English

Differential Chaos Shift Keying-based Wireless Power Transfer with Nonlinearities

Signal Processing 2022-05-10 v1 Systems and Control Systems and Control

Abstract

In this paper, we investigate conventional communication-based chaotic waveforms in the context of wireless power transfer (WPT). Particularly, we present a differential chaos shift keying (DCSK)-based WPT architecture, that employs an analog correlator at the receiver, in order to boost the energy harvesting (EH) performance. We take into account the nonlinearities of the EH process and derive closed-form analytical expressions for the harvested direct current (DC) under a generalized Nakagami-m block fading model. We show that, in this framework, both the peak-to-average-power-ratio of the received signal and the harvested DC, depend on the parameters of the transmitted waveform. Furthermore, we investigate the case of deterministic unmodulated chaotic waveforms and demonstrate that, in the absence of a correlator, modulation does not affect the achieved harvested DC. On the other hand, it is shown that for scenarios with a correlator-aided receiver, DCSK significantly outperforms the unmodulated case. Based on this observation, we propose a novel DCSK-based signal design, which further enhances the WPT capability of the proposed architecture; corresponding analytical expressions for the harvested DC are also derived. Our results demonstrate that the proposed architecture and the associated signal design, can achieve significant EH gains in DCSK-based WPT systems. Furthermore, we also show that, even by taking into account the nonlinearities at the transmitter amplifier, the proposed chaotic waveform performs significantly better in terms of EH, when compared with the existing multisine signals.

Keywords

Cite

@article{arxiv.2105.13966,
  title  = {Differential Chaos Shift Keying-based Wireless Power Transfer with Nonlinearities},
  author = {Priyadarshi Mukherjee and Constantinos Psomas and Ioannis Krikidis},
  journal= {arXiv preprint arXiv:2105.13966},
  year   = {2022}
}

Comments

To appear in IEEE Journal of Selected Topics in Signal Processing

R2 v1 2026-06-24T02:34:50.244Z