Determining channel characteristics in a wireless communication system that uses multi-element antenna

• US 6,925,131 B2
• Filed: 08/03/2001
• Issued: 08/02/2005
• Est. Priority Date: 08/03/2001
• Status: Active Grant

• Current Assignee: Lucent Technologies, Inc. (Nokia Corporation)
• Original Assignee: Lucent Technologies, Inc. (Nokia Corporation)
• Inventors: Viswanathan, Harish, Balakrishnan, Jaiganesh
• Primary Examiner(s): Bocure, Tesfaldet
• Application Number:
  US09/922,203
• Publication Number:
  US 20030058926A1
• Time in Patent Office: 1,460 Days
• Field of Search: 375/260, 375/267, 375/295, 375/299, 375/354, 375362-366, 370509-514, 455/91, 455/101
• US Class Current: 375/299
• CPC Class Codes: H04B 2201/70701 featuring pilot assisted reception
• CPC Class Codes: H04B 7/04 using two or more spaced independent antennas
• CPC Class Codes: H04L 25/0204 of multiple channels
• CPC Class Codes: H04L 25/0226 sounding signals per se
• CPC Class Codes: H04L 25/0242 using matrix methods

Abstract

A method and apparatus for increasing in the data rate of a multiple-input and/or multiple-output system that has frequency selective fading by using training sequences with both low normalized auto-correlation and low normalized cross-correlation. Both 1) the sum of the square of the normalized auto-correlation of each training sequence over an auto-correlation window and 2) the sum of the square of the normalized cross-correlation of each pair of the training sequences over a cross-correlation window, are significantly less than unity. In one embodiment of the invention the training sequences are shifted versions of each other, and the low normalized cyclic-auto-correlation of cyclic sequences is significantly less than unity, with each cyclic sequence being N′, N′=N−L+1, symbols of one of the at least two training sequences. In another embodiment, the training sequences are ones where the trace of the inverse of the product of the matrix of training sequences'"'"' symbols and the conjugate transpose of this matrix is low. The matrix is a function of the number of symbols over which multipaths of significant power can arrive, the number of training sequences, and the number of symbols in a training sequence. More particularly the matrix is a block-toeplitzmatrix composed of the training symbols.

Claims

1. A method for use in a system that is adapted to transmit a data burst over at least two antennas, the method comprising the step of:

transmitting at least two training sequences, each of the at least two training sequences being transmitted via a different respective one of said antennas,

each of the at least two training sequences having a normalized auto-correlation below an auto-correlation threshold, the auto-correlation threshold being significantly less than unity, and

each pair of the at least two training sequences having a normalized cross-correlation below a cross-correlation threshold, the cross-correlation threshold being significantly less than unity.

2. The method of claim 1, wherein each of the at least two training sequences having the normalized auto-correlation below the auto-correlation threshold comprises a sum of the squares of a normalized auto-correlation of one of the at least two training sequences over an auto-correlation window being below the auto-correlation threshold.

3. The method of claim 1, wherein each pair of the at least two training sequences having the normalized cross-correlation below the cross-correlation threshold comprises a sum of the squares of a normalized cross-correlation of the pair of the at least two training sequences over a cross-correlation window being below the cross-correlation threshold.

4. The method of claim 1, wherein the auto-correlation threshold is 0.06.

5. The method of claim 1, wherein the cross-correlation threshold is 0.12.

6. The method of claim 1, wherein:

the normalized auto-correlation is an auto-correlation normalized by the number of symbols in one of the training sequences, and

the normalized cross-correlation is a cross-correlation normalized by the number of symbols in one of the training sequences.

7. The method of claim 1, wherein the system exhibits frequency selective fading.

8. The method of claim 1, wherein:

the data burst includes a plurality of sub-streams, each sub-stream representing different bits than the other sub-streams of the plurality of sub-streams; and

at a particular time each of at least two of the sub-streams are transmitted over a different respective antenna of the at least two antennas.

9. The method of claim 1, wherein the cross-correlation is taken over a cross-correlation window of −

L+1 to 0 and 0 to L−

1, L being the number of symbols over which multipaths of significant power can arrive.

10. The method of claim 1, wherein the auto-correlation is taken over an auto-correlation window of −

L+1 to L−

1, excluding 0, L being the number of symbols over which multipaths of significant power can arrive.

11. The method of claim 1, wherein:

the system is adapted to transmit a plurality of data bursts; and

the transmitting step is repeated for each data burst.

