阅读说明：本技术 5g通信信号干扰的处理方法、装置、电子设备及存储介质 (Method and device for processing 5G communication signal interference, electronic equipment and storage medium ) 是由 张立亚 姜玉峰 孟庆勇 连龙飞 郝博南 吴文臻 戴万波 王勇 于 2021-11-11 设计创作，主要内容包括：本公开提供了一种5G通信信号干扰的处理方法、装置、电子设备及存储介质,涉及信号处理领域。该方案为：接收多通道传输的混合井下信号集；基于盲源分离的当前分离矩阵,对多通道传输的混合井下信号集的干扰进行过滤,以获取目标井下信号集；响应于到达干扰监控周期,则对目标井下信号集进行干扰监控,获取信噪比；响应于信噪比小于预设阈值,则执行盲源分离对当前分离矩阵进行更新,并返回执行接收多通道传输的混合井下信号集及后续操作。本公开中通过分离矩阵自适应地过滤掉井下信号中的干扰成分,提高了信号抗干扰处理的效率,同时可以基于盲源分离对分离矩阵进行更新,使获取的信号的信噪比始终小于一个特定值。(The disclosure provides a method and a device for processing 5G communication signal interference, electronic equipment and a storage medium, and relates to the field of signal processing. The scheme is as follows: receiving a multi-channel transmitted mixed downhole signal set; based on a current separation matrix of blind source separation, filtering interference of a multi-channel transmission mixed underground signal set to obtain a target underground signal set; in response to the arrival of the interference monitoring period, performing interference monitoring on the target underground signal set to obtain a signal-to-noise ratio; and in response to the signal-to-noise ratio being smaller than a preset threshold value, performing blind source separation to update the current separation matrix, and returning to perform the receiving of the multi-channel transmitted mixed downhole signal set and subsequent operations. According to the method and the device, the interference components in the underground signals are filtered out in a self-adaptive mode through the separation matrix, the efficiency of signal anti-interference processing is improved, meanwhile, the separation matrix can be updated based on blind source separation, and the signal-to-noise ratio of the obtained signals is always smaller than a specific value.)

1. A method for processing interference of a 5G communication signal is characterized by comprising the following steps:

receiving a multi-channel transmitted mixed downhole signal set;

filtering interference of the multi-channel transmitted mixed underground signal set based on a current separation matrix of blind source separation to obtain a target underground signal set;

in response to the arrival of an interference monitoring period, performing interference monitoring on the target underground signal set to obtain a signal-to-noise ratio;

and in response to the signal-to-noise ratio being smaller than a preset threshold value, performing blind source separation to update the current separation matrix, and returning to perform the receiving of the multi-channel transmitted mixed downhole signal set and subsequent operations.

2. The method of claim 1, wherein the filtering the interference of the multi-channel transmitted mixed downhole signal set based on the current separation matrix of blind source separation to obtain a target downhole signal set comprises:

and multiplying the multi-channel transmitted mixed downhole signal set with the current separation matrix to obtain the target downhole signal set.

3. The method of claim 1, wherein the monitoring the interference of the target downhole signal set to obtain a signal-to-noise ratio comprises:

inputting the target underground signal set into a deep complex network, acquiring a feature map of the target underground signal set by the deep complex network, and performing classification and identification according to the feature map to acquire the category of the signal in the target underground signal set;

and acquiring the signal-to-noise ratio according to the category of the target downhole signal set signal.

4. The method according to claim 3, wherein the obtaining the feature map of the target downhole signal by the deep complex network and performing classification recognition according to the feature map to obtain the category of the signal in the target downhole signal comprises:

performing feature map extraction on the target downhole signal set by a feature extraction layer of the deep complex network to obtain a real part and an imaginary part of the feature map;

carrying out nonlinear mapping on the real part and the imaginary part of the feature map by a complex excitation layer of the deep complex network to obtain the real part and the imaginary part of the mapped feature map;

pooling the real part and the imaginary part of the mapped feature map by a plurality of pooling layers of the deep complex network to obtain a pooled feature map;

and carrying out full connection operation on the pooled characteristic graphs by a full connection layer of the deep complex network so as to output the category of the target downhole signal concentrated signal.

