Macro-modeling of non-linear pre-emphasis differential driver circuits

Differential signaling has become important in high speed digital and mixed signal systems because of its numerous advantages over single-ended signaling. Differential signaling reduces effects like simultaneous switching noise (SSN), electro magnetic interference (EMI) and crosstalk coupling. Signal integrity (SI) and timing analysis using differential drivers is computationally exhaustive due to increased complexity in design that includes features such as pre-compensation and slew rate control. Therefore, accurate macro-modeling of differential driver circuits for a quality design is a huge challenge. In this paper, a modeling technique based on recurrent neural network (RNN) is proposed to model differential driver circuits with and without pre-emphasis. Good accuracy is obtained in the test cases shown for the proposed modeling methodology at minimum computational cost.