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

被引：2
|
作者：
Nishikawa, Madoka [1 ]
Nakamura, Yasuaki [1 ]
Kanai, Yasushi [2 ]
Okamoto, Yoshihiro [1 ]
机构：
[1] Ehime Univ, Grad Sch Sci & Engn, Matsuyama, Ehime 7908577, Japan
[2] Niigata Inst Technol, Dept Engn, Niigata 9451195, Japan
来源：
IEEE TRANSACTIONS ON MAGNETICS | 2023年 / 59卷 / 11期
基金：
日本学术振兴会;
关键词：
Iterative decoding; low-density parity-check (LDPC) code; neural network (NN); shingled magnetic recording (SMR);
D O I：
10.1109/TMAG.2023.3278377
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
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 ultrahigh-density hard disk drives (HDD). In addition, we have proposed the application of the neural network (NN) to improve decoding performance and realize the automation of iterative decoding. In this study, we apply an NN to accelerate iterative decoding in the sum-product (SP) decoder. As the result, the SP decoder with the NN realized "no errors" at the fewest times of the iterative decoding compared to our previous studies.
引用
收藏
页数：5
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