5. The method of any one of claims 1-4, wherein after acquiring the set of target downhole signals, further comprising:

performing channel estimation on the target downhole signal set;

performing channel compensation on the target downhole signal set subjected to channel estimation;

performing channel equalization processing on the target underground signal set subjected to channel compensation to generate an equalized underground signal set;

and performing signal judgment on the equalized downhole signal set.

6. The method according to any of claims 1-4, wherein the interference monitoring period is greater than the sum of the processing duration of the interference monitoring and the processing duration of the blind source separation.

7. An apparatus for processing interference of a 5G communication signal, comprising:

the receiving module is used for receiving a multi-channel transmitted mixed downhole signal set;

the interference filtering module is used for filtering the interference of the multi-channel transmission mixed underground signal set based on the current separation matrix of blind source separation to obtain a target underground signal set;

the interference monitoring module is used for carrying out interference monitoring on the target underground signal set when an interference monitoring period is reached, and acquiring a signal-to-noise ratio;

and the matrix updating module is used for executing blind source separation to update the current separation matrix when the signal-to-noise ratio is smaller than a preset threshold value.

8. The apparatus of claim 7, wherein the interference filtering module is further configured to:

and multiplying the multi-channel transmitted mixed downhole signal set with the current separation matrix to obtain the target downhole signal set.

9. The apparatus of claim 7, wherein the interference monitoring module is further configured to:

inputting the target underground signal set into a deep complex network, acquiring a feature map of the target underground signal set by the deep complex network, and performing classification and identification according to the feature map to acquire the category of the signal in the target underground signal set;

and acquiring the signal-to-noise ratio according to the category of the target downhole signal set signal.

10. A downhole communication device comprising processing of signal interference according to any of claims 7-9.

Technical Field

The present disclosure relates to the field of signal processing, and in particular, to a method and an apparatus for processing 5G communication signal interference, an electronic device, and a storage medium.

Background

The underground coal mine roadway is complex, the space is narrow, large electromechanical equipment is numerous, and the superposition of multi-factor interference on signals is easy to generate. The actual interference situation considered in the related technology is less, the actual interference situation of a coal mine cannot be processed perfectly and comprehensively, meanwhile, different methods are used for processing different interference sources, and the direct superposition and integration of multiple methods can cause overlarge calculation amount, cause overhigh time delay and influence the speed and efficiency of signal anti-interference processing.

Disclosure of Invention

The disclosure provides a method and a device for processing 5G communication signal interference, electronic equipment and a storage medium.

According to an aspect of the present disclosure, a method for processing 5G communication signal interference is provided, including:

receiving a multi-channel transmitted mixed downhole signal set;

based on a current separation matrix of blind source separation, filtering interference of a multi-channel transmission mixed underground signal set to obtain a target underground signal set;

in response to the arrival of the interference monitoring period, performing interference monitoring on the target underground signal set to obtain a signal-to-noise ratio;

and in response to the signal-to-noise ratio being smaller than a preset threshold value, performing blind source separation to update the current separation matrix, and returning to perform the receiving of the multi-channel transmitted mixed downhole signal set and subsequent operations.

In the embodiment of the disclosure, the separation matrix adaptively filters out interference components in the downhole signal, so that the efficiency of signal anti-interference processing is improved, and meanwhile, the separation matrix can be updated based on blind source separation, so that the signal-to-noise ratio of the signal obtained through the separation matrix is always smaller than a specific value.

According to another aspect of the present disclosure, there is provided a processing apparatus for 5G communication signal interference, including:

the receiving module is used for receiving a multi-channel transmitted mixed downhole signal set;

the interference filtering module is used for filtering the interference of the multi-channel transmission mixed underground signal set based on the current separation matrix of blind source separation so as to obtain a target underground signal set;

the interference monitoring module is used for carrying out interference monitoring on the target underground signal set when an interference monitoring period is reached, and acquiring a signal-to-noise ratio;

and the matrix updating module is used for executing blind source separation to update the current separation matrix when the signal-to-noise ratio is smaller than a preset threshold value.

