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This paper presents a large-signal hetrojunction bipolar transistor model for III-V technologies. A standard HBT compact model is demonstrated accurate in most regions of operation. At low collector supplies and high input drive levels, however, the compact model fails to accurately predict largesignal RF performance. Model inaccuracies are, through largesignal network analyzer measurements, attributed to minority carrier injection due to forward biased base-collector junction; a phenomenon which is not accounted for in the compact model. A hybrid model is proposed. This is a combination of the standard compact model and an artificial neural network based behavioral model. The artificial neural network is trained to empirically model minority carrier injection in the base-collector junction. Significant accuracy improvement is demonstrated and it is verified that greater accuracy comes at the expense of a very small degradation in execution speed.