Signal equalization method, device and system and storage medium

Abstract

The invention provides a signal equalization method, device and system and a storage medium. The method comprises: according to amplitudes of a target signal at two adjacent moments, determining coordinate values of the target signal at central positions of decision values corresponding to a plurality of branch paths, the plurality of branch paths being paths when a target level state is transferred at the two adjacent moments; according to the coordinate value of the central position and the tap coefficient, a central metric value of the target signal at the current moment is determined, and the central metric value is used for measuring the distance between the decision value and the central position; and determining a state transition path of the level state transition of the target signal from the starting moment to the current moment according to the center metric value, the path accumulated metric value at the previous moment and the tap coefficient. According to the scheme, the signals can be balanced, and the overhead of computing resources and the time delay in the signal balancing process are reduced.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a signal equalization method, device, system and storage medium. Background Art

[0002] With the rapid development of cloud computing, big data, the Internet of Things, artificial intelligence and other related industries, the amount of data has shown an explosive growth. High-speed link technology has become the basic technology for chip interconnection and interface, including electrical interconnection links and optical interconnection links. As the communication rate continues to increase, the inter-symbol interference (ISI) in the end-to-end link deteriorates more and more seriously, making it increasingly difficult for the bit error rate to meet communication needs.

[0003] Currently, signal equalization can reduce inter-symbol interference and make the bit error rate meet communication requirements. Therefore, a signal equalization method is urgently needed. Summary of the invention

[0004] The embodiments of the present application provide a signal equalization method, device, system and storage medium, which can equalize signals and thus reduce inter-symbol interference.

[0005] In a first aspect, an embodiment of the present application provides a signal equalization method, which is applied to a signal receiving device in a signal transmission system, wherein the signal transmission system includes a signal sending device and the signal receiving device that are communicatively connected via an interconnection link, including:

[0006] receiving a target signal sent by the signal sending device;

[0007] Determine, according to the amplitude of the target signal at two adjacent moments, the coordinate values ​​of the center positions of the decision values ​​of the target signal corresponding to the plurality of branch paths, the plurality of branch paths being paths when the target level state is transferred at the two adjacent moments, the two adjacent moments including the previous moment and the current moment, the target level state being the level state after the dimensionality reduction of the plurality of level states;

[0008] Determine, according to the coordinate value of the center position and the tap coefficient, a center metric value of the target signal at the current moment, wherein the center metric value is used to measure the distance between the decision value and the center position, and the tap coefficient represents the characteristics of the channel formed by the interconnected link;

[0009] According to the central measurement value, the path cumulative measurement value at the previous moment and the tap coefficient, the state transition path of the level state transition of the target signal from the starting moment to the current moment is determined, wherein the path cumulative measurement value is used to measure the sum of the Euclidean distances between the amplitude of the target signal and the decision value at different moments.

[0010] According to this solution, through the symmetry of the decision values ​​corresponding to the multiple branch paths, the center position of the decision value corresponding to the branch path can be determined based on the amplitude of the target signal at two adjacent moments. Based on the center position corresponding to the decision value, the center measurement value of the target signal at the current moment is derived, so as to determine the distance between each decision value and the center position, and then the state transition path of the target signal from the starting moment to the current moment can be determined based on the center measurement value and the path cumulative measurement value at the previous moment, so as to complete the equalization of the target signal through the state transition path, wherein the path cumulative measurement can measure the path cumulative measurement value for measuring the sum of the Euclidean distances between the amplitude of the target signal and the decision value at different moments. Moreover, the target level state is the level state after dimensionality reduction, which simplifies the calculation process and reduces the overhead of computing resources.

[0011] In a possible implementation, determining the state transition path of the level state transition of the target signal from the starting time to the current time according to the center metric value, the path cumulative metric value at the previous time, and the tap coefficient includes:

[0012] Determine the path center metric value of the target signal at the current moment according to the center metric value, the path cumulative metric value at the previous moment and the tap coefficient, wherein the path center metric value is used to measure the distance from the target signal to the center of the branch path;

[0013] A state transition path for the target signal to perform level state transition from the starting time to the current time is determined according to the path center metric value and the tap coefficient.

