  The growing popularity of virtual and augmented reality communications and
360{\deg} video streaming is moving video communication systems into much more
dynamic and resource-limited operating settings. The enormous data volume of
360{\deg} videos requires an efficient use of network bandwidth to maintain the
desired quality of experience for the end user. To this end, we propose a
framework for viewport-driven rate-distortion optimized 360{\deg} video
streaming that integrates the user view navigation pattern and the
spatiotemporal rate-distortion characteristics of the 360{\deg} video content
to maximize the delivered user quality of experience for the given
network/system resources. The framework comprises a methodology for
constructing dynamic heat maps that capture the likelihood of navigating
different spatial segments of a 360{\deg} video over time by the user, an
analysis and characterization of its spatiotemporal rate-distortion
characteristics that leverage preprocessed spatial tilling of the 360{\deg}
view sphere, and an optimization problem formulation that characterizes the
delivered user quality of experience given the user navigation patterns,
360{\deg} video encoding decisions, and the available system/network resources.
Our experimental results demonstrate the advantages of our framework over the
conventional approach of streaming a monolithic uniformly encoded 360{\deg}
video and a state-of-the-art reference method. Considerable video quality gains
of 4 - 5 dB are demonstrated in the case of two popular 4K 360{\deg} videos.
