Multipath interference noise suppression method and device and storage medium

Abstract

The invention discloses a multipath interference noise suppression method and device and a storage medium. The method comprises the following steps: determining a target sampling signal according to an analog signal; filtering recovery operation is carried out on the target sampling signal to obtain an original sampling signal, and the original sampling signal is the original form of the target sampling signal; eliminating the level shift of the original sampling signal through the adaptive offset to obtain a first sampling signal; demodulating the first sampling signal to obtain and output binary data corresponding to the first sampling signal; the MPI noise suppression is realized by introducing an adaptive offset which can be updated, and the signal quality and the signal transmission performance are improved; and the adaptive offset is updated in real time according to the second sampling signal and the preset updating step length, so that the stability and robustness of noise suppression in different environments are ensured, and the system can keep high-performance operation in a complex and variable practical application scene.

Description

Technical Field

[0001] The present application relates to the technical field of noise processing, and in particular to a method, device and storage medium for suppressing multipath interference noise. Background Art

[0002] In data centers, short-distance fiber-optic communication systems are the preferred solution for high-speed interconnection between servers, storage devices, and network devices, and the intensity modulation and direct detection (IMDD) solution has become the main choice for short-distance interconnection in data centers due to its simple structure, low cost, and energy efficiency. The IMDD system transmits data by modulating the intensity of the light source and directly detects changes in light intensity at the receiving end. Therefore, it has the characteristics of simple structure and low cost, which makes the IMDD system particularly suitable for data centers with thousands to tens of thousands of optical fiber links deployed internally.

[0003] However, with the dense deployment of fiber links inside data centers, the problem of multipath interference (MPI) in the system has become increasingly prominent. MPI is mainly caused by reflection signals in the fiber connectors. These reflection signals will be superimposed on the transmission signal at the receiving end, causing interference and seriously affecting the signal quality. Especially in the IMDD-based system, the four-level pulse amplitude modulation (Pulse Amplitude Modulation with 4 levels, PAM4) used is highly sensitive to MPI noise. MPI noise will introduce irregular fluctuations to the received PAM4 signal, seriously reducing the transmission quality of the PAM4 signal, making MPI noise one of the key factors affecting the performance of the IMDD short-distance fiber communication system based on PAM4. Since the reflected signal is delayed by several kilometers compared to the original signal, which is equivalent to a delay of tens of thousands of baud cycles compared to the original symbol, which exceeds the time range of the traditional equalizer tap, the equalization technology used for inter-symbol interference (ISI) compensation in the related technology cannot effectively compensate for MPI. At present, there are two main MPI mitigation algorithms using balanced digital signal processing algorithms: the MPI fluctuation mitigation (MPI-FM) algorithm and the intensity-dependent MPI mitigation (ID-MPI-M) algorithm. However, these two algorithms are highly complex and difficult to implement. Summary of the invention

[0004] The following is a summary of the subject matter described in detail herein. This summary is not intended to limit the scope of the claims.

[0005] The embodiments of the present application provide a multipath interference noise suppression method, device and storage medium, which can effectively suppress MPI noise.

[0006] In a first aspect, an embodiment of the present application provides a method for suppressing multipath interference noise, the method comprising: Acquire an analog signal of the original received data, and determine a target sampling signal according to the analog signal; Performing filtering and recovery operations on the target sampling signal to obtain an original sampling signal that satisfies the signal-to-noise ratio, wherein the original sampling signal is the original form of the target sampling signal; Eliminating the level offset of the original sampling signal by an adaptive offset to obtain a first sampling signal; Demodulating the first sampling signal to obtain and output binary data corresponding to the first sampling signal; The adaptive offset is updated in real time according to a second sampling signal and a preset update step, the second sampling signal is the first sampling signal that has output corresponding binary data, and the preset update step represents the amplitude of each update of the adaptive offset.

[0007] According to the multipath interference noise suppression method provided by some embodiments of the present application, eliminating the level offset of the original sampling signal by the adaptive offset to obtain the first sampling signal includes: Update and obtain the adaptive offset; The adaptive offset is superimposed on the original sampling signal to obtain the first sampling signal.

[0008] According to the multipath interference noise suppression method provided by some embodiments of the present application, the updating and obtaining of the adaptive offset includes: Acquire the adaptive offset, the standard decision value and the second sampling signal; Determining an error value according to the standard decision value and the second sampling signal; The adaptive offset is updated according to the error value and a preset update step size.

[0009] According to the multipath interference noise suppression method provided by some embodiments of the present application, the filtering and recovery operations are performed on the target sampled signal to obtain the original sampled signal that satisfies the signal-to-noise ratio, including: Performing matched filtering on the target sampling signal to improve the signal-to-noise ratio of the target sampling signal; The target sampling signal with improved signal-to-noise ratio is subjected to feed-forward equalization to obtain the original sampling signal.

