IRS-Assisted RF-Powered IoT Networks: System Modeling and Performance Analysis

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 RF-powered 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.

I. Introduction

With the booming Internet of Things (IoT), the number of IoT devices is expected to reach tens of billions. To meet the vision of sustainable development of the IoTs, an efficient utilization of energy has been served as the principal issue. Recent advances in wireless energy harvesting (EH) technology, particularly radio frequency (RF) EH [1], have broken new ground to support IoT devices to collect energy from natural energy sources or ambient RF sources. It gave birth to the wireless powered communication networks (WPCNs) [2] in which wireless nodes harvest energy from the base station (BS) RF signals and then transmit information by using the harvested energy. However, one of the major technical challenges in WPCN is the low efficiency of power transmission over long distances, resulting in the limited amount of energy harvested and poor network performance.