A Blind Modulation Recognition Algorithm Suitable for MIMO-STBC Systems

Blind modulation recognition is a challenging problem in Multiple Input Multiple Output (MIMO) systems in association with Space-Time Block Code (STBC). To our knowledge, there is no method reported in literature to deal with this problem. In this paper, a modulation classifier is presented based on Maximum Likelihood (ML) without utilizing the Channel State Information (CSI) and coding matrix. The modulations are classified into two categories according to the independence of the source signals: independent and non-independent constellations. The modulation recognition based on the ML classifier is discussed for independent (resp. non-independent) constellations by using Independent (resp. Multi-dimensional Independent) Component Analysis. Simulations show that our algorithm can work with high recognition probabilities in MIMO-STBC communication systems when CSI and coding matrix are unavailable.

[1]  Ali Abdi,et al.  Survey of automatic modulation classification techniques: classical approaches and new trends , 2007, IET Commun..

[2]  Gilles Burel,et al.  Blind Recognition of Linear Space–Time Block Codes: A Likelihood-Based Approach , 2010, IEEE Transactions on Signal Processing.

[3]  Arie Yeredor,et al.  Blind source separation via the second characteristic function , 2000, Signal Process..

[4]  Antoine Souloumiac,et al.  Jacobi Angles for Simultaneous Diagonalization , 1996, SIAM J. Matrix Anal. Appl..

[5]  Eric Moulines,et al.  A blind source separation technique using second-order statistics , 1997, IEEE Trans. Signal Process..

[6]  Gilles Burel,et al.  Modulation Recognition for MIMO Communications , 2008 .

[7]  Karim Abed-Meraim,et al.  Algorithms for joint block diagonalization , 2004, 2004 12th European Signal Processing Conference.

[8]  Branka Vucetic,et al.  Space-Time Coding , 2003 .

[9]  Fabian J. Theis,et al.  Blind signal separation into groups of dependent signals using joint block diagonalization , 2005, 2005 IEEE International Symposium on Circuits and Systems.

[10]  Marc Moeneclaey,et al.  ML-oriented NDA carrier synchronization for general rotationally symmetric signal constellations , 1994, IEEE Trans. Commun..

[11]  Y. Bar-Ness,et al.  Blind modulation classification: a concept whose time has come , 2005, IEEE/Sarnoff Symposium on Advances in Wired and Wireless Communication, 2005..

[12]  Fabian J. Theis,et al.  Multidimensional independent component analysis using characteristic functions , 2005, 2005 13th European Signal Processing Conference.

[13]  Marion Berbineau,et al.  Blind Modulation Identification for MIMO Systems , 2010, 2010 IEEE Global Telecommunications Conference GLOBECOM 2010.

[14]  E. Masoud,et al.  Space-Time Block Coding for Wireless Communications , 2008 .

[15]  Thomas Kailath,et al.  Detection of signals by information theoretic criteria , 1985, IEEE Trans. Acoust. Speech Signal Process..

[16]  Jean-François Cardoso,et al.  Multidimensional independent component analysis , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).

[17]  Elsayed Elsayed Azzouz,et al.  Algorithms for automatic modulation recognition of communication signals , 1998, IEEE Trans. Commun..