Citation
Alam, Md Mahabub and Ouameur, Messaoud Ahmed and Haque, Md Ershadul and Haque, Md. Ashraful and Tiang, Jun Jiat and Singh, Narinderjit Singh Sawaran and Alsulami, Ruwaybih and Alzahrani, Saeed (2026) Circular MIMO antenna with ML-based bandwidth and isolation prediction for 6G communications. Scientific Reports, 16 (1). ISSN 2045-2322|
Text
s41598-026-54274-w.pdf - Published Version Restricted to Repository staff only Download (6MB) |
Abstract
The demanding requirements of next-generation 6G wireless systems necessitate the development of compact, wideband, and high-isolation terahertz (THz) MIMO antennas, while conventional fullwave electromagnetic optimization remains computationally expensive for complex multi-parameter designs. To overcome these challenges, this work introduces a compact circular MIMO antenna integrated with a machine learning (ML)-based framework for efficient performance prediction and design optimization. The proposed antenna consists of two co-oriented circular radiating elements, enhanced with a concentric ring and side stubs to improve impedance matching and broaden bandwidth. High inter-element isolation is achieved through the incorporation of isolation walls and an optimized partial ground structure. The polyimide-based antenna, with compact dimensions of 130×70 μm², operates at 5.55 THz and provides a wide bandwidth of 4.56–5.86 THz, a peak gain of 8.04 dB, a radiation efficiency of 85.64%, a diversity gain (DG) of 9.985 dB, and a total active reflection coefficient (TARC) below −35 dB. To enable rapid performance estimation, an ML-based predictive model employing five supervised regression algorithms is trained using crucial geometrical parameters, including inner ring radius, feedline width, stub width, element spacing, and substrate height. Among the evaluated models, Cat Boost regression achieves the highest prediction accuracy, with R² scores of 97.05% for bandwidth and 92.56% for isolation. These results demonstrate that the proposed circular MIMO antenna, supported by ML-based predictive modeling, offers a promising solution for compact, high-performance antennas in 6G THz communication systems.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | THz antenna, Isolation, 6G |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101-6720 Telecommunication. Including telegraphy, telephone, radio, radar, television |
| Divisions: | Faculty of Artificial Intelligence & Engineering (FAIE) |
| Depositing User: | Ms Rosnani Abd Wahab |
| Date Deposited: | 30 Jun 2026 03:32 |
| Last Modified: | 30 Jun 2026 03:32 |
| URII: | http://shdl.mmu.edu.my/id/eprint/16126 |
Downloads
Downloads per month over past year
Edit (login required) |
