Comparison between asymmetric generalized Gaussian (AGG) and symmetric-α-stable (SαS) noise models for signal estimation in non Gaussian environments
Alessandra Teseï, Roberto Bozzano, Carlo S. Regazzoni · 2002
This paper focuses on the problem of multilevel digital signal estimation in the presence of generic noise in a communication system. Noise is assumed unimodal, independent identically distributed, generically non Gaussian, that is eventually asymmetric, impulsive or not. The proposed solution is based on a previously developed estimator which requires the analytical probability density function model of the noise. The selected estimator was originally applied under the assumption of S/spl alpha/S noise distribution. In this paper the asymmetric generalized Gaussian (agg) model is selected as a suitable model to describe the noise processes: hence, it is discussed and compared with the S/spl alpha/S distributions in terms of decoding performances. Tests were performed on simulated binary sequences corrupted by interference generated as S/spl alpha/S processes. Test results outlines comparable performances of the two families of parametric noise models.