438 research outputs found
Decoding of Repeated-Root Cyclic Codes up to New Bounds on Their Minimum Distance
The well-known approach of Bose, Ray-Chaudhuri and Hocquenghem and its
generalization by Hartmann and Tzeng are lower bounds on the minimum distance
of simple-root cyclic codes. We generalize these two bounds to the case of
repeated-root cyclic codes and present a syndrome-based burst error decoding
algorithm with guaranteed decoding radius based on an associated folded cyclic
code. Furthermore, we present a third technique for bounding the minimum
Hamming distance based on the embedding of a given repeated-root cyclic code
into a repeated-root cyclic product code. A second quadratic-time probabilistic
burst error decoding procedure based on the third bound is outlined. Index
Terms Bound on the minimum distance, burst error, efficient decoding, folded
code, repeated-root cyclic code, repeated-root cyclic product cod
Lemma for Linear Feedback Shift Registers and DFTs Applied to Affine Variety Codes
In this paper, we establish a lemma in algebraic coding theory that
frequently appears in the encoding and decoding of, e.g., Reed-Solomon codes,
algebraic geometry codes, and affine variety codes. Our lemma corresponds to
the non-systematic encoding of affine variety codes, and can be stated by
giving a canonical linear map as the composition of an extension through linear
feedback shift registers from a Grobner basis and a generalized inverse
discrete Fourier transform. We clarify that our lemma yields the error-value
estimation in the fast erasure-and-error decoding of a class of dual affine
variety codes. Moreover, we show that systematic encoding corresponds to a
special case of erasure-only decoding. The lemma enables us to reduce the
computational complexity of error-evaluation from O(n^3) using Gaussian
elimination to O(qn^2) with some mild conditions on n and q, where n is the
code length and q is the finite-field size.Comment: 37 pages, 1 column, 10 figures, 2 tables, resubmitted to IEEE
Transactions on Information Theory on Jan. 8, 201
Study of application of practical performance criteria for the implementation of efficient error-reduction coding Final report
Criteria for implementation of efficient error reduction codin
The Euclidean Algorithm for Generalized Minimum Distance Decoding of Reed-Solomon Codes
This paper presents a method to merge Generalized Minimum Distance decoding
of Reed-Solomon codes with the extended Euclidean algorithm. By merge, we mean
that the steps taken to perform the Generalized Minimum Distance decoding are
similar to those performed by the extended Euclidean algorithm. The resulting
algorithm has a complexity of O(n^2)
A comparison of VLSI architectures for time and transform domain decoding of Reed-Solomon codes
It is well known that the Euclidean algorithm or its equivalent, continued fractions, can be used to find the error locator polynomial needed to decode a Reed-Solomon (RS) code. It is shown that this algorithm can be used for both time and transform domain decoding by replacing its initial conditions with the Forney syndromes and the erasure locator polynomial. By this means both the errata locator polynomial and the errate evaluator polynomial can be obtained with the Euclidean algorithm. With these ideas, both time and transform domain Reed-Solomon decoders for correcting errors and erasures are simplified and compared. As a consequence, the architectures of Reed-Solomon decoders for correcting both errors and erasures can be made more modular, regular, simple, and naturally suitable for VLSI implementation
Decoding of Projective Reed-Muller Codes by Dividing a Projective Space into Affine Spaces
A projective Reed-Muller (PRM) code, obtained by modifying a (classical)
Reed-Muller code with respect to a projective space, is a doubly extended
Reed-Solomon code when the dimension of the related projective space is equal
to 1. The minimum distance and dual code of a PRM code are known, and some
decoding examples have been represented for low-dimensional projective space.
In this study, we construct a decoding algorithm for all PRM codes by dividing
a projective space into a union of affine spaces. In addition, we determine the
computational complexity and the number of errors correctable of our algorithm.
Finally, we compare the codeword error rate of our algorithm with that of
minimum distance decoding.Comment: 17 pages, 4 figure
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