Reducing nonlinear OFDM signal distortions using neural networks in the time domain

Author

Louet, Yves ; Tertois, Sylvain ; Barreau, Pascal

Author_Institution

ETSN Dept., SUPELEC, France

fYear

2004

fDate

19-23 April 2004

Firstpage

267

Lastpage

268

Abstract

The temporal OFDM signal has a high PAPR (Peak to Average Power Ratio), often referenced as "the peak factor problem". This means that the signal has some peaks with a power much higher than the average power and as such is sensitive to the nonlinear characteristics of the HPA (high power amplifier). Neural networks are used to compensate the HPA nonlinear distortion effects in OFDM. This paper put the stress on the robustness of the presented neural networks in the time domain with multipaths channels simulations and with a variable number of carriers. The SSPA (solid state power amplifier) amplifier model and the additive Gaussian channel is used.

Keywords

AWGN channels; multipath channels; neural nets; nonlinear distortion; power amplifiers; time-domain analysis; HPA; SSPA; additive Gaussian channel; high power amplifier; multipath channels; neural networks; nonlinear signal distortion reduction; solid state power amplifier; temporal OFDM signal; time domain; High power amplifiers; Multipath channels; Neural networks; Nonlinear distortion; OFDM; Peak to average power ratio; Power amplifiers; Robustness; Solid state circuits; Stress;

fLanguage

English

Publisher

ieee

Conference_Titel

Information and Communication Technologies: From Theory to Applications, 2004. Proceedings. 2004 International Conference on

Print_ISBN

0-7803-8482-2

Type

conf

DOI

10.1109/ICTTA.2004.1307729

Filename

1307729