Accelerating Model Adaptation of Multi-Metric Digital Predistortion for RF Power Amplifiers Using Composited Quadratic Loss Function

Abstract

The conventional model extraction of digital predistortion (DPD) for RF power amplifiers is usually based on minimizing errors in the time domain, such as the normalized mean square error. In the forthcoming systems, not only time-variant, but also multi-metric requirements in both the time and frequency domains will be posed, such as error vector magnitude and spectrum mask. Correspondingly, the DPD coefficients must be fast adapted, so as to satisfy the multiple requirements in a timely manner. In this paper, a composited quadratic loss function is proposed, so that the DPD coefficients can converge to the desired values to meet the multi-metric requirements with fewer iterations, when using the quadratic simultaneous perturbation stochastic approximation (SPSA) algorithm. The validation on a sequential load modulated balanced amplifier indicates that the proposed method is promising to be employed in the emerging scenarios.