Nonparametric Blind Signal Detection Based on Logarithmic Moments in Very Impulsive Noise

Abstract

The detection problem in impulsive noise modeled by the symmetric alpha stable SαS distribution is studied. The traditional detectors based on the second or higher order moments fail in SαS noise, and the method based on the fractional lower order moments (FLOMs) performs poorly when the noise distribution has small values of characteristic exponent. In this paper, a detector based on the logarithmic moments is investigated. The analytical expressions of the false alarm and detection probabilities are derived in nonfading channels as well as Rayleigh fading channels. The effect of noise uncertainty on the performance is discussed. Simulation results show that the logarithmic detector performs better than the FLOM and Cauchy detectors in very impulsive noise. In addition, the logarithmic detector is a nonparametric method and avoids estimating the parameter of the noise distribution, which makes the logarithmic detector easier to implement than the FLOM detector.

Wideband signal detection in multipath environment affected by impulsive noise

“…Additionally, a diversitymerge scheme has been developed to mitigate the multipath propagation effect, but unfortunately, it increases the complexity of the detector. A logarithmic moment detector and fractional low-order moment detector have been investigated under Rayleigh fading channel assumption (Luo et al, 2018). These detectors have simple structures and good robustness characteristics, but they are both blind detectors based on the assumption that the transmitted LFM is unknown, which is not the typical case in UWA communications.…”