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Near Shannon limit error-correcting coding and decoding (1993)
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BibTeX
@INPROCEEDINGS{Berrou93nearshannon,
author = {Claude Berrou and Alain Glavieux and Punya Thitimajshima},
title = {Near Shannon limit error-correcting coding and decoding},
booktitle = {},
year = {1993},
pages = {1064--1070}
}
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Abstract
Abstract- This paper deals with a new class of convolutional codes called Turbo-codes, whose performances in terms of Bit Error Rate (BER) are close to the SHANNON limit. The Turbo-Code encoder is built using a parallel concatenation of two Recursive Systematic Convolutional codes and the associated decoder, using a feedback decoding rule, is implemented as P pipelined identical elementary decoders. Consider a binary rate R=1/2 convolutional encoder with constraint length K and memory M=K-1. The input to the encoder at time k is a bit dk and the corresponding codeword
Keyphrases
error-correcting coding constraint length new class associated decoder bit error rate memory k-1 recursive systematic convolutional code turbo-code encoder shannon limit corresponding codeword parallel concatenation convolutional encoder feedback decoding rule identical elementary decoder binary rate convolutional code
