CN114745027B - Power line communication impulse noise identification method and system and storage medium - Google Patents
Power line communication impulse noise identification method and system and storage medium Download PDFInfo
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Abstract
The invention discloses a power line communication impulse noise identification method and system and a storage medium, wherein the method comprises the following steps: collecting signals in a power line communication channel, wherein the signals comprise a plurality of sampling points; acquiring probability density of the signal, and acquiring an accumulated distribution function according to the probability density; determining an amplitude threshold of the signal according to the accumulated distribution function and the probability threshold; determining sampling points exceeding the amplitude threshold and sampling points not exceeding the amplitude threshold in a plurality of sampling points according to the amplitude threshold; and determining whether impulse noise exists according to the sampling points exceeding the amplitude threshold and the sampling points not exceeding the amplitude threshold. Therefore, the method judges whether impulse noise exists or not based on the statistical analysis of the signals obtained by sampling, has low complexity and high instantaneity, and improves the recognition accuracy of the impulse noise.
Description
Technical Field
The present invention relates to the field of communication noise recognition technology, and in particular, to a power line communication impulse noise recognition method, a computer readable storage medium, and a power line communication impulse noise recognition system.
Background
The power line communication network has incomparable coverage advantages, and also has the advantages of no need of rewiring, quick deployment, low cost and the like. At present, a large number of power line communication terminals are deployed in China, and along with continuous expansion of technologies and applications of smart grids, smart home and the like, the power line carrier communication has wider and wider market demand application prospects. However, there are a large number of branches and electrical devices in the power line communication system, and a large amount of noise is generated in the power line communication channel. Such as background color noise caused by common household appliances, narrowband interference caused by wireless signals outside the power grid, impact noise caused by disconnecting switches, circuit breakers and the like, periodic impulse noise synchronous with the power frequency caused by power frequency switching devices (rectifier diodes) and the like, periodic impulse noise asynchronous with the power frequency caused by switching power supplies and the like, random impulse noise caused by switching transients and the like. The random impulse noise has high randomness and high noise intensity, and can cause serious damage to the power line communication system. Therefore, identifying noise characteristics in a PLC (Power Line Communications, power line communication) channel, particularly whether there is an obvious impulse noise characteristic, and thus turning on impulse noise suppression has important engineering application value for improving PLC communication performance.
In the related art, whether impulse noise exists in a PLC channel is judged by using two parameters of an absolute variance average ratio and a noise threshold, and the setting of the noise threshold influences the detection result to a great extent. Or judging whether impulse noise exists by setting a plurality of sections of minimum pulse amplitude threshold values, designing the duration of each section of pulse and other conditions on the channel sampling point, wherein the maximum pulse amplitude threshold value, the maximum time and the minimum time of one pulse duration are difficult to determine.
In addition, in actual signal reception, processing of impulse noise is provided between an ADC (Analog-to-Digital Converter ) and a synchronization/demodulation link. In general, impulse noise is identified by buffering a segment of sampled data, and in addition, the complexity of hardware implementation and the real-time performance of signal processing are also required to be considered for impulse noise identification, so that too complex algorithm has the defects of high complexity and low calculation real-time performance.
Disclosure of Invention
The present invention aims to solve at least one of the technical problems in the related art to some extent. Therefore, a first object of the present invention is to provide a method for identifying impulse noise of power line communication, which is capable of determining whether impulse noise exists based on statistical analysis of signals obtained by sampling, and has low complexity, high real-time performance, and improved accuracy of identifying impulse noise.
A second object of the present invention is to propose a computer readable storage medium.
A third object of the present invention is to provide a power line communication impulse noise identification system.
To achieve the above object, an embodiment of a first aspect of the present invention provides a method for identifying impulse noise of power line communication, including: collecting signals in a power line communication channel, wherein the signals comprise a plurality of sampling points; acquiring probability density of the signal, and acquiring an accumulated distribution function according to the probability density; determining an amplitude threshold of the signal according to the accumulated distribution function and the probability threshold; determining sampling points exceeding the amplitude threshold and sampling points not exceeding the amplitude threshold in a plurality of sampling points according to the amplitude threshold; and determining whether impulse noise exists according to the sampling points exceeding the amplitude threshold and the sampling points not exceeding the amplitude threshold.
According to the power line communication impulse noise identification method, firstly, signals in a power line communication channel are collected, probability density of the signals is obtained, an accumulated distribution function is obtained according to the probability density, an amplitude threshold of the signals is determined according to the accumulated distribution function and a probability threshold, sampling points exceeding the amplitude threshold and sampling points not exceeding the amplitude threshold in a plurality of sampling points are determined according to the amplitude threshold, and finally whether impulse noise exists is determined according to the sampling points exceeding the amplitude threshold and the sampling points not exceeding the amplitude threshold. Therefore, the method judges whether impulse noise exists or not based on the statistical analysis of the signals obtained by sampling, has low complexity and high instantaneity, and improves the recognition accuracy of the impulse noise.
