Staff View
Automatic modulation recognition using the discrete wavelet transform

Descriptive

TitleInfo
Title
Automatic modulation recognition using the discrete wavelet transform
Name (type = personal)
NamePart (type = family)
Kuber
NamePart (type = given)
Tejashri
NamePart (type = date)
1988-
DisplayForm
Tejashri Kuber
Role
RoleTerm (authority = RULIB)
author
Name (type = personal)
NamePart (type = family)
Daut
NamePart (type = given)
David G
DisplayForm
David G Daut
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
chair
Name (type = personal)
NamePart (type = family)
Gajic
NamePart (type = given)
Zoran
DisplayForm
Zoran Gajic
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
internal member
Name (type = personal)
NamePart (type = family)
Orfanidis
NamePart (type = given)
Sophocles
DisplayForm
Sophocles Orfanidis
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
internal member
Name (type = corporate)
NamePart
Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
Name (type = corporate)
NamePart
Graduate School - New Brunswick
Role
RoleTerm (authority = RULIB)
school
TypeOfResource
Text
Genre (authority = marcgt)
theses
OriginInfo
DateCreated (qualifier = exact)
2013
DateOther (qualifier = exact); (type = degree)
2013-05
Place
PlaceTerm (type = code)
xx
Language
LanguageTerm (authority = ISO639-2b); (type = code)
eng
Abstract (type = abstract)
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.
Subject (authority = RUETD)
Topic
Electrical and Computer Engineering
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_4710
PhysicalDescription
Form (authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
ix, 35 p. : ill.
Note (type = degree)
M.S.
Note (type = bibliography)
Includes bibliographical references
Note (type = statement of responsibility)
by Tejashri Kuber
Subject (authority = ETD-LCSH)
Topic
Modulators (Electronics)
Identifier (type = hdl)
http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000068901
RelatedItem (type = host)
TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier (type = local)
rucore19991600001
Location
PhysicalLocation (authority = marcorg); (displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier (type = doi)
doi:10.7282/T3WW7G7Q
Genre (authority = ExL-Esploro)
ETD graduate
Back to the top

Rights

RightsDeclaration (ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder (type = personal)
Name
FamilyName
Kuber
GivenName
Tejashri
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2013-04-15 13:52:16
AssociatedEntity
Name
Tejashri Kuber
Role
Copyright holder
Affiliation
Rutgers University. Graduate School - New Brunswick
AssociatedObject
Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
Back to the top

Technical

RULTechMD (ID = TECHNICAL1)
ContentModel
ETD
OperatingSystem (VERSION = 5.1)
windows xp
Back to the top
Version 8.4.8
Rutgers University Libraries - Copyright ©2022