CN110661548A

CN110661548A - PLC signal filtering method and system utilizing L1 mode inversion

Info

Publication number: CN110661548A
Application number: CN201910867638.8A
Authority: CN
Inventors: 翟明岳
Original assignee: Guangdong University of Petrochemical Technology
Current assignee: Guangdong University of Petrochemical Technology
Priority date: 2019-09-13
Filing date: 2019-09-13
Publication date: 2020-01-07

Abstract

The embodiment of the invention discloses a PLC signal filtering method and a system utilizing L1 mode inversion, wherein the method comprises the following steps: step 1, inputting an actually measured PLC signal sequence S; step 2, carrying out noise filtering processing on the PLC signal sequence S according to an L1 model inversion theory, wherein the signal sequence after noise filtering is S_NEWSpecifically, S_NEWDR; wherein D is a selection matrix; and R is an L1 modulus vector.

Description

PLC signal filtering method and system utilizing L1 mode inversion

Technical Field

The invention relates to the field of electric power, in particular to a PLC signal filtering method and system.

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 over power line (NPL) and Broadband over power line (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 regulated bandwidth (3-148.5 kHz) of European CENELEC, a regulated bandwidth (9-490 kHz) of the U.S. Federal Communications Commission (FCC), a regulated bandwidth (9-450 kHz) of the Association of Radio Industries and Businesses (ARIB), and a regulated bandwidth (3-500 kHz) 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 the bandwidth limited between 1.6-30 MHz and the communication speed 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.

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, a common low-pass filter is difficult to achieve an ideal filtering effect in a non-stationarity and non-Gaussian noise environment, the non-stationarity and non-Gaussian noise is difficult to filter, and the performance of a PLC communication system is seriously influenced.

Disclosure of Invention

The invention aims to provide a PLC signal filtering method and a system utilizing L1 mode inversion, and the method utilizes the difference of a PLC modulation signal and background noise in L1 mode representation and distinguishes the PLC modulation signal and the background noise through an L1 mode inversion matrix. The method has good noise filtering performance and is simple in calculation.

In order to achieve the purpose, the invention provides the following scheme:

a PLC signal filtering method using L1 mode inversion, comprising:

step 1, inputting an actually measured PLC signal sequence S;

step 2, carrying out noise filtering processing on the PLC signal sequence S according to an L1 model inversion theory, wherein the signal sequence after noise filtering is S_NEWSpecifically, S_NEWDR; wherein D is a selection matrix; and R is an L1 modulus vector.

A PLC signal filtering system utilizing L1 mode inversion, comprising:

the acquisition module inputs an actually measured PLC signal sequence S;

the filtering module is used for carrying out noise filtering processing on the PLC signal sequence S according to an L1 model inversion theory, and the signal sequence after noise filtering is S_NEWSpecifically, S_NEWDR; wherein D is a selection matrix; and R is an L1 modulus vector.

According to the specific embodiment provided by the invention, the invention discloses the following technical effects:

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; 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, a common low-pass filter is difficult to achieve an ideal filtering effect in a non-stationarity and non-Gaussian noise environment, the non-stationarity and non-Gaussian noise is difficult to filter, and the performance of a PLC communication system is seriously influenced.

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 diagram 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 signal filtering method using L1 mode inversion

Fig. 1 is a schematic flow chart of a PLC signal filtering method using L1 mode inversion according to the present invention. As shown in fig. 1, the PLC signal filtering method using L1 mode inversion specifically includes the following steps:

step 1, inputting an actually measured PLC signal sequence S;

Before the step 2, the method further comprises:

and 3, solving the selection matrix D and the L1 model vector R.

The step 3 comprises the following steps:

step 301, calculating a mean value and a mean square error of the signal sequence S, specifically:

mean value of the signal sequence S

Mean square error of the signal sequence S

Wherein

s_n: the nth element [ N ═ 1,2, …, N of the signal sequence S]

N: length of the signal sequence S

Step 302, obtaining a threshold matrix, specifically:

H＝[h_ij]_N×N

wherein:

h_ij: ith row and jth column element of the threshold matrix

c_ij: the ith row and jth column elements in the covariance matrix C of the signal sequence S

C＝[S-m_S]^T[S-m_S]

[S-m_S]^T: vector [ S-m_S]Is transferred to

SNR: signal-to-noise ratio of the signal sequence S

Step 303, obtaining an L1 model transformation matrix G, specifically:

G＝HC+[S^TS]^-1

wherein:

[S^TS]^-1: matrix [ S ]^TS]Inverse matrix of

Step 304, solving the L1 modulo vector R, specifically:

R＝[I+F^-1G]HS

wherein:

F＝[S^TS-C]: depolarization matrix

I: unit matrix

Step 305, obtaining the selection matrix D, specifically:

FIG. 2 structural intent of a PLC signal filtering system using L1 mode inversion

Fig. 2 is a schematic structural diagram of a PLC signal filtering system using L1 mode inversion according to the present invention. As shown in fig. 2, the PLC signal filtering system using the L1 mode inversion includes the following structure:

the acquisition module 401 inputs an actually measured PLC signal sequence S;

the filtering module 402 is used for performing noise filtering processing on the PLC signal sequence S according to an L1 model inversion theory, wherein the signal sequence after noise filtering is S_NEWSpecifically, S_NEWDR; wherein D is a selection matrix; and R is an L1 modulus vector.