[0014] In this way, the center metric value of the path can be determined through the center metric value, and the state transition path can be determined based on the path center metric value and the cumulative metric value of the path at the previous moment. The state transition path can be determined without calculating the Euclidean distance between the amplitude of the target signal and the decision value, which simplifies the method of determining the state transition path and reduces the overhead of computing resources.

[0015] In a possible implementation, the path center metric value of the target signal satisfies the following formula:

[0016] c(tk)=pm(tk-1)+αp(tk);

[0017] Among them, c(tk) represents the path center metric value at time tk, pm(tk-1) represents the path center metric value at time tk-1, α represents the tap coefficient, and p(tk) represents the center metric value at time tk.

[0018] In this way, the path center metric value can be determined only through a simple calculation method, and the state transition path can be determined without the need for complex Euclidean distance calculation, thereby reducing the overhead of computing resources.

[0019] In a possible implementation, determining, according to the path center metric value and the tap coefficient, a state transition path for the target signal to perform level state transition from the starting moment to the current moment includes:

[0020] Determine a comparison result by comparing the path center metric value and the tap coefficient;

[0021] Determining a plurality of maximum likelihood paths from the plurality of branch paths according to the comparison result;

[0022] Determine the cumulative metric value of the path at the current moment according to the comparison result;

[0023] The state transition path is determined according to the path accumulated metric value and the multiple maximum likelihood paths.

[0024] In this way, multiple maximum likelihood paths can be determined only by using the path center metric and the tap coefficient, without the need to perform complex Euclidean distance calculations, thus reducing the cost of computing resources.

[0025] In a possible implementation, the state transition path is a path with the smallest sum of Euclidean distances among the multiple maximum likelihood paths.

[0026] In a possible implementation, determining the coordinate values ​​of the center positions of the decision values ​​of the target signal corresponding to each of the plurality of branch paths according to the amplitudes of the target signal at two adjacent moments includes:

[0027] Determine, from a plurality of level states, a level state that is closest to the amplitude of the target signal at the current moment;

[0028] Determine, from the multiple level states, a level state that is closest to the amplitude of the target signal at the previous moment;

[0029] Determine a first error between the amplitude of the target signal at the current moment and the level state closest to the amplitude of the target signal at the current moment;

[0030] Determine a second error between the amplitude of the target signal at the previous moment and the level state closest to the amplitude of the target signal at the previous moment;

[0031] The coordinate value of the center position is determined according to the first error, the second error, the level state closest to the amplitude of the target signal at the previous moment, and the level state closest to the amplitude of the target signal at the previous moment.

[0032] In this way, based on the symmetry of the decision values ​​corresponding to the branch paths after dimensionality reduction, the coordinate value of the center position can be determined, thereby simplifying the subsequent maximum likelihood path determination process and reducing the cost of computing resources.

[0033] In a possible implementation, the coordinate value (m, n) of the center position satisfies the following formula:

[0034] m=2*(sign(a+sign(e))+1)-2, n=2*(sign(a'+sign(e'))+1)-2;

[0035] Among them, sign is a sign function, a represents the level state closest to the amplitude of the target signal at the current moment, e represents the first error, a' represents the level state closest to the amplitude of the target signal at the previous moment, e' represents the second error, and sign is a sign function.

[0036] In a possible implementation, the central metric value satisfies the following formula:

[0037] p(tk)=u(tk)-(m+nα);

[0038] Among them, p(tk) represents the center measurement value at time tk, u(tk) represents the amplitude of the target signal at time tk, (m, n) represents the coordinate value of the center position, and α represents the tap coefficient.

[0039] In a second aspect, an embodiment of the present application provides a signal equalization method, which is applied to a signal receiving device in a signal transmission system, wherein the signal transmission system includes a signal sending device and the signal receiving device connected to each other through an interconnection link, including:

[0040] receiving a target signal sent by the signal sending device, wherein the target signal includes amplitudes at different times;

[0041] In the case where burst error detection is started, determining an original error sequence of a burst error occurring in the target signal, the original error sequence comprising a plurality of error values ​​formed from a burst error start (Sob) position to a burst error end (Eob) position of the target signal, each of the plurality of error values ​​being an error between an amplitude of the target signal and a level state of modulating the target signal, and the tap coefficient representing a characteristic of a channel formed by the interconnected link;

[0042] Calculate the difference between the Euclidean distance of the original error sequence and the Euclidean distance of the corrected error sequence according to the original error sequence, the tap coefficient, the burst error start Sob position and the burst error end Eob position;

[0043] According to the size of the difference, the target signal after equalization is determined.

