Classification of digital modulated signals based on time frequency representation
dc.contributor.author | Haq, K. | |
dc.contributor.author | Mansour, A. | |
dc.contributor.author | Nordholm, Sven | |
dc.date.accessioned | 2017-01-30T15:36:47Z | |
dc.date.available | 2017-01-30T15:36:47Z | |
dc.date.created | 2016-09-12T08:36:39Z | |
dc.date.issued | 2010 | |
dc.identifier.citation | Haq, K. and Mansour, A. and Nordholm, S. 2010. Classification of digital modulated signals based on time frequency representation. | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/47974 | |
dc.identifier.doi | 10.1109/ICSPCS.2010.5709731 | |
dc.description.abstract |
This paper proposes a new method for classifying Digital Modulations, including the typical PSK (Phase Shift Keying), FSK (Frequency Shift Keying), ASK (Amplitude Shift Keying) as well as the present OFDM (Orthogonal Frequency Division Multiplex) modulation. The method is based on the analysis of the time frequency representation of the digitally modulated signals. At first, some experiments have been done to monitor the time frequency representation for different types of modulations. Then a statistical method has been applied and finally a peak detection technique has been employed to classify the modulation types. The method is capable to classify PSK, ASK, FSK 2, FSK 4, FSK 8, FSK16 and OFDM signals. Finally many simulations have been conducted and it is shown that, our method is capable to classify the right modulation against an SNR (Signal to Noise Ratio) of less than 5 dB. The classification rate is 100% for PSK and ASK signals, and 96.5% for OFDM signals. No explicit prior information is required for this method. ©2010 IEEE. | |
dc.title | Classification of digital modulated signals based on time frequency representation | |
dc.type | Conference Paper | |
dcterms.source.title | 4th International Conference on Signal Processing and Communication Systems, ICSPCS'2010 - Proceedings | |
dcterms.source.series | 4th International Conference on Signal Processing and Communication Systems, ICSPCS'2010 - Proceedings | |
dcterms.source.isbn | 9781424479078 | |
curtin.department | Department of Electrical and Computer Engineering | |
curtin.accessStatus | Fulltext not available |
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