Spatial processing and timing estimation using a training sequence in a radio communications system

• US 20020150182A1
• Filed: 04/24/2001
• Published: 10/17/2002
• Est. Priority Date: 11/30/2000
• Status: Active Grant

• Current Assignee: Intel Corporation
• Original Assignee: ArrayComm LLC (Ygomi LLC)
• Inventors: Petrus, Paul, Trott, Mitchell D., Dogan, Mithat C.
• Granted Patent: US 6,650,714 B2
• Time in Patent Office: Days
• US Class Current: 375/343
• CPC Class Codes: H04B 7/0851 using training sequences or error signal minimizing error signal H04B7/0854
• CPC Class Codes: H04L 27/18 Phase-modulated carrier systems, i.e. using phase-shift keying H04L27/32 takes precedence

Abstract

A method and apparatus are provided that performs spatial processing, timing estimation and frequency offset using a training sequence of a received burst. According to one aspect of the present invention, the invention includes receiving a burst having a known training sequence at a set of diversity antennas, sampling the received burst at each antenna, determining a coarse timing estimate for samples from at least one antenna, and determining a spatial weighting vector using the coarse timing estimate. The embodiment further includes applying the spatial weighting vector to the received burst samples for each antenna to form a single channel signal, determining a fine timing estimate for the single channel signal, determining a second spatial weighting vector using the fine timing estimate, applying the second spatial weighting vector to the received burst samples for each antenna to form a second single channel signal, and demodulating the second single channel signal.

Claims

1. A method comprising:

receiving a burst having a known training sequence at a set of diversity antennas;

sampling the received burst at each antenna;

determining a coarse timing estimate for samples from at least one antenna;

determining a spatial weighting vector using the coarse timing estimate;

applying the spatial weighting vector to the received burst samples for each antenna to form a single channel signal;

determining a fine timing estimate for the single channel signal;

determining a second spatial weighting vector using the fine timing estimate;

applying the second spatial weighting vector to the received burst samples for each antenna to form a second single channel signal; and

demodulating the second single channel signal.

2. The method of claim 1, further comprising determining a frequency offset estimate for the second single channel signal and wherein determining a second spatial weighting vector includes using the frequency offset estimate.

3. The method of claim 2, wherein determining a frequency offset comprises calculating cross correlation vectors for a plurality of candidate offsets based on a portion of the samples and selecting a candidate corresponding to a peak of the cross-correlation function.

4. The method of claim 1, further comprising refining the coarse timing estimate by analyzing hypothetical timing estimates proximate the coarse timing estimate.

5. The method of claim 1, wherein determining a coarse timing estimate comprises:

calculating a cross correlation vector for a portion of the samples with respect to a selected part of the training sequence, each cross correlation vector corresponding to a relative timing hypothesis and each cross correlation vector combining samples that occur at intervals within an analysis window;

calculating a least squares fit for each hypothesis using the calculated cross correlation vectors; and

selecting the combination of samples corresponding to the minimal least squares fit as the coarse timing of the received burst.

6. The method of claim 5, wherein calculating a least squares fit comprises comparing a hypothetical received sequence to the known sequence for each hypothesis.

7. The method of claim 6, wherein the hypothetical received sequence is determined based on the cross correlation vector and a Cholesky factor.

8. The method of claim 5, wherein calculating a cross correlation vector comprises calculating a cross correlation vector for a portion of evenly spaced ones of the samples.

9. The method of claim 1, wherein determining a fine timing estimate further comprises determining the fine timing of the selected sample by applying a timing estimation algorithm to an interpolated sequence of the samples.

10. A machine-readable medium having stored thereon data representing sequences of instructions which, when executed by a machine, cause the machine to perform operations comprising comprising:

receiving a burst having a known training sequence at a set of diversity antennas;

sampling the received burst at each antenna;

determining a coarse timing estimate for samples from at least one antenna;

determining a spatial weighting vector using the coarse timing estimate;

applying the spatial weighting vector to the received burst samples for each antenna to form a single channel signal;

determining a fine timing estimate for the single channel signal;

determining a second spatial weighting vector using the fine timing estimate;

applying the second spatial weighting vector to the received burst samples for each antenna to form a second single channel signal; and

demodulating the second single channel signal.

11. The medium of claim 10, further comprising instructions which, when executed by the machine, cause the machine to perform further operations comprising determining a frequency offset estimate for the second single channel signal and wherein determining a second spatial weighting vector includes using the frequency offset estimate.

12. The medium of claim 11, wherein the instructions for determining a frequency offset further comprise instructions which, when executed by the machine, cause the machine to perform further operations comprising calculating cross correlation vectors for a plurality of candidate offsets based on a portion of the samples and selecting a candidate corresponding to a peak of the cross-correlation function.

13. The medium of claim 10, further comprising instructions which, when executed by the machine, cause the machine to perform further operations comprising refining the coarse timing estimate by analyzing hypothetical timing estimates proximate the coarse timing estimate.

14. The medium of claim 10, wherein the instructions for determining a coarse timing estimate further comprise instructions which, when executed by the machine, cause the machine to perform further operations comprising:

calculating a cross correlation vector for a portion of the samples with respect to a selected part of the training sequence, each cross correlation vector corresponding to a relative timing hypothesis and each cross correlation vector combining samples that occur at intervals within an analysis window;

calculating a least squares fit for each hypothesis using the calculated cross correlation vectors; and

selecting the combination of samples corresponding to the minimal least squares fit as the coarse timing of the received burst.

15. The medium of claim 14, wherein the instructions for calculating a least squares fit further comprise instructions which, when executed by the machine, cause the machine to perform further operations comprising comparing a hypothetical received sequence to the known sequence for each hypothesis.

16. The medium of claim 15, wherein the hypothetical received sequence is determined based on the cross correlation vector and a Cholesky factor.

17. The medium of claim 14, wherein the instructions for calculating a cross correlation vector further comprise instructions which, when executed by the machine, cause the machine to perform further operations comprising calculating a cross correlation vector for a portion of evenly spaced ones of the samples.

18. The method of claim 10, wherein the instructions for determining a fine timing estimate further comprise instructions which, when executed by the machine, cause the machine to perform further operations comprising determining the fine timing of the selected sample by applying a timing estimation algorithm to an interpolated sequence of the samples.

20. The apparatus of claim 19, further comprising means for determining a frequency offset estimate for the second single channel signal and wherein the means for determining a second spatial weighting vector includes means for using the frequency offset estimate.

19. An apparatus comprising:

a set of diversity antennas to receive a burst having a known training sequence;

means for sampling the received burst at each antenna;

means for determining a coarse timing estimate for samples from at least one antenna;

means for determining a spatial weighting vector using the coarse timing estimate;

means for applying the spatial weighting vector to the received burst samples for each antenna to form a single channel signal;

means for determining a fine timing estimate for the single channel signal;

means for determining a second spatial weighting vector using the fine timing estimate;

means for applying the second spatial weighting vector to the received burst samples for each antenna to form a second single channel signal; and

means for demodulating the second single channel signal.