Signal noise reduction processing method and communication device

Abstract

The present application provides a signal processing method and apparatus, wherein the signal processing method includes: obtaining a signal segment containing impulse noise, the signal segment including N0 sampling points, where N0 is an integer greater than or equal to 1; calculating a signal-to-interference-and-noise ratio (SIR) corresponding to the signal segment, and determining a first noise reduction parameter corresponding to the signal segment based on the SIR; determining at least one sampling point from the N0 sampling points having an amplitude greater than the first noise reduction parameter, and performing noise reduction on the amplitude of the at least one sampling point. Using this application, noise reduction performance can be improved.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a signal noise reduction processing method and a communication device. Background Art

[0002] With the advancement of science and technology and improvements in living standards, people's demands for communication speed and quality are increasing. Power line communication (PLC) is a type of communication technology that uses power lines to transmit signals. Power lines are complex transmission media and can be harsh communication channels. PLC systems are subject to various types of noise, such as periodic impulse noise, Gaussian white noise, colored background noise, and power frequency noise. Among these, impulse noise has the greatest impact on PLC system quality, reducing transmission speed and degrading synchronization performance at the receiving end.

[0003] Existing methods for reducing impulse noise in signals mainly include the zeroing method, which sets a threshold and directly sets the amplitude of sampling points that exceed the threshold to zero. The selection of this threshold is directly related to the noise reduction effect. Currently, a threshold is uniformly set based on experience, and this method has relatively poor noise reduction performance. Summary of the Invention

[0004] The embodiments of the present application provide a signal noise reduction processing method and a communication device, which can specifically set a first noise reduction parameter corresponding to a signal segment, thereby improving noise reduction performance.

[0005] In a first aspect, embodiments of the present application provide a signal noise reduction processing method, which can be performed by a power line communication device or by a component of the power line communication device (e.g., a processor, a chip, or a chip system). The signal noise reduction processing method may include: obtaining a signal segment containing impulse noise, where the signal segment may include N0 sampling points, where N0 is an integer greater than or equal to 1. Further, calculating a signal-to-interference-and-noise ratio corresponding to the signal segment, and determining a first noise reduction parameter corresponding to the signal segment based on the signal-to-interference-and-noise ratio.

[0006] After determining the first noise reduction parameter corresponding to the signal segment, at least one sampling point having an amplitude greater than the first noise reduction parameter is determined from the N0 sampling points, and noise reduction processing is performed on the amplitude of the at least one sampling point.

[0007] By implementing the embodiments of the present application, a first noise reduction parameter corresponding to a signal segment can be determined based on the signal-to-interference-noise ratio corresponding to the signal segment, and at least one sampling point having an amplitude greater than the first noise reduction parameter is determined from the N0 sampling points included in the signal segment. Noise reduction processing is performed on the amplitude of the at least one sampling point, thereby specifically setting the first noise reduction parameter and improving noise reduction performance.

[0008] In one possible implementation, in the embodiment of the present application, the noise reduction processing for the amplitude of at least one sampling point may be performed by, for each sampling point of the at least one sampling point, obtaining a first sampling point and a second sampling point associated with the sampling point from the N0 sampling points, wherein the first sampling point is a sampling point that is before the sampling point and closest to the sampling point and has a value less than the first noise reduction parameter, and the second sampling point is a sampling point that is after the sampling point and closest to the sampling point and has a value less than the first noise reduction parameter.

[0009] Furthermore, the first amplitude is obtained based on the amplitude of the first sampling point and the amplitude of the second sampling point. For example, the first amplitude can be calculated based on the amplitude of the first sampling point and the amplitude of the second sampling point using an interpolation method. The interpolation method includes but is not limited to a linear interpolation method or a high-order interpolation method.

[0010] Update the amplitude of the sampling point to the calculated first amplitude.

[0011] By implementing this embodiment, the updated first amplitude of the sampling point can be calculated based on the amplitude of the first sampling point that is before the sampling point and closest to the sampling point and is smaller than the first noise reduction parameter, and the amplitude of the second sampling point that is after the sampling point and closest to the sampling point and is smaller than the first noise reduction parameter, thereby better eliminating the impulse noise and improving the noise reduction performance.

[0012] In one possible implementation, the method for obtaining a signal segment containing impulse noise in an embodiment of the present application may be to obtain a signal to be processed, where the signal to be processed includes n sampling points, where n is an integer greater than or equal to N0; for each of the n sampling points, obtain a preset number of consecutive sampling points starting from the sampling point; for example, a sliding window method can be used to obtain a preset number of sampling points, and the average power of the preset number of sampling points is calculated, and the average power is used as the sliding window energy corresponding to the sampling point.

[0013] Obtain a sliding window energy corresponding to each of the n sampling points, take a sampling point whose sliding window energy is greater than a first threshold as a starting sampling point, obtain N0 consecutive sampling points starting from the starting sampling point, and determine a signal segment composed of the N0 sampling points as a signal segment containing impulse noise.

[0014] By implementing this embodiment, it is possible to avoid determining a signal with a relatively large occasional amplitude change in a valid signal as containing impulse noise, thereby accurately obtaining a signal segment containing impulse noise.

[0015] In one possible implementation, the signal-to-interference-and-noise ratio (SINR) corresponding to a signal segment in the embodiment of the present application may be calculated by obtaining a feature value corresponding to the signal segment, where the feature value is used to represent a statistical feature of the signal segment. Furthermore, the SINR of the signal segment is calculated based on the feature value corresponding to the signal segment.

[0016] By implementing this embodiment, the signal-to-interference-and-noise ratio of the signal segment can be calculated conveniently and quickly based on the feature quantity corresponding to the signal segment.

[0017] In one possible implementation, the signal to interference plus noise ratio of the signal segment may be calculated based on the feature quantity corresponding to the signal segment by obtaining a first linear relationship satisfied between the feature quantity corresponding to the signal segment and the signal to interference plus noise ratio, and further calculating the signal to interference plus noise ratio of the signal segment based on the feature quantity corresponding to the signal segment and the first linear relationship.

[0018] By implementing this embodiment, the signal to interference plus noise ratio of the signal segment can be obtained quickly and accurately based on the first linear relationship satisfied between the characteristic quantity corresponding to the signal segment and the signal to interference plus noise ratio.

[0019] In a possible implementation, the characteristic quantity corresponding to the signal segment may be one or more of the following information: the average amplitude of the signal segment, the average power of the signal segment, the variance of the amplitude of the signal segment, and the maximum amplitude of the signal segment.

[0020] In one possible implementation, the first noise reduction parameter corresponding to the signal segment may be determined based on the signal-to-interference-plus-noise ratio. If the signal-to-interference-plus-noise ratio is less than a second threshold, a first set value may be determined as the first noise reduction parameter corresponding to the signal segment. That is, when the interfering impulse noise is relatively strong, a relatively small first noise reduction parameter may be set to achieve better noise reduction.

