In small signal modeling, the perennial wisdom is that if you can match the S-parameters, then you will have an excellent model. However, this is not always the case. The input and output reflection coefficients, along with the stability factor K and the maximum available gain, are also very important optimization goals for a model. These goals are rarely met for a typical small signal model. Matching the S-parameters from data can be accomplished through optimization of intrinsic and extrinsic elements. This created model may not be accurate; the maximum available gain and K may not meet with the data's characteristics. Therefore, watching these parameters allows for a more accurate model. Adding reflection coefficients, max gain and K as goals allows the model to be as precise as possible. In the past, a model would be generated without any knowledge of the reflection coefficients, maximum gain or K and sent on to a designer. Any credible designer would automatically label it as unreliable and not use it for designing.
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