A crosscorrelation predistorter using memory polynomials

Amplification of signals with fluctuating envelopes inevitably leads to distortion because of nonlinear behavior of the power amplifier (PA). Digital predistortion can counteract these nonlinear effects. In this paper, a digital predistortion architecture is presented which is based on the calculation of correlation functions using coarsely quantized signals. The crosscorrelation functions are transformed to the frequency domain and the spectra are used to calculate the coefficients of the predistorter memory polynomial. This method has reduced complexity and slightly improved average performance in comparison with existing schemes

Modeling Power Amplifiers using Memory Polynomials

In this paper we present measured in- and output data of a power amplifier (PA). We compare this data with an AM-AM and AM-PM model. We conclude that a more sophisticated PA model is needed to cope with severe memory effects. We suggest to use memory polynomials and introduce two approaches to deduce the polynomial coefficients from the measured data: the Least-Squares and Crosscorrelation approaches. We construct PA models according to both approaches, using the measured data. We compare the two PA models with the original AM-AM and AM-PM model

Interim research assessment 2003-2005 - Computer Science

This report primarily serves as a source of information for the 2007 Interim Research Assessment Committee for Computer Science at the three technical universities in the Netherlands. The report also provides information for others interested in our research activities