaptive streaming

2014 ◽  
Vol 18 (4) ◽  
pp. 45-62 ◽  
Author(s):  
Johan De Vriendt ◽  
Danny De Vleeschauwer ◽  
Dave C. Robinson
Keyword(s):  
Adaptive Streaming ◽  
Lte Network ◽  
Http Adaptive Streaming ◽  
Qoe Model

Improving QoE and Fairness in HTTP Adaptive Streaming Over LTE Network

2016 ◽  
Vol 26 (12) ◽  
pp. 2284-2298 ◽  
Author(s):  
Sergio Cicalo ◽  
Nesrine Changuel ◽  
Velio Tralli ◽  
Bessem Sayadi ◽  
Frederic Faucheux ◽  
...  
Keyword(s):  
Adaptive Streaming ◽  
Lte Network ◽  
Http Adaptive Streaming

scholarly journals Enhancing QoE for Mobile Users by Environment-Aware HTTP Adaptive Streaming

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3645 ◽  
Author(s):  
Weizhan Zhang ◽  
Hao He ◽  
Shuyan Ye ◽  
Zhiwen Wang ◽  
Qinghua Zheng
Keyword(s):  
Video Quality ◽  
Rate Adaptation ◽  
Dynamic Network ◽  
Mobile Users ◽  
Adaptive Streaming ◽  
Adaptation Algorithm ◽  
Model Driven ◽  
Http Adaptive Streaming ◽  
Qoe Model

HTTP adaptive streaming (HAS) has become a dominated media streaming paradigm in today’s Internet, which enriches the user’s experience by matching the video quality with the dynamic network conditions. A range of HAS mechanisms have been proposed to enhance the Quality of Experience (QoE). However, existing mechanisms ignore the environmental impact in the QoE evaluation of mobile users, while the popularity of mobile video allows users to watch videos in diversified scenarios. In this paper, we propose an environment-aware HAS scheme that fully concentrates on the different criteria for evaluating video QoE under different environments. Using the advantage of the sensors in mobile phones, the scheme constructs and validates a video QoE model based on environment perception and then designs a model-driven, environment-aware HAS rate adaptation algorithm. We also evaluate the scheme with an environment-aware DASH (Dynamic Adaptive Streaming over HTTP) player in real mobile environments. Compared to the benchmark HAS mechanism, the experimental results demonstrate that our scheme can provide appropriate differentiated rate adaptation for different environments, resulting in a higher QoE.

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