Black-Box Modeling Approach with PGB Metric for PSRR Prediction in Op-Amps

The rapid advancement of electronic technology demands circuit designs that minimize power consumption while maximizing performance. The power supply rejection ratio (PSRR) is a critical metric for quantifying an amplifier’s ability to suppress supply noise, yet accurately predicting PSRR in high-frequency domains and complex multi-stage architectures is increasingly challenging. In this work, we introduce a new framework for PSRR prediction that overcomes these limitations. Leveraging a simplified circuit abstraction based on Thevenin’s theorem, we reduced multi-stage operational amplifiers to “black-box” models—collapsing intricate small-signal networks into a tractable form without sacrificing accuracy. Building on this foundation, we proposed the Power-Supply Rejection Gain-Bandwidth (PGB) metric, which concisely captures the trade-off between an amplifier’s DC PSRR and the frequency range over which that rejection is effective. Using PGB, designers gain an intuitive figure-of-merit for early-stage optimization of PSRR. We validated the efficacy of the combined black-box modeling and PGB approach through detailed case studies, including a 180 nm CMOS two-stage op-amp design. These findings confirmed that the proposed black box plus PGB framework can reliably guide the design of analog circuits with stringent PSRR requirements.