Reduction of inter-symbol interference using artifical neural network system in multicarrier OFDM system
Автор: Jyoti Makka, Himanshu Monga, Silki Baghla
Журнал: International Journal of Wireless and Microwave Technologies @ijwmt
Статья в выпуске: 5 Vol.8, 2018 года.
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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.
OFDM, Artificial Neural Network (ANN), FFT, QAM, BER, ISI, MMSE
Короткий адрес: https://sciup.org/15016942
IDR: 15016942 | DOI: 10.5815/ijwmt.2018.05.02
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