12. A method for use in a system that is adapted to transmit a data burst over at least two antennas, the method comprising the step of:

transmitting at least two training sequences, each of the at least two training sequences being transmitted via a different respective one of said antennas,

the training sequences being shifted versions of each other,

with each cyclic sequence having a normalized cyclic-auto-correlation below a cyclic-auto-correlation threshold, each cyclic sequence being N′

, N′

=N−

L+1, symbols of one of the at least two training sequences, the cyclic-auto-correlation threshold being significantly less than unity, L being the number of symbols over which multipaths of significant power can arrive, and N being the number of symbols in one of the training sequences.

13. The method of claim 12, wherein each cyclic sequence having the normalized cyclic-auto-correlation below the cyclic-auto-correlation threshold comprises a sum of the squares of a normalized cyclic-auto-correlation of one of the cyclic sequences over a cyclic-auto-correlation window being below the cyclic auto-correlation threshold.

14. The method of claim 12, wherein the cyclic-auto-correlation threshold comprises 0.2.

15. The method of claim 12, wherein the normalized cyclic-auto-correlation is a cyclic-auto-correlation normalized by N′

.

16. The method of claim 12, wherein the system exhibits frequency selective fading.

17. The method of claim 12, wherein:

the data burst includes a plurality of sub-streams, each sub-stream representing different bits than the other sub-streams of the plurality of sub-streams; and

at a particular time each of at least two of the sub-streams are transmitted over a different respective antenna of the at least two antennas.

18. The method of claim 12, wherein:

the system is adapted to transmit a plurality of data bursts; and

the transmitting step is repeated for each data burst.

19. A method for use in a system that is adapted to transmit a data burst over at least two antennas, the method comprising the step of:

transmitting at least two training sequences, each of the at least two training sequences being transmitted via a different respective one of said antennas,

a trace of an inverse of a product of a matrix of symbols of the at least two training sequences and a conjugate transpose of the matrix is below a trace threshold,

the trace threshold being below 5 ML/(N−

L+1), L being the number of symbols over which multipaths of significant power can arrive, M being the number of training sequences, and N being the number of symbols in one of the training sequences.

20. The method of claim 19, wherein the trace threshold is 1.2 ML/(N−

L+1).

21. The method of claim 19, wherein the matrix is a function of at least one of the following:

the number of symbols over which multipaths of significant power can arrive;

the number of training sequences; and

the number of symbols of one of the training sequences.

22. The method of claim 19, wherein matrix is a block-toepliz matrix.

23. The method of claim 22, wherein the block-toepliz matrix includes:

M blocks, M being the number of training sequences,

each block having L columns, L being the number of symbols over which multipaths of significant power can arrive, and

each block having N−

L+1 rows, N being the number of symbols in one training sequence.

24. The method of claim 19, wherein the system exhibits frequency selective fading.

25. The method of claim 19, wherein:

the system is adapted to transmit a plurality of data bursts; and

the transmitting step is repeated for each data burst.

26. A transmitter adapted to be coupled to at least two antennas,

the transmitter being further adapted to transmit at least two training sequences, each of the at least two training sequences being transmitted via a different respective one of said antennas,

each of the at least two training sequences having a normalized auto-correlation below an auto-correlation threshold, the auto-correlation threshold being significantly less than unity, and

each pair of the at least two training sequences having a normalized cross-correlation below a cross-correlation threshold, the cross-correlation threshold being significantly less than unity.

27. The transmitter of claim 26, wherein each of the at least two training sequences having the normalized auto-correlation below the auto-correlation threshold comprises a sum of the squares of a normalized auto-correlation of one of the at least two training sequences over an auto-correlation window being below the auto-correlation threshold.

28. The transmitter of claim 26, wherein each pair of the at least two training sequences having the normalized cross-correlation below the cross-correlation threshold comprises a sum of the squares of a normalized cross-correlation of the pair of the at least two training sequences over a cross-correlation window being below the cross-correlation threshold.

29. The transmitter of claim 26, wherein the auto-correlation threshold is 0.06.

30. The transmitter of claim 26, wherein the cross-correlation threshold is 0.12.

31. The transmitter of claim 26, wherein the transmitter is adapted for use in a system having frequency selective fading.

32. The transmitter of claim 26, wherein:

the normalized auto-correlation is an auto-correlation normalized by the number of symbols in one of the training sequences, and

the normalized cross-correlation is a cross-correlation normalized by the number of symbols in one of the training sequences.

33. The transmitter of claim 26, wherein the cross-correlation is taken over a window of −

L+1 to 0 and 0 to L−

1, L being the number of symbols over which multipaths of significant power can arrive.

34. The transmitter of claim 26, wherein the auto-correlation is taken over a window of −

L+1 to L−

1, excluding 0, L being the number of symbols over which multipaths of significant power can arrive.