Open AccessStudy of the Discrete Wavelet Transform based Designed System under Different Simulation Conditions
Author(s) -
Simmi Garg,
Anuj Sharma,
Anurag Tyagi
Publication year - 2020
Publication title -
international journal of circuits, systems and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.156
H-Index - 13
ISSN - 1998-4464
DOI - 10.46300/9106.2020.14.126
Subject(s) - discrete wavelet transform , orthogonal wavelet , wavelet , second generation wavelet transform , biorthogonal system , algorithm , wavelet packet decomposition , electronic engineering , stationary wavelet transform , wavelet transform , computer science , fast wavelet transform , lifting scheme , biorthogonal wavelet , mathematics , artificial intelligence , engineering
Wavelet Transforms is an Important Part of, Systems Theory and Signal Processing and finds numerous important applications in Science and Engineering. In this paper, we investigated the performance of proposed scheme coded Discrete wavelet transform based Orthogonal frequency division multiplexing scheme over Additive white Gaussian noise channel using Pulse Amplitude Modulation in terms of Energy bits per noise ratio values. The simulation has been done using MATLAB software and results are compared with ½ rate convolution coded Discrete wavelet transform based Orthogonal frequency division multiplexing system. It is found by MATLAB simulations that the performance of proposed scheme coded Discrete wavelet transform based Orthogonal frequency division multiplexing outperforms than that of ½ rate convolution encoded Discrete wavelet transform based Orthogonal frequency division multiplexing with 16-Pulse Amplitude Modulation. Along with this, different orders of reverse biorthogonal and biorthogonal wavelets are implemented to simulate the proposed system with 16-Pulse Amplitude Modulation scheme. The performance of proposed system is compared and it is found that proposed system performs better than conventional system under all different simulation conditions. This study finds important applications in Signal Processing.