[0010] According to the multipath interference noise suppression method provided by some embodiments of the present application, the step of acquiring an analog signal of original received data and determining a target sampling signal according to the analog signal includes: Acquire an analog signal of original received data, and convert the analog signal into a discrete digital signal; According to the preset sampling rate, the sampling rate of the discrete digital signal is adjusted to obtain the target sampling signal.

[0011] According to the multipath interference noise suppression method provided by some embodiments of the present application, after outputting binary data corresponding to the first sampling signal, the method further includes: Obtaining a data bit error rate of the binary data; When the data bit error rate is greater than a preset threshold, the preset update step size is adjusted according to the data bit error rate.

[0012] According to the multipath interference noise suppression method provided by some embodiments of the present application, the data bit error rate of the binary data is obtained according to the following steps: Comparing the original received data with the binary data bit by bit to determine the error bit ratio of the binary data; The data bit error rate is determined according to the error bit ratio.

[0013] In a second aspect, an embodiment of the present application provides a multipath interference noise suppression device, including: A resampling module, used to obtain an analog signal and determine a target sampling signal according to the analog signal; A filtering and recovery module performs a filtering and recovery operation on the target sampling signal to obtain an original sampling signal, where the original sampling signal is the original form of the target sampling signal; An adaptive level offset elimination module, used to eliminate the level offset of the original sampling signal by using the adaptive offset to obtain a first sampling signal; A demodulation module, used for demodulating the first sampling signal to obtain and output binary data corresponding to the first sampling signal; The adaptive offset is updated in real time according to a second sampling signal and a preset update step, the second sampling signal is the first sampling signal that has output corresponding binary data, and the preset update step represents the amplitude of each update of the adaptive offset.

[0014] In a third aspect, an embodiment of the present application provides an electronic device, including: at least one processor; at least one memory for storing at least one program; When at least one of the programs is executed by at least one of the processors, the multipath interference noise suppression method as described in the first aspect of the embodiment of the present application is implemented.

[0015] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program executable by a processor, and the processor-executable computer program is used to implement the method according to any one of claims 1 to 7 when executed by the processor.

[0016] In the embodiment of the present application, the target sampling signal is determined according to the analog signal; the target sampling signal is filtered and restored to obtain the original sampling signal, which is the original form of the target sampling signal; the level offset of the original sampling signal is eliminated by the adaptive offset to obtain the first sampling signal; the first sampling signal is input into the demodulation module for demodulation to obtain and output the binary data corresponding to the first sampling signal; the adaptive offset is updated in real time according to the second sampling signal and the preset update step length, the second sampling signal is the first sampling signal that has output the corresponding binary data, and the preset update step length represents the amplitude of each update of the adaptive offset. By introducing an adaptive offset that can be updated, the suppression of MPI noise is achieved, and the signal quality and signal transmission performance are improved; and the adaptive offset is updated in real time according to the second sampling signal and the preset update step length, which ensures the stability and robustness of the system in different environments, so that the system can maintain high-performance operation in complex and changeable practical application scenarios.

[0017] Other features and advantages of the present application will be described in the following description, and partly become apparent from the description, or understood by practicing the present application. The purpose and other advantages of the present application can be realized and obtained through the structures particularly pointed out in the description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings are used to provide further understanding of the technical solution of the present application and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the technical solution of the present application and do not constitute a limitation on the technical solution of the present application.

[0019] Figure 1 A schematic diagram of the steps of a multipath interference noise suppression method provided in an embodiment of the present application; Figure 2 A schematic diagram of sub-steps of step S110 provided in an embodiment of the present application; Figure 3 A schematic diagram of a level shift elimination module provided in an embodiment of the present application; Figure 4 for Figure 1 Schematic diagram of sub-steps of step S130; Figure 5 A schematic diagram of the steps of updating an adaptive offset provided in an embodiment of the present application; Figure 6 A schematic diagram of another level shift elimination module provided in an embodiment of the present application; Figure 7 A schematic diagram of the structure of a multipath interference noise suppression device provided in an embodiment of the present application; Figure 8 It is a schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0020] The present application is further described below in conjunction with the accompanying drawings and specific embodiments. The described embodiments should not be regarded as limiting the present application, and all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application.

[0021] In the following description, reference is made to “some embodiments”, which describe a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0022] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0023] Before further describing the embodiments of the present application in detail, the nouns and terms involved in the embodiments of the present application are explained. The nouns and terms involved in the embodiments of the present application are subject to the following interpretations.

[0024] Short-distance fiber-optic communication refers to the technology of using optical fiber for data transmission over a relatively short distance. This communication method is widely used in data centers, local area networks (LAN), metropolitan area networks (MAN), and interconnection between devices. Short-distance fiber-optic communication has the advantages of high bandwidth, low latency, high reliability and anti-electromagnetic interference, making it an important part of modern communication systems.

