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Reed-Solomon Coding Algorithms Based on Reed-Muller Transform for Any Number of Parities
Based on the Reed-Muller (RM) transform, this paper proposes a Reed-Solomon (RS) encoding/erasure decoding algorithm for any number of parities. Specifically, we first generalize the previous RM-based syndrome calculation, which allows only up to seven parities, to support any number of parities. Th...
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Published in: | IEEE transactions on computers 2023-09, Vol.72 (9), p.2677-2688 |
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description | Based on the Reed-Muller (RM) transform, this paper proposes a Reed-Solomon (RS) encoding/erasure decoding algorithm for any number of parities. Specifically, we first generalize the previous RM-based syndrome calculation, which allows only up to seven parities, to support any number of parities. Then we propose a general encoding/erasure decoding algorithm. The proposed encoding algorithm eliminates the operations in solving linear equations, and this improves the computational efficiency of existing RM-based RS algorithms. In terms of erasure decoding, this paper employs the generalized RM-based syndrome calculation and lower-upper (LU) decomposition to accelerate the computational efficiency. Analysis shows that the proposed encoding/erasure decoding algorithm approaches the complexity of \lfloor \lg T \rfloor + 1 ⌊lgT⌋+1 XORs per data bit with N N increasing, where T T and N N denote the number of parities and codeword length respectively. To highlight the advantage of the proposed RM-based algorithms, the implementations with Single Instruction Multiple Data (SIMD) technology are provided. Simulation results show that the proposed algorithms are competitive, as compared with other cutting-edge implementations. |
doi_str_mv | 10.1109/TC.2023.3262922 |
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Specifically, we first generalize the previous RM-based syndrome calculation, which allows only up to seven parities, to support any number of parities. Then we propose a general encoding/erasure decoding algorithm. The proposed encoding algorithm eliminates the operations in solving linear equations, and this improves the computational efficiency of existing RM-based RS algorithms. In terms of erasure decoding, this paper employs the generalized RM-based syndrome calculation and lower-upper (LU) decomposition to accelerate the computational efficiency. Analysis shows that the proposed encoding/erasure decoding algorithm approaches the complexity of <inline-formula><tex-math notation="LaTeX">\lfloor \lg T \rfloor + 1</tex-math> <mml:math><mml:mrow><mml:mo>⌊</mml:mo><mml:mo form="prefix">lg</mml:mo><mml:mi>T</mml:mi><mml:mo>⌋</mml:mo><mml:mo>+</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:math><inline-graphic xlink:href="yu-ieq1-3262922.gif"/> </inline-formula> XORs per data bit with <inline-formula><tex-math notation="LaTeX">N</tex-math> <mml:math><mml:mi>N</mml:mi></mml:math><inline-graphic xlink:href="yu-ieq2-3262922.gif"/> </inline-formula> increasing, where <inline-formula><tex-math notation="LaTeX">T</tex-math> <mml:math><mml:mi>T</mml:mi></mml:math><inline-graphic xlink:href="yu-ieq3-3262922.gif"/> </inline-formula> and <inline-formula><tex-math notation="LaTeX">N</tex-math> <mml:math><mml:mi>N</mml:mi></mml:math><inline-graphic xlink:href="yu-ieq4-3262922.gif"/> </inline-formula> denote the number of parities and codeword length respectively. To highlight the advantage of the proposed RM-based algorithms, the implementations with Single Instruction Multiple Data (SIMD) technology are provided. Simulation results show that the proposed algorithms are competitive, as compared with other cutting-edge implementations.]]></description><identifier>ISSN: 0018-9340</identifier><identifier>EISSN: 1557-9956</identifier><identifier>DOI: 10.1109/TC.2023.3262922</identifier><identifier>CODEN: ITCOB4</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Algorithms ; Codes ; Coding ; computational complexity ; Computational efficiency ; Computing time ; Decoding ; Encoding ; Galois fields ; Linear equations ; Mathematical analysis ; Mathematical models ; Matrix decomposition ; Reed-Muller transform ; Reed-Solomon code ; storage erasure codes ; Transforms ; Vandermonde matrix</subject><ispartof>IEEE transactions on computers, 2023-09, Vol.72 (9), p.2677-2688</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2023</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c290t-6459b3f475deb4e5927892cd7fd97afc7625d1b3561924a1be161bbef44846c73</citedby><cites>FETCH-LOGICAL-c290t-6459b3f475deb4e5927892cd7fd97afc7625d1b3561924a1be161bbef44846c73</cites><orcidid>0000-0003-3528-5483 ; 0000-0002-6309-2876 ; 0000-0001-7328-9341 ; 0000-0001-8861-2535</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/10086680$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,54796</link.rule.ids></links><search><creatorcontrib>Yu, Leilei</creatorcontrib><creatorcontrib>Lin, Sian-Jheng</creatorcontrib><creatorcontrib>Hou, Hanxu</creatorcontrib><creatorcontrib>Li, Zhengrui</creatorcontrib><title>Reed-Solomon Coding Algorithms Based on Reed-Muller Transform for Any Number of Parities</title><title>IEEE transactions on computers</title><addtitle>TC</addtitle><description><![CDATA[Based on the Reed-Muller (RM) transform, this paper proposes a Reed-Solomon (RS) encoding/erasure decoding algorithm for any number of parities. Specifically, we first generalize the previous RM-based syndrome calculation, which allows only up to seven parities, to support any number of parities. Then we propose a general encoding/erasure decoding algorithm. The proposed encoding algorithm eliminates the operations in solving linear equations, and this improves the computational efficiency of existing RM-based RS algorithms. In terms of erasure decoding, this paper employs the generalized RM-based syndrome calculation and lower-upper (LU) decomposition to accelerate the computational efficiency. Analysis shows that the proposed encoding/erasure decoding algorithm approaches the complexity of <inline-formula><tex-math notation="LaTeX">\lfloor \lg T \rfloor + 1</tex-math> <mml:math><mml:mrow><mml:mo>⌊</mml:mo><mml:mo form="prefix">lg</mml:mo><mml:mi>T</mml:mi><mml:mo>⌋</mml:mo><mml:mo>+</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:math><inline-graphic xlink:href="yu-ieq1-3262922.gif"/> </inline-formula> XORs per data bit with <inline-formula><tex-math notation="LaTeX">N</tex-math> <mml:math><mml:mi>N</mml:mi></mml:math><inline-graphic xlink:href="yu-ieq2-3262922.gif"/> </inline-formula> increasing, where <inline-formula><tex-math notation="LaTeX">T</tex-math> <mml:math><mml:mi>T</mml:mi></mml:math><inline-graphic xlink:href="yu-ieq3-3262922.gif"/> </inline-formula> and <inline-formula><tex-math notation="LaTeX">N</tex-math> <mml:math><mml:mi>N</mml:mi></mml:math><inline-graphic xlink:href="yu-ieq4-3262922.gif"/> </inline-formula> denote the number of parities and codeword length respectively. To highlight the advantage of the proposed RM-based algorithms, the implementations with Single Instruction Multiple Data (SIMD) technology are provided. Simulation results show that the proposed algorithms are competitive, as compared with other cutting-edge implementations.]]></description><subject>Algorithms</subject><subject>Codes</subject><subject>Coding</subject><subject>computational complexity</subject><subject>Computational efficiency</subject><subject>Computing time</subject><subject>Decoding</subject><subject>Encoding</subject><subject>Galois fields</subject><subject>Linear equations</subject><subject>Mathematical analysis</subject><subject>Mathematical models</subject><subject>Matrix decomposition</subject><subject>Reed-Muller transform</subject><subject>Reed-Solomon code</subject><subject>storage erasure codes</subject><subject>Transforms</subject><subject>Vandermonde matrix</subject><issn>0018-9340</issn><issn>1557-9956</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNpNkDtPwzAURi0EEqUwszBYYk65fsdjiXhJ5SEIEpuVh11SJXGxm6H_npR2YLl3-M53r3QQuiQwIwT0TZ7NKFA2Y1RSTekRmhAhVKK1kMdoAkDSRDMOp-gsxhUASAp6gr7era2TD9_6zvc483XTL_G8XfrQbL67iG-LaGs8Rn_c89C2NuA8FH10PnR4HHjeb_HL0JVj4B1-K8ZmY-M5OnFFG-3FYU_R5_1dnj0mi9eHp2y-SCqqYZNILnTJHFeitiW3QlOValrVytVaFa5SkoqalExIoikvSGmJJGVpHecpl5ViU3S9v7sO_mewcWNWfgj9-NLQlCstGSg9Ujd7qgo-xmCdWYemK8LWEDA7fSbPzE6fOegbG1f7RmOt_UdDKmUK7BfK2Gpm</recordid><startdate>20230901</startdate><enddate>20230901</enddate><creator>Yu, Leilei</creator><creator>Lin, Sian-Jheng</creator><creator>Hou, Hanxu</creator><creator>Li, Zhengrui</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0003-3528-5483</orcidid><orcidid>https://orcid.org/0000-0002-6309-2876</orcidid><orcidid>https://orcid.org/0000-0001-7328-9341</orcidid><orcidid>https://orcid.org/0000-0001-8861-2535</orcidid></search><sort><creationdate>20230901</creationdate><title>Reed-Solomon Coding Algorithms Based on Reed-Muller Transform for Any Number of Parities</title><author>Yu, Leilei ; Lin, Sian-Jheng ; Hou, Hanxu ; Li, Zhengrui</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c290t-6459b3f475deb4e5927892cd7fd97afc7625d1b3561924a1be161bbef44846c73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Algorithms</topic><topic>Codes</topic><topic>Coding</topic><topic>computational complexity</topic><topic>Computational efficiency</topic><topic>Computing time</topic><topic>Decoding</topic><topic>Encoding</topic><topic>Galois fields</topic><topic>Linear equations</topic><topic>Mathematical analysis</topic><topic>Mathematical models</topic><topic>Matrix decomposition</topic><topic>Reed-Muller transform</topic><topic>Reed-Solomon code</topic><topic>storage erasure codes</topic><topic>Transforms</topic><topic>Vandermonde matrix</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yu, Leilei</creatorcontrib><creatorcontrib>Lin, Sian-Jheng</creatorcontrib><creatorcontrib>Hou, Hanxu</creatorcontrib><creatorcontrib>Li, Zhengrui</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Xplore</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>IEEE transactions on computers</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yu, Leilei</au><au>Lin, Sian-Jheng</au><au>Hou, Hanxu</au><au>Li, Zhengrui</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Reed-Solomon Coding Algorithms Based on Reed-Muller Transform for Any Number of Parities</atitle><jtitle>IEEE transactions on computers</jtitle><stitle>TC</stitle><date>2023-09-01</date><risdate>2023</risdate><volume>72</volume><issue>9</issue><spage>2677</spage><epage>2688</epage><pages>2677-2688</pages><issn>0018-9340</issn><eissn>1557-9956</eissn><coden>ITCOB4</coden><abstract><![CDATA[Based on the Reed-Muller (RM) transform, this paper proposes a Reed-Solomon (RS) encoding/erasure decoding algorithm for any number of parities. Specifically, we first generalize the previous RM-based syndrome calculation, which allows only up to seven parities, to support any number of parities. Then we propose a general encoding/erasure decoding algorithm. The proposed encoding algorithm eliminates the operations in solving linear equations, and this improves the computational efficiency of existing RM-based RS algorithms. In terms of erasure decoding, this paper employs the generalized RM-based syndrome calculation and lower-upper (LU) decomposition to accelerate the computational efficiency. Analysis shows that the proposed encoding/erasure decoding algorithm approaches the complexity of <inline-formula><tex-math notation="LaTeX">\lfloor \lg T \rfloor + 1</tex-math> <mml:math><mml:mrow><mml:mo>⌊</mml:mo><mml:mo form="prefix">lg</mml:mo><mml:mi>T</mml:mi><mml:mo>⌋</mml:mo><mml:mo>+</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:math><inline-graphic xlink:href="yu-ieq1-3262922.gif"/> </inline-formula> XORs per data bit with <inline-formula><tex-math notation="LaTeX">N</tex-math> <mml:math><mml:mi>N</mml:mi></mml:math><inline-graphic xlink:href="yu-ieq2-3262922.gif"/> </inline-formula> increasing, where <inline-formula><tex-math notation="LaTeX">T</tex-math> <mml:math><mml:mi>T</mml:mi></mml:math><inline-graphic xlink:href="yu-ieq3-3262922.gif"/> </inline-formula> and <inline-formula><tex-math notation="LaTeX">N</tex-math> <mml:math><mml:mi>N</mml:mi></mml:math><inline-graphic xlink:href="yu-ieq4-3262922.gif"/> </inline-formula> denote the number of parities and codeword length respectively. To highlight the advantage of the proposed RM-based algorithms, the implementations with Single Instruction Multiple Data (SIMD) technology are provided. Simulation results show that the proposed algorithms are competitive, as compared with other cutting-edge implementations.]]></abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TC.2023.3262922</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0003-3528-5483</orcidid><orcidid>https://orcid.org/0000-0002-6309-2876</orcidid><orcidid>https://orcid.org/0000-0001-7328-9341</orcidid><orcidid>https://orcid.org/0000-0001-8861-2535</orcidid></addata></record> |
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subjects | Algorithms Codes Coding computational complexity Computational efficiency Computing time Decoding Encoding Galois fields Linear equations Mathematical analysis Mathematical models Matrix decomposition Reed-Muller transform Reed-Solomon code storage erasure codes Transforms Vandermonde matrix |
title | Reed-Solomon Coding Algorithms Based on Reed-Muller Transform for Any Number of Parities |
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