Forthcoming

ANN-Enabled Gain Prediction and Optimization in Dual-Band SIW Antenna Designs for 5G Networks

Authors

  • Md Mahabub Alam Universiti Malaysia Pahang Al-Sultan Abdullah, Pahang, Malaysia https://orcid.org/0009-0005-5036-4608
  • Md Raihanul Islam Tomal Universiti Malaysia Pahang Al-Sultan Abdullah, Pahang, Malaysia
  • Ahmad Afif Mohd Faudzi Universiti Malaysia Pahang Al-Sultan Abdullah, Pahang, Malaysia
  • Nurhafizah Abu Talip Yusof Universiti Malaysia Pahang Al-Sultan Abdullah, Pahang, Malaysia https://orcid.org/0000-0001-9762-5119

DOI:

https://doi.org/10.26636/jtit.2026.1.2424

Keywords:

5G Network, ANN, gain prediction, machine learning, mmWave, SIW antenna

Abstract

Artificial neural networks (ANNs) help improve antenna design process by enabling adaptive optimization strategies that address important challenges in 5G wireless systems, including signal interference, limited coverage, and high user density. This study presents an AI-assisted design methodology for a compact dual-band substrate integrated waveguide (SIW) antenna optimized for 5G operation at 28 and 38 GHz. The antenna is implemented on a Rogers RT/Duroid 5880 substrate using a novel slot configuration with strategically positioned vias to enhance radiation characteristics. The fabricated prototype achieves gains of 8.05 dBi at 28 GHz and 7.89 dBi at 38 GHz, with fractional bandwidths of 6.41% (27.491 - 29.277 GHz) and 1.81% (37.496 - 38.179 GHz), while maintaining a return loss below -10 dB across both operating bands. The pivotal contribution of this work is the development of an ANN-based predictive model capable of accurately estimating antenna gain and radiation efficiency from main parameters such as slot dimensions, via size and feedline width. The proposed model demonstrates excellent predictive accuracy, achieving mean squared error values in the range of 0.00 to 0.001 for gain prediction and 0.018 to 0.066 for radiation efficiency estimation. This AI-driven framework significantly reduces design iterations, computational overhead, and prototyping requirements, offering an automated framework for efficient antenna development in next-generation 5G communication networks.

Downloads

Download data is not yet available.

References

[1] B. Kaur et al., "Internet of Things (IoT) Security Dataset Evolution: Challenges and Future Directions", Internet of Things, vol. 22, art. no. 100780, 2023. DOI: https://doi.org/10.1016/j.iot.2023.100780
View in Google Scholar

[2] N. Hussain et al., "A Metasurface-based Low-profile Wideband Circularly Polarized Patch Antenna for 5G Millimeter-wave Systems", IEEE Access, vol. 8, pp. 22127-22135, 2020. DOI: https://doi.org/10.1109/ACCESS.2020.2969964
View in Google Scholar

[3] B.A. Esmail and S. Koziel, "Design and Optimization of Metamaterial-based Dual-band 28/38 GHz 5G MIMO Antenna with Modified Ground for Isolation and Bandwidth Improvement", IEEE Antennas and Wireless Propagation Letters, vol. 22, pp. 1069-1073, 2022. DOI: https://doi.org/10.1109/LAWP.2022.3232622
View in Google Scholar

[4] S.K. Hinga and A.A. Atayero, "Deterministic 5G mmWave Large-scale 3D Path Loss Model for Lagos Island, Nigeria", IEEE Access, vol. 9, pp. 134270-134288, 2021. DOI: https://doi.org/10.1109/ACCESS.2021.3114771
View in Google Scholar

[5] J. Lu, G. Huang, D. Hu, and W. Kuai, "Multi-path Data Transmission System Based on 5G Communication Technology", Journal of ICT Standardization, vol. 12, no. 1, pp. 71-94, 2024. DOI: https://doi.org/10.13052/jicts2245-800X.1214
View in Google Scholar

[6] N.S. Khair et al., "Recent Advances and Open Challenges in RFID Antenna Applications", Enabling Industry 4.0 through Advances in Mechatronics, vol. 900, pp. 507-517, 2022. DOI: https://doi.org/10.1007/978-981-19-2095-0_43
View in Google Scholar

[7] B. Qian, X. Chen, and A.A. Kishk, "Decoupling of Microstrip Antennas with Defected Ground Structure Using the Common/differential Mode Theory", IEEE Anten. and Wireless Prop. Lett., vol. 20, pp. 828-832, 2021. DOI: https://doi.org/10.1109/LAWP.2021.3064972
View in Google Scholar

[8] B.S. Bari et al., "Performance Comparison of Early Breast Cancer Detection Precision Using AI and Ultra-wideband (UWB) Bio-antennas", Proc. of Conference on Cyber Security and Computer Science, pp. 354-365, 2020. DOI: https://doi.org/10.1007/978-3-030-52856-0_28
View in Google Scholar

