  Aiming at the limited battery capacity of widely deployed low-power smart
devices in the Internet-of-things (IoT), this paper proposes a novel
intelligent reflecting surface (IRS) empowered unmanned aerial vehicle (UAV)
simultaneous wireless information and power transfer (SWIPT) network framework,
in which IRS is used to reconstruct the wireless channel to enhance the
wireless energy transmission efficiency and coverage area of the UAV SWIPT
networks. In this paper, we formulate an achievable sum-rate maximization
problem by jointly optimizing UAV trajectory, successive interference
cancellation (SIC) decoding order, UAV transmit power allocation, power
splitting (PS) ratio and IRS reflection coefficient while taking account of
user non-orthogonal multiple access (NOMA) and a non-linear energy harvesting
model. Due to the coupling of optimization variables, this problem is a complex
non-convex optimization problem, and it is challenging to solve it directly. We
first transform the problem, and then apply the alternating optimization (AO)
algorithm framework to divide the transformed problem into four sub-problems to
solve it. Specifically, by applying successive convex approximation (SCA),
penalty function method and difference-convex (DC) programming, UAV trajectory,
SIC decoding order, UAV transmit power allocation, PS ratio and IRS reflection
coefficient are alternately optimized until the convergence is achieved.
Numerical simulation results verify the effectiveness of our proposed algorithm
compared to other algorithms.
