US2014233130A1PendingUtilityA1
Systems and Methods for Determining Noise Components in a Signal Set
Est. expiryJan 5, 2030(~3.4 yrs left)· nominal 20-yr term from priority
H04B 17/345G11B 20/10046
52
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Claims
Abstract
Various embodiments of the present invention provide systems and methods for estimating noise components in a received signal set. For example, one embodiment of the present invention provides a noise estimation circuit that includes a data detector circuit and a noise component calculation circuit. The data detector circuit receives a series of data samples and provides a detected output, and the noise component calculation circuit provides an electronics noise power output and a media noise power output each calculated based at least in part on the detected output and the series of data samples.
Claims
exact text as granted — not AI-modifiedWhat is claimed is:
1 . A method for noise component estimation, the method comprising:
receiving a data input; applying a data detection algorithm by a data detection circuit to the data input to yield a detected output; calculating a set of noise prediction coefficients based at least in part on the data input; calculating a partial correlation value based at least in part on the data input; calculating an error power value based at least in part on the data input and the detected output; calculating a noise power value based on both the error power value and the partial correlation value; and calculating an electronics noise value based at least in part on the noise power value.
2 . The method of claim 1 , wherein the method further comprises:
calculating a media noise value based at least in part on the electronics noise value.
3 . The method of claim 1 , wherein the data input is a first data input, and wherein the method further comprises:
performing a noise predictive filtering of a second data input based upon a coefficient set to yield the first series of data samples.
4 . The method of claim 3 , wherein calculating the partial correlation value is done based at least in part on the coefficient set.
5 . The method of claim 4 , wherein:
calculating the partial correlation value includes performing the following calculation:
f
k
,
m
[
i
]
=
f
k
,
m
+
1
[
i
]
+
K
k
[
m
+
1
]
·
f
k
,
m
+
1
[
m
+
1
-
i
]
1
-
K
k
2
[
m
+
1
]
,
for
i
=
1
,
2
,
…
,
m
,
and
K
k
[
m
]
=
f
k
,
m
[
m
]
;
calculating the error power value includes performing the following calculation:
P
y
,
k
=
1
N
k
∑
n
∈
S
k
y
k
2
[
n
]
for
k
=
,
1
,
2
,
…
,
M
;
and
calculating the noise power value includes performing the following calculation:
P
x
,
k
=
P
y
,
k
∏
m
=
1
N
(
1
-
K
2
2
[
m
]
)
.
6 . The method of claim 5 , wherein:
calculating the electronics noise value includes performing the following calculation:
P
electronics
=
P
x
,
1
+
P
x
,
M
2
.
7 . The method of claim 1 , wherein the data detection algorithm is selected from a group consisting of: a maximum a posteriori data detection process and a Viterbi algorithm data detection process.
8 . The method of claim 1 , wherein the data input is derived from a storage medium.
9 . The method of claim 1 , wherein receiving the data input comprises:
accessing information from a storage medium; using an analog processing circuit to process the information and provide an analog signal corresponding to the data set; and wherein the data input is derived from the data input.
10 . The method of claim 9 , wherein the method further comprises:
converting the analog signal to a series of digital samples, wherein the data input is derived from the series of digital samples.
11 . The method of claim 10 , wherein the method further comprises:
equalizing the series of digital samples to yield the data input.
12 . The method of claim 1 , wherein the method further comprises:
applying a data decode algorithm to the detected output to yield a decoded output.
13 . The method of claim 12 , wherein the data decode algorithm is a low density parity check encoding algorithm.
14 . The method of claim 1 , wherein the partial correlation value is calculated using an inverse Levinson-Durbin algorithm.
15 . A method for noise component estimation, the method comprising:
applying a data detection algorithm to the data input to yield a detected output; calculating a set of noise prediction coefficients using a calculation circuit based at least in part on the data input; calculating a partial correlation value based at least in part on the data input; calculating an error power value based at least in part on the data input and the detected output; calculating a noise power value based on both the error power value and the partial correlation value; and calculating an electronics noise value based at least in part on the noise power value.
16 . The method of claim 15 , wherein the method further comprises:
calculating a media noise value based at least in part on the electronics noise value.
17 . The method of claim 15 , wherein the data input is a first data input, and wherein the method further comprises:
performing a noise predictive filtering of a second data input based upon a coefficient set to yield the first series of data samples.
18 . The method of claim 17 , wherein calculating the partial correlation value is done based at least in part on the coefficient set.
19 . The method of claim 18 , wherein:
calculating the partial correlation value includes performing the following calculation:
f
k
,
m
[
i
]
=
f
k
,
m
+
1
[
i
]
+
K
k
[
m
+
1
]
·
f
k
,
m
+
1
[
m
+
1
-
i
]
1
-
K
k
2
[
m
+
1
]
,
for
i
=
1
,
2
,
…
,
m
,
and
K
k
[
m
]
=
f
k
,
m
[
m
]
;
calculating the error power value includes performing the following calculation:
P
y
,
k
=
1
N
k
∑
n
∈
S
k
y
k
2
[
n
]
for
k
=
,
1
,
2
,
…
,
M
;
and
calculating the noise power value includes performing the following calculation:
P
x
,
k
=
P
y
,
k
∏
m
=
1
N
(
1
-
K
2
2
[
m
]
)
.
20 . The method of claim 19 , wherein:
calculating the electronics noise value includes performing the following calculation:
P
electronics
=
P
x
,
1
+
P
x
,
M
2
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