  Intelligent reflecting surface (IRS) is an emerging technology to enhance the
energy- and spectrum-efficiency of wireless powered communication networks
(WPCNs). In this paper, we investigate an IRS-assisted multiuser multiple-input
single-output (MISO) WPCN, where the single-antenna wireless devices (WDs)
harvest wireless energy in the downlink (DL) and transmit their information
simultaneously in the uplink (UL) to a common hybrid access point (HAP)
equipped with multiple antennas. Our goal is to maximize the weighted sum rate
(WSR) of all the energy-harvesting users. To make full use of the beamforming
gain provided by both the HAP and the IRS, we jointly optimize the active
beamforming of the HAP and the reflecting coefficients (passive beamforming) of
the IRS in both DL and UL transmissions, as well as the transmit power of the
WDs to mitigate the inter-user interference at the HAP. To tackle the
challenging optimization problem, we first consider fixing the passive
beamforming, and converting the remaining joint active beamforming and user
transmit power control problem into an equivalent weighted minimum mean square
error (WMMSE) problem, where we solve it using an efficient block-coordinate
descent (BCD) method. Then, we fix the active beamforming and user transmit
power, and optimize the passive beamforming coefficients of the IRS in both the
DL and UL using a semidefinite relaxation (SDR) method. Accordingly, we apply a
block-structured optimization (BSO) method to update the two sets of variables
alternately. Numerical results show that the proposed joint optimization
achieves significant performance gain over other representative benchmark
methods and effectively improves the throughput performance in multiuser MISO
WPCNs.
