Theoretical Analysis of Nonlinear Energy Harvesting From Wireless Mobile Nodes

Saito, Hiroshi

doi:10.1109/lwc.2021.3086192

Cited by 5 publications

(2 citation statements)

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“…where ψ(•) ≥ 0 is DC power converted from RF power, α > 2 is a path-loss exponent, G is a constant gain, and H x,y is small-scale fading (an independent random variable) modeled as Rayleigh fading with mean 1. On the basis of field data [26], [27], a few DC-to-RF power conversion models have been proposed [3], [28]- [32]. Among them, the model (Eq.…”

Section: System Model and Assumptionmentioning

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Theoretical Analysis of Fully Wireless-Power-Transfer Node Networks

Saito

2023

IEICE Trans. Commun.

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The performance of a fully wireless-power-transfer (WPT) node network, in which each node transfers (and receives) energy through a wireless channel when it has sufficient (and insufficient) energy in its battery, was theoretically analyzed. The lost job ratio (LJR), namely, is the ratio of (i) the amount of jobs that cannot be done due to battery of a node running out to (ii) the amount of jobs that should be done, is used as a performance metric. It describes the effect of the battery of each node running out and how much additional energy is needed. Although it is known that WPT can reduce the probability of the battery running out among a few nodes within a small area, the performance of a fully WPT network has not been clarified. By using stochastic geometry and first-passage-time analysis for a diffusion process, the expected LJR was theoretically derived. Numerical examples demonstrate that the key parameters determining the performance of the network are node density, threshold switching of statuses between "transferring energy" and "receiving energy," and the parameters of power conversion. They also demonstrate the followings: (1) The mean energy stored in the node battery decreases in the networks because of the loss caused by WPT, and a fully WPT network cannot decrease the probability of the battery running out under the current WPT efficiency. (2) When the saturation value of power conversion increases, a fully WPT network can decrease the probability of the battery running out although the mean energy stored in the node battery still decreases in the networks. This result is explained by the fact that the variance of stored energy in each node battery becomes smaller due to transfer of energy from nodes of sufficient energy to nodes of insufficient energy. key words: wireless power transfer (WPT), performance evaluation, stochastic geometry, first passage time, lost job ratio, probability of battery running out IntroductionRecently, the number of mobile devices in our environment has been rapidly growing. Millions of such devices require power via a battery, which must be frequently replaced. However, as the number of devices increases, such frequent large-scale replacement of batteries becomes infeasible. In the meantime, the number of wireless sensors installed in our environment is also increasing, and bundles of cables for supplying power to those sensors may become problematic. "Wireless power transfer" (WPT) is a promising technology for solving these problems [1], [2]. WPT is also essential for connecting a huge number of devices to the Internet of Things (IoT) [3].

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