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The increased track density in bit patterned media recording (BPMR) causes increased inter-track interference (ITI), which degrades the bit error rate (BER) performance. In order to mitigate the effect of the ITI, signals from multiple tracks can be equalized by a 2D equalizer with 1D target. Usually, the 2D fixed equalizer coefficients are obtained by using a pseudo-random bit sequence (PRBS) for training. In this study, a2Dvariable equalizer is proposed, where various sets of 2D equalizer coefficients are predetermined and stored for different ITI patterns besides the usual PRBS training. For data detection, as the ITI patterns are unknownin the first global iteration, the main and adjacent tracks are equalized with the conventional 2D fixed equalizer, detected with Bahl- Cocke-Jelinek-Raviv (BCJR) detector and decoded with low-density parity-check (LDPC) decoder. Then using the estimated bit information from main and adjacent tracks, the ITI pattern for each island of the main track can be estimated and the corresponding 2D variable equalizers are used to better equalize the bits on the main track. This process is executed iteratively by feeding back the main track information. Simulation results indicate that for both single-track and two-track detection, the proposed 2D variable equalizer can achieve better BER and frame error rate (FER) compared to that with the 2D fixed equalizer. [ABSTRACT FROM AUTHOR]

Focuses on a study which presented a time-domain model to characterize the noise from particulate recording media. Autocorrelation function of the media noise; Inadequacy of power spectrum measurements; Information on the stationary stochastic processes used to model the nonstationary media noise in the time domain.