Filter Design Using Discrete Part-Value Optimization in Cadence AWR Design Environment

Optimization is often required to achieve desired performance when designing RF filters and other high- frequency circuits with today’s simulation software tools. As an example, optimizing a lumped-element filter involves adjusting the values of its lumped components until the filter achieves an optimal frequency response. But once the component values have been determined via optimization, they may still need to be adjusted to the closest discrete, or “real-life,” manufacturer part values. Depending on the design’s complexity, this extra step can create a bit of extra legwork for the designer.

This application note explains how a discrete part-value optimization method can be leveraged to design a lumped-element bandpass filter designed using the Cadence AWR Design Environment (AWRDE). The design includes Modelithics measurement-based passive-component models, which enable simulations to accurately predict the filter’s real performance. After completing an initial filter design, a discrete part-value optimization is carried out to achieve the desired frequency response. A yield analysis is also performed to determine the effect of component tolerances. At the conclusion, measured data is compared to the simulated results.