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Modulation Classification of Satellite Communication Signals Using Cumulants and Neural NetworksNational Aeronautics and Space Administration (NASA)'s future communication architecture is evaluating cognitive technologies and increased system intelligence. These technologies are expected to reduce the operational complexity of the network, increase science data return, and reduce interference to self and others. In order to increase situational awareness, signal classification algorithms could be applied to identify users and distinguish sources of interference. A significant amount of previous work has been done in the area of automatic signal classification for military and commercial applications. As a preliminary step, we seek to develop a system with the ability to discern signals typically encountered in satellite communication. Proposed is an automatic modulation classifier which utilizes higher order statistics (cumulants) and an estimate of the signal-to-noise ratio. These features are extracted from baseband symbols and then processed by a neural network for classification. The modulation types considered are phase-shift keying (PSK), amplitude and phase-shift keying (APSK),and quadrature amplitude modulation (QAM). Physical layer properties specific to the Digital Video Broadcasting - Satellite- Second Generation (DVB-S2) standard, such as pilots and variable ring ratios, are also considered. This paper will provide simulation results of a candidate modulation classifier, and performance will be evaluated over a range of signal-to-noise ratios, frequency offsets, and nonlinear amplifier distortions.
Document ID
20170008742
Acquisition Source
Glenn Research Center
Document Type
Presentation
Authors
Smith, Aaron
(NASA Glenn Research Center Cleveland, OH United States)
Evans, Michael
(NASA Glenn Research Center Cleveland, OH United States)
Downey, Joseph
(NASA Glenn Research Center Cleveland, OH United States)
Date Acquired
September 11, 2017
Publication Date
June 27, 2017
Subject Category
Communications And Radar
Report/Patent Number
GRC-E-DAA-TN43813
Meeting Information
Meeting: Cognitive Communications for Aerospace Applications Workshop
Location: Cleveland, OH
Country: United States
Start Date: June 27, 2017
End Date: June 28, 2017
Sponsors: American Inst. of Aeronautics and Astronautics, NASA Glenn Research Center, Institute of Electrical and Electronics Engineers
Funding Number(s)
WBS: WBS 553323.04.10.09.01.01
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
Keywords
Signal Classification
Satellite Communication
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