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Power-pattern synthesis for energy beamforming in wireless power transmission

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Abstract

This paper proposed a power-pattern optimization method for suppressing the maximum side lobe level outside of the collection region (CSL) of energy beamforming for wireless power transmission based on the biogeography-based optimization with local search (BBOLS). Two improved components, local search operator and selection operator, are introduced into the normal biogeography-based optimization to improve the performance of the algorithm. These two introduced factors can significantly help the algorithm to improve the convergence rate, prevent the candidate solutions from being trapped into the local optimum. Simulation results show that the CSL of the planar antenna array obtained by BBOLS can be depressed effectively while the beam collection efficiency can be enhanced. Moreover, the accuracy and the convergence rate of BBOLS are better than other algorithms. In addition, the power-pattern performance obtained by BBOLS is also verified by the electromagnetic simulations.

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Acknowledgements

We would like to thank the anonymous referees for their many valuable suggestions and comments. This study was supported by the National Natural Science Foundation of China (Grant No. 61373123) and Chinese Scholarship Council (No. [2016] 3100) and the Graduate Innovation Fund of Jilin University (No. 2017016).

Funding

This study was supported by the National Natural Science Foundation of China (Grant No. 61373123), the Chinese Scholarship Council (No. [2016] 3100) and the Graduate Innovation Fund of Jilin University (No. 2017016).

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Authors and Affiliations

  1. College of Computer Science and Technology, Jilin University, Changchun, 130012, China

    Geng Sun, Yanheng Liu, Han Li & Aimin Wang

  2. Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, 130012, China

    Geng Sun, Yanheng Liu, Han Li & Aimin Wang

  3. School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA

    Geng Sun, Jionghui Li & Ying Zhang

  4. National Space Science Center, Chinese Academy of Sciences, Beijing, 100190, China

    Jionghui Li

  5. University of Chinese Academy of Science, Beijing, 100049, China

    Jionghui Li

Authors
  1. Geng Sun
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  2. Yanheng Liu
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  3. Han Li
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  4. Jionghui Li
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  5. Aimin Wang
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  6. Ying Zhang
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Correspondence to Ying Zhang.

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All of the authors declare that they have no conflict of interest.

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Cite this article

Sun, G., Liu, Y., Li, H. et al. Power-pattern synthesis for energy beamforming in wireless power transmission. Neural Comput & Applic 30, 2327–2342 (2018). https://doi.org/10.1007/s00521-017-3255-6

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  • DOI: https://doi.org/10.1007/s00521-017-3255-6

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