International Journal of Engineering Research in Electronics and Communication Engineering(IJERECE)

Monthly Journal for Electronics and Communication Engineering

Volume3,May 2016,

Topic : Design and Implementation of SCF method for PAPR Reduction of OFDM Signals Using ANN

Authors:Monika Patil || S.N.Prasad

Abstract:Clipping and filtering methods is considered one of the simplest ways to cut down high peak to average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) signals. The existing simplified CF method clips the high PAPR in single iteration with reduced complexity. However, these low complexity methods depend upon large complicated fast Fourier transform procedures. In this paper we come up with an advanced method which adopts trained ANN to incorporate with the SCF algorithm. Compared to SCF method, the advanced proposal based on ANN and SCF method provides good performance with respect to bit error rate (BER) with incomparably shortened computing complications. In addition to this it also presents an attractive metric which is a more efficient predictor than peak to average power ratio..

Keywords: Artificial neural networks, SCF, BER, OFDM

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DOI: 01.1617/vol3iss5pid279


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Editor-in-Chief

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Dr.Zhongfu Tan
National Professor,
North China Electric Power University,
CHINA


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IMPACT FACTOR: 3.689

ISSN(Online): 2394-6849

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Thomson Reuters ID : q-6288-2016.
ORCiD Research ID : 0000-0001-9540-6799

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