A study on acceleration of SP decoder using reliability of recording sequence by neural network based on parity check result in SMR system

We study signal processing methods to realize ultra-high-density hard disk drives (HDDs). Among them, we have applied the neural network to improve decoding performance in low-density parity-check (LDPC) coding and iterative decoding in the shingled magnetic recording (SMR) system. In this study, we realize acceleration of the sum-product (SP) decoding by updating the decoding reliability of the SP decoding using the reliability of the recording sequence calculated by the neural network based on the parity check results. As a result, the proposed system achieved error-free with the fewest number of iterations in the SP decoder compared to our previous studies.