KSII Transactions on Internet and Information Systems (TIIS)

Korean Society for Internet Information (한국인터넷정보학회)
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Signal Detection Based on a Decreasing Exponential Function in Alpha-Stable Distributed Noise

  • Luo, Jinjun (School of Electronic Science and Engineering, National University of Defense Technology) ;
  • Wang, Shilian (School of Electronic Science and Engineering, National University of Defense Technology) ;
  • Zhang, Eryang (School of Electronic Science and Engineering, National University of Defense Technology)
  • Received : 2017.06.25
  • Accepted : 2017.09.15
  • Published : 2018.01.31
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Abstract

Signal detection in symmetric alpha-stable ($S{\alpha}S$) 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 $S{\alpha}S$ 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 $S{\alpha}S$ noise with small characteristic exponent values. In addition, the DEF detector outperforms the fractional lower order moment (FLOM)-based detector in $S{\alpha}S$ noise for most characteristic exponent values with the same order of magnitude of computational complexity.

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References

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