In this paper, surrogate modeling techniques are applied for passive component modeling. These techniques are exploited to develop and compare two alternative strategies for automated radio-frequency (RF) circuit design. The first one is a traditional approach where passive components are designed during the optimization stage. The second one, inspired on bottom-up circuit design methodologies, builds passive component Pareto-optimal fronts (POFs) prior to any circuit optimization. Afterwards, these POFs are used as an optimized library from where the passive components are selected. This work exploits the advantages of evolutionary computation algorithms in order to efficiently explore the circuit design space, and the accuracy and efficiency of surrogate models to model passive components.

Peer reviewed