Signal Detection Based on a Decreasing Exponential Function in Alpha-Stable Distributed Noise

• Jinjun Luo,
• Shilian Wang,
• Eryang Zhang,

Vol. 12, No. 1, January 30, 2018
10.3837/tiis.2018.01.013, Download Paper (Free):

• Alpha-stable distribution
• Impulsive noise
• decreasing exponential function
• signal detection

Abstract

Signal detection in symmetric alpha-stable (SS α ) distributed noise is a challenging problem. This paper proposes a detector based on a decreasing exponential function (DEF). The DEF detector can effectively suppress the impulsive noise and achieve good performance in the presence of SS α noise. The analytical expressions of the detection and false alarm probabilities of the DEF detector are derived, and the parameter optimization for the detector is discussed. A performance analysis shows that the DEF detector has much lower computational complexity than the Gaussian kernelized energy detector (GKED), and it performs better than the latter in SS α noise with small characteristic exponent values. In addition, the DEF detector outperforms the fractional lower order moment (FLOM)-based detector in SS α noise for most characteristic exponent values with the same order of magnitude of computational complexity.

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