Abstract

In this work, a two-port graphene-ceramic-based antenna is designed and discussed. Some important features for the proposed two-port radiator are (a) the feed layout produces dual radiating modes, i.e., HEM11δ and HEM12δ inside the ceramic at 2.6 and 5.2 THz, respectively; (b) the asymmetrical swastik-shaped aperture creates the circularly polarized waves within dual operating bands, i.e., 2.71–2.84 and 5.15–5.42 THz; (c) a coating of graphene over ceramic makes the radiator frequency tunable by varying its chemical potential; and (d) deep neural network (DNN) and XGBoost-based machine learning (ML) algorithms are used to predict the |S11| parameter of the designed antenna in order to reduce the computational complexity. By comparing the optimized outcome obtained from HFSS with the CST EM simulator and predicted values from ML algorithms, it is verified that the designed two-port radiator works in dual frequency bands, i.e., 2.4–3.2 and 5.0–5.43 THz. Stable values of MIMO, as well as the far-field parameter, confirm the applicability of the designed antenna for THz wireless applications.

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