  This paper considers LEO satellite- and cache-assisted UAV communications for
content delivery in terrestrial networks, which shows great potential for
next-generation systems to provide ubiquitous connectivity and high capacity.
Specifically, caching is provided by the UAV to reduce backhaul congestion, and
the LEO satellite supports the UAV's backhaul link. In this context, we aim to
maximize the minimum achievable throughput per ground user (GU) by jointly
optimizing cache placement, the UAV's resource allocation, and trajectory while
cache capacity and flight time are limited. The formulated problem is
challenging to solve directly due to its non-convexity and combinatorial
nature. To find a solution, the problem is decomposed into three sub-problems:
(1) cache placement optimization with fixed UAV resources and trajectory,
followed by (2) the UAV resources optimization with fixed cache placement
vector and trajectory, and finally, (3) we optimize the UAV trajectory with
fixed cache placement and UAV resources. Based on the solutions of
sub-problems, an efficient alternating algorithm is proposed utilizing the
block coordinate descent (BCD) and successive convex approximation (SCA)
methods. Simulation results show that the max-min throughput and total
achievable throughput enhancement can be achieved by applying our proposed
algorithm instead of other benchmark schemes.
