The Threshold Optimization of the Canonical Piecewise Linear Function-Based Model With a Modified Quadratic SPSA

Abstract

The canonical piecewise linear (CPWL) function-based model has been proposed for behavioral modeling of power amplifiers (PAs) because it can provide good modeling accuracy and low complexity. In the CPWL, thresholds are preselected as different constants, which are usually based on experience. The letter focuses on the threshold optimization of the CPWL, and a modified quadratic simultaneous perturbation stochastic approximation (SPSA) algorithm is employed to estimate the coefficients and optimize thresholds of the CPWL-based model. This method is more suitable for hardware implementation than the conventional least square (LS) by coefficient iterations rather than matrix inversion operations. Experimental results show that, compared with the LS, the proposed approach achieves comparable modeling and digital predistortion (DPD) performance of the CPWL-based model with fewer thresholds and coefficients after threshold optimization when a wideband PA is excited by a Long-Term Evolution (LTE)-Advanced signal of 100-MHz bandwidth.