Communications: directive radio wave systems and devices (e.g. – Directive – Utilizing correlation techniques
Reexamination Certificate
2002-12-17
2004-08-03
Tarcza, Thomas H. (Department: 3662)
Communications: directive radio wave systems and devices (e.g.,
Directive
Utilizing correlation techniques
C342S372000, C342S378000, C455S276100
Reexamination Certificate
active
06771219
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates to a smart antenna system and, in particular, to an improved adaptive beamforming method for an antenna array in a Code Division Multiple Access (CDMA) communication system.
2. Background of the Related Art
In wireless communication systems, various diverse methods are used for increasing the coverage area and capacity of the system.
Rake receiver architecture provides an effective immunity to the inter-symbol interference (ISI) in multipath propagation environments, which cause the same signal to be repeatedly received at an antenna at a plurality of different time intervals.
Recently, directive antennas have been employed to increase the signal-to-interference plus noise ratio (SINR) by increasing the energy radiated to a desired mobile terminal, while simultaneously reducing the interference energy radiated to other remote mobile terminals. Such reduction in the interference energy radiated to mobile terminals can be achieved by generating spatially selective, directive transmission beam patterns.
One directive antenna technique is adaptive beamforming, in which the beam pattern produced by beamforming antenna arrays of the base station adapts in response to changing multipath conditions. In such beamforming arrays, weight vectors are used to generate on antenna beam pattern that maximizes signal energy transmitted to and received from an intended mobile terminal.
There are a number of algorithms presently in use for calculating the weight vectors. These algorithms rely on adjusting the weight vector so as to track the more slowly changing components of the received signal and assume that more rapidly changing random signal components are removed by integration and are hence not tracked.
These algorithms update the weight vector based on a generalized eigenvalue problem, and the generalized eigenvalue problem is converted so as to be an ordinary eigenvalue problem. Continuously, a positive definite matrix is taken among two matrixes consisting of the generalized eigenvalue problem, and the positive definite matrix is written with two matrixes such that an inverse matrix should be obtained from one of the two written matrixes.
However, the conventional algorithms have a drawback in that the weight vector calculation is so complicated and time-consuming that it is not appropriate for an array antenna system that requires real time environment adaptation.
SUMMARY OF THE INVENTION
An object of the invention is to solve at least the above problems and/or disadvantages and to provide at least the advantages described hereinafter.
It is an object of the present invention to provide an adaptive beamforming method capable of reducing total computational load for computing weight vector.
It is another object of the present invention to provide an adaptive beamforming method capable of maximizing the Signal to Interference plus Noise (SINR).
To achieve the above objects, the adaptive beamforming method of the present invention comprises the steps of setting an initial weight vector w; updating present autocovariance matrixes
R
xx
and
R
yy
of the generalized eigenvalue problem with the signal vectors
y
and
x
at a present snapshot; obtaining diagonal and off-diagonal matrixes of one of the autocovariance matrixes
R
xx
and
R
yy
; computing the maximum eigenvalue &lgr; using the weight vector
w
, the autocovariance matrixes
R
xx
and
R
yy
at the present snapshot, and the diagonal and off-diagonal matrixes; and updating the weight vector using the present weight vector
w
, the eigenvalue &lgr;, and autocovariance matrixes
R
xx
and
R
yy
.
The diagonal matrix is a matrix whose diagonal elements are identical to diagonal elements of a square matrix and whose off-diagonal elements are zero, and the off-diagonal matrix is a matrix whose diagonal elements are zero and whose off-diagonal elements are identical to off-diagonal elements of the square matrix.
In one aspect of the present invention, the diagonal and off-diagonal matrixes are
R
xx
D
and
R
xx
O
derived from the autocovariance matrix
R
xx
.
The maximum eigenvalue &lgr; is calculated in accordance with the following equation:
λ
=
w
_
H
R
_
_
yy
w
_
w
_
H
R
_
_
xx
w
_
where H is the Hermitian operator.
