Graph-Based Channel Detection for Multitrack Recording Channels

  • Jun Hu1,

    Affiliated with

    • Tolga M. Duman2Email author and

      Affiliated with

      • M. Fatih Erden3

        Affiliated with

        EURASIP Journal on Advances in Signal Processing20092008:738281

        DOI: 10.1155/2008/738281

        Received: 26 March 2008

        Accepted: 28 November 2008

        Published: 20 January 2009

        Abstract

        We propose a low complexity detection technique for multihead multitrack recording systems. By exploiting sparseness of two-dimensional partial response (PR) channels, we develop an algorithm which performs belief propagation (BP) over corresponding factor graphs. We consider the BP-based detector not only for partial response channels but also for more practical conventional media and bit-patterned media storage systems, with and without media noise. Compared to the maximum likelihood detector which has a prohibitively high complexity that is exponential with both the number of tracks and the number of intersymbol interference (ISI) taps, the proposed detector has a much lower complexity and a fast parallel structure. For the multitrack recording systems with PR equalization, the price is a small performance penalty (less than one dB if the intertrack interference (ITI) is not too high). Furthermore, since the algorithm is soft-input soft-output in nature, turbo equalization can be employed if there is an outer code. We show that a few turbo equalization iterations can provide significant performance improvement even when the ITI level is high.

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        Authors’ Affiliations

        (1)
        Qualcomm Inc
        (2)
        Electrical Engineering Department, Ira A. Fulton School of Engineering, Arizona State University
        (3)
        Seagate Technology

        Copyright

        © The Author(s). 2008

        This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.