Density Evolution for SUDOKU Codes on the Erasure Channel
Codes based on SUDOKU puzzles are discussed, and belief propagation decoding introduced for the erasure channel. Despite the non-linearity of the code constraints, it is argued that density evolution can be used to analyse code performance due to the invariance of the code under alphabet permutation...
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creator | Atkins, Caroline Sayir, Jossy |
description | Codes based on SUDOKU puzzles are discussed, and belief propagation decoding
introduced for the erasure channel. Despite the non-linearity of the code
constraints, it is argued that density evolution can be used to analyse code
performance due to the invariance of the code under alphabet permutation. The
belief propagation decoder for erasure channels operates by exchanging messages
containing sets of possible values. Accordingly, density evolution tracks the
probability mass functions of the set cardinalities. The equations governing
the mapping of those probability mass functions are derived and calculated for
variable and constraint nodes, and decoding thresholds are computed for long
SUDOKU codes with random interleavers. |
doi_str_mv | 10.48550/arxiv.1407.4328 |
format | Article |
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introduced for the erasure channel. Despite the non-linearity of the code
constraints, it is argued that density evolution can be used to analyse code
performance due to the invariance of the code under alphabet permutation. The
belief propagation decoder for erasure channels operates by exchanging messages
containing sets of possible values. Accordingly, density evolution tracks the
probability mass functions of the set cardinalities. The equations governing
the mapping of those probability mass functions are derived and calculated for
variable and constraint nodes, and decoding thresholds are computed for long
SUDOKU codes with random interleavers.</description><identifier>DOI: 10.48550/arxiv.1407.4328</identifier><language>eng</language><subject>Computer Science - Information Theory ; Mathematics - Information Theory</subject><creationdate>2014-07</creationdate><rights>http://arxiv.org/licenses/nonexclusive-distrib/1.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,780,885</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/1407.4328$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.1407.4328$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Atkins, Caroline</creatorcontrib><creatorcontrib>Sayir, Jossy</creatorcontrib><title>Density Evolution for SUDOKU Codes on the Erasure Channel</title><description>Codes based on SUDOKU puzzles are discussed, and belief propagation decoding
introduced for the erasure channel. Despite the non-linearity of the code
constraints, it is argued that density evolution can be used to analyse code
performance due to the invariance of the code under alphabet permutation. The
belief propagation decoder for erasure channels operates by exchanging messages
containing sets of possible values. Accordingly, density evolution tracks the
probability mass functions of the set cardinalities. The equations governing
the mapping of those probability mass functions are derived and calculated for
variable and constraint nodes, and decoding thresholds are computed for long
SUDOKU codes with random interleavers.</description><subject>Computer Science - Information Theory</subject><subject>Mathematics - Information Theory</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNotj72OgkAURqfZwuj2VmZeABzm586lNIjrRhMLpSYXGCIJwmZAs779qmv1Jaf4cg5j80iEGo0RS_K_zS2MtLChVhInLF67bmjGO09vfXsdm77jde_5MVsfdhlP-soN_MHGs-Opp-HqHU_O1HWunbGPmtrBfb53yk6b9JRsg_3h6ztZ7QMCg0FUIxmKNRQWtTRVgWAtUCUtGi1ASe0wUqUqq_iBCgAN0iGAEQoJrVFTtvi_fannP765kL_nz4T8maD-AHo1PjY</recordid><startdate>20140716</startdate><enddate>20140716</enddate><creator>Atkins, Caroline</creator><creator>Sayir, Jossy</creator><scope>AKY</scope><scope>AKZ</scope><scope>GOX</scope></search><sort><creationdate>20140716</creationdate><title>Density Evolution for SUDOKU Codes on the Erasure Channel</title><author>Atkins, Caroline ; Sayir, Jossy</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a658-1f8a5a946b78425db86776ad2785406324e813c3cd9278b66462e8665038a8753</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Computer Science - Information Theory</topic><topic>Mathematics - Information Theory</topic><toplevel>online_resources</toplevel><creatorcontrib>Atkins, Caroline</creatorcontrib><creatorcontrib>Sayir, Jossy</creatorcontrib><collection>arXiv Computer Science</collection><collection>arXiv Mathematics</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Atkins, Caroline</au><au>Sayir, Jossy</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Density Evolution for SUDOKU Codes on the Erasure Channel</atitle><date>2014-07-16</date><risdate>2014</risdate><abstract>Codes based on SUDOKU puzzles are discussed, and belief propagation decoding
introduced for the erasure channel. Despite the non-linearity of the code
constraints, it is argued that density evolution can be used to analyse code
performance due to the invariance of the code under alphabet permutation. The
belief propagation decoder for erasure channels operates by exchanging messages
containing sets of possible values. Accordingly, density evolution tracks the
probability mass functions of the set cardinalities. The equations governing
the mapping of those probability mass functions are derived and calculated for
variable and constraint nodes, and decoding thresholds are computed for long
SUDOKU codes with random interleavers.</abstract><doi>10.48550/arxiv.1407.4328</doi><oa>free_for_read</oa></addata></record> |
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subjects | Computer Science - Information Theory Mathematics - Information Theory |
title | Density Evolution for SUDOKU Codes on the Erasure Channel |
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