Abstract

This paper studies the performance of an intelligent reflecting surface (IRS)-assisted radio frequency (RF)-powered wireless network. In the considered network, a multi-antenna base station (BS) communicates with its users (UEs) through downlink transmission and energy-constrained internet-of-things (IoT) devices, which are randomly deployed around a cluster head (CH), utilize the resources of BS for energy harvesting and information transmission. IRS, deployed randomly around CH, reflects the RF signals transmitted by BS to the IoT devices, providing additional energy to harvest. For the considered network, average distances between BS, CH, IRS, and an IoT device have been computed, statistically. Furthermore, the average harvested energy at an IoT device is computed. Instead of considering a fixed transmit power (FTP) of an IoT device, we consider that its transmit power varies randomly depending on the stored energy. Using the Markov chain model, we obtain transmission probability and state-dependent transmit power (SDTP). Analytical expressions for outage probability and throughput of an IoT device are obtained. To manifest the effectiveness of derived expressions, numerical results are compared with Monte-Carlo simulation results. Our results reveal that the proposed SDTP scheme has a performance gain over the FTP scheme, especially in scenarios where harvested energy is in abundance.

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