A Hybrid QOGWO-GPR Algorithm for Antenna Optimization

作者

  • Hao-Yun Zhu School of Information Science and Engineering, State Key Laboratory of Millimeter Waves Southeast University, Nanjing, 210096, China
  • Jia-Wei Qian School of Information Science and Engineering, State Key Laboratory of Millimeter Waves Southeast University, Nanjing, 210096, China
  • Xiao-Hui Tang School of Information Science and Engineering, State Key Laboratory of Millimeter Waves Southeast University, Nanjing, 210096, China
  • Wei-Dong Li School of Information Science and Engineering, State Key Laboratory of Millimeter Waves Southeast University, Nanjing, 210096, China

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https://doi.org/10.13052/2023.ACES.J.380906

关键词:

Antenna optimization, Gaussian process regression, grey wolf optimization, quasi-opposition

摘要

Optimization of antenna performance is a non-linear, multi-dimensional and complex issue, which entails a significant investment of time and labor. In this paper, a hybrid algorithm of quasi-opposition grey wolf optimization (QOGWO) and Gaussian process regression (GPR) model is proposed for antenna optimization. The QOGWO is prone to global optimality, high precision for complex problems, and fast convergence rate at the later stage. The GPR model can reduce time cost of antenna samples generation. After being optimized by the proposed approach, a stepped ultrawideband monopole antenna and a dual-band MIMO antenna for WLAN can achieve wider bandwidth and higher gain or isolation at low time cost, compared to other intelligent algorithms and published literatures.

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Hao-Yun Zhu received the M.S. degree in computer technology in 2022 from Southeast University, Nanjing, China. During the graduate period, he majored in electromagnetic computation, and his research interest focuses on optimization algorithms for electromagnetic simulations.

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Jia-Wei Qian received the B.S. degree in electronic and information engineering in 2020 from the Nanjing University of Posts and Telecommunications, Nanjing, China. He is currently working toward for the master’s degree in electronic and information engineering at Southeast University. His current research interest is full-wave algorithm in time domain and optimization algorithms.

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Xiao-Hui Tang received the B.S. degree in electromagnetic fields and wireless technology in 2021 from the Nanjing University of Posts and Telecommunications, Nanjing, China, where she is currently working toward the master’s degree in electronic and information engineering at Southeast University. Her current research interest is optimization algorithms for antenna array.

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Wei-Dong Li received the M.S. degree in mathematics and the Ph.D. degree in radio engineering from Southeast University, Nanjing, China, in 2003 and 2007, respectively.

He is currently an associate professor of School of Information Science and Engineering. From January 2008 to January 2009, he was a visiting scholar with the Technische Universität Darmstadt, Germany. His research interests include optimization of sparse antenna array, integral equation numerical modeling and fast algorithm, fast and accurate inter/extrapolation techniques, and DGTD in computational EM. He has authored or co-authored over 40 technical papers. He serves as reviewers for IEEE Transactions on Antennas and Propagation and IET Microwave, Antennas and Propagation.

参考

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已出版

2023-09-30

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[1]
H.-Y. . Zhu, J.-W. . Qian, X.-H. . Tang, 和 W.-D. . Li, 《A Hybrid QOGWO-GPR Algorithm for Antenna Optimization》, ACES Journal, 卷 38, 期 09, 页 674–680, 9月 2023.

期

2023: Vol 38 Iss 9

栏目

Special Issue on ACES-China 2022 Conference