Digital modulation classification using power moment matrices
Hero, A.O., III; Hadinejad-Mahram, H.
Acoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on
Volume 6, Issue , 12-15 May 1998 Page(s):3285 - 3288 vol.6
Digital Object Identifier 10.1109/ICASSP.1998.679566
Summary:With the rising number of modulation types used in multi-user and
multi-service digital communication systems, the need to find efficient
methods for their discrimination in the presence of noise has become
increasingly important. We present a new approach based on a pattern
recognition method previously applied to word spotting problems in
binary images. In this approach, a large number of spatial moments are
arranged in a symmetric positive definite matrix for which
eigendecomposition and noise subspace processing methods can be applied.
The resultant denoised moment matrix has entries which are used in place
of the raw moments for improved pattern classification. In this paper,
we generalize the moment matrix technique to grey scale images and apply
the technique to discrimination between M-ary PSK and QAM constellations
in signal space. Invariance to unknown phase angle and signal amplitude
is achieved by representing the in-phase and quadrature components of
the signal in the complex plane, and computing joint moments of
normalized magnitude and phase components
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