Generalized backpropagation algorithm for training a data predistorter with memory in radio systems

The authors present a neural network based data-predistorter with memory, for the compensation of high-power amplifier (HPA) nonlinearities in digital microwave radio systems. The overall system (predistorter, pulse shaping filter and HPA) can be seen as a unique FIR multilayer neural network, for which a specific complex-valued backpropagation algorithm can be developed to realise the data predistorter. The proposed scheme can also control the spectrum of the signal after the HP