CN112104392A - PLC channel impulse noise detection method and system using state matrix - Google Patents

PLC channel impulse noise detection method and system using state matrix Download PDF

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CN112104392A
CN112104392A CN202011068034.6A CN202011068034A CN112104392A CN 112104392 A CN112104392 A CN 112104392A CN 202011068034 A CN202011068034 A CN 202011068034A CN 112104392 A CN112104392 A CN 112104392A
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impulse noise
type
serial number
state matrix
value
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CN112104392B (en
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翟明岳
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Guangdong University of Petrochemical Technology
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Guangdong University of Petrochemical Technology
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B3/00—Line transmission systems
    • H04B3/02—Details
    • H04B3/46—Monitoring; Testing
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
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    • H04B3/54—Systems for transmission via power distribution lines

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Abstract

The embodiment of the invention discloses a PLC channel impulse noise detection method and a system by using a state matrix, wherein the method comprises the following steps: step 101, acquiring a signal sequence S acquired according to a time sequence; 102, acquiring a pulse noise type sample matrix B through actual investigation; step 103, solving a feature vector p; step 104 of obtaining candidate impulse noise event vector e and candidate state matrix alpha*(ii) a Step 105, obtaining a state matrix alpha; step 106 determines impulse noise.

Description

PLC channel impulse noise detection method and system using state matrix
Technical Field
The invention relates to the field of communication, in particular to a method and a system for detecting pulse noise of a PLC channel.
Background
Compared with various wired communication technologies, the power line communication has the advantages of no need of rewiring, easiness in networking and the like, and has wide application prospect. The power line communication technology is divided into narrowband power line communication (NPL) and broadband power line communication (BPL); the narrow-band power line communication refers to a power line carrier communication technology with the bandwidth limited between 3k and 500 kHz; the power line communication technology includes a prescribed bandwidth (3148.5kHz) of european CENELEC, a prescribed bandwidth (9490kHz) of the Federal Communications Commission (FCC) in the united states, a prescribed bandwidth (9450kHz) of the japan wireless industry and business Association (ARIB), and a prescribed bandwidth (3500kHz) of china. The narrow-band power line communication technology mainly adopts a single carrier modulation technology, such as a PSK technology, a DSSS technology, a Chirp technology and the like, and the communication speed is less than 1 Mbits/s; the broadband power line communication technology refers to a power line carrier communication technology with a bandwidth limited between 1.630MHz and a communication rate generally above 1Mbps, and adopts various spread spectrum communication technologies with OFDM as a core.
Although power line communication systems are widely used and the technology is relatively mature, a large number of branches and electrical devices in the power line communication system generate a large amount of noise in the power line channel; random impulse noise has high randomness and high noise intensity, and seriously damages a power line communication system, so that the technology for inhibiting the random impulse noise is always the key point for the research of scholars at home and abroad; and the noise model does not fit into a gaussian distribution. Therefore, the traditional communication system designed aiming at the gaussian noise is not suitable for a power line carrier communication system any more, and a corresponding noise suppression technology must be researched to improve the signal-to-noise ratio of the power line communication system, reduce the bit error rate and ensure the quality of the power line communication system. In practical applications, some simple non-linear techniques are often applied to eliminate power line channel noise, such as Clipping, Blanking and Clipping/Blanking techniques, but these research methods must work well under a certain signal-to-noise ratio, and only the elimination of impulse noise is considered, in the power line communication system, some commercial power line transmitters are characterized by low transmission power, and in some special cases, the transmission power may be even lower than 18w, so that in some special cases, the signal will be submerged in a large amount of noise, resulting in a low signal-to-noise ratio condition of the power line communication system.
Disclosure of Invention
With the application and popularization of nonlinear electrical appliances, background noise in a medium and low voltage power transmission and distribution network presents obvious non-stationarity and non-Gaussian characteristics, pulse noise becomes more common and more serious, and to filter the pulse noise, the pulse noise is detected first, and then corresponding measures can be further taken, but the existing method and system lack sufficient attention on the detection of the pulse noise.