[0025] Intensity modulation and direct detection (IMDD) is a modulation and detection technology widely used in fiber-optic communication systems. IMDD technology is simple, reliable, and suitable for various transmission distances and data rates. It is particularly suitable for short-distance and medium-distance fiber-optic communication systems. It mainly uses four-level pulse amplitude modulation. In intensity modulation, the information signal is used to modulate the intensity of the light source. Specifically, the electrical signal drives the laser or light-emitting diode (LED) to change the intensity of its output light, thereby encoding information into the optical signal; in direct detection, the received optical signal is converted into an electrical signal by a photodetector (such as a PIN photodiode or an avalanche photodiode). The photodetector converts the intensity change of the optical signal into a corresponding electrical signal, and then restores the original information through processing steps such as amplification, filtering, and decoding. The IMDD system has the characteristics of simple structure, easy implementation and maintenance, low cost, and strong anti-interference ability. However, due to the limited linearity of direct detection, the IMDD system may encounter performance bottlenecks in high-bandwidth applications, and direct detection is sensitive to noise, especially under low optical power conditions. In order to ensure signal quality, the IMDD system usually requires a high signal-to-noise ratio.

[0026] Four-level pulse amplitude modulation (PAM4) is a modulation technique that transmits information by using four different raw sampled signals. Compared with traditional binary modulation (such as NRZ, Non-Return-to-Zero), PAM4 can achieve twice the data transmission rate at the same baud rate, so it has been widely used in high-speed communication systems, especially in Ethernet, data centers, and high-performance computing. PAM4 uses four different levels to represent information, usually expressed as 00, 01, 10, and 11. These four levels can be recorded as -3, -1, 1, and 3 (assuming normalized levels), and each symbol can carry 2 bits of information. For example, level -3 represents 00 and level -1 represents 01.

[0027] A key equalization technology in PAM4 is feed-forward equalization (FFE), which is used to reduce inter-symbol interference (ISI) and improve signal quality.

[0028] Multipath interference (MPI) is a common phenomenon in fiber optic communications, especially in short-haul and medium-haul fiber optic communication systems. MPI occurs when optical signals reach the receiving end through multiple paths. The lengths of these paths are different, resulting in different signal arrival times, which causes phase distortion and interference effects, ultimately affecting signal quality. The interference effect causes the intensity of the received optical signal to fluctuate, which may cause an increase in the bit error rate, while the phase difference of the multipath signal will cause signal phase distortion, affecting signal integrity.

[0029] In data centers, short-distance optical fiber communication systems are the preferred solution for high-speed interconnection between servers, storage devices, and network devices, and the IMDD solution has become the main choice for short-distance interconnection in data centers due to its simple structure, low cost, and energy efficiency. The IMDD system transmits data by modulating the intensity of the light source and directly detects changes in light intensity at the receiving end. Therefore, it has the characteristics of simple structure and low cost, which makes the IMDD system particularly suitable for data centers with thousands to tens of thousands of optical fiber links deployed internally.

[0030] However, with the dense deployment of fiber links inside data centers, the MPI problem has become increasingly prominent. MPI is mainly caused by reflection signals in fiber connectors. These reflection signals will be superimposed on the transmission signal at the receiving end, causing interference and seriously affecting the signal quality. Especially in the IMDD-based system, the PAM4 modulation used is highly sensitive to MPI noise. MPI noise will introduce irregular fluctuations to the received PAM4 signal, seriously reducing the transmission quality of the PAM4 signal, making MPI noise one of the key factors affecting the performance of the IMDD short-distance fiber communication system based on PAM4. Since the reflected signal is delayed by several kilometers compared to the original signal, which is equivalent to thousands of baud cycles delayed compared to the original symbol, it exceeds the time range of the traditional equalizer tap. Therefore, the equalization technology used for ISI compensation in related technologies cannot effectively compensate for MPI. At present, there are two main MPI mitigation algorithms using balanced digital signal processing algorithms: MPI fluctuation mitigation (MPI-FM) algorithm and intensity-dependent MPI mitigation (ID-MPI-M) algorithm. However, these two algorithms are highly complex and difficult to implement.

[0031] Based on this, the embodiments of the present application provide a multipath interference noise suppression method, device and storage medium to suppress MPI noise and improve signal quality and signal transmission performance.

[0032] Please refer to Figure 1 , is a schematic diagram of the steps of a multipath interference noise suppression method provided in an embodiment of the present application, such as Figure 1 As shown, in the embodiment of the present application, the multipath interference noise suppression method provided may include but is not limited to steps S110 to S140: Step S110: Acquire an analog signal of the original received data, and determine a target sampling signal according to the analog signal.

[0033] It should be noted that in the embodiment of the present application, a resampling operation needs to be performed after the original received data is received so that the signal can match the sampling rate adapted by the system to facilitate subsequent signal processing.

[0034] For example, please refer to Figure 2, is a schematic diagram of sub-steps of step S110 provided in an embodiment of the present application, such as Figure 2 As shown, in the embodiment of the present application, the resampling process of the received signal may include but is not limited to step S111 and step S112: Step S111: Acquire the analog signal of the original received data, and convert the analog signal into a discrete digital signal.

[0035] It is understandable that the analog signal of the acquired original received data needs to be converted into a discrete digital signal in order to ensure that the computer can process it efficiently.

