Diagnosis of small-signal parameters for broadband amplifiers through S-parameter measurements and sensitivity-guided evolutionary search

With increasing uncertainties in the modeling and processing of semiconductor devices, it is essential that the sources of failures be identified once the devices are manufactured. We present a methodology to diagnose the problems in broadband amplifiers by determining the most important small signal parameters of the internal transistors. We use an evolutionary algorithm specifically designed to mimic the expected errors to ensure fast convergence to the correct solution. Sensitivity analysis is used to determine the set of the most impactful small signal parameters and to guide the evolutionary search. Experimental results indicate the proposed algorithm determines the parameters accurately and it scales well in terms of accuracy and computation time.