[0021] If the signal to interference plus noise ratio is greater than or equal to the second threshold, a second linear relationship between the signal to interference plus noise ratio and the first noise reduction parameter is obtained, and the first noise reduction parameter corresponding to the signal segment is calculated based on the signal to interference plus noise ratio and the second linear relationship.

[0022] By implementing this embodiment, the first noise reduction parameter can be set according to the signal to interference plus noise ratio in a targeted manner, thereby improving the noise reduction performance.

[0023] In a possible implementation, a signal segment after noise reduction processing is further obtained.

[0024] If the signal frame included in the signal segment is a first frame structure, synchronization processing is performed on the signal segment after noise reduction using a time-frequency joint synchronization algorithm, wherein the synchronization header of the first frame structure includes a preset number of preset sequences. For example, the synchronization header of the first frame structure includes 7 known repeating sequences.

[0025] If the signal frame included in the signal segment is not the first frame structure, a time domain autocorrelation algorithm is used to perform synchronization processing on the signal segment after the noise reduction processing.

[0026] By implementing this embodiment, synchronization processing can be further performed on the noise-reduced signal segments, thereby improving synchronization performance.

[0027] In a second aspect, an embodiment of the present application provides a communication device, which may be a power line communication device or a component of a power line communication device (such as a processor, a chip, or a chip system). The communication device may include an acquisition module, a calculation module, and a noise reduction module, wherein:

[0028] an acquisition module, configured to acquire a signal segment containing impulse noise, wherein the signal segment includes N0 sampling points, where N0 is an integer greater than or equal to 1;

[0029] a calculation module, configured to calculate a signal-to-interference-plus-noise ratio (SINR) corresponding to the signal segment, and determine a first noise reduction parameter corresponding to the signal segment based on the SINR;

[0030] The denoising module is configured to determine at least one sampling point whose amplitude is greater than the first denoising parameter from the N0 sampling points, and perform denoising on the amplitude of the at least one sampling point.

[0031] In one possible implementation, the noise reduction module is specifically configured to:

[0032] For each sampling point of the at least one sampling point, obtaining a first sampling point and a second sampling point associated with the sampling point from the N0 sampling points, wherein the first sampling point is a sampling point that is before the sampling point and closest to the sampling point and has a value less than the first noise reduction parameter, and the second sampling point is a sampling point that is after the sampling point and closest to the sampling point and has a value less than the first noise reduction parameter;

[0033] Obtaining a first amplitude according to the amplitude of the first sampling point and the amplitude of the second sampling point;

[0034] The amplitude of the sampling point is updated to the first amplitude.

[0035] In a possible implementation, the acquisition module is specifically configured to:

[0036] Acquire a signal to be processed, where the signal to be processed includes n sampling points, where n is an integer greater than or equal to N0;

[0037] For each of the n sampling points, obtaining a preset number of consecutive sampling points starting from the sampling point;

[0038] Calculating the average power of the preset number of sampling points, and using the average power as the sliding window energy corresponding to the sampling points;

[0039] Obtaining a sliding window energy corresponding to each of the n sampling points, taking a sampling point whose sliding window energy is greater than a first threshold as a starting sampling point, and obtaining N0 consecutive sampling points starting from the starting sampling point;

[0040] The signal segment consisting of the N0 sampling points is determined to be a signal segment containing impulse noise.

[0041] In one possible implementation, the calculation module is specifically configured to:

[0042] Acquiring a feature value corresponding to the signal segment, where the feature value is used to represent a statistical feature of the signal segment;

[0043] Calculate the signal to interference noise ratio of the signal segment according to the feature quantity corresponding to the signal segment.

[0044] In one possible implementation, the calculation module is specifically configured to:

[0045] Acquire a first linear relationship satisfied between a feature quantity corresponding to the signal segment and the signal to interference and noise ratio;

[0046] The signal to interference plus noise ratio (SINR) of the signal segment is calculated according to the feature quantity corresponding to the signal segment and the first linear relationship.

[0047] In a possible implementation, the characteristic quantity includes one or more of the following information: an average amplitude of the signal segment, an average power of the signal segment, a variance of the amplitude of the signal segment, and a maximum amplitude of the signal segment.

[0048] In one possible implementation, the calculation module is specifically configured to:

[0049] If the signal to interference plus noise ratio is less than a second threshold, determining a first set value as a first noise reduction parameter corresponding to the signal segment;

[0050] If the signal to interference plus noise ratio is greater than or equal to the second threshold, a second linear relationship satisfied by the signal to interference plus noise ratio and the first noise reduction parameter is obtained, and a first noise reduction parameter corresponding to the signal segment is calculated based on the signal to interference plus noise ratio and the second linear relationship.

[0051] In a possible implementation, the apparatus further includes:

[0052] A synchronization module is used to obtain the signal segment after the noise reduction processing; if the signal frame included in the signal segment is a first frame structure, a time-frequency joint synchronization algorithm is used to synchronize the signal segment after the noise reduction processing, wherein the synchronization header of the first frame structure includes a preset number of preset sequences; if the signal frame included in the signal segment is not a first frame structure, a time domain autocorrelation algorithm is used to synchronize the signal segment after the noise reduction processing.

[0053] In a third aspect, embodiments of the present application provide a communication device comprising a processor. The processor is coupled to a memory and configured to execute instructions in the memory to implement the method of the first aspect. Optionally, the communication device further comprises a memory. Optionally, the communication device further comprises a communication interface, the processor being coupled to the communication interface.

[0054] In a fourth aspect, an embodiment of the present application provides a processor, comprising: an input circuit, an output circuit, and a processing circuit. The processing circuit is configured to receive a signal through the input circuit and transmit a signal through the output circuit, so that the processor executes the method of the first aspect.

[0055] In a specific implementation, the processor may be one or more chips, the input circuit may be an input pin, the output circuit may be an output pin, and the processing circuit may be a transistor, a gate circuit, a trigger, or various logic circuits. The input signal received by the input circuit may be, for example, but not limited to, received and input by a receiver, and the signal output by the output circuit may be, for example, but not limited to, output to and transmitted by a transmitter. The input circuit and the output circuit may be the same circuit, which functions as an input circuit and an output circuit at different times. The embodiments of the present application do not limit the specific implementation of the processor and various circuits.

[0056] In a fifth aspect, an embodiment of the present application provides a processing device, comprising a processor and a memory. The processor is configured to read instructions stored in the memory and receive signals via a receiver and transmit signals via a transmitter to execute the method of the first aspect.

[0057] Optionally, there are one or more processors and one or more memories.