[0036] Specifically, in a feasible embodiment of the present application, converting the analog signal into a digital signal may include: Sampling: Extracting instantaneous values ​​from the analog signal of the acquired original received data at fixed time intervals to form a series of amplitude values ​​at discrete time points; Quantization: Mapping the amplitude values ​​obtained by sampling to a finite discrete level, each possible amplitude value is assigned to the nearest quantization level; Encoding: Convert the quantized amplitude value into binary digital form, and the quantization level corresponds to a unique binary code.

[0037] The processing method for converting analog signals into discrete digital signals can be selected according to actual needs. The analog-to-digital conversion method provided in the embodiment of the present application can be selected, or other conversion methods can be used. The present application does not impose too many restrictions on the method for converting analog signals into discrete digital signals.

[0038] By converting the analog signal into a discrete digital signal, the subsequent signal processing in the computer can be more efficient. However, the sampling rate of the discrete digital signal obtained by analog-to-digital conversion may not match the sampling rate in the subsequent processing system, so step S112 is required.

[0039] Step S112: adjusting the sampling rate of the discrete digital signal according to a preset sampling rate to obtain a target sampling signal.

[0040] It is understandable that in a communication system, different devices and standards may use different sampling rates. Resampling can convert a signal from one sampling rate to another sampling rate to ensure compatibility and interoperability between different devices. Therefore, according to the preset sampling rate, the sampling rate of the discrete digital signal is adjusted to obtain the target sampling signal.

[0041] The selection of the preset sampling rate can be set according to the system selected in the actual operation, and this application does not impose any restrictions on the selection of the preset sampling rate. Resampling according to the preset sampling rate can adopt upsampling method to interpolate to increase the sampling rate or use downsampling method to reduce the sampling rate.

[0042] Specifically, in a feasible embodiment of the present application, if the preset sampling rate is greater than the sampling rate of the discrete digital signal obtained through step S111, an upsampling method is used for resampling, and zero values ​​are inserted between discrete digital signals to increase the number of samples. For example, if the goal is to double the sampling rate, a zero value can be inserted between every two original samples. After inserting the zero value, high-frequency components will appear in the signal, and these components do not actually exist in the original signal. Therefore, a low-pass filter is required to remove these additional high-frequency components to restore the smoothness of the signal and obtain a target sampling signal that meets the preset sampling rate.

[0043] In another feasible embodiment of the present application, if the preset sampling rate is lower than the sampling rate of the discrete digital signal obtained through step S112, the downsampling method is used for resampling. First, the discrete digital signal needs to be low-pass filtered to prevent aliasing. Aliasing will cause high-frequency signals to be mistakenly interpreted as low-frequency signals, thereby destroying the integrity of the signal. After low-pass filtering, some samples are deleted according to certain rules (usually uniformly spaced) to achieve the purpose of reducing the sampling rate and obtain a target sampling signal that meets the preset sampling rate.

[0044] In the embodiment of the present application, after resampling, a target sampling signal is obtained to perform step S120.

[0045] Step S120 , filtering and restoring the target sampled signal to obtain an original sampled signal satisfying the signal-to-noise ratio, where the original sampled signal is the original form of the target sampled signal.

[0046] It should be noted that in the embodiment of the present application, since IMDD is used for modulation detection, the requirements for the obtained target sampling signal are relatively high. At this time, it is necessary to improve the signal-to-noise ratio of the target sampling signal through filtering in step S120; at the same time, in order to eliminate the subsequent level offset, the target sampling signal is restored to its original form through a recovery operation, laying the foundation for eliminating the level offset.

[0047] Exemplarily, in the embodiment of the present application, the target sampled signal is filtered and restored to obtain the original sampled signal, which may include but is not limited to: Perform matched filtering on the target sampling signal to improve the signal-to-noise ratio of the target sampling signal; The target sampling signal with improved signal-to-noise ratio is feed-forward equalized to obtain the original sampling signal.

[0048] It should be noted that matched filtering is used to improve the signal-to-noise ratio of the signal, so that the signal can be concentrated in a specific frequency band, thereby reducing the interference of noise on the signal. Specifically, in the embodiment of the present application, matched filtering can be implemented by a matched filter, and the target sampling signal can be matched filtered by convolution.

[0049] After the target sampling signal is obtained, it is input into the set matched filter to increase the frequency of the target sampling signal. Matched filtering can effectively improve the quality of the signal, thereby providing a good input for subsequent equalization processing.

[0050] After matched filtering, the target sampled signal for improving the signal-to-noise ratio is fed-forward equalized, and the feed-forward equalization is implemented using a pre-trained feed-forward equalizer. The feed-forward equalizer is the most common linear equalizer, which delays, multiplies and adds the received signal through a finite impulse response filter. The setting of the feed-forward equalizer can be obtained by referring to the feed-forward equalizer training method in the relevant technology, and will not be described in detail here. The original form of the signal can be restored through feed-forward equalization.

