Parameterized and DC-Compliant Small-Signal Macromodels of RF Circuit Blocks

Abstract

This paper presents a new approach for the generation of reduced-order compact macromodels of analog circuit blocks (CBs) in highly integrated radio frequency and analog/mixed-signal design. The circuits under investigation are designed and assumed to operate at certain bias points, where they should perform as linear as possible. Therefore, they can be well approximated to first order by linearized transfer function models, assuming small-signal excitation around these operating points. This paper concentrates on a number of key aspects. First, a fully parameterized macromodeling flow is described, for the closed-form inclusion of external geometrical or design parameters in the macromodel responses. This aspect is important for fast optimization, design centering, and what-if analyses. Second, a parameterized DC correction strategy is presented, to guarantee that the DC response of the linearized macromodel matches to machine precision the true DC responses of the original CB. This aspect is fundamental when the macromodel is used in a system-level simulation deck that combines linearized and fully nonlinear models of other components. The main result of proposed approach is a SPICE-compatible reduced-order macromodel that can replace complex transistor-level CBs plus passive interconnect networks, thus enabling dramatic speedup in transient system-level analyses and signal integrity verifications.