[0058] Optionally, the memory may be integrated with the processor, or the memory may be provided separately from the processor.

[0059] In the specific implementation process, the memory can be a non-transitory memory, such as a read-only memory (ROM), which can be integrated with the processor on the same chip or can be set on different chips. The embodiments of the present application do not limit the type of memory and the setting method of the memory and the processor.

[0060] The processing device in the fifth aspect described above may be one or more chips. The processor in the processing device may be implemented in hardware or software. When implemented in hardware, the processor may be a logic circuit, an integrated circuit, or the like; when implemented in software, the processor may be a general-purpose processor implemented by reading software code stored in a memory, which may be integrated into the processor or located independently of the processor.

[0061] In a sixth aspect, an embodiment of the present application provides a computer program product, which includes: a computer program (also referred to as code, or instructions), which, when executed, enables a computer to execute the method of the first aspect above.

[0062] In a seventh aspect, an embodiment of the present application provides a readable storage medium, which stores a computer program (also referred to as code, or instructions) that, when executed on a computer, enables the method of the first aspect described above to be implemented.

[0063] In an eighth aspect, a chip system is provided, comprising a processor and an interface circuit. The processor is configured to retrieve and execute a computer program (also referred to as code or instructions) stored in a memory to implement the functions described in the first aspect. In one possible design, the chip system further comprises a memory configured to store necessary program instructions and data. The chip system may consist of a chip alone or may include a chip and other discrete components. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 This is a schematic diagram of a received signal provided by the present application;

[0065] Figure 2 This is a simulation curve of SINR after noise reduction along with noise reduction parameters provided by the present application;

[0066] Figure 3 This is a flow chart of a signal noise reduction processing method provided by the present application;

[0067] Figure 4 This is a schematic diagram of energy changes of the received signal provided by this application;

[0068] Figure 5 is the energy normal curve after low-pass filtering provided by this application;

[0069] Figure 6 This is a schematic diagram of linear interpolation noise reduction provided by this application;

[0070] Figure 7 is a schematic diagram of another signal noise reduction processing method provided by the present application;

[0071] Figure 8 is a schematic diagram of a lookup table provided in this application;

[0072] Figure 9 It is a schematic diagram of a correlation curve provided by this application;

[0073] Figure 10 This is a schematic diagram of determining a rising edge provided by the present application;

[0074] Figure 11 This is a simulation diagram of a timing error provided by this application;

[0075] Figure 12 is a schematic diagram of a signal noise reduction processing method provided by the present application;

[0076] Figure 13 is a schematic block diagram of a communication device provided by the present application;

[0077] Figure 14 is a schematic block diagram of another communication device provided in an embodiment of the present application;

[0078] Figure 15 This is a schematic diagram of the structure of a chip provided in an embodiment of the present application. DETAILED DESCRIPTION

[0079] The following describes the process of simulating and obtaining the first linear relationship and the second linear relationship in this application. The first linear relationship refers to the relationship between the characteristic quantity corresponding to a signal segment and the signal-to-interference-and-noise ratio corresponding to the signal segment. The second linear relationship refers to the relationship between the signal-to-interference-and-noise ratio corresponding to the signal segment and the first noise reduction parameter corresponding to the signal segment. The first noise reduction parameter corresponding to the signal segment may be the optimal noise reduction parameter corresponding to the signal segment.

[0080] For ease of description, in the subsequent embodiments, the SINR of the signal segment before noise reduction is expressed as The SINR after noise reduction of the signal segment is denoted as SINR.

[0081] (1) The transmitter sends a signal containing a known sequence, which is then supplemented with impulse noise after passing through the channel.

[0082] (2) The receiving end receives the signal, such as Figure 1 As shown in FIG, it is a schematic diagram of receiving signals, such as Figure 1 As shown in FIG, when a pulse arrives, the signal will be disturbed for a short duration, while when there is no additional pulse noise, the signal is relatively stable, that is, when there is no pulse noise, noise reduction is not required.

[0083] The embodiment of the present application takes the orthogonal frequency division multiplexing (OFDM) technology, namely the OFDM time domain signal, as an example. The time domain characteristics of the OFDM time domain signal, according to the 3-σ principle, the probability that the amplitude s[n] is outside the amplitude ±3 is very low, so the first threshold can be set to 3.5 or 4. When the amplitude of the sampling point at a certain moment is greater than the first threshold, it is very likely that pulse interference has arrived. On the other hand, considering the small probability situation, the amplitude of the effective signal at certain moments may be greater than the first threshold. Therefore, the average power of several consecutive sampling points can be continuously obtained. If the average power is greater than the second threshold, it can be determined that pulse noise has arrived. The second threshold can be set to a value greater than 3^2.

[0084] Furthermore, according to the sample data of actual impulse noise interference, the duration of each impulse noise is relatively fixed. For example, assuming the empirical value is 0.4ms, the corresponding number of sampling points is N0 sampling points. Therefore, after determining that the impulse noise arrives, the signal segment 0.4ms after the sampling point can be denoised.

[0085] (3) For each extracted signal segment, since each signal segment contains a known sequence and known impulse noise, the signal-to-interference-noise ratio corresponding to each signal segment can be calculated.

[0086] (4) Calculate the feature quantity corresponding to each signal segment, and perform a multivariate regression of the feature quantity to the signal interference noise ratio corresponding to the signal segment, to obtain a first linear relationship between the feature quantity corresponding to the signal segment and the signal interference noise ratio corresponding to the signal segment.

[0087] Specifically, the OFDM time domain signal obeys the N(0,1) Gaussian distribution and is considered to be time-stationary. Therefore, for the signal segment, the change comes from the amplitude of the pulse interference. For example, the lower the signal to noise ratio, the stronger the pulse interference, and the greater the total power of the signal segment. This shows that there is a correlation between some characteristic quantities of the signal segment and the signal to noise ratio. This application uses the multivariate regression method to calculate the signal segment corresponding to the signal segment. (Signal to Interference plus Noise Ratio, SINR) is estimated.

[0088] Get a large number of signal segments containing impulse noise and calculate the corresponding For each signal segment, calculate some characteristic quantities of the signal segment, such as the average amplitude of the signal segment, the average power of the signal segment, the variance of the amplitude of the signal segment, and the maximum amplitude of the signal segment. Further complete the multivariate regression of the characteristic quantity corresponding to the signal segment to the signal interference and noise ratio corresponding to the signal segment, and obtain the relationship satisfied between the characteristic quantity corresponding to the signal segment and the SINR corresponding to the signal segment. Among them, x1, x2, ... are feature quantities.

[0089] For example, the average amplitude x1 of the signal segment is used as an example for regression, where x1 is expressed as follows:

[0090]

[0091] x1 is the average value of the amplitude of each sampling point in the received signal segment {x[0],x[1],…x[N0-1]}.