The invention aims to provide a PLC channel impulse noise detection method and a PLC channel impulse noise detection system using a state matrix. The method has better robustness and simpler calculation.
In order to achieve the purpose, the invention provides the following scheme:
a PLC channel impulse noise detection method using a state matrix comprises the following steps:
step 101, acquiring a signal sequence S acquired according to a time sequence;
step 102, obtaining an impulse noise type sample matrix B through actual investigation, specifically: the ith row and the jth column of the impulse noise type sample matrix B have BijA j-th sampling value representing impulse noise belonging to an i-th type;
wherein:
i represents the serial number of impulse noise type, and the value range is i ═ 1,2, ·, Ni
j represents the sample number with the value range of j ═ 1,2, ·, N
N is the length of the signal sequence S;
Nithe total number of impulse noise types;
step 103, solving a feature vector p, specifically: the ith element of the feature vector p is piAnd expressing the characteristic value of the impulse noise of the type i, and the calculation formula is as follows:
Figure BDA0002714423680000021
wherein:
Figure BDA0002714423680000022
the kth differential characteristic value is of type i;
k ═ 1,2, ·, N: the sequence number of the differential characteristic value;
Figure BDA0002714423680000023
offset value
Figure BDA0002714423680000024
Get the whole on
*: representing any independent variable
If the element serial number j is less than or equal to 0, setting the element serial number to be 1;
if the element serial number j is more than or equal to N, setting the element serial number as N;
Figure BDA0002714423680000025
the mean value of the ith row element in the noise type sample matrix B;
step 104 of obtaining candidate impulse noise event vector e and candidate state matrix alpha*The method specifically comprises the following steps:
e＝[em]1×N
Figure BDA0002714423680000026
wherein:
the mth element of the candidate impulse noise event vector e is emThe calculation method comprises the following steps: at all less than or equal to
Figure BDA0002714423680000027
Of said characteristic value piTo select the maximum value pqAnd order em＝q；
z is a first summation parameter;
the candidate state matrix α*The row o and column m elements of
Figure BDA0002714423680000028
The calculation formula is as follows:
Figure BDA0002714423680000029
m＝1,2,···,NE: candidate impulse noise event sequence numbers
Figure BDA0002714423680000031
E thmPoint difference eigenvalue
Figure BDA0002714423680000032
Differential eigenvalue of j point
sl: the l-th element of the signal sequence S
l: second sum parameter
If the element serial number l is less than or equal to 0, setting the element serial number to be 1;
if the element serial number l is larger than or equal to N, setting the element serial number as N;
m0: mean value of the signal sequence S
o＝1,2,···,Ni: impulse noise type serial number
Step 105, obtaining a state matrix α, specifically: the element of the o row and the u column of the state matrix alpha is alphao,uThe calculation method comprises the following steps: at αo,uOf the possible two values 0,1, the formula is chosen such that
Figure BDA0002714423680000033
Is taken as ao,uA value of (d);
wherein:
Figure BDA0002714423680000034
e thuPoint difference eigenvalue
Figure BDA0002714423680000035
Confidence of type o impulse noise
po: eigenvalues of type o impulse noise
pq: eigenvalues of type q impulse noise
q＝1,2,···,Ni: impulse noise type number;
u is a third summation parameter;
step 106, determining the impulse noise, specifically: for the ith row and jth column element α in the state matrix αijIf α isij1, then that impulse noise of type i is present at data point j; if α isij0 indicates that at data point j, impulse noise of type i is not present.
