  Mobile crowdsensing (MCS) enables data collection from massive devices to
achieve a wide sensing range. Wireless power transfer (WPT) is a promising
paradigm for prolonging the operation time of MCS systems by sustainably
transferring power to distributed devices. However, the efficiency of WPT
significantly deteriorates when the channel conditions are poor. Unmanned
aerial vehicles (UAVs) and reconfigurable intelligent surfaces (RISs) can serve
as active or passive relays to enhance the efficiency of WPT in unfavourable
propagation environments. Therefore, to explore the potential of jointly
deploying UAVs and RISs to enhance transmission efficiency, we propose a novel
transmission framework for the WPT-assisted MCS systems, which is enhanced by a
UAV-mounted RIS. Subsequently, under different compression schemes, two
optimization problems are formulated to maximize the weighted sum of the data
uploaded by the user equipments (UEs) by jointly designing the WPT and
uploading time, the beamforming matrics, the CPU cycles, and the UAV
trajectory. A block coordinate descent (BCD) algorithm based on the closed-form
beamforming designs and the successive convex approximation (SCA) algorithm is
proposed to solve the formulated problems. Furthermore, to highlight the
insight of the gains brought by the compression schemes, we analyze the energy
efficiencies of compression schemes and confirm that the gains gradually reduce
with the increasing power used for compression. Simulation results demonstrate
that the amount of collected data can be effectively increased in
wireless-powered MCS systems.
