Turbo-detection for Multilayer Magnetic Recording Using Deep Neural Network-based Equalizer and Media Noise Predictor

Amirhossein Sayyafan; Ahmed Aboutaleb; Benjamin J. Belzer; Krishnamoorthy Sivakumar; Simon Greaves

doi:10.1109/TMRC53175.2021.9605105

Turbo-detection for Multilayer Magnetic Recording Using Deep Neural Network-based Equalizer and Media Noise Predictor

Amirhossein Sayyafan, Ahmed Aboutaleb, Benjamin J. Belzer, Krishnamoorthy Sivakumar, Simon Greaves

Broadband Engineering Division

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In the hard disk drive (HDD) industry, new technologies are being developed to increase density such as two-dimensional magnetic recording (TDMR). TDMR utilizes 2D signal processing without changes to existing magnetic media to get remarkable density gains [1]. In multilayer magnetic recording (MLMR), an additional magnetic media layer is vertically stacked to a TDMR system to achieve additional density gains [2], [3]. We study deep neural network (DNN) based methods for equalization and detection for MLMR, using a realistic grain switching probability (GSP) model [4] for generating waveforms.

Original language	English
Title of host publication	32nd Magnetic Recording Conference, TMRC 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665440370
DOIs	https://doi.org/10.1109/TMRC53175.2021.9605105
Publication status	Published - 2021
Event	32nd Magnetic Recording Conference, TMRC 2021 - Virtual, Pittsburgh, United States Duration: 2021 Aug 16 → 2021 Aug 19

Publication series

Name	32nd Magnetic Recording Conference, TMRC 2021

Conference

Conference	32nd Magnetic Recording Conference, TMRC 2021
Country/Territory	United States
City	Virtual, Pittsburgh
Period	21/8/16 → 21/8/19

ASJC Scopus subject areas

Media Technology
Electronic, Optical and Magnetic Materials
Instrumentation

Access to Document

10.1109/TMRC53175.2021.9605105

Cite this

Sayyafan, A., Aboutaleb, A., Belzer, B. J., Sivakumar, K., & Greaves, S. (2021). Turbo-detection for Multilayer Magnetic Recording Using Deep Neural Network-based Equalizer and Media Noise Predictor. In 32nd Magnetic Recording Conference, TMRC 2021 (32nd Magnetic Recording Conference, TMRC 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/TMRC53175.2021.9605105

Turbo-detection for Multilayer Magnetic Recording Using Deep Neural Network-based Equalizer and Media Noise Predictor. / Sayyafan, Amirhossein; Aboutaleb, Ahmed; Belzer, Benjamin J. et al.

32nd Magnetic Recording Conference, TMRC 2021. Institute of Electrical and Electronics Engineers Inc., 2021. (32nd Magnetic Recording Conference, TMRC 2021).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Sayyafan, A, Aboutaleb, A, Belzer, BJ, Sivakumar, K & Greaves, S 2021, Turbo-detection for Multilayer Magnetic Recording Using Deep Neural Network-based Equalizer and Media Noise Predictor. in 32nd Magnetic Recording Conference, TMRC 2021. 32nd Magnetic Recording Conference, TMRC 2021, Institute of Electrical and Electronics Engineers Inc., 32nd Magnetic Recording Conference, TMRC 2021, Virtual, Pittsburgh, United States, 21/8/16. https://doi.org/10.1109/TMRC53175.2021.9605105

Sayyafan A, Aboutaleb A, Belzer BJ, Sivakumar K, Greaves S. Turbo-detection for Multilayer Magnetic Recording Using Deep Neural Network-based Equalizer and Media Noise Predictor. In 32nd Magnetic Recording Conference, TMRC 2021. Institute of Electrical and Electronics Engineers Inc. 2021. (32nd Magnetic Recording Conference, TMRC 2021). doi: 10.1109/TMRC53175.2021.9605105

@inproceedings{80ee9dd752b24078af055fe3e869287f,

title = "Turbo-detection for Multilayer Magnetic Recording Using Deep Neural Network-based Equalizer and Media Noise Predictor",

abstract = "In the hard disk drive (HDD) industry, new technologies are being developed to increase density such as two-dimensional magnetic recording (TDMR). TDMR utilizes 2D signal processing without changes to existing magnetic media to get remarkable density gains [1]. In multilayer magnetic recording (MLMR), an additional magnetic media layer is vertically stacked to a TDMR system to achieve additional density gains [2], [3]. We study deep neural network (DNN) based methods for equalization and detection for MLMR, using a realistic grain switching probability (GSP) model [4] for generating waveforms. ",

author = "Amirhossein Sayyafan and Ahmed Aboutaleb and Belzer, {Benjamin J.} and Krishnamoorthy Sivakumar and Simon Greaves",

note = "Funding Information: Benjamin J. BELZER E-mail: belzer@wsu.edu tel: +1-509-335-4970 Work funded by ASRC and by NSF grant CCF-1817083 Publisher Copyright: {\textcopyright} 2021 IEEE.; 32nd Magnetic Recording Conference, TMRC 2021 ; Conference date: 16-08-2021 Through 19-08-2021",

year = "2021",

doi = "10.1109/TMRC53175.2021.9605105",

language = "English",

series = "32nd Magnetic Recording Conference, TMRC 2021",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "32nd Magnetic Recording Conference, TMRC 2021",

}

TY - GEN

T1 - Turbo-detection for Multilayer Magnetic Recording Using Deep Neural Network-based Equalizer and Media Noise Predictor

AU - Sayyafan, Amirhossein

AU - Aboutaleb, Ahmed

AU - Belzer, Benjamin J.

AU - Sivakumar, Krishnamoorthy

AU - Greaves, Simon

PY - 2021

Y1 - 2021

N2 - In the hard disk drive (HDD) industry, new technologies are being developed to increase density such as two-dimensional magnetic recording (TDMR). TDMR utilizes 2D signal processing without changes to existing magnetic media to get remarkable density gains [1]. In multilayer magnetic recording (MLMR), an additional magnetic media layer is vertically stacked to a TDMR system to achieve additional density gains [2], [3]. We study deep neural network (DNN) based methods for equalization and detection for MLMR, using a realistic grain switching probability (GSP) model [4] for generating waveforms.

AB - In the hard disk drive (HDD) industry, new technologies are being developed to increase density such as two-dimensional magnetic recording (TDMR). TDMR utilizes 2D signal processing without changes to existing magnetic media to get remarkable density gains [1]. In multilayer magnetic recording (MLMR), an additional magnetic media layer is vertically stacked to a TDMR system to achieve additional density gains [2], [3]. We study deep neural network (DNN) based methods for equalization and detection for MLMR, using a realistic grain switching probability (GSP) model [4] for generating waveforms.

UR - http://www.scopus.com/inward/record.url?scp=85123462164&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85123462164&partnerID=8YFLogxK

U2 - 10.1109/TMRC53175.2021.9605105

DO - 10.1109/TMRC53175.2021.9605105

M3 - Conference contribution

AN - SCOPUS:85123462164

T3 - 32nd Magnetic Recording Conference, TMRC 2021

BT - 32nd Magnetic Recording Conference, TMRC 2021

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 32nd Magnetic Recording Conference, TMRC 2021

Y2 - 16 August 2021 through 19 August 2021

ER -

Turbo-detection for Multilayer Magnetic Recording Using Deep Neural Network-based Equalizer and Media Noise Predictor

Abstract

Publication series

Conference

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this