Nanoscale bit-patterned media for next generation magnetic data storage applications

Author(s):  
Dmitri Litvinov ◽  
Vishal Parekh ◽  
E. Chunsheng ◽  
Darren Smith ◽  
James Rantschler ◽  
...  
2020 ◽  
Vol 10 (24) ◽  
pp. 8819
Author(s):  
Seongkwon Jeong ◽  
Jaejin Lee

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.


2008 ◽  
Vol 3 (2) ◽  
pp. 93-112 ◽  
Author(s):  
Dmitri Litvinov ◽  
Vishal Parekh ◽  
E Chunsheng ◽  
Darren Smith ◽  
James Rantschler ◽  
...  

2006 ◽  
Vol 13 (2) ◽  
pp. 189-196 ◽  
Author(s):  
B. D. Terris ◽  
T. Thomson ◽  
G. Hu

2022 ◽  
Vol 12 (2) ◽  
pp. 620
Author(s):  
Seongkwon Jeong ◽  
Jaejin Lee

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.


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