International Journal of Wireless and Microwave Technologies (IJWMT)
IJWMT Vol. 8, No. 5, 8 Sep. 2018
Cover page and Table of Contents: PDF (size: 893KB)
Reduction of Inter-Symbol Interference Using Artifical Neural Network System in Multicarrier OFDM System
Full Text (PDF, 893KB), PP.10-18
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Author(s)
Jyoti Makka
1,*
Himanshu Monga
1
Silki Baghla
1
Index Terms
OFDM, Artificial Neural Network (ANN), FFT, QAM, BER, ISI, MMSE
Abstract
The work proposes Inter-Symbol Interference (ISI) reduction scheme, ISI being a major problem in Optical systems, which produces various type of non-linear distortions. So the implementation of OFDM system using Artificial Neural Network (ANN) scheme with M-QAM modulation technique is proposed and compared with the conventional OFDM system without using ANN. This proposed scheme is implementation of Back-propagation (BP) algorithm over AWGN channels to achieve an effective ISI reduction in orthogonal frequency division multiplexing (OFDM) systems. Simulation results prove that ANN equalizer can further reduce ISI effectively and provide acceptable BER and better MSE plot compared to conventional OFDM system.
Cite This Paper
Jyoti Makka, Himanshu Monga, Silki Baghla, " Reduction of Inter-Symbol Interference Using Artifical Neural Network System in Multicarrier OFDM System ", International Journal of Wireless and Microwave Technologies(IJWMT), Vol.8, No.5, pp. 10-18, 2018. DOI: 10.5815/ijwmt.2018.05.02
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