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QoE-Driven Coupled Uplink and Downlink Rate Adaptation for 360-Degree Video Live Streaming

机译:QoE驱动的耦合上行链路和下行链路速率适配360度视频直播

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摘要

360-degree video provides an immersive 360-degree viewing experience and has been widely used in many areas. The 360-degree video live streaming systems involve capturing, compression, uplink (camera to video server) and downlink (video server to user) transmissions. However, few studies have jointly investigated such complex systems, especially the rate adaptation for the coupled uplink and downlink in the 360-degree video streaming under limited bandwidth constraints. In this letter, we propose a quality of experience (QoE)-driven 360-degree video live streaming system, in which a video server performs rate adaptation based on the uplink and downlink bandwidths and information concerning each user's real-time field-of-view (FoV). We formulate it as a nonlinear integer programming problem and propose an algorithm, which combines the Karush-Kuhn-Tucker (KKT) condition and branch and bound method, to solve it. The numerical results show that the proposed optimization model can improve users' QoE significantly in comparison with other baseline schemes.
机译:360度视频提供了沉浸式360度观看体验,并且已广泛用于许多领域。 360度视频直播系统涉及捕获,压缩,上行链路(相机到视频服务器)和下行链路(视频服务器到用户)传输。然而,很少有研究已经共同调查了这种复杂的系统,特别是在有限的带宽约束下360度视频流中的耦合上行链路和下行链路的速率适应。在这封信中,我们提出了一种经验质量(QoE) - 驱动的360度视频直播系统,其中视频服务器基于上行链路和下行链路带宽和关于每个用户的实时字段的信息执行速率自适应 - 查看(FOV)。我们将其制定为非线性整数编程问题,并提出一种算法,该算法结合了karush-kuhn-tucker(kkt)条件和分支和绑定方法来解决它。数值结果表明,与其他基线方案相比,所提出的优化模型可以显着改善用户QoE。

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