[0092] The average amplitude x1 corresponding to the signal segment to the signal-to-noise ratio corresponding to the signal segment The multiple regression fitting relationship is as follows:

[0093]

[0094] Therein, the characteristic quantity corresponding to the signal segment and the signal-to-interference-and-noise ratio corresponding to the signal segment satisfy a first linear relationship. It can be understood that when the superimposed impulse noise is different, the parameters in the fitting relationship may vary.

[0095] (5) A second linear relationship between the signal-to-interference-and-noise ratio (SINR) corresponding to the signal segment and the first noise reduction parameter is further obtained. The first noise reduction parameter is the optimal noise reduction parameter. In the embodiment of the present application, the SINR corresponding to the signal segment refers to the SINR of the signal segment before noise reduction processing.

[0096] Specifically, we further solve the best estimate in the probability sense for the noise reduction parameter T. Assume that the causal response of the impulse interference is a deterministic function h(nT s ), the amplitude coefficient is η, then the pulse interference of the signal segment is expressed as h(nT s )×η.

[0097] The received signal undergoes noise reduction processing, wherein the value of the noise reduction parameter T of the noise reduction processing is different, and accordingly, the total power of the effective signal after the noise reduction processing is different, that is, the noise reduction effect is different. In the embodiment of the present application, the noise reduction effect can be represented by the SINR after noise reduction. Among them, the noise reduction processing method can adopt the interpolation method of the present application for noise reduction, or it can adopt two-stage noise reduction (i.e., zeroing method noise reduction), etc. The following uses two-stage noise reduction as an example. The total power of the effective signal after the noise reduction processing changes with the noise reduction parameter T. The total power of the effective signal after the noise reduction processing is expressed as:

[0098]

[0099] Where s[n] is the sampling point of the time domain signal of Orthogonal Frequency Division Multiplexing (OFDM) technology and obeys the Gaussian distribution:

[0100]

[0101]

[0102] Q s[n] (-T,T) is defined as:

[0103]

[0104] The total power of the pulse interference is expressed as:

[0105]

[0106] Here, η is a zero-mean Gaussian distribution, and the variance is determined by the variance of the determination function h(nTs) and s[n].

[0107] The function {h[1],h[2],…,h[N]} represents the clustered pulse noise of unit power. η represents the power amplification factor of the pulse.

[0108] The SINR after noise reduction is expressed as:

[0109]

[0110] It is understandable that when different impulse noises are superimposed, the total power of the impulse interference is different. Accordingly, the signal fragments correspond to is also different, that is, the signal segment before the noise reduction process However, for a certain superimposed impulse noise, the SINR after noise reduction changes with the change of the noise reduction parameter T.

[0111] According to the theoretical derivation of the above model, we can get the In the case of (that is, when different impulse noises are superimposed), the simulation curve of SINR after noise reduction changes with parameter T is as follows: Figure 2 As shown, that is, before different noise reduction In the case of , the SINR after noise reduction changes with the parameter T.

[0112] As shown in the figure, the curves from bottom to top represent the Under the condition of 0dB to 14dB, the SINR of the signal segment after noise reduction changes with the parameter T, where * represents the change of the SINR of a signal segment before noise reduction. In this case, the optimal noise reduction parameter T * According to the simulation results, it is easy to conclude that before noise reduction When the noise level is low, the signal segment has a lot of pulse interference, so the optimal noise reduction parameter T is * Lower, by suppressing pulse interference to increase the SINR after noise reduction; before noise reduction When the value is higher, the pulse interference in the signal segment is small, and the optimal noise reduction parameter is T. * Gradually increase, by increasing the retention rate of OFDM signal to increase the SINR after noise reduction; when the Too high, for example, when the pulse noise has been submerged in the effective signal, it is actually impossible to detect it in the pulse detection stage, which is shown in the simulation results as T * If the value is very large, the pulse noise reduction process is stopped, that is, the noise reduction module should stop working.

[0113] according to Figure 2 The simulation graph shown above calculates the extreme point of the simulation curve, which is the corresponding value before noise reduction. The theoretical optimal noise reduction parameter T under * . Further, the regression method can be used to achieve the and T * For example, by Figure 2 The simulation curve shown is the one before noise reduction. and T * The fitted relationship of the correlation is as follows:

[0114]

[0115] In the embodiment of the present application, before noise reduction, When the value is relatively small, a relatively small setting value can be set as the optimal noise reduction parameter, as shown in the figure below, that is, before noise reduction When the optimal noise reduction parameter T is different * The value of:

[0116]

[0117] In this embodiment, when the signal segment before noise reduction is When it is lower than -10dB, it can be considered that the effective signal is completely submerged. The optimal noise reduction parameter is T * Set to a small value of 0.1; otherwise T satisfies the linear fitting relationship.

[0118] Please refer to Figure 3 , is a flow chart of a signal noise reduction processing method provided in an embodiment of the present application, such as Figure 3 As shown, the method may include: S100, S101 and S102, wherein the execution order of S100, S101 and S102 is not limited in the embodiment of the present application. As shown in the figure, the signal noise reduction processing method of the embodiment of the present application includes but is not limited to the following steps:

[0119] S100, obtaining a signal segment containing impulse noise, where the signal segment includes N0 sampling points, where N0 is an integer greater than or equal to 1;

[0120] In one embodiment, a power line communication device obtains a signal to be processed, where the signal to be processed may include n sampling points, where n is an integer greater than or equal to N0. The power line communication device includes, but is not limited to, a router, a home gateway, and the like. Optionally, there are multiple methods for obtaining a signal segment containing impulse noise from the signal to be processed. Two optional implementations are described below as examples:

[0121] A first optional method is to determine a rising edge sampling point from the n sampling points, wherein the amplitude of the rising edge sampling point exceeds a certain threshold, and the amplitudes of the sampling points adjacent to the rising edge sampling point before the rising edge sampling point are less than the threshold, and the amplitudes of the sampling points adjacent to the rising edge sampling point after the rising edge sampling point are greater than the threshold. Optionally, if the signal to be processed is an OFDM time-domain signal, the threshold can be set to 3.5 or 4. When the signal value at a certain moment is greater than the threshold, it is likely that pulse interference has arrived. On the other hand, considering the low probability that the signal amplitude at certain moments may be greater than the threshold, it is necessary to measure the average power of several consecutive sampling points. If the average power of several consecutive sampling points is greater than another threshold, it can be used as a basis for determining the arrival of a pulse.

[0122] Furthermore, according to the sample data of actual pulse interference, the duration of each pulse is relatively fixed (assuming the empirical value is 0.4ms, and the corresponding number of sampling points is N0), so the signal segment 0.4ms after the sampling point where the pulse arrives can be regarded as the signal segment containing pulse noise.

