Optimizing High-Frequency Antenna Design through Genetic Algorithm-Based Electromagnetic Simulation
DOI:
https://doi.org/10.51903/jtie.v4i3.452Keywords:
6G Communication, Broadband Antenna, Genetic Algorithm, Electromagnetic Simulation, CST/HFSSAbstract
The emergence of sixth-generation (6G) wireless networks demands broadband antennas capable of ultra-high data throughput and seamless global connectivity. This study presents a genetic-algorithm (GA) optimization framework to enhance antenna performance, focusing on patch dimensions, ground-plane size, and feed position. Full-wave electromagnetic simulations were performed in CST Microwave Studio and ANSYS HFSS, employing defined mesh sizes, solver types, and boundary conditions to ensure accurate evaluation. The GA-based optimization achieved an impedance bandwidth of 3.2–6.1 GHz, a peak gain improvement of 2.8 dB, and radiation efficiency exceeding 92%, outperforming conventional gradient-based tuning. The optimized antenna exhibited stable S-parameters and an omnidirectional radiation pattern across the target spectrum, confirming reliable operation at high frequencies. This approach highlights the advantages of evolutionary algorithms in enabling efficient, manufacturable, and high-performance broadband antenna designs for next-generation wireless systems. Beyond immediate 6G applications, the methodology can be extended to millimeter-wave and terahertz antennas, supporting continued innovation in ultra-reliable, high-capacity wireless communications.
References
Ahmad, T., Zhang, D., Huang, C., Zhang, H., Dai, N., Song, Y., & Chen, H. (2021). Artificial Intelligence in Sustainable Energy Industry: Status Quo, Challenges and Opportunities.
Akhtar, M. W., Hassan, S. A., Ghaffar, R., Jung, H., Garg, S., & Hossain, M. S. (2020). The shift to 6G communications: vision and requirements. Human-Centric Computing and Information Sciences, 10(1). https://doi.org/10.1186/s13673-020-00258-2
Ali, M. Z., Abohmra, A., Usman, M., Zahid, A., Heidari, H., Imran, M. A., & Abbasi, Q. H. (2023). Quantum for 6G communication: A perspective. IET Quantum Communication, 4(3), 112–124. https://doi.org/10.1049/qtc2.12060
Al-Sehemi, A., Al-Ghamdi, A., Dishovsky, N., Atanasova, G., & Atanasov, N. (2020). A flexible broadband antenna for IoT applications. International Journal of Microwave and Wireless Technologies, 12(6), 531–540. https://doi.org/10.1017/S1759078720000161
An, Q., Li, D., Liao, W., Liu, T., Joralmon, D., Li, X., & Zhao, J. (2023). A Novel Ultra-Wideband Electromagnetic-Wave-Absorbing Metastructure Inspired by Bionic Gyroid Structures. Advanced Materials, 35(26). https://doi.org/10.1002/adma.202300659
Anwar, M. S., Abufanas, H., & Bangert, A. (2020). 3D printed dielectric lens for the gain enhancement of a broadband antenna. International Journal of RF and Microwave Computer-Aided Engineering, 30(4). https://doi.org/10.1002/mmce.22115
Chandan, R. R., Soni, S., Raj, A., Veeraiah, V., Dhabliya, D., Pramanik, S., & Gupta, A. (2023). Genetic Algorithm and Machine Learning (pp. 167–182). https://doi.org/10.4018/978-1-6684-5656-9.ch009
Chowdhury, M. Z., Shahjalal, M., Ahmed, S., & Jang, Y. M. (2020). 6G Wireless Communication Systems: Applications, Requirements, Technologies, Challenges, and Research Directions. IEEE Open Journal of the Communications Society, 1, 957–975. https://doi.org/10.1109/OJCOMS.2020.3010270
Dang, S., Amin, O., Shihada, B., & Alouini, M.-S. (2020). What should 6G be? https://doi.org/10.1038/s41928-019-0355-6
Gad, A. F. (2021). PyGAD: An Intuitive Genetic Algorithm Python Library. http://arxiv.org/abs/2106.06158
Ghofur, M. J. U., & Riyanto, E. (2025). AI-Driven Adaptive Radar Systems for Real-Time Target Tracking in Urban Environments. Journal of Technology Informatics and Engineering, 4(1). https://doi.org/10.51903/jtie.v4i1.289
Gustavsson, U., Frenger, P., Fager, C., Eriksson, T., Zirath, H., Dielacher, F., Studer, C., Pärssinen, A., Correia, R., Matos, J. N., Belo, D., & Carvalho, N. B. (2021). Implementation Challenges and Opportunities in Beyond-5G and 6G Communication. IEEE Journal of Microwaves, 1(1), 86–100. https://doi.org/10.1109/JMW.2020.3034648
