Signal receiving method and receiver
Embodiments of the present invention provide a signal receiving method and a receiver. The signal receiving method includes: sequentially preprocessing a received first signal to obtain to-be-processed second signals; generating filtering coefficients for the second signals by converting colored noise of the second signals into white noise; and filtering the corresponding second signals according to the filtering coefficients. Filtering can be performed according to different channel conditions and transmission requirements, thereby improving system performance of the receiver.
1. A signal receiving method, comprising:
sequentially preprocessing a received first signal to obtain to-be-processed second signals;
generating filtering coefficients for the second signals by converting colored noise of the second signals into white noise; and
filtering the corresponding second signals according to the filtering coefficients, wherein the generating filtering coefficients for the second signals by converting colored noise of the second signals into white noise comprises:
if data of the second signals is marked as XI(k), original sending data of the second signals XI(k) is marked as d(k), the colored noise of the second signals XI(k) is marked as n(k), and n(k)=XI(k)−d(k), obtaining filtering coefficients W 0 , W 1 , W 2 . . . W N according to
min
W
0
,
W
1
,
W
2
…
W
N
(
n
(
k
)
-
W
0
n
(
k
)
-
W
1
n
(
k
-
1
)
-
W
2
n
(
k
-
2
)
…
-
W
N
n
(
k
-
N
)
)
2
,
wherein N is a quantity of filter taps, N is a nonnegative integer, and k corresponds to a time serial number of the second signal.
2. The method according to claim 1 , wherein
the obtaining filtering coefficients W 0 , W 1 , W 2 . . . W N according to
min
W
0
,
W
1
,
W
2
…
W
N
(
n
(
k
)
-
W
0
n
(
k
)
-
W
1
n
(
k
-
1
)
-
W
2
n
(
k
-
2
)
…
-
W
N
n
(
k
-
N
)
)
2
comprises:
correlating n(k)=XI(k)−d(k) of the second signals XI(k) to obtain a correlation matrix
[
R
(
0
)
R
(
1
)
…
R
(
N
)
R
(
1
)
R
(
0
)
…
R
(
N
-
1
)
⋮
⋮
⋱⋮
R
(
N
)
R
(
N
-
1
)
…
R
(
0
)
]
,
wherein R is an autocorrelation function of the noise n(k), the correlation matrix has a dimension of (N+1)*(N+1), and N+1 is a length of a filter; and
obtaining
[
W
~
0
W
~
1
⋮
W
~
N
]
according to
[
R
(
0
)
R
(
1
)
…
R
(
N
)
R
(
1
)
R
(
0
)
…
R
(
N
-
1
)
⋮
⋮
⋱⋮
R
(
N
)
R
(
N
-
1
)
…
R
(
0
)
]
[
W
~
0
W
~
1
⋮
W
~
N
]
=
[
R
(
0
)
0
⋮
0
]
,
and normalizing
[
W
~
0
W
~
1
⋮
W
~
N
]
to obtain values of
[
W
0
W
1
⋮
W
N
]
,
and determining the filtering coefficients W 0 , W 1 , W 2 , . . . , and W N according to the values of
[
W
0
W
1
⋮
W
N
]
.
3. The method according to claim 1 , wherein the original sending data is obtained according to a training sequence or a decision feedback.
4. A signal receiving method, comprising:
sequentially preprocessing a received first signal to obtain to-be-processed second signals;
generating filtering coefficients for the second signals by converting colored noise of the second signals into white noise; and
filtering the corresponding second signals according to the filtering coefficients, wherein W L , W L+1 . . . W N in the filtering coefficients W 0 , W 1 , W 2 . . . W N are all less than a preset threshold, wherein 0<L<N; and
the filtering the corresponding second signals according to the filtering coefficients comprises:
filtering the corresponding second signals according to W 0 , W 1 , . . . W L−1 in the filtering coefficients.
5. The method according to claim 4 , wherein the filtering coefficients are finite impulse response FIR filtering coefficients.
