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https://doi.org/10.1109/isit.2...
Article . 2016 . Peer-reviewed
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https://dx.doi.org/10.48550/ar...
Article . 2016
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Balanced Reed-Solomon codes

Authors: Halbawi, Wael; Liu, Zihan; Hassibi, Babak;

Balanced Reed-Solomon codes

Abstract

We consider the problem of constructing linear Maximum Distance Separable (MDS) error-correcting codes with generator matrices that are sparsest and balanced. In this context, sparsest means that every row has the least possible number of non-zero entries, and balanced means that every column contains the same number of non-zero entries. Codes with this structure minimize the maximal computation time of computing any code symbol, a property that is appealing to systems where computational load-balancing is critical. The problem was studied before by Dau et al. where it was shown that there always exists an MDS code over a sufficiently large field such that its generator matrix is both sparsest and balanced. However, the construction is not explicit and more importantly, the resulting MDS codes do not lend themselves to efficient error correction. With an eye towards explicit constructions with efficient decoding, we show in this paper that the generator matrix of a cyclic Reed-Solomon code of length $n$ and dimension $k$ can always be transformed to one that is both sparsest and balanced, for all parameters $n$ and $k$ where $\frac{k}{n}(n - k + 1)$ is an integer.

Submitted to ISIT 2016

Country
United States
Related Organizations
Keywords

FOS: Computer and information sciences, Computer Science - Information Theory, Information Theory (cs.IT), Reed–Solomon Codes, Erasure Codes, Welch-Berlekamp Algorithm, Distributed Storage, Error-Correcting Codes, Load Balancing, 004

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
18
Top 10%
Top 10%
Top 10%
Green