The weight vector
w
is updated in accordance with the following equation:
w
_
(
k
+
1
)
=
[
R
_
_
yy
(
k
)
(
R
_
_
xx
D
(
k
)
)
-
1
-
λ
R
_
_
xx
O
(
k
)
(
R
_
_
xx
D
(
k
)
)
-
1
]
w
_
(
k
)
λ
where k is a snapshot index for receiving the signal vector and for updating the weight vector.
The maximum eigenvalue &lgr;(k) at the present snapshot is computed in accordance with the following equation:
λ
(
k
)
=
λ
nom
(
k
)
λ
den
(
k
)
where nom denotes numerator and den denotes denominator,
&lgr;
nom
(
k
)=ƒ&lgr;
nom
(
k−
1)+|&agr;(
k
)|
2
, and &lgr;
den
(
k
)=ƒ&lgr;
den
(
k−
1)+|&bgr;(
k
)|
2
.
&agr;(k) is obtained in accordance with &agr;(k)=
y
H
(k)
w
(k), and &bgr;(k) is obtained in accordance with &bgr;(k)=
x
H
(k)
w
(k).
The weight vector is updated in accordance with the following equation:
w
(
k+
1)=
w
(
k
)+
o
(
k
),
where
o
_
(
k
)
=
[
R
_
_
xx
D
(
k
)
]
-
1
[
1
λ
(
k
)
v
_
(
k
)
-
q
_
(
k
)
]
.
v
(k) is obtained in accordance with the following equation:
v
_
(
k
)
=
f
R
_
_
yy
(
k
-
1
)
w
_
(
k
)
+
y
_
(
k
)
+
y
_
H
(
k
)
w
_
(
k
)
≈
f
R
_
_
yy
(
k
-
1
)
w
_
(
k
-
1
)
+
y
_
(
k
)
y
_
H
(
k
)
w
_
(
k
)
.
≈
f
v
_
(
k
-
1
)
+
α
(
k
)
y
_
(
k
)
.
q
(k) is obtained in accordance with the following equation:
q
_
(
k
)
=
f
R
_
_
xx
(
k
-
1
)
w
_
(
k
)
+
x
_
(
k
)
x
_
H
(
k
)
w
_
(
k
)
.
≈
f
q
_
(
k
-
1
)
+
β
(
k
)
x
_
(
k
)
.
In another aspect of the present invention, the diagonal and off-diagonal matrixes are
R
yy
D
and
R
yy
O
derived from the autocovariance matrix
R
yy
.
The maximum eigenvalue &lgr; is calculated in accordance with the following equation:
λ
=
w
_
H
R
_
_
yy
w
_
w
_
H
R
_
_
xx
w
_
where H is the Hermitian operator.
The weight vector
w
is updated in accordance with the following equation:
w
(
k+
1)=
w
(
k
)+
p
(
k
)
where
p
(k)=[
R
yy
D
(k)]
−1
[&lgr;(k)
&ggr;
(k)−
&eegr;
(k)].
&ggr;(k) is obtained in accordance with the following equation:
γ
_
(
k
)
=
f
R
_
_
xx
(
k
-
1
)
w
_
(
k
)
+
x
_
(
k
)
x
_
H
(
k
)
w
_
(
k
)
≈
f
γ
_
(
k
-
1
)
+
β
(
k
)
x
_
(
k
)
where &bgr;(k)=
x
H
(k)
w
(k).
&eegr;
(k) is obtained in accordance with the following equation:
η
_
(
k
)
=
f
R
_
_
yy
(
k
-
1
)
w
_
(
k
)
+
y
_
(
k
)
y
_
H
(
k
)
w
_
(
k
)
≈
f
η
_
(
k
-
1
)
+
α
(
k
)
y
_
(
k
)
where &agr;(k)=
y
H
(k)
w
(k).
To achieve at least the above objects, in whole or in part, there, is provided a method for updating a weight factor for input signals from a plurality of antennas of a wireless communication system, including setting an initial weight vector for weighting the input signals, separating desired signals from the input signals, obtaining auto-covariance matrixes of the separated desired signals and the input signals, respectively, computing an eigenvalue that maximizes a ratio of a vector that is a multiplicat
Fleshner & Kim LLP
LG Electronics Inc.
Mull F H
Tarcza Thomas H.
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