6. A signal receiving method, comprising:
sequentially preprocessing a received first signal to obtain to-be-processed second signals;
generating filtering coefficients for the second signals by converting colored noise of the second signals into white noise; and
filtering the corresponding second signals according to the filtering coefficients, wherein after the filtering the corresponding second signals according to the filtering coefficients, the method further comprises:
performing sequence detection on the filtered second signals by using a maximum likelihood sequence detection (MLSD) algorithm or a BCJR algorithm, wherein branch metrics in the sequence detection are calculated according to the filtering coefficients.
7. The method according to claim 6 , wherein
W L , W L+1 . . . W N in the filtering coefficients W 0 , W 1 , W 2 . . . W N are all less than the preset threshold, wherein 0<L<N; and
the calculating branch metrics according to the filtering coefficients comprises:
calculating the branch metrics according to W 0 , W 1 , . . . W L−1 in the filtering coefficients.
8. A receiver, comprising:
a processor, configured to sequentially preprocess a received first signal to obtain to-be-processed second signals;
a calculator, configured to generate filtering coefficients for the second signals by converting colored noise of the second signals into white noise; and
a filter, configured to filter the corresponding second signals according to the filtering coefficients, wherein
the calculator is configured to: if data of the second signals is marked as XI(k), original sending data of the second signals XI(k) is marked as d(k), the colored noise of the second signals XI(k) is marked as n(k), and n(k)=XI(k)−d(k),
obtain filtering coefficients W 0 , W 1 , W 2 . . . W N according to
min
W
0
,
W
1
,
W
2
…W
N
(
n
(
k
)
-
W
0
n
(
k
)
-
W
1
n
(
k
-
1
)
-
W
2
n
(
k
-
2
)
…
-
W
N
n
(
k
-
N
)
)
2
,
wherein N is a quantity of filter taps, N is a nonnegative integer, and k corresponds to a time serial number of the second signal.
9. The receiver according to claim 8 , wherein
the calculator is configured to: correlate n(k)=XI(k)−d(k) of the second signals XI(k), to obtain a correlation matrix
[
R
(
0
)
R
(
1
)
…
R
(
N
)
R
(
1
)
R
(
0
)
…
R
(
N
-
1
)
⋮
⋮
⋱⋮
R
(
N
)
R
(
N
-
1
)
…
R
(
0
)
]
,
wherein R is an autocorrelation function of the noise n(k), the correlation matrix has a dimension of (N+1)*(N+1), and N+1 is a length of a filter; and
obtain
[
W
~
0
W
~
1
⋮
W
~
N
]
according to
[
R
(
0
)
R
(
1
)
…
R
(
N
)
R
(
1
)
R
(
0
)
…
R
(
N
-
1
)
⋮
⋮
⋱⋮
R
(
N
)
R
(
N
-
1
)
…
R
(
0
)
]
[
W
~
0
W
~
1
⋮
W
~
N
]
=
[
R
(
0
)
0
⋮
0
]
,
normalize
[
W
~
0
W
~
1
⋮
W
~
N
]
to obtain values of
[
W
0
W
1
⋮
W
N
]
,
and determine the filtering coefficients W 0 , W 1 , W 2 , . . . , and W N according to the values of
[
W
0
W
1
⋮
W
N
]
.
10. A receiver, comprising:
a processor, configured to sequentially preprocess a received first signal to obtain to-be-processed second signals;
a calculator, configured to generate filtering coefficients for the second signals by converting colored noise of the second signals into white noise; and
a filter, configured to filter the corresponding second signals according to the filtering coefficients, wherein
the filter is configured to filter the corresponding second signals according to W 0 , W 1 , . . . W L−1 in the filtering coefficients if the filtering coefficients W L , W L+1 W N in W 0 , W 1 , W 2 . . . W N are all less than a preset threshold, wherein 0<L<N.
11. A receiver, comprising:
a processor, configured to sequentially preprocess a received first signal to obtain to-be-processed second signals;
a calculator, configured to generate filtering coefficients for the second signals by converting colored noise of the second signals into white noise; and
a filter, configured to filter the corresponding second signals according to the filtering coefficients, wherein
the processor is further configured to perform sequence detection on the filtered second signals by using a maximum likelihood sequence detection MLSD algorithm or a BCJR algorithm, wherein branch metrics in the sequence detection are calculated according to the filtering coefficients.
