Wireless Energy Transfer Using Chirp Waveform With Joint Subband Selection and Max-Min Power Control for IoT Networks

Abstract

Wireless energy transfer (WET) is a promising method to extend the operation time of sensors in energy-constrained wireless networks. Specially, for the low-power applications such as the Internet-of-Things (IoT) and machine-to-machine communications, most of the existing works have so far focused on using fixed-frequency waveforms for WET. In this paper, we investigate the potential of superposed chirp waveforms for downlink (DL) WET from a multi-antenna access point (AP) to a group of sensors over orthogonal subbands while satisfying the peak power constraint. To this end, we first propose the general design of superposed chirp waveforms and establish key properties required to optimize WET. We derive novel closed-form analytical expressions using order statistics for average received energy based on DL WET via superposed chirps and via fixed-frequency waveforms over subbands selected independently for each sensor based on their estimated channel gain, and evaluate average harvested energy (HE) considering both linear and nonlinear energy harvesting models. For both superposed chirps and fixed-frequency based DL-WET, we then derive max-min optimal power control coefficients in closed-form to ensure that the sensors placed at different distances from the AP receive the same amount of energy. As a benchmark, we present the corresponding analysis considering perfect channel knowledge. Through our analytical and numerical results, for the considered setup, we prove and elucidate that superposed chirp-based WET over select subbands and under max-min power control provides an improvement of 40% in average HE performance as compared to multisine waveforms consisting of a set of fixed-frequency cosine signals, and extends the operating range of energy transfer by about 17.5% over fixed-frequency waveforms.