In addition, the power line communication impulse noise identification method according to the above embodiment of the present invention may further have the following additional technical features:
According to one embodiment of the present invention, determining whether impulse noise exists according to a sampling point exceeding an amplitude threshold and a sampling point not exceeding the amplitude threshold includes: acquiring a first average power of sampling points exceeding an amplitude threshold, and acquiring a second average power of sampling points not exceeding the amplitude threshold; acquiring a power ratio according to the first average power and the second average power; and determining whether impulse noise exists according to the power ratio.
According to one embodiment of the invention, determining whether impulse noise is present based on the power ratio comprises: when the power ratio is larger than a set threshold value, determining that impulse noise exists; and when the power ratio is smaller than or equal to a set threshold value, determining that impulse noise is not present.
According to one embodiment of the invention, the power ratio is obtained by the following formula:
Wherein PNPR denotes a power ratio, E { Num (n i)*xi 2 } denotes a first average power, E { (1-Num (n i))*xi 2 } denotes a second average power), num (n i) denotes an identification of a sampling point if the amplitude threshold is exceeded, num (n i) =1 when the amplitude threshold is exceeded, and conversely, num (n i)＝0,ni denotes a sampling point, i=0, 1,2, …, x i denotes the amplitude of the sampling point.
According to one embodiment of the invention, determining the amplitude threshold of the pulse signal according to the cumulative distribution function and the probability threshold comprises: determining a probability threshold of each sampling point according to the accumulated distribution function; sequentially comparing the probability threshold of each sampling point with a probability threshold according to the time sequence; and taking the amplitude value of the sampling point with the probability threshold larger than the probability threshold value of the sampling point determined for the first time as the amplitude value threshold.
According to one embodiment of the present invention, determining, according to an amplitude threshold, a sampling point exceeding the amplitude threshold and a sampling point not exceeding the amplitude threshold from a plurality of sampling points includes: acquiring the amplitude values of a plurality of sampling points; when the amplitude of the sampling point is greater than or equal to the amplitude threshold, determining the sampling point as the sampling point exceeding the amplitude threshold; and when the amplitude of the sampling point is smaller than the amplitude threshold, determining the sampling point as the sampling point which does not exceed the amplitude threshold.
According to one embodiment of the invention, the probability density of a signal is obtained by the following formula:
Where P (x) represents the probability density, x represents the magnitude of the sample point, and σ represents the variance.
According to one embodiment of the present invention, the power line communication impulse noise identification method further includes: respectively obtaining the number of continuous sampling points in the sampling points which do not exceed the amplitude threshold; obtaining the maximum value of the number of continuous sampling points; the sparsity of the impulse noise is determined from the maximum value.
To achieve the above object, a second aspect of the present invention provides a computer-readable storage medium having stored thereon a power line communication impulse noise identification program which, when executed by a processor, implements the above power line communication impulse noise identification method.
According to the computer readable storage medium, the power line communication impulse noise identification method is realized by executing the power line communication impulse noise identification program stored on the processor, the complexity is low, the instantaneity is high, and the identification precision of impulse noise is improved.
To achieve the above object, an embodiment of a third aspect of the present invention provides a power line communication impulse noise identification system, including: the signal acquisition module is used for acquiring signals in the power line communication channel, wherein the signals comprise a plurality of sampling points; the acquisition module is used for acquiring the probability density of the signal; the calculation module is used for obtaining an accumulated distribution function according to the probability density; the first determining module is used for determining the amplitude threshold of the signal according to the accumulated distribution function and the probability threshold; the second determining module is used for determining sampling points exceeding the amplitude threshold and sampling points not exceeding the amplitude threshold in the plurality of sampling points according to the amplitude threshold; and the third determining module is used for determining whether impulse noise exists according to the sampling points exceeding the amplitude threshold and the sampling points not exceeding the amplitude threshold.
According to the power line communication impulse noise identification system, signals in a power line communication channel are acquired through a signal acquisition module, probability density of the signals is acquired through an acquisition module, an accumulated distribution function is acquired through a calculation module according to the probability density, an amplitude threshold of the signals is determined through a first determination module according to the accumulated distribution function and a probability threshold, sampling points exceeding the amplitude threshold and sampling points not exceeding the amplitude threshold in a plurality of sampling points are determined through a second determination module according to the amplitude threshold, and a third determination module determines whether impulse noise exists according to the sampling points exceeding the amplitude threshold and the sampling points not exceeding the amplitude threshold. Therefore, the system judges whether impulse noise exists or not based on the statistical analysis of the signals obtained by sampling, the complexity is low, the real-time performance is high, and the recognition accuracy of the impulse noise is improved.
