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Volume 45 Issue 12
Dec.  2019
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Journal of Beijing University of Aeronautics and Astronautics  > 2019  >  45(12): 2385-2392.
Li Hanghang, Song Bifeng, Gao Hongjianet al. Computation method improvement of military training plane effectiveness[J]. Journal of Beijing University of Aeronautics and Astronautics, 2006, 32(06): 680-683. (in Chinese)
Citation: LI Jie, FENG Ransheng, YANG Yangzhao, et al. QoE driven adaptation for VR video capturing and transmission[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(12): 2385-2392. doi: 10.13700/j.bh.1001-5965.2019.0364(in Chinese)
shu

QoE driven adaptation for VR video capturing and transmission

doi: 10.13700/j.bh.1001-5965.2019.0364
  • 1.

    School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230000, China

  • 2.

    Academy of Electronics and Information Technology, China Electronics Technology Group Corporation, Beijing 100084, China

  • 3.

    School of Electrical Engineering and Automation, Hefei University of Technology, Hefei 230000, China

Funds:

National Natural Science Foundation of China 51877060

the Fundamental Research Funds for the Central Universities JZ2019HGTB0089

the Fundamental Research Funds for the Central Universities JZ2018HGTB0253

the Fundamental Research Funds for the Central Universities PA2019GDQT0006

More Information
  • Corresponding author: LI Jie. E-mail: lijie@hfut.edu.cn
  • Received Date: 08 Jul 2019
  • Accepted Date: 23 Aug 2019
  • Publish Date: 20 Dec 2019
    Abstract

  • In virtual reality (VR) video streaming media transmission, how to further improve user's quality of experience (QoE) under bandwidth-constrained conditions is a huge challenge. In order to improve resource utilization rate and user QoE, a multi-user QoE-driven uplink and downlink joint VR video streaming media adaptive acquisition and transmission system is proposed, which is different from the traditional VR video wireless transmission system. The proposed system considers the uplink transmission part. The video server selects code rate and allocates resources based on the rate adaptation based on the bandwidth information of the uplink channel and the downlink channel and the real-time view information of the user. In addition, we define the problem of QoE-driven rate selection and resource allocation to maximize the QoE value of all users across the system. Finally, we propose an optimal adaptive rate selection algorithm combining the KKT condition and the branch and bound method. The experimental results show that the system can effectively improve the QoE value of the total system users, improve the system performance by 14.27% based on the average uplink allocation, and improve the performance of the VR video rate adaptive algorithm by 23.47%.

     

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