Evolutionary beamforming optimization for radio frequency charging in wireless rechargeable sensor networks

Ke Han Yao, Jehn Ruey Jiang, Chung Hsien Tsai, Zong Syun Wu

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

This paper investigates how to efficiently charge sensor nodes in a wireless rechargeable sensor network (WRSN) with radio frequency (RF) chargers to make the network sustainable. An RF charger is assumed to be equipped with a uniform circular array (UCA) of 12 antennas with the radius λ, where λ is the RF wavelength. The UCA can steer most RF energy in a target direction to charge a specific WRSN node by the beamforming technology. Two evolutionary algorithms (EAs) using the evolution strategy (ES), namely the Evolutionary Beamforming Optimization (EBO) algorithm and the Evolutionary Beamforming Optimization Reseeding (EBO-R) algorithm, are proposed to nearly optimize the power ratio of the UCA beamforming peak side lobe (PSL) and the main lobe (ML) aimed at the given target direction. The proposed algorithms are simulated for performance evaluation and are compared with a related algorithm, called Particle Swarm Optimization Gravitational Search Algorithm-Explore (PSOGSA-Explore), to show their superiority.

Original languageEnglish
Article number1918
JournalSensors (Switzerland)
Volume17
Issue number8
DOIs
StatePublished - 20 Aug 2017

Keywords

  • Antenna array
  • Beamforming
  • Evolution strategy
  • Evolutionary algorithm
  • RF charging

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