In addition, the power line communication impulse noise identification system according to the above embodiment of the present invention may further have the following additional technical features:
According to one embodiment of the present invention, the third determining module determines whether impulse noise exists according to the sampling points exceeding the amplitude threshold and the sampling points not exceeding the amplitude threshold, and is specifically configured to: acquiring a first average power of sampling points exceeding an amplitude threshold, and acquiring a second average power of sampling points not exceeding the amplitude threshold; acquiring a power ratio according to the first average power and the second average power; and determining whether impulse noise exists according to the power ratio.
According to one embodiment of the present invention, the third determining module determines whether impulse noise exists according to the power ratio, specifically for: when the power ratio is larger than a set threshold value, determining that impulse noise exists; and when the power ratio is smaller than or equal to a set threshold value, determining that impulse noise is not present.
According to one embodiment of the invention, the power ratio is obtained by the following formula:
Wherein PNPR denotes a power ratio, E { Num (n i)*r(ni)2 } denotes a first average power, E { (1-Num (n i))*r(ni)2 } denotes a second average power), num (n i) denotes an identification of a sampling point if the amplitude threshold is exceeded, num (n i) =1 when the amplitude threshold is exceeded, and conversely, num (n i)＝0,ni denotes a sampling point, i=0, 1,2, …, x i denotes the amplitude of the sampling point.
According to one embodiment of the present invention, the first determining module determines the amplitude threshold of the pulse signal according to the cumulative distribution function and the probability threshold, and is specifically configured to: determining a probability threshold of each sampling point according to the accumulated distribution function; sequentially comparing the probability threshold of each sampling point with a probability threshold according to the time sequence; and taking the amplitude value of the sampling point with the probability threshold larger than the probability threshold value of the sampling point determined for the first time as the amplitude value threshold.
According to one embodiment of the present invention, the second determining module determines, according to the amplitude threshold, a sampling point exceeding the amplitude threshold and a sampling point not exceeding the amplitude threshold from among the plurality of sampling points, and is specifically configured to: acquiring the amplitude values of a plurality of sampling points; when the amplitude of the sampling point is greater than or equal to the amplitude threshold, determining the sampling point as the sampling point exceeding the amplitude threshold; and when the amplitude of the sampling point is smaller than the amplitude threshold, determining the sampling point as the sampling point which does not exceed the amplitude threshold.
According to one embodiment of the invention, the probability density of a signal is obtained by the following formula:
Where P (x) represents the probability density, x represents the magnitude of the sample point, and σ represents the variance.
According to an embodiment of the invention, the third determining module is further configured to: respectively obtaining the number of continuous sampling points in the sampling points which do not exceed the amplitude threshold; obtaining the maximum value of the number of continuous sampling points; the sparsity of the impulse noise is determined from the maximum value.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
Fig. 1 is a flowchart of a power line communication impulse noise identification method according to an embodiment of the present invention;
Fig. 2 is a flowchart of a power line communication impulse noise identification method according to one embodiment of the present invention;
FIG. 3 is a waveform diagram of Gaussian white noise samples according to an embodiment of the invention;
FIG. 4 is a diagram illustrating a distribution of sample positions of Gaussian white noise samples exceeding a statistical threshold according to an embodiment of the invention;
FIG. 5 is a second diagram illustrating a distribution of sample positions of Gaussian white noise samples exceeding a statistical threshold according to an embodiment of the invention;
FIG. 6 is a third exemplary distribution of sample positions of Gaussian white noise samples exceeding a statistical threshold according to an embodiment of the invention;
FIG. 7 is a diagram of a national network standard test pulse sample waveform according to one embodiment of the present invention;
FIG. 8 is a probability density function of national network standard test impulse noise according to one embodiment of the invention;
FIG. 9 is a schematic diagram of sample point location distribution of national network standard test pulse samples exceeding a statistical threshold value according to one embodiment of the present invention;
fig. 10 is a block diagram of a power line communication impulse noise identification system according to an embodiment of the invention.
Detailed Description
Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are illustrative and intended to explain the present invention and should not be construed as limiting the invention.
The power line communication impulse noise identification method, the computer-readable storage medium, and the power line communication impulse noise identification system according to the embodiments of the present invention are described below with reference to the accompanying drawings.
Fig. 1 is a flowchart of a power line communication impulse noise identification method according to an embodiment of the present invention.
As shown in fig. 1, the method for identifying impulse noise of power line communication according to an embodiment of the present invention may include:
S1, collecting signals in a power line communication channel, wherein the signals comprise a plurality of sampling points.
Specifically, the signal in the power line communication channel is sampled in the sampling period t to obtain a plurality of sampling points, and a corresponding discrete input signal is obtained as an input signal of the impulse noise identification method, that is, the signal obtained by collection is a discrete input signal which is collected from the power line communication channel and contains a plurality of signals such as a power line carrier communication signal, an interference noise signal, a background noise signal and the like, that is, the sampling points obtained at each sampling time include a plurality of signals such as the power line carrier communication signal, the interference noise signal, the background noise signal and the like in the power line communication channel.