[0051] The target sampling signal with a signal-to-noise ratio that meets the requirement can be obtained through matched filtering in step S120, and then the original form of the target sampling signal, that is, the original sampling signal, can be obtained through feedforward equalization.

[0052] Step S130: Eliminate the level offset of the original sampling signal by using an adaptive offset to obtain a first sampling signal.

[0053] It should be noted that in the embodiment of the present application, the adaptive offset is updated in real time according to the second sampling signal and the preset update step size, the second sampling signal is the first sampling signal that has output the corresponding binary data, and the preset update step size represents the amplitude of each update of the adaptive offset.

[0054] In the embodiment of the present application, an adaptive offset is added to eliminate the level offset of the original sampled signal. Since the adaptive offset can be updated, level elimination can be achieved in real time according to the received signal.

[0055] Exemplarily, in the embodiment of the present application, step S130 is performed by setting a level offset elimination module, please refer to Figure 3 , is a schematic diagram of a level shift elimination module provided in an embodiment of the present application, such as Figure 3 As shown, in the embodiment of the present application, the level offset elimination module includes three adders and a multiplier, wherein one multiplier and one adder are located in the adaptive offset update unit, E (n) is the original input sampling signal, y(n) is the first sampling signal, offset(n) is the adaptive offset, when the original sampling signal x EAfter (n) is input into the level offset elimination module, it first passes through an adder, where it is level-eliminated by an adaptive offset offset (n) to obtain a first sampling signal y (n); The acquisition formula of the first sampling signal y(n) is as follows: y(n)=x E (n)+offset(n).

[0056] It should be noted that in the embodiment of the present application, since the level offset introduced by the MPI noise is different at different times, the use of a fixed offset will not be able to effectively eliminate the level offset at different times. Therefore, in the embodiment of the present application, an adaptive offset that can be updated in real time is used to achieve dynamic adjustment and elimination of the level offset. When the first sampling signal is obtained, the first sampling signal is output and the adaptive offset is updated as the second sampling signal to obtain an updated adaptive offset for level elimination of the next original sampling signal.

[0057] Please refer to Figure 4 , is a schematic diagram of the sub-steps of step S130 in the embodiment of the present application, such as Figure 4 As shown, in the embodiment of the present application, step S130 may include but is not limited to step S131 and step S132: Step S131: Update and obtain the adaptive offset.

[0058] By updating the adaptive offset, it can be ensured that the adaptive offset used for offset elimination each time can accurately eliminate the offset of the original sampling signal.

[0059] For example, refer to Figure 5 , is a schematic diagram of a step of adaptive offset updating provided in an embodiment of the present application, such as Figure 5 As shown, in the embodiment of the present application, the updating step of the adaptive offset may include but is not limited to step S210 to step S230: Step S210: Acquire an adaptive offset, a standard decision value, and a second sampling signal.

[0060] It should be noted that if Figure 6 As shown, in the embodiment of the present application, the adaptive offset is offset(n), when it is used for the original sampling signal x E After the offset of (n) is eliminated, a first sampling signal y(n) is obtained. After the first sampling signal y(n) is output, it is used as a second sampling signal to perform adaptive offset update of the next original sampling signal.

[0061] Specifically, in a feasible embodiment of the present application, it is assumed that the original sampling signal includes x E (1) x E(2), …, x E (n), the adaptive offset is offset (1), when the input x E (1), offset is eliminated by adaptive offset offset (1), and the first sampling signal y (1) is obtained, and then y (1) is output. After the offset elimination is completed, the adaptive offset offset (1) needs to be updated. First, y (1) and adaptive offset offset (1) are obtained. y (1) is used as the second sampling signal to update the adaptive offset offset (1); when offset (1) is updated, the updated adaptive offset offset (2) is obtained. Offset (2) is used to update x E (2) Eliminate the offset, and so on until x is completed. E (n) offset elimination.

[0062] It should be noted that if Figure 6 As shown, in the embodiment of the present application, the updating of the adaptive offset offset(n) also requires a standard decision value d(n), which is a reference level used to determine which logic state the received signal belongs to. These decision levels are usually set at the midpoint of adjacent levels. By comparing the received signal with the standard decision value, the logic state of the signal can be determined.

[0063] In the embodiment of the present application, the setting of the standard decision value can be set according to the actual situation. For example, in a feasible embodiment of the present application, assuming that the four levels of PAM4 are -1V, -0.33V, 0.33V and 1V, the standard decision value can be set to -0.665V, 0V and 0.665V, and the standard decision value is selected according to the interval in which the level of the second sampling signal falls, for example: If the second sampling signal falls between -1V and -0.33V, the standard decision value is selected to be -0.665V; If the second sampling signal falls between -0.33V and 0.33V, the standard decision value is selected as 0V; If the second sampling signal falls between 0.33V and 1V, the standard decision value is selected as 0.665V.

[0064] After obtaining the adaptive offset, the standard decision value and the second sampling signal, execute step S220. Step S220: determine the error value according to the standard decision value and the second sampling signal.

