Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

IEEE Transactions on Information Theory

On the error-correcting capability of algebraic analog decoding (Corresp.)

Tai-Yang Hwang

Published Jan 1, 1980• 1 citation
Publisher

Abstract

The error-correctiog capability of algebraic analog decoding is found when the decoding region is extended to a hypercone-like region which contains the original decoding sphere. In addition, an analogy between algebraic analog decoding and generalized minimum distance decoding is established; both are quasi-soft decision algorithms.
DOI
10.1109/tit.1980.1056147

Related papers

Algebraic analog decoding of linear binary codes

L. Rudolph, Carlos R. P. Hartmann, Tai-Yang Hwang +1 more

Bit-by-bit soft-decision decoding of binary cyclic codes is considered. A significant reduction in decoder complexity can be achieved by requiring only that the decoder correct all analog error patterns which fall within a Euclidean sphere whose radius is equal to half the minimum Euclidean distance of the code. Such a "maximum-radius" scheme is asymptotically optimum for the additive white Gaussian noise (AWGN) channel. An iterative extension of the basic algebraic analog decoding scheme is discussed, and performance curves are given for the (17,9), (21,11), and (73,45) codes on the AWGN channel.

IEEE Transactions on Information Theory•Jul 1, 1979•21 citations

Generalized minimum distance decoding algorithms for Qary output channels (Corresp.)

Christopher C.H. Yu, Daniel J. Costello

A new condition for a generalized minimum distance decoder to guarantee correct decoding is developed. Based on this condition, decoding algorithms for block codes, product codes, and completely orthogonalizable codes onQary output channels are presented. The results of computer simulations comparing the performance of these decoding algorithms with several other soft-decision decoding algorithma are also presented.

IEEE Transactions on Information Theory•Mar 1, 1980•23 citations

Hard- and soft-decision decoding beyond the half minimum distance---An algorithm for linear codes (Corresp.)

Martin Bossert, F. Hergert

A decoding algorithm for linear codes that uses the minimum weight words of the dual code as parity checks is defined. This algorithm is able to correct beyond the half minimum distance and has the capability of including soft-decision decoding. Results on applying this algorithm to quadratic residue (QR) codes, BCH codes, and the Golay codes (with and without soft-decision decoding) are presented.

IEEE Transactions on Information Theory•Sep 1, 1986•38 citations

Decoding algorithms with maximum error correction

W.E. Stark, Amer A. Hassan

Decoding algorithms with reliability information are of considerable interest in error control coding. Such information when available and when properly used increases the error correcting capability of the decoder. We find decoding algorithms that use soft decision with optimal error correcting capability for fixed constraints on decoder complexity.>

IEEE International Symposium on Information Theory (ISIT)•Dec 17, 2002•1 citation

with Threshold Erasing

Khaled A. S. Abdel-Ghaffarl, Jos H. Weber

The error-correction capability and the performance of generalized minimum distance decod- ing based on threshold erasing is studied as a function of the number of decoding trials and of the allowable reliability values. Generalized Minimum Distance (GMD) decoding, as intro- duced by Forney (l), is a multitrial decoding algorithm that combines reliability information, represented by numbers in the closed interval (0,1), with algebraic decoding algorithms for error correction. In each trial, a fixed number of the most unreliable symbols in the received sequence is erased. If a cer- tain distance criterion is satisfied, Forney has shown that the transmitted codeword can be retrieved in at most (d/2) trials, where d is the Hamming distance of the code. In this work, we study a variation on Forney's scheme where, in each trial, symbols whose reliabilities are below a certain threshold are erased, and hence there is no need to sort the received symbols according to reliability values be- fore erasing as in Forney's GMD decoding. Furthermore, we consider limiting the allowable reliability values to the set R, = u~=mo/2'{1 - 2i/m}, where m = 1,2,3,. . .. This covers the simple cases of taking only hard decisions (m = l), allow- ing erasures (m = 2), or accommodating the full range (0,1) of reliability values as in Forney's GMD decoding (m + 00). Limiting the reliability values may be of importance since, in any digital implementation, the reliability values need to be quantized. Moreover, in some applications, e.g., GMD decod- ing of concatenated codes over discrete channels, the reliabil- ity values are discrete in nature (2). The maximum number of trials is kept as a parameter. Limiting the reliability values and the number of trials leads to the concept of reduced GMD decoding.

•Jan 1, 2001•0 citations

Generalized minimum distance decoding

G. David Forney

We introduce a new distance measure which permits likelihood information to be used in algebraic minimum distance decoding techniques. We give an efficient decoding algorithm, and develop exponential bounds on the probability of not decoding correctly. In one application, this technique yields the same probability of error as maximum likelihood decoding.

IEEE Transactions on Information Theory•Apr 1, 1966•565 citations
Bit-by-bit soft-decision decoding of binary cyclic codes is considered. A significant reduction in decoder complexity can be achieved by requiring only that the decoder correct all analog error patterns which fall within a Euclidean sphere whose radius is equal to half the minimum Euclidean distance of the code. Such a "maximum-radius" scheme is asymptotically optimum for the additive white Gaussian noise (AWGN) channel. An iterative extension of the basic algebraic analog decoding scheme is discussed, and performance curves are given for the (17,9), (21,11), and (73,45) codes on the AWGN channel.
The error-correction capability and the performance of generalized minimum distance decod- ing based on threshold erasing is studied as a function of the number of decoding trials and of the allowable reliability values. Generalized Minimum Distance (GMD) decoding, as intro- duced by Forney (l), is a multitrial decoding algorithm that combines reliability information, represented by numbers in the closed interval (0,1), with algebraic decoding algorithms for error correction. In each trial, a fixed number of the most unreliable symbols in the received sequence is erased. If a cer- tain distance criterion is satisfied, Forney has shown that the transmitted codeword can be retrieved in at most (d/2) trials, where d is the Hamming distance of the code. In this work, we study a variation on Forney's scheme where, in each trial, symbols whose reliabilities are below a certain threshold are erased, and hence there is no need to sort the received symbols according to reliability values be- fore erasing as in Forney's GMD decoding. Furthermore, we consider limiting the allowable reliability values to the set R, = u~=mo/2'{1 - 2i/m}, where m = 1,2,3,. . .. This covers the simple cases of taking only hard decisions (m = l), allow- ing erasures (m = 2), or accommodating the full range (0,1) of reliability values as in Forney's GMD decoding (m + 00). Limiting the reliability values may be of importance since, in any digital implementation, the reliability values need to be quantized. Moreover, in some applications, e.g., GMD decod- ing of concatenated codes over discrete channels, the reliabil- ity values are discrete in nature (2). The maximum number of trials is kept as a parameter. Limiting the reliability values and the number of trials leads to the concept of reduced GMD decoding.