In a bit-patterned media recording (BPMR) system, reducing the spacing between adjacent bit islands in the down- and cross-track directions increases areal density; however, two-dimensional (2-D) interference comprising intersymbol and intertrack interferences degrades the system performance. To mitigate error patterns that increase the 2-D interference in BPMRs, 2-D modulation coding schemes have been proposed. In this letter, we present a modulation code and its decoding using a multilayer perceptron (MLP) for BPMRs. Modulation decoding using an MLP can achieve significantly better performance than that using the minimum Euclidean distance which is generally used to decode received modulated data. Similarly, when comparing the system performance at the same user density, modulation decoding using an MLP at 3 Tb/in $^2$ shows better performance than an uncoded system (partial response maximum likelihood detector) at 2 Tb/in $^2$ .

Because of the exponential increase in internal and external information, we need to handle the enormous amount of data. However, there is a limit to data storage on hard disk drives because of a super-paramagnetism phenomenon which prevents the formation of a high areal density (AD). Accordingly, research about bit-patterned media recording (BPMR) that stores one bit in a single magnetic island is actively in progress. BPMR can increase stored data quantities by adjusting the distance between islands. However, inter-symbol interference and inter-track interference cause problems that degrade performance due to bit period and small track pitch, respectively. Moreover, the island pattern also affects the performance because depending on the pattern, 2-D interference is changed. In this paper, we experiment to find the case that minimizes the bit error ratio in the same AD with various distances between the islands, and compares the performance in the staggered and rectangular patterns.

Because of the physical and engineering problems of conventional magnetic data storage systems, bit-patterned media recording (BPMR) is expected to be a promising technology for extending the storage density to beyond 1 Tb /in². To increase the storage density in BPMR systems, the separation between islands in both down- and cross-track directions must be reduced; this reduction results in two-dimensional interference from neighboring symbols in those directions, which is a major performance degradation factor in BPMR. Herein, we propose an iterative signal detection scheme between a Viterbi detector and a multilayer perceptron to improve the performance of a BPMR system. In the proposed signal detection scheme, we use the modified output of a multilayer perceptron as a priori information to improve equalization and extrinsic information to decrease the effect of intertrack interference.

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.

To meet the demand for storing large amounts of data, there has been a stronger focus on increasing the recording density of a hard disk drive (HDD). While conventional HDD suffers from thermal effect and superparamagnetic limit, bit-patterned media recording (BPMR) has the potential to resolve these problems and is capable of increasing areal density beyond one terabit per square inch. To increase the areal density of BPMR, the distance between islands in both the down-and cross-track directions must be reduced. Consequently, the decreased bit period and track pitch induce more intersymbol interference and intertrack interference, which degrade the bit error rate performance. In this study, extrinsic information obtained from a multilayer perceptron equalizer is used as a priori information in a partial response maximum likelihood (PRML) detector to improve the detection performance of BPMR. The proposed detection scheme shows better performance compared to both the multilayer perceptron equalizer and conventional PRML alone. Additionally, it was found that the proposed detector provides improved performance when track misregistration occurs.

Because of the explosion in data growth, the requirement for high-density storage systems has increased. Bit-patterned media recording (BPMR) is a candidate for the next-generation magnetic recording systems, and its many advantages facilitate the achievement of recording densities of 1 Tb/in $^{2}$ and beyond. In BPMR, each information bit is represented by a magnetic island; however, due to the small spacings between the along- and across-track islands that are for the achievement of a high areal density, severe extents of the inter-symbol interference (ISI) and inter-track interference (ITI) appear. These error factors degrade the system performance of the recording system. In this paper, an iterative channel detection scheme with a low-density parity check (LDPC) product code for which the extrinsic information between the soft output Viterbi algorithm (SOVA) and the LDPC product code is used for the BPMR is proposed. For the improvement of the BPMR performance, the modified extrinsic information data are exploited.