Proceedings ArticleDOI
Decoding "turbo"-codes with the soft output Viterbi algorithm (SOVA)
J. Hagenauer,L. Papke +1 more
- pp 164
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TLDR
The simple soft output viterbi algorithm (SOVA) meets all the requirements for iterative decoding if an a priori term is added and surprisingly good performance is achieved for the Gaussian and Rayleigh channel.Abstract:
Iterative decoding of two dimensional systematic convolutional codes has been termed "turbo"-(de)coding. It is shown that the simple soft output viterbi algorithm (SOVA) meets all the requirements for iterative decoding if an a priori term is added. With simple 4 and 16 state codes surprisingly good performance is achieved for the Gaussian and Rayleigh channel with a very small degradation relative to the complicated MAP algorithm. >read more
Citations
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Journal ArticleDOI
Iterative decoding of binary block and convolutional codes
TL;DR: Using log-likelihood algebra, it is shown that any decoder can be used which accepts soft inputs-including a priori values-and delivers soft outputs that can be split into three terms: the soft channel and aPriori inputs, and the extrinsic value.
Codes and Decoding on General Graphs
TL;DR: It is showed that many iterative decoding algorithms are special cases of two generic algorithms, the min-sum and sum-product algorithms, which also include non-iterative algorithms such as Viterbi decoding.
Journal ArticleDOI
A distance spectrum interpretation of turbo codes
TL;DR: The interleaver in the turbo encoder is shown to reduce the number of low-weight codewords through a process called "spectral thinning," which results in the free distance asymptote being the dominant performance parameter for low and moderate signal-to-noise ratios.
Proceedings ArticleDOI
Hybrid concatenated codes and iterative decoding
Dariush Divsalar,F. Pollara +1 more
TL;DR: An upper bound to the bit error rate (BER) of the hybrid code is obtained and a low-complexity iterative decoding algorithm with near maximum-likelihood performance is proposed.
References
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Proceedings ArticleDOI
Near Shannon limit error-correcting coding and decoding: Turbo-codes. 1
TL;DR: In this article, a new class of convolutional codes called turbo-codes, whose performances in terms of bit error rate (BER) are close to the Shannon limit, is discussed.
Journal ArticleDOI
Optimal decoding of linear codes for minimizing symbol error rate (Corresp.)
TL;DR: The general problem of estimating the a posteriori probabilities of the states and transitions of a Markov source observed through a discrete memoryless channel is considered and an optimal decoding algorithm is derived.
Proceedings ArticleDOI
A Viterbi algorithm with soft-decision outputs and its applications
TL;DR: The Viterbi algorithm is modified to deliver the most likely path sequence in a finite-state Markov chain, as well as either the a posteriori probability for each bit or a reliability value, with the aim of producing soft decisions to be used in the decoding of outer codes.