Methods and systems for symbol estimation in a receiver

• US 6,301,315 B1
• Filed: 12/22/1999
• Issued: 10/09/2001
• Est. Priority Date: 12/22/1999
• Status: Expired due to Term

• Current Assignee: AT&T Corporation (AT&T, Inc.)
• Original Assignee: AT&T Corporation (AT&T, Inc.)
• Inventors: Li, Ye
• Primary Examiner(s): Pham, Chi
• Assistant Examiner(s): PHU, PHUONG M
• Application Number:
  US09/469,482
• Time in Patent Office: 657 Days
• Field of Search: 375/346, 375/350, 375/229, 375/262, 375/287, 375/284, 375/285, 375/340, 375/341, 375/343
• US Class Current: 375/346
• CPC Class Codes: H04L 25/03006 Arrangements for removing intersymbol interference

Abstract

The present invention provides systems and methods for mitigating interference on a received signal by providing an equalizer having a truncated response time preceded by a linear filter which compensates for the truncated response time. The invention also provides methods and systems for mitigating the interference on a received signal by providing a receiver having a filter, an equalizer with a truncated response time and a symbol mapper using a symbol mapping technique that takes advantage of noise correlation produced by the equalizer by adjusting symbol mapping boundaries accordingly.

Claims

1. A method for extracting symbols from a received signal containing symbol information, comprising:

filtering the received signal;

estimating a plurality of observed vectors based on the filtered signal, wherein each observed vector has a symbol portion and a noise portion; and

determining at least a first symbol by using a symbol portion of a first observed vector of the plurality of observed vectors and at least one or more noise portions of at least one or more other observed vectors, wherein the step of determining includes adjusting a decision space that maps the symbol portion of the first observed vector to at least one or more symbol points in a constellation of symbol points based on the correlation of the first observed vector and the at least one or more noise portions of at least one or more other observed vectors.

2. The method of claim 1, wherein the step of determining at least a first symbol is further based on a correlation of a noise portion of the first observed vector and the at least one or more noise portions of at least one or more other observed vectors.

3. The method of claim 1, wherein the steps of estimating and mapping are performed using a Viterbi technique.

4. A method for extracting symbols from a received signal containing symbol information, comprising:

filtering the received signal using a linear filter and, wherein the frequency response of the linear filter is further based on a response time of the estimation step, wherein the received signal has at least a symbol information portion and a noise portion, and the linear filter substantially maximizes a signal to noise ratio of the received signal at substantially all frequency components;

estimating a plurality of symbol vectors using the filtered signal; and

mapping the plurality of symbol vectors to symbols as the extracted symbols.

5. The method of claim 4, wherein the received signal further has an interference portion, and the linear filter substantially maximizes a signal to noise plus interference ratio of the received signal at substantially all frequency components.

6. The method of claim 4, wherein the frequency response of the linear filter is performed according to the following formula:

$H_{\mathrm{linear}}<br><br>\left(\mathrm{\omega <br><br>}\right)=\frac{1}{r<br><br>\left(\mathrm{\omega <br><br>}\right)+N_o<br><br>\mathrm{\Delta <br><br>}},$

wherein r(ω

) is a measure of the received signal, N_o is the average white Gaussian noise (AWGN) of the received signal, and Δ

is a number ranging from 0 to 1.

7. The method of claim 4, wherein the steps of estimating and mapping use a Viterbi technique.

8. The method of claim 4, wherein the steps of filtering, estimating and mapping use a Viterbi technique.

9. The method of claim 5, wherein the signal to noise plus interference ratio is based on at least co-channel interference.

10. The method of claim 4, wherein the step of estimating uses an estimator having a response substantially shorter than an impulse response of the received signal.

11. The method of claim 10, wherein the estimator is based on a maximum likelihood sequence estimation (MLSE) technique.

12. A symbol estimation device for extracting symbols from a received signal containing symbol information, comprising:

a receive filter for filtering the received signal;

an estimation device that uses the filtered signal to estimate a plurality of observed vectors, wherein each observed vector has a symbol portion and a noise portion; and

a decision making device that determines at least a first symbol using the symbol portion of a first observed vector of the plurality of observed vectors and one or more of the noise portions of one or more other observed vectors, wherein the decision making device determines the at least the first symbol by adjusting a decision space that maps the symbol portion of the first observed vector to at least one or more symbol points in a constellation of symbol points based on the correlation of the first observed vector and the at least one or more noise portions of at least one or more other observed vectors.

13. The device of claim 12, wherein the decision making device further determines at least the first symbol based on a correlation of a noise portion of the first observed vector and the at least one or more noise portions of at least one or more other observed vectors.

14. The device of claim 12, wherein the estimation device and the decision making device are implemented using a Viterbi technique.

15. A symbol estimation device for extracting symbols from a received signal containing symbol information, comprising:

a linear filter that filters the received signal and, wherein the frequency response of the linear filter is further based on a response time of the estimation step, wherein the received signal has at least a symbol information portion and a noise portion, and the linear filter substantially maximizes a signal to noise ratio of the received signal at substantially all frequency components;

an estimation device that estimates a plurality of symbol vectors using the filtered signal; and

a decision making device that maps the plurality of symbol vectors to symbols as the extracted symbols.

16. The device of claim 15, wherein the received signal further has an interference portion, and the linear filter substantially maximizes a signal to noise plus interference ratio of the received signal at substantially all frequency components.

17. The device of claim 15, wherein the frequency response of the linear filter is performed according to the following formula:

$H_{\mathrm{linear}}<br><br>\left(\mathrm{\omega <br><br>}\right)=\frac{1}{r<br><br>\left(\mathrm{\omega <br><br>}\right)+N_o<br><br>\mathrm{\Delta <br><br>}},$

wherein r(ω

) is a measure of the received signal, N_o is the average white Gaussian noise (AWGN) of the received signal, and Δ

is a number ranging from 0 to 1.

18. The device of claim 15, wherein the estimation device and the decision making device use a Viterbi technique.

19. The device of claim 15, wherein linear filter, the estimation device and the decision making device use a Viterbi technique.

20. The method of claim 16, wherein the signal to noise plus interference ratio is based on at least co-channel interference.

21. The method of claim 15, wherein the estimation device has a response substantially shorter than the impulse response of the received signal.

22. The method of claim 21, wherein the estimation device is based on a maximum likelihood sequence estimation (MLSE) technique.