Enhancing Log-Likelihood Ratios with Mutual Information on Three-Reader One-Track Detection in Staggered BPMR Systems

Because so much information is currently being shared online, there has been a sharp rise in the need for data storage devices over the past ten years. The main storage option is the hard disk drive (HDD), which is less expensive than some other types of data storage. Physical constraints, such as the superparamagnetic limit, are difficult to overcome using existing HDD technology. Consequently, bit-patterned magnetic recording (BPMR) has emerged as a potential solution, offering higher areal densities whilst maintaining thermal stability. Nevertheless, BPMR poses new challenges, such as inter-symbol interference and inter-track interference. Consequently, a number of approaches, such as staggered island layouts and array-reader magnetic recording, have been proposed to overcome these issues. However, this article proposes a three-reader one-track detection method to enhance data retrieval in a staggered BPMR system. Leveraging three-track reading for one-track detection, we obtain three readback signals that function as mutual data sequences. This substantially enhances the detection process in one-dimensional partial-response maximum-likelihood channels. Next, using these mutual data sequences, four novel techniques are presented to enhance bit-error rate (BER) performance and detection accuracy: hard-information flipping, maximum soft-information finding, bit-summation detection, and multilayer perceptron (MLP). This study shows that these proposed techniques can provide better BER performance compared with conventional methods and that the MLP is the most effective technique in enhancing system performance.

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Publication Details

Journal
Applied Sciences
Published
2025-02-21
DOI
https://doi.org/10.3390/app15052329
Citations
1
Primary Topic
Blind Source Separation Techniques
Type
article
Field-Weighted Citation Impact
1.49

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article

Enhancing Log-Likelihood Ratios with Mutual Information on Three-Reader One-Track Detection in Staggered BPMR Systems

Santi Koonkarnkhai, Natthakan Rueangnetr, Piya Kovintavewat, Simon John Greaves et al.
1 citations
Applied Sciences
Blind Source Separation Techniques
1.49
article

Enhancing Log-Likelihood Ratios with Mutual Information on Three-Reader One-Track Detection in Staggered BPMR Systems

Santi Koonkarnkhai, Natthakan Rueangnetr, Piya Kovintavewat, Simon John Greaves, Chanon Warisarn
article en
1 citations

Abstract

Because so much information is currently being shared online, there has been a sharp rise in the need for data storage devices over the past ten years. The main storage option is the hard disk drive (HDD), which is less expensive than some other types of data storage. Physical constraints, such as the superparamagnetic limit, are difficult to overcome using existing HDD technology. Consequently, bit-patterned magnetic recording (BPMR) has emerged as a potential solution, offering higher areal densities whilst maintaining thermal stability. Nevertheless, BPMR poses new challenges, such as inter-symbol interference and inter-track interference. Consequently, a number of approaches, such as staggered island layouts and array-reader magnetic recording, have been proposed to overcome these issues. However, this article proposes a three-reader one-track detection method to enhance data retrieval in a staggered BPMR system. Leveraging three-track reading for one-track detection, we obtain three readback signals that function as mutual data sequences. This substantially enhances the detection process in one-dimensional partial-response maximum-likelihood channels. Next, using these mutual data sequences, four novel techniques are presented to enhance bit-error rate (BER) performance and detection accuracy: hard-information flipping, maximum soft-information finding, bit-summation detection, and multilayer perceptron (MLP). This study shows that these proposed techniques can provide better BER performance compared with conventional methods and that the MLP is the most effective technique in enhancing system performance.

Applied SciencesVol. 15(5)
Tohoku University (JP), Nakhon Pathom Rajabhat University (TH), King Mongkut's Institute of Technology Ladkrabang (TH)
King Mongkut's Institute of Technology Ladkrabang
Openalex Percentile: Top 23%
Blind Source Separation Techniques
1.49
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