A PLC channel impulse noise detection system using a state matrix, comprising:
the module 201 acquires a signal sequence S acquired in time sequence;
the module 202 obtains an impulse noise type sample matrix B through actual investigation, specifically: the ith row and the jth column of the impulse noise type sample matrix B have BijA j-th sampling value representing impulse noise belonging to an i-th type;
wherein:
i represents the serial number of impulse noise type, and the value range is i ═ 1,2, ·, Ni
j represents the sample number with the value range of j ═ 1,2, ·, N
N is the length of the signal sequence S;
Nithe total number of impulse noise types;
the module 203 calculates a feature vector p, specifically: the ith element of the feature vector p is piAnd expressing the characteristic value of the impulse noise of the type i, and the calculation formula is as follows:
Figure BDA0002714423680000041
wherein:
Figure BDA0002714423680000042
the kth differential characteristic value is of type i;
k ═ 1,2, ·, N: the sequence number of the differential characteristic value;
Figure BDA0002714423680000043
offset value
Figure BDA0002714423680000044
Get the whole on
*: representing any independent variable
If the element serial number j is less than or equal to 0, setting the element serial number to be 1;
if the element serial number j is more than or equal to N, setting the element serial number as N;
Figure BDA0002714423680000045
the mean value of the ith row element in the noise type sample matrix B;
module 204 finds candidate impulse noise event vector e and candidate state matrix α*The method specifically comprises the following steps:
e＝[em]1×N
Figure BDA0002714423680000046
wherein:
the mth element of the candidate impulse noise event vector e is emThe calculation method comprises the following steps: at all less than or equal to
Figure BDA0002714423680000047
Of said characteristic value piTo select the maximum value pqAnd order em＝q；
z is a first summation parameter;
the candidate state matrix α*The row o and column m elements of
Figure BDA00027144236800000411
The calculation formula is as follows:
Figure BDA0002714423680000048
m＝1,2,···,NE: candidate impulse noise event sequence numbers
Figure BDA0002714423680000049
E thmPoint difference eigenvalue
Figure BDA00027144236800000410
Differential eigenvalue of j point
sl: the l-th element of the signal sequence S
l: second sum parameter
If the element serial number l is less than or equal to 0, setting the element serial number to be 1;
if the element serial number l is larger than or equal to N, setting the element serial number as N;
m0: mean value of the signal sequence S
o＝1,2,···,Ni: impulse noise type serial number
The module 205 calculates a state matrix α, specifically: the element of the o row and the u column of the state matrix alpha is alphao,uThe calculation method comprises the following steps: at αo,uOf the possible two values 0,1, the formula is chosen such that
Figure BDA0002714423680000051
Is taken as ao,uA value of (d);
wherein:
Figure BDA0002714423680000052
e thuPoint difference eigenvalue
Figure BDA0002714423680000053
Confidence of type o impulse noise
po: eigenvalues of type o impulse noise
pq: eigenvalues of type q impulse noise
q＝1,2,···,Ni: impulse noise type number;
u is a third summation parameter;
the module 206 determines impulse noise, specifically: for the ith row and jth column element α in the state matrix αijIf α isij1, then that impulse noise of type i is present at data point j; if α isij0 indicates that at data point j, impulse noise of type i is not present.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
with the application and popularization of nonlinear electrical appliances, background noise in a medium and low voltage power transmission and distribution network presents obvious non-stationarity and non-Gaussian characteristics, pulse noise becomes more common and more serious, and to filter the pulse noise, the pulse noise is detected first, and then corresponding measures can be further taken, but the existing method and system lack sufficient attention on the detection of the pulse noise.
The invention aims to provide a PLC channel impulse noise detection method and a PLC channel impulse noise detection system using a state matrix. The method has better robustness and simpler calculation.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments will be briefly described below. It is obvious that the drawings in the following description are only some embodiments of the invention, and that for a person skilled in the art, other drawings can be derived from them without inventive effort.
FIG. 1 is a schematic flow diagram of the process of the present invention;
FIG. 2 is a schematic flow chart of the system of the present invention;
FIG. 3 is a flow chart illustrating an embodiment of the present invention.
