Open AccessSimple Detection Based on Soft‐Limiting for Binary Transmission in a Mixture of Generalized Normal‐Laplace Distributed Noise and Gaussian Noise
Author(s) -
Kim Sangchoon
Publication year - 2011
Publication title -
etri journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.295
H-Index - 46
eISSN - 2233-7326
pISSN - 1225-6463
DOI - 10.4218/etrij.11.0211.0026
Subject(s) - gaussian noise , mathematics , gaussian , gradient noise , binary number , additive white gaussian noise , laplace transform , impulse noise , algorithm , noise (video) , noise measurement , white noise , mathematical analysis , noise reduction , computer science , noise floor , statistics , physics , artificial intelligence , pixel , arithmetic , quantum mechanics , image (mathematics)
In this letter, a simplified suboptimum receiver based on soft‐limiting for the detection of binary antipodal signals in non‐Gaussian noise modeled as a generalized normal‐Laplace (GNL) distribution combined with Gaussian noise is presented. The suboptimum receiver has low computational complexity. Furthermore, when the number of diversity branches is small, its performance is very close to that of the Neyman‐Pearson optimum receiver based on the probability density function obtained by the Fourier inversion of the characteristic function of the GNL‐plus‐Gaussian distribution.