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Proceedings Paper

Channel identification using a combination of blind and nonblind methods
Author(s): Jyotsna L. Bapat; Stephan V. Schell
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Paper Abstract

Identification of pulse (dibit) and step (transition) responses for magnetic storage channels is important for the design of detection circuitry and for comparison of various media, heads, and other channel components. One of the standard techniques for channel identification is measuring the read-head response to any known data sequence written on the medium and then applying least squares procedure to identify the dibit and transition responses. The other techniques involve either measuring the average response of the system to an isolated transition or performing a discrete Fourier transform on the read-head response to a pseudorandom data pattern. We propose a technique that improves on the least squares estimate by taking advantage of the statistical information available from the over sampled channel output. Reliable estimates can be obtained even when the training sequence is not long enough to estimate the channel response using only conventional least squares. Since the resulting adaptive identifier uses both a short training sequence (nonblind technique) and properties of the transmitted signal (blind technique) to estimate the channel response, it is called a semiblind or a partially blind technique. This can also be looked at from the adaptive system identification point of view where both the direct (training signal) and indirect (data statistics) knowledge about the system are used for better system identification.

Paper Details

Date Published: 8 December 1995
PDF: 10 pages
Proc. SPIE 2605, Coding and Signal Processing for Information Storage, (8 December 1995); doi: 10.1117/12.228230
Show Author Affiliations
Jyotsna L. Bapat, The Pennsylvania State Univ. (United States)
Stephan V. Schell, The Pennsylvania State Univ. (United States)


Published in SPIE Proceedings Vol. 2605:
Coding and Signal Processing for Information Storage
Raghuveer M. Rao; Soheil A. Dianat; Steven W. McLaughlin; Martin Hassner, Editor(s)

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