Extraction of passive device model parameters using genetic algorithms

The extraction of model parameters for embedded passive components is cruci al for designing and characterizing the performance of multichip module (MC M) substrates, In this paper, a method for optimizing the extraction of the se parameters using genetic algorithms is presented. The results of this me thod are compared with optimization using the Levenberg-Marquardt (LM) algo rithm used in the HSPICE circuit modeling tool A set of integrated resistor structures are fabricated, and their scattering parameters are measured fo r a range of frequencies from 45 MHz to 5 GHz Optimal equivalent circuit mo dels for these structures are derived from the s-parameter measurements usi ng each algorithm. Predicted s-parameters for the optimized equivalent circ uit are then obtained from HSPICE. The difference between the measured and predicted s-parameters in the frequency range of interest is used as a meas ure of the accuracy of the two optimization algorithms. It is determined th at the LM method is extremely dependent upon the initial starting point of the parameter search and is thus prone to become trapped in local minima Th is drawback is alleviated and the accuracy of the parameter values obtained is improved using genetic algorithms.