  Providing a high-quality real-time video streaming experience to mobile users
is one of the biggest challenges in cellular networks. This is due to the need
of these services for high rates with low variability, which is not easy to
accomplish given the competition among (usually a high number of) users for
constrained network resources and the high variability of their channel
characteristics. A way of improving the user experience is by exploiting their
buffers and the ability to provide a constant data rate to everyone, as one of
the features of 5G networks. However, the latter is not very efficient. To this
end, in this paper we provide a theoretical-analysis framework for resource
allocation in 5G networks that leads to an improved user experience when
watching live video. We do this by solving three problems, in which the
objectives are to provide the highest achievable video resolution to all
one-class and two-class users, and to maximize the number of users that
experience a given resolution. The analysis is validated by simulations that
are run on traces. We also compare the performance of our approach against
other techniques for different QoE metrics. Results show that the performance
can be improved by at least 15% with our approach.