S2, acquiring the probability density of the signal, and acquiring an accumulated distribution function according to the probability density.
According to one embodiment of the invention, the probability density of a signal is obtained by the following formula:
Where P (x) represents the probability density, x represents the magnitude of the sample point, and σ represents the variance.
Specifically, the acquired signals are in Rayleigh distribution, and the amplitude values of the acquired sampling points are substituted into the formula (1) to obtain the probability density of the acquired signals. The amplitude x of the sampling point is the sum of the amplitudes of a plurality of signals such as a power line carrier communication signal, an interference noise signal, a background noise signal and the like obtained at the sampling moment. Then through the formulaAnd calculating to obtain the cumulative distribution function of the signals.
S3, determining the amplitude threshold of the signal according to the accumulated distribution function and the probability threshold.
According to one embodiment of the invention, determining the amplitude threshold of the pulse signal according to the cumulative distribution function and the probability threshold comprises: determining a probability threshold of each sampling point according to the accumulated distribution function; sequentially comparing the probability threshold of each sampling point with a probability threshold according to the time sequence; and taking the amplitude value of the sampling point with the probability threshold larger than the probability threshold value of the sampling point determined for the first time as the amplitude value threshold. The probability threshold can be set according to actual conditions, and is smaller than 1 and generally takes a value between 0.7 and 0.98.
Specifically, the probability of the occurrence of the amplitude of each sampling point is calculated according to the cumulative distribution function and is used as a probability threshold of each sampling point, and meanwhile, the probability threshold is sequentially compared with the probability threshold according to the sampling time until the probability threshold of the sampling point which is larger than the probability threshold is generated, and when the probability threshold of the sampling point is larger than the probability threshold, the comparison is stopped, and the amplitude of the sampling point is used as the amplitude threshold.
S4, determining sampling points exceeding the amplitude threshold and sampling points not exceeding the amplitude threshold in the plurality of sampling points according to the amplitude threshold.
According to one embodiment of the present invention, determining, according to an amplitude threshold, a sampling point exceeding the amplitude threshold and a sampling point not exceeding the amplitude threshold from a plurality of sampling points includes: acquiring the amplitude values of a plurality of sampling points; when the amplitude of the sampling point is greater than or equal to the amplitude threshold, determining the sampling point as the sampling point exceeding the amplitude threshold; and when the amplitude of the sampling point is smaller than the amplitude threshold, determining the sampling point as the sampling point which does not exceed the amplitude threshold.
Specifically, the amplitude of the sampling point in the signal obtained by sampling is compared with the amplitude threshold obtained by the calculation, and the number of the sampling points with the amplitude greater than or equal to the amplitude threshold and the number of the sampling points with the amplitude smaller than the amplitude threshold are calculated respectively.
S5, determining whether impulse noise exists according to the sampling points exceeding the amplitude threshold and the sampling points not exceeding the amplitude threshold.
According to one embodiment of the present invention, determining whether impulse noise exists according to a sampling point exceeding an amplitude threshold and a sampling point not exceeding the amplitude threshold includes: acquiring a first average power of sampling points exceeding an amplitude threshold, and acquiring a second average power of sampling points not exceeding the amplitude threshold; acquiring a power ratio according to the first average power and the second average power; and determining whether impulse noise exists according to the power ratio.
According to one embodiment of the invention, the power ratio is obtained by the following formula:
Wherein PNPR denotes a power ratio, E { Num (n i)*xi 2 } denotes a first average power, E { (1-Num (n i))*xi 2 } denotes a second average power), num (n i) denotes an identification of a sampling point if the amplitude threshold is exceeded, num (n i) =1 when the amplitude threshold is exceeded, and conversely, num (n i)＝0,ni denotes a sampling point, i=0, 1,2, …, x i denotes the amplitude of the sampling point.
According to one embodiment of the invention, determining whether impulse noise is present based on the power ratio comprises: when the power ratio is larger than a set threshold value, determining that impulse noise exists; and when the power ratio is smaller than or equal to a set threshold value, determining that impulse noise is not present. The setting threshold value can be set according to actual conditions.
Specifically, assuming that the number of sampling points is 5, the number is represented by n 0、n1、n2、n3、n4, where the amplitude x 2、x3 of the sampling point n 2、n3 exceeds the amplitude threshold, the amplitude of the sampling point n 0、n1、n4 does not exceed the amplitude threshold, then the sampling point n 2、n3 is a pulse interference sampling point, the average power of the two sampling points is a first average power, the value of Num (n 2)、Num(n3) is 1, the sampling point n 0、n1、n4 is not a pulse interference sampling point, the average power of the three sampling points is a second average power, the value of Num (n 0)、Num(n1)、Num(n4) is 0, then a power ratio is calculated according to formula (2), and then the power ratio is compared with a set threshold, if the power ratio is greater than the set threshold, then pulse noise exists in the power line communication channel, otherwise, pulse noise does not exist.
