Intelligent optimization of a graphene-based tunable THz split ring resonator metamaterial MIMO antenna for next-generation 6G wireless networks

A high-performance MIMO antenna system is proposed for next-generation 6G wireless communication. The design leverages advanced materials and compact geometry to ensure robust performance across THz frequencies. The antenna is engineered using metamaterials that integrate split ring resonators and thin wire structures, significantly enhancing its bandwidth, gain, and isolation for high-performance 6G communication applications. The Graphene is employed as a tunable switch, enabling dynamic control of antenna parameters and achieving effective reconfigurability in the design. Optimization is performed by varying key physical parameters to achieve enhanced antenna performance and ensure efficient 6G communication functionality. This novel approach of the presented work combines metamaterial inclusion, graphene tunability, and machine learning optimization, which can offer broadband, reconfigurability, and reproducible terahertz MIMO antenna performance. This terahertz MIMO antenna operates between 0.1 THz and 10 THz of frequency range. The achieved gain is 8.04 dB, and isolation is 50 dB. The design is showing ultrabroadband response with 2.5 THz bandwidth which can help in higher data rates. The performance analysis reveals that the Channel Capacity Loss (CCL) is measured at 0.03 bits/THz, indicating minimal degradation in channel capacity. Machine learning algorithms are implemented to predict antenna behavior and optimize various design parameters, resulting in improved performance, enhanced efficiency, and adaptability. The highest R 2 value is 0.9998 using a linear regression model of a machine learning algorithm. The designed antenna, offering dynamic reconfiguration, elevated gain, and broad frequency coverage, serves as an excellent solution for next-generation 6G and Terahertz Wireless Personal Area Network (TWPAN) systems.