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| 型號： | ZFBLEWP |
| 英文描述： | ZF-BLE Joint Detection for TD-SCDMA |
| 中文描述： | 迫零線性均衡的聯(lián)合檢測的TD - SCDMA |
| 文件頁數(shù)： | 13/20頁 |
| 文件大?。?/td> | 316K |
| 代理商： | ZFBLEWP |
13
4.
Zero Force Block Joint Estimator
We want to find the estimate of the transmitted data vector
d
from the received signal
E.
N
d
I
A
E
+
=
)
(
)
(
Ka
(13)
If we treat the data vector
d
as an unknown nonrandom vector, we want to find an estimate of the
N
data
symbols transmitted by the k
th
user during the sub frame Based on the principle of Maximum Likelihood
estimation, we can obtain this estimate by
e
R
A
A
R
A
d
1
n
H
1
1
n
H
)
}
(
=
(14)
where
singular. We will use the Cholesky decomposition:
R
n
The estimation of the data block the data block
d
can be broken to a Whitening Filter
A
H
R
n
Zero-Force Equalizer (
A
H
R
n
{
H
n
E
nn
R
=
is the noise covariance matrix. Since we need
R
n
-1
we assume that
R
n
is non-
-1
-1
= L
H
L
to arrive at
R
n
-1
followed by a
-1
A
)
-1
(see Figure 4-1).
Channel
A
e
=
Ad
+
n
Whitening
Filter
L
Matched
Filter
A
H
L
H=
(
LA
)
H
Zero-Force
equalizer
(
A
H
R
n-1
A
)
-1
^
d
n
Figure 4-1 ZF-BLE Estimator
To estimate the data vector
d,
we need to know both noise covariance matrix
R
n
and the channel matrix
A.
4.1.
Estimating the Channel Matrix
A
Estimation of the channel matrix
A
is based on the midamble chips in each slot.
Suppose
e
m
antenna k
a
and the received midamble chips are not contaminated by its previous data
symbol. (Thus, we pick up the midamble chips from 17 to 144 for a total of 128 chips,
i.e. L = 128 and we assume that the multi-path dispersion is within 16 chips).
(ka)
= (e
1
(ka)
, e
2
(ka)
,. . . , e
L
(ka)
)
T
is the received midamble chip vector from
We stack all Ka such vectors together to form the received matrix.
e
R
A
A
R
A
d
1
n
H
1
1
n
H
)
(
=
(15)
E
m
= [
e
m
(1)
,
e
m
(2)
, … ,
e
m
(ka)
]
(16)
Similarly, the received noise vector for antenna k
a
is
F
Freescale Semiconductor, Inc.
For More Information On This Product,
Go to: www.freescale.com
n
.
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