An adaptive digital predistortion for compensating nonlinear distortions in RF power amplifier with memory effects

In this paper, an adaptive digital predistortion based on a memory polynomial model is proposed in order to linearize the power amplifier with memory effect. The coefficients of the power amplifier model have been extracted using a least square method and those of predistortion have been identified by applying an indirect learning structure. Finally, the performance of digital predistortion has been demonstrated using the simulation of the power amplifier and the digital predistortion excited by a modulated 16 QAM signal in Matlab software. According to the simulation results, the criterion of adjacent channel power ratio (ACPR) declined by around 15dB and the input/output power spectrum density of the power amplifier has quite similar curves. The linearized power amplifier output spectrum demonstrates the superiority of the proposed predistorter in eliminating the spectral regrowth which is caused by the memory effect in comparison to the other linearization methods. An effective adaptive digital predistortion is proposed in order to linearize a power amplifier with memory effect.Use of a memory polynomial model has been suggested in order to model the power amplifier and a digital predistortion.The trade-off between linearity and efficiency in the power amplifier has been broken by a proposed structure.The criterion of adjacent channel power ratio (ACPR) has been improved by around 15dB.

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