[0065] For example, Figure 6 As shown, in the embodiment of the present application, the error value is e(n), and the error value e(n) is determined by the standard decision value d(n) and the second sampling signal y(n), and the formula is as follows: e(n)=y(n)-d(n); The error value e(n) obtained by calculation can be used to update the adaptive offset.

[0066] Step S230: Update the adaptive offset according to the error value and the preset update step size.

[0067] For example, Figure 6 As shown, in the embodiment of the present application, the adaptive offset offset (n) is updated according to the error value e (n) and the preset update step size μ (not shown in the figure), and the update formula is as follows: offset(n+1)=offset(n)+μ*e(n); It should be noted that the preset update step size μ in the embodiments of the present application can be set specifically according to factors such as noise tolerance, system linearity and transmission distance. The user makes corresponding choices based on the actual equipment used. The setting of the preset update step size in this application will be specifically described in the embodiments below.

[0068] The updated adaptive offset offset (n+1) is used for the next original sample signal x E (n) level offset is eliminated.

[0069] In the embodiment of the present application, through steps S210 to S230, the adaptive offset is updated in real time to achieve dynamic adjustment and elimination of the level offset, thereby avoiding the inability to effectively eliminate the level offset due to the differences in the introduced original sampling signals at different times.

[0070] Step S132: Superimpose the adaptive offset with the original sampling signal to obtain a first sampling signal.

[0071] When the updated adaptive offset is obtained, it can be superimposed on the original sampling signal to eliminate the level offset of the original sampling signal and obtain the first sampling signal.

[0072] Step S140: demodulate the first sampling signal to obtain and output binary data corresponding to the first sampling signal.

[0073] After the level offset is eliminated, the first sampling signal is obtained, which can be demodulated into binary data for output. In the embodiment of the present application, the target sampling signal is determined according to the analog signal; the target sampling signal is filtered and restored to obtain the original sampling signal, which is the original form of the target sampling signal; the level offset of the original sampling signal is eliminated by the adaptive offset to obtain the first sampling signal; the first sampling signal is input into the demodulation module for demodulation, and the binary data corresponding to the first sampling signal is obtained and output; the adaptive offset is updated in real time according to the second sampling signal and the preset update step size, and the second sampling signal is the first sampling signal that has output the corresponding binary data, and the preset update step size represents the amplitude of each update of the adaptive offset. By introducing an adaptive offset that can be updated, the suppression of MPI noise is achieved, and the signal quality and signal transmission performance are improved; and the adaptive offset is updated in real time according to the second sampling signal and the preset update step size, which ensures the stability and robustness of the system in different environments, so that the system can maintain high-performance operation in complex and changeable practical application scenarios.

[0074] It should be noted that, in the embodiment of the present application, after outputting the binary data corresponding to the first sampling signal, it is necessary to compare the binary data with the received original received data, and further adjust the parameters used for multipath interference noise suppression. The parameters used for multipath interference noise suppression are the preset update step size. For example, Figure 7 As shown, in the embodiment of the present application, the step of adjusting the preset update step size may include but is not limited to step S310 and step S320: Step S310, obtaining a data bit error rate of binary data; It can be understood that the bit error rate is used to determine whether the first sampling signal after level offset correction is the same as the original received signal. A lower bit error rate means that the quality of the system transmission signal running the multipath interference noise suppression method is better and the system performance is more stable; on the contrary, a higher bit error rate indicates that the first sampling signal is seriously affected by interference or noise, and there are major problems with the system performance. When the bit error rate is higher than a certain threshold, the system needs to be optimized.

[0075] Exemplarily, in one embodiment of the present application, the bit error rate of binary data can be obtained according to the following steps: Compare the original received data and the binary data corresponding to the first sampling signal bit by bit to determine the error bit ratio of the binary data; The data bit error rate is determined based on the error bit ratio.

[0076] The bit error rate is statistically calculated for subsequent parameter adjustment, and step S320 is executed.

[0077] Step S320: When the data bit error rate is greater than a preset threshold, adjust the preset update step size according to the data bit error rate.

[0078] It can be understood that in the embodiment of the present application, when it is found that the bit error rate is greater than the preset threshold, it indicates that the effect of level offset suppression is reduced. At this time, it is necessary to adjust the system for level offset suppression so that it can effectively suppress the level offset. In the embodiment of the present application, the bit error rate is reduced by adjusting the preset update step size.

[0079] Exemplarily, in one embodiment of the present application, adjustment factors α and β are set, where α>1, β<1. When the bit error rate exceeds a preset threshold, the preset update step size is first adjusted using the adjustment factor α by a multiplication operation. After the adjustment, a level shift suppression operation is further performed. If the bit error rate decreases, the adjustment factor α continues to be used to adjust the preset update step size until the bit error rate is lower than the preset threshold. When the bit error rate has not decreased or has increased, the preset update step size is restored and the adjustment factor β is used to adjust the preset update step size until the bit error rate is lower than the preset threshold.

