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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
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10 Modulation Classifier Design for Military Applications
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End User License Agreement
Index
adaptive modulation and coding (AM&C)
additive noise
additive white Gaussian noise (AWGN) channel
analogue communication system
analogue modulation
AM
FM
PM
automatic modulation recognition
AWGN channel
back propagation
blind modulation classifier
broadband over power line (BPL)
centroid parameter
channel effect
channel estimation
expectation maximization
expectation maximization estimation
minimum centroid estimation
channel gain
channel state information (CSI)
classification accuracy
computational complexity
constellation
continuous wavelet transform (CWT)
covariance matrix
cumulant based feature
cumulative distribution function (CDF)
AWGN channel
cyclic cumulant based feature
cyclic moment based feature
cyclostationary process
cyclic autocorrelation
cyclic domain profile
spectral coherence
spectral correlation function
digital communication system
digital modulation
ASK
FSK
PAM
PSK
QAM
dimension reduction
feature selection
direct sequence spread sectrum (DSSS)
discrete signal
distribution based classifier
CvM test classifier
distribution test
Anderson–Darling test
Cramer–von Mises test
Kolmogorov–Smirnov test
distribution test based classifier
AD test classifier
KS test classifier
ODST classifier
phase difference classifier
electronic support
electronic attack
electronic warfare
electronic attack
electronic protect
electronic support
empirical cumulative distribution function (ECDF)
expectation maximization (EM)
expectation step
maximization step
update function
expectation/condition maximization (ECM)
fading channel
attenuation
fast fading
frequency offset
offset
phase offset
slow fading
feature based classifier
cumulant based classifier
cumulant based feature
moment based feature
feature combination
artificial neural network
genetic programming
feature selection
genetic algorithm
genetic programming
logistic regression
feature space
Fisher’s criterion
fitness
evaluation
function
frequency-hopping spread spectrum (FHSS)
Gaussian Mixture Model
Gaussian mixture model (GMM)
genetic algorithm
genetic operator
crossover
mutation
goodness of fit
high order modulation
I-Q
in-phase component
quadrature component
impulsive noise
jamming
K-means clustering
k-nearest neighbour (KNN)
likelihood based classifier
likelihood ratio test
maximum a posteriori
maximum likelihood
minimum distance likelihood
minimum likelihood distance
non-parametric likelihood
likelihood function (LF)
AWGN channel
fading channel
non-Gaussian channel
likelihood ratio test
average likelihood ratio test
generalized likelihood ratio test
hybrid likelihood ratio test
linear kernel
link adaptation (LA)
log likelihood function
logistic function
logit function
low probability of detection
DSSS
FHSS
machine learning
artificial neural network
genetic algorithm
KNN classifier
logistic regression
support vector machine
machine learning based classifier
KNN classifier
KNN classifier
SVM classifier
membership
hard membership
soft membership
modulation accuracy
modulation candidate pool
modulation classification
modulation hypothesis
modulation identification
modulation recognition
moment based feature
multi-layer perceptron (MLP)
multiple-input and multiple output (MIMO)
non-Gaussian channel
Gaussian mixture model
Middleton’s Class A
symmetric alpha stable
non-linear kernel
polynomial kernel
non-parametric likelihood function (NPLF)
pilot sample
prior probability
probability density function (PDF)
pulse shaping
Rayleigh distribution
Rayleigh fading channel
Rice distribution
semi-blind classifiers
signal distribution
AWGN channel
fading channel
non-Gaussian channel
signal-to-centroid distance
signal-to-noise ratio (SNR)
space-time coding (STC)
spatial multiplexing (SM)
spectral based feature
surveillance
symbol mapping
Symmetric Alpha Stable (SαS) model
threat analysis
timing error
von Mises distribution
wavelet transform feature
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