• DocumentCode
    1320396
  • Title

    From Component SNR to System SFR

  • Author

    Yeh, Nan-Hsiung ; Zhang, Zhenyong ; Steiner, Philip

  • Author_Institution
    Seagate Technol., Fremont, CA, USA
  • Volume
    48
  • Issue
    11
  • fYear
    2012
  • Firstpage
    3899
  • Lastpage
    3902
  • Abstract
    A methodology that enables the projection of system performance from component characteristics is presented in this study. Equalized signal-to-noise ratio (eSNR), which refers to the SNR seen by the sequence detector, is a metric that can link component parametrics to Viterbi BER. Orthogonal breakdown of eSNR into contributions from head noise, transition noise, remanence noise, nonlinear distortion and adjacent track interference allows all the disturbances to be weighted properly at the system level. Sector-based BER together with the channel transfer function can further project sector failure rate up to the maximum number of low density parity check iterations without stressing the recording condition. Anticipated system performance from component improvement is readily predictable based on this approach.
  • Keywords
    Viterbi decoding; error statistics; failure analysis; interference (signal); iterative methods; nonlinear distortion; parity check codes; transfer functions; Viterbi BER; adjacent track interference; channel transfer function; component SNR; eSNR; equalized signal-to-noise ratio; head noise; link component parametrics; low density parity check iterations; nonlinear distortion; orthogonal breakdown; project sector failure; remanence noise; sequence detector; system SFR; transition noise; Bit error rate; Head; Media; Parity check codes; Signal to noise ratio; Viterbi algorithm; Iterative decoding; Viterbi detection; magnetic recording; signal-to-noise ratio (SNR); system analysis and design;
  • fLanguage
    English
  • Journal_Title
    Magnetics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9464
  • Type

    jour

  • DOI
    10.1109/TMAG.2012.2201923
  • Filename
    6332621