[0123] The second optional method is to obtain a signal to be processed, which includes n sampling points, where n is an integer greater than or equal to N0; for each of the n sampling points, obtain a preset number of consecutive sampling points starting from the sampling point; calculate the average power of the preset number of sampling points, and use the average power as the sliding window energy corresponding to the sampling point; optionally, a sliding window method can be used to observe the received signal. For example, the window length is set to 3, the window is slid over time, and after each sliding, the average power of the signal in the window is calculated as the sliding window energy of the starting sampling point in the window. Figure 4 The figure is a schematic diagram of the sliding window energy result obtained by sliding the window. The result obtained by the sliding window method is mixed with many high-frequency components, which is not conducive to determining the decision point. Therefore, the signal can be filtered through a low-pass filter to obtain the filtered result. Figure 5 As shown in FIG, this is a schematic diagram of the result after low-pass filtering.

[0124] Obtain the sliding window energy corresponding to each of the n sampling points, and use the sampling point whose sliding window energy is greater than the first threshold as the starting sampling point, and obtain N0 consecutive sampling points starting from the starting sampling point; determine the signal segment composed of the N0 sampling points as a signal segment containing impulse noise. Continuing with the above sliding window as an example, if the average power of the signal within the window is greater than the first threshold, it is determined to be the pulse arrival time. For example, the first threshold can be set to 2.5, and the signal segment consisting of the N0 sampling points is determined to be the pulse arrival time. Figure 5 The curve shown determines a rising edge of the curve, which means that the sliding window energy of the sampling point is greater than a first threshold, while the sliding window energy of the sampling point before the sampling point is less than the first threshold.

[0125] After the pulse arrival time of the signal in the window is determined, a signal segment is intercepted after the arrival time according to the average duration of the actual pulse noise, and is considered to be the signal segment containing the pulse noise.

[0126] S101, calculating a signal-to-interference-plus-noise ratio (SIR) corresponding to the signal segment, and determining a first noise reduction parameter corresponding to the signal segment based on the SIR;

[0127] In one embodiment, a feature value corresponding to the signal segment is obtained, where the feature value is used to represent a statistical feature of the signal segment. Exemplarily, the feature value may include, but is not limited to, one or more of the following information: an average amplitude of the signal segment, an average power of the signal segment, a variance of the amplitude of the signal segment, and a maximum amplitude of the signal segment.

[0128] The power line communication device further calculates the signal-to-interference-and-noise ratio corresponding to the signal segment based on the characteristic quantity corresponding to the signal segment. Specifically, the characteristic quantity corresponding to the signal segment and the signal-to-interference-and-noise ratio corresponding to the signal segment satisfy a first linear relationship. For example, in the aforementioned embodiment, the average amplitude x1 of the signal segment is obtained by a multiple regression method to obtain the signal-to-interference-and-noise ratio corresponding to the signal segment. The following fitting relationship is satisfied. It can be understood that this fitting relationship is only an example of the first linear relationship:

[0129]

[0130] The signal to interference noise ratio (SINR) corresponding to the signal segment can be calculated based on the characteristic quantity corresponding to the signal segment.

[0131] After obtaining the signal-to-interference-plus-noise ratio (SINR) corresponding to the signal segment, a first noise reduction parameter, i.e., an optimal noise reduction parameter, corresponding to the signal segment can be further determined based on the SINR. In embodiments of the present application, a second threshold can be set, where the value of the second threshold can depend on the tolerance for impulse noise. For example, if the tolerance for impulse noise is relatively low, the second threshold can be set to 0 dB, or alternatively, to -10 dB. If the SINR is less than the second threshold, it indicates that the valid signal is being overwhelmed, and the optimal noise reduction parameter can be set to a relatively small value. If the SINR is greater than or equal to the second threshold, the optimal noise reduction parameter and the SINR corresponding to the signal segment satisfy a second linear relationship.

[0132] For example, in the above embodiment, the optimal noise reduction parameter T * The values ​​of are:

[0133]

[0134] In the embodiment of the present application, the range of the signal-to-noise ratio corresponding to the signal segment is determined, thereby determining the first noise reduction parameter corresponding to the signal segment, that is, the optimal noise reduction parameter. For example, if the signal-to-noise ratio corresponding to the signal segment is less than -10dB, 0.1 can be set as the first noise reduction parameter corresponding to the signal segment. If the signal-to-noise ratio corresponding to the signal segment is a value greater than or equal to -10dB, A first noise reduction parameter corresponding to the signal segment is calculated.

[0135] S102: Determine at least one sampling point from the N0 sampling points whose amplitude is greater than the first noise reduction parameter, and perform noise reduction processing on the amplitude of the at least one sampling point.

[0136] In one embodiment, the power line communication device determines at least one sampling point whose amplitude is greater than the first noise reduction parameter from the N0 sampling points, and for each sampling point in the at least one sampling point, obtains a first sampling point and a second sampling point associated with the sampling point from the N0 sampling points. The first sampling point is the sampling point that is before the sampling point and closest to the sampling point and has an amplitude less than the first noise reduction parameter, and the second sampling point is the sampling point that is after the sampling point and closest to the sampling point and has an amplitude less than the first noise reduction parameter. Figure 6 As shown, the amplitude of sampling point n-1 is greater than the first noise reduction parameter, and the first sampling point n-2 associated with sampling point n-1 and the second sampling point n associated with sampling point n-1 are obtained. It can be understood that if the amplitude of sampling point n-2 is also greater than or equal to the first noise reduction parameter, it can be determined whether the amplitude of sampling point n-3 is less than the first noise reduction parameter. If the amplitude of sampling point n-3 is less than the first noise reduction parameter, sampling point n-3 is determined as the first sampling point associated with sampling point n-1. If the amplitude of sampling point n-3 is also greater than or equal to the first noise reduction parameter, it can be determined whether the amplitude of sampling point n-4 is less than the first noise reduction parameter. This process is repeated until a sampling point before sampling point n-1 and with an amplitude less than the first noise reduction parameter is obtained as the first sampling point. Similarly, if the amplitude of sampling point n is also greater than or equal to the first noise reduction parameter, it can be determined whether the amplitude of sampling point n+1 is less than the first noise reduction parameter, and so on, until a sampling point after sampling point n-1 and with an amplitude less than the first noise reduction parameter is obtained as the second sampling point.

[0137] The first amplitude is obtained according to the amplitude of the first sampling point and the amplitude of the second sampling point. Optionally, an interpolation method can be used to calculate the first amplitude according to the amplitude of the first sampling point and the amplitude of the second sampling point, and the amplitude of the sampling point is updated to the first amplitude. In the embodiment of the present application, the interpolation method may include but is not limited to linear interpolation or high-order interpolation. Figure 6 As shown, the updated amplitude of the sampling point n-1 is obtained by linear interpolation.

