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A Dual-Band Ambient Energy Harvesting Rectenna Design for Wireless Power Communications

Surajo Muhammad, Jun Jiat Tiang, Sew Kin Wong, Amor Smida, Ridha Ghayoula, Amjad Iqbal

2021IEEE Access81 citationsDOIOpen Access PDF

Abstract

In this paper, a long-range dual-band rectenna for harvesting ambient radio frequency (RF) energy from GSM/900 and GSM/1800 is presented. Theoretical analysis of the proposed dual-band impedance matching network (IMN) is conducted using a modified <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\Pi $ </tex-math></inline-formula> –section matching network (MN). The RF-rectifier is integrated with a dual-band inverted-F monopole antenna. The rectenna circuit complexity is minimized by introducing a dual-band IMN, which plays a significant role in improving the harvester RF-to-dc power conversion efficiency (PCE). Measurement results of the proposed design achieved a peak RF-to-dc PCE of 12.93% and 8.0% for an input power of −30 dBm at 0.9 GHz, and 1.8 GHz, respectively. The RF harvester ambiance measurement attained an output dc voltage of 0.374 V. The circuit generates 0.747 V using a low-powered bq25504-674 evaluation module (EVM). Thus, adequate energy management of the proposed rectenna can be used to power many low-powered devices from the harvested ambient RF energy.

Topics & Concepts

RectennaMulti-band deviceRadio frequencyRectifier (neural networks)Impedance matchingElectrical engineeringEnergy harvestingAntenna (radio)GSMElectronic engineeringRF power amplifierComputer sciencePower (physics)WirelessVoltageElectrical impedanceEngineeringTelecommunicationsPhysicsRectificationRecurrent neural networkQuantum mechanicsArtificial neural networkStochastic neural networkAmplifierMachine learningCMOSEnergy Harvesting in Wireless NetworksAntenna Design and AnalysisFull-Duplex Wireless Communications
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