Signal classification in fading channels using cyclic spectral analysis

Authors:
Eric Like;Vasu D. Chakravarthy;Paul Ratazzi;Zhiqiang Wu
Affiliations:
Air Force Institute of Technology, Department of Electrical Engineering, Wright-Patterson Air Force Base, OH;Air Force Research Laboratory, Wright-Patterson Air Force Base, OH;Air Force Research Laboratory, Griffiss Air Force Base, NY;Department of Electrical Engineering, Wright State University, Dayton, OH
Venue:
EURASIP Journal on Wireless Communications and Networking
Year:
2009

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Abstract

Cognitive Radio (CR), a hierarchical Dynamic Spectrum Access (DSA) model, has been considered as a strong candidate for future communication systems improving spectrum efficiency utilizing unused spectrum of opportunity. However, to ensure the effectiveness of dynamic spectrum access, accurate signal classification in fading channels at low signal to noise ratio is essential. In this paper, a hierarchical cyclostationary-based classifier is proposed to reliably identify the signal type of a wide range of unknown signals. The proposed system assumes no a priori knowledge of critical signal statistics such as carrier frequency, carrier phase, or symbol rate. The system is designed with a multistage approach to minimize the number of samples required to make a classification decision while simultaneously ensuring the greatest reliability in the current and previous stages. The system performance is demonstrated in a variety of multipath fading channels, where several multiantenna-based combining schemes are implemented to exploit spatial diversity.