Pattern-Dependent Noise Predictive Soft Detection in the Post-Processor With Error Filters

• Published in: IEEE transactions on magnetics Vol. 46; no. 6; pp. 1959 - 1962
• Main Authors: Djurdjevic, Ivana, Wilson, Bruce A., Oenning, Travis R.
• Format: Journal Article Conference Proceeding
• Language: English
• Published: New York, NY IEEE 01.06.2010; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Base-line wander compensation; Channels; Circuit noise; Compensation; Complexity; Cross-disciplinary physics: materials science; rheology; Detectors; Error detection; Exact sciences and technology; Filters; Gaussian noise; Magnetic noise; Magnetism; Materials science; Mathematical models; Maximum likelihood detection; Noise; Optimization; Other topics in materials science; pattern-dependent autoregressive noise model; Performance loss; Perpendicular magnetic recording; Physics; Post-processing; Probability distribution; soft detection; Viterbi algorithm; post-processing; pattern-dependent autoregressive noise model; Base-line wander compensation; Modelling; perpendicular magnetic recording; Magnetic recording; Magnetic properties; soft detection
• ISSN: 0018-9464; 1941-0069
• DOI: 10.1109/TMAG.2010.2043227

This paper investigates a pattern-dependent noise predictive soft detection method for channel architectures that are based on a long target response and post-processing rather than a short target response and base-line wander compensation. We utilize properties of the autoregressive pattern-dependent noise model to compare tentative Viterbi sequence with alternative sequences in the post-processor and efficiently compute soft information. Even though the post-processor cannot consider all possible sequences like trellis-based detectors can, we demonstrate for a short target response that our post-processing solution does not experience any loss in performance compared to the optimal maximum a posteriori trellis-based soft detector. The complexity of the computations in the post-processor grows only linearly with the target length, as opposed to the exponential growth in complexity in trellis-based detectors. In this way we can efficiently perform nearly optimal pattern-dependent soft detection in the post-processor for a very long target response without base-line wander compensation.