Power-pattern synthesis for energy beamforming in wireless power transmission

• Published in: Neural computing & applications Vol. 30; no. 7; pp. 2327 - 2342
• Main Authors: Sun, Geng, Liu, Yanheng, Li, Han, Li, Jionghui, Wang, Aimin, Zhang, Ying
• Format: Journal Article
• Language: English
• Published: London Springer London 01.10.2018; Springer Nature B.V
• Subjects: Algorithms; Antenna arrays; Artificial Intelligence; Beamforming; Biogeography; Collection; Computational Biology/Bioinformatics; Computational Science and Engineering; Computer Science; Computer simulation; Convergence; Data Mining and Knowledge Discovery; Image Processing and Computer Vision; Optimization; Original Article; Performance enhancement; Probability and Statistics in Computer Science; Sidelobes; Wireless power transmission; Wireless power transmission; Power pattern; Biogeography-based optimization; Antenna array
• ISSN: 0941-0643; 1433-3058
• DOI: 10.1007/s00521-017-3255-6

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.