Advertisement

Electrical Engineering

, Volume 100, Issue 2, pp 645–651 | Cite as

Development and validation of ANN approach for extraction of MESFET/HEMT noise model parameters

  • Vladica Ɖorđević
  • Zlatica Marinković
  • Vera Marković
  • Olivera Pronić-Rančić
Original Paper
  • 57 Downloads

Abstract

Most of the transistor noise models refer to the intrinsic device, providing relationships between the transistor noise model parameters and the noise parameters of the intrinsic device. Having in mind that the measured noise parameters correspond to the whole device including the device parasitics, the parameters of the noise models are most often determined by using optimizations in circuit simulators. In this paper, an efficient neural approach for straightforward determination of the noise model parameters, avoiding optimizations, is proposed. A detailed validation of the proposed approach was done by comparison of the measured transistor noise parameters with those obtained by using the extracted noise model parameters for two noise models—the Pospieszalski’s noise model and the noise wave model.

Keywords

Artificial neural network HEMT MESFET Noise parameters Noise wave model Pospieszalski’s noise model 

Notes

Acknowledgements

The work was supported by the TR-32052 Project of the Serbian Ministry of Education, Science and Technological Development. The authors would like to thank prof. Alina Caddemi, University of Messina, Italy, for providing the measured data.

References

  1. 1.
    Pucel RA, Haus HA, Statz H (1975) Signal and noise properties of gallium arsenide microwave field-effect transistors. Adv Electron Electron Phys 38:195–265. doi: 10.1016/S0065-2539(08)61205-6 CrossRefGoogle Scholar
  2. 2.
    Fukui H (1979) Design of microwave GaAs MESFET’s for broad-band low-noise amplifiers. IEEE Trans Microw Theory 27(7):643–650. doi: 10.1109/TMTT.1979.1129694 CrossRefGoogle Scholar
  3. 3.
    Cappy A, Vanoverschelde A, Schortgen A, Versnaeyen C, Salmer G (1985) Noise modeling in submicrometer-gate two-dimensional electron-gas field-effect transistors. IEEE Trans Electron Dev 32(12):2787–2795. doi: 10.1109/T-ED.1985.22417 CrossRefGoogle Scholar
  4. 4.
    Gupta MS, Pitzalis O, Rosenbaum SE, Greiling PT (1987) Microwave noise characterization of GaAs MESFETs: evaluation by on-wafer low-frequency output noise current measurement. IEEE Trans Microw Theory 35(12):1208–1218. doi: 10.1109/TMTT.1987.1133839 CrossRefGoogle Scholar
  5. 5.
    Pospieszalski MW (1989) Modeling of noise parameters of MESFET’s and MODFET’s and their frequency and temperature dependence. IEEE Trans Microw Theory 37(9):1340–1350. doi: 10.1109/22.32217 CrossRefGoogle Scholar
  6. 6.
    Meys RP (1978) A wave approach to the noise properties of linear microwave devices. IEEE Trans Microw Theory 26(1):34–37. doi: 10.1109/TMTT.1978.1129303 CrossRefGoogle Scholar
  7. 7.
    Hecken RP (1981) Analysis of liner noisy two-ports using scattering waves. IEEE Trans Microw Theory 29(10):997–1004. doi: 10.1109/TMTT.1981.1130490 CrossRefGoogle Scholar
  8. 8.
    Wedge SW, Rutledge DB (1992) Wave techniques for noise modeling and measurement. IEEE Trans Microw Theory 40(11):2004–2012. doi: 10.1109/22.168757 CrossRefGoogle Scholar
  9. 9.
    Pronić O, Marković V, Maleš-Ilić N (1999) MESFET noise modeling based on noise wave temperatures. In: Proceedings of international conference on telecommunications in modern satellite, cable and broadcasting services TELSIKS’99, Niš, pp 407–410. doi: 10.1109/TELSKS.1999.806241
  10. 10.
    Pronić O, Marković V, Maleš-Ilić N (2001) The wave approach to noise modeling of microwave transistors by including the correlation effect. Microw Opt Technol Lett 28(6):426–430. doi: 10.1002/1098-2760(20010320) 28:6\(<\)426: AID-MOP1061\(>\)3.0.CO;2-JCrossRefGoogle Scholar
  11. 11.
    Pronić O, Marković V (2002) A wave approach to signal and noise modeling of dual-gate MESFET. AEU-Int J Electron Commun 56(1):61–64. doi: 10.1109/MIKON.2000.913926 CrossRefGoogle Scholar
  12. 12.
