Kankhunthod, Kittipon

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Kankhunthod, Kittipon
Alternative Name
Kankhunthod, K.
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Email
kittipon.ka@kmitl.ac.th

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    Item type:Publication,
    Multilayer Perceptron-Based Soft-Information Modification Technique for Double-Layer Bit-Patterned Magnetic Recording Systems
    (2024-01-01)
    Sawangarom, Visawa
    ;
    Kankhunthod, Kittipon
    ;
    Warisarn, Chanon
    The growing demand for data storage necessitates continuous improvements in hard disk drive (HDD) technologies. Double-layer magnetic recording (DLMR) and bit-patterned magnetic recording (BPMR) technologies are pivotal in enhancing areal density (AD), but they also introduce challenges such as inter-layer interference (ILl) and two-dimensional (2D) inter-ference. This study addresses these challenges by integrating a multilayer perceptron (MLP)-based soft-information modifier into the double-layer BPMR system. The proposed method optimizes the log-likelihood ratio sequence for the recorded tracks on the second recording layer, which are more prone to interference compared with the first recording layer. Our simulations demonstrate significant improvements in bit-error-rate performance across varying levels of media noise and track misregistration. The results also indicate that the MLP-based approach effectively mitigates the adverse effects of interference, thereby enhancing the reliability of data retrieval in high-AD HDD systems.
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    Item type:Publication,
    A Multilayer-Perceptron based Method for Track Misregistration Mitigation in Dual-reader/Two-track Reading BPMR Systems
    (2022-01-01)
    Kankhunthod, Kittipon
    ;
    Lee, Jaejin
    ;
    Warisarn, Chanon
    Bit-patterned magnetic recording (BPMR) is the future hard disk drive technology that is expected to gain an areal density of over 4.0 Terabit-per-square-inch (Tbits/in2). However, one of the serious problems is track misregistration (TMR), which easily degrade the overall system's performance. To ensure that the system's performance is acceptable; therefore, we present the TMR mitigation method on a dual-reader/two-track reading (DRTR) BPMR system using an artificial neural network (ANN) model and deep learning technique. To estimate TMR levels, the equalized readback signals are directly fed into a proposed TMR estimator that is performed based on a multilayer perceptron (MLP). In the TMR correction process, both the estimated TMR and equalized readback signals are fed to the MLP detector to detect recorded data bits. The simulation results reveal that the utilization of our proposed TMR mitigation method can improve the bit-error-rate performance of the BPMR system when they were compared with the system that uses another mitigation method.
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    Item type:Publication,
    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.