Nonlinear compensation of high power amplifier distortion for communication using a histogram-based method

A probabilistic approach to compensate the nonlinear distortion caused by a high power amplifier (HPA) in a communication system is proposed here. This is a nonparametric method that involves estimating two probabilistic cumulative distribution functions without any explicit parameter estimation as in the conventional compensation techniques. It is shown analytically that the maximum compensation error of the proposed method is bounded and small. An adaptive implementation is developed. Experiments are setup to collect the HPA data. Real data analysis shows that the proposed predistorter has an improved performance compared to the conventional polynomial and neural network predistortion techniques.