Journal ArticleDOI
An efficient maximum-likelihood-decoding algorithm for linear block codes with algebraic decoder
TLDR
Computer simulation results indicate, for some signal-to-noise ratios (SNR), that the proposed soft decoding algorithm requires less average complexity than those of the other two algorithms, but the performance of the algorithm is always superior to those ofthe other two.Abstract:
A new soft decoding algorithm for linear block codes is proposed. The decoding algorithm works with any algebraic decoder and its performance is strictly the same as that of maximum-likelihood-decoding (MLD). Since our decoding algorithm generates sets of different candidate codewords corresponding to the received sequence, its decoding complexity depends on the received sequence. We compare our decoding algorithm with Chase (1972) algorithm 2 and the Tanaka-Kakigahara (1983) algorithm in which a similar method for generating candidate codewords is used. Computer simulation results indicate, for some signal-to-noise ratios (SNR), that our decoding algorithm requires less average complexity than those of the other two algorithms, but the performance of ours is always superior to those of the other two. >read more
Citations
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Journal ArticleDOI
Soft decision decoding of linear block codes based on ordered statistics
M.P.C. Fossorier,Shu Lin +1 more
TL;DR: A novel approach to soft decision decoding for binary linear block codes that achieves a desired error performance progressively in a number of stages and is terminated at the stage where either near-optimum error performance or a desired level of error performance is achieved.
Book
The art of error correcting coding
TL;DR: This chapter discusses encoding and decoding of binary BCH codes as well as some of the techniques used in the Viterbi algorithm, which simplifies the decoding process and increases the chances of success in the face of uncertainty.
Journal ArticleDOI
Iterative reliability-based decoding of low-density parity check codes
TL;DR: A stopping criterion which reduces the average number of iterations at the expense of very little performance degradation is proposed for this combined decoding approach to bridge the error performance gap between belief propagation decoding which remains suboptimum, and maximum likelihood decoding which is too complex to be implemented for the codes considered.
Journal ArticleDOI
Efficient priority-first search maximum-likelihood soft-decision decoding of linear block codes
TL;DR: In this paper, a generalized Dijkstra's algorithm is employed to search through a trellis for an equivalent code of the transmitted code, guided by an evaluation function f defined to take advantage of the information provided by the received vector and the inherent properties of transmitted code.
Journal ArticleDOI
On iterative soft-decision decoding of linear binary block codes and product codes
R. Lucas,M. Bossert,M. Breitbach +2 more
TL;DR: A decoding algorithm which only uses parity check vectors of minimum weight is proposed, which gives results close to soft decision maximum likelihood (SDML) decoding for many code classes like BCH codes.
References
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Generalized minimum distance decoding
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Journal ArticleDOI
Efficient maximum likelihood decoding of linear block codes using a trellis
TL;DR: It is shown that soft decision maximum likelihood decoding of any (n,k) linear block code over GF(q) can be accomplished using the Viterbi algorithm applied to a trellis with no more than q^{(n-k)} states.
Journal ArticleDOI
An improvement to generalized-minimum-distance decoding
D.J. Taipale,Michael B. Pursley +1 more
TL;DR: The performance of generalized minimum distance (GMD) decoding is better if the new criterion is used, and the weights used in GMD decoding are generalized to permit each of the possible M symbol values to have a different weight.
Journal ArticleDOI
Simplified correlation decoding by selecting possible codewords using erasure information (Corresp.)
H. Tanaka,K. Kakigahara +1 more
TL;DR: A new algorithm for soft-decision decoding is presented, simplifying the correlation scheme by selecting certain codewords and decreasing decoding complexity by using erasure information.