Pulse or digital communications – Receivers – Particular pulse demodulator or detector
Reexamination Certificate
1999-03-31
2002-07-23
Pham, Chi (Department: 2631)
Pulse or digital communications
Receivers
Particular pulse demodulator or detector
Reexamination Certificate
active
06424686
ABSTRACT:
TECHNICAL FIELD
This invention relates to maximum likelihood detection of data recorded as analog signals representing a finite number of states, and, more particularly to reduction of errors resulting from maximum likelihood detection.
BACKGROUND OF THE INVENTION
Maximum likelihood detection of data recorded as analog signals and detected from partial response samples is highly advantageous in magnetic disk drives, where the disks and heads are fixed and non-removable. The characteristics of the channel are fixed, including the particular disk media, the particular recording and read heads, the linear velocity and flying height between the disk media and the recording and read heads, and the recording and read electronics. The channel characteristics can be measured and, once known, tend to remain constant. Additionally, a specific code may be employed which maximizes the distances between the sensed states. Only limited changes are taken into account, such as differences in data rates between inner and outer tracks, minor servo offtrack operation, minor disk defects, and some head wear over time. Thus, a specific maximum likelihood detection circuit can be designed which is specific to the type of disk drive and which will have a low error rate at high recording densities. Further, such minor changes have been accommodated by employing digital FIR (finite impulse response) filters whose coefficients are programmable, thus changing the frequency response of the filters to better match the signal being read to the maximum likelihood detector. Examples include, U.S. Pat. No. 5,321,559, Nguyen et al., U.S. Pat. No. 5,365,342, Abbott et al., and U.S. Pat. No. 5,442,760, Abbott et al.
It becomes more difficult to use such maximum likelihood detection with recording devices which have removable media.
Removable media devices tend to be mass storage devices which allow data to be recorded on media which is removed from the device and stored elsewhere, such as in the storage shelves of an automated data storage library, or in true archive storage outside of a drive or library on storage shelves or in boxes and other containers. The amount of data so stored quickly becomes very large and, if a new and upgraded media is introduced, there is a desire on the part of the user to resist re-recording all of the archived data onto the upgraded media. Hence, a backwards compatibility is typically required for removable media devices. Examples of removable media devices include optical disk and optical tape storage, which may be read-only, write-once, and rewritable media, and be different types of media, such as molded, magneto-optic and phase-change media.
Optical media is subject to variation from media to media in recorded data output characteristics based on the type of media, above, variation in media materials between manufacturers and over time, and between recording densities.
Another example of removable media devices includes magnetic tape recording, which have media to media variation based on different data densities on the same type of media, different types of media such as chromium-based, nickel-based, ferrous-based media, or between materials used by different manufacturers. Additionally, tape media may have differing thicknesses and therefore differing media to head (flying and contact) characteristics over the recording and read head, resulting in differing head to media spacings.
Maximum likelihood detection in such differing circumstances is exceedingly difficult, and may require a different maximum likelihood detector for each circumstance.
Further, in the context of a single drive type, the drives may have an alignment of the head with respect to the media which differs between drives, also resulting in differing channel characteristics.
The use of a changeable FIR, as in the above patents, is unlikely to compensate for the change in channel characteristics.
Additionally, the maximum likelihood trellis for maximum likelihood detection conventionally utilizes continuing accumulation of metrics until the accumulation reaches an overflow condition, and the register containing the accumulated metric is then reset, normalizing the accumulated value.
SUMMARY OF THE INVENTION
It is therefore an object of the present invention to provide maximum likelihood detection of data recorded as analog signals representing a finite number of states which reduces errors resulting from maximum likelihood detection with normalized values.
Disclosed are a maximum likelihood detector and a method for maximum likelihood detection of digital samples of data recorded as analog signals representing a finite number of states, the digital samples representing the channel output of recorded analog signals at a predetermined timing with respect thereto. The method comprises the steps of:
providing numerical metric coefficients relating to the probability of the digital samples comprising a data sequence;
respectively applying the numerical metric coefficients to each of the digital samples to generate alternative metrics;
providing a previous metric which comprises a difference metric function of a previous digital sample;
selecting the one of the respective generated alternative metrics which minimizes the mean squared error with respect to the previous metric;
identifying the one of the finite number of states represented by the selected metric; and
responding to the identified one of the finite states, setting a maximum likelihood state detector to a maximum likelihood state dictated by the identified one of the finite states, the set maximum likelihood state detecting the recorded analog signals.
Each separate set of metric coefficients may comprise programmed numerical metric coefficients relating to the probability of the samples comprising a data sequence under different detection characteristics.
The alternative metrics are compared to the previous metric, and, the selection of the provided metric is based upon the comparison.
The numerical metric coefficients are derived from the difference between metrics directly associating “0” and “1” states of the recorded signal. This insures that there is no unbounded accumulation of metrics.
The derived numerical coefficients are applied to each of the digital samples to provide at least one difference metric. A lot plurality of alternative metrics are generated relating to the digital samples. The one of the respective generated alternative metrics is selected which remains within defined positive and negative bounds by comparing the generated alternative metrics to the difference metric. The one of the finite number of states represented by the selected metric is identified, and the maximum likelihood detector is set, detecting the analog signal.
Where the recorded analog signals having the different detection characteristics are recorded on different media, the step of programming each metric coefficient may be conducted based upon an identification of the different media.
The programmed numerical metric coefficients may be derived from logarithmic relationships of the digital samples to the finite number of states.
For a fuller understanding of the present invention, reference should be made to the following detailed description taken in conjunction with the accompanying drawings.
REFERENCES:
patent: 5321559 (1994-06-01), Nguyen et al.
patent: 5345342 (1994-09-01), Abbott et al.
patent: 5422760 (1995-06-01), Abbott et al.
patent: 5432803 (1995-07-01), Liu et al.
patent: 5533067 (1996-07-01), Jamal et al.
patent: 5650988 (1997-07-01), Kuribayashi
patent: 5661760 (1997-08-01), Patapoutian et al.
patent: 6289060 (2001-09-01), Chen
Hutchins Robert Allen
Paranjape Sushama Mahesh
Sonu Gene Ho
Holcombe John H.
Pham Chi
Tran Khai
LandOfFree
Maximum likelihood detection with difference metrics and... does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Maximum likelihood detection with difference metrics and..., we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Maximum likelihood detection with difference metrics and... will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-2854460