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Author: search.filters.author.Buajong, ChaiwatSubject: search.filters.subject.intertrack interference (ITI)

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    Deep Neural Network Detection With an ITI Subtraction for Non-Uniform Track-Width Two-Dimensional Magnetic Recording
    (2024-04-01)
    Buajong, Chaiwat
    ;
    Lee, Jaejin
    ;
    Warisarn, Chanon
    Continuously expanding the magnetic recording density results in unavoidable interferences including intersymbol interference (ISI) and intertrack interference (ITI) that both critically degrade the system performance. Even with advanced signal processing tools, two-dimensional magnetic recording (TDMR) still struggles to provide satisfactory performance. Thus, this article proposes the deep neural network (DNN)-based detection deployed in conjunction with an equalizer for the TDMR system. The coding scheme uses a low-density parity-check (LDPC) code, enabling the information exchange or the turbo decoding. The retrieval of data occurs within a group of three adjacent tracks. We also explore two different track configurations: uniform and non-uniform tracks that involve doubling the width of the middle track among the three adjacent tracks. The utilization of the highly reliable signal obtained from the double-width track enables the application of ITI subtraction technique, enhancing the information exchange. This technique can mitigate the ITI effect by subtracting the target signal with the imitated ITI signal. In addition, we investigate two different DNN architectures including the multilayer perceptron (MLP) and convolutional neural network (CNN), along with two scenarios for the detections in different passes of turbo decoding. The simulation results conducted on the Voronoi media model, with realistic grains and non-magnetic grain boundaries, show that the proposed detection systems with the non-uniform track configuration offer a performance gain up to 5.3 dB over the system with the uniform track configuration. Moreover, iteration for the turbo decoding passes incrementally improves the system performance in the proposed systems with the non-uniform track while the systems with the uniform track no longer provide performance gain as the number of iterations goes on.
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    Multilayer Perceptron-based Detector for a Coded Two-Dimensional Magnetic Recording
    (2022-01-01)
    Buajong, Chaiwat
    ;
    Warisam, Chanon
    Recently, magnetic recording technology is on the verge of reaching its recording density limit. Two-dimensional (2- D) magnetic recording (TDMR) becomes a candidate for next- generation magnetic recording because of its compatibility with the current technology and powerful 2-D signal processing tools. However, the degradation in signal quality due to 2-D interference is inevitable. In this paper, we introduce the multilayer perceptron (MLP)-based detector that can produce soft-output information in the form of a log-likelihood ratio (LLR). Such a detector can also execute turbo decoding by exchanging information with a low- density parity-check (LDPC) code. The simulation result shows that the proposed system outperforms the systems that use the conventional detector based on the Viterbi algorithm.