Automatic modulation recognition of MPSK signals using constellation rotation and its 4th order cumulant

Marled Pedzlsz , A. Mansour

Ecole Nationale Sup\'e9rieure des Ing\'e9nieurs des Etudes et Techniques d'Armement,
 Lab. "Extraction et Exploitation de l'Information en Environnements Incertains'' (E3l2),
2 rue Francois Verny, 29806| Brest cedex 9, France

Available online 18 January 2005

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
 cumulate of a 1D distribution of the signal's in-phase component. Using Fourier series
 expansion of this cumulate as a function of the rotation angle, we extract invariant features
 which are then used in a neural classifier. Discrimination power of the pro- posed set of
 features is verified through extensive simulations, and the performance of the suggested
 algorithm is compared to tie 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.

@ 2005 Elsevier Inc. All rights reserved.

Keywords.. Automatic modulation recognition;
Signal classification; Constellation identification) Higher-order statistics