Abstract

As conventional data storage systems are faced with critical problems such as the superparamagnetic limit, bit-patterned media recording (BPMR) has received significant attention as a promising next-generation magnetic data storage system. However, the reduced spacing between islands at increased areal density causes severe intersymbol and intertrack interference, which degrade BPMR system performance. In this study, we introduce a soft-output detector using multi-layer perceptron to predict reliable information. A received signal is equalized and detected by the MLP detector. The MLP detector provides a well-estimated value by using the binary-cross entropy function as a loss function and the identity function as an activation function for the output layer of the MLP detector. This study investigates the received probability distributions out of the detectors and compares the performance of various versions against a conventional detector. Compared with the conventional detection, the proposed MLP detectors provide a small variance and better BER performance than the conventional detection. Simulations of MLP designs show an advantage over conventional detection. Moreover, the proposed MLP detectors with the demodulator exhibit better BER performance than the conventional detector with the demodulator.

Highlights

  • To match data growth, the capacity of hard disk drives (HDDs) is required to increase.shrinking the magnetic grains further and cramming them closer to increase the capacity of the HDD results in the superparamagnetic effects [1]

  • To compare the bit error ratio (BER) performance depending on the detection schemes, we utilize a conventional detection technique based on partial response maximum likelihood (PRML).onAthe detector employed in data

  • Performance depending detection schemes, we utilize a storage systems consists of an equalizer and a channel decoder to mitigate this conventional detection technique based on PRML

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Summary

Introduction

The capacity of hard disk drives (HDDs) is required to increase. As ITI is generally more severe than ISI in a BPMR system, modulation coding schemes have been proposed to prevent the occurrence of cross-track patterns such as [−1, +1, −1]T and [+1, −1, +1]T [7,8]. In [10], a detection scheme with a track misregistration (TMR) estimator based on multi-layer perceptrons (MLPs) was proposed for BPMR systems. TMR by the MLP-based TMR estimator helps the MLP-based data detector to detect the received signal, the proposed scheme exhibits a better bit error ratio (BER) performance than a conventional partial response maximum likelihood (PRML) detector. We introduce a soft-output detector using multi-layer perceptron for a BPMR system to predict reliable information.

BPMR Channel Model
Proposed
Discussion
The of MLP detectors can reduce the overand
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