论文标题
360度视频直播QOE驱动的耦合上行链路和下行链路速率改编
QoE-driven Coupled Uplink and Downlink Rate Adaptation for 360-degree Video Live Streaming
论文作者
论文摘要
360度视频提供了沉浸式360度观看体验，并在许多领域被广泛使用。 360度视频实时流媒体系统涉及捕获，压缩，上行链路（视频服务器）和下行链路（视频服务器到用户）的传输。但是，很少有研究共同研究了这样的复杂系统，尤其是在有限的带宽约束下，在360度视频流中耦合上行链路和下行链路的速率适应。在这封信中，我们提出了体验质量（QOE）驱动的360度视频实时流媒体系统，其中视频服务器基于上行链路链接和下行链路带宽以及有关每个用户的实时视野（FOV）的信息进行速率适应。我们将其作为非线性整数编程问题提出，并提出了一种算法，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，提出的优化模型可以显着改善用户的QOE。
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.
