Digital predistortion is an effective technical method to improve the nonlinearization of power amplifier. Based on the fractional-order memory polynomial model and the traditional bilinear polynomial model
an improved fractional-order bilinear polynomial model predistortion method for indirect learning structure is proposed. The model uses the indirect learning structure and Recursive Least Square(RLS) adaptive identification algorithm to simulate the adaptive predistortion system. The experimental results show that
compared with the traditional bilinear polynomial model
the Normalized Mean Square Error(NMSE) is improved by 2.6 dB with 34.3% reduction of the number of model coefficients and the improvement of Adjacent Channel Power Ratio(ACPR) of 5 dB. Therefore
the model can effectively compensate the distortion of the power amplifier.
关键词
数字预失真记忆多项式间接学习结构功率放大器
Keywords
digital predistortionmemory polynomialindirect learning architecturepower amplifiers