Perpendicular magnetic recording (PMR) techniques may enable higher recording densities on magnetic storage media than conventional longitudinal magnetic recording techniques. PMR systems include heads that record bits perpendicular to the plane of the disk. PMR disks include a high permeability (“soft”) magnetic underlayer between a perpendicularly magnetized thin film data storage layer and the substrate. An image of the magnetic head pole created by the head is produced in the magnetically soft underlayer. Consequently, the storage layer is effectively in the gap of the recording head, where the magnetic recording field is larger than the fringing field produced by a longitudinal magnetic recording (LMR) head. The larger recording field makes it possible to record using smaller grain sizes and smaller bit sizes than in LMR systems.
In PMR, the channel response has a DC component. For a channel that is AC-coupled to the preamplifier and read channel, or that contains some other means for high-pass filtering the channel response, there may be DC-distortion. The DC-distortion may manifest itself as a data dependent baseline wander, which can severely affect the performance of a system that equalizes the channel response to a response target that is not DC-free.
In an embodiment, a perpendicular magnetic recording (PMR) system may scramble an input data sequence with a first scramble seed and encode the scrambled data sequence with a modulation encoder (e.g., a run length limited (RLL) encoder). The system may then determine whether the scrambled and encoded data sequence includes one or more patterns associated with large baseline wander, using, e.g., the running digital sum (RDS) over the sequence or a low pass filter as a metric. If such a pattern is detected, the system may control the scrambler to re-scramble the data sequence with another scrambler seed, encode the re-scrambled sequence, and determine whether this scrambled and encoded sequence includes on or more patterns associated with large baseline wander. This process may be repeated until a scrambled and encoded sequence without such patterns is generated, or until all available scrambler seeds are exhausted, in which case, the scrambler seed with the least amount of baseline wander may be used. The best scrambled and decoded sequence may then be written to the magnetic recording medium.
In an alternative embodiment, a PMR system may scramble an input data sequence with a first scramble seed and encode the scrambled data sequence with a modulation encoder (e.g., a run length limited (RLL) encoder). A write signal may be generated and the encoded data sequence written to the magnetic recording medium. The write signal may also be fed back to a read channel in the system. The write signal may be passed through a filter to mimic the magnetic recording channel. The read channel may then determine if DC-wander in the write signal is too large to be accurately decoded. If so, the data sequence may be scrambled with another scramble seed, encoded, and used to over-write the first encoded data sequence in the magnetic recording medium. This process may be repeated until an encoded data sequence that can be accurately decoded by the read channel is generated.
For both of the alternative embodiments described above, the data sequence may not be scrambled in the first run through the system.
In PMR, the channel response has a DC component. For a channel that is AC-coupled to the preamplifier and read channel, or that contains some other means for high-pass filtering the channel response, there may be DC-distortion. The DC-distortion may manifest itself as a data dependent baseline wander, which can severely affect the performance of a system that equalizes the channel response to a response target that is not DC-free.
A number of different scramblers may be used. For example, in an embodiment, a pseudo-noise (PN) sequence generated using a maximum-length shift register may be added modulo-2 to each data bit to be scrambled. Regardless of the type of scrambler used, the detector must know if and how the data was scrambled to properly descramble the data. In an embodiment, the detector may know how the data is scrambled, but may not necessarily know the initial conditions or the scrambler seed that was used to scramble the data. This information (e.g., the scrambler seed or method) may be embedded in the data that is written. Alternatively, the detector may descramble the data by trial and error. For example, the detector may descramble the data following a predetermined list of scramblers/scrambler seeds until the descrambled data decodes properly by some error-control code (ECC) 213, cyclic redundancy check (CRC) code, or some other check. In an embodiment, the scrambling is done prior to ECC encoding in the write channel, and descrambling is done after ECC decoding at the detector.
The write signal generated by the write channel is written to the disk (block 305). The write signal is also fed back into the read channel 204 (block 306), possibly via a filter 214 to mimic the magnetic channel. The read channel 204 processes the signal (block 308), and a decision block 220 determines if the DC-wander is too severe to be handled in the read channel (block 310). If the DC-wander is determined to be within acceptable limits at block 310, then the next data sequence in the input data stream is scrambled (block 312) and encoded. However, if the DC-wander is determined to be too severe, the read channel requests that the sector be rewritten with another scrambler seed (block 314). The newly scrambled data sequence is then encoded (block 316) and re-written to the disk (block 318), over-writing the “bad” sequence.
