Extraction of Pospieszalski's noise model parameters of microwave FETs based on ANNs

Abstract

A new neural approach for extraction of the Pospieszalski's noise model parameters of microwave FETs is presented in this paper. This approach is based on the use of two artificial neural networks. The first network is aimed at calculating the intrinsic noise parameters from the given equivalent circuit parameters, transistor total noise parameters, frequency and ambient temperature. Since the gate noise temperature in the Pospieszalski's noise model is approximately equal to the ambient temperature, only the value of drain noise temperature is to be determined. Therefore, the second network is trained to determine drain noise temperature from the given extracted intrinsic noise parameters, equivalent intrinsic circuit parameters, frequency and ambient temperature. The proposed extracting approach enables avoiding time-consuming optimization procedures in microwave simulators, which are conventionally used for the determination of the noise model parameters. A detailed validation of the proposed approach was done by comparison of the measured transistor noise parameters with those obtained by using the extracted drain noise temperature.