[0138] In the embodiment of the present application, an interpolation method is used to update the amplitude of the sampling points exceeding the first noise reduction parameter instead of crudely setting it to zero, thereby retaining more effective signals and improving the noise reduction performance.

[0139] Please refer to Figure 7 , is a flow chart of another signal noise reduction processing method provided in an embodiment of the present application. As shown in the figure, the signal noise reduction processing method includes but is not limited to the following steps:

[0140] S200, obtaining a signal segment containing impulse noise, where the signal segment includes N0 sampling points, where N0 is an integer greater than or equal to 1;

[0141] S201, calculating a signal-to-interference-plus-noise ratio (SINR) corresponding to the signal segment, and determining a first noise reduction parameter corresponding to the signal segment based on the SINR.

[0142] S202: Determine at least one sampling point from the N0 sampling points whose amplitude is greater than the first noise reduction parameter, and perform noise reduction processing on the amplitude of the at least one sampling point.

[0143] For steps S200 to S202 of this embodiment, please refer to Figure 3 Steps S100 to S102 of the illustrated embodiment will not be described in detail here.

[0144] S203, obtaining the signal segment after the noise reduction processing;

[0145] S204: If the signal frame included in the signal segment is a first frame structure, synchronize the signal segment after the noise reduction processing using a time-frequency joint synchronization algorithm, wherein the synchronization header of the first frame structure includes a preset number of preset sequences;

[0146] S205: If the signal frame included in the signal segment is not the first frame structure, use a time domain autocorrelation algorithm to perform synchronization processing on the signal segment after the noise reduction processing.

[0147] In one embodiment, different synchronization algorithms may be used to synchronize the noise-reduced signal segments based on the different frame structures of the signal frames included in the noise-reduced signal segments. If the signal frames included in the signal segments have a standard frame structure, that is, the signal frames included in the signal segments have a first frame structure, a time-frequency joint synchronization algorithm may be used to synchronize the noise-reduced signal segments. Optionally, the first frame structure may include 7 known sequences S1 in the synchronization header, with one S1 symbol being 256 sampling points long. The first frame structure may be an International Telecommunication Union (ITU) frame structure.

[0148] The following is an introduction to the time-frequency joint synchronization algorithm: First, the transmitter generates a lookup table in the frequency domain, selects a sliding window length of 1024, which is exactly the length of 4 S1s, and slides point by point from the head of the first S1, and retains the index and data corresponding to each slide as the lookup table, such as Figure 8 As shown in FIG. , this is a schematic diagram of a lookup table.

[0149] First, perform rough timing at the receiving end, and calculate the correlation value of two adjacent S1 length data blocks by sliding to obtain the correlation curve, such as Figure 9The figure below is a schematic diagram of the correlation curve. The sudden rise in the curve can be considered the arrival of the first S1. A threshold is set, for example, to 0.8 for the autocorrelation result, to capture the decision point of the rising edge. Assume its discrete moment is n0. Because the decision occurs on the rising edge of the correlation curve, n0 is considered to be within the first short sequence.

[0150] Then perform fine synchronization in the frequency domain. Figure 10 As shown in the figure, 1024 sampling points are selected consecutively starting at n0, transformed into the frequency domain through FFT, and scaled to match the total energy in the lookup table. The geometric distances between each item are compared, and the closest item is selected. The index corresponding to this item in the lookup table is the time offset represented by n0. Using this time offset to correct n0, correct frame synchronization is achieved.

[0151] If the signal frame included in the signal segment is not the first frame structure, that is, it is a non-standard frame, a time domain autocorrelation algorithm may be used to perform synchronization processing on the signal segment after the noise reduction processing.

[0152] After the noise reduction method of the embodiment of the present application is used to reduce the impulse noise contained in the signal segment, and then synchronization processing is performed, the synchronization error can be reduced, such as Figure 11 As shown, the synchronization timing error after noise reduction using the method proposed in this application and the synchronization timing error without noise reduction. It can be seen that the synchronization timing error after noise reduction using the method proposed in this application is much smaller than the synchronization timing error without noise reduction.

[0153] like Figure 12 The figure is a flow chart of the signal noise reduction processing method provided by the present application. As shown in the figure, the method includes but is not limited to the following steps:

[0154] S300: Calculate local area energy using the sliding window method and determine if a pulse is detected based on whether it exceeds a set threshold. If a pulse is detected, a rectangular window is added to extract the signal fragment and execute step S301. If no pulse is detected, no noise reduction is performed and synchronization is performed using a time-frequency synchronization algorithm based on the standard ITU structure.

[0155] S301, using the fitting curve obtained by multivariate regression, completing the fitting from the characteristic quantity of the signal segment to the noise reduction parameter, thereby obtaining the optimal noise reduction parameter;

[0156] S302: For sampling points whose amplitude exceeds the optimal noise reduction parameter, a linear interpolation method is used to restore the signal segments, i.e., noise reduction processing is performed. If it is a standard ITU structure, a time-frequency joint synchronization algorithm is used for synchronization processing.

[0157] It is understandable that Figure 12The specific description can refer to the description of the above embodiment and will not be repeated here.

[0158] Above, combined Figures 1 to 12 The method provided in the embodiment of the present application is described in detail. Figures 13 to 15 The device provided in the embodiments of the present application is described in detail.

[0159] It is understood that in order to implement the functions in the above embodiments, the power line communication device includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should readily appreciate that, in combination with the units and method steps of the various examples described in the embodiments disclosed in this application, this application can be implemented in the form of hardware, software, or a combination of hardware and software. Whether a function is executed in hardware, software, or by computer software driving hardware depends on the specific application scenario and design constraints of the technical solution.

[0160] Figure 13 : is a schematic block diagram of a communication device provided in an embodiment of the present application. Figure 13 As shown, the communication device may include an acquisition module 10, a calculation module 11, and a noise reduction module 12. Optionally, the communication device may also include a synchronization module 13. The acquisition module 10, the calculation module 11, the noise reduction module 12, and the synchronization module 13 may be software, hardware, or a combination of software and hardware. Each module is described below:

[0161] An acquisition module 10 is configured to acquire a signal segment containing impulse noise, wherein the signal segment includes N0 sampling points, where N0 is an integer greater than or equal to 1;

[0162] a calculation module 11, configured to calculate a signal-to-interference-plus-noise ratio (SINR) corresponding to the signal segment, and determine a first noise reduction parameter corresponding to the signal segment based on the SINR;

[0163] The noise reduction module 12 is configured to determine at least one sampling point whose amplitude is greater than the first noise reduction parameter from the N0 sampling points, and perform noise reduction processing on the amplitude of the at least one sampling point.

