Optimization of an Irregular Slot Antenna Based on Conditional Generative Adversarial Networks
- Resource Type
- Conference
- Authors
- Liu, Yitao; Chen, Ping; Tian, Jin; Wu, Jing; Xiao, Jun; Ye, Qiubo
- Source
- 2023 Cross Strait Radio Science and Wireless Technology Conference (CSRSWTC) Cross Strait Radio Science and Wireless Technology Conference (CSRSWTC), 2023. :1-3 Nov, 2023
- Subject
- Computing and Processing
Fields, Waves and Electromagnetics
Photonics and Electrooptics
Signal Processing and Analysis
Wireless communication
Slot antennas
Bandwidth
Generative adversarial networks
Impedance
Optimization
Genetic algorithms
conditional generative adversarial networks (CGAN)
Genetic Algorithm (GA)
antenna optimization
- Language
- ISSN
- 2377-8512
In this paper, to address the problem of multilayer perceptron (MLP) with weak generalization ability, conditional generative adversarial networks (CGAN) is proposed to learn the complex nonlinear relationship between antenna structure parameters and performance parameters. CGAN in combination with Genetic Algorithm (GA) can be used to achieve antenna optimization quickly. The simulated impedance bandwidth obtained by the manual design of an irregular slot antenna is 45.9% (2.28-3.61 GHz) and the optimized impedance bandwidth is 49.66% (2.24-3.72 GHz). The experimental results show that the predicted data basically match the HFSS simulation data and the optimization objective is well accomplished. The method proposed in this paper speeds up the antenna optimization process and CGAN performs better in the optimization compared to MLP. The effectiveness and reliability of the method is demonstrated.