Neural network classification of SDR signal modulation
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F16%3A86098899" target="_blank" >RIV/61989100:27240/16:86098899 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27740/16:86098899
Result on the web
<a href="http://link.springer.com/content/pdf/10.1007/978-3-319-45378-1_15.pdf" target="_blank" >http://link.springer.com/content/pdf/10.1007/978-3-319-45378-1_15.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-45378-1_15" target="_blank" >10.1007/978-3-319-45378-1_15</a>
Alternative languages
Result language
angličtina
Original language name
Neural network classification of SDR signal modulation
Original language description
With the rising popularity of Software Defined Radios (SDR), there is a strong demand for automatic detection of the modulation type and signal parameters. Automatic modulation classification is an approach to identify the modulation type and its parameters such as the carrier frequency or symbol rate. In electronic warfare, it enables real-time signal interception and processing. In civil applications, it can be used, e.g., by the amateur radio operators to automatically set the transceiver to the appropriate modulation and communication protocol. This paper presents a modulation classification driven by a neural network. A set of signal features are provided as an input of the neural network. The paper discusses the relevance of different signal features and its impact on the success rate of the neural network classification. The proposed approach is tested on both artificial and real samples captured by the SDR.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/LQ1602" target="_blank" >LQ1602: IT4Innovations excellence in science</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Computer information systems and industrial management : 15th IFIP TC8 International Conference, CISIM 2016 : Vilnius, Lithuania, September 14-16, 2016 : proceedings
ISBN
978-3-319-45377-4
ISSN
0302-9743
e-ISSN
—
Number of pages
12
Pages from-to
160-171
Publisher name
Springer
Place of publication
Cham
Event location
Vilnius
Event date
Sep 14, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000388720000015