A Unified, SNR-Aware SC-LDPC Code Design With Applications to Magnetic Recording
Spatially coupled (SC)-low-density parity-check (LDPC) codes are known to have outstanding error-correction performance and low decoding latency, which make them an excellent choice for high-density magnetic recording (MR) technologies. Whereas previous works on LDPC and SC-LDPC codes mostly take ei...
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Veröffentlicht in: | IEEE transactions on magnetics 2023-03, Vol.59 (3), p.1-9 |
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description | Spatially coupled (SC)-low-density parity-check (LDPC) codes are known to have outstanding error-correction performance and low decoding latency, which make them an excellent choice for high-density magnetic recording (MR) technologies. Whereas previous works on LDPC and SC-LDPC codes mostly take either an asymptotic or a finite-length design approach, we propose a unified framework for jointly optimizing the codes' thresholds and cycle counts to address both regimes. We focus on circulant-based (CB) SC-LDPC code family as a representative, high-performance exemplar of structured SC-LDPC codes. The framework is based on efficient traversal and pruning of the code search space, building on the fact that the performance of a CB SC-LDPC code depends on some characteristics of the code's partitioning matrix, which by itself is much smaller than the code's full parity-check matrix. We then propose an algorithm that traverses all non-equivalent partitioning matrices and outputs a list of codes, each offering an attractive point on the trade-off between asymptotic and finite-length performance. Our simulations show that our framework results in SC-LDPC codes that outperform the state-of-the-art constructions, over both additive white Gaussian noise (AWGN) and partial response (PR) channel models, and that it offers the flexibility to choose low-signal-to-noise ratio (SNR), high-SNR, or in- between SNR region considering system requirements, e.g., that of the MR device. |
doi_str_mv | 10.1109/TMAG.2022.3204923 |
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Whereas previous works on LDPC and SC-LDPC codes mostly take either an asymptotic or a finite-length design approach, we propose a unified framework for jointly optimizing the codes' thresholds and cycle counts to address both regimes. We focus on circulant-based (CB) SC-LDPC code family as a representative, high-performance exemplar of structured SC-LDPC codes. The framework is based on efficient traversal and pruning of the code search space, building on the fact that the performance of a CB SC-LDPC code depends on some characteristics of the code's partitioning matrix, which by itself is much smaller than the code's full parity-check matrix. We then propose an algorithm that traverses all non-equivalent partitioning matrices and outputs a list of codes, each offering an attractive point on the trade-off between asymptotic and finite-length performance. Our simulations show that our framework results in SC-LDPC codes that outperform the state-of-the-art constructions, over both additive white Gaussian noise (AWGN) and partial response (PR) channel models, and that it offers the flexibility to choose low-signal-to-noise ratio (SNR), high-SNR, or in- between SNR region considering system requirements, e.g., that of the MR device.</description><identifier>ISSN: 0018-9464</identifier><identifier>EISSN: 1941-0069</identifier><identifier>DOI: 10.1109/TMAG.2022.3204923</identifier><identifier>CODEN: IEMGAQ</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Algorithms ; Asymptotic properties ; Building codes ; Channel coding ; Codes ; Decoding ; Error correcting codes ; Error correction ; Low density parity check codes ; Magnetic recording ; Magnetism ; Optimization ; Parity ; Parity check codes ; partial-response (PR) channel ; Partitioning ; Performance evaluation ; Random noise ; Signal to noise ratio ; signal-to-noise ratio (SNR) ; spatially coupled (SC) low-density parity-check (LDPC) codes</subject><ispartof>IEEE transactions on magnetics, 2023-03, Vol.59 (3), p.1-9</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2023</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c245t-e861359f6ca2ed88005487c2afb93e8da32fe79ed84cd9e1d4a3dc6aea1213443</cites><orcidid>0000-0001-6369-6699 ; 0000-0003-3736-4345 ; 0000-0003-1217-692X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9878357$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9878357$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Esfahanizadeh, Homa</creatorcontrib><creatorcontrib>Ram, Eshed</creatorcontrib><creatorcontrib>Cassuto, Yuval</creatorcontrib><creatorcontrib>Dolecek, Lara</creatorcontrib><title>A Unified, SNR-Aware SC-LDPC Code Design With Applications to Magnetic Recording</title><title>IEEE transactions on magnetics</title><addtitle>TMAG</addtitle><description>Spatially coupled (SC)-low-density parity-check (LDPC) codes are known to have outstanding error-correction performance and low