[0080] It can be understood that in the embodiment of the present application, a test signal can be used in advance to test the system for multipath interference noise suppression. After executing steps S110 to S140, the test bit error rate is determined, and then the preset step size is adjusted. When the level offset suppression effect that meets the requirements is obtained in the test signal, PAM4 signal modulation is performed.

[0081] The level offset suppression effect of the signal is guaranteed by adjusting the preset update step size, so that the level offset suppression system can effectively reduce the impact caused by the level offset.

[0082] It should be noted that in the embodiment of the present application, adjustments can also be made by analyzing the causes of bit errors. In addition to MPI, the main causes of bit errors also include ISI and insufficient signal-to-noise ratio. Therefore, in the embodiment of the present application, when the bit error rate cannot be reduced by adjusting the preset update step size, it is still necessary to analyze the causes of the bit errors in order to make adjustments based on the causes of the bit errors.

[0083] For example, in an embodiment of the present application, when the bit error rate cannot be reduced by adjusting the preset update step size, the following method can be used to analyze whether the high bit error rate is caused by ISI: 1. Time domain analysis: The waveform of the signal can be observed through time domain analysis. ISI will cause waveform distortion, especially at the symbol boundary; 2. Equalizer performance: By observing the performance of the equalizer, the impact of ISI can be evaluated. If the equalizer cannot effectively reduce ISI, it means that ISI may be the main cause of bit errors.

[0084] When it is determined that the bit error rate exceeds the preset threshold value due to ISI, the problem of excessively high bit error rate caused by ISI can be reduced by adjusting the filtering and recovery operation steps (i.e., step S120 in the embodiment of the present application). The specific adjustment method may be adjusting the parameters of the equalizer for feedforward equalization. The adjustment method may use the design adjustment method of the equalizer in the relevant technical solution, which will not be described in detail here.

[0085] In another embodiment of the present application, when the bit error rate cannot be reduced by adjusting the preset update step size, the following method can be used to analyze whether the high bit error rate is caused by insufficient signal-to-noise ratio: 1. Signal-to-noise ratio measurement: By measuring the signal-to-noise ratio, the quality of the signal can be directly evaluated. If the SNR is lower than the threshold required by the system, it means that insufficient SNR may be the main cause of bit errors; 2. Noise source analysis: By analyzing the noise source, the source of the noise can be determined, such as external interference, power supply noise, etc.

[0086] When it is determined that the bit error rate exceeds the preset threshold value due to insufficient signal-to-noise ratio, the problem of excessively high bit error rate caused by insufficient signal-to-noise ratio can be reduced by adjusting the filtering and recovery operation steps (i.e., step S120 in the embodiment of the present application). The specific adjustment method can be adjusting the matched filter parameters for matched filtering. The adjustment method can use the design adjustment method of the matched filter in the relevant technical solution, which will not be described in detail here.

[0087] Please refer to Figure 7 , is a schematic diagram of the structure of a multipath interference noise suppression device provided in an embodiment of the present application, such as Figure 7 As shown, in the embodiment of the present application, the multipath interference noise suppression device 100 provided may include but is not limited to: The resampling module 110 is used to obtain an analog signal and determine a target sampling signal according to the analog signal; The filtering and restoring module 120 performs a filtering and restoring operation on the target sampled signal to obtain an original sampled signal, where the original sampled signal is the original form of the target sampled signal; An adaptive level offset elimination module 130, configured to eliminate the level offset of the original sampling signal by adaptively offsetting the amount of the offset to obtain a first sampling signal; The demodulation module 140 is used to demodulate the first sampling signal to obtain and output binary data corresponding to the first sampling signal; The adaptive offset is updated in real time according to the second sampling signal and the preset update step length, the second sampling signal is the first sampling signal that has output the corresponding binary data, and the preset update step length represents the amplitude of each update of the adaptive offset.

[0088] It can be understood that in an embodiment of the present application, the filtering recovery module 120 may include a matched filter unit 121 and an equalizer unit 122, wherein the matched filter unit 121 is used to perform matched filtering on the target sampling signal to provide a signal-to-noise ratio of the target sampling signal, and the equalizer unit 122 is used to perform feed-forward equalization on the target sampling signal after the signal-to-noise ratio is improved.

[0089] It should be noted that in the embodiment of the present application, after the first sampling signal is demodulated and output, a bit error rate calculation will also be performed. When the bit error rate is higher than a preset threshold, the preset update step size will be updated. Therefore, the multipath interference noise suppression device 100 provided in the embodiment of the present application may also include a bit error rate calculation module.

[0090] Reference Figure 8 The embodiment of the present application further discloses an electronic device, the electronic device 1100 comprising: at least one processor 1101; At least one memory 1102, used to store at least one program; When at least one program is executed by at least one processor 1101, the multipath interference noise suppression method as described above is implemented.

[0091] The embodiment of the present application further discloses a computer-readable storage medium, which stores a computer program executable by a processor. When the computer program executable by the processor is executed by the processor, it is used to implement the multipath interference noise suppression method as described above.

