  This paper considers an intelligent reflecting surface(IRS)-aided wireless
powered communication network (WPCN), where devices first harvest energy from a
power station (PS) in the downlink (DL) and then transmit information using
non-orthogonal multiple access (NOMA) to a data sink in the uplink (UL).
However, most existing works on WPCNs adopted the simplified linear
energy-harvesting model and also cannot guarantee strict user
quality-of-service requirements. To address these issues, we aim to minimize
the total transmit energy consumption at the PS by jointly optimizing the
resource allocation and IRS phase shifts over time, subject to the minimum
throughput requirements of all devices. The formulated problem is decomposed
into two subproblems, and solved iteratively in an alternative manner by
employing difference of convex functions programming, successive convex
approximation, and penalty-based algorithm. Numerical results demonstrate the
significant performance gains achieved by the proposed algorithm over benchmark
schemes and reveal the benefits of integrating IRS into WPCNs. In particular,
employing different IRS phase shifts over UL and DL outperforms the case with
static IRS beamforming.
