Reduced-order modeling of time-varying systems

We present algorithms for reducing large circuits, described at SPICE-level detail, to much smaller ones with similar input-output behavior. A key fea ture of our method, called time-varying Fade (TVP), is that it is capable o f reducing time-varying linear systems. This enables it to capture frequenc y-translation and sampling behavior, important in communication subsystems such as mixers and switched-capacitor filters. Krylov-subspace methods are employed in the model reduction process. The macromodels can be generated i n SPICE-like or AHDL format, and can be used in both time- and frequency-do main verification tools. We present applications to wireless subsystems, ob taining size reductions and evaluation speedups of orders of magnitude with insignificant loss of accuracy. Extensions of TVP to nonlinear terms and c yclostationary noise are also outlined.