What is the Curtice model for a GaAs FET and when is it used?
Curtice GaAs FET Model
The Curtice model was groundbreaking when introduced in the 1980s, providing the first practical nonlinear model for GaAs MESFET circuit design. Understanding its limitations helps explain why more advanced models (Angelov, EE-HEMT) were developed.
Frequently Asked Questions
Are Curtice models still in circuit simulators?
Yes. Both Keysight ADS and Cadence AWR include the Curtice model in their transistor model libraries. This is primarily for: backward compatibility (older designs that use Curtice models can still be simulated), educational use (the Curtice model is simpler to understand than Angelov, making it useful for teaching), and quick simulations (the model runs faster than Angelov due to fewer parameters and simpler equations). However: for any new design, use the foundry-provided model (typically Angelov or EE-HEMT) or extract an Angelov model from measured data.
How many parameters does Curtice have vs Angelov?
Curtice quadratic: approximately 10-15 parameters (beta, V_TO, lambda, alpha, capacitance coefficients, and extrinsic elements). Curtice cubic: approximately 15-20 parameters. Angelov GaN: approximately 40-80 parameters (drain current: 10-15, charge model: 15-25, dispersion: 5-10, thermal: 3-5, extrinsic: 10-15). The higher parameter count in Angelov is needed to capture: the bell-shaped g_m (requires higher-order psi terms), the nonlinear capacitances (multi-dimensional charge functions), the dispersion (separate DC and RF parameters), and the self-heating (thermal resistance and temperature coefficients). The additional complexity provides significantly better accuracy, especially for: PA design in compression, harmonic prediction, and temperature-varying environments.
Can I convert a Curtice model to Angelov?
Not directly (the model equations are different). However: if you have measured data that was used to extract the Curtice model (DC I-V, S-parameters): you can re-extract an Angelov model from the same data. If you only have the Curtice model parameters (no measured data): (1) Generate synthetic I-V and S-parameter data from the Curtice model (simulate the Curtice model at many bias points). (2) Fit the Angelov model to the synthetic data. This provides an Angelov model that matches the Curtice behavior. But: it does not improve the accuracy (the Angelov model is only as good as the Curtice data it was fitted to). To truly improve accuracy: measure the actual device and extract a fresh Angelov model.