  Emerged as a promising solution for future wireless communication systems,
intelligent reflecting surface (IRS) is capable of reconfiguring the wireless
propagation environment by adjusting the phase-shift of a large number of
reflecting elements. To quantify the gain achieved by IRSs in the radio
frequency (RF) powered Internet of Things (IoT) networks, in this work, we
consider an IRS-assisted cellular-based RFpowered IoT network, where the
cellular base stations (BSs) broadcast energy signal to IoT devices for energy
harvesting (EH) in the charging stage, which is utilized to support the uplink
(UL) transmissions in the subsequent UL stage. With tools from stochastic
geometry, we first derive the distributions of the average signal power and
interference power which are then used to obtain the energy coverage
probability, UL coverage probability, overall coverage probability, spatial
throughput and power efficiency, respectively. With the proposed analytical
framework, we finally evaluate the effect on network performance of key system
parameters, such as IRS density, IRS reflecting element number, charging stage
ratio, etc. Compared with the conventional RF-powered IoT network, IRS passive
beamforming brings the same level of enhancement in both energy coverage and UL
coverage, leading to the unchanged optimal charging stage ratio when maximizing
spatial throughput.
