Generalized belief propagation detector for TDMR microcell model

Seyed Mehrdad Khatami, Bane V Vasic

Research output: Contribution to journalArticle

17 Citations (Scopus)

Abstract

Signal processing in TDMR encounters several challenges such as read channel modeling and detection in the presence of severe two-dimensional intersymbol interference (2-D ISI). The contribution of this paper is twofold. 1) In this paper, we introduce a novel 2-D read channel model which we call the 2-D Microcell model. In this model, we use generalized 2-D microtracks called microcells to captures the properties of irregular grain boundaries of the medium in a relatively simple yet accurate manner. The data dependent noise (DDN) distributions are analytically derived for this model. The derivation of the DDN distributions makes the 2-D Microcell suitable for detector design purposes. 2) We propose a new framework for designing truly two-dimensional detectors for the Microcell model based on near-optimal generalized belief propagation (GBP). The GBP algorithm is purposefully applied for detection in this model in order to handle the data dependent media noise which is caused by irregular bit transitions in both dimensions. Results are provided to show that the incorporation of the DDN distributions into the GBP detection helps improving the detection performance.

Original languageEnglish (US)
Article number6559027
Pages (from-to)3699-3702
Number of pages4
JournalIEEE Transactions on Magnetics
Volume49
Issue number7
DOIs
StatePublished - 2013

Fingerprint

Detectors
Intersymbol interference
Signal processing
Grain boundaries

Keywords

  • 2-D microcell model
  • Data dependent noise
  • generalized belief propagation (GBP)
  • intersymbol interference (ISI)
  • two dimensional magnetic recording (TDMR)

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials

Cite this

Generalized belief propagation detector for TDMR microcell model. / Khatami, Seyed Mehrdad; Vasic, Bane V.

In: IEEE Transactions on Magnetics, Vol. 49, No. 7, 6559027, 2013, p. 3699-3702.

Research output: Contribution to journalArticle

@article{cda426661b824ebe8786d6208db2bb6b,
title = "Generalized belief propagation detector for TDMR microcell model",
abstract = "Signal processing in TDMR encounters several challenges such as read channel modeling and detection in the presence of severe two-dimensional intersymbol interference (2-D ISI). The contribution of this paper is twofold. 1) In this paper, we introduce a novel 2-D read channel model which we call the 2-D Microcell model. In this model, we use generalized 2-D microtracks called microcells to captures the properties of irregular grain boundaries of the medium in a relatively simple yet accurate manner. The data dependent noise (DDN) distributions are analytically derived for this model. The derivation of the DDN distributions makes the 2-D Microcell suitable for detector design purposes. 2) We propose a new framework for designing truly two-dimensional detectors for the Microcell model based on near-optimal generalized belief propagation (GBP). The GBP algorithm is purposefully applied for detection in this model in order to handle the data dependent media noise which is caused by irregular bit transitions in both dimensions. Results are provided to show that the incorporation of the DDN distributions into the GBP detection helps improving the detection performance.",
keywords = "2-D microcell model, Data dependent noise, generalized belief propagation (GBP), intersymbol interference (ISI), two dimensional magnetic recording (TDMR)",
author = "Khatami, {Seyed Mehrdad} and Vasic, {Bane V}",
year = "2013",
doi = "10.1109/TMAG.2013.2244063",
language = "English (US)",
volume = "49",
pages = "3699--3702",
journal = "IEEE Transactions on Magnetics",
issn = "0018-9464",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "7",

}

TY - JOUR

T1 - Generalized belief propagation detector for TDMR microcell model

AU - Khatami, Seyed Mehrdad

AU - Vasic, Bane V

PY - 2013

Y1 - 2013

N2 - Signal processing in TDMR encounters several challenges such as read channel modeling and detection in the presence of severe two-dimensional intersymbol interference (2-D ISI). The contribution of this paper is twofold. 1) In this paper, we introduce a novel 2-D read channel model which we call the 2-D Microcell model. In this model, we use generalized 2-D microtracks called microcells to captures the properties of irregular grain boundaries of the medium in a relatively simple yet accurate manner. The data dependent noise (DDN) distributions are analytically derived for this model. The derivation of the DDN distributions makes the 2-D Microcell suitable for detector design purposes. 2) We propose a new framework for designing truly two-dimensional detectors for the Microcell model based on near-optimal generalized belief propagation (GBP). The GBP algorithm is purposefully applied for detection in this model in order to handle the data dependent media noise which is caused by irregular bit transitions in both dimensions. Results are provided to show that the incorporation of the DDN distributions into the GBP detection helps improving the detection performance.

AB - Signal processing in TDMR encounters several challenges such as read channel modeling and detection in the presence of severe two-dimensional intersymbol interference (2-D ISI). The contribution of this paper is twofold. 1) In this paper, we introduce a novel 2-D read channel model which we call the 2-D Microcell model. In this model, we use generalized 2-D microtracks called microcells to captures the properties of irregular grain boundaries of the medium in a relatively simple yet accurate manner. The data dependent noise (DDN) distributions are analytically derived for this model. The derivation of the DDN distributions makes the 2-D Microcell suitable for detector design purposes. 2) We propose a new framework for designing truly two-dimensional detectors for the Microcell model based on near-optimal generalized belief propagation (GBP). The GBP algorithm is purposefully applied for detection in this model in order to handle the data dependent media noise which is caused by irregular bit transitions in both dimensions. Results are provided to show that the incorporation of the DDN distributions into the GBP detection helps improving the detection performance.

KW - 2-D microcell model

KW - Data dependent noise

KW - generalized belief propagation (GBP)

KW - intersymbol interference (ISI)

KW - two dimensional magnetic recording (TDMR)

UR - http://www.scopus.com/inward/record.url?scp=84880831481&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84880831481&partnerID=8YFLogxK

U2 - 10.1109/TMAG.2013.2244063

DO - 10.1109/TMAG.2013.2244063

M3 - Article

AN - SCOPUS:84880831481

VL - 49

SP - 3699

EP - 3702

JO - IEEE Transactions on Magnetics

JF - IEEE Transactions on Magnetics

SN - 0018-9464

IS - 7

M1 - 6559027

ER -