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Dual-band graphene-based THz MIMO antenna for 6G-enabled biomedical application using supervised regression machine
Md Ashraful Haque1, Maruf Billah2, Jun-Jiat Tiang3
1Department of Electrical and Electronic Engineering, University of Liberal Arts Bangladesh (ULAB), Dhaka, 1207, Bangladesh. limon.ashraf@gmail.com.
Scientific Reports
|May 1, 2026
Summary
This study introduces a novel graphene antenna for terahertz (THz) frequencies, enhancing 6G wireless and biomedical sensing. The design achieves high gain and efficiency, optimized using machine learning for faster development.
Area of Science:
- Electrical Engineering
- Materials Science
- Biomedical Engineering
Background:
- Increasing wireless data traffic necessitates advanced antenna solutions.
- Terahertz (THz) frequencies offer potential for high-speed communication and sensitive biomedical sensing.
Purpose of the Study:
- To design and optimize a graphene-based microstrip patch antenna for 6G communications and biomedical applications.
- To explore novel slot geometries and MIMO configurations for improved antenna performance.
Main Methods:
- Development of a dual-band graphene microstrip patch antenna with novel slot designs.
- Integration of RLC equivalent circuit modeling and machine learning (ML) for performance optimization.
- Material analysis to identify optimal materials (graphene, polyimide) for THz devices.
Main Results:
- Achieved dual-band operation with a narrowband (0.2839 THz) and wideband (3.8201 THz).
- Demonstrated high peak gain (12.83 dB), efficiency (93.1%), and isolation (-38.8 dB).
- ML model validation showed high accuracy and reduced design time.
Conclusions:
- The proposed graphene antenna is suitable for high-data-rate, low-latency wireless systems and advanced biomedical sensing.
- The integration of ML significantly accelerates the design and optimization process for THz antennas.
- Graphene and polyimide are promising materials for efficient, miniaturized THz devices.
