Online Learning for QoE-based Video Streaming to Mobile Receivers

被引:0
|
作者
Changuel, Nesrine [1 ]
Sayadi, Bessem [1 ]
Kieffer, Michel [2 ,3 ]
机构
[1] Alcatel Lucent Bell Labs France, Route Villejust, F-91620 Nozay, France
[2] Univ Paris Sud, SUPELEC, CNRS, L2S, F-91192 Gif Sur Yvette, France
[3] Telecom ParisTech, CNRS, LTCI, F-75013 Paris, France
关键词
Cross-layer optimization; learning; QoE estimation; stochastic control; video streaming; SCHEDULING ALGORITHMS; WIRELESS;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper proposes a cross-layer control mechanism to stream efficiently scalable videos to mobile receivers. Its goal is to maximize the quality of the received video while accounting for the variations of the characteristics of the transmitted content and of the channel. The control problem is cast in the framework of Markov Decision Processes. The optimal actions to apply to the system are learned using reinforcement learning. For that purpose, the quality of the decoded frames at receiver is inferred by an observation (i) of the quality of the various scalability layers and (ii) of the level of queues at the Application and Medium Access Control layers of the transmitter only. Delayed as well as absence of information on the channel state are considered. Experiments show that the performance of the proposed solution is only slightly degraded with delayed or missing channel state information. The performance degradation is larger when considering a basic bitstream extractor, which serves as reference (1).
引用
收藏
页码:1319 / 1324
页数:6
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