Fisher information and noise-aided power estimation from one-bit quantizers
We investigate power estimation on a random noise from measurements taken by one-bit quantizers, with an efficacy assessed by the Fisher information. In isolated quantizers, an optimal tuning of the quantization threshold exists to maximize the estimation efficacy. When the quantizers are assembled in parallel arrays, no specific tuning of the quantization threshold is any longer required. Instead, addition of noise in the array can be employed as a means of enhancing the estimation efficacy. This is interpreted as a form of stochastic resonance or improvement by noise, applied to parametric estimation on a noise, which is shown improvable by adding more noise.
fisher information noise power estimation quantizer stochastic resonance