Adaptive Predistortion Using Threshold Decomposition-Based Piecewise Linear Modeling
A new adaptive predistortion approach for nonlinear power amplifiers based on the piecewise linear (PWL) approximation of nonlinear functions is presented. The PWL model is obtained using threshold decomposition (TD) of the input-output characteristics. The TD based PWL model is used to develop a baseband predistorter using both the direct and the indirect learning architectures. The proposed predistorter is proved to provide a better performance in suppressing nonlinear distortion than conventional polynomial predistorters and a reduced hardware complexity as compared to lookup table (LUT) approach. (C) 2011 Wiley Periodicals, Inc. Int J RF and Microwave CAE 21: 145-156, 2011.
adaptive predistortion threshold decomposition piecewise linear power amplifiers indirect learning architecture nonlinear distortion nonlinearity with memory memory polynomial direct learning architecture