NSSC OpenIR  > 空间技术部
Power-pattern synthesis for energy beamforming in wireless power transmission
Sun Geng; Liu Yanheng; Li Han; Li Jionghui; Wang Aimin; Zhang Ying; Zhang, Ying (yzhang@gatech.edu)
Department空间技术部
Source PublicationNeural Computing and Applications
2017
Pages1-16
ISSN0941-0643
Language英语
AbstractThis 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. © 2017 The Natural Computing Applications Forum
Indexed BySCI ; EI
Document Type期刊论文
Identifierhttp://ir.nssc.ac.cn/handle/122/6075
Collection空间技术部
Corresponding AuthorZhang, Ying (yzhang@gatech.edu)
Recommended Citation
GB/T 7714
Sun Geng,Liu Yanheng,Li Han,et al. Power-pattern synthesis for energy beamforming in wireless power transmission[J]. Neural Computing and Applications,2017:1-16.
APA Sun Geng.,Liu Yanheng.,Li Han.,Li Jionghui.,Wang Aimin.,...&Zhang, Ying .(2017).Power-pattern synthesis for energy beamforming in wireless power transmission.Neural Computing and Applications,1-16.
MLA Sun Geng,et al."Power-pattern synthesis for energy beamforming in wireless power transmission".Neural Computing and Applications (2017):1-16.
Files in This Item:
File Name/Size DocType Version Access License
2017s00521-017-3255-(2803KB)期刊论文作者接受稿开放获取CC BY-NC-SAApplication Full Text
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Sun Geng]'s Articles
[Liu Yanheng]'s Articles
[Li Han]'s Articles
Baidu academic
Similar articles in Baidu academic
[Sun Geng]'s Articles
[Liu Yanheng]'s Articles
[Li Han]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Sun Geng]'s Articles
[Liu Yanheng]'s Articles
[Li Han]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.