A Study on Accelerating SP decoding by Neural Network in SMR System

We have previously studied low-density parity-check (LDPC) coding and iterative decoding in the shingled magnetic recording (SMR) system as a signal processing method to realize ultra-high-density hard disk drives (HDD). In addition, we have proposed the application of the neural network to improve...

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Bibliographic Details
Published in:IEEE transactions on magnetics 2023-11, Vol.59 (11), p.1-1
Main Authors: Nishikawa, Madoka, Nakamura, Yasuaki, Kanai, Yasushi, Okamoto, Yoshihiro
Format: Article
Language:English
Subjects:
Artificial neural networks
Decoding
Disk drives
Error correcting codes
Iterative decoding
low-density parity-check (LDPC) code
Magnetic recording
Magnetism
Mathematical models
neural network
Neural networks
Shingled magnetic recording
shingled magnetic recording (SMR)
Signal to noise ratio
Target tracking
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Summary:We have previously studied low-density parity-check (LDPC) coding and iterative decoding in the shingled magnetic recording (SMR) system as a signal processing method to realize ultra-high-density hard disk drives (HDD). In addition, we have proposed the application of the neural network to improve decoding performance and realize the automation of iterative decoding. In this study, we apply a neural network to accelerate iterative decoding in the sum-product (SP) decoder. As the result, the SP decoder with the neural network realized "no errors" at the fewest times of the iterative decoding compared to our previous studies.
ISSN:0018-9464
1941-0069
DOI:10.1109/TMAG.2023.3278377