A new hybrid multibias analytical/decomposition-based FET parameter extraction algorithm with intelligent bias point selection

A new hybrid multibias analytical/decomposition-based parameter extraction procedure for GaAs FETs is described. The analytical calculations are integrated into an existing decomposition-based optimizer in a complementary approach, further increasing the robustness of the existing algorithm. It is illustrated that, in order to increase the reliability with which the full 15-element small-signal model can be extracted, it is necessary to exploit the underlaying characteristics of the system and the measured data used. This is achieved through the use of cold Sparameter data, along with simple modifications to the extraction algorithm, and a new intelligent selection algorithm for the active bias points used in the multi-bias extraction. The selection algorithm employs a simple geometric abstraction for the S-parameter data that allows it to select bias points that maximize the information available to the extraction procedure. The new selection algorithm shows for the first time what the influence of the bias points is on the performance of a multibias extraction procedure. Experimental results proving the robustness and accuracy of the described procedures are presented.