QoE-driven Coupled Uplink and Downlink Rate Adaptation for 360-degree Video Live Streaming
This work addresses the challenge of enhancing immersive video streaming performance for users, though it is incremental as it builds on existing rate adaptation methods for a specific domain.
The authors tackled the problem of optimizing 360-degree video live streaming by jointly adapting uplink and downlink rates under bandwidth constraints, resulting in a significant improvement in users' quality of experience compared to baseline schemes.
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.