Evolution of SWIPT for the IoT World: Near- and Far-Field Solutions for Simultaneous Wireless Information and Power Transfer

Abstract

In the past few years, many interesting approaches have been studied and designed to advance the practical implementation of wireless information and power transfer (WIPT) <xref ref-type="bibr" rid="ref1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1]</xref> and simultaneous WIPT (SWIPT) <xref ref-type="bibr" rid="ref2" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[2]</xref> , <xref ref-type="bibr" rid="ref3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[3]</xref> in the contexts of everyday life, academic research, and industry. The ever-growing array of Internet of Things (IoT) technologies presents a tangible answer to the need for modern, densely populated networks of wirelessly connected devices. In this context, node maintenance is a challenging task, given both the enormous size of the networks and the location of the devices, which can be spread across difficult-to-reach areas. In particular, the SWIPT paradigm <xref ref-type="bibr" rid="ref4" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[4]</xref> is being investigated in a wide range of systems for industrial applications combined with emerging technologies typical of the industrial IoT, namely wireless sensor networks (WSNs) that enable unlimited and uninterrupted connectivity in generic commercial environments. The main goal is to continuously monitor key components by using smart sensors that are able to track, in almost real time, rotation, position, speed, temperature, acceleration, and all the other vital parameters of the devices that have to be observed <xref ref-type="bibr" rid="ref5" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[5]</xref> .

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