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Frequency and bandwidth reconfigurable MIMO dielectric resonator antenna and its optimization using Taguchi neural network

Published online by Cambridge University Press:  14 November 2025

Yajush Rai
Affiliation:
Department of Electronics and Communication Engineering, Motilal Nehru National Institute of Technology Allahabad, Prayagraj, UP, India
Suyash Kumar Singh
Affiliation:
Department of Electronics and Communication Engineering, Indian Institute of Information Technology Allahabad, Prayagraj, UP, India
Anand Sharma*
Affiliation:
Department of Electronics and Communication Engineering, Motilal Nehru National Institute of Technology Allahabad, Prayagraj, UP, India
Smriti Agarwal
Affiliation:
Department of Electronics and Communication Engineering, Motilal Nehru National Institute of Technology Allahabad, Prayagraj, UP, India
Rajeev Gupta
Affiliation:
Department of Electronics and Communication Engineering, Motilal Nehru National Institute of Technology Allahabad, Prayagraj, UP, India
*
Corresponding author: Anand Sharma; Email: anandsharma@mnnit.ac.in
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Abstract

In this article, a 1 × 2 bandwidth (BW) and frequency-reconfigurable dielectric resonator-based multiple input multiple output (MIMO) antenna array is presented for 5G sub-6 GHz (3.3–6.0 GHz)/Wi-Fi 6E (5.925–6.425 GHz)/Wi-Fi 5G (5.15–5.85 GHz) applications. Additional dual-ring-open loop resonator structures with varied dimensions are introduced within antenna’s feeding network to achieve BW and frequency reconfigurability. RF PIN and varactor diodes (VDs) are integrated with proposed structure to enable switching between various modes and continuous tuning of frequency and BW, respectively. Further, Taguchi neural network (TNN) has been incorporated to predict percentage bandwidth of proposed antenna, getting a maximum deviation of only 0.6% from actual value. The proposed structure operated from 4.98 to 6.5 GHz, achieving wide continuous frequency tuning of 20.36% in passband and 6.1% reconfiguration for notch band. It also demonstrates continuous BW tunability from 16.69% to 34.44% with measured BWs of 19.58%, 34.44%, and 16.69% at 0, 3, and 8 V reverse bias voltages of VDs, respectively. MIMO antenna array structure also shows enhanced gain performance with a peak gain of 11.03 dBi and an overall gain above 7 dBi in the whole operating band.

Information

Type
Research Paper
Copyright
© The Author(s), 2025. Published by Cambridge University Press in association with The European Microwave Association.
Figure 0

Figure 1. Schematic of a single-element antenna for array design with key parameters and components.

Figure 1

Figure 2. Schematic diagram of (a) Ant. 1, (b) Ant. 2, (c) Ant. 3, and (d) Ant. 4.

Figure 2

Figure 3. S11 and E-field distribution for all four antenna configurations.

Figure 3

Figure 4. (a) Geometrical layout for isolation check between the two radiating elements for array design, and (b) S-parameters versus frequency curve.

Figure 4

Figure 5. A 1 × 2 array geometry with 3-dB power divider line.

Figure 5

Figure 6. (a) Comparative S11, and (b) Gain for single radiator geometry and array design.

Figure 6

Figure 7. (a) Bandpass and (b) Bandreject filter structures without diodes and biasing and their S-parameter curves, (c) Reconfigurable bandpass, (d) Bandreject filter design, (e, f) Single port reconfigurable filter + antenna array layout with biasing circuit for diodes and (g, h) S11 response of structures shown in (c, d), respectively, and surface current distribution for (i) All diodes OFF, PB mode at VD cap. (j) 0.55 pF, (k) 1.18 pF, (l) 9.01 pF and NB mode at VD cap, (m) 0.72 pF, and (n) 1.18 pF.

Figure 7

Figure 8. (a) Diode bias voltage-controlling diagram, and (b) DC biasing circuit, PIN diodes in (c) ON state, (d) OFF state, and (e) Varactor diode equivalent circuit diagram.

Figure 8

Table 1. Lumped elements (PD, VD) switching and tuning configurations for different modes of operation

Figure 9

Figure 9. Geometrical layout: (a) Top view and (b) Perspective view of the proposed reconfigurable 2-port MIMO antenna array structure.

Figure 10

Figure 10. (a, b) Simulated S-parameters for wideband mode, (c) Partial BW and frequency reconfigurable states for PB response at different capacitance values, (d) NB frequency tunability and MIMO performance parameters, (e) ECC/DG, and (f) CCL/TARC.

Figure 11

Figure 11. The Taguchi L9 design flow.

Figure 12

Figure 12. Architectural framework of the proposed TNN algorithm.

Figure 13

Table 2. Independent values used for the prediction

Figure 14

Table 3. The performance obtained in each trial of L9 Taguchi Network

Figure 15

Table 4. Comparison among different ML models

Figure 16

Figure 13. (a) Training and validation loss (mean square error) over epochs and (b) Comparative curve of actual and predicted values of the target variable.

Figure 17

Figure 14. (a) Plot of residuals (difference between actual and predicted values) vs the predicted values, (b) Distribution of residuals with superimposed density curve, and (c) comparative PDFs of predicted and actual values.

Figure 18

Figure 15. Fabricated prototype and measurement setup.

Figure 19

Figure 16. (a) Simulated and measured S11 parameter for mode 1, measured S11 for (b) Passband mode at 0, 3 and 8 V and (c) Notch band mode at 3, 4, and 5 V reverse bias voltages.

Figure 20

Figure 17. Simulated and measured (a) S-parameters for mode-1 (all diodes OFF), and (b) Gain, and simulated radiation efficiency of proposed reconfigurable MIMO antenna array.

Figure 21

Figure 18. Measured E/H plane co- and cross-polarization pattern at (a) 5.75 GHz and (b) 6 GHz.

Figure 22

Table 5. Comparative performance of the proposed structure with previous reconfigurable antennas