Detailed Description
The technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
FIG. 1 is a schematic flow chart of a PLC channel impulse noise detection method using a state matrix
Fig. 1 is a schematic flow chart of a PLC channel impulse noise detection method using a state matrix according to the present invention. As shown in fig. 1, the method for detecting impulse noise of a PLC channel using a state matrix specifically includes the following steps:
step 101, acquiring a signal sequence S acquired according to a time sequence;
step 102, obtaining an impulse noise type sample matrix B through actual investigation, specifically: the ith row and the jth column of the impulse noise type sample matrix B have BijA j-th sampling value representing impulse noise belonging to an i-th type;
wherein:
i represents the serial number of impulse noise type, and the value range is i ═ 1,2, ·, Ni
j represents the sample number with the value range of j ═ 1,2, ·, N
N is the length of the signal sequence S;
Nithe total number of impulse noise types;
step 103, solving a feature vector p, specifically: the ith element of the feature vector p is piAnd expressing the characteristic value of the impulse noise of the type i, and the calculation formula is as follows:
Figure BDA0002714423680000061
wherein:
Figure BDA0002714423680000062
the kth differential characteristic value is of type i;
k ═ 1,2, ·, N: the sequence number of the differential characteristic value;
Figure BDA0002714423680000063
offset value
Figure BDA0002714423680000064
Get the whole on
*: representing any independent variable
If the element serial number j is less than or equal to 0, setting the element serial number to be 1;
if the element serial number j is more than or equal to N, setting the element serial number as N;
Figure BDA0002714423680000065
the mean value of the ith row element in the noise type sample matrix B;
step 104 of obtaining candidate impulse noise event vector e and candidate state matrix alpha*The method specifically comprises the following steps:
e＝[em]1×N
Figure BDA0002714423680000071
wherein:
the mth element of the candidate impulse noise event vector e is emThe calculation method comprises the following steps: at all less than or equal to
Figure BDA0002714423680000072
Of said characteristic value piTo select the maximum value pqAnd order em＝q；
z is a first summation parameter;
the above-mentionedCandidate state matrix alpha*The row o and column m elements of
Figure BDA0002714423680000073
The calculation formula is as follows:
Figure BDA0002714423680000074
m＝1,2,···,NE: candidate impulse noise event sequence numbers
Figure BDA0002714423680000075
E thmPoint difference eigenvalue
Figure BDA0002714423680000076
Differential eigenvalue of j point
sl: the l-th element of the signal sequence S
l: second sum parameter
If the element serial number l is less than or equal to 0, setting the element serial number to be 1;
if the element serial number l is larger than or equal to N, setting the element serial number as N;
m0: mean value of the signal sequence S
o＝1,2,···,Ni: impulse noise type serial number
Step 105, obtaining a state matrix α, specifically: the element of the o row and the u column of the state matrix alpha is alphao,uThe calculation method comprises the following steps: at αo,uOf the possible two values 0,1, the formula is chosen such that
Figure BDA0002714423680000077
Is taken as ao,uA value of (d);
wherein:
Figure BDA0002714423680000078
e thuPoint difference eigenvalue
Figure BDA0002714423680000079
Confidence of type o impulse noise
po: eigenvalues of type o impulse noise
pq: eigenvalues of type q impulse noise
q＝1,2,···,Ni: impulse noise type number;
u is a third summation parameter;
step 106, determining the impulse noise, specifically: for the ith row and jth column element α in the state matrix αijIf α isij1, then that impulse noise of type i is present at data point j; if α isij0 indicates that at data point j, impulse noise of type i is not present.