According to one embodiment of the present invention, the power line communication pulse identification method further includes: respectively obtaining the number of continuous sampling points in the sampling points which do not exceed the amplitude threshold; obtaining the maximum value of the number of continuous sampling points; and determining the sparsity of the impulse noise according to the maximum value.
Specifically, an observation window is first set, the number of sampling points of continuous 0 in Num (n i) within the observation window is counted, and the maximum value of the number of continuous 0 is taken as a parameter of existence or sparsity of a reaction pulse, denoted as NegNum, and since the size l_noise of the observation window varies, identification is performed with a normalization parameter, namely NegNum/l_noise. This parameter may reflect the time-sparse nature of impulse noise, with a larger parameter meaning that impulse noise is more sparse.
Further, as a specific embodiment of the present invention, as shown in fig. 2, the power line communication impulse noise identification method of the embodiment of the present invention includes the following steps:
s101, setting a probability threshold.
S102, collecting signals in a power line communication channel.
S103, calculating the probability density of the signal amplitude.
S104, calculating an accumulated distribution function according to the probability density.
S105, searching from the cumulative distribution function to obtain the amplitude threshold of the sampled signal according to the probability threshold.
S106, obtaining the distribution Num of the sampling points exceeding and not exceeding the amplitude threshold.
S107, calculating the power ratio of the sampling point exceeding the amplitude threshold to the sampling point not exceeding the amplitude threshold.
S108, judging whether the power ratio is larger than a set threshold. If not, go to step S109; if yes, go to step S110.
S109, the power line communication channel is free of impulse noise.
S110, counting the number of sampling points with continuous 0 in Num to obtain a maximum value NegNum of the number with continuous 0.
S111, determining sparsity of impulse noise according to NegNum/L_noise. Where l_noise is the size of the observation window.
S112, impulse noise exists in the power line communication channel.
The technical effects of the power line communication impulse noise identification method of the present invention are further described below in conjunction with simulation experiments.
Fig. 3 is a gaussian white noise sample waveform, fig. 4 is a gaussian white noise Num generated by a probability threshold p_th=0.90, fig. 5 is a gaussian white noise Num generated by a probability threshold p_th=0.95, and fig. 6 is a gaussian white noise Num generated by a probability threshold p_th=0.98. The invention extracts the same Gaussian white noise by using different probability thresholds, and can find out that the Num graph can reflect the sparsity of the noise by referring to fig. 4, 5 and 6, and the sparsity of the noise is related to the size of the probability threshold, and the larger the probability threshold is, the more obvious the sparsity is.
Fig. 7 is a sample waveform of a national network standard test pulse, fig. 8 is a probability density function of the national network standard test pulse, fig. 9 is a national network standard test pulse Num graph generated by a probability threshold p_th=0.90, and comparing fig. 4 and fig. 9, the invention extracts different noises by using the same probability threshold, and can see that the number and the proportion of samples exceeding the threshold are relatively close when the national network standard test pulse is given with the same probability threshold, but the distribution of the two samples is different, and the national network standard test pulse shows the sparse characteristic of the period, so the Num graph can reflect the existence and the characteristic of the pulse noise to a certain extent, and the Num graph shows sparse and approximate periodic characteristics, but can not accurately determine whether the pulse noise exists and the characteristic only through the Num graph.
Further, referring to table 1, the peak-to-average power ratio PAPR (Peak to Average Power Ratio) =12 dB obtained under the white gaussian noise, and the peak-to-average power ratio papr=12.5 dB obtained by the national network standard test pulse, so that the white gaussian noise is similar to the PAPR of the national network standard test pulse, and the PAPR parameter is not suitable as a basis for judging whether the impulse noise exists. Under Gaussian white noise, the power ratio PNPR of the first average power of the sampling points exceeding the amplitude threshold to the second average power of the sampling points not exceeding the amplitude threshold is 8.7 when the probability threshold p_th=0.98, and is 8.3 when the probability threshold p_th=0.95; when the probability threshold p_th=0.90 is 8.5, taking the average value of the above three embodiments as the power ratio PNPR =8.5, it can be judged by PNPR that the gaussian noise has no impulse noise interference. Under the national network standard test pulse, PNPR =28.46 has larger value, and the existence of strong impulse noise interference can be judged through PNPR, so the defined power ratio PNPR can be used for judging whether impulse noise exists in a power line communication channel or not, and the intensity of the impulse noise can be reflected.
TABLE 1
Therefore, the power line communication impulse noise identification method disclosed by the invention solves the identification problem of whether impulse noise appears in the PLC, gives out the statistical characteristics of the impulse noise, has low complexity and high real-time performance, and improves the identification precision of the impulse noise.
