Channel Models and Detectors for Two-Dimensional Magnetic Recording

Chan, Kheong Sann; Radhakrishnan, Rathnakumar; Eason, Kwaku; Elidrissi, Moulay Rachid; Miles, J.J.; Vasić, Bane; Krishnan, Anantha Raman

doi:10.1109/tmag.2009.2035635

Cited by 79 publications

(25 citation statements)

References 15 publications

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“…Actually, the TDMR bit cell size is comparable to the resolution of the read head, which adds a considerable amount of 2-D interference to the TDMR readback signal [6][7][8][9] .…”

Section: ⅱ Four-grain Model For Tdmrmentioning

confidence: 99%

“…Here   is the half pulse-width, and T is the length of the square bit cell [6,9] . x, y denote locations along down-track and cross-track directions, respectively.…”

Section: ⅱ Four-grain Model For Tdmrmentioning

confidence: 99%

“…Some researchers have tried three-track Viterbi algorithm (3TVA) and decision feedback Viterbi algorithm (DFVA) and achieving a bit error rate (BER) in the range of 13%-16% [5], and 2-D MAP detector achieved 0.06-0.08 BER [6] . Usually, LDPC code is used for TDMR encoder.…”

Section: ⅰ Introductionmentioning

confidence: 99%

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Parallel Writing and Detection for Two Dimensional Magnetic Recording Channel

Zhang¹,

Lee

2012

The Journal of Korean Institute of Communications and Informati

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BSTRACTTwo-dimensional magnetic recording (TDMR) is treated as the next generation magnetic recording method, but because of its high channel bit error rate, it is difficult to use in practices. In this paper, we introduce a new writing method that can decrease the nonlinear media error effectively, and it can also achieve 10 Tb/in 2 of user bit density on a magnetic recording medium with 20 Teragrains/in 2 .

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“…Actually, the TDMR bit cell size is comparable to the resolution of the read head, which adds a considerable amount of 2-D interference to the TDMR readback signal [6][7][8][9] .…”

Section: ⅱ Four-grain Model For Tdmrmentioning

confidence: 99%

“…Here   is the half pulse-width, and T is the length of the square bit cell [6,9] . x, y denote locations along down-track and cross-track directions, respectively.…”

Section: ⅱ Four-grain Model For Tdmrmentioning

confidence: 99%

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Parallel Writing and Detection for Two Dimensional Magnetic Recording Channel

Zhang¹,

Lee

2012

The Journal of Korean Institute of Communications and Informati

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“…TDMR (Two-Dimensional Magnetic Recording) and shingled magnetic recording (SMR) are recently proposed magnetic recording strategies which can achieve densities around 10 Tbit/in. 2 [2], [3], [4], [5], [6].…”

Section: Introductionmentioning

confidence: 99%

Inter-track interference cancelation in presence of frequency offset for shingled magnetic recording

Kumar

Bellorado

Marrow

et al. 2013

2013 IEEE International Conference on Communications (ICC)

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The enormous growth of consumer electronic industry is driving the need for achieving ultra-high areal storage densities. Shingled magnetic recording (SMR) is a promising high density storage technique where shingles are created by overlapping tracks for increasing the track per inch (TPI) and achieving higher areal densities. High TPI values, however, introduce sidetrack interference in the equalized output of the center track sensed through the read head. The problem of removing interference from the center track signal can be formulated as estimating pulse shapes of sidetracks assuming sidetracks are decodable. In this paper, we first propose a solution using the correlation method for estimating the pulse shape and the phase-misalignment. The correlation method fails when there is a frequency offset present from sidetracks. Furthermore, we devise a solution based on the least mean square (LMS) algorithm which can provide time varying estimates of the sidetrack pulse shapes and remove the interference from the center track signal. Experimental and simulation results which corroborate the analysis of the proposed algorithm, demonstrate that the proposed algorithm outperforms other techniques and gives the minimum bit error rate (BER). The complexity of the proposed algorithm is low and it can be easily implemented on the hardware.

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“…An inversion detector has been studied [Krishnan 2009], and reasonable error rate performance was reported. The maximum-likelihood (ML) and maximum a posteriori (MAP) detectors based on the trellis or graph of the TDMR channels have been studied [Chan 2010]. Hwang et al [2010] used a linear minimum mean-squared error (MMSE) equalizer and a low-density parity-check code to study the detection in a TDMR system.…”

Section: Introductionmentioning

confidence: 99%

Novel system design for readback at 10 terabits per square inch user areal density

2012

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A novel system design for sensing very high density magnetic recording data, such as that envisioned for twodimensional magnetic recording, is proposed. The key idea is a rotated sense head, so that the shields are aligned downtrack, combined with oversampled signal processing to regain the lost down-track resolution. Based on a random Voronoi grain model, simulation indicates that for bits with dimension of 8 nm × 6 nm, 5.5 nm grains, and a reader with 4 nm × 18 nm × 18 nm free layer and 11 nm shield-shield spacing, the bit error rate can drop from 20.9% for a normally positioned head array to 4.2% for a single-rotated single head with sampling period of 2 nm, a minimum mean squared error equalizer, and pattern-dependent noise prediction detector. The user density computed using the Shannon capacity limit is greatly increased to 10.1 Tb/in 2 .

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Channel Models and Detectors for Two-Dimensional Magnetic Recording

Cited by 79 publications

References 15 publications

Parallel Writing and Detection for Two Dimensional Magnetic Recording Channel

Parallel Writing and Detection for Two Dimensional Magnetic Recording Channel

Inter-track interference cancelation in presence of frequency offset for shingled magnetic recording

Novel system design for readback at 10 terabits per square inch user areal density

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