Modeling and Optimization of RF-Energy Harvesting-assisted Quantum Battery System

Abstract

The quest for finding a small-sized energy supply to run the small-scale wireless gadgets, with almost an infinite lifetime, has intrigued humankind since past several decades. In this context, the concept of Quantum batteries has come into limelight more recently to serve the purpose. However, the main issue revolving around the closed-system design of Quantum batteries is to ensure a loss-less environment, which is extremely difficult to realize in practice. In this paper, we present the modeling and optimization aspects of a Radio-Frequency (RF) Energy Harvesting (EH) assisted Quantum battery, wherein several EH modules (in the form of micro-or nano-sized integrated circuits (ICs)) help each of the involved Quantum sources achieve the so-called quasi-stable state. Specifically, a micro-controller manages the overall harvested energy from the RF-EH ICs and a photon emitting device, such that the emitted photons are absorbed by the electrons in the Quantum sources. In order to precisely model and optimize the considered framework, we formulate a transmit power minimization problem for an RFbased wireless system to optimize the number of RF-EH ICs under the given EH constraints at the Quantum battery-enabled wireless device. We obtain an analytical solution to the abovementioned problem using a rational approach, while additionally seeking another solution obtained via a non-linear program solver. The effectiveness of the proposed technique is reported in the form of numerical results by taking a range of system parameters into account.

Boosting Quantum Battery-Based IoT Gadgets via RF-Enabled Energy Harvesting

“… The miniaturization concept of RF-EH modules into micro- or nano-meter-sized ICs is depicted herein. As its working principle, an RF antenna absorbs the ambient (or specific band(s) of) RF signal and converts its energy into the equivalent DC type of output [ 40 ]. …”

“… Minimized transmit power (in dBW) versus the demanded harvested energy for altering values of N [ 40 ]. …”

“… Minimized transmit power (in dBW) versus N for different value selections pertaining to the separation distance between the transmitter and IoT user [ 40 ]. …”

“…Second, we directly solve the (main) formulated non-convex problem using an optimization solver. Unlike [ 40 ], we formulate and solve an additional optimization problem to minimize the total number of RF-EH ICs, under constraints on the total transmit power and overall harvested energy (please note that this paper is an extension of the authors’ prior work, published as [ 40 ] ( © 2021 IEEE)). Specifically, the main contributions and novelty of this work are summarized below.…”

Hybrid Active-and-Passive Relaying Model for 6G-IoT Greencom Networks with SWIPT

“…As the technological advancements in the field of wireless communications continue to amaze the mankind in several ways, a major hurdle in this progress is our dependence on the energy sources, which are as strong as on the gadgets themselves [10]. An early EH concept of getting energy from/through the air to power all equipment, was proposed by Nikola Tesla in the late 1890s to early 1900s [11,12].…”