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Acoustics, Speech, and Signal Processing, IEEE International Conference on (1993)
Minneapolis, MN, USA
Apr. 27, 1993 to Apr. 30, 1993
ISBN: 0-7803-0946-4
pp: 33-36
A.G. Dabak , Dept. Electr. & Comput. Eng., Rice Univ., Houston, TX, USA
D.H. Johnson , Dept. Electr. & Comput. Eng., Rice Univ., Houston, TX, USA
ABSTRACT
On the basis of a geometric theory of detection, the authors extend the notion of a signal constellation, a concept deeply rooted in Gaussian problems, to the non-Gaussian case. Significant differences between optimal designs for Gaussian and non-Gaussian situations are shown. In particular, square-wave signals are much more important in heavy-tailed, non-Gaussian noise situations than in Gaussian ones. Furthermore, design guidelines for non-Gaussian problems can vary with the number of signal set members and can depend on SNR. The extent to which suboptimal designs affect performance (using Gaussian-based designs in non-Gaussian situations, for example) can be predicted from calculations of the Kullback information, but only in the sense of determining how the logarithmic error probability rates differ.
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CITATION

A. Dabak and D. Johnson, "Signal constellations for non-Gaussian communication problems," Acoustics, Speech, and Signal Processing, IEEE International Conference on(ICASSP), Minneapolis, MN, USA, 1993, pp. 33-36.
doi:10.1109/ICASSP.1993.319428
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