In an embodiment, all of the functions in the read channel 204 that would be expected to be active in the actual reading of a waveform from the disk are active. An error signal generated internally in the read channel may be used to monitor how severe the DC-wander is at the detector input (at block 310). If the DC-wander is determined to be too large, a re-write request may be asserted by the read channel. In other embodiments, various functions of the read channel may disabled. For example, in an embodiment, the bit detector may be disabled, since the bits can be obtained directly from the write channel.
Several parameters may be used by the decision block 220 to determine whether the DC-wander is too large. The following are exemplary parameters for determining excessive DC-wander:
(a) Simple threshold: the decision block 220 considers the DC-wander to be too large if the absolute value of the error signal is larger than a given threshold at any point in the data sequence;
(b) The decision block 220 considers the DC-wander to be too large if the absolute value of the error signal is larger than a given threshold for a total of at least a given number of clock cycles;
(c) The decision block 220 considers the DC-wander to be too large if the absolute value of the error signal exceeds the given threshold for at least a given number of consecutive clock cycles. For example, in an embodiment, the threshold is 3 and the given number of consecutive cycles is three. The error sequence |e|={0, 1, 4, 5, 1, 6, 3, 4, 6, 7, 2, 3, 7} has seven numbers greater than 3. However, only the three consecutive occurrences of numbers greater than 3 (i.e., the sub-sequence {4, 6, 7}) are counted.
The parameters described above may be used separately or combined. For example, the “simple threshold” (a) and “consecutive clock cycle” (c) parameters can be combined. Then the threshold for (a) should be larger than the threshold for (c).
In an embodiment, an encoded data sequence may be inspected for patterns that might cause large baseline wander before being written to disk, i.e., in the write channel. The data sequence may be repeatedly scrambled and encoded until an acceptable level of estimated DC-wander has been achieved. The data sequence may then be written to disk.
After the RLL encoder, the encoded data may be output to an output buffer 510 and a DC-wander estimation module 512 (block 406). The DC-wander estimation module may screen for patterns that might cause large baseline wander (i.e., “bad” patterns) (block 408). If no such pattern is found, the output buffer may output the encoded data to the write channel for further processing and writing to the disk (block 410). Otherwise, the data is scrambled using another scrambler seed (block 412) and then encoded by the RLL encoder 508 (block 404). The newly encoded data sequence is then screened for patterns that may cause large baseline wander (block 408). This process may continue until the encoded data sequence is determined to contain no bad patterns. The encoded data is then output to the write channel. In the case that all scrambler seeds are exhausted (block 414), the data may be scrambled using the scrambler seed that yielded the least baseline wander (block 416).
Several metrics may be used by the DC-wander estimation module 512 to measure baseline wander. In an embodiment, the maximum absolute value of the running digital sum (RDSmax) over the entire sequence may be used.
The running digital sum of a binary sequence x={x0, x1, . . . }, where xi=±1 is defined as
The maximum absolute value of RDS over a sequence of length N is
A first method to determine if a sequence has large baseline wander uses equation (2) for the entire sequence. If RDSmax is above a certain threshold, the sequence is considered to have a large baseline wander. In the case that all available sequences have a large baseline wander, the sequence with the smallest RDSmax may be selected.
A second method splits the sequence into two or more subsequences, and uses the first method for each sub-sequence. In the case that all available sequences have one or more sub-sequences with large baseline wander, the sequence with the smallest number of sub-sequences with large baseline wander may be selected. A tie among those can, for example, be broken by selecting the sequence with the smallest RDSmax.
For a third method, the number of bit periods for which the absolute value of the RDS is greater than a threshold is counted.
where Ii is an indicator function
If RDScount is greater than a certain value, the sequence is determined to have a large baseline wander. If all available sequences have large baseline wander, then the sequence with the smallest RDScount is selected.