FIG. 2 is a structural view of a PLC channel impulse noise detection system using a state matrix
Fig. 2 is a schematic structural diagram of a PLC channel impulse noise detection system using a state matrix according to the present invention. As shown in fig. 2, the PLC channel impulse noise detection system using a state matrix includes the following structures:
the module 201 acquires a signal sequence S acquired in time sequence;
the module 202 obtains an impulse noise type sample matrix B through actual investigation, specifically: the ith row and the jth column of the impulse noise type sample matrix B have BijA j-th sampling value representing impulse noise belonging to an i-th type;
wherein:
i represents the serial number of impulse noise type, and the value range is i ═ 1,2, ·, Ni
j represents the sample number with the value range of j ═ 1,2, ·, N
N is the length of the signal sequence S;
Nithe total number of impulse noise types;
module 203 finds feature vectorsp, specifically: the ith element of the feature vector p is piAnd expressing the characteristic value of the impulse noise of the type i, and the calculation formula is as follows:
Figure BDA0002714423680000081
wherein:
Figure BDA0002714423680000082
the kth differential characteristic value is of type i;
k ═ 1,2, ·, N: the sequence number of the differential characteristic value;
Figure BDA0002714423680000083
offset value
Figure BDA0002714423680000084
Get the whole on
*: representing any independent variable
If the element serial number j is less than or equal to 0, setting the element serial number to be 1;
if the element serial number j is more than or equal to N, setting the element serial number as N;
Figure BDA0002714423680000085
the mean value of the ith row element in the noise type sample matrix B;
module 204 finds candidate impulse noise event vector e and candidate state matrix α*The method specifically comprises the following steps:
e＝[em]1×N
Figure BDA0002714423680000086
wherein:
mth element of the candidate impulse noise event vector eIs emThe calculation method comprises the following steps: at all less than or equal to
Figure BDA0002714423680000091
Of said characteristic value piTo select the maximum value pqAnd order em＝q；
z is a first summation parameter;
the candidate state matrix α*The row o and column m elements of
Figure BDA0002714423680000092
The calculation formula is as follows:
Figure BDA0002714423680000093
m＝1,2,···,NE: candidate impulse noise event sequence numbers
Figure BDA0002714423680000094
E thmPoint difference eigenvalue
Figure BDA0002714423680000095
Differential eigenvalue of j point
sl: the l-th element of the signal sequence S
l: second sum parameter
If the element serial number l is less than or equal to 0, setting the element serial number to be 1;
if the element serial number l is larger than or equal to N, setting the element serial number as N;
m0: mean value of the signal sequence S
o＝1,2,···,Ni: impulse noise type serial number
The module 205 calculates a state matrix α, specifically: the element of the o row and the u column of the state matrix alpha is alphao,uThe calculation method comprises the following steps: at αo,uOf the possible two values 0,1, the formula is chosen such that
Figure BDA0002714423680000096
Is taken as ao,uA value of (d);
wherein:
Figure BDA0002714423680000097
e thuPoint difference eigenvalue
Figure BDA0002714423680000098
Confidence of type o impulse noise
po: eigenvalues of type o impulse noise
pq: eigenvalues of type q impulse noise
q＝1,2,···,Ni: impulse noise type number;
u is a third summation parameter;
the module 206 determines impulse noise, specifically: for the ith row and jth column element α in the state matrix αijIf α isij1, then that impulse noise of type i is present at data point j; if α isij0 indicates that at data point j, impulse noise of type i is not present.
