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On modeling of substrate loading in GaN HEMT using grey wolf algorithm

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In this paper, four different equivalent circuit models to describe substrate loading effect in GaN HEMT on Si substrate are investigated. The effect is characterized by Z-parameter measurements of open de-embedding structure for 16 × 200-μm GaN HEMT on Si substrate. The grey wolf optimization (GWO)-based procedure is developed to extract optimal values for the model elements. The performance of the proposed technique is evaluated by using two other meta-heuristic optimizations, the well-known particle swarm and the recently developed whale algorithm. The three extraction procedures are evaluated in terms of their effectiveness and rate of convergences. The models are validated by means of S-parameters simulation for the considered device at different passive and active bias conditions. A very good agreement with measurements is achieved when using the GWO, validating its applicability for small- and large-signal modeling applications.

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The author gratefully acknowledges the support from the University of Sharjah, Sharjah, United Arab Emirates.

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Correspondence to Anwar Jarndal.

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Jarndal, A. On modeling of substrate loading in GaN HEMT using grey wolf algorithm. J Comput Electron (2020).

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  • Grey wolf optimizer
  • Whale optimization algorithm
  • Particle swarm optimization
  • GaN HEMT
  • Open de-embedding structure
  • Substrate loading