[0044] In this solution, based on the original error sequence, combined with the tap coefficient, the burst error start Sob position and the burst error end Eob position, the difference between the Euclidean distance of the original error sequence and the Euclidean distance of the corrected error sequence can be determined. There is no need to calculate the Euclidean distance of the original error sequence, nor is there any need to calculate the Euclidean distance of the corrected error sequence, which simplifies the calculation method and reduces the overhead of computing resources.

[0045] In a possible implementation manner, the equalized target signal is the target signal or the corrected target signal.

[0046] In a possible implementation, the difference ΔDist satisfies the following formula:

[0047]

[0048] Among them, e 1 represents the first error in the original error sequence, e i represents the ith error in the original error sequence, n represents the identifier of the burst error cutoff Eob position, and i=1, 2, ... n, sign is a sign function, representing a tap coefficient.

[0049] In a third aspect, an embodiment of the present application provides a signal equalization device, which is applied to a signal receiving device in a signal transmission system, wherein the signal transmission system includes a signal sending device and the signal receiving device connected to each other through an interconnection link, including:

[0050] A receiving module, receiving a target signal sent by the signal sending device;

[0051] A first determining device is used to determine the coordinate values ​​of the center positions of the decision values ​​of the target signal corresponding to the multiple branch paths respectively according to the amplitudes of the target signal at two adjacent moments, the multiple branch paths are paths when the target level state is transferred at the two adjacent moments, the two adjacent moments include the previous moment and the current moment, and the target level state is the level state after the multiple level states are reduced in dimension;

[0052] a second determining means for determining a center metric value of the target signal at the current moment according to the coordinate value of the center position and the tap coefficient, wherein the center metric value is used to measure the distance between the decision value and the center position, and the tap coefficient represents the characteristics of the channel formed by the interconnected links;

[0053] The third determination device is used to determine the state transition path of the level state transition of the target signal from the starting moment to the current moment based on the central measurement value, the path cumulative measurement value at the previous moment and the tap coefficient, wherein the path cumulative measurement value is used to measure the sum of the Euclidean distances between the amplitude of the target signal and the decision value at different moments.

[0054] According to this solution, through the symmetry of the decision values ​​corresponding to the multiple branch paths, the center position of the decision value corresponding to the branch path can be determined based on the amplitude of the target signal at two adjacent moments. Based on the center position corresponding to the decision value, the center measurement value of the target signal at the current moment is derived, so as to determine the distance between each decision value and the center position, and then the state transition path of the target signal from the starting moment to the current moment can be determined based on the center measurement value and the path cumulative measurement value at the previous moment, so as to complete the equalization of the target signal through the state transition path, wherein the path cumulative measurement can measure the path cumulative measurement value for measuring the sum of the Euclidean distances between the amplitude of the target signal and the decision value at different moments. Moreover, the target level state is the level state after dimensionality reduction, which simplifies the calculation process, reduces the overhead of computing resources and the delay of the equalization process.

[0055] In a possible implementation manner, the third determining device is used to:

[0056] Determine the path center metric value of the target signal at the current moment according to the center metric value, the path cumulative metric value at the previous moment and the tap coefficient, wherein the path center metric value is used to measure the distance from the target signal to the center of the branch path;

[0057] A state transition path for the target signal to perform level state transition from the starting time to the current time is determined according to the path center metric value and the tap coefficient.

[0058] In this way, the center metric value of the path can be determined through the center metric value, and the state transition path can be determined based on the path center metric value and the cumulative metric value of the path at the previous moment. The state transition path can be determined without calculating the Euclidean distance between the amplitude of the target signal and the decision value, which simplifies the method of determining the state transition path and reduces the overhead of computing resources.

