Error detection/correction and fault detection/recovery – Pulse or data error handling – Error/fault detection technique
Reexamination Certificate
2000-04-11
2003-06-17
Decady, Albert (Department: 2784)
Error detection/correction and fault detection/recovery
Pulse or data error handling
Error/fault detection technique
C714S701000
Reexamination Certificate
active
06581184
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
This invention relates to improvements in methods and apparatuses for dynamic information storage or retrieval, and more particularly to improvements in methods and circuitry for detection and correction of errors, especially in information storage and retrieval systems that use a magnetic data storage medium, and still more particularly to improvements in methods and apparatuses for improving data detection in dynamic information storage or retrieval systems of the type that use post-processor data detection techniques.
2. Relevant Background
Mass data storage devices may include, for example, hard disk drive apparatuses (HDA), or other similar data recording devices. Mass data storage devices include well known hard disk drives that have one or more spinning magnetic disks or platters onto which data is recorded for storage and subsequent retrieval. Hard disk drives may be used in many applications, including personal computers, set top boxes, video and television applications, audio applications, or some mix thereof. Many applications are still being developed. Applications for hard disk drives are increasing in number, and are expected to further increase in the future.
A typical hard disk drive includes one or more spinning discs that are coated with a magnetic material so that data can be written to and read from concentric rings in the magnetic media of the disk by one or more magnetic transducer devices that are located in proximity to the disc and selectively located to particular rings in which the data is written. Mass data storage devices may include other types of devices that are susceptible to the same type of error creating mechanisms as HDAs.
In the construction of the data channel used in hard disk drives, or the like, there has been significant recent interest in Partial Response Maximum-likelihood (PRML) signaling techniques. The most common PRML systems are PR4ML (a partial response class 4) and EPR4ML (extended partial response class 4). Maximum-likelihood detectors, which use a Viterbi algorithm, are generally used for these partial response channels.
Recently, an EPR4 channel has been introduced. In comparison to previously used PR4 partial response target, which is 1−D)*1+D), the EPR4 partial response target, which is 1−D)*1+D)
2
, where D is a delay operator, equal to e
jw&tgr;
, where w is frequency, and &tgr; is delay time.
In such systems, the use of EPR4 Viterbi data detection techniques is widely employed. EPR4 Viterbi detectors are well known, and involve probabilistic techniques for determining data states in the data channel. As data rates increase in the data channel, it becomes increasingly difficult to distinguish adjacent data pulses, and the Viterbi techniques have been found to be very useful.
Unfortunately, significant errors still occur in data detection. For example, using EPR4 techniques, a bit error rate (BER) of about 10
−5
typically occurs. As the data packing densities are increased, the more difficult the accurate read back of the data becomes. For example, bit error rates (BERs) in the neighborhood of 10
−7
, or better, are presently being expected of modern day HDA's, and it is expected that this requirement will continue to become more stringent. However it has been observed that if the signal-to-noise ratio in a system could be reduced by even as little as, for example, 1 dB, the bit error rate can be improved by an order of magnitude improvement. Thus, even small improvements in the signal-to-noise ratio results in large improvements in the bit error rate using EPR4 detection techniques.
In the past, a typical EPR4 circuit would receive an input signal that has been amplified by a pre-amplifier from the data transducer of the storage device. The amplified signal is applied to an EPR4 equalizer that produces an output that is detected by an EPR4 Viterbi detector. The output from the EPR4 Viterbi detector typically contains the desired data which has been decoded using the above mentioned probabilistic techniques.
Partial response channels are subject to certain error-events. An error event occurs when the channel symbol that represents the polarity of a write current is misread. It should be noted that as data is written to the magnetic medium, it is written synchronously with a clock that requires the data at each clock cycle to assume a particular state. In addition, the nomenclature used to represent the write current sequence is referred to as “non-return-to-zero” or “NRZ” notation. The number of MTR states is cut in half by using “non-return-to-zero-inverse” or “NRZI” notation, where a zero corresponds to no transition, and a one corresponds to a transition. Consequently, the initial coding done on data to be written is to NRZI data.
In many recent applications, maximum transition run length (MTR) coding has used to improve the performance of partial response channels. In MTR coding, a number of input bits are mapped to a larger number of possible bits. For example, a typical MTR code is a 16/17 coding in which 16 input bits are mapped to a 17-bit frame. Thus, after characterizing a magnetic recording partial response channel, a list of dominant error-events is compiled. Then, an MTR code is designed so that code mappings do not contain any dominant error-events. However, merely constraining the sequences to a given coding constraint is not enough to obtain a significant coding gain. Rather, a Viterbi detector which is matched to the combination of the channel and the code must be used to insure that the detected sequence is allowed by the constraint.
Additionally, MTR codes eliminate certain consecutive transition errors. By removing certain transitions possibilities, corresponding write current sequences are not allowed. Therefore, many of the dominant error-events at high densities are removed along with many other likely error-events. Such code reduces the number of transitions and increases the spacing between transitions.
Thus, MTR coding permits a predetermined number of consecutive transitions, and prohibits a predetermined number of consecutive non-transitions. A transition for purposes of MTR coding is either a transition from 0 to 1 or a transition from 1 to 0. The basic idea of MTR coding is to eliminate certain input bit patterns that would cause most error-events in a sequence detector. For example, a MTR (
3
:
11
) coding requires that no more than three consecutive input transitions occur, and that no input condition results in more than 11 consecutive time periods during which no transition occurs. This eliminates four or more consecutive transitions, and eliminates 12 or more non-transitions. With the MTR constraint, precompensation can be performed more accurately.
In general, the MTR constraint removes branches and/or states from the Viterbi detector for the channel. Therefore, MTR coding provides coding gain at high densities without adding complexity to the system. While MTR codes provide coding gain without adding complexity, a number of error conditions still remain, particularly in the presence of additive white Gaussian noise (AWGN) and media noise. Moreover, as the processing level is increased, several problems have emerged. For example, although the EPR4 channel yields better performance than the PR4 channel for higher recording densities, the complexity of the Viterbi detector used in an EPR4 channel increases by more than twice, and the maximum data rate decreases. In order to avoid these drawbacks, several techniques have been proposed.
One technique is the use of a post-processor. Since a post-processor can use the same metric as an EPR4 Viterbi detector, the criteria used to correct minimum distance error-events can be the same criteria as those used in an EPR4 Viterbi detector to select survivor paths. The main benefits to such post-processing approaches is reduced complexity in the feedback path associated with the updating process for the Viterbi detector, allowing for higher channel rates.
Palmer Michael J.
Saeki Koshiro
Brady W. James
Britt C
De'cady Albert
Swayze, Jr. W. Daniel
Telecky , Jr. Frederick J.
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