Blind Digital Modulation Identification for Spatially-Correlated MIMO Systems

• Published in: IEEE transactions on wireless communications Vol. 11; no. 2; pp. 683 - 693
• Main Authors: Hassan, K., Dayoub, I., Hamouda, W., Nzeza, C. N., Berbineau, M.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.02.2012; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Acceptability; Applied sciences; Blinds; Channels; Classification; Correlation; Detection, estimation, filtering, equalization, prediction; Digital; Engineering Sciences; Exact sciences and technology; Feature extraction; Higher order statistics; Information, signal and communications theory; MIMO; Modulation; modulation identification; multiple-input multiple-output systems; Signal and communications theory; Signal processing algorithms; Signal representation. Spectral analysis; Signal to noise ratio; Signal, noise; spatial correlation; Systems, networks and services of telecommunications; Telecommunications; Telecommunications and information theory; Transmission and modulation (techniques and equipments); Vectors; Waveforms; Wireless communication; MIMO system; High performance; Automatic classification; Parameter estimation; Spatial correlation; Signal estimation; multiple-input multipleoutput systems; Blind identification; modulation identification; Algorithm; Signal classification; Linear modulation; Higher order statistic; Channel estimation; Multiple system; System identification; Cumulant; Signal to noise ratio; Higher order statistics; Correlation; Modulation; Signal processing algorithms; Feature extraction; MIMO; Vectors
• ISSN: 1536-1276; 1558-2248
• DOI: 10.1109/TWC.2011.122211.110236

Modulation type is one of the most important characteristics used in signal waveform identification and classification. Spatial correlation is a crucial factor for practical multiple-input multiple-output (MIMO) systems. This paper addresses the problem of blind digital modulation identification in spatially-correlated MIMO systems. The proposed algorithm is verified using higher order statistical moments and cumulants of the received signal. The purpose is to discriminate among different M-ary shift keying linear modulation schemes without any priori signal information. This study employs several MIMO techniques to identify the modulation with and without channel state information (CSI). The proposed classifier shows a high identification performance in acceptable signal-to-noise ratio (SNR) range.