Performance Evaluation of Neuro ITI Canceller for Two-Dimensional Magnetic Recording by Shingled Magnetic Recording

• Published in: IEEE transactions on magnetics Vol. 49; no. 7; pp. 3810 - 3813
• Main Authors: Yamashita, Masato, Okamoto, Yoshihiro, Nakamura, Yasuaki, Osawa, Hisashi, Muraoka, Hiroaki
• Format: Journal Article Conference Proceeding
• Language: English
• Published: New York, NY IEEE 01.07.2013; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Bit error rate; Cross-disciplinary physics: materials science; rheology; Encoding; Exact sciences and technology; Iterative decoding; LDPC coding and iterative decoding system; Magnetic recording; Magnetism; Materials science; neuro intertrack interference canceller (neuro-ITIC); Neurons; Noise; Other topics in materials science; Physics; shingled magnetic recording (SMR); two-dimensional magnetic recording (TDMR); two-dimensional neural network equalizer (2D-NNE); shingled magnetic recording (SMR); two-dimensional neural network equalizer (2D-NNE); Neural networks; LDPC coding and iterative decoding system; neuro intertrack interference canceller (neuro-ITIC); Artificial intelligence; two-dimensional magnetic recording (TDMR); Magnetic recording; Magnetic properties
• ISSN: 0018-9464; 1941-0069
• DOI: 10.1109/TMAG.2013.2242437

A neuro intertrack interference canceller (neuro-ITIC) is proposed to diminish the influences of ITI and jitter-like medium noise for two-dimensional magnetic recording (TDMR) by shingled magnetic recording. The bit error rate (BER) performance of a low-density parity-check coding and iterative decoding system including a generalized partial response class-I channel with the neuro-ITIC is also obtained via computer simulation using a read/write channel model under TDMR specifications of 4 Tb/in , and it is compared to those for a two-dimensional neural network equalizer (2D-NNE) and an ITI canceller (ITIC) with a one-dimensional finite impulse response equalizer (1D-FIRE). It is clarified that the BER performance for the neuro-ITIC is far superior to those for the 2D-NNE and the ITIC with the 1D-FIRE.