Advanced Techniques For Automatic Classification Of Digitally Modulated Communication Signals
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Advanced Techniques For Automatic Classification Of Digitally Modulated Communication Signals
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Author : Liang Hong
language : en
Publisher:
Release Date : 2002
Advanced Techniques For Automatic Classification Of Digitally Modulated Communication Signals written by Liang Hong and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Automatic classification categories.
Automatic classification of the modulation type of a received signal is an indispensable step in many communication systems. It provides necessary information for data demodulation, information extraction and signal exploitation. In recent years, modulation classification is one of the most promising research areas and has found a variety of military and commercial applications. In this research, a set of advanced techniques are proposed and investigated for automatic classification of digitally modulated signals. For inter-class classification at moderate to high signal-to-noise ratio (SNR) environment, we propose to use the wavelet transform to discriminate among quadrature amplitude modulation (QAM), phase shift keying (PSK) and frequency shift keying (FSK) signals. The wavelet transform can effectively extract the transient characteristics from different modulation types for simple identification. Then we focus on intra-class classification between binary PSK (BPSK) and quadrature PSK (QPSK) at moderate to low SNR environment. At low SNR environment, the performance of the classifier using wavelet transform degrades quickly, because the extracted features are masked by the noise and difficult to recognize. On the other hand, the decision theoretic technique that is based on likelihood function works well at all SNR environment. We developed the composite hypothesis tests to identify between BPSK and unbalanced QPSK signals, and to discriminate between BPSK and QPSK signals without prior knowledge of signal level. Furthermore, we applied the composite hypothesis testing approach to operate on antenna array outputs for the purpose of increasing the accuracy of BPSK and QPSK identification when only a short data record is available. The above decision theoretic based classifiers require some unknown parameters that must be estimated before the classification decision can be made. Hence, Cramer-Rao lower bound is derived to evaluate the performance of the proposed estimators in obtaining the unknown parameters.
Automatic Modulation Recognition Of Communication Signals
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Author : Elsayed Azzouz
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-04-17
Automatic Modulation Recognition Of Communication Signals written by Elsayed Azzouz and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-17 with Science categories.
Automatic modulation recognition is a rapidly evolving area of signal analysis. In recent years, interest from the academic and military research institutes has focused around the research and development of modulation recognition algorithms. Any communication intelligence (COMINT) system comprises three main blocks: receiver front-end, modulation recogniser and output stage. Considerable work has been done in the area of receiver front-ends. The work at the output stage is concerned with information extraction, recording and exploitation and begins with signal demodulation, that requires accurate knowledge about the signal modulation type. There are, however, two main reasons for knowing the current modulation type of a signal; to preserve the signal information content and to decide upon the suitable counter action, such as jamming. Automatic Modulation Recognition of Communications Signals describes in depth this modulation recognition process. Drawing on several years of research, the authors provide a critical review of automatic modulation recognition. This includes techniques for recognising digitally modulated signals. The book also gives comprehensive treatment of using artificial neural networks for recognising modulation types. Automatic Modulation Recognition of Communications Signals is the first comprehensive book on automatic modulation recognition. It is essential reading for researchers and practising engineers in the field. It is also a valuable text for an advanced course on the subject.
Automatic Modulation Classification
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Author : Zhechen Zhu
language : en
Publisher: John Wiley & Sons
Release Date : 2015-02-16
Automatic Modulation Classification written by Zhechen Zhu and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-02-16 with Technology & Engineering categories.
Automatic Modulation Classification (AMC) has been a key technology in many military, security, and civilian telecommunication applications for decades. In military and security applications, modulation often serves as another level of encryption; in modern civilian applications, multiple modulation types can be employed by a signal transmitter to control the data rate and link reliability. This book offers comprehensive documentation of AMC models, algorithms and implementations for successful modulation recognition. It provides an invaluable theoretical and numerical comparison of AMC algorithms, as well as guidance on state-of-the-art classification designs with specific military and civilian applications in mind. Key Features: Provides an important collection of AMC algorithms in five major categories, from likelihood-based classifiers and distribution-test-based classifiers to feature-based classifiers, machine learning assisted classifiers and blind modulation classifiers Lists detailed implementation for each algorithm based on a unified theoretical background and a comprehensive theoretical and numerical performance comparison Gives clear guidance for the design of specific automatic modulation classifiers for different practical applications in both civilian and military communication systems Includes a MATLAB toolbox on a companion website offering the implementation of a selection of methods discussed in the book
Automatic Classification Of Digitally Modulated Signals
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Author : Martin P. DeSimio (CIVILIAN.)
language : en
Publisher:
Release Date : 1987
Automatic Classification Of Digitally Modulated Signals written by Martin P. DeSimio (CIVILIAN.) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1987 with Adaptive signal processing categories.
Automatic Classification Of Digitally Modulated Signals
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Author : Martin P. DeSimio
language : en
Publisher:
Release Date : 1987
Automatic Classification Of Digitally Modulated Signals written by Martin P. DeSimio and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1987 with categories.
