Abstract
The growing demand for high-speed communication necessitates antennas operating at higher frequencies in the THz range with broad bandwidth, compact size and higher gain. In this research, we have proposed a compact THz antenna designed with metamaterial-inspired elements to achieve improved gain and wideband performance. This paper presents the design and performance analysis of a high-efficiency MIMO antenna system for terahertz (THz) communication applications. The proposed antenna is optimized to deliver robust diversity performance, low mutual coupling, and minimal channel degradation. The design is also optimized with machine learning, with the highest R2 value of 0.95. The optimized design gives 54 THz bandwidth and 7.6 dBi gain. The ECC remains well below 0.005, ensuring excellent isolation between elements. The TARC exhibits values below − 10 dB across the critical bandwidth, confirming low reflection under simultaneous port excitation. These results demonstrate the designed structure’s potential for integration into THz communication and THz Wireless Personal Area Network.
Data availability
The data supporting the findings in this work are available from the corresponding author with reasonable request.
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Acknowledgements
This work was funded by the Deanship of Graduate Studies and Scientific Research at Jouf University under grant No. (DGSSR-2025-02-01655). This article has been produced with the financial support of the European Union under the REFRESH – Research Excellence For Region Sustainability and High-tech Industries project number CZ.10.03.01/00/22_003/0000048 via the Operational Programme Just Transition.
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Methodology, M.A, and Y.S. ,; software, M.A., Y.S. A.A, and K.A.; investigation, A.F. and S.P.; formal Analysis, all authors; writing—original draft preparation, All Authors,; writing—review and editing, All Authors,; All authors have read and agreed to the published version of the manuscript.
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Alsharari, M., Sharma, Y., Armghan, A. et al. Square-slotted THz metamaterial-inspired MIMO antenna design optimized with machine learning for TWPAN networks and next-generation communication systems. Sci Rep (2026). https://doi.org/10.1038/s41598-026-41207-w
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DOI: https://doi.org/10.1038/s41598-026-41207-w
