Abstract :

The Rapid Evolution Of Sixth-generation (6G) Wireless Communication Demands Highly Efficient, Compact, And Intelligent Antenna Systems Capable Of Operating In The Terahertz (THz) Frequency Spectrum. Conventional Antenna Design Methods Rely On Repeated Full-wave Electromagnetic Simulations And Iterative Optimization Techniques, Resulting In High Computational Cost, Long Development Cycles, And Limited Scalability For Complex Antenna Geometries. To Overcome These Challenges, This Research Proposes An Artificial Intelligence (AI)-Driven Inverse Design And Optimization Framework For Compact Terahertz Antennas In 6G Wireless Communication Systems. The Proposed Framework Integrates MATLAB-based Electromagnetic Simulation With Deep Learning Techniques To Automate Antenna Synthesis Based On User-defined Electromagnetic Performance Requirements.

Published:

25-7-2026

Issue:

Vol. 26 No. 7 (2026)

Page Nos:

941 - 949

Section:

Articles

License:

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

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