[0164] In a possible implementation, the noise reduction module 12 is specifically configured to:

[0165] For each sampling point of the at least one sampling point, obtaining a first sampling point and a second sampling point associated with the sampling point from the N0 sampling points, wherein the first sampling point is a sampling point that is before the sampling point and closest to the sampling point and has a value less than the first noise reduction parameter, and the second sampling point is a sampling point that is after the sampling point and closest to the sampling point and has a value less than the first noise reduction parameter;

[0166] Obtaining a first amplitude according to the amplitude of the first sampling point and the amplitude of the second sampling point;

[0167] The amplitude of the sampling point is updated to the first amplitude.

[0168] In a possible implementation, the acquisition module 10 is specifically configured to:

[0169] Acquire a signal to be processed, where the signal to be processed includes n sampling points, where n is an integer greater than or equal to N0;

[0170] For each of the n sampling points, obtaining a preset number of consecutive sampling points starting from the sampling point;

[0171] Calculating the average power of the preset number of sampling points, and using the average power as the sliding window energy corresponding to the sampling points;

[0172] Obtaining a sliding window energy corresponding to each of the n sampling points, taking a sampling point whose sliding window energy is greater than a first threshold as a starting sampling point, and obtaining N0 consecutive sampling points starting from the starting sampling point;

[0173] The signal segment consisting of the N0 sampling points is determined to be a signal segment containing impulse noise.

[0174] In a possible implementation, the calculation module 11 is specifically configured to:

[0175] Acquiring a feature value corresponding to the signal segment, where the feature value is used to represent a statistical feature of the signal segment;

[0176] Calculate the signal to interference noise ratio of the signal segment according to the feature quantity corresponding to the signal segment.

[0177] In a possible implementation, the calculation module 11 is specifically configured to:

[0178] Acquire a first linear relationship satisfied between a feature quantity corresponding to the signal segment and the signal to interference and noise ratio;

[0179] The signal to interference plus noise ratio (SINR) of the signal segment is calculated according to the feature quantity corresponding to the signal segment and the first linear relationship.

[0180] In a possible implementation, the characteristic quantity includes one or more of the following information: an average amplitude of the signal segment, an average power of the signal segment, a variance of the amplitude of the signal segment, and a maximum amplitude of the signal segment.

[0181] In a possible implementation, the calculation module 11 is specifically configured to:

[0182] If the signal to interference plus noise ratio is less than a second threshold, determining a first set value as a first noise reduction parameter corresponding to the signal segment;

[0183] If the signal to interference plus noise ratio is greater than or equal to the second threshold, a second linear relationship satisfied by the signal to interference plus noise ratio and the first noise reduction parameter is obtained, and a first noise reduction parameter corresponding to the signal segment is calculated based on the signal to interference plus noise ratio and the second linear relationship.

[0184] In a possible implementation, the apparatus further includes:

[0185] A synchronization module 13 is configured to obtain the signal segment after the noise reduction processing; if the signal frame included in the signal segment is a standard ITU frame structure, a time-frequency joint synchronization algorithm is used to synchronize the signal segment after the noise reduction processing, wherein the synchronization header of the standard ITU frame structure includes a preset number of preset sequences; if the signal frame included in the signal segment is not a standard ITU frame structure, a time domain autocorrelation algorithm is used to synchronize the signal segment after the noise reduction processing.

[0186] Please refer to Figure 14 , is a schematic structural diagram of a communication device according to an embodiment of the present application. It should be understood that Figure 14 The communication device shown is only an example. The communication device of the embodiment of the present application may also include other components, or include Figure 14 components similar in function to the components in Figure 14 All parts in.

[0187] The communication device includes a communication interface 21 and at least one processor 22 .

[0188] The communication device may correspond to a power line communication device. A communication interface 21 is used to transmit and receive signals, and at least one processor 22 executes program instructions, enabling the communication device to implement the corresponding process of the method performed by the power line communication device in the above-mentioned method embodiment. For details, please refer to the description of the above-mentioned method embodiment and will not be repeated here.

[0189] For the case where the communication device may be a chip or a chip system, see Figure 15 Schematic diagram of the chip structure shown. Figure 15 The chip 30 shown includes a processor 31 and an interface 32. The number of processors 31 can be one or more, and the number of interfaces 32 can be multiple. It should be noted that the functions corresponding to the processor 31 and the interface 32 can be implemented through hardware design, software design, or a combination of hardware and software, without limitation.

[0190] Optionally, the chip may further include a memory 33, which is used to store necessary program instructions and data.

[0191] In the present application, processor 31 may be configured to retrieve from memory a program implementing the signal noise reduction processing method provided in one or more embodiments of the present application in a power line communication device and execute the instructions contained in the program. Interface 32 may be configured to output the execution results of processor 31. In the present application, interface 32 may be specifically configured to output various messages or information from processor 31. For details regarding the signal noise reduction processing method provided in one or more embodiments of the present application, reference may be made to the aforementioned method embodiments and will not be further elaborated here.

[0192] The processor in the embodiments of the present application may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc.

[0193] According to the method provided in the embodiment of the present application, the present application also provides a computer program product, which includes: computer program code, which, when running on a computer, enables the computer to execute the method in the aforementioned method embodiment.

[0194] An embodiment of the present application further provides a processing device, including a processor and an interface; the processor is used to execute the method in any of the above method embodiments.

[0195] It should be understood that the above-mentioned processing device can be a chip. For example, the processing device can be a field programmable gate array (FPGA), a general-purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, a system on chip (SoC), a central processing unit (CPU), a network processor (NP), a digital signal processing circuit (DSP), a microcontroller unit (MCU), a programmable logic device (PLD) or other integrated chip. The methods, steps and logic block diagrams disclosed in the embodiments of the present application can be implemented or executed. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in conjunction with the embodiments of the present application can be directly embodied as being executed by a hardware decoding processor, or can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium well-known in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in the memory, and the processor reads the information in the memory and, in conjunction with its hardware, completes the steps of the above method.

[0196] It is understood that the memory in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), and direct RAM bus RAM (DR RAM). It should be noted that the memory of the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0197] In the above embodiments, all or part of the embodiments may be implemented by software, hardware, firmware, or any combination thereof. When implemented using software, all or part of the embodiments may be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present application are generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) method. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated therein. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a high-density digital video disc (DVD)), or a semiconductor medium (eg, a solid state disc (SSD)).

[0198] As used in this specification, the terms "component," "module," "system," and the like are used to refer to computer-related entities, hardware, firmware, a combination of hardware and software, software, or software in execution. For example, a component can be, but is not limited to, a process running on a processor, a processor, an object, an executable file, an execution thread, a program, or a computer. By way of illustration, both applications running on a computing device and a computing device can be components. One or more components can reside in a process or execution thread, and a component can be located on a single computer or distributed between two or more computers. In addition, these components can be executed from various computer-readable media having various data structures stored thereon. Components can communicate, for example, through local or remote processes based on signals having one or more data packets (e.g., data from two components interacting with another component on a local system, a distributed system, or a network, such as the Internet interacting with other systems via signals).

