Joint Classification and Parameter Estimation of Compressive Sampled FSK Signals

Luca De Vito, Octavia A. Dobre

Abstract

This paper deals with the classification and parameter estimation of frequency-shift-keying (FSK) signals that are acquired using a compressive sampling approach. Such a technique allows reducing the sampling frequency needs, as the FSK signals are compressible in the frequency domain; the spectrum of FSK signal is sparse, being concentrated to a finite number of harmonics which depend on the modulation order. The classification and parameter estimation rely on the first-order cyclostationarity. The proposed method has been implemented in GNU Octave, and validated in simulation.

Keywords

Modulation classification, parameter estimation, FSK, Compressive sampling, Tone spacing

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IMEKO-TC4-2014-999.pdf

DOI

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IMEKO TC

TC4 - Measurement of Electrical Quantities

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