Motion-Prediction-based Wireless Scheduling for Multi-User Panoramic Video Streaming
Motion-Prediction-based Wireless Scheduling for Multi-User Panoramic Video Streaming
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DOI：
10.1109/infocom42981.2021.9488771
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发表时间：
2021-05
期刊：
影响因子：
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通讯作者：
Jiangong Chen;Xudong Qin;Guangyu Zhu;Bo Ji;Bin Li
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文献类型：
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作者：
Jiangong Chen;Xudong Qin;Guangyu Zhu;Bo Ji;Bin Li
在相同分辨率下，多用户全景视频流需要4 ~ 6倍的普通视频带宽，这对无线调度设计提出了很大的挑战。另一方面，最近的研究表明，人们可以有效地预测用户的视野（FoV），从而简单地提供相应的部分，而不是整个场景。基于这一重要事实，我们的目标是采用自回归过程进行运动预测，并将用户成功观看的概率分析表征为交付部分的函数。然后，我们考虑了无线调度设计的问题，其目标是在最小所需的服务率和无线干扰约束下最大化应用级吞吐量（即成功查看所需内容的平均速率）和服务规律性性能（即每个用户成功查看的频率）。因此，我们将用户的成功查看概率纳入我们的调度设计中，并开发了一种调度算法，该算法不仅渐近地实现了最优的应用级吞吐量，而且提供了服务规律性的保证。最后，我们使用用户头部运动的真实数据集进行仿真，以证明我们提出的算法的效率。
Multi-user panoramic video streaming demands 4∼6× bandwidth of a regular video with the same resolution, which poses a significant challenge on the wireless scheduling design to achieve desired performance. On the other hand, recent studies reveal that one can effectively predict the user’s Field-of-View (FoV) and thus simply deliver the corresponding portion instead of the entire scenes. Motivated by this important fact, we aim to employ autoregressive process for motion prediction and analytically characterize the user’s successful viewing probability as a function of the delivered portion. Then, we consider the problem of wireless scheduling design with the goal of maximizing application-level throughput (i.e., average rate for successfully viewing the desired content) and service regularity performance (i.e., how often each user gets successful views) subject to the minimum required service rate and wireless interference constraints. As such, we incorporate users’ successful viewing probabilities into our scheduling design and develop a scheduling algorithm that not only asymptotically achieves the optimal application-level throughput but also provides service regularity guarantees. Finally, we perform simulations to demonstrate the efficiency of our proposed algorithm using a real dataset of users’ head motion.