[9] L.H. Xu et al., "Bandwidth Enhancement of the Millimeter-wave Microstrip Linear Array with Loading of Shorting Pins", IEEE Transactions on Antennas and Propagation, vol. 71, pp. 1105-1110, 2022. DOI: https://doi.org/10.1109/TAP.2022.3211398
View in Google Scholar

[10] B. Cheng and Z. Du, "A Wideband Low-profile Microstrip MIMO Antenna for 5G Mobile Phones", IEEE Transactions on Antennas and Propagation, vol. 70, pp. 1476-1481, 2021. DOI: https://doi.org/10.1109/TAP.2021.3111330
View in Google Scholar

[11] M.M. Alam et al., "Design and Optimization of Π-shaped Slotted Dual-band SIW Antenna for 5G Applications", Applications of Modelling and Simulation, vol. 9, pp. 92-106, 2025.
View in Google Scholar

[12] D. Prabhakar, P. Karunakar, S.R. Rao, and K. Srinivas, "Prediction of Microstrip Antenna Dimension Using Optimized Auto-metric Graph Neural Network", Intelligent Systems with Applications, vol. 21, art. no. 200326, 2024. DOI: https://doi.org/10.1016/j.iswa.2024.200326
View in Google Scholar

[13] P. Kontou, S.B. Smida, and D.E. Anagnostou, "Contactless Respiration Monitoring Using Wi-Fi and Artificial Neural Network Detection Method", IEEE Journal of Biomedical and Health Informatics, vol. 28, pp. 1297-1308, 2023. DOI: https://doi.org/10.1109/JBHI.2023.3337001
View in Google Scholar

[14] M.A. Haque et al., "Machine Learning-based Approach for Bandwidth and Frequency Prediction for N77 band 5G Antenna", Physica Scripta, vol. 99, art. no. 026005, 2024. DOI: https://doi.org/10.1088/1402-4896/ad1d40
View in Google Scholar

[15] H. Ibn-Khedher et al., "Next-generation Edge Computing Assisted Autonomous Driving Based Artificial Intelligence Algorithms", IEEE Access, vol. 10, pp. 53987-54001, 2022. DOI: https://doi.org/10.1109/ACCESS.2022.3174548
View in Google Scholar

[16] M.M. Alam et al., "Machine Learning-based Approach for Bandwidth and Frequency Prediction of Circular SIW Antenna", Journal of King Saud University-Engineering Sciences, vol. 37, art. no. 9, 2025. DOI: https://doi.org/10.1007/s44444-025-00010-0
View in Google Scholar

[17] S. Koziel, A. Pietrenko-Dabrowska, and L. Leifsson, "Antenna Optimization Using Machine Learning with Reduced-dimensionality Surrogates", Scientific Reports, vol. 14, art. no. 21567, 2024. DOI: https://doi.org/10.1038/s41598-024-72478-w
View in Google Scholar

[18] J. Zhang, M.O. Akinsolu, B. Liu, and G.A. Vandenbosch, "Automatic AI-driven Design of Mutual Coupling Reducing Topologies for Frequency Reconfigurable Antenna Arrays", IEEE Transactions on Antennas and Propagation, vol. 69, pp. 1831-1836, 2020. DOI: https://doi.org/10.1109/TAP.2020.3012792
View in Google Scholar

[19] Z. Xu, J. Liu, S. Huang, and Y. Li, "Gain-enhanced SIW Cavity-backed Slot Antenna by Using TE410 Mode Resonance", AEU - International Journal of Electronics and Communications, vol. 98, pp. 68-73, 2019. DOI: https://doi.org/10.1016/j.aeue.2018.10.039
View in Google Scholar

[20] Y. Shi, W.J. Wang, and T.T. Hu, "A Transparent SIW Cavity-based Millimeter-wave Slot Antenna for 5G Communication", IEEE Antennas and Wireless Propagation Letters, vol. 21, pp. 1105-1109, 2022. DOI: https://doi.org/10.1109/LAWP.2022.3158418
View in Google Scholar

[21] R. Olu-Ajayi et al., "Building Energy Consumption Prediction for Residential Buildings Using Deep Learning and Other Machine Learning Techniques", Journal of Building Engineering, vol. 45, art. no. 103406, 2022. DOI: https://doi.org/10.1016/j.jobe.2021.103406
View in Google Scholar

[22] Z.M. Abdhafith, R.A. Ali, and N. Abohmooed, "Impact of Substrate Thickness on the Rectangular Patch Antenna for 5G Communication System by CST Studio", Wadi Alshatti University Journal of Pure and Applied Sciences, vol. 2, pp. 79-83, 2024 (https://waujpas.com/index.php/journal/article/view/60/37).
View in Google Scholar

