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 HPA
Generalized backpropagation algorithm for training a data predistorter with memory in radio systems / Benvenuto, N.; Piazza, F.; Uncini, Aurelio; Visintin, M.. - In: ELECTRONICS LETTERS. - ISSN 0013-5194. - STAMPA. - 32 Nr. 20:(1996), pp. 1925-1926. [10.1049/el:19961279]
Generalized backpropagation algorithm for training a data predistorter with memory in radio systems
UNCINI, Aurelio;
1996
Abstract
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 HPAI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
