Cyclostationarity-based blind classification of analog and digital modulations

Authors:
Octavia A. Dobre;Ali Abdi;Yeheskel Bar-Ness;Wei Su
Affiliations:
Faculty of Eng. and Applied Science, Memorial University of Newfoundland, NL, Canada;CCSPR, Dept. of ECE, New Jersey Institute of Technology, Newark, NJ;CCSPR, Dept. of ECE, New Jersey Institute of Technology, Newark, NJ;RDECOM, Fort Monmouth, NJ
Venue:
MILCOM'06 Proceedings of the 2006 IEEE conference on Military communications
Year:
2006

Citing 5
Cited 2

Cyclic higher-order statistics: input/output relations for discrete- and continuous-time MIMO linear almost-periodically time-variant systems

Signal Processing
Identification algorithm of upper sideband and lower sideband SSB signals

Signal Processing
Automatic Modulation Recognition of Communication Signals

Automatic Modulation Recognition of Communication Signals
Classification of co-channel communication signals using cyclic cumulants

ASILOMAR '95 Proceedings of the 29th Asilomar Conference on Signals, Systems and Computers (2-Volume Set)
Higher-order cyclic cumulants for high order modulation classification

MILCOM'03 Proceedings of the 2003 IEEE conference on Military communications - Volume I

Automatic modulation classification for cognitive radios using cyclic feature detection

IEEE Circuits and Systems Magazine
Joint signal detection and classification based on first-order cyclostationarity for cognitive radios

EURASIP Journal on Advances in Signal Processing - Special issue on dynamic spectrum access for wireless networking

Quantified Score

Hi-index	0.00

Visualization

Abstract

The problem of blind analog and digital modulation classification is tackled in this paper. A cyclostationarity-based classifier is proposed, which does not require estimation of carrier phase and frequency offset, signal and noise powers, and timing recovery as preprocessing tasks. Numerical simulations are performed to validate theoretical developments.