Contents I. Introduction
Intelligent reflecting surface (IRS) can adaptively tune the phase shifts of its reflected signals by a large number of low-cost reflecting elements integrated on it to achieve high reflect beamforming gain [1], [2]. Therefore, leveraging IRS’s intelligent reflection has been regarded as a promising way to improve the spectrum and energy efficiency of future wireless communication networks [3], [4]. On the other hand, wireless power transfer has been introduced into the rapidly developing Internet-of-Things (IoT) networks to resolve the network devices’ energy limitation problem. Such networks are also called wireless power communication networks (WPCNs) [5], which provide an efficient way to realize sustainable IoT networks. Recently, both the transmit power minimization study in [6] and the weighted sum-rate maximization study in [7] have unveiled that IRSs can achieve high wireless power transfer and information transmission efficiency due to the high reflective beamforming gain. Therefore, integrating IRSs with WPCN is a concrete step toward the realization of low-cost sustainable IoT networks. In [8], the throughput maximization of a two-user IRS-assisted WPCN has been investigated, where IRS reflect beamforming, power allocation and time allocation have been jointly optimized. In [9], joint optimization of IRS reflect beamforming and network resource allocation for throughput maximization have been investigated in a multiuser IRS-assisted WPCN.
