Zusammenfassung
Dieser Artikel behandelt die adaptive Vorverzerrung von nichtlinearen Systemen. Die Nichtlinearität wird als Hammerstein- bzw. Wiener-Modell dargestellt und die adaptive Vorverzerrung entsprechend mit einem Wiener- bzw. Hammerstein-System durchgeführt. Der "Nonlinear Filtered-x Prediction Error Method (NFxPEM)"-Algorithmus schätzt gleichzeitig die Parameter des linearen und des nichtlinearen Blocks des Vorverzerrungssystems. Der NFxPEM-Algorithmus wird unter der Bedingung, dass sich die Parameter des Vorverzerrungssystems während der Adaptation nur langsam ändern, hergeleitet. Simulationen zeigen, dass der vorgeschlagene NFxPEM-Algorithmus in der Lage ist, nichtlineare Verzerrungen zu kompensieren und die spektrale Fortpflanzung effektiv zu reduzieren. Zusätzlich wird gezeigt, dass der vorgeschlagene NFxPEM-Algorithmus wesentlich bessere Ergebnisse als der "Nonlinear Filtered-x Least Mean Squares (NFxLMS)"-Algorithmus erzielt.
Summary
Adaptive predistortion of nonlinear systems described using Hammerstein and Wiener models is considered in this paper. The adaptive predistorter is modeled as a Wiener or Hammerstein system, respectively. The parameters of the linear and nonlinear blocks of the predistorter are estimated simultaneously using the Nonlinear Filtered-x Prediction Error Method (NFxPEM) algorithm. The NFxPEM algorithm is derived under the assumption that the parameters of the Wiener and Hammerstein predistorters are changing slowly during adaptation. Simulation study shows that the suggested predistorter using the NFxPEM algorithm can well compensate nonlinear distortion and effectively reduce spectral regrowth. Moreover, the suggested NFxPEM algorithm achieves much better results as compared to the Nonlinear Filtered-x Least Mean Squares (NFxLMS) algorithm.
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Abd-Elrady, E., Gan, L. & Kubin, G. Predistortion of Hammerstein and Wiener systems using the Nonlinear Filtered-x Prediction Error Method algorithm. Elektrotech. Inftech. 127, 285–290 (2010). https://doi.org/10.1007/s00502-010-0776-4
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DOI: https://doi.org/10.1007/s00502-010-0776-4