According to another aspect of the present disclosure, there is provided an electronic device comprising a memory, a processor;

the processor reads the executable program codes stored in the memory to run programs corresponding to the executable program codes, so as to implement the method for processing the 5G communication signal interference in the embodiment of the first aspect of the present disclosure.

According to another aspect of the present disclosure, there is provided a computer-readable storage medium, on which a computer program is stored, which when executed by a processor, implements the method for processing 5G communication signal interference according to the embodiment of the first aspect of the present disclosure.

According to another aspect of the present disclosure, there is provided a computer program product comprising a computer program, which when executed by a processor, implements the method for processing 5G communication signal interference of the first aspect of the present disclosure.

It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.

Drawings

Fig. 1 is a flow chart of a method of processing 5G communication signal interference according to one embodiment of the present disclosure;

FIG. 2 is a schematic diagram of blind source separation;

FIG. 3 is an algorithm flow for blind source separation based on independent component analysis;

fig. 4 is a flow chart of a method of processing 5G communication signal interference according to one embodiment of the present disclosure;

fig. 5 is a flow chart of a method of processing 5G communication signal interference according to one embodiment of the present disclosure;

fig. 6 is a flow chart of a method of processing 5G communication signal interference according to one embodiment of the present disclosure;

fig. 7 is a block diagram of a 5G communication signal interference processing apparatus according to one embodiment of the present disclosure;

fig. 8 is a block diagram of an electronic device for implementing a method for processing 5G communication signal interference according to an embodiment of the present disclosure.

Detailed Description

Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.

The method, the apparatus, the electronic device and the storage medium for processing the interference of the 5G communication signal according to the present disclosure are described below with reference to the accompanying drawings.

Fig. 1 is a flowchart of a method for processing interference of a 5G communication signal according to an embodiment of the present disclosure, as shown in fig. 1, the method includes the following steps:

and S101, receiving a multi-channel transmitted mixed downhole signal set.

Obtaining N hybrid downhole signals x from N channels_i(t), i =1,2,.. N, constituting a hybrid downholeSet of signals, represented by a vector as x = [ x ]₁(t),x₂(t),...,x_N(t)]^TBecause all signals are based on the same time axis t, the vector of the hybrid downhole signal set can be abbreviated as x = [ x ]₁,x₂,...,x_N]^T。

The hybrid downhole signal is transmitted by wireless communication, optionally using radio, or other electromagnetic wave wireless technologies, such as light, magnetic fields, electric fields, etc.

The hybrid downhole signal set includes downhole 5G communication signals.

S102, filtering the interference of the multi-channel transmission mixed underground signal set based on the current separation matrix of blind source separation to obtain a target underground signal set.

Blind source separation is a technique for recovering or extracting individual source signals using a mixture of source signals without knowledge of either the distribution of the source signals or the source signal mixture model. Fig. 2 is a schematic diagram of blind source separation, as shown in fig. 2, M independent source signals are mixed into N mixed signals after passing through a mixing matrix a, where a is an N × M mixing matrix, when a source signal vector s = [ s ]₁,s₂,...,s_M]^TMixed signal vector x = [ x ]₁,x₂,...,x_N]^TWhen, x = As. In an embodiment of the present disclosure, the blended signal is a received set of blended downhole signals.

The objective of blind source separation is to recover a source signal vector s using a mixed signal vector x, i.e., s ≈ y = Wx, i.e., in the embodiment of the present disclosure, a target downhole signal set is obtained using a mixed downhole signal set, and the obtained target downhole signal set is regarded as a source signal set. Since both the source signal vector and the mixing matrix a are unknown, solving for the separation matrix W is referred to as blind source separation.

In the embodiment of the disclosure, a separation matrix is obtained based on blind source separation, a multi-channel transmission mixed downhole signal set is multiplied by the current separation matrix to obtain a target downhole signal set, and the interference suppression capability and the low delay characteristic are considered.