[0199] It should be understood that references to "embodiments" throughout this specification mean that a particular feature, structure, or characteristic associated with the embodiment is included in at least one embodiment of the present application. Therefore, various embodiments throughout this specification do not necessarily refer to the same embodiment. Furthermore, these particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0200] It should be understood that in the embodiments of the present application, the numbers "first", "second"... are only for distinguishing different objects, such as to distinguish different network devices, and do not constitute a limitation on the scope of the embodiments of the present application. The embodiments of the present application are not limited to this.

[0201] It should also be understood that in this application, "when", "if" and "if" all mean that the network element will make corresponding processing under certain objective circumstances, which is not a time limit, and does not require the network element to make judgment actions when implementing it, nor does it mean that there are other limitations.

[0202] It should also be understood that in each embodiment of the present application, "A corresponds to B" means that B is associated with A, and B can be determined based on A. However, it should also be understood that determining B based on A does not mean determining B based solely on A, and B can also be determined based on A and / or other information.

[0203] It should also be understood that the term "and / or" as used herein simply describes a relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. Furthermore, the character " / " as used herein generally indicates that the associated objects are in an "or" relationship.

[0204] In this application, expressions similar to “the item includes one or more of the following: A, B, and C” generally mean, unless otherwise specified, that the item can be any one of the following: A; B; C; A and B; A and C; B and C; A, B and C; A and A; A, A and A; A, A and B; A, A and C, A, B and B; A, C and C; B and B, B, B and B, B, B and C, C and C; C, C and C, and other combinations of A, B and C. The above examples use A, B, and C as an example to illustrate the optional items of the item. When the expression is “the item includes at least one of the following: A, B, …, and X”, that is, when the expression contains more elements, the items applicable to the item can also be obtained according to the above rules.

[0205] It is understood that the power line communication device in the embodiments of the present application can perform some or all of the steps in the embodiments of the present application. These steps or operations are merely examples, and the embodiments of the present application can also perform other operations or variations of various operations. In addition, the various steps can be performed in a different order than those presented in the embodiments of the present application, and it is possible that not all operations in the embodiments of the present application need to be performed.

[0206] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0207] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0208] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0209] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0210] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0211] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory ROM, a random access memory RAM, a magnetic disk, or an optical disk.

[0212] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A signal processing method, characterized in that: The method comprises: Acquire a signal segment containing impulse noise, where the signal segment includes N0 sampling points, where N0 is an integer greater than or equal to 1; calculating a signal-to-interference-plus-noise ratio (SIR) corresponding to the signal segment, and determining a first noise reduction parameter corresponding to the signal segment based on the SIR; Determining at least one sampling point having an amplitude greater than the first noise reduction parameter from the N0 sampling points, and performing noise reduction processing on the amplitude of the at least one sampling point; The determining, according to the signal to interference plus noise ratio, a first noise reduction parameter corresponding to the signal segment includes: If the signal to interference plus noise ratio is less than a second threshold, determining a first set value as a first noise reduction parameter corresponding to the signal segment; If the signal to interference plus noise ratio is greater than or equal to the second threshold, a second linear relationship satisfied by the signal to interference plus noise ratio and the first noise reduction parameter is obtained, and a first noise reduction parameter corresponding to the signal segment is calculated based on the signal to interference plus noise ratio and the second linear relationship.

2. The method according to claim 1, wherein The performing noise reduction processing on the amplitude of the at least one sampling point includes: For each sampling point of the at least one sampling point, obtaining a first sampling point and a second sampling point associated with the sampling point from the N0 sampling points, wherein the first sampling point is a sampling point that is before the sampling point and closest to the sampling point and has a value less than the first noise reduction parameter, and the second sampling point is a sampling point that is after the sampling point and closest to the sampling point and has a value less than the first noise reduction parameter; Obtaining a first amplitude according to the amplitude of the first sampling point and the amplitude of the second sampling point; The amplitude of the sampling point is updated to the first amplitude.

3. The method according to claim 1 or 2, wherein: The obtaining of the signal segment containing the impulse noise comprises: Acquire a signal to be processed, where the signal to be processed includes n sampling points, where n is an integer greater than or equal to N0; For each of the n sampling points, obtaining a preset number of consecutive sampling points starting from the sampling point; Calculating the average power of the preset number of sampling points, and using the average power as the sliding window energy corresponding to the sampling points; Obtaining a sliding window energy corresponding to each of the n sampling points, taking a sampling point whose sliding window energy is greater than a first threshold as a starting sampling point, and obtaining N0 consecutive sampling points starting from the starting sampling point; The signal segment consisting of the N0 sampling points is determined to be a signal segment containing impulse noise.

4. The method according to claim 1, wherein The calculating the signal to interference plus noise ratio corresponding to the signal segment includes: Acquiring a feature value corresponding to the signal segment, where the feature value is used to represent a statistical feature of the signal segment; Calculate the signal to interference noise ratio (SINR) corresponding to the signal segment according to the feature quantity corresponding to the signal segment.

5. The method according to claim 4, wherein The calculating the signal to interference noise ratio of the signal segment according to the feature quantity corresponding to the signal segment includes: Acquire a first linear relationship satisfied between a feature quantity corresponding to the signal segment and the signal to interference and noise ratio; The signal to interference plus noise ratio (SINR) of the signal segment is calculated according to the feature quantity corresponding to the signal segment and the first linear relationship.

6. The method according to claim 4 or 5, characterized in that The feature quantity includes one or more of the following information: an average amplitude of the signal segment, an average power of the signal segment, a variance of the amplitude of the signal segment, and a maximum amplitude of the signal segment.

7. The method according to any one of claims 1, 2, 4 and 5, wherein: The method further comprises: Obtaining the signal segment after the noise reduction processing; If the signal frame included in the signal segment is a first frame structure, performing synchronization processing on the signal segment after noise reduction processing by using a time-frequency joint synchronization algorithm, wherein the first frame structure includes a preset number of preset sequences; If the signal frame included in the signal segment is not the first frame structure, a time domain autocorrelation algorithm is used to perform synchronization processing on the signal segment after the noise reduction processing.

8. A communication device, characterized in that: include: A processor, wherein when the processor calls a computer program or instruction in a memory, the method according to any one of claims 1 to 7 is executed.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium includes a computer program or instructions. When the computer program or instructions are executed on a computer, the computer is caused to perform the method according to any one of claims 1 to 7.

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