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Performance prediction of a circularly polarized graphene-dielectric resonator-based antenna for THz frequency application using machine learning algorithms

Kundan Kumar and Pradip Kumar Sadhu

Open Access Open Access

Abstract

In this article, a graphene-dielectric resonator-based antenna is designed in the THz frequency regime. Circular polarization is achieved by feeding the cylindrical-shaped ceramic using a perturbed square-shaped aperture. Graphene loading over the alumina ceramic provides the frequency reconfigurable feature. In order to overcome the difficulty of simulating the THz antenna (i.e., very large simulation time), machine learning algorithms such as the artificial neural network (ANN) and random forest are used to effectively predict the performance of the designed antenna. The proposed antenna works effectively in between 5.0 and 5.5 THz with a 3 dB axial ratio frequency range from 5.1 to 5.35 THz. There is good correlation found between the predicted, measured, and simulated reflection coefficient and axial ratio. Due to stable radiation properties and good diversity performance within the operating frequency band, the proposed antenna can be employable for different wireless applications in the THz frequency regime.

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Data availability

Data underlying the results presented in this paper may be obtained from the authors upon reasonable request.

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Figures (13)
Fig. 1.
Fig. 1. Designed layout of ceramic-based THz antenna. (a) Excitation mechanism; (b) panoramic view.

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Fig. 2.
Fig. 2. $|{\rm S11|}$ variation of designed antenna in the presence/absence of cylindrical ceramic.

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Fig. 3.
Fig. 3. E-field variation on cylindrical ceramic at 5.15 THz. (a) Top view; (b) side view.

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Fig. 4.
Fig. 4. $|{\rm S11|}$ variation of with different changes in the square-shaped slot.

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Fig. 5.
Fig. 5. Axial ratio variation of with different changes in the square-shaped slot.

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Fig. 6.
Fig. 6. $|{\rm S11|}$ variation with change in chemical potential (uc) of graphene.

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Fig. 7.
Fig. 7. Axial ratio variation with change in chemical potential (uc) of graphene.

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Fig. 8.
Fig. 8. Comparison between actual and predicted $|{\rm S11|}$. (a) ANN; (b) random forest.

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Fig. 9.
Fig. 9. Comparison between actual and predicted axial ratio. (a) ANN; (b) random forest.

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Fig. 10.
Fig. 10. $|{\rm S11|}$ variation with HFSS/CST-MWS/ANN/Random Forest.

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Fig. 11.
Fig. 11. Axial ratio $|{\rm S11|}$ variation with HFSS/CST-MWS/ANN/Random Forest.

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Fig. 12.
Fig. 12. Gain variation of designed antenna w.r.t. frequency.

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Fig. 13.
Fig. 13. 2D RHCP/LHCP radiation pattern of designed antenna in XZ plane at 5.25 THz.

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Tables (4)

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Table 1. Optimized Dimension of Various Parameters of Structured THz Antenna

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Table 2. Performance Comparison of ANN and Random Forest Based on MAE, MSE, and R-Square Value for | S 11 | Prediction

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Table 3. Performance Comparison of ANN and Random Forest Based on MAE, MSE, and R-Square Value for Axial Ratio Prediction

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Table 4. Performance Assessment of Designed THz Antenna with Other Published Ceramic-Based THz Radiators

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Equations (5)

Equations on this page are rendered with MathJax. Learn more.

ε A S = ε a i r [ ε r − f p 2 { f + i f c l } ] .
f r , H E M 11 δ = 6.324 c 2 π D ε S i + 2 { 0.27 + 0.36 ( D H ) + 0.02 ( d H ) 2 } .
M S E = ( 1 / n ) ∗ Σ ( a c t u a l − f o r e c a s t ) 2 ,
M A E = ( T r u e v a l u e s − P r e d i c t e d v a l u e s ) .
R - s q u a r e = 1 − ( S u m o f s q u a r e s o f r e s i d u a l s / T o t a l s u m o f s q u a r e s ) .
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