Neural network based adaptable control method for linearization of high power amplifiers

The proposed adaptable control method for linearization of high power amplifiers is powered by the neural networks technique that supports analogue polynomial type of predistorters, which are widely utilized in commercial power amplifiers for wireless communication purposes. This paper presents an algorithm to determine the coefficients by use of artificial neural networks and its generalization feature that helps to map the power amplifier response with optimal coefficients of the polynomial, which in a proper way pre-distorts an input signal of the amplifier. The concept of the predistortion has been introduced. Furthermore, the overall step-by-step initialization and functionality of the control process has also been described. The method has been tested successfully in a real power amplifier equipped with an analogue predistorting circuits. Presented measurement results imply that this approach is robust and well suited for such category of the power amplifier design, in which the artificial neural networks play substantial role.