Optionally, the blind source separation may adopt an independent component analysis algorithm, and three conditions need to be satisfied to realize independent component analysis: the source signals are statistically independent of each other, the source signals satisfy a non-gaussian distribution, and the mixing matrix is column-full-rank. For the coal mine underground 5G communication signals and the interference signals, the first two conditions are naturally met, the third condition requires that the number of observation channels is not less than the number of source signals, namely N is more than or equal to M, a sampling diversity technology can be used, and an algorithm flow is shown in fig. 3.

In the first step, a whitening pre-process is performed on the received mixed signal to "de-correlate" the data to facilitate rapid convergence of the algorithm. Whitening means that the covariance matrix of the vector is an identity matrix, and is generally achieved by eigenvalue decomposition of the covariance matrix.

Second, select the initial separation point W₀Carry out initial output y₀=W₀x。

Thirdly, updating the separation matrix W by iterating the updating rule_n+1=W_n+μ(I+f(x)x^H)W_nWhere μ is a learning factor, I is a unit matrix, f (x) is an activation function, f (x) = - | x | y³sgn(x)。

The fourth step, determine if W is convergent, i.e., | (W)_n+1)^HW_nIf | is close to 1, if not converging, n = n +1, return to the third step, if converging, output the separation matrix W.

S103, in response to the arrival of the interference monitoring period, performing interference monitoring on the target underground signal set to obtain a signal-to-noise ratio.

And setting a fixed time length as an interference monitoring period of the signal, acquiring a target underground signal set output at the moment every other interference monitoring period, and carrying out interference monitoring on the target underground signal set to obtain a signal-to-noise ratio.

Signal-to-noise ratio refers to the ratio of signal to noise in an electronic device or system. In the disclosed embodiment, the signal refers to a target downhole signal set output, the noise refers to an irregular additional signal that does not exist in the mixed downhole signal set, and the noise does not change with the change of the mixed downhole signal set.

Generally, the larger the signal-to-noise ratio, the smaller the noise mixed in the signal, and the higher the signal quality; the smaller the signal-to-noise ratio, the more noise mixed in the signal and the lower the signal quality.

In the implementation of the embodiment of the present disclosure, the interference monitoring period needs to be greater than the sum of the processing duration of interference monitoring and the processing duration of blind source separation. When the monitored signal quality of the target underground signal set does not meet the requirement, blind source separation is needed to update the separation matrix, and the target underground signal set is continuously output after the update is completed. The number of interference monitoring periods is smaller than the sum of the processing time of interference monitoring and the processing time of blind source separation, and it may happen that the system is updating the separation matrix and cannot acquire the correct signal-to-noise ratio of the signal when interference monitoring is performed.

The interference monitoring period can be determined according to the time change rule of the signal-to-noise ratio, the signal-to-noise ratio of the target underground signal set within a period of time is monitored in real time, the signal-to-noise ratio of the target underground signal set is observed to be reduced from the highest value to the lowest acceptable value after a certain period of time, and the period of time is used as the interference monitoring period. Optionally, in order to ensure that the signal quality of the target downhole signal set is always kept in a good state, the duration of the interference monitoring period may be shortened, and the interference monitoring period is ensured to be greater than the sum of the processing duration of the interference monitoring and the processing duration of the blind source separation.

And S104, in response to the signal-to-noise ratio being smaller than the preset threshold value, performing blind source separation to update the current separation matrix, and returning to perform the mixed downhole signal set for receiving multi-channel transmission and subsequent operations.

And setting the signal-to-noise ratio of the signal corresponding to the lowest acceptable signal quality as a threshold value of the signal-to-noise ratio, and when the signal-to-noise ratio acquired by interference monitoring is smaller than a preset threshold value, proving that the signal quality of the target downhole signal set reaches the lowest acceptable signal quality.

