神经网络辅助双频U型槽贴片天线优化

doi:10.16180/j.cnki.issn1007-7820.2025.07.005

Abstract

Abstract:

In order to improve the efficiency of antenna design, a double-frequency U-slot patch antenna based on PSO-BPNN (Particle Swarm Optimization-Back Propagation Neural Network) model is designed using machine learning to assist antenna optimization design. The operating frequency covers IEEE802.11y (3.65 GHz) and IEEE802.11a (5.20 GHz), and is compared with the antenna designed based on PSO algorithm. According to the simulation model, the antenna is fabricated and tested. The results show that at the resonant frequency of 5.20 GHz, the antenna return loss designed by PSO-BPNN model and PSO model algorithm is close. At the resonant frequency of 3.65 GHz, the return loss of the antenna designed based on the PSO-BPNN model is -22.65 dB and the impedance bandwidth is 0.205 GHz, which is 47.85% and 11.41% higher than that designed by the PSO algorithm, respectively. Test results reveal that the radiation characteristics of the antenna designed based on the PSO-BPNN model algorithm are in good agreement with the measured results.

Key words: BP neural network, particle swarm algorithm, antenna optimization design, dual frequency, patch antenna, U-slot, electromagnetic simulation, return loss

CLC Number:

TN82

ZHANG Bin, DING Haibing, WANG Jing, XUE Qianzhong. Dual-Band U-Slot Patch Antenna Optimization Using Neural Network Model[J].Electronic Science and Technology, 2025, 38(7): 34-39.

Figures/Tables 10

Figure 1.

Figure 2.

Figure 3.

Table 1.

Figure 4.

Table 2.

Table 3.

Figure 5.

Figure 6.

Figure 7.

References 19

[1]	Radavaram S, Pour M. Wideband radiation reconfigurable microstrip patch antenna loaded with two inverted U-Slots[J]. IEEE Transactions on Antennas and Propagation, 2019, 67(3):1501-1508.
[2]	Fan T Q, Jiang B T, Liu R Z, et al. A novel double U-Slot microstrip patch antenna design for low-profile and broad bandwidth applications[J]. IEEE Transactions on Antennas and Propagation, 2022, 70(4):2543-2549.
[3]	Misilamni H M, Naous T, Khatib S K. A review on the design and optimization of antennas using machine learning algorithms and techniques[J]. International Journal of RF and Microwave Computer-Aided Engineering, 2020, 30(10):1-28.
[4]	Zhang J P, Xu J W, Chen Q, et al. Machine-learning-assisted antenna optimization with data augmentation[J]. IEEE Antennas and Wireless Propagation Letters, 2023, 22(8):1932-1936.
[5]	Wang Z B, Fang S J, Wang Q, et al. An ANN-based synthesis model for the single-feed circularly-polarized square microstrip antenna with truncated corners[J]. IEEE Transactions on Antennas and Propagation, 2012, 60(12):5989-5992.
[6]	Sharma Y, Zhang H H, Xin H. Machine learning techniques for optimizing design of double T-shaped monopole antenna[J]. IEEE Transactions on Antennas and Propagation, 2020, 68(7):5658-5663.
[7]	Shi D, Lian C, Cui K Y, et al. An intelligent antenna synthesis method based on machine learning[J]. IEEE Transactions on Antennas and Propagation, 2022, 70(7):4965-4976.
[8]	Mcculloch W S, Pitts W. A logical calculus of the ideas immanent in nervous activity[J]. Bulletin of Mathematical Biology, 1990, 52(1-2):99-115.
[9]	Anuradha D, Patnkaik A, Sinha S N. Design of custom-made fractal multi-band antennas using ANN-PSO[J]. IEEE Antennas and Propagation Magazine, 2011, 53(4):94-101.
[10]	李文华, 牛国波, 刘羽佳. 基于遗传算法优化BP神经网络的液压系统故障诊断[J]. 机床与液压, 2023, 51(8):159-164.
	Li Wenhua, Niu Guobo, Liu Yujia. Hydraulic system fault diagnosis based on genetic algorithm optimized BP neural network[J]. Machine Tool and Hydraulics, 2023, 51(8):159-164.
[11]	丁慧慧, 邵婷婷, 乔曦. 基于BP神经网络的小角度井斜方位角误差补偿研究[J]. 电子科技, 2022, 35(5):33-37.
	Ding Huihui, Shao Tingting, Qiao Xi. Research on azimuth error compensation based on BP neural network at small-angle deviation[J]. Electronic Science and Technology, 2022, 35(5):33-37.
[12]	周志华. 机器学习[M]. 北京: 清华大学出版社, 2016:101-106.
	Zhou Zhihua. Machine learning[M]. Beijing: Tsinghua University Press, 2016:101-106.
[13]	王闪闪. 基于群智能算法的神经网络建模研究[J]. 电子科技, 2017, 30(4):56-59.
	Wang Shanshan. Research of neural network model based on swarm intelligence algorithm[J]. Electronic Science and Technology, 2017, 30(4):56-59.
[14]	黄泽明, 单志勇. 基于火烈鸟搜索算法的天线优化设计[J]. 电子科技, 2024, 37(9):14-19.
	Huang Zeming, Shan Zhiyong. Antenna optimal design based on flamingo search algorithm[J]. Electronic Science and Technology, 2024, 37(9):14-19.
[15]	周驰, 高海兵, 高亮, 等. 粒子群优化算法[J]. 计算机应用研究, 2003, 20(12):7-11.
	Zhou Chi, Gao Haibing, Gao Liang, et al. Particle swarm optimization algorithm[J]. Application Research of Computers, 2003, 20(12):7-11.
[16]	Tian Y B, Zhang S L, Li J Y. Modeling resonant frequency of microstrip antenna based on neural network ensemble[J]. International Journal of Numerical Modelling-Electronic Networks Devices and Fields, 2011, 24(1):77-86.
[17]	Dhaliwai B S, Pattnaik S S. Development of PSO-ANN ensemble hybrid algorithm and its application in compact crown circular fractal patch antenna design[J]. Wireless Personal Communications, 2017, 96(1):135-152.
[18]	Dong J, Qin W W, Wang M. Fast multi-objective optimization of multi-parameter antenna structures based on improved BPNN surrogate model[J]. IEEE Access, 2019(7):77692-77701.
[19]	潘昊, 侯清兰. 基于粒子群优化算法的BP网络学习研究[J]. 计算机工程与应用, 2006(16):41-43,66.
	Pan Hao, Hou Qinglan. A BP neural networks learning algorithm research based on particle swarm optimizer[J]. Computer Engineering and Applications, 2006(16):41-43,66.