    Rohde U (1991) Improved noise modeling of GaAs FETs part 2: using a noise de-embedding technique. Microw J 34:87–95Google Scholar
  13. 13.
    Pucel RA, Struble W, Hallgren R, Rohde UL (1992) A general noise de-embedding procedure for packed two-port linear active devices. IEEE Trans Microw Theory 40(11):2014–2024CrossRefGoogle Scholar
  14. 14.
    Crupi G, Schreurs DMM-P (2013) Microwave de-embedding: from theory to applications. Academic, OxfordGoogle Scholar
  15. 15.
    Guney K, Sarikaya N (2004) Artificial neural networks for the narrow aperture dimension calculation of optimum gain pyramidal horns. Electr Eng 86(3):157–163. doi: 10.1007/s00202-003-0197-z CrossRefGoogle Scholar
  16. 16.
    Rayas-Sanchez JE (2004) EM-based optimization of microwave circuits using artificial neural networks: the state-of-the-art. IEEE Trans Microw Theory 52(1):420–435. doi: 10.1109/TMTT.2003.820897 CrossRefGoogle Scholar
  17. 17.
    Marinković Z, Marković V (2005) Temperature dependent models of low-noise microwave transistors based on neural networks. Int J RF Microw Comput Aided Eng 15(6):567–577. doi: 10.1002/mmce.20102 CrossRefGoogle Scholar
  18. 18.
    Marinković Z, Pronić-Rančić O, Marković V (2008) ANN applications in improved noise wave modeling of microwave FETs. Microw Opt Technol Lett 50(10):2512–2516. doi: 10.1002/mop.23771 CrossRefGoogle Scholar
  19. 19.
    Marinković Z, Crupi G, Caddemi A, Marković V (2010) Comparison between analytical and neural approaches for multibias small signal modeling of microwave scaled FETs. Microw Opt Technol Lett 52(10):2238–2244. doi: 10.1002/mop.25432 CrossRefGoogle Scholar
  20. 20.
    Kabir H, Zhang L, Yu M, Aaen P, Wood J, Zhang QJ (2010) Smart modeling of microwave devices. IEEE Microw Mag 11(3):105–108CrossRefGoogle Scholar
  21. 21.
    Marinković Z, Crupi G, Schreurs DMM-P, Caddemi A, Marković V (2012) Multibias neural modeling of FIN field-effect transistor admittance parameters. Microw Opt Technol Lett 54(9):2082–2088. doi: 10.1002/mop.27020 CrossRefGoogle Scholar
  22. 22.
    Marinković Z, Ivković N, Pronić-Rančić O, Marković V, Caddemi A (2013) Analysis and validation of neural approach for extraction of small-signal models of microwave transistors. Microelectron Reliab 53(3):414–419. doi: 10.1016/j.microrel.2012.09.003 CrossRefGoogle Scholar
  23. 23.
    Cheng Z, Wang X, Zhang Q (2013) A novel modeling of millimeter-wave Al\(_{0.27}\)Ga\(_{0.73}\)N/AlN/GaN Hemt based on artificial neural network. Microw Opt Technol Lett 55(9):2124–2127. doi: 10.1002/mop.27776 CrossRefGoogle Scholar
  24. 24.
    Zhang QJ, Gupta KC (2000) Neural networks for RF and microwave design. Artech House, BostonGoogle Scholar
  25. 25.
    Đorđević V, Marinković Z, Marković V, Pronić-Rančić O (2014) A new procedure for extraction of noise wave parameters of microwave FETs. In: Proceedings of international scientific conference on information, communication and energy systems and technologies ICEST 2014, Niš, pp 135–138Google Scholar
  26. 26.
    Đorđević V, Marinković Z, Marković V, Pronić-Rančić O (2014) Extraction of Pospieszalski’s noise model parameters of microwave FETs based on ANNs. In: Proceedings of 12th symposium on neural network applications in electrical engineering NEUREL 2014, Belgrade, pp 51–54. doi: 10.1109/NEUREL.2014.7011457
  27. 27.
    Advanced Design System-version 2.7 (2008), Agilent Eesof EDAGoogle Scholar
  28. 28.
    Caddemi A, Di Paola A, Sannino M (1996) Microwave noise parameters of HEMTs vs. temperature by a simplified measurement procedure. In: Proceedings of high performance electron devices for microwave and optoelectronic applications workshop EDMO96, Leeds, pp 153–157. doi: 10.1109/EDMO.1996.575819

Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  • Vladica Ɖorđević
    • 1
  • Zlatica Marinković
    • 2
  • Vera Marković
    • 2
  • Olivera Pronić-Rančić
    • 2
  1. 1.Innovation Centre of Advanced TechnologiesNišSerbia
  2. 2.Faculty of Electronic EngineeringUniversity of NišNišSerbia

Personalised recommendations