Multi-dimensional Lorenz-Based Chaotic Waveforms for Wireless Power Transfer

TL;DR

This paper explores multi-dimensional Lorenz-based chaotic waveforms for wireless power transfer, analyzing their energy harvesting efficiency considering nonlinearities and hardware limitations, and compares them with other waveform types.

Contribution

It introduces a novel framework for analyzing Lorenz-based chaotic signals in WPT, accounting for nonlinearities and HPA limitations, and compares their performance with Henon and multisine waveforms.

Findings

Lorenz signals can enhance WPT efficiency under certain conditions.

HPA imperfections degrade energy transfer more than PAPR does.

Lorenz and Henon signals outperform traditional multisine waveforms in WPT.

Abstract

In this paper, we investigate multi-dimensional chaotic signals with respect to wireless power transfer (WPT). Specifically, we analyze a multi-dimensional Lorenz-based chaotic signal under a WPT framework. By taking into account the nonlinearities of the energy harvesting process, closed-form analytical expressions for the average harvested energy are derived. Moreover, the practical limitations of the high power amplifier (HPA) at the transmitter are also taken into consideration. We interestingly observe that for these types of signals, high peak-to-average-power-ratio (PAPR) is not the only criterion for obtaining enhanced WPT. We demonstrate that while the HPA imperfections do not significantly affect the signal PAPR, it notably degrades the energy transfer performance. As the proposed framework is general, we also demonstrate its application with respect to a Henon signal based WPT. Finally we compare Lorenz and Henon signals with the conventional multisine waveforms in terms of WPT performance.