Harrisha, M., Monikasree, J., Swathi, J., & Karthika, D. (2025). Smart Healthcare: Harnessing AI for Early prediction of Neurodegenerative disease. Journal of Technology Informatics and Engineering, 4(2), 214–224. https://doi.org/10.51903/jtie.v4i2.269
Ibrahim, S. M., Go, E.-M., & Iranda, J. (2024). Scalable and Secure IoT-Driven Vibration Monitoring: Advancing Predictive Maintenance in Industrial Systems. Journal of Technology Informatics and Engineering, 3(3), 370–381. https://doi.org/10.51903/jtie.v3i3.210
Jiang, J., & Fan, J. A. (2019). Simulator-based training of generative neural networks for the inverse design of metasurfaces. Nanophotonics, 1059–1069. https://doi.org/10.1515/nanoph-2019-0330
Kiarashinejad, Y., Abdollahramezani, S., & Adibi, A. (2020). Deep learning approach based on dimensionality reduction for designing electromagnetic nanostructures. Npj Computational Materials, 6(1). https://doi.org/10.1038/s41524-020-0276-y
Kim, C., Batra, R., Chen, L., Tran, H., & Ramprasad, R. (2020). Polymer Design using Genetic Algorithm and Machine Learning. https://www.sciencedirect.com/science/article/pii/S0927025620305589
Liu, Y., Yuan, X., Xiong, Z., Kang, J., Wang, X., & Niyato, D. (2020). Federated Learning for 6G Communications: Challenges, Methods, and Future Directions. https://doi.org/10.23919/JCC.2020.09.009
Lv, H., Yang, Z., Xu, H., Wang, L., & Wu, R. (2020). An Electrical Switch-Driven Flexible Electromagnetic Absorber. Advanced Functional Materials, 30(4). https://doi.org/10.1002/adfm.201907251
Mohammed, S. H., Ameen, M. M., & Hasan, S. O. (2023). Optimization of Pyramidal and Conical Horn Antennas Parameters to Operate with High Radiation Performances for 5G Communication Using CST and HFSS Techniques. https://doi.org/10.21271/zjpas
Naji, D. K. (2023). A Compact Dual-Band CPW-Fed Slotted-Ring Monopole Antenna with Circular Fractal Elements for WiMAX and C Bands Applications. In Progress In Electromagnetics Research C (Vol. 137).
Nayak, S., & Patgiri, R. (2020). 6G Communication: Envisioning the Key Issues and Challenges. https://doi.org/10.4108/eai.11-11-2020.166959
Packard, D. A., Cooleybeck, A., Jordan, N. M., Sporer, B. J., Mazarakis, A. E., Lau, Y. Y., Gilgenbach, R. M., & McBride, R. D. (2020). HFSS and CST Simulations of a GW-Class MILO. IEEE Transactions on Plasma Science, 48(6), 1894–1901. https://doi.org/10.1109/TPS.2020.2990163
Saha, S., Gan, Z., Cheng, L., Gao, J., Kafka, O. L., Xie, X., Li, H., Tajdari, M., Kim, H. A., & Liu, W. K. (2020). Hierarchical Deep Learning Neural Network (HiDeNN): an Artificial Intelligence (AI) Framework for Computational Science and Engineering. https://www.elsevier.com/open-access/userlicense/1.0/
Sholekhah, D. Z., & Noviar, D. (2025). Integrative Deep Learning Architecture for High-Accuracy Medical Image Segmentation: Combining U-Net, ResNet, and Transformers. Journal of Technology Informatics and Engineering, 4(1), 115–134. https://doi.org/10.51903/jtie.v4i1.288
Sifat, R., Faruque, M. R. I., Ramachandran, T., Abdullah, M., Islam, M. T., & Al-Mugren, K. S. (2024). Development of double-layer metamaterial with high effective medium ratio values for S- and C-band applications. Heliyon, 10(1). https://doi.org/10.1016/j.heliyon.2023.e23851
Susatyono, J. D., Suasana, I. S., & Rozikin, K. (2024). Integrating Big Data and Edge Computing for Enhancing AI Efficiency in Real-Time Applications. Journal of Technology Informatics and Engineering, 3(3), 337–349. https://doi.org/10.51903/jtie.v3i3.204
Weiss, R. (2022). Republication of: Electromagnetically coupled broadband gravitational antenna. General Relativity and Gravitation, 54(11). https://doi.org/10.1007/s10714-022-03021-3
Zheng, Y., Vandenbosch, G. A. E., & Yan, S. (2020). Low-Profile Broadband Antenna with Pattern Diversity. IEEE Antennas and Wireless Propagation Letters, 19(7), 1231–1235. https://doi.org/10.1109/LAWP.2020.2996196
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