Automatic Digital Modulation Recognition Using Features from the Continuous Wavelet Transform PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Automatic Digital Modulation Recognition Using Features from the Continuous Wavelet Transform PDF full book. Access full book title Automatic Digital Modulation Recognition Using Features from the Continuous Wavelet Transform by Grady Ward Manley. Download full books in PDF and EPUB format.
Author: Grady Ward Manley
Publisher:
ISBN:
Category :
Languages : en
Pages : 140
Get Book Here
Book Description
Author: Grady Ward Manley
Publisher:
ISBN:
Category :
Languages : en
Pages : 140
Get Book Here
Book Description
Author: Tejashri Kuber
Publisher:
ISBN:
Category : Modulators (Electronics)
Languages : en
Pages : 35
Get Book Here
Book Description
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.
Author: Ka Mun Ho
Publisher:
ISBN:
Category : Modulation (Electronics)
Languages : en
Pages : 201
Get Book Here
Book Description
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.
Author: Zhechen Zhu
Publisher: John Wiley & Sons
ISBN: 1118906497
Category : Technology & Engineering
Languages : en
Pages : 204
Get Book Here
Book Description
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
Author:
Publisher: ScholarlyEditions
ISBN: 146496372X
Category : Technology & Engineering
Languages : en
Pages : 3775
Get Book Here
Book Description
Issues in Electronic Circuits, Devices, and Materials: 2011 Edition is a ScholarlyEditions™ eBook that delivers timely, authoritative, and comprehensive information about Electronic Circuits, Devices, and Materials. The editors have built Issues in Electronic Circuits, Devices, and Materials: 2011 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Electronic Circuits, Devices, and Materials in this eBook to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Issues in Electronic Circuits, Devices, and Materials: 2011 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.
Author: Mihir Narayan Mohanty
Publisher: Springer Nature
ISBN: 9811908257
Category : Technology & Engineering
Languages : en
Pages : 570
Get Book Here
Book Description
The book presents high-quality research papers presented at 4th International Conference on Intelligent Computing and Advances in Communication (ICAC 2021) organized by Siksha ‘O’ Anusandhan, Deemed to be University, Bhubaneswar, Odisha, India, in November 2021. This book brings out the new advances and research results in the fields of theoretical, experimental, and applied signal and image processing, soft computing, networking, and antenna research. Moreover, it provides a comprehensive and systematic reference on the range of alternative conversion processes and technologies.
Author: Fuliang Yin
Publisher: Springer Science & Business Media
ISBN: 3540228411
Category : Computers
Languages : en
Pages : 1073
Get Book Here
Book Description
The two volume set LNCS 3173/3174 constitutes the refereed proceedings of the International Symposium on Neural Networks, ISNN 2004, held in Dalian, China in August 2004. The 329 papers presented were carefully reviewed and selected from more than 800 submissions. The papers span the entire scope of neural computing and its applications; they are organized in 11 major topical parts on theoretical analysis; learning and optimization; support vector machines; blind source separation, independent component analysis, and principal component analysis; clustering and classification; robotics and control; telecommunications; signal image, and time series analysis; biomedical applications; detection, diagnosis, and computer security; and other applications.
Author: Zhechen Zhu
Publisher: John Wiley & Sons
ISBN: 1118906527
Category : Technology & Engineering
Languages : en
Pages : 184
Get Book Here
Book Description
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
Author: Dennis John Simms
Publisher:
ISBN:
Category :
Languages : en
Pages : 48
Get Book Here
Book Description
Author: Sabri Arik
Publisher: Springer
ISBN: 3319265326
Category : Computers
Languages : en
Pages : 758
Get Book Here
Book Description
The four volume set LNCS 9489, LNCS 9490, LNCS 9491, and LNCS 9492 constitutes the proceedings of the 22nd International Conference on Neural Information Processing, ICONIP 2015, held in Istanbul, Turkey, in November 2015. The 231 full papers presented were carefully reviewed and selected from 375 submissions. The 4 volumes represent topical sections containing articles on Learning Algorithms and Classification Systems; Artificial Intelligence and Neural Networks: Theory, Design, and Applications; Image and Signal Processing; and Intelligent Social Networks.
