An Efficient Scheme for Nonlinear Modeling and Predistortion in Mixed-Signal Systems

Abstract

A novel identification and predistortion scheme of weakly nonlinear systems for mixed-signal devices, which takes into account practical implementation aspects, is presented. It is well known that for the identification of weakly nonlinear systems, despite the spectral regrowth, it suffices to sample the input-output (I/O) data of the system at the Nyquist rate of the input signal. Many applications such as linearization and mixed-signal simulations require system models at a higher sampling rate than Nyquist. Up to now, the construction of such high-rate models has been done by oversampling the corresponding I/O data. This leads to high computational complexity, ill posedness of the estimation, and high demand on the analog-to-digital-converter sampling rate for the implementation. This brief discusses an efficient way to obtain high-rate models and predistorters from low-rate models and shows the validity of the proposed scheme for a very-high-speed-digital-subscriber-line power amplifier, where an adjacent channel power supression of 20 dB is achieved