Orthogonal neural network based predistortion for OFDM systems

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Resumen

This paper proposes a predistortion scheme based on an orthogonal hidden layer feedforward neural network for reducing nonlinear distortion introduced by a traveling wave tube amplifier (TWTA) over orthogonal frequency division multiplexing (OFDM) signals. In predistorter, the inputs weight are fixed and based on this the output weights are analytically determined. Computer simulation results confirm that once the 16QAM-OFDM signals are predistorted and amplified at an input back-off level of 0 dB there is a bit error rate performance very close to the ideal case of linear amplification.

Idioma originalInglés
Título de la publicación alojadaElectr., Rob. Autom. Mech. Conf., CERMA - Proc.
Páginas225-228
Número de páginas4
DOI
EstadoPublicada - 2007
EventoElectronics, Robotics and Automotive Mechanics Conference, CERMA 2007 - Cuernavaca, Morelos, México
Duración: 25 sep. 200728 sep. 2007

Serie de la publicación

NombreElectronics, Robotics and Automotive Mechanics Conference, CERMA 2007 - Proceedings

Conferencia

ConferenciaElectronics, Robotics and Automotive Mechanics Conference, CERMA 2007
País/TerritorioMéxico
CiudadCuernavaca, Morelos
Período25/09/0728/09/07

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