The following provides an embodiment for further illustrating the invention
FIG. 3 is a flow chart illustrating an embodiment of the present invention. As shown in fig. 3, the method specifically includes the following steps:
step 301, acquiring a signal sequence S acquired according to a time sequence;
step 302, obtaining an impulse noise type sample matrix B through actual investigation, specifically: the ith row and the jth column of the impulse noise type sample matrix B have BijA j-th sampling value representing impulse noise belonging to an i-th type;
wherein:
i represents the serial number of impulse noise type, and the value range is i ═ 1,2, ·, Ni
j represents the sample number with the value range of j ═ 1,2, ·, N
N is the length of the signal sequence S;
Nithe total number of impulse noise types;
step 303, obtaining a feature vector p, specifically: the ith element of the feature vector p is piAnd expressing the characteristic value of the impulse noise of the type i, and the calculation formula is as follows:
Figure BDA0002714423680000101
wherein:
Figure BDA0002714423680000102
the kth differential characteristic value is of type i;
k ═ 1,2, ·, N: the sequence number of the differential characteristic value;
Figure BDA0002714423680000103
offset value
Figure BDA0002714423680000104
Get the whole on
*: representing any independent variable
If the element serial number j is less than or equal to 0, setting the element serial number to be 1;
if the element serial number j is more than or equal to N, setting the element serial number as N;
Figure BDA0002714423680000105
the mean value of the ith row element in the noise type sample matrix B;
step 304 finds candidate impulse noise event vector e and candidate state matrix alpha*The method specifically comprises the following steps:
e＝[em]1×N
Figure BDA0002714423680000106
wherein:
the mth element of the candidate impulse noise event vector e is emThe calculation method comprises the following steps: at all less than or equal to
Figure BDA0002714423680000107
Of said characteristic value piTo select the maximum value pqAnd order em＝q；
z is a first summation parameter;
the candidate state matrix α*The row o and column m elements of
Figure BDA0002714423680000111
The calculation formula is as follows:
Figure BDA0002714423680000112
m＝1,2,···,NE: candidate impulse noise event sequence numbers
Figure BDA0002714423680000113
E thmPoint difference eigenvalue
Figure BDA0002714423680000114
Differential eigenvalue of j point
sl: the l-th element of the signal sequence S
l: second sum parameter
If the element serial number l is less than or equal to 0, setting the element serial number to be 1;
if the element serial number l is larger than or equal to N, setting the element serial number as N;
m0: mean value of the signal sequence S
o＝1,2,···,Ni: impulse noise type serial number
Step 305 finds a state matrix α, specifically: the element of the o row and the u column of the state matrix alpha is alphao,uThe calculation method comprises the following steps: at αo,uOf the possible two values 0,1, the formula is chosen such that
Figure BDA0002714423680000115
Is taken as ao,uA value of (d);
wherein:
Figure BDA0002714423680000116
e thuPoint difference eigenvalue
Figure BDA0002714423680000117
Confidence of type o impulse noise
po: eigenvalues of type o impulse noise
pq: eigenvalues of type q impulse noise
q＝1,2,···,Ni: impulse noise type number;
u is a third summation parameter;
step 306, determining the impulse noise, specifically: for the ith row and jth column element α in the state matrix αijIf α isij1, then that impulse noise of type i is present at data point j; if α isij0 indicates that at data point j, impulse noise of type i is not present.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is simple because the system corresponds to the method disclosed by the embodiment, and the relevant part can be referred to the method part for description.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.

Claims (2)

1. A PLC channel impulse noise detection method using a state matrix is characterized by comprising the following steps:
step 101, acquiring a signal sequence S acquired according to a time sequence;
step 102, obtaining an impulse noise type sample matrix B through actual investigation, specifically: the ith row and the jth column of the impulse noise type sample matrix B have BijA j-th sampling value representing impulse noise belonging to an i-th type;
wherein:
i represents the serial number of impulse noise type, and the value range is i ═ 1,2, ·, Ni
