The sensing of the radio frequency environment has important commercial and military applications and is fundamental to the concept of cognitive radio. The detection and classification of low signal-to-noise ratio signals with relaxed a priori information on their parameters are essential prerequisites to the demodulation of an intercepted signal. This paper proposes an algorithm based on first-order cyclostationarity for the joint detection and classification of frequency shift keying (FSK) and amplitude-modulated (AM) signals. A theoretical analysis of the algorithm performance is also presented and the results compared against a performance benchmark based on the use of limited assumed a priori information on signal parameters at the receive-side. The proposed algorithm has the advantage that it avoids the need for carrier and timing recovery and the estimation of signal and noise powers. © 2009 O. A. Dobre et al.
CITATION STYLE
Dobre, O. A., Rajan, S., & Inkol, R. (2009). Joint signal detection and classification based on first-order cyclostationarity for cognitive radios. Eurasip Journal on Advances in Signal Processing, 2009. https://doi.org/10.1155/2009/656719
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