  This paper is concerned with the issue of improving video subscribers'
quality of experience (QoE) by deploying a multi-unmanned aerial vehicle (UAV)
network. Different from existing works, we characterize subscribers' QoE by
video bitrates, latency, and frame freezing and propose to improve their QoE by
energy-efficiently and dynamically optimizing the multi-UAV network in terms of
serving UAV selection, UAV trajectory, and UAV transmit power. The dynamic
multi-UAV network optimization problem is formulated as a challenging
sequential-decision problem with the goal of maximizing subscribers' QoE while
minimizing the total network power consumption, subject to some physical
resource constraints. We propose a novel network optimization algorithm to
solve this challenging problem, in which a Lyapunov technique is first explored
to decompose the sequential-decision problem into several repeatedly optimized
sub-problems to avoid the curse of dimensionality. To solve the sub-problems,
iterative and approximate optimization mechanisms with provable performance
guarantees are then developed. Finally, we design extensive simulations to
verify the effectiveness of the proposed algorithm. Simulation results show
that the proposed algorithm can effectively improve the QoE of subscribers and
is 66.75\% more energy-efficient than benchmarks.
