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This article is cited in 5 scientific papers (total in 5 papers)
Information Theory
Error Exponents for Product Convolutional
Codes
C. Medinaa, V. R. Sidorenkoba, V. V. Zyablovb a University of Ulm
b Institute for Information Transmission Problems, Russian Academy of Sciences
Abstract:
An upper bound on the error probability (first error event) of product convolutional
codes over a memoryless binary symmetric channel, and the resulting error exponent are derived.
The error exponent is estimated for two decoding procedures. It is shown that, for both decoding
methods, the error probability exponentially decreasing with the constraint length of product
convolutional codes can be attained with nonexponentially increasing decoding complexity.
Both estimated error exponents are similar to those for woven convolutional codes with outer
and inner warp.
Received: 09.02.2006 Revised: 10.05.2006
Citation:
C. Medina, V. R. Sidorenko, V. V. Zyablov, “Error Exponents for Product Convolutional
Codes”, Probl. Peredachi Inf., 42:3 (2006), 3–20; Problems Inform. Transmission, 42:3 (2006), 167–182
Linking options:
https://www.mathnet.ru/eng/ppi49 https://www.mathnet.ru/eng/ppi/v42/i3/p3
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Abstract page: | 443 | Full-text PDF : | 149 | References: | 46 | First page: | 6 |
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