And responding to the signal-to-noise ratio smaller than a preset threshold value, receiving a mixed underground signal set transmitted by multiple channels, executing blind source separation to obtain a new separation matrix, and updating the current separation matrix. After the updating is finished, multiplying the multi-channel transmission mixed underground signal set with the updated separation matrix, continuously obtaining a target underground signal set, and carrying out interference monitoring on the target underground signal set when an interference monitoring period is reached. And in response to the fact that the signal-to-noise ratio of the signal obtained by the interference monitoring at a certain time is smaller than a preset threshold value, performing blind source separation again to update the current separation matrix, and returning to the execution of the mixed underground signal set for receiving the multi-channel transmission and subsequent operations.

In the embodiment of the disclosure, a multi-channel transmitted mixed downhole signal set is received, interference of the multi-channel transmitted mixed downhole signal set is filtered based on a current separation matrix of blind source separation to obtain a target downhole signal set, interference monitoring is performed on the target downhole signal set in response to reaching an interference monitoring period to obtain a signal-to-noise ratio, blind source separation is executed to update the current separation matrix in response to the signal-to-noise ratio being smaller than a preset threshold, and reception of the multi-channel transmitted mixed downhole signal set and subsequent operations are returned to be executed. In the embodiment of the disclosure, the separation matrix adaptively filters out interference components in the downhole signal, so that the efficiency of signal anti-interference processing is improved, and meanwhile, the separation matrix can be updated based on blind source separation, so that the signal-to-noise ratio of the signal obtained through the separation matrix is always smaller than a specific value.

Fig. 4 is a flowchart of a method for processing 5G communication signal interference according to an embodiment of the present disclosure, and on the basis of the above embodiment, with further reference to fig. 4, a process of monitoring interference on a target downhole signal set and acquiring a signal-to-noise ratio is explained, including the following steps:

s401, inputting the target underground signal set into a deep complex network, obtaining a characteristic diagram of the target underground signal set by the deep complex network, and carrying out classification and identification according to the characteristic diagram to obtain the category of the signal in the target underground signal set.

A convolutional network is essentially an input-to-output mapping that is able to learn a large number of input-to-output mapping relationships without any precise mathematical expression between the inputs and outputs, and the network has the ability to map between input-output pairs as long as the convolutional network is trained with known patterns. Common convolutional networks include deep complex networks, convolutional neural networks, and the like.

The deep complex network is an extension of a convolutional neural network, has richer characterization capability and is more robust to noise. The input signal, weight and activation function of the complex neural network are complex, and a special network structure needs to be designed for complex numbers, including complex convolution, complex activation function and complex batch normalization.

And inputting the target downhole signal set into a deep complex network, and extracting a feature map of the target downhole signal set by a feature extraction layer of the deep complex network to obtain a real part and an imaginary part of the feature map. And carrying out nonlinear mapping on the real part and the imaginary part of the feature map by a complex excitation layer of the depth complex network to obtain the real part and the imaginary part of the mapped feature map. And performing pooling operation on the real part and the imaginary part of the mapped feature map by a complex pooling layer of the deep complex network to obtain a pooled feature map. And carrying out full connection operation on the pooled characteristic graphs by a full connection layer of the deep complex network so as to output the category of the target underground signal concentrated signal.

S402, acquiring a signal-to-noise ratio according to the category of the target downhole signal concentrated signal.

And different signal categories correspond to different signal characteristics, including signal to noise ratios of signals, and the corresponding signal to noise ratios are obtained according to the categories of the signals in the target underground signal set.

In the embodiment of the disclosure, a target downhole signal set is input into a deep complex network, the deep complex network acquires a feature map of the target downhole signal set, performs classification and identification according to the feature map, acquires the category of the target downhole signal set, and acquires the signal-to-noise ratio according to the category of the target downhole signal set. In the embodiment of the disclosure, the category of the target underground signal set is obtained based on the learning capability of the deep complex network, and the signal-to-noise ratio of the signal is further obtained, so that the signal-to-noise ratio of the signal does not need to be obtained through an accurate mathematical expression, errors are avoided, and the accuracy of the signal-to-noise ratio is improved.

