REDUCED COMPLEXITY SLIDING WINDOW BASED EQUALIZER

• US 20100067620A1
• Filed: 09/23/2009
• Published: 03/18/2010
• Est. Priority Date: 03/03/2003
• Status: Abandoned Application

• Current Assignee: Interdigital Technology Corporation (InterDigital, Inc.)
• Original Assignee: Interdigital Technology Corporation (InterDigital, Inc.)
• Inventors: Yang, Rui, Reznik, Alexander, Zeira, Ariela, Li, Bin
• Application Number:
  US12/565,284
• Publication Number:
  US 20100067620A1
• Time in Patent Office: Days
• US Class Current: 375/340
• CPC Class Codes: H04B 1/71052 using decorrelation matrix
• CPC Class Codes: H04L 2025/03426 transmission using multiple-input and multiple-output channels
• CPC Class Codes: H04L 2025/03509 fractionally spaced H04L2025/03515 takes precedence
• CPC Class Codes: H04L 2025/03605 Block algorithms
• CPC Class Codes: H04L 25/0212 of impulse response
• CPC Class Codes: H04L 25/0242 using matrix methods
• CPC Class Codes: H04L 25/03057 with a recursive structure H04L25/03031 takes precedence
• CPC Class Codes: H04L 25/03292 with channel estimation circuitry

Abstract

A method and apparatus for use in data estimation in wireless communication are provided. A wireless communications signal is received and transformed to produce a received vector. The received vector is processed using a sliding window based approach that includes processing each of a plurality of windows. For each window, an approximate circulant channel response matrix is produced for use in estimating a data vector corresponding to the window.

Claims

1. An apparatus for use in wireless communication comprising:

a receiver configured to transform a received wireless communications signal to produce a received vector by sampling at a multiple of a data signal chip rate; and

a processor configured to process the received vector using a sliding window based approach, such that for each processing window in a plurality of processing windows an approximate circulant channel response matrix is produced and used to estimate a data vector corresponding to the window.

3. The apparatus of claim 1, further comprising:

a root-raised cosine filtering unit configured to apply a root-raised cosine filter to the received vector.

4. The apparatus of claim 1, wherein the processor is configured to ignore noise cross correlation.

5. The apparatus of claim 1, wherein the processor is configured to use the received vector and the approximate circulant channel response matrix arranged in a natural order.

6. The apparatus of claim 1, wherein the receiver is configured to transform a plurality of received wireless communications signals from a plurality of antennas to produce a received vector.

7. The apparatus of claim 1, wherein the processor is configured to multiply a discrete Fourier transform of a pulse shaping filter by a measured noise variance to produce a discrete Fourier transform of the noise vector cross correlation.

8. The apparatus of claim 1, wherein the processor is configured to multiply a discrete Fourier transform of an ideal pulse shape by a measured noise variance to produce a discrete Fourier transform of the noise vector cross correlation.

9. The apparatus of claim 1, further comprising:

a summer, configured to combine the data vector corresponding to each window to form a combined data vector.

10. The apparatus of claim 1 configured as a wireless transmit/receive unit (WTRU).

11. The apparatus of claim 1 configured as a base station.

2. (canceled)

12. A method for use in wireless communications, the method comprising:

transforming a received wireless communications signal to produce a received vector by sampling at a multiple of a data signal chip rate; and

processing the received vector using a sliding window based approach, such that for each processing window in a plurality of processing windows an approximate circulant channel response matrix is produced and used to estimate a data vector corresponding to the window.

14. The method of claim 12, further comprising:

applying a root-raised cosine filter to the received vector.

15. The method of claim 12, wherein the processing includes ignoring noise cross correlation.

16. The method of claim 12, wherein the processing includes using the received vector and the approximate circulant channel response matrix arranged in a natural order.

17. The method of claim 12, wherein the transforming includes producing a plurality of received vectors corresponding to a plurality of received wireless communications signals from a plurality of antennas.

18. The method of claim 12, wherein the processing includes multiplying a discrete Fourier transform of the pulse shaping filter by a measured noise variance to produce a discrete Fourier transform of the noise vector cross correlation.

19. The method of claim 12, wherein the processing includes multiplying a discrete Fourier transform of an ideal pulse shape by a measured noise variance to produce a discrete Fourier transform of the noise vector cross correlation.

20. The method of claim 12, further comprising:

combining the data vector corresponding to each window to form a combined data vector.

13. (canceled)