System and method for adjusting combiner weights using an adaptive algorithm in wireless communications system

• US 7,170,924 B2
• Filed: 05/17/2001
• Issued: 01/30/2007
• Est. Priority Date: 05/17/2001
• Status: Expired due to Term

• Current Assignee: Qualcomm, Inc.
• Original Assignee: Qualcomm, Inc.
• Inventors: Smee, John Edward, Jayaraman, Srikant, Corbaton, Ivan Jesus Fernandez
• Primary Examiner(s): Bocure; Tesfaldet
• Application Number:
  US09/860,705
• Publication Number:
  US 20030035468A1
• Time in Patent Office: 2,084 Days
• Field of Search: 375/148, 375/232, 375/130, 375/231, 375/147, 375/144, 370/335, 370/342, 370/441, 708/322, 708/319, 333/18, 333/28.R
• US Class Current: 375/148
• CPC Class Codes: H04B 1/712 Weighting of fingers for combining, e.g. amplitude control or phase rotation using an inner loop
• CPC Class Codes: H04B 2201/70701 featuring pilot assisted reception
• CPC Class Codes: H04B 7/0854 using error minimizing algorithms, e.g. minimum mean squared error [MMSE], "cross-correlation" or matrix inversion
• CPC Class Codes: H04B 7/0897 using beamforming per multi-path, e.g. to cope with different directions of arrival [DOA] at different multi-paths

Abstract

Method and apparatus to compute the combiner coefficients for wireless communication systems using an adaptive algorithm. One embodiment trains the weights on a signal known a priori that is time multiplexed with other signals, such as a pilot signal in a High Data Rate, HDR, system, wherein the signal is transmitted at full power. The adaptive algorithm recursively computes the weights during the pilot interval and applies the weights generated to the traffic signals. In one embodiment, the algorithm is a recursive least squares algorithm employing a transversal filter and weight calculation unit.

Claims

1. In a wireless communication system having a plurality of receive antennas, each coupled to a rake receiver, and a combiner for combining signals from rake fingers of each rake receiver, a method for determining combiner weights applied in the combiner, comprising:

receiving a frame comprising samples of a first type of symbols from a plurality of rake receiver outputs and samples of a second type of symbols from the plurality of rake receiver outputs;

determining combiner weights for combining the plurality of rake receiver outputs using the samples of the first type of symbols using an adaptive algorithm, wherein the adaptive algorithm is a recursive least squares algorithm, and wherein the determining includes iteratively calculating a combiner weight as a function of at least one previous combiner weight, and a received signal comprising the first type of symbols, and further wherein the combiner weight is a function of a gain factor determining an amount of past iterative information maintained by the algorithm; and

processing the samples of the second type of symbols using the combiner weights.

2. The method of claim 1, wherein the determining comprises:

filtering the samples of the first type of symbols using a transversal filter having a plurality of taps, wherein the combiner weights are applied to the plurality of taps.

3. The method of claim 2, wherein the determining further comprises:

determining an error between desired symbols and filtered samples of the first type of symbols, wherein the error is used to determine combiner weights.

4. The method of claim 1, wherein the first type of symbols corresponds to a pilot signal and the second type of symbols corresponds to a data signal time multiplexed with the pilot signal.

5. In a wireless communication system having a plurality of receive antennas, each coupled to a rake receiver, and a combiner for combining signals from rake fingers of each rake receiver, a method for determining combiner weights applied in the combiner, comprising:

receiving a frame comprising samples of a first type of symbols and samples of a second type of symbols;

determining combiner weights using the samples of the first type of symbols using a recursive least squares algorithm, wherein the determining comprises iteratively calculating a combiner weight as a function of at least one previous combiner weight and a received signal comprising the first type of symbols, and wherein the calculating a combiner weight, W( ), for iteration k, is given as;

W(k+1)=W(k)−

K(k+1)(W^H(k)X(k+1)−

y(k+1))*,

wherein K( ) is a gain applied to weight iterations, X( ) is received data, and y( ) is desired data; and

processing the samples of the second type of symbols using the combiner weights.

6. A The method of claim 5, wherein the gain K( ) is calculated as:

$K<br><br>\left(k+1\right)=\frac{{\mathrm{\lambda <br><br>}}^{-1}<br><br>P<br><br>\left(k\right)<br><br>X<br><br>\left(k\right)}{1+{\mathrm{\lambda <br><br>}}^{-1}<br><br>{X<br><br>\left(k\right)}^H<br><br>P<br><br>\left(k\right)<br><br>X<br><br>\left(k\right)},$

wherein λ

is a history gain factor for the algorithm less than or equal to one, the history gain factor determining an amount of past iterative information maintained by the algorithm.

7. An apparatus in a wireless communication system having a plurality of receive antennas, each coupled to a rake receiver, and a combiner for combining signals from rake fingers of each rake receiver, the apparatus comprising:

means for receiving a frame comprising samples of a first type of symbols from a plurality of rake receiver outputs and samples of a second type of symbols from the plurality of rake receiver outputs;

means for determining combiner weights for combining the plurality of rake receiver outputs using the samples of the first type of symbols using an adaptive algorithm, wherein the adaptive algorithm is a recursive least squares algorithm, and wherein the determining includes iteratively calculating a combiner weight as a function of at least one previous combiner weight, and a received signal comprising the first type of symbols, and further wherein the combiner Weights a function of a gain factor determining an amount of past iterative information maintained by the algorithm; and

means for processing the samples of the second type of symbols using the combiner weights.

8. The apparatus of claim 7, wherein the means for determining comprises:

means for filtering the samples of the first type of symbols using a transversal filter having a plurality of taps, wherein die combiner weights are applied to the plurality of taps.

9. A The apparatus of claim 8, wherein the means for determining further comprises:

means for determining an error between desired symbols and filtered samples of the first type of symbols, wherein the error is used to determine combiner weights.

10. An apparatus in a wireless communication system having a plurality of receive antennas, each coupled to a rake receiver, and a combiner for combining signals from rake fingers of each rake receiver, the apparatus comprising:

means for receiving a frame comprising samples of a first type of symbols and samples of a second type of symbols;

means for determining combiner weights using the samples of the first type of symbols using a recursive least squares algorithm, wherein the determining comprises iteratively calculating a combiner weight as a function of at least one previous combiner weight and a received signal comprising the first type of symbols, and wherein the calculating a combiner weight, W( ), for iteration k, is given as;

W(k+1)=W(k)−

K(k+1)(W^H(k)X(k+1)−

y(k+1))*,

wherein K( ) is a gain applied to weight iterations, X( ) is received data, and y( ) is desired data; and

means for processing the samples of the second type of symbols using the combiner weights.

11. The apparatus of claim 10, wherein the gain K( ) is calculated as:

$K<br><br>\left(k+1\right)=\frac{{\mathrm{\lambda <br><br>}}^{-1}<br><br>P<br><br>\left(k\right)<br><br>X<br><br>\left(k\right)}{1+{\mathrm{\lambda <br><br>}}^{-1}<br><br>{X<br><br>\left(k\right)}^H<br><br>P<br><br>\left(k\right)<br><br>X<br><br>\left(k\right)},$

wherein λ

is a history gain factor for the algorithm less than or equal to one, the history gain factor determining an amount of past iterative information maintained by the algorithm.