In summary, according to the method for identifying impulse noise of power line communication in the embodiment of the present invention, firstly, signals in a power line communication channel are collected, wherein the signals include a plurality of sampling points, probability density of the signals is obtained, an accumulated distribution function is obtained according to the probability density, an amplitude threshold of the signals is determined according to the accumulated distribution function and a probability threshold, then sampling points exceeding the amplitude threshold and sampling points not exceeding the amplitude threshold in the plurality of sampling points are determined according to the amplitude threshold, and finally whether impulse noise exists is determined according to the sampling points exceeding the amplitude threshold and the sampling points not exceeding the amplitude threshold. Therefore, the method judges whether impulse noise exists or not based on the statistical analysis of the signals obtained by sampling, has low complexity and high instantaneity, and improves the recognition accuracy of the impulse noise.
The present invention also proposes a computer-readable storage medium corresponding to the above-described embodiments.
A computer-readable storage medium according to an embodiment of the present invention has stored thereon a power line communication impulse noise identification program which, when executed by a processor, implements the above-described power line communication impulse noise identification method.
According to the computer readable storage medium, the power line communication impulse noise identification method is realized by executing the power line communication impulse noise identification program stored on the processor, the complexity is low, the instantaneity is high, and the identification precision of impulse noise is improved.
Corresponding to the embodiment, the invention also provides a power line communication impulse noise identification system.
As shown in fig. 10, the power line communication impulse noise identification system according to the embodiment of the present invention may include: the system comprises a signal acquisition module 10, an acquisition module 20, a calculation module 30, a first determination module 40, a second determination module 50 and a third determination module 60.
The signal acquisition module 10 is configured to acquire a signal in a power line communication channel, where the signal includes a plurality of sampling points. The acquisition module 20 is configured to acquire a probability density of the signal. The calculation module 30 is configured to obtain a cumulative distribution function according to the probability density. The first determining module 40 is configured to determine an amplitude threshold of the signal according to the cumulative distribution function and the probability threshold. The second determining module 50 is configured to determine, according to the amplitude threshold, a sampling point exceeding the amplitude threshold and a sampling point not exceeding the amplitude threshold from the plurality of sampling points. The third determining module 60 is configured to determine whether impulse noise exists according to the sampling points exceeding the amplitude threshold and the sampling points not exceeding the amplitude threshold.
According to one embodiment of the present invention, the third determining module 60 determines whether impulse noise exists according to the sampling points exceeding the amplitude threshold and the sampling points not exceeding the amplitude threshold, specifically for: acquiring a first average power of sampling points exceeding an amplitude threshold, and acquiring a second average power of sampling points not exceeding the amplitude threshold; acquiring a power ratio according to the first average power and the second average power; and determining whether impulse noise exists according to the power ratio.
According to one embodiment of the present invention, the third determining module 60 determines whether impulse noise exists according to the power ratio, specifically for: when the power ratio is larger than a set threshold value, determining that impulse noise exists; and when the power ratio is smaller than or equal to a set threshold value, determining that impulse noise is not present.
According to one embodiment of the invention, the power ratio is obtained by the following formula:
Wherein PNPR denotes a power ratio, E { Num (n i)*r(ni)2 } denotes a first average power, E { (1-Num (n i))*r(ni)2 } denotes a second average power), num (n i) denotes an identification of a sampling point if the amplitude threshold is exceeded, num (n i) =1 when the amplitude threshold is exceeded, and conversely, num (n i)＝0,ni denotes a sampling point, i=0, 1,2, …, x i denotes the amplitude of the sampling point.
According to one embodiment of the present invention, the first determining module 40 determines the amplitude threshold of the pulse signal according to the cumulative distribution function and the probability threshold, specifically for: determining a probability threshold of each sampling point according to the accumulated distribution function; sequentially comparing the probability threshold of each sampling point with a probability threshold according to the time sequence; and taking the amplitude value of the sampling point with the probability threshold larger than the probability threshold value of the sampling point determined for the first time as the amplitude value threshold.
According to one embodiment of the present invention, the second determining module 50 determines, according to the amplitude threshold, a sampling point exceeding the amplitude threshold and a sampling point not exceeding the amplitude threshold from the plurality of sampling points, specifically for: acquiring the amplitude values of a plurality of sampling points; when the amplitude of the sampling point is greater than or equal to the amplitude threshold, determining the sampling point as the sampling point exceeding the amplitude threshold; and when the amplitude of the sampling point is smaller than the amplitude threshold, determining the sampling point as the sampling point which does not exceed the amplitude threshold.
According to one embodiment of the invention, the probability density of a signal is obtained by the following formula:
Where P (x) represents the probability density, x represents the magnitude of the sample point, and σ represents the variance.
