  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.
