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Convexity of error rates in digital communications under non-Gaussian noise

Loyka, Sergey and Kostina, Victoria and Gagnon, François (2013) Convexity of error rates in digital communications under non-Gaussian noise. In: 2013 IEEE International Symposium on Information Theory. IEEE , Piscataway, NJ, pp. 41-45. ISBN 978-1-4799-0446-4.

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Convexity properties of error rates of a class of decoders, including the ML/min-distance one as a special case, are studied for arbitrary constellations. Earlier results obtained for the AWGN channel are extended to a wide class of (non-Gaussian) noise densities, including unimodal and spherically-invariant noise. Under these broad conditions, symbol error rates are shown to be convex functions of the SNR in the high-SNR regime with an explicitly-determined threshold, which depends only on the constellation dimensionality and minimum distance, thus enabling an application of the powerful tools of convex optimization to such digital communication systems in a rigorous way. It is the decreasing nature of the noise power density around the decision region boundaries that insures the convexity of symbol error rates in the general case. The known high/low SNR bounds of the convexity/concavity regions are tightened and no further improvement is shown to be possible in general.

Item Type:Book Section
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Kostina, Victoria0000-0002-2406-7440
Additional Information:© 2013 IEEE.
Record Number:CaltechAUTHORS:20190213-075441906
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Official Citation:S. Loyka, V. Kostina and F. Gagnon, "Convexity of error rates in digital communications under non-Gaussian noise," 2013 IEEE International Symposium on Information Theory, Istanbul, 2013, pp. 41-45. doi: 10.1109/ISIT.2013.6620184
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:92868
Deposited By: Tony Diaz
Deposited On:13 Feb 2019 16:01
Last Modified:16 Nov 2021 16:54

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