Adaptive channel estimation in a wireless communication system

• US 6,985,469 B2
• Filed: 06/27/2002
• Issued: 01/10/2006
• Est. Priority Date: 08/23/1999
• Status: Expired due to Term

• Current Assignee: Qualcomm, Inc.
• Original Assignee: Qualcomm, Inc.
• Inventors: Leung, Gilbert
• Primary Examiner(s): Pezzlo, John
• Assistant Examiner(s): Tsegaye, Saba
• Application Number:
  US10/185,785
• Publication Number:
  US 20020167913A1
• Time in Patent Office: 1,293 Days
• Field of Search: 370/206, 370/252, 370/310, 370/318, 370/320, 370/335, 370/500, 375/135, 375/144, 375147-148, 375/130
• US Class Current: 370/335
• CPC Class Codes: H04B 1/707 using direct sequence modulation
• CPC Class Codes: H04B 2201/70701 featuring pilot assisted reception
• CPC Class Codes: H04L 25/0202 Channel estimation

Abstract

A method and circuit for adaptively estimating channel conditions of a pilot channel in a wireless communication system. The method includes estimating channel statistics of the pilot channel, and adaptively filtering the pilot channel in response to the estimated channel statistics. The estimation is performed by filtering a channel signal derived from the pilot channel to determine an estimated channel mean and an estimated channel covariance. In order to perform the adaptive filtering, the present invention partitions the pilot channel into one or more time slots and weights each time slot according to the channel statistics. Thus, an advantage of the present invention is that it automatically and continually updates the pilot filter parameters in order to optimize the pilot filter performance over a broad range of channel conditions.

Claims

1. A method for adaptively estimating channel conditions of a pilot channel in a wireless communication system, the method comprising the steps of:

partitioning pilot channel data from said pilot channel into one or more time slots;

estimating channel statistics of said pilot channel, wherein said estimating step comprises filtering a channel signal derived from any received communication channels to determine an estimated channel mean and an estimated channel covariance; and

adaptively filtering said pilot channel data using said one or more time slots based in part on said estimated channel statistics.

2. The method as in claim 1, wherein the one or more time slots are of equal duration.

3.The method as in claim 1, wherein the one or more time slots are of unequal duration.

3. The method of claim 1 wherein said step of filtering said channel signal comprises filtering said channel signal in an infinite impulse response filter.

4. The method of claim 1 wherein said step of filtering said channel signal comprises filtering said channel signal in a combination of infinite impulse response and finite impulse response filters.

5. The method as in claim 1, wherein estimating channel statistics further comprises:

generating the estimated channel mean, ^{{circumflex over (m)}y[n]}, according to the following relationship;

{circumflex over (m)}_y[n]=g₁*y[n]

wherein g₁ is a filter impulse response and * represents convolution in the time domain.

9. The method as in claim 1, wherein estimating channel statistics further comprises:

generating ^{{circumflex over (K)}xy}, an estimated covariance of a desired channel signal x, according to the following relationship;

{circumflex over (K)}_xy[l,n]=g₂*((x[l]−

{circumflex over (m)}_x[l])(y[n]−

{circumflex over (m)}_y[n])*)

wherein g₂ is a filter impulse response, l and n are the row and column vector indices, respectively; and

the superscript * is the complex conjugate.

13. The method as in claim 1, wherein estimating channel statistics further comprises:

generating ^{{circumflex over (K)}yy} , an estimated covariance of received channel signal y[n] vector, according to the following relationship;

{circumflex over (K)}_yy[l,n]=g₃*((y[l]−

{circumflex over (m)}_y[l])(y[n]−

{circumflex over (m)}_y[n])*)

wherein g₃ is a filter impulse response, l and n are row and column vector indices and the superscript * denotes complex conjugate.

17. The method of claim 1 wherein said step of filtering channel signal further comprises the steps of:

weighting a first received communication channel signal with a first weighting factor;

weighting a second received communication channel signal with a second weighting factor; and

combining said first and second weighted received communication channel signals to generate said channel signal.

18. The method of claim 1 wherein said step of estimating further comprises combining a plurality of channel signals from a plurality of rake receiver fingers.

6. The method as in claim 6, wherein generating the estimated channel mean is performed by a Finite Impulse Response (FIR) type filter.

7. The method as in claim 6, wherein generating the estimated channel mean is performed by an Infinite Impulse Response (IIR) type filter.

8. The method as in claim 6, wherein generating the estimated channel mean is performed by a combination of an Infinite Impulse Response (IIR) type filter and a Finite Impulse Response (FIR) type filter.

10. The method as in claim 10, wherein generating the estimated channel mean is performed by a Finite Impulse Response (FIR) type filter.

11. The method as in claim 10, wherein generating the estimated channel mean is performed by an Infinite Impulse Response (IIR) type filter.

12. The method as in claim 10, wherein generating the estimated channel mean is performed by a combination of an Infinite Impulse Response (IIR) type filter and a Finite Impulse Response (FIR) type filter.

14. The method as in claim 14, wherein generating the estimated channel mean is performed by a Finite Impulse Response (FIR) type filter.