The system further comprises:

and a calculation module 403 for obtaining the selection matrix D and the modulo vector R of L1.

The calculation module 403 further includes the following units:

the first calculation unit 4031 calculates the mean and mean square error of the signal sequence S, specifically:

mean value of the signal sequence S

Mean square error of the signal sequence S

Wherein

s_n: the nth element [ N ═ 1,2, …, N of the signal sequence S]

N: length of the signal sequence S

The second calculation unit 4032 calculates a threshold matrix, which specifically includes:

H＝[h_ij]_N×N

wherein:

h_ij: ith row and jth column element of the threshold matrix

C＝[S-m_S]^T[S-m_S]

[S-m_S]^T: vector [ S-m_S]Is transferred to

SNR: signal-to-noise ratio of the signal sequence S

The third calculation unit 4033 calculates an L1 modulo conversion matrix G, which specifically is:

G＝HC+[S^TS]^-1

wherein:

[S^TS]^-1: matrix [ S ]^TS]Inverse matrix of

The fourth calculating unit 4034 calculates the modulo vector R of L1, which specifically is:

R＝[I+F^-1G]HS

wherein:

F＝[S^TS-C]: depolarization matrix

I: unit matrix

The fifth calculation unit 4035, which calculates the selection matrix D, specifically is:

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:

1. inputting measured PLC signal sequence

S＝[s₁,s₂,…,s_N-1,s_N]

Wherein:

s: measured PLC signal data sequence with length N

s_iI is 1,2, …, N is measured PLC signal with serial number i

2. Mean and mean square error are obtained

Mean value of the signal sequence S

Mean square error of the signal sequence S

Wherein

s_n: the nth element [ N ═ 1,2, …, N of the signal sequence S]

N: length of the signal sequence S

3. Determining a threshold matrix

H＝[h_ij]_N×N

Wherein:

h_ij: ith row and jth column element of the threshold matrix

C＝[S-m_S]^T[S-m_S]

[S-m_S]^T: vector [ S-m_S]Is transferred to

SNR: signal-to-noise ratio of the signal sequence S

4. Solving L1 model conversion matrix

G＝HC+[S^TS]^-1

Wherein:

[S^TS]^-1: matrix [ S ]^TS]Inverse matrix of

5. Solving the L1 model vector

R＝[I+F^-1G]HS

Wherein:

F＝[S^TS-C]: depolarization matrix

I: unit matrix

6. Determining a selection matrix

7. Filtering

According to the L1 mode inversion theory, the PLC signal sequence S is subjected to noise filtering processing, and the signal sequence after noise filtering is S_NEWSpecifically, S_NEWDR; wherein D is a selection matrix; and R is an L1 modulus vector.

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

1. A PLC signal filtering method using L1 mode inversion, comprising:

step 1, inputting an actually measured PLC signal sequence S;

2. The method of claim 1, wherein prior to step 2, the method further comprises:

and 3, solving the selection matrix D and the L1 model vector R.

3. The method of claim 2, wherein step 3 comprises:

mean value of the signal sequence S

Mean square error of the signal sequence S

Wherein

s_n: the nth element [ N ═ 1,2, …, N of the signal sequence S]

N: length of the signal sequence S

Step 302, obtaining a threshold matrix, specifically:

H＝[h_ij]_N×N

wherein:

h_ij: ith row and jth column element of the threshold matrix

C＝[S-m_S]^T[S-m_S]

[S-m_S]^T: vector [ S-m_S]Is transferred to

SNR: signal-to-noise ratio of the signal sequence S

Step 303, obtaining an L1 model transformation matrix G, specifically:

G＝HC+[S^TS]^-1

wherein:

[S^TS]^-1: matrix [ S ]^TS]Inverse matrix of

Step 304, solving the L1 modulo vector R, specifically:

R＝[I+F^-1G]HS

wherein:

F＝[S^TS-C]: depolarization matrix

I: unit matrix

Step 305, obtaining the selection matrix D, specifically:

4. a PLC signal filtering system using L1 mode inversion, comprising:

the acquisition module inputs an actually measured PLC signal sequence S;

5. The system of claim 4, further comprising:

and the calculation module is used for solving the selection matrix D and the L1 modulus vector R.