A Novel Demodulation System Based on Continuous Wavelet Transform

Considering the problem of EBPSK signal demodulation, a new approach based on the wavelet scalogram using continuous wavelet transform is proposed. Our system is twofold: an adaptive wavelet construction method that replaces manual selection existing wavelets method and, on the other hand, a nonline...

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Main Authors: Lanting Fang, Lenan Wu, Yudong Zhang
Format: Article
Language:English
Published: Hindawi Limited 2015-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2015/513849
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spelling doaj-c8e8ca07b9954a2f8098b94c9f007e882020-11-24T21:28:19ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472015-01-01201510.1155/2015/513849513849A Novel Demodulation System Based on Continuous Wavelet TransformLanting Fang0Lenan Wu1Yudong Zhang2School of Information Science and Engineering, Southeast University, Nanjing 210096, ChinaSchool of Information Science and Engineering, Southeast University, Nanjing 210096, ChinaSchool of Computer Science and Technology, Nanjing Normal University, Nanjing 210023, ChinaConsidering the problem of EBPSK signal demodulation, a new approach based on the wavelet scalogram using continuous wavelet transform is proposed. Our system is twofold: an adaptive wavelet construction method that replaces manual selection existing wavelets method and, on the other hand, a nonlinear demodulation system based on image processing and pattern classification is proposed. To evaluate the performance of the adaptive wavelet and compare the performance of the proposed system with the existing systems, a series of comprehensive simulation experiments is conducted under the environment of uniform white noise, colored noise, and additive white Gaussian noise channel, respectively. Simulation results of different wavelets show that the system using adaptive wavelet has lower bit error rate (BER). Moreover, simulation results of several systems show that the BER of the proposed system is the lowest among all systems, such as amplitude detection, integral detection, and some continuous wavelet transform systems (specific scales and times and maximum lines). In a word, the adaptive wavelet construction proposed in this paper yields superior performances compared with the manual selection, and the proposed system has better performances than the existing systems. Index terms are signal demodulation, adaptive wavelet, continuous wavelet transform, and BER.http://dx.doi.org/10.1155/2015/513849
collection DOAJ
language English
format Article
sources DOAJ
author Lanting Fang
Lenan Wu
Yudong Zhang
spellingShingle Lanting Fang
Lenan Wu
Yudong Zhang
A Novel Demodulation System Based on Continuous Wavelet Transform
Mathematical Problems in Engineering
author_facet Lanting Fang
Lenan Wu
Yudong Zhang
author_sort Lanting Fang
title A Novel Demodulation System Based on Continuous Wavelet Transform
title_short A Novel Demodulation System Based on Continuous Wavelet Transform
title_full A Novel Demodulation System Based on Continuous Wavelet Transform
title_fullStr A Novel Demodulation System Based on Continuous Wavelet Transform
title_full_unstemmed A Novel Demodulation System Based on Continuous Wavelet Transform
title_sort novel demodulation system based on continuous wavelet transform
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2015-01-01
description Considering the problem of EBPSK signal demodulation, a new approach based on the wavelet scalogram using continuous wavelet transform is proposed. Our system is twofold: an adaptive wavelet construction method that replaces manual selection existing wavelets method and, on the other hand, a nonlinear demodulation system based on image processing and pattern classification is proposed. To evaluate the performance of the adaptive wavelet and compare the performance of the proposed system with the existing systems, a series of comprehensive simulation experiments is conducted under the environment of uniform white noise, colored noise, and additive white Gaussian noise channel, respectively. Simulation results of different wavelets show that the system using adaptive wavelet has lower bit error rate (BER). Moreover, simulation results of several systems show that the BER of the proposed system is the lowest among all systems, such as amplitude detection, integral detection, and some continuous wavelet transform systems (specific scales and times and maximum lines). In a word, the adaptive wavelet construction proposed in this paper yields superior performances compared with the manual selection, and the proposed system has better performances than the existing systems. Index terms are signal demodulation, adaptive wavelet, continuous wavelet transform, and BER.
url http://dx.doi.org/10.1155/2015/513849
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