  In this paper, we investigate the resource allocation algorithm design for
multicarrier solar-powered unmanned aerial vehicle (UAV) communication systems.
In particular, the UAV is powered by solar energy enabling sustainable
communication services to multiple ground users. We study the joint design of
the three-dimensional (3D) aerial trajectory and the wireless resource
allocation for maximization of the system sum throughput over a given time
period. As a performance benchmark, we first consider an offline resource
allocation design assuming non-causal knowledge of the channel gains. The
algorithm design is formulated as a mixed-integer non-convex optimization
problem taking into account the aerodynamic power consumption, solar energy
harvesting, a finite energy storage capacity, and the quality-of-service (QoS)
requirements of the users. Despite the non-convexity of the optimization
problem, we solve it optimally by applying monotonic optimization to obtain the
optimal 3D-trajectory and the optimal power and subcarrier allocation policy.
Subsequently, we focus on online algorithm design which only requires real-time
and statistical knowledge of the channel gains. The optimal online resource
allocation algorithm is motivated by the offline scheme and entails a high
computational complexity. Hence, we also propose a low-complexity iterative
suboptimal online scheme based on successive convex approximation. Our results
unveil the tradeoff between solar energy harvesting and power-efficient
communication. In particular, the solar-powered UAV first climbs up to a high
altitude to harvest a sufficient amount of solar energy and then descents again
to a lower altitude to reduce the path loss of the communication links to the
users it serves.