This experiment investigates the performance of an adaptive technique for the classification of the following types of digitally modulated signals: binary amplitude shift keying (BASK), binary phase shift keying (BPSK), quaternary phase shift keying (QPSK), and binary frequency shift keying (BFSK). The feature extraction process uses the mean and variance of the signal, and magnitudes and locations of the maxima in the spectrum of the signal, the spectrum of the signal squared, and the spectrum of the signal raised to the fourth power. The process of raising the signal to the second and fourth power and searching for narrowband energy near twice and four times the intermediate frequency is shown to provide useful information for the classification of BPSK and QPSK signals. A computer simulation is performed to measure the properties of the classifier. First, the classifier is trained with a set of feature vectors calculated from 20 dB SNR signals. The Least Mean Squares (IMS) algorithm is the adaptive procedure used to generate the weight vectors used to form the linear decision functions.
Automatic Modulation Recognition Of Communication Signals
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Author : Elsayed Azzouz
language : en
Publisher: Springer
Release Date : 2013-01-17
Automatic Modulation Recognition Of Communication Signals written by Elsayed Azzouz and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-17 with Science categories.
Automatic modulation recognition is a rapidly evolving area of signal analysis. In recent years, interest from the academic and military research institutes has focused around the research and development of modulation recognition algorithms. Any communication intelligence (COMINT) system comprises three main blocks: receiver front-end, modulation recogniser and output stage. Considerable work has been done in the area of receiver front-ends. The work at the output stage is concerned with information extraction, recording and exploitation and begins with signal demodulation, that requires accurate knowledge about the signal modulation type. There are, however, two main reasons for knowing the current modulation type of a signal; to preserve the signal information content and to decide upon the suitable counter action, such as jamming. Automatic Modulation Recognition of Communications Signals describes in depth this modulation recognition process. Drawing on several years of research, the authors provide a critical review of automatic modulation recognition. This includes techniques for recognising digitally modulated signals. The book also gives comprehensive treatment of using artificial neural networks for recognising modulation types. Automatic Modulation Recognition of Communications Signals is the first comprehensive book on automatic modulation recognition. It is essential reading for researchers and practising engineers in the field. It is also a valuable text for an advanced course on the subject.
Automatic Modulation Classification Of Digital Communication Signals
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Author : Qijun Xu
language : en
Publisher:
Release Date : 2001
Automatic Modulation Classification Of Digital Communication Signals written by Qijun Xu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with categories.
Automatic Recognition And Demodulation Of Digitally Modulated Communications Signals Using Wavelet Domain Signatures
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Author : Ka Mun Ho
language : en
Publisher:
Release Date : 2010
Automatic Recognition And Demodulation Of Digitally Modulated Communications Signals Using Wavelet Domain Signatures written by Ka Mun Ho and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Modulation (Electronics) categories.
Wavelet transform-based methodologies for both Automatic Modulation Recognition (AMR) and Demodulation of digitally modulated communications signals can be utilized in an enabling platform for the implementation of a new class of communications systems. In particular, such techniques could enable the development of agile radio transceivers for use in both commercial and military applications. Such radio transceivers would have the ability to transmit and receive signals using many different modulation schemes while employing a common receiver architecture based on a single demodulator. In this dissertation, the development of AMR and Demodulation techniques are based on the relatively new mathematical theory of Wavelet Transforms (WTs). Information-bearing signals acquired by communications receivers are transformed into the wavelet-domain using the Continuous Wavelet Transform (CWT) and then applied to signal processing algorithms that also use the CWT in conjunction with pattern recognition techniques. In particular, the method of template-matching is used for both the AMR and Demodulation processes. Signal templates characterizing various modulated signals are used for both processes. The signal templates are determined based on the signal features present in the fractal patterns of their corresponding scalograms for specific modulation schemes as they appear in the wavelet-domain. The algorithms developed in this work are capable of both classifying the method of modulation used in the acquired signal, as well as subsequently automatically demodulating the signal to recover the message. The classes of digitally modulated signals considered in this work include variants of the Amplitude-, Frequency-, Phase-Shift Keying modulation families, i.e., ASK, FSK, and PSK, respectively, and multiple-level Quadrature Amplitude Modulation (M-ary QAM) families. The AMR and Demodulation performances are evaluated in the presence of Additive White Gaussian Noise (AWGN) over a wide range of Signal-to-Noise Ratio (SNR) values. Through extensive Monte Carlo computer simulations it is determined that the average correct classification rates using wavelet-based AMR for PSK, ASK, and QAM are over 98%, and over 90% for FSK signals, all at an SNR of 0 dB. The Bit Error Rate (BER) performance obtained using wavelet-based Demodulation is at least one order of magnitude better than the matched filter-based BER performance realized for the modulation schemes considered.
The Automatic Classification Of The Modulation Type Of Communication Signals
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Author : Philip Charles Sapiano
language : en
Publisher:
Release Date : 1997
The Automatic Classification Of The Modulation Type Of Communication Signals written by Philip Charles Sapiano and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with categories.
Analysis Of Decision Theoretic Modulation Classification Methods For Digital Communication Signals
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Author :
language : en
Publisher:
Release Date : 2004
Analysis Of Decision Theoretic Modulation Classification Methods For Digital Communication Signals written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with categories.
Automated modulation classification is a fundamental requirement for electronic support measures. Existing automated classifiers use a variety of different modulation recognition techniques. This paper reviews the category of decision-theoretic approaches and discusses the relationships between decision-theoretic methods and other statistical modulation classification methods.