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.

Additional Metadata
Persistent URL dx.doi.org/10.1155/2009/656719
Journal Eurasip Journal on Advances in Signal Processing
Citation
Dobre, O.A. (O. A.), Rajan, S, & Inkol, R. (R.). (2009). Joint signal detection and classification based on first-order cyclostationarity for cognitive radios. Eurasip Journal on Advances in Signal Processing, 2009. doi:10.1155/2009/656719