scholarly journals Effective Generalized Partial Response Target and Serial Detector for Two-Dimensional Bit-Patterned Media Recording Channel Including Track Mis-Registration

2020 ◽  
Vol 10 (17) ◽  
pp. 5738 ◽  
Author(s):  
Thien An Nguyen ◽  
Jaejin Lee
Keyword(s):  
Partial Response ◽  
Data Storage ◽  
High Density ◽  
Cloud Services ◽  
Two Dimensional ◽  
Magnetic Islands ◽  
Bit Patterned Media ◽  
Increasing Demand ◽  
Cross Track ◽  
Response Target

With the development of 5G technology, programs are gradually moving to cloud services. This leads to an increasing demand for storage. In the field of high-density data storage, bit-pattern media recording (BPMR) is considered a promising approach, as it can expand the data density to 4 Tb/in2. However, in high-density BPMR, bits or magnetic islands are very close to each other, leading to significant intertrack interference (ITI) from the cross-track direction and intersymbol interference (ISI) from the down-track direction. To minimize two-dimensional interference, including ITI and ISI, the serial detector method has been highly effective. However, in this method, the signal at the output of the first decoder is still a hard output. Therefore, we suggest methods to convert the output of the first detector into a soft output. Additionally, we have developed a new form of generalized partial response target to overcome the track mis-registration. The results show that our proposed methods apparently improve bit error rate performance.

scholarly journals Serial Detection with Neural Network-Based Noise Prediction for Bit-Patterned Media Recording Systems

2021 ◽  
Vol 11 (10) ◽  
pp. 4387
Author(s):  
Thien An Nguyen ◽  
Jaejin Lee
Keyword(s):  
Neural Network ◽  
Data Storage ◽  
Detection Algorithm ◽  
Noise Signal ◽  
High Density ◽  
Noise Prediction ◽  
Magnetic Islands ◽  
Bit Patterned Media ◽  
Proposed Model ◽  
Cross Track

Ultra-high density data storage has gained high significance given the increasing amounts of data; many technologies have been proposed to achieve a high density. Among them, bit-pattern media recording (BPMR) is a promising technology. In BPMR systems, data are stored on magnetic islands. Therefore, high densities can be achieved by reducing the distance between the magnetic islands. Because of the closeness between the magnetic islands, the readback signal is distorted by two-dimensional (2D) interference, which includes the intersymbol interference according to the down-track direction and the intertrack interference according to the cross-track direction. A simple and effective serial detection algorithm was recently proposed to mitigate the 2D interference. However, serial detection utilizes the hard output in inner detection, and this degrades the serial detection performance. To resolve this problem, a subsequent study used feedback to estimate the noise and used this noise signal to create a soft output for inner detection. Following up, in this paper we propose a model that utilizes a neural network for noise prediction. The proposed neural network-based model and the model with the feedback line were compared in terms of bit error rate (BER). The results show that the proposed model achieves a gain of approximately 1 dB at a BER of 10−6.

scholarly journals Target and Equalizer Design for High-Density Bit-Patterned Media Recording

1970 ◽  
Vol 6 (2) ◽  
pp. 128-135
Author(s):  
Santi Koonkarnkhai ◽  
Phongsak Keeratiwintakorn ◽  
Piya Kovintavewat
Keyword(s):  
Partial Response ◽  
Mean Squared Error ◽  
Bit Patterned Media ◽  
Patterned Media ◽  
Media Noise ◽  
Minimum Mean Squared Error ◽  
Squared Error ◽  
Cross Track ◽  
Partial Response Maximum Likelihood ◽  
Better Than

In bit-patterned media recording (BPMR) channels, the inter-track interference (ITI) is extremely severe at ultra high areal densities, which significantly degrades the system performance. The partial-response maximum-likelihood (PRML) technique that uses an one-dimensional (1D) partial response target might not be able to cope with this severe ITI, especially in the presence of media noise and track mis-registration (TMR). This paper describes the target and equalizer design for highdensity BPMR channels. Specifically, we proposes a two-dimensional (2D) cross-track asymmetric target, based on a minimum mean-squared error (MMSE) approach, to combat media noise and TMR. Results indicate that the proposed 2D target performs better than the previously proposed 2D targets, especially when media noise and TMR is severe.

Intrinsic multiferroicity in two-dimensional VOCl2 monolayers

Nanoscale ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 1103-1110 ◽  
Author(s):  
Haoqiang Ai ◽  
Xiaohan Song ◽  
Siyun Qi ◽  
Weifeng Li ◽  
Mingwen Zhao
Keyword(s):  
Data Storage ◽  
Bulk Material ◽  
High Density ◽  
Two Dimensional

The coexistence of ferroelectricity and magnetism in VOCl2 monolayer which is mechanically strippable from the bulk material offers a tantalizing potential for high-density multistate data storage.

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