Competitive evolutionary algorithms for building performance database of a microwave transistor


GÜNEŞ F., Belen M. A., Mahouti P.

INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS, cilt.46, sa.2, ss.244-258, 2018 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 46 Sayı: 2
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1002/cta.2386
  • Dergi Adı: INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.244-258
  • Anahtar Kelimeler: microwave transistor, multiobjective optimization, competitive evolutionary algorithms, low-noise amplifier (LNA), cuckoo search algorithm, firefly algorithm, differential evolution algorithm, DIFFERENTIAL EVOLUTION, OPTIMIZATION, POWER
  • Yıldız Teknik Üniversitesi Adresli: Evet

Özet

In this work, the simultaneous trade-off relations among the noise figure F, gain G(T), input V-in, and output V-out VSWRs of a microwave transistor operated at a certain (V-DS, I-DS, f) condition are obtained fast and as accurate as the corresponding analytical results using multiobjective optimization process without any need for expertise on the microwave device, circuit, and noise. Three powerful evolutionary algorithms, cuckoo search, firefly, and differential evolution, are implemented comparatively as a study case to obtain the trade-off relations of a typical low-noise amplifier transistor NE3511S02 for its operation between 9 and 17GHz at V-DS=2V and I-DS=10mA. Finally, differential evolution is found as the most successful algorithm to demonstrate the typical trade-off relations of NE3511S02. It can be concluded that these trade-off relations being obtained by using a signal and noise model of the transistor enable performance database covering all the (FFmin, G(T), V(in)1, V(out)1) quadruples with their (Z(S), Z(L)) termination pairs using solely an evolutionary optimization process. Thus, a small signal transistor can be identified by its performance database to be used in the design optimization of high-performance low-noise amplifiers with the full device capacity.