[0092] An embodiment of the present application also discloses a computer program product, including a computer program or computer instructions, wherein the computer program or computer instructions are stored in a computer-readable storage medium, a processor of an electronic device reads the computer program or computer instructions from the computer-readable storage medium, and the processor executes the computer program or computer instructions, so that the electronic device performs the multipath interference noise suppression method as described above.

[0093] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein, for example. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0094] It should be understood that in the present application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0095] In the several embodiments provided in the present 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 only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, 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 an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0096] In the embodiments of the present application, the term "module" or "unit" refers to a computer program or a part of a computer program that has a predetermined function and works together with other related parts to achieve a predetermined goal, and can be implemented in whole or in part by using software, hardware (such as processing circuits or memories), or a combination thereof. Similarly, a processor (or multiple processors or memories) can be used to implement one or more modules or units. In addition, each module or unit can be part of an overall module or unit that includes the function of the module or unit.

[0097] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0098] 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. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0099] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, referred to as ROM), random access memory (Random Access Memory, referred to as RAM), disk or optical disk and other media that can store program codes.

[0100] The step numbers in the above method embodiment are only provided for the convenience of explanation and description, and no limitation is imposed on the order of the steps. The execution order of each step in the embodiment can be adaptively adjusted according to the understanding of those skilled in the art.

Claims

1. A method for suppressing multipath interference noise, the method comprising: Acquire an analog signal of the original received data, and determine a target sampling signal according to the analog signal; Performing filtering and recovery operations on the target sampling signal to obtain an original sampling signal that satisfies the signal-to-noise ratio, wherein the original sampling signal is the original form of the target sampling signal; Eliminating the level offset of the original sampling signal by an adaptive offset to obtain a first sampling signal; Demodulating the first sampling signal to obtain and output binary data corresponding to the first sampling signal; The adaptive offset is updated in real time according to a second sampling signal and a preset update step, the second sampling signal is the first sampling signal that has output corresponding binary data, and the preset update step represents the amplitude of each update of the adaptive offset.

2. The multipath interference noise suppression method according to claim 1, characterized in that: Eliminating the level offset of the original sampling signal by using the adaptive offset to obtain a first sampling signal includes: Update and obtain the adaptive offset; The adaptive offset is superimposed on the original sampling signal to obtain the first sampling signal.

3. The multipath interference noise suppression method according to claim 2, characterized in that: The updating and obtaining of the adaptive offset includes: Acquire the adaptive offset, the standard decision value and the second sampling signal; Determining an error value according to the standard decision value and the second sampling signal; The adaptive offset is updated according to the error value and a preset update step size.

4. The multipath interference noise suppression method according to claim 1, characterized in that: The filtering and restoring operation is performed on the target sampled signal to obtain an original sampled signal satisfying the signal-to-noise ratio, including: Performing matched filtering on the target sampling signal to improve the signal-to-noise ratio of the target sampling signal; The target sampling signal with improved signal-to-noise ratio is subjected to feed-forward equalization to obtain the original sampling signal.

5. The multipath interference noise suppression method according to claim 1, characterized in that: The step of acquiring an analog signal of the original received data and determining a target sampling signal according to the analog signal comprises: Acquire an analog signal of original received data, and convert the analog signal into a discrete digital signal; According to the preset sampling rate, the sampling rate of the discrete digital signal is adjusted to obtain the target sampling signal.

6. The multipath interference noise suppression method according to claim 1, characterized in that: After outputting the binary data corresponding to the first sampling signal, the method further includes: Obtaining a data bit error rate of the binary data; When the data bit error rate is greater than a preset threshold, the preset update step size is adjusted according to the data bit error rate.

7. The multipath interference noise suppression method according to claim 6, characterized in that: The data bit error rate of the binary data is obtained according to the following steps: Comparing the original received data with the binary data bit by bit to determine the error bit ratio of the binary data; The data bit error rate is determined according to the error bit ratio.

8. A multipath interference noise suppression device, characterized in that: include: A resampling module, used to obtain an analog signal and determine a target sampling signal according to the analog signal; A filtering and recovery module performs a filtering and recovery operation on the target sampling signal to obtain an original sampling signal, where the original sampling signal is the original form of the target sampling signal; An adaptive level offset elimination module, used to eliminate the level offset of the original sampling signal by using the adaptive offset to obtain a first sampling signal; A demodulation module, used for demodulating the first sampling signal to obtain and output binary data corresponding to the first sampling signal; The adaptive offset is updated in real time according to a second sampling signal and a preset update step, the second sampling signal is the first sampling signal that has output corresponding binary data, and the preset update step represents the amplitude of each update of the adaptive offset.

9. An electronic device, characterized in that: include: at least one processor; at least one memory for storing at least one program; When at least one of the programs is executed by at least one of the processors, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: A computer program executable by a processor is stored therein, and when the computer program executable by the processor is executed by the processor, it is used to implement the method according to any one of claims 1 to 7.

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