15. The method as in claim 14, wherein generating the estimated channel mean is performed by an Infinite Impulse Response (IIR) type filter.

16. The method as in claim 14, wherein generating the estimated channel mean is performed by a combination of an Infinite Impulse Response (IIR) type filter and a Finite Impulse Response (FIR) type filter.

19. An apparatus for adaptively estimating channel conditions in a wireless communication system, the method comprising the steps of:

means for partitioning channel data from a channel into one or more time slots;

means for estimating channel statistics of said channel, wherein said estimating means comprises means for filtering a channel signal derived from any received communication channels to determine an estimated channel mean and an estimated channel covariance; and

means for adaptively filtering said channel data using said one or more time slots based in part on said estimated channel statistics.

20. The apparatus as in claim 20, wherein the means for estimating channel statistics further comprises:

means for generating the estimated channel mean, ^{{circumflex over (m)}y[n]}, according to the following relationship;

{circumflex over (m)}_y[n]=g₁*y[n]

wherein g₁ is a filter impulse response and * represents convolution in the time domain.

21. The apparatus as in claim 20, wherein the means for estimating channel statistics further comprises:

means for generating ^{{circumflex over (K)}xy}, an estimated covariance of a desired channel signal x, according to the following relationship;

{circumflex over (K)}_xy[l,n]=g₂*((x[l]−

{circumflex over (m)}_x[l])y[n]−

{circumflex over (m)}_y[n])*)

wherein g₂ is a filter impulse response, l and n are the row and column vector indices, respectively; and

the superscript * denotes the complex conjugate.

22. The apparatus as in claim 20, wherein the means for estimating channel statistics further comprises:

means for generating ^{{circumflex over (K)}yy}, an estimated covariance of received channel signal y[n] vector, according to the following relationship;

{circumflex over (K)}^yy[l,n]=g₃*((y[l]−

{circumflex over (m)}_y[l])(y[n]−

{circumflex over (m)}_y[n])*)

wherein g₃ is a filter impulse response, l and n are row and column vector indices and the superscript * denotes complex conjugate.

23. The apparatus as in claim 23, wherein the estimated covariance is conjugate symmetric, and satisfies:

{circumflex over (K)}_yy[l,n]={circumflex over (K)}_yy*[n,l]

24. The apparatus as in claim 23, wherein the time slots are of equal duration and for any integer value k, the estimated covariance satisfies:

{circumflex over (K)}_yy[l,n]={circumflex over (K)}_yy[l+k,n+k].

25. A circuit for adaptively estimating channel conditions of a pilot channel in a wireless communication system, the circuit comprising:

a data buffer to partition pilot channel data from said pilot channel into one or more time slots;

channel statistics estimator that estimates channel statistics of said pilot channel, wherein said channel statistics estimator filters a channel signal derived from any received communication channels to determine an estimated channel mean and an estimated channel covarince; and

an adaptive pilot filter that adaptively filters said pilot channel data using said one or more time slots based in part on said estimated channel statistics;

wherein said channel statistics estimator filters a channel signal derived from said pilot channel to determine an estimated channel mean and an estimated channel covariance.

26. The circuit of claim 26, wherein said channel statistics estimator comprises an infinite impulse response filter for filtering said channel signal.

27. The circuit of claim 26, wherein said channel statistics estimator comprises a combination of infinite impulse response and finite impulse response filters for filtering said channel signal.

28. The circuit as in claim 26, wherein the one or more time slots comprises a plurality of time slots, wherein the plurality of time slots includes different length time slots.

29. The circuit of claim 26, wherein said channel statistics estimator weights a first received communication channel signal with a first weighting factor;

weighs a second received communication channel signal with a second weighting factor; and

combines said first and second weighted received communication channel signals to generate said channel signal.

30. The circuit of claim 26, wherein said channel statistics estimator combines a plurality of channel signals from a plurality of rake receiver fingers.

31. The circuit as in claim 26, wherein the channel statistics estimator further comprises:

a channel means estimator for generating the estimated channel mean, ^{{circumflex over (m)}y}[n], according to the following relationship;

{circumflex over (m)}_y[n]=g₁*y[n]

wherein g₁ is a filter impulse response and * represents convolution in the time domain.

32. The circuit as in claim 26, wherein the channel statistics estimator further comprises:

a covariance estimator for generating ^{{circumflex over (K)}xy}, an estimated covariance of a desired channel signal x, according to the following relationship;

{circumflex over (K)}_xy[l,n]=g₂*((x[l]−

{circumflex over (m)}_x[l])(y[n]−

{circumflex over (m)}_y[n])*)

wherein g₂ is a filter impulse response, l and n are the row and column vector indices, respectively; and

the superscript * denotes the complex conjugate.

33. The circuit as in claim 26, wherein the channel statistics estimator further comprises:

a covariance estimator for generating ^{{circumflex over (K)}yy}, an estimated covariance of received channel signal y[n] vector, according to the following relationship;

 

{circumflex over (K)}_yy[l,n]=g₃*((y[l]−

{circumflex over (m)}_y[l])(y[n]−

{circumflex over (m)}_y[n])*)

wherein g₃ is a filter impulse response, l and n are row and column vector indices and the superscript * denotes complex conjugate.