[23] R. Ramasamy and M.A. Bennet, "An Efficient Antenna Parameters Estimation Using Machine Learning Algorithms", Progress In Electromagnetics Research C, vol. 130, pp. 169-181, 2023. DOI: https://doi.org/10.2528/PIERC22121004
View in Google Scholar

[24] D.S.K. Karunasingha, "Root Mean Square Error or Mean Absolute Error? Use their Ratio as Well", Information Sciences, vol. 585, pp. 609-629, 2022. DOI: https://doi.org/10.1016/j.ins.2021.11.036
View in Google Scholar

[25] T.O. Hodson, "Root Mean Square Error (RMSE) or Mean Absolute Error (MAE): When to Use Them or Not", Geoscientific Model Development, vol. 15, pp. 5481-5487, 2022. DOI: https://doi.org/10.5194/gmd-15-5481-2022
View in Google Scholar

[26] P. Liu et al., "Patch Antenna Loaded with Paired Shorting Pins and H-shaped Slot for 28/38 GHz Dual-band MIMO Applications", IEEE Access, vol. 8, pp. 23705-23712, 2020. DOI: https://doi.org/10.1109/ACCESS.2020.2964721
View in Google Scholar

[27] P. Kumawat and S. Joshi, "5G Dual-band Slotted SIW Array Antenna", Journal of Taibah University for Science, vol. 15, pp. 321-328, 2021. DOI: https://doi.org/10.1080/16583655.2021.1978830
View in Google Scholar

[28] J. Singh, F.L. Lohar, and B.S. Sohi, "Design of Dual Band Millimeter Wave Antenna Using SIW Material for 5G Cellular Network Applications", Materials Today: Proceedings, vol. 45, pp. 5405-5409, 2021. DOI: https://doi.org/10.1016/j.matpr.2021.02.106
View in Google Scholar

[29] A.E. Farahat and K.F. Hussein, "Dual-band (28/38 GHz) Wideband MIMO Antenna for 5G Mobile Applications", IEEE Access, vol. 10, pp. 32213-32223, 2022. DOI: https://doi.org/10.1109/ACCESS.2022.3160724
View in Google Scholar

[30] A. Khabba, J. Amadid, S. Ibnyaich, and A. Zeroual, "Pretty-small Four-port Dual-wideband 28/38 GHz MIMO Antenna with Robust Isolation and High Diversity Performance for Millimeter-wave 5G Wireless Systems", Analog Integrated Circuits and Signal Processing, vol. 112, pp. 83-102, 2022. DOI: https://doi.org/10.1007/s10470-022-02045-8
View in Google Scholar

[31] K. Cuneray, N. Akcam, T. Okan, and G.O. Arican, "28/38 GHz Dual-band MIMO Antenna with Wideband and High Gain Properties for 5G Applications", AEU - International Journal of Electronics and Communications, vol. 162, art. no. 154553, 2023. DOI: https://doi.org/10.1016/j.aeue.2023.154553
View in Google Scholar

[32] R.R. Elsharkawy, K.F. Hussein, and A.E. Farahat, "Dual-band (28/38 GHz) Compact MIMO Antenna System for Millimeter-wave Applications", Journal of Infrared, Millimeter, and Terahertz Waves, vol. 44, pp. 1016-1037, 2023. DOI: https://doi.org/10.1007/s10762-023-00943-0
View in Google Scholar

[33] L. Sellak et al., "ANN-based Design of Miniaturized Circular Dual-band 4×4 MIMO Antenna for 28/38 GHz 5G mmWave Applications", Telkomnika, vol. 22, pp. 1280-1292, 2024. DOI: https://doi.org/10.12928/telkomnika.v22i5.26347
View in Google Scholar

[34] S. Md, R. Islam, and S. Sarker, "Machine Learning Based on Patch Antenna Design and Optimization for 5 G Applications at 28 GHz", Results in Engineering, vol. 24, art. no. 103366, 2024. DOI: https://doi.org/10.1016/j.rineng.2024.103366
View in Google Scholar

cover page 1_2026 early access

Downloads

Published

2026-03-02

Issue

Early View

Section

ARTICLES FROM THIS ISSUE

License

Copyright (c) 2026 Md Mahabub Alam, Md Raihanul Islam Tomal, Ahmad Afif Mohd Faudzi, Nurhafizah Abu Talip Yusof

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
M. M. . Alam, M. R. I. . Tomal, A. A. M. Faudzi, and N. Abu Talip Yusof, “ANN-Enabled Gain Prediction and Optimization in Dual-Band SIW Antenna Designs for 5G Networks”, JTIT, vol. 103, no. 1, pp. 69–78, Mar. 2026, doi: 10.26636/jtit.2026.1.2424.