Adaptive Cooperative Streaming of Holographic Video Over Wireless Networks: A Proximal Policy Optimization Solution
<|reference_start|>Adaptive Cooperative Streaming of Holographic Video Over Wireless Networks: A Proximal Policy Optimization Solution: Adapting holographic video streaming to fluctuating wireless channels is essential to maintain consistent and satisfactory Quality of Experience (QoE) for users, which, however, is a challenging task due to the dynamic and uncertain characteristics of wireless networks. To address this issue, we propose a holographic video cooperative streaming framework designed for a generic wireless network in which multiple access points can cooperatively transmit video with different bitrates to multiple users. Additionally, we model a novel QoE metric tailored specifically for holographic video streaming, which can effectively encapsulate the nuances of holographic video quality, quality fluctuations, and rebuffering occurrences simultaneously. Furthermore, we formulate a formidable QoE maximization problem, which is a non-convex mixed integer nonlinear programming problem. Using proximal policy optimization (PPO), a new class of reinforcement learning algorithms, we devise a joint beamforming and bitrate control scheme, which can be wisely adapted to fluctuations in the wireless channel. The numerical results demonstrate the superiority of the proposed scheme over representative baselines.<|reference_end|>
@article{wen2024adaptive,
    title={Adaptive Cooperative Streaming of Holographic Video Over Wireless
  Networks: A Proximal Policy Optimization Solution},
    author={Wanli Wen, Jiping Yan, Yulu Zhang, Zhen Huang, Liang Liang, and
  Yunjian Jia},
    journal={arXiv preprint arXiv:2406.08806},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.08806},
    primaryClass={eess.SY cs.SY}
}