j represents the sample number with the value range of j ═ 1,2, ·, N
N is the length of the signal sequence S;
Nithe total number of impulse noise types;
step 103, solving a feature vector p, specifically: the ith element of the feature vector p is piAnd expressing the characteristic value of the impulse noise of the type i, and the calculation formula is as follows:
Figure FDA0002714423670000011
wherein
Figure FDA0002714423670000012
The kth differential characteristic value is of type i;
k ═ 1,2, ·, N: the sequence number of the differential characteristic value;
Figure FDA0002714423670000013
offset value
Figure FDA0002714423670000014
Get the whole on
*: representing any independent variable
If the element serial number j is less than or equal to 0, setting the element serial number to be 1;
if the element serial number j is more than or equal to N, setting the element serial number as N;
Figure FDA0002714423670000015
the mean value of the ith row element in the noise type sample matrix B;
step 104 of obtaining candidate impulse noise event vector e and candidate state matrix alpha*The method specifically comprises the following steps:
e＝[em]1×N
Figure FDA0002714423670000016
wherein:
the mth element of the candidate impulse noise event vector e is emThe calculation method comprises the following steps: at all less than or equal to
Figure FDA0002714423670000017
Of said characteristic value piTo select the maximum value pqAnd order em＝q；
z is a first summation parameter;
the candidate state matrix α*The row o and column m elements of
Figure FDA0002714423670000018
The calculation formula is as follows:
Figure FDA0002714423670000019
m＝1,2,···,NE: candidate impulse noise event sequence numbers
Figure FDA0002714423670000021
E thmPoint difference eigenvalue
Figure FDA0002714423670000022
Differential eigenvalue of j point
sl: the l-th element of the signal sequence S
l: second sum parameter
If the element serial number l is less than or equal to 0, setting the element serial number to be 1;
if the element serial number l is larger than or equal to N, setting the element serial number as N;
m0: mean value of the signal sequence S
o＝1,2,···,Ni: impulse noise type serial number
Step 105, obtaining a state matrix α, specifically: the element of the o row and the u column of the state matrix alpha is alphao,uThe calculation method comprises the following steps: at αo,uOf the possible two values 0,1, the formula is chosen such that
Figure FDA0002714423670000023
Is taken as ao,uA value of (d);
wherein:
Figure FDA0002714423670000024
e thuPoint difference eigenvalue
Figure FDA0002714423670000025
Confidence of type o impulse noise
po: eigenvalues of type o impulse noise
pq: eigenvalues of type q impulse noise
q＝1,2,···,Ni: impulse noise type number;
u is a third summation parameter;
step 106, determining the impulse noise, specifically: for the ith row and jth column element α in the state matrix αijIf α isij1, then that impulse noise of type i is present at data point j; if α isij0 indicates that at data point j, impulse noise of type i is not present.
2. A PLC channel impulse noise detection system using a state matrix, comprising:
the module 201 acquires a signal sequence S acquired in time sequence;
the module 202 obtains an impulse noise type sample matrix B through actual investigation, specifically: the ith row and the jth column of the impulse noise type sample matrix B have BijA j-th sampling value representing impulse noise belonging to an i-th type;
wherein:
i represents the serial number of impulse noise type, and the value range is i ═ 1,2, ·, Ni
j represents the sample number with the value range of j ═ 1,2, ·, N
N is the length of the signal sequence S;
Nithe total number of impulse noise types;
the module 203 calculates a feature vector p, specifically: the ith element of the feature vector p is piAnd expressing the characteristic value of the impulse noise of the type i, and the calculation formula is as follows:
Figure FDA0002714423670000031
wherein:
Figure FDA0002714423670000032
the kth differential characteristic value is of type i;
k ═ 1,2, ·, N: the sequence number of the differential characteristic value;
Figure FDA0002714423670000033
offset value
Figure FDA0002714423670000034
Get the whole on
*: representing any independent variable
If the element serial number j is less than or equal to 0, setting the element serial number to be 1;
if the element serial number j is more than or equal to N, setting the element serial number as N;
Figure FDA0002714423670000035
