Trans-RL: A Prediction-Control Approach for QoE-Aware Point Cloud Video Streaming

Cunhui Zhang, Yangjie Cao, Zhi Liu, Rui Yin, Yongdong Zhu, Xianfu Chen

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

Abstract

In point cloud video streaming systems, the field of view (FoV) prediction is critical for selecting the tiles, the objective of which is to optimize the expected long-term quality-of-experience (QoE) from the perspective of a user. On one hand, a satisfactory QoE accounts for not only the playback quality but also the playback smoothness. On the other hand, the large data volume of a selected tile requires the transmission to be adaptive to the system uncertainties. This paper applies a Markov decision process to formulate the problem of tile selection across the infinite discrete time horizon. In particular, a system state includes the FoV information, which is predicted from the Transformer. To alleviate the dependence on system uncertainty statistics, a deep reinforcement learning approach is derived for solving the optimal control policy. Under different settings, we conduct experiments based on the real throughput and head-mounted display data. The results show that compared to the existing baselines, our proposed prediction-control approach achieves a higher FoV prediction accuracy, better playback quality as well as smoothness, and hence a better average QoE for the user.

Original languageEnglish
Title of host publication2022 IEEE Global Communications Conference, GLOBECOM 2022
PublisherIEEE Institute of Electrical and Electronic Engineers
Pages1899-1904
ISBN (Electronic)978-1-6654-3540-6
ISBN (Print)978-1-6654-3541-3
DOIs
Publication statusPublished - 2023
MoE publication typeA4 Article in a conference publication
EventIEEE Global Communications Conference, GLOBECOM 2022: Accelerating the Digital Transformation through Smart Communications - Hybrid: In-Person and Virtual Conference, Rio de Janeiro, Brazil
Duration: 4 Dec 20228 Dec 2022

Conference

ConferenceIEEE Global Communications Conference, GLOBECOM 2022
Country/TerritoryBrazil
CityRio de Janeiro
Period4/12/228/12/22

Keywords

  • deep reinforcement learning
  • FoV prediction
  • Markov decision process
  • Point cloud video
  • quality of experience
  • Transformer

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