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dc.contributor.authorPedzisz, M.
dc.contributor.authorMansour, Ali
dc.date.accessioned2017-01-30T12:00:38Z
dc.date.available2017-01-30T12:00:38Z
dc.date.created2010-03-17T20:03:15Z
dc.date.issued2005
dc.identifier.citationPedzisz, Maciej and Mansour, Ali. 2005. Automatic Modulation Recognition of MPSK Signals Using Constellation Rotation and its 4-th Order Cumulant. Digital Signal Processing. 15 (3): pp. 295-304.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/17244
dc.identifier.doi10.1016/j.dsp.2004.12.007
dc.description.abstract

We derive and analyze a new pattern recognition approach for automatic modulation recognition of MPSK (2, 4, and 8) signals in broad-band Gaussian noise. Presented method is based on constellation rotation of the received symbols, and a 4th order cumulant of a 1D distribution of the signal's in-phase component. Using Fourier series expansion of this cumulant as a function of the rotation angle, we extract invariant features which are then used in a neural classifier. Discrimination power of the proposed set of features is verified through extensive simulations, and the performance of the suggested algorithm is compared to the maximum-likelihood (ML) classifiers. Corresponding results show that our technique is comparable to the coherent ML classifier and outperforms the non-coherent pseudo-ML method for all considered signal-to-noise ratio (SNR) without the computational overhead of the latter.

dc.publisherAcademic Press
dc.titleAutomatic Modulation Recognition of MPSK Signals Using Constellation Rotation and its 4-th Order Cumulant
dc.typeJournal Article
dcterms.source.volume15
dcterms.source.startPage295
dcterms.source.endPage304
dcterms.source.issn10512004
dcterms.source.titleDigital Signal Processing
curtin.accessStatusFulltext not available
curtin.facultyDepartment of Electrical and Computer Engineering
curtin.facultySchool of Engineering
curtin.facultyFaculty of Science and Engineering


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