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Automatic Modulation Classifier - A Blind Feature-Based Tool

Cutno, Patrick
http://orcid.org/0000-0002-8149-465X
http://rave.ohiolink.edu/etdc/view?acc_num=miami1480079193743277

Abstract Details

2016, Master of Science, Miami University, Computational Science and Engineering.
Automatic modulation classifiers (AMC) are one of the basic building blocks of electronic warfare receivers and cognitive radios. Although many research papers on AMC algorithms have been published, very few results on their implementation are available. This thesis presents a feature-based AMC built upon a software-defined radio platform. The developed AMC can detect signals over a broad spectrum and classify the modulation used. The modulation schemes considered in this thesis are amplitude modulation (AM), frequency modulation (FM), phase-shift keying (PSK), and quadrature amplitude modulation (QAM). Experimental results demonstrate the validity of the developed AMC algorithm and its implementation.
Chi-Hao Cheng, Ph.D (Advisor)
Dmitriy Garmatyuk, Ph.D (Committee Member)
Jason Pennington, Ph.D (Committee Member)
40 p.
Communication; Computer Engineering; Computer Science; Electrical Engineering; Engineering; Experiments; Technology
Software Defined Radio; NI USRP-2920; USRP; Modulation; Automatic Modulation Detection; Automatic Modulation Classification; AMC; High Order Statistics; LabVIEW; Implementation; Electronic Warfare; Cognitive Radio; AM; FM; PSK; QAM; Energy Analyzer; SNR

Recommended Citations

Citations

  • Cutno, P. (2016). Automatic Modulation Classifier - A Blind Feature-Based Tool [Master's thesis, Miami University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=miami1480079193743277

    APA Style (7th edition)

  • Cutno, Patrick. Automatic Modulation Classifier - A Blind Feature-Based Tool . 2016. Miami University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=miami1480079193743277.

    MLA Style (8th edition)

  • Cutno, Patrick. "Automatic Modulation Classifier - A Blind Feature-Based Tool ." Master's thesis, Miami University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=miami1480079193743277

    Chicago Manual of Style (17th edition)

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This open access ETD is published by Miami University and OhioLINK.