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.

中文翻译：

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QoE驱动的360度视频直播耦合上行和下行速率适配

360度视频提供身临其境的360度观看体验，并已被广泛应用于许多领域。360 度视频直播系统涉及捕获、压缩、上行（摄像机到视频服务器）和下行（视频服务器到用户）传输。然而，很少有研究联合研究这种复杂的系统，特别是在有限带宽约束下，360 度视频流中耦合上下行链路的速率自适应。在这封信中，我们提出了一种体验质量 (QoE) 驱动的 360 度视频直播系统，其中视频服务器根据上下行带宽和每个用户的实时现场信息进行速率适配。视图（FoV）。我们将其表述为非线性整数规划问题并提出一种算法，它结合了 Karush-Kuhn-Tucker (KKT) 条件和分支定界法来解决它。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提高用户的 QoE。