According to one embodiment of the invention, the third determining module 60 is specifically further configured to: respectively obtaining the number of continuous sampling points in the sampling points which do not exceed the amplitude threshold; obtaining the maximum value of the number of continuous sampling points; the sparsity of the impulse noise is determined from the maximum value.
It should be noted that, for details not disclosed in the power line communication impulse noise identification system according to the embodiment of the present invention, please refer to details disclosed in the power line communication impulse noise identification method according to the above embodiment of the present invention, and details thereof are not described herein.
According to the power line communication impulse noise identification system, signals in a power line communication channel are acquired through a signal acquisition module, probability density of the signals is acquired through an acquisition module, an accumulated distribution function is acquired through a calculation module according to the probability density, an amplitude threshold of the signals is determined through a first determination module according to the accumulated distribution function and a probability threshold, sampling points exceeding the amplitude threshold and sampling points not exceeding the amplitude threshold in a plurality of sampling points are determined through a second determination module according to the amplitude threshold, and a third determination module determines whether impulse noise exists according to the sampling points exceeding the amplitude threshold and the sampling points not exceeding the amplitude threshold. Therefore, the system judges whether impulse noise exists or not based on the statistical analysis of the signals obtained by sampling, the complexity is low, the real-time performance is high, and the recognition accuracy of the impulse noise is improved.
It should be noted that the logic and/or steps represented in the flowcharts or otherwise described herein, for example, may be considered as a ordered listing of executable instructions for implementing logical functions, and may be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). In addition, the computer readable medium may even be paper or other suitable medium on which the program is printed, as the program may be electronically captured, via, for instance, optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner, if necessary, and then stored in a computer memory.
It is to be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, may be implemented using any one or combination of the following techniques, as is well known in the art: discrete logic circuits having logic gates for implementing logic functions on data signals, application specific integrated circuits having suitable combinational logic gates, programmable Gate Arrays (PGAs), field Programmable Gate Arrays (FPGAs), and the like.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In the description of the present invention, the meaning of "plurality" means at least two, for example, two, three, etc., unless specifically defined otherwise.
In the present invention, unless explicitly specified and limited otherwise, the terms "mounted," "connected," "secured," and the like are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally formed; can be mechanically or electrically connected; either directly or indirectly, through intermediaries, or both, may be in communication with each other or in interaction with each other, unless expressly defined otherwise. The specific meaning of the above terms in the present invention can be understood by those of ordinary skill in the art according to the specific circumstances.
While embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the invention, and that variations, modifications, alternatives and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the invention.
Claims (15)
1. A power line communication impulse noise identification method, comprising:
collecting signals in a power line communication channel, wherein the signals comprise a plurality of sampling points;
Acquiring probability density of the signal, and acquiring an accumulated distribution function according to the probability density;
determining an amplitude threshold of the signal according to the accumulated distribution function and a probability threshold;
determining sampling points exceeding the amplitude threshold and sampling points not exceeding the amplitude threshold in the plurality of sampling points according to the amplitude threshold;
determining whether impulse noise exists according to the sampling points exceeding the amplitude threshold and the sampling points not exceeding the amplitude threshold;
wherein determining the amplitude threshold of the impulse noise according to the cumulative distribution function and the probability threshold comprises:
Determining a probability threshold of each sampling point according to the accumulated distribution function;
sequentially comparing the probability threshold of each sampling point with the probability threshold according to the time sequence;
and taking the amplitude of the sampling point with the probability threshold larger than the probability threshold value determined for the first time as the amplitude threshold.
2. The method of claim 1, wherein determining whether impulse noise is present based on the sampling points exceeding the amplitude threshold and the sampling points not exceeding the amplitude threshold comprises:
acquiring a first average power of the sampling points exceeding the amplitude threshold, and acquiring a second average power of the sampling points not exceeding the amplitude threshold;
acquiring a power ratio according to the first average power and the second average power;
and determining whether impulse noise exists according to the power ratio.
3. The power line communication impulse noise identification method according to claim 2, wherein determining whether impulse noise is present according to the power ratio comprises:
when the power ratio is larger than a set threshold value, determining that impulse noise exists;
And when the power ratio is smaller than or equal to a set threshold value, determining that impulse noise does not exist.
4. The power line communication impulse noise identification method according to claim 2, wherein the power ratio is obtained by the following formula:
Wherein PNPR denotes the power ratio, E { Num (n i)*xi 2 } denotes the first average power, E { (1-Num (n i))*xi 2 } denotes the second average power), num (n i) denotes an identification of whether the sampling point exceeds the amplitude threshold, and Num (n i) =1 when the sampling point exceeds the amplitude threshold, whereas Num (n i)＝0,ni denotes the sampling point, i=0, 1,2, …, x i denotes the amplitude of the sampling point.