Fig. 5 is a flowchart of a method for processing 5G communication signal interference according to an embodiment of the present disclosure, and on the basis of the above embodiment, further with reference to fig. 5, a process after a target downhole signal set is acquired is explained, including the following steps:

s501, channel estimation is carried out on the target underground signal set.

The performance of a wireless communication system is greatly affected by wireless channels, such as shadow fading, frequency selective fading, and the like, and the wireless channels are not fixed and predictable as wired channels, but have great randomness, so that the channels need to be estimated, thereby providing required channel information for subsequent signal processing.

Channel estimation, which is the process of estimating the model parameters of a certain assumed channel model from the received data, is a mathematical representation of the influence of the channel on the input signal. In the embodiment of the disclosure, the received data is a target downhole signal set, and channel estimation is performed on the target downhole signal set to obtain channel parameters.

And S502, performing channel compensation on the target underground signal set subjected to channel estimation.

And performing channel compensation on the target underground signal set based on the channel parameters obtained by channel estimation, namely reinforcing the signals by a technical means. Through channel compensation, the quality of information transmission can be enhanced, information packet loss is avoided, and normal information transmission is guaranteed.

And S503, performing channel equalization processing on the target downhole signal set subjected to channel compensation to generate an equalized downhole signal set.

Channel equalization refers to an anti-fading measure taken to improve the transmission performance of a communication system in a fading channel. The method is mainly used for eliminating or weakening the problem of intersymbol interference caused by multipath time delay in broadband communication.

And (3) carrying out channel equalization processing on the target downhole signal set subjected to channel compensation, optionally, compensating the characteristics of a channel or the whole transmission system, and generating an equalized downhole signal set.

And S504, performing signal judgment on the equalized downhole signal set.

Various interferences, such as noise and intersymbol interference, exist in the transmission process of the signal, and after the signal interference is processed, an error may still be generated, so that the obtained signal value is different from the actual value.

When the received signal is a square pulse wave, the signal is sampled to obtain discrete values at different time instants, for example, 0.9 is sampled at the first time instant, and the signal decision is performed to find that the value at this time instant is very close to 1, so that the value of the signal at this time instant is regarded as 1. Accordingly, signal decision is made for the signal values at other times, and it is determined whether the original value is 0 or 1 at the end.

In the embodiment of the disclosure, channel estimation is performed on a target downhole signal set, channel compensation is performed on the target downhole signal set subjected to channel estimation, channel equalization processing is performed on the target downhole signal set subjected to channel compensation, an equalized downhole signal set is generated, and signal judgment is performed on the equalized downhole signal set. According to the embodiment of the disclosure, the signal processing is performed on the target underground signal set, so that the anti-interference capability of the signal is further improved, and the signal quality of the signal is improved.

Fig. 6 is a flowchart of a method for processing 5G communication signal interference according to an embodiment of the present disclosure, and as shown in fig. 6, a process of processing signal interference in an actual application scenario includes the following steps based on the method for processing 5G communication signal interference provided by the present disclosure.

Step one, receiving a multi-channel transmitted mixed downhole signal set.

And step two, filtering the interference of the multi-channel transmission mixed underground signal set based on the current separation matrix of blind source separation to obtain a target underground signal set.

And step three, performing channel estimation on the target underground signal set.

And step four, performing channel compensation on the target underground signal set subjected to channel estimation.

And step five, performing channel equalization processing on the target underground signal set subjected to channel compensation to generate an equalized underground signal set.

And step six, performing signal judgment on the balanced underground signal set and outputting the signal.

And step seven, responding to the arrival interference monitoring period, performing interference monitoring on the target underground signal set, and acquiring the signal-to-noise ratio.

And step eight, in response to the signal-to-noise ratio being smaller than the preset threshold value, executing blind source separation to update the current separation matrix, and returning to execute the mixed underground signal set for receiving multi-channel transmission and subsequent operations.

For specific implementation of each step in this embodiment, reference may be made to related descriptions in each embodiment of the present disclosure, and details are not described here.

