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

• Main Authors: Jinjun Luo, Shilian Wang, Eryang Zhang, Xin Man
• Format: Article
• Language: English
• Published: Hindawi Limited 2018-01-01
• Series: Mobile Information Systems
• Online Access: http://dx.doi.org/10.1155/2018/7328910

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.