Blind modulation classification: a concept whose time has come

We address the problem of identifying the modulation format of an incoming signal. We review many existing techniques for digital modulation recognition in a systematic way, which helps the reader to see the main features of each technique. The goal is to provide useful guidelines for choosing appropriate classification algorithms for different modulations, from the large pool of available techniques. Furthermore, the performance of a benchmark classifier is presented, as well as its sensitivity to several model mismatches. Open problems and possible directions for further research are briefly discussed

[1]  C. Spooner.  On the utility of sixth-order cyclic cumulants for RF signal classification , 2001, Conference Record of Thirty-Fifth Asilomar Conference on Signals, Systems and Computers (Cat.No.01CH37256).

[2]  Jean-Louis Lacoume,et al.  Multiple hypothesis modulation classification based on cyclic cumulants of different orders , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).

[3]  Y. Bar-Ness,et al.  Modulation classification in fading channels using antenna arrays , 2004, IEEE MILCOM 2004. Military Communications Conference, 2004..

[4]  C. L. Nikias,et al.  Higher-order spectra analysis : a nonlinear signal processing framework , 1993 .

[5]  D. Boudreau,et al.  A fast automatic modulation recognition algorithm and its implementation in a spectrum monitoring application , 2000, MILCOM 2000 Proceedings. 21st Century Military Communications. Architectures and Technologies for Information Superiority (Cat. No.00CH37155).

[6]  Y. Bar-Ness,et al.  Higher-order cyclic cumulants for high order modulation classification , 2003, IEEE Military Communications Conference, 2003. MILCOM 2003..

[7]  Jerry M. Mendel,et al.  Maximum-likelihood classification for digital amplitude-phase modulations , 2000, IEEE Trans. Commun..

[8]  K. C. Ho,et al.  Identification of digital modulation types using the wavelet transform , 1999, MILCOM 1999. IEEE Military Communications. Conference Proceedings (Cat. No.99CH36341).

[9]  K. C. Ho,et al.  Modulation identification of digital signals by the wavelet transform , 2000 .

[10]  Octavia A. Dobre,et al.  Robust QAM modulation classification algorithm using cyclic cumulants , 2004, 2004 IEEE Wireless Communications and Networking Conference (IEEE Cat. No.04TH8733).

[11]  J.E. Mazo,et al.  Digital communications , 1985, Proceedings of the IEEE.

[12]  Achilleas Anastasopoulos,et al.  Likelihood ratio tests for modulation classification , 2000, MILCOM 2000 Proceedings. 21st Century Military Communications. Architectures and Technologies for Information Superiority (Cat. No.00CH37155).

[13]  Brian M. Sadler,et al.  Hierarchical digital modulation classification using cumulants , 2000, IEEE Trans. Commun..

[14]  Andreas Polydoros,et al.  Likelihood methods for MPSK modulation classification , 1995, IEEE Trans. Commun..

[15]  A. Polydoros,et al.  Further results in likelihood classification of QAM signals , 1994, Proceedings of MILCOM '94.

[16]  J. Reichert,et al.  Automatic classification of communication signals using higher order statistics , 1992, [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[17]  Georgios B. Giannakis,et al.  Asymptotic theory of mixed time averages and k th-order cyclic-moment and cumulant statistics , 1995, IEEE Trans. Inf. Theory.

[18]  Samir S. Soliman,et al.  Signal classification using statistical moments , 1992, IEEE Trans. Commun..

[19]  Mark E. Johnson.  Multivariate Statistical Simulation: Johnson/Multivariate , 1987 .

[20]  D.H. Johnson,et al.  The Signal Processing Information Base , 1993, IEEE Signal Processing Magazine.

[21]  M. Melamed.  Detection , 2021, SETI: Astronomy as a Contact Sport.

[22]  C.M. Spooner,et al.  Classification of co-channel communication signals using cyclic cumulants , 1995, Conference Record of The Twenty-Ninth Asilomar Conference on Signals, Systems and Computers.

[23]  Harry L. Van Trees,et al.  Detection, Estimation, and Modulation Theory, Part I , 1968 .

[24]  Charles L. Weber,et al.  Asynchronous classification of MFSK signals using the higher order correlation domain , 1998, IEEE Trans. Commun..

[25]  Charles L. Weber,et al.  Higher-Order Correlation-Based Approach to Modulation Classification of Digitally Frequency-Modulated Signals , 1995, IEEE J. Sel. Areas Commun..