Abstract-This paper presents a hardware implementation of a digital predistorter (DPD) for linearizing RF power amplifiers (PAs) for wideband applications. The proposed predistortion linearizer is based on a nonlinear auto-regressive moving average (NARMA) structure, which can be derived from the NARMA PA behavioral model and then mapped into a set of scalable lookup tables (LUTs). The linearizer takes advantage of its recursive nature to relax the LUT count needed to compensate memory effects in PAs. Experimental support is provided by the implementation of the proposed NARMA DPD in a field-programmable gate-array device to linearize a 170-W peak power PA, validating the recursive DPD NARMA structure for W-CDMA signals and flexible transmission bandwidth scenarios. To the best of the authors' knowledge, it is the first time that a recursive structure is experimentally validated for DPD purposes. In addition to the results on PA efficiency and linearity, this paper addresses many practical implementation issues related to the use of FPGA in DPD applications, giving an original insight on actual prototyping scenarios. Finally, this study discusses the possibility of further enhancing the overall efficiency by degrading the PA operation mode, provided that DPD may be unavoidable due to the impact of memory effects.Index Terms-Digital predistortion (DPD), field programmable gate array (FPGA), nonlinear auto-regressive moving average (NARMA) models, power amplifier (PA) linearization.
Abstract-This letter presents a new digital adaptive predistorter (PD) for power amplifier (PA) linearization based on a nonlinear auto-regressive moving average (NARMA) structure. The distinctive characteristic of this PD is its straightforward deduction from the NARMA PA model, without the need of using an indirect learning approach to identify the PD function. The PD itself presents a NARMA structure, and hence it can be quickly implemented by means of lookup tables. Single and multicarrier modulated signals collected from a three-stage LDMOS class AB PA, with a maximum output power of 48-dBm CW have been used to validate the linearity performance of this new predictive predistorter.Index Terms-Amplifier distoriton, digital predistorter (PD), digital radio, direct learning approach, linearization, microwave power amplifiers (PAs), nonlinear auto-regressive moving average (NARMA), radio transmitters.
-A nonlinear auto-regressive moving average (ARMA) structure capable of compensating nonlinear memory effects in RF power amplifiers is here presented. Results on the linearity improvement, in both in-band and out-of-band distortion compensation, achieved by this baseband digital predistorter are provided. Moreover, a study on this nonlinear ARMA system stability is also reported.
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