Reduction of Inter-Symbol Interference using Artificial Neural Network System in Multicarrier OFDM System

Authors(3) :-Jyoti Makkar, Dr. Himanshu Monga, Silki Baglha

The work proposes Inter-Symbol Interference (ISI) reduction scheme, ISI is a major problem in Optical systems, which produces various types 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 an 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 the conventional OFDM system.

Authors and Affiliations

Jyoti Makkar
M.Tech Scholar, ECE Department, J.C.D.M College of Engineering, Sirsa, Haryana, India
Dr. Himanshu Monga
Professor, ECE Department, J.C.D.M College of Engineering, Sirsa Haryana, India
Silki Baglha
Assistant Professor, ECE Department, J.C.D.M College of Engineering, Sirsa Haryana, India

OFDM, Artificial Neural Network (ANN), FFT, QAM, BER, ISI, MMSE

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Publication Details

Published in : Volume 2 | Issue 5 | September-October 2017
Date of Publication : 2017-10-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 553-558
Manuscript Number : CSEIT172595
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Jyoti Makkar, Dr. Himanshu Monga, Silki Baglha, "Reduction of Inter-Symbol Interference using Artificial Neural Network System in Multicarrier OFDM System", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 5, pp.553-558, September-October-2017.
Journal URL : http://ijsrcseit.com/CSEIT172595

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