Automatic Modulation Recognition of Communication Signals

Automatic Modulation Recognition of Communication Signals
Author: Elsayed Azzouz
Publisher: Springer Science & Business Media
Total Pages: 233
Release: 2013-04-17
Genre: Science
ISBN: 1475724691

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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 Recognition of Communication Signals

Automatic Modulation Recognition of Communication Signals
Author: Elsayed Azzouz
Publisher: Springer
Total Pages: 218
Release: 2013-01-17
Genre: Science
ISBN: 9781475724707

Download Automatic Modulation Recognition of Communication Signals Book in PDF, Epub and Kindle

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 Recognition of Communication Signals

Automatic Modulation Recognition of Communication Signals
Author: Elsayed Azzouz
Publisher: Springer Science & Business Media
Total Pages: 242
Release: 1996-11-30
Genre: Science
ISBN: 9780792397960

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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

Automatic Modulation Classification
Author: Zhechen Zhu
Publisher: John Wiley & Sons
Total Pages: 204
Release: 2015-02-16
Genre: Technology & Engineering
ISBN: 1118906497

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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 Modulation Recognition Using the Discrete Wavelet Transform

Automatic Modulation Recognition Using the Discrete Wavelet Transform
Author: Tejashri Kuber
Publisher:
Total Pages: 35
Release: 2013
Genre: Modulators (Electronics)
ISBN:

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An Automatic Modulation Recognition (AMR) process using the Discrete Wavelet Transform (DWT) is presented in this work. The AMR algorithm involves the use of wavelet domain signal templates derived from digitally modulated signals that are used to transmit binary data. The signal templates, locally stored in a receiver, are cross-correlated with the incoming noisy, received signal after it has been transformed into the wavelet domain. The signal template that yields the largest cross-correlation value determines the type of digital modulation that had been employed at the transmitter. The specific binary-valued digital modulation schemes considered in this work include BASK, BFSK and BPSK. The discrete wavelet used for the creation of the signal templates is the Haar, or Daubechies 1, wavelet. Extensive computer simulations have been performed to evaluate the modulation recognition performance of the AMR algorithm as a function of channel SNR. It has been determined that the rate of correct classification for BASK signals is 68% for an SNR = 5 dB and 90% for an SNR = 10 dB SNR. The rate of correct classification for BFSK signals is 71% for an SNR = 5 dB and 92% for an SNR = 10 dB. Correct classification of BPSK signals is 71% for an SNR = 5 dB and 92% for an SNR = 10 dB. In comparison to alternative AMR methods reported in the literature, the AMR algorithm developed in this study produces reliable results even at relatively low values of SNR which are characteristic of realistic communications channels.

Communications, Signal Processing, and Systems

Communications, Signal Processing, and Systems
Author: Qilian Liang
Publisher: Springer Nature
Total Pages: 2070
Release: 2021-06-07
Genre: Technology & Engineering
ISBN: 9811584117

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This book brings together papers presented at the 2020 International Conference on Communications, Signal Processing, and Systems, which provides a venue to disseminate the latest developments and to discuss the interactions and links between these multidisciplinary fields. Spanning topics ranging from communications, signal processing and systems, this book is aimed at undergraduate and graduate students in Electrical Engineering, Computer Science and Mathematics, researchers and engineers from academia and industry as well as government employees (such as NSF, DOD and DOE).

Digital and Analog Communication Systems

Digital and Analog Communication Systems
Author: Leon W. Couch
Publisher:
Total Pages: 626
Release: 1983
Genre: Technology & Engineering
ISBN:

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For second and third year introductory communication systems courses for undergraduates, or an introductory graduate course. This revision of Couch's authoritative text provides the latest treatment of digital communication systems. The author balances coverage of both digital and analog communication systems, with an emphasis on design. Students will gain a working knowledge of both classical mathematical and personal computer methods to analyze, design, and simulate modern communication systems. MATLAB is integrated throughout.