Home Page Icon
Home Page
Table of Contents for
Title page
Close
Title page
by Asoke K. Nandi, Zhechen Zhu
Automatic Modulation Classification: Principles, Algorithms and Applications
Cover
Title page
Copyright page
Dedication page
About the Authors
Preface
List of Abbreviations
List of Symbols
1 Introduction
1.1 Background
1.2 Applications of AMC
1.3 Field Overview and Book Scope
1.4 Modulation and Communication System Basics
1.5 Conclusion
References
2 Signal Models for Modulation Classification
2.1 Introduction
2.2 Signal Model in AWGN Channel
2.3 Signal Models in Fading Channel
2.4 Signal Models in Non-Gaussian Channel
2.5 Conclusion
References
3 Likelihood-based Classifiers
3.1 Introduction
3.2 Maximum Likelihood Classifiers
3.3 Likelihood Ratio Test for Unknown Channel Parameters
3.4 Complexity Reduction
3.5 Conclusion
References
4 Distribution Test-based Classifier
4.1 Introduction
4.2 Kolmogorov–Smirnov Test Classifier
4.3 Cramer–Von Mises Test Classifier
4.4 Anderson–Darling Test Classifier
4.5 Optimized Distribution Sampling Test Classifier
4.6 Conclusion
References
5 Modulation Classification Features
5.1 Introduction
5.2 Signal Spectral-based Features
5.3 Wavelet Transform-based Features
5.4 High-order Statistics-based Features
5.5 Cyclostationary Analysis-based Features
5.6 Conclusion
References
6 Machine Learning for Modulation Classification
6.1 Introduction
6.2 K-Nearest Neighbour Classifier
6.3 Support Vector Machine Classifier
6.4 Logistic Regression for Feature Combination
6.5 Artificial Neural Network for Feature Combination
6.6 Genetic Algorithm for Feature Selection
6.7 Genetic Programming for Feature Selection and Combination
6.8 Conclusion
References
7 Blind Modulation Classification
7.1 Introduction
7.2 Expectation Maximization with Likelihood-based Classifier
7.3 Minimum Distance Centroid Estimation and Non-parametric Likelihood Classifier
7.4 Conclusion
References
8 Comparison of Modulation Classifiers
8.1 Introduction
8.2 System Requirements and Applicable Modulations
8.3 Classification Accuracy with Additive Noise
8.4 Classification Accuracy with Limited Signal Length
8.5 Classification Robustness against Phase Offset
8.6 Classification Robustness against Frequency Offset
8.7 Computational Complexity
8.8 Conclusion
References
9 Modulation Classification for Civilian Applications
9.1 Introduction
9.2 Modulation Classification for High-order Modulations
9.3 Modulation Classification for Link-adaptation Systems
9.4 Modulation Classification for MIMO Systems
9.5 Conclusion
References
10 Modulation Classifier Design for Military Applications
10.1 Introduction
10.2 Modulation Classifier with Unknown Modulation Pool
10.3 Modulation Classifier against Low Probability of Detection
10.4 Conclusion
References
Index
End User License Agreement
Search in book...
Toggle Font Controls
Playlists
Add To
Create new playlist
Name your new playlist
Playlist description (optional)
Cancel
Create playlist
Sign In
Email address
Password
Forgot Password?
Create account
Login
or
Continue with Facebook
Continue with Google
Sign Up
Full Name
Email address
Confirm Email Address
Password
Login
Create account
or
Continue with Facebook
Continue with Google
Prev
Previous Chapter
Automatic Modulation Classification
Next
Next Chapter
Copyright page
Automatic Modulation Classification
Principles, Algorithms and Applications
Zhechen Zhu and Asoke K. Nandi
Brunel University London,
UK
Add Highlight
No Comment
..................Content has been hidden....................
You can't read the all page of ebook, please click
here
login for view all page.
Day Mode
Cloud Mode
Night Mode
Reset