In the embodiment of the disclosure, the mixed downhole signal set is subjected to signal separation, channel compensation, channel equalization and other processing, so that interference components in the downhole signal are filtered to the greatest extent, and meanwhile, the separation matrix can be updated based on blind source separation, so that the signal-to-noise ratio of the target downhole signal set is always smaller than a specific value.

Fig. 7 is a block diagram of a processing apparatus for 5G communication signal interference according to an embodiment of the present disclosure, and as shown in fig. 7, the processing apparatus 700 for 5G communication signal interference includes:

a receiving module 710 for receiving a multi-channel transmitted mixed downhole signal set;

the interference filtering module 720 is configured to filter interference of a multi-channel transmitted mixed downhole signal set based on a current separation matrix of blind source separation to obtain a target downhole signal set;

the interference monitoring module 730 is configured to perform interference monitoring on the target downhole signal set when an interference monitoring period is reached, and acquire a signal-to-noise ratio;

and a matrix updating module 740, configured to execute blind source separation to update the current separation matrix when the signal-to-noise ratio is greater than a preset threshold.

In the embodiment of the disclosure, the separation matrix adaptively filters out interference components in the downhole signal, so that the efficiency of signal anti-interference processing is improved, and meanwhile, the separation matrix can be updated based on blind source separation, so that the signal-to-noise ratio of the signal obtained through the separation matrix is always smaller than a specific value.

It should be noted that the explanation of the foregoing embodiment of the method for processing 5G communication signal interference is also applicable to the apparatus for processing 5G communication signal interference of this embodiment, and details are not repeated here.

Further, in a possible implementation manner of the embodiment of the present disclosure, the interference filtering module 720 is further configured to: and multiplying the multi-channel transmitted mixed downhole signal set by the current separation matrix to obtain a target downhole signal set.

Further, in a possible implementation manner of the embodiment of the present disclosure, the interference monitoring module 730 is further configured to: inputting a target underground signal set into a deep complex network, acquiring a characteristic diagram of the target underground signal set by the deep complex network, and carrying out classification and identification according to the characteristic diagram to acquire the category of the signal in the target underground signal set; and acquiring the signal-to-noise ratio according to the category of the target downhole signal concentrated signal.

Further, in a possible implementation manner of the embodiment of the present disclosure, the interference monitoring module 730 is further configured to: extracting a characteristic diagram of the target downhole signal set by a characteristic extraction layer of the deep complex network to obtain a real part and an imaginary part of the characteristic diagram; carrying out nonlinear mapping on the real part and the imaginary part of the feature map by a complex excitation layer of the depth complex network to obtain the real part and the imaginary part of the mapped feature map; performing pooling operation on the real part and the imaginary part of the mapped feature map by a complex pooling layer of the deep complex network to obtain a pooled feature map; and carrying out full connection operation on the pooled characteristic graphs by a full connection layer of the deep complex network so as to output the category of the target underground signal concentrated signal.

Further, in a possible implementation manner of the embodiment of the present disclosure, the apparatus 700 for processing 5G communication signal interference further includes: a signal processing module 750 for performing channel estimation on the target downhole signal set; performing channel compensation on the target underground signal set subjected to channel estimation; performing channel equalization processing on the target underground signal set subjected to channel compensation to generate an equalized underground signal set; and performing signal judgment on the equalized downhole signal set.

Further, in a possible implementation manner of the embodiment of the present disclosure, the interference monitoring period is greater than a sum of the processing duration of the interference monitoring and the processing duration of the blind source separation.

The present disclosure also provides an electronic device, a readable storage medium, and a computer program product according to embodiments of the present disclosure.

FIG. 8 illustrates a schematic block diagram of an example electronic device 800 that can be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.

As shown in fig. 8, the apparatus includes a memory 810, a processor 820 and a computer program stored in the memory 810 and executable on the processor 820, and when the processor 820 executes the computer program, the method for processing the interference of the 5G communication signal is implemented.

In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.

The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server with a combined blockchain.

Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise.

In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean 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 invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. 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, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.

Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.