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 language | English |
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Title of host publication | 2022 IEEE Global Communications Conference, GLOBECOM 2022 |
Publisher | IEEE Institute of Electrical and Electronic Engineers |
Pages | 1899-1904 |
ISBN (Electronic) | 978-1-6654-3540-6 |
ISBN (Print) | 978-1-6654-3541-3 |
DOIs | |
Publication status | Published - 2023 |
MoE publication type | A4 Article in a conference publication |
Event | IEEE 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 2022 → 8 Dec 2022 |
Conference
Conference | IEEE Global Communications Conference, GLOBECOM 2022 |
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Country/Territory | Brazil |
City | Rio de Janeiro |
Period | 4/12/22 → 8/12/22 |
Keywords
- deep reinforcement learning
- FoV prediction
- Markov decision process
- Point cloud video
- quality of experience
- Transformer