Progress In Electromagnetics Research
ISSN: 1070-4698, E-ISSN: 1559-8985
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By X. Li and J. Gao

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An approach for the PAD modeling technique for microwave on wafer measurement based on a combination of the conventional equivalent circuit model and artificial neural network (ANN) is presented in this paper. The PAD capacitances are determined from S parameters of different size of PAD test structure based on EM (electromagnetic) simulation and described as functions of the dimensions of the PAD structure by using sub-ANN. Good agreement is obtained between ANN-based modeling and EM simulated results up to 40 GHz. The de-embedding procedure for PHEMT device utilizing the ANN based PAD model is demonstrated.

X. Li and J. Gao, "Pad Modeling by Using Artificial Neural Network," Progress In Electromagnetics Research, Vol. 74, 167-180, 2007.

1. Kim, C. S. and J.-W. Park, "Gate layout and bonding pad structure of a RF n-MOSFET for low noise performance," IEEE Electron Device Letter, Vol. 21, No. 12, 607-609, 2000.

2. Sang, L. P., et al., "High-isolation bonding pad design for silicon RFIC up to 20 GHz," IEEE Electron Device Letters, Vol. 24, No. 9, 601-603, 2003.

3. Troels, E. K., "Shield-based microwave on-wafer device measurements," IEEE Transactions on Microwave Theory and Techniques, Vol. 49, No. 6, 1039-1044, 2001.

4. Han, S., J. Kim, Dean, and P. Neikirk, "Impact ofpad de-embedding on the extraction ofin terconnect parameters," 2006IEEE APS, Vol. 1, 76-81, 2006.

5. Ewout, P., V. Dominique, M. M.-P. Schreures, and C. Van Dinther, "Improved three-step de-embedding method to accurately account for the influence of pad parasitics in silicon onwafer RF test-structures," IEEE Transactions on Electon Devices, Vol. 48, No. 4, 737-742, 2001.

6. Su, C. Y., et al., "Effect ofCoplanar probe pad design on noise figures of0.35 um MOSFETS," Electronics Letters, Vol. 36, No. 15, 1280-1281, 2000.

7. Adem, A. and M. Ismail, "Pad de-embedding in RF CMOS," Circuit and System, 8-11, 2001.

8. Cascade Microtech, Inc., "On-wafer vector network analyzer calibration and measurements," Application Note..

9. Cascade Microtech, Inc., "Introduction to bipolar device GHz measurement techniques," Application Note..

10. Cascade Microtech, Inc., "Layout rules for GHz-probing," Application Note..

11. Van Wijnen, P. J., et al., A new straightforward calibration and correction procedure for on wafer high frequency s-parameter measurements (45 MHz-18 GHz), Proc. 1987 Bipolar Circuits and Technology Meeting, 70-73, 1987.

12. Fraser, A., R. Gleason, and E. W. Strid, GHz on-silicon wafer probing calibration methods, Proc. 1988 Bipolar Circuits and Technology Meeting, 154-157, 1988.

13. Li, X. P., J. J. Gao, and G. Boeck, "Printed dipole antenna design by artificial neural network modeling for RFID application," International Journal of RF and Microwave Computer-Aided Engineering, Vol. 16, No. 6, 607-611, 2006.

14. Li, X. P., J. J. Gao, J.-G. Yook, and X. D. Chen, Bandpass filter design by artificial neural network modeling, Asia-Pacific Microwave Conference, Vol. 2, 713-716, 2005.

15. Guney, K., C. Yildiz, S. Kaya, and M. Turkmen, "Artificial neural networks for calculating the characteristic impedance of airsuspended trapezoidal and rectangular-shaped microshield lines," Journal of Electromagnetic Waves and Applications, Vol. 20, No. 9, 1161-1174, 2006.

16. Jin, L., C. L. Ruan, and L. Y. Chun, "Design E-plane bandpass filter based on EM-ANN model," Journal of Electromagnetic Waves and Applications, Vol. 20, No. 8, 1061-1069, 2006.

17. Mohamed, M. D. A., E. A. Soliman, and M. A. El- Gamal, "Optimization and characterization ofelectromagnetically coupled patch antennas using RBF neural networks," Journal of Electromagnetic Waves and Applications, Vol. 20, No. 8, 1101-1114, 2006.

18. Ayestarn, R. G. and F. Las-Heras, "Near field to far field transformation using neural networks and source reconstruction," Journal of Electromagnetic Waves and Applications, Vol. 20, No. 15, 2201-2213, 2006.

19. Zhang, Q. J., K. Gupta, C. Devabhaktuni, and K. Vijay, "Artificial neural networks for RF and microwave design—from theory to practice," IEEE Trans. Microwave Theory Tech., Vol. 51, 1339-1350, 2003.

20. Li, X. P., J. J. Gao, and G. Boeck, "Microwave nonlinear device modeling using artificial neural network," Semicond. Sci. Technol., Vol. 21, 833-840, 2006.

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