A fourth method is similar to the third method, but only the first instance when several consecutive values of the RDS is greater than a threshold is counted.
where
For example, if the RDS for a sequence of length 20 is given by {1, 0, −1, −2, −3, −4, −5, −4, −3, −4, −3, −2, −1, 1, 2, 1, 2, 3, 2}, and the threshold th=3. Then RDScount=4 using equation (3), and RDSnbr=2 using equation (5).
In a fifth method, the mean of the absolute value of the RDS is used.
If RDSmean is greater than a threshold, the baseline wander may be considered to be large.
In an alternative embodiment, a low pass filtered version of the sequence is used as a metric rather than the RDS of the sequence. The main source of baseline wander in many systems is AC coupling or other high pass filtering circuits. The amount of baseline wander caused by a code sequence can be estimated by passing the sequence through a model of the high pass filter 602 (which mimics AC-coupling), and subtracting the output of the filter from the input sequence, as shown in
Other, usually more complex, filters can be designed to mimic not only the impact of high pass filters, but also the impact of the write and read process and the signal shaping in the read channel.
Although several examples have been given, any filter that generates an estimate of the DC-offset based on the encoded data sequence as input can be used for this purpose.
The following are exemplary parameters that may be used to determine if a sequence has a large DC-wander in systems using low pass filtered sequences as a metric:
If the largest DC-offset of the sequence is larger than a threshold;
If the largest DC-offsets of the sub-sequences are larger than a threshold;
If the DC-offset is larger than a threshold for more than another threshold number of bit-cycles;
If the DC-offset is larger than a threshold for more than another threshold number of times;
If the mean of the absolute value of the DC-offset is greater than a threshold.
In another embodiment, a low pass filtered sequence with DC correction is used as a metric. Instead of just estimating the DC-offset based on filtering the encoded sequence, this method assumes that there is a DC-correction circuit built into the system. Different types of DC-correction circuits can be used. In
In an alternative embodiment, several seeds may be used to scramble the encoded sequence in parallel. The scrambled sequences may then be encoded and evaluated in parallel. The seed that provides the best response may then be selected.
In other alternative embodiments, the first trial may not be scrambled. For example, block 302 and 402 in
A number of embodiments have been described. Nevertheless, it will be understood that various modifications may be made without departing from the spirit and scope of the invention. For example, blocks in the flowcharts may be skipped or performed out of order and still produce desirable results. Accordingly, other embodiments are within the scope of the following claims.
This application claims priority to U.S. Provisional Application Ser. No. 60/478,869, filed on Jun. 16, 2003, and to U.S. Provisional Application Ser. No. 60/485,216, filed on Jul. 7, 2003, both of which are incorporated herein by reference.
Number | Name | Date | Kind |
---|---|---|---|
5757294 | Fisher et al. | May 1998 | A |
5898394 | Kobayashi et al. | Apr 1999 | A |
5978162 | Behrens et al. | Nov 1999 | A |
6140857 | Bazes | Oct 2000 | A |
6148025 | Shirani et al. | Nov 2000 | A |
6173019 | Hee et al. | Jan 2001 | B1 |
6177890 | Keirn et al. | Jan 2001 | B1 |
6208477 | Cloke et al. | Mar 2001 | B1 |
6211716 | Nguyen et al. | Apr 2001 | B1 |
6219192 | Gopalaswamy et al. | Apr 2001 | B1 |
6266202 | Nguyen et al. | Jul 2001 | B1 |
6415003 | Raghavan | Jul 2002 | B1 |
6512644 | Hall et al. | Jan 2003 | B1 |
6578164 | Stokes et al. | Jun 2003 | B1 |
6661356 | Oberg | Dec 2003 | B1 |
6738935 | Kimmitt | May 2004 | B1 |
6762895 | Osafune | Jul 2004 | B2 |
6792566 | Chen et al. | Sep 2004 | B2 |
6862701 | Walker et al. | Mar 2005 | B2 |
6917314 | Oberg | Jul 2005 | B1 |
7006016 | Feng | Feb 2006 | B1 |
7103123 | Chang et al. | Sep 2006 | B2 |
7116504 | Oberg | Oct 2006 | B1 |
20040130816 | Feyh | Jul 2004 | A1 |
Number | Date | Country | |
---|---|---|---|
60485216 | Jul 2003 | US | |
60478869 | Jun 2003 | US |