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    Mutual Soft-Information Improvement Techniques for Lower Layer Performance Improvement in Double-Layered Magnetic Recording Systems
    (2025-01-01)
    Khametong, Anawin
    ;
    Greaves, Simon John
    ;
    Warisarn, Chanon
    Double-layer magnetic recording (DLMR) development aims to increase areal density (AD) by stacking multiple recording layers on the same platter. This has the potential to revolutionize magnetic recording. On the other hand, bit-patterned magnetic recording (BPMR) uses nanoscale bit islands to enhance storage density, reduce transition noise, and maintain thermal stability. This study focuses on combining BPMR and DLMR to further increase AD. Unfortunately, this approach encounters difficulties in separating data from different layers within a single readback signal, which results in poor performance. Retrieving data from the lower layer is additionally complicated by its distance from the reader, leading to degraded bit-error-rate (BER) performance. To address this, we have developed mutual soft-information improvement techniques (MIITs) such as the maximum soft-information (MSI) and sum soft-information (SSI) schemes. These techniques enhance the soft-information output obtained from a soft-output Viterbi algorithm (SOVA) detector. Additionally, we propose three iterative systems that exchange soft information between SOVA and low-density parity-check (LDPC) codes. Our demonstrations show improved BER performance for both upper and lower layers, compared to conventional systems with single-layer media at the same AD of 4 Tb/in<sup>2</sup>
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    An MLP-based skew angle mitigation method for bit-patterned magnetic recording
    (2024-06-01)
    Koonkarnkhai, Santi
    ;
    Kankhunthod, Kittipon
    ;
    Kovintavewat, Piya
    Skew angle (SA) is one of the crucial problems in a bit-patterned magnetic recording (BPMR) system. Practically, during the read process, the read head may be tilted up to 30 degrees (<sup>◦</sup>) away from the target track. Without the SA detection and correction mechanism, the performance of the BPMR system will be unbearable. This paper proposes a SA mitigation strategy for a BPMR system based on a multilayer perceptron (MLP) so as to estimate and rectify the SA. Specifically, the MLP-based SA estimator extracts the SA amount directly from the readback signal, which will then be used in the MLP-based detector to produce the estimated recording bits. Simulation results show that the proposed method can estimate the SA embedded in the readback signal more precisely than the conventional one, which just uses a look-up table to detect the SA from the target coefficients. Particularly, for the system operating at an areal density (AD) of 3 terabits per square inch with SA = 15<sup>◦</sup> and 30<sup>◦</sup>, the suggested system performs better than the system without the SA mitigation method.
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    Magnetic Recording Reliability Evaluation
    (2022-01-01)
    Phonyiam, Ekkaphon
    ;
    Netisopakul, Ponrudee
    Magnetic recording heads in Hard Disk Drive (HDD) integrates of two main components included of writer and reader devices for injecting and reading the pattern on recording media. Both features were fabricated in a single piece and become a multi-layer structure. Reliability test for magnetic recording head has become a challenge that could introduce complex problems when failure occurred. This paper aims to conceptualize testing workflow and measurement for magnetic recording head reliability evaluation. The testing process lets head performing cycles of writing and reading operations in designated ambient until it meets stopping criteria. And the reliability analysis procedure focuses on lifetime analysis with Weibull distribution on different failure modes and characters extracting from time-series bit-error-rate profile which was obtained from reliability test.
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    A simple parity check matrix LDPC code for perpendicular magnetic recording channels
    (2013-09-02)
    Timakul, Sekson
    ;
    Choochuay, Somsak
    In LDPC code design, the structure of code's parity check matrix can be very crucial to code performance. In this paper, we have investigated a simple designed parity check matrix when the code is applied to a PMR channel of a storage system. Belief propagation algorithm and min-sum algorithm are two major decoding algorithms used to benchmarked the code's merits. Additive white Gaussian noise channel (AWGN) and perpendicular magnetic recording (PMR) channel with SISO equalizer in PR2 target are the conditions of our investigation. The LDPC code itself is a modified array type. Its construction fairly simple compared to normal array and quasi-cyclic code. We used two decision variables to define the permutation matrix. A method proposed by Tanner's et.al had been adapted to the modified array code. The decoders have been tested for 5 and 20. iterations. SNR versus BER and BLER were measured. © 2013 IEEE.