Transistor-level optimization methodology for the complete design of switched-capacitor filter circuits

This paper presents an automatic procedure for the design and optimization of switched-capacitor (SC) filters, including the automatic sizing of transistors in the amplifiers and switches. The optimization procedure is based on genetic algorithms (GAs) where the circuit's fitness is first computed using equations describing the filter's transfer function and then using transient simulations. These equations are obtained using a fast numerical methodology that takes into consideration the electrical behavior of all components in the circuit. The poles and zeros of the SC filter's transfer function are computed using a system of differential equations, obtained from the inspection of the circuit. This system describes the filter's behavior for all switch combinations, including the non-ideal effects of the transistors in the switches and amplifiers. Due to the low computational effort and accuracy of this methodology, it is possible to use a large population in the GA. After finding a solution through equations, the more computationally intensive SPICE transient simulations are used to fine-tune the solution, with a much smaller population in the GA. Taking advantage of the equations' low computational load and accuracy, process, voltage, temperature (PVT) corners and mismatch errors optimizations are also performed, allowing the chromosomes fitness to be calculated taking into consideration multiple cases, thus resulting in a low sensitivity design.