An adaptive predistortion for power amplifier nonlinearity in the presence of measurement noise

抄録

In this paper, we propose a robust adaptive predistortion (PD) scheme based on a hybrid direct learning (HDL) structure for mitigating the effects of measurement noise derived from the feedback path of power amplifier (PA). In particular, by means of an additional gradient adaptive term, a modified normalized least mean square (MNLMS) algorithm was developed to identify the coefficients of PA forward model with relative long-term memory in the noisy feedback environments. The performance of this PD scheme is validated with numerical simulations.