Author_Institution :
127 E. 91st St., New York, NY, USA
Abstract :
The subject here is generalized (i.e., non-Gaussian) noise models, and specifically their first-order probability density functions (PDFs). Attention is focused primarily on the author´s canonical statistical-physical Class A and Class B models. In particular, Class A noise describes the type of electromagnetic interference (EMI) often encountered in telecommunication applications, where this ambient noise is largely due to other, “intelligent” telecommunication operations. On the other hand, ambient Class B noise usually represents man-made or natural “nonintelligent”-i.e., nonmessage-bearing noise-and is highly impulsive. Class A noise is not an α-stable process, nor is it reducible to such, except in the limiting Gaussian cases of high-density noise (by the central limit theorem). Class B noise is also asymptotically normal (before model approximation). Under rather broad conditions, principally governed by the source propagation and distribution scenarios, the PDF of Class B noise alone (no Gaussian component) can usually be approximated by (1) a symmetric Gaussian α-stable (SαS) model in the case of narrowband reception, or when the PDF ω1(α) of the amplitude is symmetric; and (2) a nonsymmetric α-stable (NSαS) model (no Gaussian component) can be constructed in broadband regimes. New results here include: (i) counting functional methods for constructing the general qth-order characteristic functions (CFs) of Class A and Class B noise, from which (all) moments and (in principle), the PDFs follow; (ii) the first-order CFs, PDFs, and cumulative probabilities (APDs) of nonsymmetric broadband Class B noise, extended to include additive Gauss noise (AGN); (iii) proof of the existence of all moments in the basic Class A and Class B models; (iv) the key physical role of AGN and the fact that AGN removes α-stability; (v) the explicit roles of the propagation and distribution scenarios; and (vi) extension to noise fields. Although telecommunication applications are emphasized, Class A and Class B noise models apply selectively, but equally well, to other physical regimes, e.g., underwater acoustics and EM (radar, optics, etc.). Supportive empirical data are included
Keywords :
electromagnetic interference; probability; signal processing; telecommunication; EMI; Poisson model; additive Gauss noise; ambient noise; asymptotically normal noise; canonical statistical-physical models; characteristic functions; class A noise model; class B noise model; cumulative probabilities; electromagnetic interference; first-order probability density functions; functional methods; generalized nonGaussian noise models; man-made noise; narrowband reception; natural noise; nonsymmetric α-stable model; optics; radar; signal processing; source distribution; source propagation; symmetric Gaussian α-stable model; telecommunication applications; underwater acoustics; Additive noise; Electromagnetic interference; Gaussian noise; Limiting; Narrowband; Noise level; Noise reduction; Optical noise; Probability density function; Signal processing;