Orthogonal neural network based predistortion for OFDM systems

NIBALDO RODRIGUEZ AGURTO, Claudio Cubillos

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

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.

Original languageEnglish
Title of host publicationElectr., Rob. Autom. Mech. Conf., CERMA - Proc.
Pages225-228
Number of pages4
DOIs
StatePublished - 1 Dec 2007
EventElectronics, Robotics and Automotive Mechanics Conference, CERMA 2007 - Cuernavaca, Morelos, Mexico
Duration: 25 Sep 200728 Sep 2007

Publication series

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

Conference

ConferenceElectronics, Robotics and Automotive Mechanics Conference, CERMA 2007
CountryMexico
CityCuernavaca, Morelos
Period25/09/0728/09/07

Fingerprint Dive into the research topics of 'Orthogonal neural network based predistortion for OFDM systems'. Together they form a unique fingerprint.

Cite this