Soft-Decision Metrics for Coded Orthogonal Signaling in Symmetric Alpha-Stable Noise

Published

March 1, 2005

Author(s)

Michael R. Souryal, E G. Larsson, B M. Peric, B R. Vojcic

Abstract

This paper derives new soft decision metrics for coded orthogonal signaling in symmetric a-stable noise, which has been used to model impulsive noise. In addition to the optimum metrics for Gaussian (a = 2) noise and Cauchy (a = 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 a, and GLR metrics are found which provide performance gains relative to the Gaussian metric, but with lower complexity and less a priori information.

Proceedings Title

Proceedings of the 2005 IEEE International Conference on Acoustics; Speech; and Signal Processing (ICASSP)

Volume

3

Conference Dates

March 18-23, 2005

Conference Location

March 18-23,

Conference Title

IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

Pub Type

Conferences

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Keywords

generalized likelihood ratio, impulsive noise, non-coherent detection, soft-decision metrics, stable distribution

Citation

Souryal, M. , Larsson, E. , Peric, B. and Vojcic, B. (2005), Soft-Decision Metrics for Coded Orthogonal Signaling in Symmetric Alpha-Stable Noise, Proceedings of the 2005 IEEE International Conference on Acoustics; Speech; and Signal Processing (ICASSP), March 18-23, , [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=50117 (Accessed December 22, 2024)