结构参数	数值/mm	结构参数	数值/mm
L_g	50.00	V	1.25
W_g	55.00	U_l	8.00~9.00
L	23.00	U_w	12.00~14.00
W	27.00	U_d	6.00~7.00
X_f	0.00	R_l	3.00~4.00
Y_f	2.25	R_w	17.00~19.00

网络模型类别	MSE最小值	MSE平均值
BPNN	0.061 32	0.067 47
PSO-BPNN	0.055 11	0.061 96

优化方法	U_l/mm	U_w/mm	U_d/mm	R_l/mm	R_w/mm
PSO	8.7	13.0	6.9	3.0	17.7
PSO-BPNN	8.5	13.0	6.5	3.5	18.0

Dual-Band U-Slot Patch Antenna Optimization Using Neural Network Model

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 10

References 19

Related Articles 15

Metrics

Comments

Recommended 0

[1]	YANG Yuanxing, DING Xudong, WANG Junchao, WU Dong. Research on BP Neural Network PID Control Algorithm of Refrigeration System Based on Smith Predictor [J]. Electronic Science and Technology, 2025, 38(8): 42-48.
[2]	ZHANG Haibo, PAN Pengcheng, ZHENG Feng. Corrosion Rate Prediction of Grounding Grid Based on Improved Whale Algorithm Optimization [J]. Electronic Science and Technology, 2025, 38(5): 8-14.
[3]	YE Xiangyu, LIN Xiaohui, DING Jiangqiao, XIE Weikun. Total Jitter Prediction Method of FPGA Embedded High-Speed Interface Based on Optimized BPNN [J]. Electronic Science and Technology, 2025, 38(2): 70-77.
[4]	MAN Yanlu, LIU Min. Joint State Estimation of Active Distribution Network Based on WLS-AUKF Hybrid Algorithm [J]. Electronic Science and Technology, 2025, 38(2): 93-102.
[5]	HUANG Zeming, SHAN Zhiyong. Antenna Optimal Design Based on Flamingo Search Algorithm [J]. Electronic Science and Technology, 2024, 37(9): 14-19.
[6]	YUAN Ao, QI Jinpeng, JIA Can, XUE Yuxin, GUO Yangyang. A Classification Method of Time Series Pathological Data Segments Based on Deep Learning [J]. Electronic Science and Technology, 2024, 37(6): 84-91.
[7]	LIN Xiangyu, ZENG Weihua. Design of Dual-Frequency Integrated Ultra-Wideband Ground Penetrating Radar Antenna [J]. Electronic Science and Technology, 2024, 37(4): 25-29.
[8]	WANG Zexue, LI Yusong, LONG Haoqi, MING Yuzhou. Research on Parameter Optimization of Cold Crucible Power Supply Based on Electromagnetic Simulation [J]. Electronic Science and Technology, 2024, 37(11): 70-77.
[9]	ZHANG Dagui,ZHOU Zhifeng,ZHANG Yi. Optimization Method of Planar Microphone Array Configuration Based on Genetic Algorithm [J]. Electronic Science and Technology, 2023, 36(7): 24-31.
[10]	LI Shuai,YANG Jian,WANG Tao,HUANG Xin,MA Shifeng. Simulation and Analysis of A Low Power RF Energy Acquisition System [J]. Electronic Science and Technology, 2023, 36(6): 50-56.
[11]	LIN Lin,WANG Wanxiong. Short-Term Wind Speed Prediction Based on EMD-GWO-SVR Combined Model [J]. Electronic Science and Technology, 2023, 36(5): 1-8.
[12]	WANG Xinyang,WANG Ruiyang,WEI Yunbing. An Arithmetic Optimization Algorithm Based Fault Section Location Method for Low Voltage Distribution Networks [J]. Electronic Science and Technology, 2023, 36(12): 25-31.
[13]	SHI Zhenli,WEI Yewen. Multi-Objective Optimization of Active Distribution Network Based on Particle Swarm Optimization [J]. Electronic Science and Technology, 2022, 35(9): 7-14.
[14]	ZHOU Yongchang,HUANG Yayu. Establishment of a Predictive Model of the Process Parameters of Secondary Moisturizing Based on BP Neural Network [J]. Electronic Science and Technology, 2022, 35(9): 79-86.
[15]	ZHANG Chongchong,HUANG Yayu. A GA-BP Neural Network for Predicting the Structure of Leaf Tobacco [J]. Electronic Science and Technology, 2022, 35(6): 35-42.