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Talks and Poster Presentations (without Proceedings-Entry):

R. Dallinger, M. Rupp:
"Adaptive Digital Pre-distortion based on Two-block Models";
Talk: IEEE Forum on Signal Processing for Radio Frequency Systems, Vienna (invited); 03-28-2011.



English abstract:
We summarise our recent research results about low complexity adaptive digital pre-distortion schemes for power amplifiers (PAs). The pre-distorter contains a memoryless nonlinearity followed by a finite impulse response filter (i.e., a Hammerstein model). The model used for the identification of the PA consists of the same blocks but with reversed order (i.e., a Wiener model). For both models, the nonlinearity is parametrised using orthogonal polynomials. The identification of the pre-distorter and the PA model is done by gradient type algorithms. In a first step, we compare the performance of different orthogonal polynomial bases with respect to the identification of a memoryless nonlinearity. Based on simulations and measurements, we evaluate the behaviour of Hammerstein pre-distorters adapted by either the indirect learning or the nonlinear filtered-x least mean squares algorithm. Finally, a robustness analysis based on the singular value decomposition allows to conjecture the robustness of Wiener models adapted by gradient type algorithms.

Created from the Publication Database of the Vienna University of Technology.