Systems and methods for reducing attenuation of information derived from a defective medium
View Patent ↗Various embodiments of the present invention provide systems and methods for data regeneration. For example, a method for data regeneration is disclosed that includes receiving a data input derived from a medium, determining a media defect corresponding to the data input, and determining an attenuation factor associated with the defective medium. Based at least in part on the determination that the medium is defective, amplifying the data input by a derivative of the attenuation factor to regenerate the data.
1. A system for regenerating data, the system comprising:
a media defect detector, wherein the media defect detector is operable to identify a potential media defect associated with a medium from which an input signal is derived;
an attenuation amplitude detector, wherein the attenuation amplitude detector generates an attenuation factor; and
a data detector, wherein the data detector processes a derivative of the input signal, wherein an amplitude of the derivative of the input signal is augmented by the attenuation factor when the potential media defect is indicated.
2. The system of claim 1 , wherein the data detector is selected from a group consisting of: a soft output Viterbi detector, and a maximum a posteriori detector.
3. The system of claim 1 , wherein an output of the data detector is provided to a decoder, and wherein the decoder provides a decoded output reflecting a regenerated value of the input signal.
4. The system of claim 3 , wherein the decoder is a low density parity check decoder.
5. The system of claim 1 , wherein the attenuation factor is represented as η, wherein augmentation of the derivative of the input signal is accomplished as part of a detection algorithm implemented by the data detector, wherein the derivative of the input signal is represented by ideal, and wherein a branch metric of the detection algorithm is represented as:
(f*y−η(ideal)) 2 /N0,
wherein f*y is a filtered version of the data input, and wherein N 0 represents white noise.
6. The system of claim 1 , wherein the data detector processes the input signal without augmentation by the attenuation factor when the potential media defect is not indicated.
7. The system of claim 1 , wherein the data detector is a first data detector, and wherein the system further comprises:
a second data detector, wherein the second data detector processes a null data set when the potential media defect is indicated.
8. The system of claim 7 , wherein the second data detector provides a soft input, wherein the attenuation factor is represented as η, wherein augmentation of the input signal is accomplished as part of a detection algorithm implemented by the first data detector, and wherein a branch metric of the detection algorithm is represented as: (f*y−η(ideal)) 2 /N 0 plus the soft input.
9. The system of claim 7 , wherein an output of the second data detector is provided to a decoder, and wherein an output of the decoder is provided to the first data detector.
10. The system of claim 9 , wherein the decoder is a low density parity check decoder.
11. The system of claim 1 , wherein the medium is selected from a group consisting of: a magnetic storage medium, a wireless transmission medium, and a wired transmission medium.
12. A system for regenerating data, the system comprising:
a media defect detector, wherein the media defect detector is operable to identify a potential media defect associated with a medium from which an input signal is derived;
an attenuation amplitude detector, wherein the attenuation amplitude detector generates an attenuation factor;
a first data detector, wherein the first data detector processes a null data set when the potential media defect is indicated;
a decoder, wherein the decoder receives the output of the first detector and provides a soft input based on the output of the first detector; and
a second data detector, wherein the second data detector processes a derivative of the input signal augmented by the attenuation factor when the potential media defect is indicated.
13. The system of claim 12 , wherein the first data detector and the second data detector are selected from a group consisting of: a soft output Viterbi detector, and a maximum a posteriori detector.
14. The system of claim 12 , wherein the decoder is a low density parity check decoder.
15. The system of claim 12 , wherein the decoder is a first decoder, and wherein the system further comprises:
a second decoder operable to provide a decoded output reflecting a regenerated value of the input signal.
16. The system of claim 12 , wherein the attenuation factor is represented as η, wherein augmentation of the derivative of the input signal is accomplished as part of a detection algorithm implemented by the data detector, wherein the derivative of the input signal is represented by ideal, and wherein a branch metric of the detection algorithm is represented as:
(f*y−η(ideal)) 2 /N0+the soft input,
wherein f*y is a filtered version of the data input, and wherein N 0 represents white noise.
17. The system of claim 12 , wherein the second data detector is operable to process the input signal without augmentation by the attenuation factor when the potential media defect is not indicated.
18. The system of claim 12 , wherein the medium is selected from a group consisting of: a magnetic storage medium, a wireless transmission medium, and a wired transmission medium.
19. A method for regenerating data derived from a defective medium, the method comprising:
receiving a data input derived from a medium;
determining a media defect corresponding to the data input;
determining an attenuation factor associated with the media defect; and
based at least in part on the determination of the media defect, augmenting an amplitude of a signal derived from the data input by an amount corresponding to the attenuation factor to regenerate a data set from the storage medium.
20. The method of claim 19 , wherein the attenuation factor is represented as η, wherein the signal derived from the data input is represented by ideal, and wherein augmenting the amplitude of the signal derived from the data input is accomplished as part of a data detection algorithm done in accordance with the following equation:
(f*y−η(ideal)) 2 ,
wherein f*y is a filtered version of the data input.
21. The method of claim 20 , wherein augmenting the amplitude of the signal derived from the data input is done as part of calculating a branch metric used in relation to the data detection algorithm in accordance with the following equation:
(f*y−η(ideal)) 2 /N0,
wherein N 0 represents white noise.
22. The method of claim 21 , wherein the data input is a first data input, wherein the method further comprises:
receiving a second data input, wherein the second data input is derived from the medium;
determining that the medium is non-defective at the location corresponding to the second data input;
processing the second data input using a detector, wherein the branch metric of the detection algorithm is represented as: (f*y−ideal) 2 /N 0 .
23. The method of claim 20 , wherein the data detection algorithm is selected from a group consisting of: a soft output Viterbi algorithm, and a maximum a posteriori algorithm.
24. The method of claim 19 , wherein augmenting the amplitude of the signal derived from the data input is done by multiplying the signal derived from the data input by an amount corresponding to the attenuation factor.
25. The method of claim 24 , wherein amplifying the data input by a derivative of the attenuation factor is replaced by nullifying the data input in a first stage processing, wherein a soft input is generated that includes the nullified data input.
26. The method of claim 25 , wherein the method further comprises:
processing the soft input using a subsequent processing stage, wherein the attenuation factor is represented as η, wherein processing the soft input using the second stage includes processing the soft input using a data detection algorithm, and wherein the a branch metric of the detection algorithm is represented as: η 2 (f*y/η−ideal) 2 /N 0 plus the soft input, wherein the attenuation factor is represented as η, wherein the signal derived from the data input is represented by ideal, wherein f*y is a filtered version of the data input, and wherein N 0 represents white noise.