Learning from experience: A dynamic closed-loop QoE optimization for video adaptation and delivery

Imen Triki, Rachid El-Azouzi, Majed Haddad, Quanyan Zhu, Zhiheng Xu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The quality of experience (QoE) is known to be subjective and context-dependent. Identifying and calculating the factors that affect QoE is indeed a difficult task. Recently, a lot of effort has been devoted to estimate the users' QoE in order to improve video delivery. In the literature, most of the QoE-driven optimization schemes that realize trade-offs among different quality metrics have been addressed under the assumption of homogenous populations. Nevertheless, people perceptions on a given video quality may not be the same, which makes the QoE optimization a hard task. This paper aims at taking a step further in order to address this limitation and meet users' profiles. Specifically, we propose a closed-loop control framework based on the users' (subjective) feedbacks to learn the QoE function and optimize it at the same time. Extensive simulation results show that the proposed scheme converges to a steady state, where the resulting QoE function noticeably improves the users' feedbacks.

Original languageEnglish (US)
Title of host publication2017 IEEE International Symposium on Personal, Indoor and Mobile Radio Communications
Subtitle of host publicationEngaged Citizens and their New Smart Worlds, PIMRC 2017 - Conference Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-5
Number of pages5
ISBN (Electronic)9781538635315
DOIs
StatePublished - Feb 14 2018
Event28th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2017 - Montreal, Canada
Duration: Oct 8 2017Oct 13 2017

Publication series

NameIEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC
Volume2017-October

Other

Other28th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2017
CountryCanada
CityMontreal
Period10/8/1710/13/17

Keywords

  • Average video quality
  • Learning
  • Neural network
  • QoE
  • Rebuffering delay
  • Startup delay
  • Video quality switching
  • Video stalls

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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