Classification of linear and non-linear modulations using the BaumWelch algorithm and MCMC methods

Signal Processing

Volumn 90, Issue 12, 2010, Pages 3242-3255

  Puengnim, Anchalee ^a   Thomas, Nathalie ^a   Tourneret, Jean Yves ^a   Vidal, Josep ^b  

^a IRIT   (France)

^b UNIVERSITAT POLITÈCNICA DE CATALUNYA   (Spain)

Author keywords

BaumWelch algorithm; Bayesian classifiers; Digital modulation classification; Linear and non linear modulations; Markov chain Monte Carlo methods

Indexed keywords

BAUM-WELCH ALGORITHMS; BAYESIAN CLASSIFIER; DIGITAL MODULATION CLASSIFICATION; MARKOV CHAIN MONTE CARLO METHOD; NON-LINEAR;

ALGORITHMS; AMPLITUDE MODULATION; BAYESIAN NETWORKS; BROADCASTING; CLASSIFIERS; MARKOV PROCESSES; PHASE SHIFT KEYING; SATELLITE LINKS; SATELLITES; SIGNAL ANALYSIS; SPECTRUM ANALYZERS; SUPPORT VECTOR MACHINES;

MONTE CARLO METHODS;

EID: 77955425660     PISSN: 01651684     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.sigpro.2010.05.030     Document Type: Article

References (24)

1. Consultative Committee for Space Data Systems (CCSDS), Radio Frequency and Modulation Systems, CCSDS, no. 401, 2001.
2. A. Swami, and B. Sadler Hierarchical digital modulation classification using cumulants IEEE Trans. Commun. 48 3 March 2000 416 429
3. O.A. Dobre, A. Abdi, Y. Bar-Ness, and W. Su Survey of automatic modulation classification techniques: classical approaches and new trends IET Commun. 1 2 April 2007 137 156
4. N. Lay, A. Polydoros, Modulation classification of signals in unknown ISI environments, in: Proceedings of the IEEE Milcom vol. 1, San Diego, CA, USA, November 1995, pp. 170174.
5. K.M. Chugg, C.S. Long, A. Polydoros, Combined likelihood power estimation and multiple hypothesis modulation classification, in: Asilomar Conference on Signals, Systems, Computers, vol. 2, November 1995, pp. 11371141.
6. L. Hong, K.C. Ho, An antenna array likelihood modulation classifier for BPSK and QPSK signals, in: Proceedings of the IEEE Milcom, vol. 1, Anaheim, CA, USA, October 2002, pp. 647651.
7. S. Soliman, and S.Z. Hsue Signal classification using statistical moments IEEE Trans. Commun. 40 May 1992 908 916
8. S. Lesage, J.-Y. Tourneret, P.M. Djuric, Classification of digital modulation by MCMC sampling, in: Proceedings of the IEEE International Confence on Acoustics, Speech, and Signal Processing (ICASSP), vol. 4, May 2001, pp. 25532555.
9. L. Rabiner A tutorial on hidden Markov models and selected applications in speech recognition Proc. IEEE 77 2 1989 257 286
10. A. Puengnim, T. Robert, N. Thomas, J. Vidal, Hidden Markov models for digital modulation classification in unknown ISI channels, in: Proceedings of the European Signal Processing Conference (EUSIPCO), Poznan, Poland, September 2007, pp. 18821885.
11. C.Y. Huang, and A. Polydoros Two small SNR classification rules for CPM Proc. IEEE Milcom 3 October 1992 1236 1240
12. C.D. Chung, A. Polydoros, Envelope based classification schemes for continuous phase binary frequency shift keyed modulation, in: Proceedings of the IEEE Milcom Fort Monmouth, NJ, October 1994, pp. 796800.
13. A.E. El-Mahdy, and N.M. Namazi Classification of multiple M-ary frequency-shift keying over a rayleigh fading channel IEEE Trans. Commun. 50 6 June 2002 967 974
14. A. Puengnim, N. Thomas, J. Tourneret, J. Vidal, Classification of linear and nonlinear modulations using the BaumWelch algorithm, in: Proceedings of the European Signal Processing Conference (EUSIPCO), Lauzanne, Switzerland, August 2008.
15. J.G. Proakis Digital Communications 2001 McGraw-Hill New York
16. F. Xiong Digital Modulation Techniques 2000 Artech House, Inc Norwood
17. W. Wei, and J.M. Mendel Maximum likelihood classification for digital amplitude-phase modulation IEEE Trans. Commun. 48 February 2000 189 193
18. A. Abdi, O.A. Dobre, R. Cauchy, Y. Bar-Ness, and W. Su Modulation classification in fading channels using antenna arrays Proc. IEEE Milcom 1 October 2004 211 217
19. C.P. Robert, and G. Casella Monte Carlo Statistical Methods second ed. 2004 Springer-Verlag New York
20. W.R. Gilks, S. Richardson, and D.J. Spiegelhalter Introducing Markov chain Monte Carlo W.R. Gilks, S. Richardson, D.J. Spiegelhalter, Markov chain Monte Carlo in Practice 1996 Chapman & Hall London, UK 1 19
21. J.M. Mendel Tutorial on higher-order statistics (spectra) in signal processing and system theory: theoretical results and some applications Proc. IEEE 79 3 March 1991 278 305
22. J.A.R. Fonollosa, J. Vidal, Application of hidden Markov models to blind channel characterization and data detection, in: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), vol. 4, Adelaide, Australia, April 1994, pp. 185188.
23. V. Krishnamurthy, and J. Moore On-line estimation of hidden Markov model parameters based on the KullbackLeibler information measure IEEE Trans. Signal Process. 41 11 1993 2557 2573
24. A.K. Jain, R.P.W. Duin, and J. Mao Statistical pattern recognition: a review IEEE Trans. Pattern Anal. Mach. Intell. 22 1 2000 4 37