Understanding the Effect of Long-Term Memory Model Parameters in Pole-Zero Identification for Stability Analysis of Power Amplifiers

TL;DR

This paper investigates how long-term memory parameters in transistor models affect pole-zero identification for power amplifier stability, proposing an algorithm to improve pole detection and reduce overfitting.

Contribution

It introduces a novel algorithm for automatic frequency domain identification of non-resonant responses and a procedure to accurately detect real low-frequency poles.

Findings

The proposed method improves detection of real poles at low frequencies.

Monte-Carlo analyses demonstrate enhanced stability assessment accuracy.

Long-term memory parameters significantly influence stability analysis outcomes.

Abstract

Understanding the nature of potential instabilities is indispensable for the stabilization of power amplifiers. Pole-zero identification is one of the techniques that can be used to determine the stability of a design in large-signal operation. In this work, the possible presence of poles at the fundamental frequency linked to the long-term memory parameters of the transistor's model (self-heating and traps) is presented and discussed. The paper shows how their effect on the identified frequency responses around the fundamental frequency may compromise the stability analysis results and the assessment of stability margins. The low observability of the poles at the fundamental frequency highlights the importance of an accurate identification of real poles in low-frequency bands. A specific algorithm for the automatic frequency domain identification of non-resonant frequency responses and a procedure for detecting and reducing overfitting of real poles is proposed in this article. The benefits of the proposed methodology to correctly detect and analyze real poles at low frequencies is demonstrated through Monte-Carlo sensitivity analyses of two different amplifier designs.