5. The method of claim 1, wherein determining, from the magnitude threshold, a sampling point of the plurality of sampling points that exceeds the magnitude threshold and a sampling point that does not exceed the magnitude threshold comprises:
Acquiring the amplitude values of a plurality of sampling points;
when the amplitude of the sampling point is greater than or equal to the amplitude threshold, determining the sampling point as the sampling point exceeding the amplitude threshold;
And when the amplitude of the sampling point is smaller than the amplitude threshold, determining the sampling point as the sampling point which does not exceed the amplitude threshold.
6. The power line communication impulse noise identification method according to claim 1, characterized in that the probability density of the signal is obtained by the following formula:
Where P (x) represents the probability density, x represents the magnitude of the sample point, and σ represents the variance.
7. The power line communication impulse noise identification method according to any one of claims 1 to 6, characterized by further comprising:
respectively obtaining the number of continuous sampling points in the sampling points which do not exceed the amplitude threshold;
obtaining the maximum value of the number of continuous sampling points;
And determining the sparsity of the impulse noise according to the maximum value.
8. A computer-readable storage medium, characterized in that a power line communication impulse noise identification program is stored thereon, which when executed by a processor implements the power line communication impulse noise identification method according to any one of claims 1-7.
9. A power line communication impulse noise identification system, comprising:
The signal acquisition module is used for acquiring signals in a power line communication channel, wherein the signals comprise a plurality of sampling points;
The acquisition module is used for acquiring the probability density of the signal;
the calculation module is used for obtaining an accumulated distribution function according to the probability density;
the first determining module is used for determining the amplitude threshold of the signal according to the accumulated distribution function and the probability threshold;
the second determining module is used for determining sampling points exceeding the amplitude threshold and sampling points not exceeding the amplitude threshold in the plurality of sampling points according to the amplitude threshold;
a third determining module, configured to determine whether impulse noise exists according to a sampling point exceeding the amplitude threshold and a sampling point not exceeding the amplitude threshold;
The first determining module determines an amplitude threshold of the impulse noise according to the cumulative distribution function and a probability threshold, and is specifically configured to:
Determining a probability threshold of each sampling point according to the accumulated distribution function;
sequentially comparing the probability threshold of each sampling point with the probability threshold according to the time sequence;
and taking the amplitude of the sampling point with the probability threshold larger than the probability threshold value determined for the first time as the amplitude threshold.
10. The power line communication impulse noise identification system of claim 9, wherein the third determining module is configured to determine whether impulse noise is present based on the sampling points exceeding the amplitude threshold and the sampling points not exceeding the amplitude threshold, and is specifically configured to:
acquiring a first average power of the sampling points exceeding the amplitude threshold, and acquiring a second average power of the sampling points not exceeding the amplitude threshold;
acquiring a power ratio according to the first average power and the second average power;
and determining whether impulse noise exists according to the power ratio.
11. The power line communication impulse noise identification system of claim 10, wherein a third determination module determines whether impulse noise is present based on the power ratio, in particular for:
when the power ratio is larger than a set threshold value, determining that impulse noise exists;
And when the power ratio is smaller than or equal to a set threshold value, determining that impulse noise does not exist.
12. The power line communication impulse noise identification system of claim 10, wherein the power ratio is obtained by the following formula:
Wherein PNPR denotes the power ratio, E { Num (n i)*xi 2 } denotes the first average power, E { (1-Num (n i))*xi 2 } denotes the second average power), num (n i) denotes an identification of whether the sampling point exceeds the amplitude threshold, and Num (n i) =1 when the sampling point exceeds the amplitude threshold, whereas Num (n i)＝0,ni denotes the sampling point, i=0, 1,2, …, x i denotes the amplitude of the sampling point.
13. The power line communication impulse noise identification system of claim 9, wherein the second determining module determines, according to the amplitude threshold, a sampling point of the plurality of sampling points that exceeds the amplitude threshold and a sampling point that does not exceed the amplitude threshold, specifically for:
Acquiring the amplitude values of a plurality of sampling points;
when the amplitude of the sampling point is greater than or equal to the amplitude threshold, determining the sampling point as the sampling point exceeding the amplitude threshold;
And when the amplitude of the sampling point is smaller than the amplitude threshold, determining the sampling point as the sampling point which does not exceed the amplitude threshold.
14. The power line communication impulse noise identification method according to claim 9, characterized in that the probability density of the signal is obtained by the following formula:
Where P (x) represents the probability density, x represents the magnitude of the sample point, and σ represents the variance.
15. The power line communication impulse noise identification system as claimed in any one of the claims 9-14, characterized in, that the third determination module is further adapted to:
respectively obtaining the number of continuous sampling points in the sampling points which do not exceed the amplitude threshold;
obtaining the maximum value of the number of continuous sampling points;
And determining the sparsity of the impulse noise according to the maximum value.
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