A compressive sampling-based method for classification and parameter estimation of FSK signals
The paper presents a new method for the classification and parameter estimation of frequency-shift-keying (FSK) signals, which exploits compressive sampling, and thus, allows to reduce the sampling rate beyond the limit of the Shannon theorem. The method identifies the modulation scheme among the se...
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| Veröffentlicht in: | Measurement : journal of the International Measurement Confederation 2017-02, Vol.98, p.439-444 |
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| container_title | Measurement : journal of the International Measurement Confederation |
| container_volume | 98 |
| creator | De Vito, Luca Dobre, Octavia A. |
| description | The paper presents a new method for the classification and parameter estimation of frequency-shift-keying (FSK) signals, which exploits compressive sampling, and thus, allows to reduce the sampling rate beyond the limit of the Shannon theorem.
The method identifies the modulation scheme among the set consisting of 2-FSK, 4-FSK, and 8-FSK, and determines the tone spacing of the modulation. The proposed method has been implemented in GNU/Octave and evaluated both by simulations and experiments on emulated FSK signals, in the presence of additive white Gaussian noise. |
| doi_str_mv | 10.1016/j.measurement.2015.12.038 |
| format | Article |
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| ispartof | Measurement : journal of the International Measurement Confederation, 2017-02, Vol.98, p.439-444 |
| issn | 0263-2241 1873-412X |
| language | eng |
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| source | Elsevier ScienceDirect Journals |
| subjects | Classification Compressive sampling Frequency-shift-keying Keying Modulation Modulation classification Normal distribution Parameter estimation Random noise Sampling Shannon theorem Simulation Statistical methods |
| title | A compressive sampling-based method for classification and parameter estimation of FSK signals |
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