Detection of Data in Signals with Data Pattern Dependent Signal Distortion

• US 20100232809A1
• Filed: 03/05/2010
• Published: 09/16/2010
• Est. Priority Date: 03/10/2009
• Status: Active Grant

• Current Assignee: SubCom, LLC
• Original Assignee: Tyco Electronics Subsea Communications LLC (TE Connectivity Limited)
• Inventors: Nissov, Morten, Pilipetskii, Alexei N., Cai, Yi
• Granted Patent: US 8,401,400 B2
• Time in Patent Office: Days
• US Class Current: 398/202
• CPC Class Codes: H04B 10/2507 for the reduction or elimination of distortion or dispersion
• CPC Class Codes: H04B 10/697 Arrangements for reducing noise and distortion
• CPC Class Codes: H04J 14/02 Wavelength-division multiplex systems
• CPC Class Codes: H04J 14/0279 WDM point-to-point architectures

Abstract

A detection system and method may be used to detect data transmitted in a signal with data pattern dependent signal distortion. In general, a detection system and method compares samples of a received signal with stored samples of distorted signals associated with known data patterns and selects the known data patterns that correspond most closely with the samples of the received signal. The detection system and method may thus mitigate the effects of data pattern dependent signal distortion.

Claims

1. A system for detecting data in a signal with data pattern dependent signal distortion, the system comprising:

a distorted signal table configured to store a plurality of known data patterns and samples of distorted signals associated with the known data patterns;

a data shift register configured to obtain samples of a received signal within a shifting data pattern window having a length corresponding to a length of the known data patterns; and

a detector configured to compare the samples in the data pattern window with the samples in the distorted signal table and to select the known data patterns in the distorted signal table that correspond most closely with the samples in the data pattern window.

2. The system of claim 1 further comprising a trainer configured to generate the samples associated with the known data patterns stored as the distorted signal table.

3. The system of claim 2 wherein the trainer is configured to receive signal samples associated with a training data sequence, to arrange the received signal samples into data pattern dependent sets based on data patterns, and to store the received signal samples as the distorted signal table indexed by the data patterns.

4. The system of claim 1 further comprising a soft decision forward error correction (FEC) decoder configured to receive a soft-decision data stream from the detector and to decode encoded data represented by the soft decision data stream to produce decoded data.

5. The system of claim 4 wherein the soft decision FEC decoder is configured to provide feedback to the detector, and the detector is configured to adjust the soft-decision data stream in response to the feedback.

6. The system of claim 1 wherein the distorted signal table is an N-bit signal table configured to store N-bit data patterns having a predetermined number (N) of bits, and wherein the data pattern window is an N-bit window.

7. The system of claim 1 wherein the detector is configured to provide maximum a posteriori probability (MAP) detection.

8. The system of claim 1 wherein the detector is configured to compare the samples and select the known data patterns by calculating Euclidean distances between the samples in the data pattern window and the samples in the distorted signal table and by selecting the samples in the distorted signal table having the minimum Euclidean distances.

9. The system of claim 1 wherein the received signal is an electrical signal converted from a modulated optical signal on which data is modulated using phase shift keying, and wherein the samples represent a phase of each symbol in the modulated optical signal.

21. The system of claim 1 wherein the transmitted signal transmits data at about 100 Gb/s.

10. A digital signal processor (DSP) based receiver comprising:

a coherent receiver configured to receive, detect and digitize a modulated optical signal to produce received signal samples; and

a DSP configured to store a distorted signal table including a plurality of known data patterns and samples of distorted signals associated with the known data patterns, to obtain samples of a received signal within a shifting data pattern window having a length corresponding to a length of the known data patterns, to compare the samples in the data pattern window with the samples in the distorted signal table, and to select the known data patterns in the distorted signal table that correspond most closely with the samples in the data pattern window.

11. The DSP based receiver of claim 10 wherein the modulated optical signal is modulated using phase shift keying, and wherein each of the samples represent a phase of the modulated optical signal.

12. The DSP based receiver of claim 10 wherein the distorted signal table is an N-bit signal table configured to store N-bit data patterns having a predetermined number (N) of bits, and wherein the data pattern window is an N-bit window.

13. The DSP based receiver of claim 10 wherein the DSP is configured to receive signal samples associated with a training data sequence, to arrange the received signal samples into data pattern dependent sets based on data patterns, and to store the received signal samples as the distorted signal table indexed by the data patterns.

14. The DSP based receiver of claim 10 further comprising a soft decision forward error correction (FEC) decoder configured to receive a soft-decision data stream from the detector and to decode encoded data represented by the soft decision data stream to produce decoded data.

15. A detection method for detecting data in a signal with data pattern dependent signal distortion, the method comprising:

providing a distorted signal table including a plurality of known data patterns and samples of distorted signals associated with the known data patterns;

receiving a digitized signal including a plurality of digitized samples;

processing the digitized signal in a digital signal processor to obtain a segment of samples in the received signal having a length corresponding to a length of the known data patterns, to compare the samples in the segment of the received signal with the samples associated with the known signal patterns, and to select the data patterns in the distorted signal table that correspond most closely with the samples in the segment of the received signal.

16. The detection method of claim 15 wherein the known data patterns are N-bit data patterns having a predetermined number (N) of bits.

17. The detection method of claim 15 wherein comparing the samples includes calculating Euclidean distances between the samples in the segment of the received signal and the samples in the distorted signal table, and wherein selecting the data patterns includes selecting data patterns associated with the samples in the distorted signal table having the minimum Euclidean distances.

18. The detection method of claim 15 further comprising:

updating the known data patterns and samples of distorted signals associated with the known data patterns.

19. A training method for training a system for detecting data in a signal with data pattern dependent signal distortion, the method comprising:

receiving in a receiver a signal representing a training data sequence;

digitizing the received signal to produce signal samples associated with the training data sequence; and

processing the digitized received signal in a digital signal processor to arrange the received signal samples into data pattern dependent sets based on data patterns and to store the received signal samples as a distorted signal table indexed by the data patterns.

20. The training method of claim 19 further comprising averaging the samples in each of the data pattern dependent sets.