Nonlinear signal detection from an array of threshold devices for non-Gaussian noise

Authors:
Youguo Wang;Lenan Wu
Affiliations:
Department of Radio Engineering, Southeast University, 210096, Nanjing, People's Republic of China and School of Mathematics and Physics, Nanjing University of Posts and Telecommunications, 210003 ...;Department of Radio Engineering, Southeast University, 210096, Nanjing, People's Republic of China
Venue:
Digital Signal Processing
Year:
2007

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Abstract

We discuss the beneficial action of non-Gaussian noise in nonlinear signal detection through an array of threshold devices based on the probability of error. For unimodal generalized Gaussian noise, only when the input signal is sub-threshold, stochastic resonance (SR) exists. The efficacy of SR reduces as the exponent parameter in the noise probability density function (PDF) becomes small. This result is analogical with a previous result where the signal PDF has an effect on the efficacy of SR. The efficacy of SR also reduces as the threshold level is raised. However, for bimodal Gaussian mixture noise, not only when the input signal is sub-threshold, SR sometimes exists, but also when the input signal is supra-threshold, supra-threshold stochastic resonance (SSR) often exists, too. The parameter in the Gaussian mixture noise PDF has an effect on the occurrence of SR and SSR. Array can enhance the efficacy of the nonlinear detection as the number of threshold devices in the array is raised. These results show further that the phenomena of SR and SSR depend on the characteristic of the threshold noise and also extend the applicability of SR and SSR in nonlinear signal detection.