Soft-decision metrics for coded orthogonal signaling in symmetric alpha-stable noise

被引：0
|
作者：
Souryal, MR [1 ]
Larsson, G [1 ]
Peric, BM [1 ]
Vojcic, BR [1 ]
机构：
[1] Natl Inst Stand & Technol, Wireless Commun Technol Grp, Gaithersburg, MD 20899 USA
来源：
2005 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS 1-5: SPEECH PROCESSING | 2005年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper derives new soft decision metrics for coded orthogonal signaling in symmetric alpha-stable noise, which has been used to model impulsive noise. In addition to the optimum metrics for Gaussian (alpha = 2) noise and Cauchy (alpha = 1) noise, a class of generalized likelihood ratio (GLR) metrics with lower side information requirements is derived. Through numerical results for a turbo code example, the Cauchy decoder is found to be robust for a wide range of alpha, and GLR metrics are found which provide performance gains relative to the Gaussian metric, but with lower complexity and less a priori information.
引用
收藏
页码：697 / 700
页数：4
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