the mean value of the ith row element in the noise type sample matrix B;
module 204 finds candidate impulse noise event vector e and candidate state matrix α*The method specifically comprises the following steps:
e＝[em]1×N
Figure FDA0002714423670000036
wherein:
the mth element of the candidate impulse noise event vector e is emThe calculation method comprises the following steps: at all less than or equal to
Figure FDA0002714423670000037
Of said characteristic value piTo select the maximum value pqAnd order em＝q；
z is a first summation parameter;
the candidate state matrix α*The row o and column m elements of
Figure FDA0002714423670000038
The calculation formula is as follows:
Figure FDA0002714423670000039
m＝1,2,···,NE: candidate impulse noise event sequence numbers
Figure FDA00027144236700000310
E thmPoint difference eigenvalue
Figure FDA00027144236700000311
Differential eigenvalue of j point
sl: the l-th element of the signal sequence S
l: second sum parameter
If the element serial number l is less than or equal to 0, setting the element serial number to be 1;
if the element serial number l is larger than or equal to N, setting the element serial number as N;
m0: mean value of the signal sequence S
o＝1,2,···,Ni: impulse noise type serial number
The module 205 calculates a state matrix α, specifically: the element of the o row and the u column of the state matrix alpha is alphao,uThe calculation method comprises the following steps: at αo,uOf the possible two values 0,1, the formula is chosen such that
Figure FDA0002714423670000041
Is taken as ao,uA value of (d);
wherein:
Figure FDA0002714423670000042
e thuPoint difference eigenvalue
Figure FDA0002714423670000043
Confidence of type o impulse noise
po: eigenvalues of type o impulse noise
pq: eigenvalues of type q impulse noise
q＝1,2,···,Ni: impulse noise type number;
u is a third summation parameter;
the module 206 determines impulse noise, specifically: for the ith row and jth column element α in the state matrix αijIf α isij1, then that impulse noise of type i is present at data point j; if α isij0 indicates that at data point j, impulse noise of type i is not present.
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Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101860512A (en) * 2010-05-07 2010-10-13 深圳国微技术有限公司 Impulse noise suppression and demapping soft decision method and system in multi-carrier system
CN107360111A (en) * 2017-06-01 2017-11-17 宁波大学 Impulsive Noise Mitigation Method in a kind of power line communication based on compressed sensing
CN108270497A (en) * 2018-01-19 2018-07-10 重庆邮电大学 A kind of pulse generation method of impulsive noise
CN109067433A (en) * 2018-09-04 2018-12-21 国网四川省电力公司电力科学研究院 Low-voltage powerline carrier communication noise suppressing method suitable for intelligent electric energy meter
CN110719121A (en) * 2019-11-02 2020-01-21 广东石油化工学院 PLC channel impulse noise detection method and system using square exponential kernel
CN111181891A (en) * 2019-10-21 2020-05-19 浙江万胜智能科技股份有限公司 Improved power line impulse noise suppression method based on compressed sensing
US10666490B1 (en) * 2019-01-24 2020-05-26 Rohde & Schwarz Gmbh & Co. Kg Method and apparatus for estimation of a bit rate of a digital signal
CN111585542A (en) * 2019-02-15 2020-08-25 广东石油化工学院 Method and filter for filtering power signal impulse noise

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101860512A (en) * 2010-05-07 2010-10-13 深圳国微技术有限公司 Impulse noise suppression and demapping soft decision method and system in multi-carrier system
CN107360111A (en) * 2017-06-01 2017-11-17 宁波大学 Impulsive Noise Mitigation Method in a kind of power line communication based on compressed sensing
CN108270497A (en) * 2018-01-19 2018-07-10 重庆邮电大学 A kind of pulse generation method of impulsive noise
CN109067433A (en) * 2018-09-04 2018-12-21 国网四川省电力公司电力科学研究院 Low-voltage powerline carrier communication noise suppressing method suitable for intelligent electric energy meter
US10666490B1 (en) * 2019-01-24 2020-05-26 Rohde & Schwarz Gmbh & Co. Kg Method and apparatus for estimation of a bit rate of a digital signal
CN111585542A (en) * 2019-02-15 2020-08-25 广东石油化工学院 Method and filter for filtering power signal impulse noise
CN111181891A (en) * 2019-10-21 2020-05-19 浙江万胜智能科技股份有限公司 Improved power line impulse noise suppression method based on compressed sensing
CN110719121A (en) * 2019-11-02 2020-01-21 广东石油化工学院 PLC channel impulse noise detection method and system using square exponential kernel

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