12. The receiver according to claim 11 , wherein
the processor is configured to calculate the branch metrics according to W 0 , W 1 , . . . W L−1 in the filtering coefficients if W L , W L+1 . . . W N in the filtering coefficients W 0 , W 1 , W 2 . . . W N are all less than the preset threshold, wherein 0<L<N.
13. A receiver, comprising:
a processing module, configured to sequentially preprocess a first signal received by a receiving module to obtain to-be-processed second signals;
a filtering coefficient generation module, configured to generate filtering coefficients for the second signals by converting colored noise of the second signals into white noise; and
a filtering module, configured to filter the corresponding second signals according to the filtering coefficients, wherein
the filtering coefficient generation module is specifically configured to: if data of the second signals is marked as XI(k), original sending data of the second signals XI(k) is marked as d(k), the colored noise of the second signals XI(k) is marked as n(k), and n(k)=XI(k)−d(k),
obtain filtering coefficients W 0 , W 1 , W 2 . . . W N according to
min
W
0
,
W
1
,
W
2
…W
N
(
n
(
k
)
-
W
0
n
(
k
)
-
W
1
n
(
k
-
1
)
-
W
2
n
(
k
-
2
)
…
-
W
N
n
(
k
-
N
)
)
2
,
wherein N is a quantity of taps of the filtering module, N is a nonnegative integer, and k corresponds to a time serial number of the second signal.
14. The receiver according to claim 13 , wherein
the filtering coefficient generation module is configured to: correlate n(k)=XI(k)−d(k) of the second signals XI(k), to obtain a correlation matrix
[
R
(
0
)
R
(
1
)
…
R
(
N
)
R
(
1
)
R
(
0
)
…
R
(
N
-
1
)
⋮
⋮
⋱
⋮
R
(
N
)
R
(
N
-
1
)
…
R
(
0
)
]
,
wherein R is an autocorrelation function of the noise n(k), the correlation matrix has a dimension of (N+1)*(N+1), and N+1 is a length of the filtering module; and
obtain
[
W
~
0
W
~
1
⋮
W
~
N
]
according to
[
R
(
0
)
R
(
1
)
…
R
(
N
)
R
(
1
)
R
(
0
)
…
R
(
N
-
1
)
⋮
⋮
⋱
⋮
R
(
N
)
R
(
N
-
1
)
…
R
(
0
)
]
[
W
~
0
W
~
1
⋮
W
~
N
]
=
[
R
(
0
)
0
⋮
0
]
,
normalize
[
W
~
0
W
~
1
⋮
W
~
N
]
to obtain values of
[
W
0
W
1
⋮
W
N
]
,
and determine the filtering coefficients W 0 , W 1 , W 2 , . . . , and W N according to the values of
[
W
0
W
1
⋮
W
N
]
.
15. A receiver, comprising:
a processing module, configured to sequentially preprocess a first signal received by a receiving module to obtain to-be-processed second signals;
a filtering coefficient generation module, configured to generate filtering coefficients for the second signals by converting colored noise of the second signals into white noise; and
a filtering module, configured to filter the corresponding second signals according to the filtering coefficients, wherein
the filtering module is configured to filter the corresponding second signals according to W 0 , W 1 , . . . W L−1 in the filtering coefficients if W L , W L+1 . . . W N in the filtering coefficients W 0 , W 1 , W 2 . . . W N are all less than a preset threshold, wherein 0<L<N.
16. A receiver, comprising:
a processing module, configured to sequentially preprocess a first signal received by a receiving module to obtain to-be-processed second signals;
a filtering coefficient generation module, configured to generate filtering coefficients for the second signals by converting colored noise of the second signals into white noise;
a filtering module, configured to filter the corresponding second signals according to the filtering coefficients; and
a sequence detection module, configured to perform sequence detection on the filtered second signals by using a maximum likelihood sequence detection MLSD algorithm or a BCJR algorithm, wherein branch metrics in the sequence detection are calculated according to the filtering coefficients.
17. The receiver according to claim 16 , wherein
the sequence detection module is configured to calculate the branch metrics according to W 0 , W 1 , . . . W L−1 in the filtering coefficients if W L , W L+1 . . . W N in the filtering coefficients W 0 , W 1 , W 2 . . . W N are all less than the preset threshold, wherein 0<L<N.