Automatic Modulation Classification: Principles, Algorithms and Applications

194 Pages·2015·1.84 MB·English

by  Zhechen Zhu

Automatic Modulation
Classification

Automatic Modulation
Classification
Principles, Algorithms
and Applications
Zhechen Zhu and Asoke K. Nandi
Brunel University London, UK
Thiseditionfirstpublished2015
©2015JohnWiley&Sons,Ltd
RegisteredOffice
JohnWiley&Sons,Ltd,TheAtrium,SouthernGate,Chichester,WestSussex,PO198SQ,UnitedKingdom
Fordetailsofourglobaleditorialoffices,forcustomerservicesandforinformationabouthowtoapplyfor
permissiontoreusethecopyrightmaterialinthisbookpleaseseeourwebsiteatwww.wiley.com.
Therightoftheauthortobeidentifiedastheauthorofthisworkhasbeenassertedinaccordancewiththe
Copyright,DesignsandPatentsAct1988.
Allrightsreserved.Nopartofthispublicationmaybereproduced,storedinaretrievalsystem,or
transmitted,inanyformorbyanymeans,electronic,mechanical,photocopying,recordingorotherwise,
exceptaspermittedbytheUKCopyright,DesignsandPatentsAct1988,withoutthepriorpermissionof
thepublisher.
Wileyalsopublishesitsbooksinavarietyofelectronicformats.Somecontentthatappearsinprintmaynot
beavailableinelectronicbooks.
Designationsusedbycompaniestodistinguishtheirproductsareoftenclaimedastrademarks.Allbrand
namesandproductnamesusedinthisbookaretradenames,servicemarks,trademarksorregistered
trademarksoftheirrespectiveowners.Thepublisherisnotassociatedwithanyproductorvendor
mentionedinthisbook.
LimitofLiability/DisclaimerofWarranty:Whilethepublisherandauthorhaveusedtheirbesteffortsin
preparingthisbook,theymakenorepresentationsorwarrantieswithrespecttotheaccuracyorcompleteness
ofthecontentsofthisbookandspecificallydisclaimanyimpliedwarrantiesofmerchantabilityorfitnessfora
particularpurpose.Itissoldontheunderstandingthatthepublisherisnotengagedinrenderingprofessional
servicesandneitherthepublishernortheauthorshallbeliablefordamagesarisingherefrom.Ifprofessional
adviceorotherexpertassistanceisrequired,theservicesofacompetentprofessionalshouldbesought
Theadviceandstrategiescontainedhereinmaynotbesuitableforeverysituation.Inviewofongoingresearch,
equipmentmodifications,changesingovernmentalregulations,andtheconstantflowofinformation
relatingtotheuseofexperimentalreagents,equipment,anddevices,thereaderisurgedtoreviewand
evaluatetheinformationprovidedinthepackageinsertorinstructionsforeachchemical,pieceofequipment,
reagent,ordevicefor,amongotherthings,anychangesintheinstructionsorindicationofusageandfor
addedwarningsandprecautions.ThefactthatanorganizationorWebsiteisreferredtointhisworkasa
citationand/orapotentialsourceoffurtherinformationdoesnotmeanthattheauthororthepublisher
endorsestheinformationtheorganizationorWebsitemayprovideorrecommendationsitmaymake.
Further,readersshouldbeawarethatInternetWebsiteslistedinthisworkmayhavechangedor
disappearedbetweenwhenthisworkwaswrittenandwhenitisread.Nowarrantymaybecreatedor
extendedbyanypromotionalstatementsforthiswork.Neitherthepublishernortheauthorshallbe
liableforanydamagesarisingherefrom.
LibraryofCongressCataloging-in-PublicationData
Zhu,Zhechen.
Automaticmodulationclassification:principles,algorithms,andapplications/ZhechenZhuand
AsokeK.Nandi.
pages cm
Includesbibliographicalreferencesandindex.
ISBN978-1-118-90649-1(cloth)
1. Modulation(Electronics) I. Nandi,AsokeKumar. II. Title.
TK5102.9.Z4772015
621.3815036–dc23
2014032270
AcataloguerecordforthisbookisavailablefromtheBritishLibrary.
Setin10/12.5ptPalatinobySPiPublisherServices,Pondicherry,India
1 2015
To
Xiaoyan and Qiaonan Zhu
Marion, Robin, David, and Anita Nandi

Contents
About the Authors xi
Preface xiii
List ofAbbreviations xv
List ofSymbols xix
1 Introduction 1
1.1 Background 1
1.2 Applications ofAMC 2
1.2.1 Military Applications 2
1.2.2 Civilian Applications 3
1.3 Field Overview and Book Scope 5
1.4 Modulation and Communication System Basics 6
1.4.1 Analogue Systemsand Modulations 6
1.4.2 Digital Systemsand Modulations 8
1.4.3 Received SignalwithChannelEffects 15
1.5 Conclusion 16
References 16
2 Signal Models forModulation Classification 19
2.1 Introduction 19
2.2 Signal Model inAWGNChannel 20
2.2.1 Signal Distribution of I-Q Segments 21
2.2.2 Signal Distribution of Signal Phase 23
2.2.3 Signal Distribution of Signal Magnitude 25
2.3 Signal Models in Fading Channel 25
2.4 Signal Models in Non-Gaussian Channel 28
2.4.1 Middleton’s Class A Model 28
viii Contents
2.4.2 Symmetric Alpha Stable Model 30
2.4.3 Gaussian Mixture Model 30
2.5 Conclusion 31
References 32
3 Likelihood-based Classifiers 35
3.1 Introduction 35
3.2 Maximum Likelihood Classifiers 36
3.2.1 Likelihood Function inAWGNChannels 36
3.2.2 Likelihood Function in Fading Channels 38
3.2.3 Likelihood Function in Non-Gaussian
Noise Channels 39
3.2.4 Maximum Likelihood Classification
Decision Making 39
3.3 Likelihood Ratio Test forUnknown
Channel Parameters 40
3.3.1 Average Likelihood Ratio Test 40
3.3.2 GeneralizedLikelihood Ratio Test 41
3.3.3 Hybrid Likelihood Ratio Test 43
3.4 Complexity Reduction 44
3.4.1 Discrete Likelihood Ratio Test and Lookup Table 44
3.4.2 Minimum Distance Likelihood Function 45
3.4.3 Non-Parametric Likelihood Function 45
3.5 Conclusion 45
References 46
4 Distribution Test-based Classifier 49
4.1 Introduction 49
4.2 Kolmogorov–Smirnov Test Classifier 50
4.2.1 The KSTest for Goodness of Fit 51
4.2.2 One-sampleKS Test Classifier 53
4.2.3 Two-sampleKS Test Classifier 55
4.2.4 Phase Difference Classifier 56
4.3 Cramer–Von MisesTest Classifier 57
4.4 Anderson–Darling Test Classifier 57
4.5 Optimized Distribution Sampling Test Classifier 58
4.5.1 Sampling Location Optimization 59
4.5.2 Distribution Sampling 60
4.5.3 ClassificationDecision Metrics 61
4.5.4 Modulation ClassificationDecision Making 62
4.6 Conclusion 63
References 63