decoding latency, which make them an excellent choice for high-density magnetic recording (MR) technologies. Whereas previous works on LDPC and SC-LDPC codes mostly take either an asymptotic or a finite-length design approach, we propose a unified framework for jointly optimizing the codes' thresholds and cycle counts to address both regimes. We focus on circulant-based (CB) SC-LDPC code family as a representative, high-performance exemplar of structured SC-LDPC codes. The framework is based on efficient traversal and pruning of the code search space, building on the fact that the performance of a CB SC-LDPC code depends on some characteristics of the code's partitioning matrix, which by itself is much smaller than the code's full parity-check matrix. We then propose an algorithm that traverses all non-equivalent partitioning matrices and outputs a list of codes, each offering an attractive point on the trade-off between asymptotic and finite-length performance. Our simulations show that our framework results in SC-LDPC codes that outperform the state-of-the-art constructions, over both additive white Gaussian noise (AWGN) and partial response (PR) channel models, and that it offers the flexibility to choose low-signal-to-noise ratio (SNR), high-SNR, or in- between SNR region considering system requirements, e.g., that of the MR device.</description><subject>Algorithms</subject><subject>Asymptotic properties</subject><subject>Building codes</subject><subject>Channel coding</subject><subject>Codes</subject><subject>Decoding</subject><subject>Error correcting codes</subject><subject>Error correction</subject><subject>Low density parity check codes</subject><subject>Magnetic recording</subject><subject>Magnetism</subject><subject>Optimization</subject><subject>Parity</subject><subject>Parity check codes</subject><subject>partial-response (PR) channel</subject><subject>Partitioning</subject><subject>Performance evaluation</subject><subject>Random noise</subject><subject>Signal to noise ratio</subject><subject>signal-to-noise ratio (SNR)</subject><subject>spatially coupled (SC) low-density parity-check (LDPC) codes</subject><issn>0018-9464</issn><issn>1941-0069</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kF1LwzAUhoMoOKc_QLwJeGtnvtoml6XqFDYd-8DLEJPTmTHbmnSI_96ODa8OL-d5z4EHoWtKRpQSdb-cFuMRI4yNOCNCMX6CBlQJmhCSqVM0IITKRIlMnKOLGDd9FCklAzQr8Kr2lQd3hxev86T4MQHwokwmD7MSl40D_ADRr2v87rtPXLTt1lvT-aaOuGvw1Kxr6LzFc7BNcL5eX6KzymwjXB3nEK2eHpflczJ5G7-UxSSxTKRdAjKjPFVVZg0DJyUhqZC5Zab6UBykM5xVkKt-JaxTQJ0w3NnMgKGMciH4EN0e7rah-d5B7PSm2YW6f6lZnqssE4TlPUUPlA1NjAEq3Qb_ZcKvpkTvxem9OL0Xp4_i-s7NoeMB4J9XMpc8zfkfkzhneQ</recordid><startdate>20230301</startdate><enddate>20230301</enddate><creator>Esfahanizadeh, Homa</creator><creator>Ram, Eshed</creator><creator>Cassuto, Yuval</creator><creator>Dolecek, Lara</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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Whereas previous works on LDPC and SC-LDPC codes mostly take either an asymptotic or a finite-length design approach, we propose a unified framework for jointly optimizing the codes' thresholds and cycle counts to address both regimes. We focus on circulant-based (CB) SC-LDPC code family as a representative, high-performance exemplar of structured SC-LDPC codes. The framework is based on efficient traversal and pruning of the code search space, building on the fact that the performance of a CB SC-LDPC code depends on some characteristics of the code's partitioning matrix, which by itself is much smaller than the code's full parity-check matrix. We then propose an algorithm that traverses all non-equivalent partitioning matrices and outputs a list of codes, each offering an attractive point on the trade-off between asymptotic and finite-length performance. Our simulations show that our framework results in SC-LDPC codes that outperform the state-of-the-art constructions, over both additive white Gaussian noise (AWGN) and partial response (PR) channel models, and that it offers the flexibility to choose low-signal-to-noise ratio (SNR), high-SNR, or in- between SNR region considering system requirements, e.g., that of the MR device.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TMAG.2022.3204923</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0001-6369-6699</orcidid><orcidid>https://orcid.org/0000-0003-3736-4345</orcidid><orcidid>https://orcid.org/0000-0003-1217-692X</orcidid></addata></record> |
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subjects | Algorithms Asymptotic properties Building codes Channel coding Codes Decoding Error correcting codes Error correction Low density parity check codes Magnetic recording Magnetism Optimization Parity Parity check codes partial-response (PR) channel Partitioning Performance evaluation Random noise Signal to noise ratio signal-to-noise ratio (SNR) spatially coupled (SC) low-density parity-check (LDPC) codes |
title | A Unified, SNR-Aware SC-LDPC Code Design With Applications to Magnetic Recording |
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