Error Event Corrections Using List-NPML Decoding and Error Detection Codes
A List-Noise Predictive Maximum Likelihood (List-NPML) decoding algorithm based on a periodic error detection mechanism is proposed for magnetic recording systems to minimize the number of error events. The proposed detector keeps a list of candidate paths ( candidates per state of a trellis) based...
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| Veröffentlicht in: | IEEE transactions on magnetics 2013-07, Vol.49 (7), p.3775-3778 |
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| container_title | IEEE transactions on magnetics |
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| creator | Arslan, Suayb S. Jaewook Lee Goker, Turguy |
| description | A List-Noise Predictive Maximum Likelihood (List-NPML) decoding algorithm based on a periodic error detection mechanism is proposed for magnetic recording systems to minimize the number of error events. The proposed detector keeps a list of candidate paths ( candidates per state of a trellis) based on the observation that most of the error events can be recovered by finding a set of most likely paths. A periodic decision making process is utilized for every bits based on error detection codes. With this approach, a tradeoff between performance and complexity is studied with various combinations of and . The proposed structure is robust to miscorrections and time-varying error events, eliminating the need for knowing the error event distributions prior to its operation. We also introduced a novel design of parity bits that meets the run length constraints of the channel and a trellis update architecture for improved performance. Simulation results show that the proposed List-NPMLD gives us significant BER performance and post-ECC gains at the expense of some increase in complexity. |
| doi_str_mv | 10.1109/TMAG.2013.2249658 |
| format | Article |
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The proposed detector keeps a list of candidate paths ( candidates per state of a trellis) based on the observation that most of the error events can be recovered by finding a set of most likely paths. A periodic decision making process is utilized for every bits based on error detection codes. With this approach, a tradeoff between performance and complexity is studied with various combinations of and . The proposed structure is robust to miscorrections and time-varying error events, eliminating the need for knowing the error event distributions prior to its operation. We also introduced a novel design of parity bits that meets the run length constraints of the channel and a trellis update architecture for improved performance. 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The proposed detector keeps a list of candidate paths ( candidates per state of a trellis) based on the observation that most of the error events can be recovered by finding a set of most likely paths. A periodic decision making process is utilized for every bits based on error detection codes. With this approach, a tradeoff between performance and complexity is studied with various combinations of and . The proposed structure is robust to miscorrections and time-varying error events, eliminating the need for knowing the error event distributions prior to its operation. We also introduced a novel design of parity bits that meets the run length constraints of the channel and a trellis update architecture for improved performance. Simulation results show that the proposed List-NPMLD gives us significant BER performance and post-ECC gains at the expense of some increase in complexity.</description><subject>Complexity theory</subject><subject>Cross-disciplinary physics: materials science; rheology</subject><subject>Data detection</subject><subject>Error correction codes</subject><subject>error correction coding (ECC)</subject><subject>error detection</subject><subject>Exact sciences and technology</subject><subject>magnetic recording</subject><subject>Magnetism</subject><subject>Materials science</subject><subject>Maximum likelihood decoding</subject><subject>Maximum likelihood detection</subject><subject>Measurement</subject><subject>Noise</subject><subject>Other topics in materials science</subject><subject>Partial Response 4 (PR4)</subject><subject>Physics</subject><subject>Prediction algorithms</subject><issn>0018-9464</issn><issn>1941-0069</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9UEtLAzEQDqJgrf4A8bIgHrdmNu9jaWtVtuqhPYc0ycqWuluTreC_N8sWLzPMfI9hPoRuAU8AsHpcr6bLSYGBTIqCKs7kGRqBopBjzNU5GmEMMleU00t0FeMujZQBHqHXRQhtyBY_vumyWRuCt13dNjHbxLr5zMo6dvnbx6rM5t62rl-ZxmWDaO67gZ2EzsdrdFGZffQ3pz5Gm6fFevacl-_Ll9m0zC3hvMvllrECpNpSJozDQoKhmHFcCE4Yo1BJu5WOGkyskwwSooxSznMjQIFiZIzuB99DaL-PPnZ61x5Dk05qoJiK9CTQxIKBZUMbY_CVPoT6y4RfDVj3kek-Mt1Hpk-RJc3DydlEa_ZVMI2t47-wEIKwvozR3cCrvff_MGdMAZfkDxm0cWs</recordid><startdate>20130701</startdate><enddate>20130701</enddate><creator>Arslan, Suayb S.</creator><creator>Jaewook Lee</creator><creator>Goker, Turguy</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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The proposed detector keeps a list of candidate paths ( candidates per state of a trellis) based on the observation that most of the error events can be recovered by finding a set of most likely paths. A periodic decision making process is utilized for every bits based on error detection codes. With this approach, a tradeoff between performance and complexity is studied with various combinations of and . The proposed structure is robust to miscorrections and time-varying error events, eliminating the need for knowing the error event distributions prior to its operation. We also introduced a novel design of parity bits that meets the run length constraints of the channel and a trellis update architecture for improved performance. 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| source | IEEE Electronic Library (IEL) |
| subjects | Complexity theory Cross-disciplinary physics: materials science rheology Data detection Error correction codes error correction coding (ECC) error detection Exact sciences and technology magnetic recording Magnetism Materials science Maximum likelihood decoding Maximum likelihood detection Measurement Noise Other topics in materials science Partial Response 4 (PR4) Physics Prediction algorithms |
| title | Error Event Corrections Using List-NPML Decoding and Error Detection Codes |
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