Two-Dimensional Voronoi-Based Model and Detection for Shingled Magnetic Recording

Todd, Richard M.; Jiang, Enfeng; Galbraith, Rick; Cruz, J.R.; Wood, Roger

doi:10.1109/tmag.2012.2197855

Cited by 24 publications

(15 citation statements)

References 5 publications

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“…The best achieved U/G corresponds to 4.6 Terabits/in 2 on media with (currently typical) grain densities of 10 Teragrains/in 2 ; this represents about a factor of 5 density increase over currently available hard disk drives. We note that this density increase is likely to be smaller if a more realistic write-process model (e.g., [5]) is used.…”

Section: Simulation Resultsmentioning

confidence: 95%

“…8 illustrates the BER performance of the designed IRA codes for the TDMR channel in comparison with generic IRA codes designed for the AWGN channel. The simulations utilize the TDMR Voronoi grain model of [5] and the write/read process explained in section II. The SNR is fixed at 13 dB.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…The TDMR random Voronoi model considered in this paper follows the proposed model in [5]. In that model, grain nuclei are initially randomly distributed throughout the input image area; the number of nuclei is chosen according to the desired number of channel coded bits per grain, and determines the average grain area A.…”

Section: A Tdmr Voronoi Model and 2d-isi Channelmentioning

confidence: 99%

“…4, the output LLRs of VNDs of different degrees have different PDFs through the IRA decoder iterations. The experimental mutual information at the VND output for each degree and iteration is calculated by using (5).…”

Section: Exit Chart Based Ira Code Design For Tdmr Channel With mentioning

confidence: 99%

“…Thus, occasionally a bit will not be written on any grain, and hence will effectively be "overwritten" (or erased) by bits on the surrounding grains. TDMR channels also suffer from two-dimensional intersymbol interference (2D-ISI) caused by down-track and cross-track direction interferences (e.g., [4], [5]). …”

Section: Introductionmentioning

confidence: 99%

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EXIT chart based IRA code design for TDMR

Mehrnoush

Belzer

Sivakumar

et al. 2016

2016 Annual Conference on Information Science and Systems (CISS)

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This paper presents an extrinsic information transfer (EXIT) chart based irregular repeat-accumulate (IRA) code design technique for a two-dimensional magnetic recording (TDMR) turbo-equalizer that employs a Voronoi magnetic grain model. The channel model also includes two-dimensional intersymbol interference (2D-ISI) and additive white Gaussian noise (AWGN). At high bit densities (e.g., between 1 and 3 magnetic grains per coded bit (GPB)), occasionally a bit will not be written on any grain, and hence will effectively be "overwritten" (or erased) by bits on surrounding grains. The proposed code design takes into account the statistics of the TDMR channel to decrease overwrite effects. The proposed receiver uses a 2D-ISI BCJR equalizer and IRA decoder in a turbo-equalization approach. To design the IRA code, we find the experimental EXIT chart curves of the check node decoder (CND) and the combination of the variable node decoder (VND) with the 2D-ISI equalizer. We fit the VND and CND EXIT chart curves to find the IRA code's optimized variable node degree distribution for the TDMR channel. Simulation results show that the IRA codes optimized for the TDMR Voronoi grain model achieve up to a 3.3% density increase in user-bits/grain (U/G) compared to IRA codes designed for AWGN channels. At 1.2 GPB, the designed IRA codes achieve densities as high as 0.455 U/G, corresponding to an areal density of about 4.6 Terabits/in 2 on typical magnetic hard disks with 10 Teragrains/in 2 ; this is nearly a factor of 5 better than the best commercially available systems.

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Section: Simulation Resultsmentioning

confidence: 95%

Section: Simulation Resultsmentioning

confidence: 99%

Section: A Tdmr Voronoi Model and 2d-isi Channelmentioning

confidence: 99%

Section: Exit Chart Based Ira Code Design For Tdmr Channel With mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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