A Comparative Analysis of the Complexity/Accuracy Tradeoff in Power Amplifier Behavioral Models

TLDR

The study compares state‑of‑the‑art microwave PA behavioral models to assess how modeling accuracy varies with computational complexity. The authors defined accuracy and complexity metrics, surveyed various models, and evaluated them on measurement data from a general‑purpose and a WiMAX Doherty PA across output power levels, analyzing both in‑band and out‑of‑band error. Results show the generalized memory polynomial model delivers the best accuracy‑versus‑complexity trade‑off, achieving high performance at roughly half the computational cost of other models.

Abstract

A comparative study of state-of-the-art behavioral models for microwave power amplifiers (PAs) is presented in this paper. After establishing a proper definition for accuracy and complexity for PA behavioral models, a short description on various behavioral models is presented. The main focus of this paper is on the modeling accuracy as a function of computational complexity. Data is collected from measurements on two PAs-a general-purpose amplifier and a Doherty PA designed for WiMAX-for different output power levels. The models are characterized in terms of accuracy and complexity for both in-band and out-of-band error. The results show that, among the models studied, the generalized memory polynomial behavioral model has the best tradeoff for accuracy versus complexity for both PAs, and can obtain high performance at half of the computational cost of all other models analyzed.