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- Title
Minimum-Error-Based Approximation Model for Symmetric Alpha Stable Distribution.
- Authors
Xu, Zhi-Jiang; Wang, Kang; Wu, Yuan; Peng, Hong; Meng, Li-Min; Hua, Jing-Yu
- Abstract
In many communication channels the impulsive noise is usually assumed to be of a symmetric alpha stable (S αS) distribution. Unfortunately, except for the Gaussian, Cauchy, and Lévy laws, the analytical expressions for the probability density functions (PDF) of alpha stable distributions are unknown, resulting in very limited application of this distribution. In a practical system, the bi-parameter Cauchy-Gaussian mixture (BCGM) distribution is used to approximate the PDF of the S αS distribution to tackle this difficulty. In this paper, we derive the optimal mixture ratio of the BCGM model based on the minimum square error criterion and furthermore propose a simplified and robust version of BCGM for the S αS distribution. Numerical simulations show that our proposed model achieves better performance and is more robust than the conventional models, without incurring additional complexity.
- Subjects
APPROXIMATION theory; MULTICHANNEL communication; GAUSSIAN distribution; DENSITY functionals; PROBABILITY theory; MATHEMATICAL complex analysis; COMPUTER simulation
- Publication
Circuits, Systems & Signal Processing, 2012, Vol 31, Issue 6, p2195
- ISSN
0278-081X
- Publication type
Article
- DOI
10.1007/s00034-012-9423-0