[0059] In a possible implementation, the path center metric value of the target signal satisfies the following formula:

[0060] c(tk)=pm(tk-1)+αp(tk);

[0061] Among them, c(tk) represents the path center metric value at time tk, pm(tk-1) represents the path center metric value at time tk-1, α represents the tap coefficient, and p(tk) represents the center metric value at time tk.

[0062] In this way, the path center metric value can be determined only through a simple calculation method, and the state transition path can be determined without the need for complex Euclidean distance calculation, thereby reducing the overhead of computing resources.

[0063] In a possible implementation manner, the third determining device is used to:

[0064] Determine a comparison result by comparing the path center metric value and the tap coefficient;

[0065] Determining a plurality of maximum likelihood paths from the plurality of branch paths according to the comparison result;

[0066] Determine the cumulative metric value of the path at the current moment according to the comparison result;

[0067] The state transition path is determined according to the path accumulated metric value and the multiple maximum likelihood paths.

[0068] In this way, multiple maximum likelihood paths can be determined only by using the path center metric and the tap coefficient, without the need to perform complex Euclidean distance calculations, thus reducing the cost of computing resources.

[0069] In a possible implementation manner, the state transition path is a path with the smallest sum of Euclidean distances among the multiple maximum likelihood paths.

[0070] In a possible implementation manner, the first determining device is configured to:

[0071] Determine, from a plurality of level states, a level state that is closest to the amplitude of the target signal at the current moment;

[0072] Determine, from the multiple level states, a level state that is closest to the amplitude of the target signal at the previous moment;

[0073] Determine a first error between the amplitude of the target signal at the current moment and the level state closest to the amplitude of the target signal at the current moment;

[0074] Determine a second error between the amplitude of the target signal at the previous moment and the level state closest to the amplitude of the target signal at the previous moment;

[0075] The coordinate value of the center position is determined according to the first error, the second error, the level state closest to the amplitude of the target signal at the previous moment, and the level state closest to the amplitude of the target signal at the previous moment.

[0076] In this way, based on the symmetry of the decision values ​​corresponding to the branch paths after dimensionality reduction, the coordinate value of the center position can be determined, thereby simplifying the subsequent maximum likelihood path determination process and reducing the cost of computing resources.

[0077] In a possible implementation, the coordinate value (m, n) of the center position satisfies the following formula:

[0078] m=2*(sign(a+sign(e))+1)-2, n=2*(sign(a'+sign(e'))+1)-2;

[0079] Among them, sign is a sign function, a represents the level state closest to the amplitude of the target signal at the current moment, e represents the first error, a' represents the level state closest to the amplitude of the target signal at the previous moment, e' represents the second error, and sign is a sign function.

[0080] In a possible implementation, the central metric value satisfies the following formula:

[0081] p(tk)=u(tk)-(m+nα);

[0082] Among them, p(tk) represents the center measurement value at time tk, u(tk) represents the amplitude of the target signal at time tk, (m, n) represents the coordinate value of the center position, and α represents the tap coefficient.

[0083] In a fourth aspect, an embodiment of the present application provides a signal equalization device, which is applied to a signal receiving device in a signal transmission system, wherein the signal transmission system includes a signal sending device and the signal receiving device that are communicatively connected via an interconnection link, including:

[0084] A receiving module, used to receive a target signal sent by the signal sending device, wherein the target signal includes amplitudes at different times;

[0085] an error value determination module, configured to determine, when burst error detection is enabled, an original error sequence of a burst error occurring in the target signal, wherein the original error sequence includes a plurality of error values ​​formed by the target signal from a burst error start position Sob to a burst error end position Eob, each of the plurality of error values ​​being an error between an amplitude of the target signal and a level state of modulating the target signal, and the tap coefficient representing a characteristic of a channel formed by the interconnected link;

[0086] A calculation module, configured to calculate a difference between the Euclidean distance of the original error sequence and the Euclidean distance of the corrected error sequence according to the original error sequence, the tap coefficient, the burst error start Sob position and the burst error end Eob position;

[0087] The signal determination module is used to determine the equalized target signal according to the size of the difference.

[0088] In this solution, based on the original error sequence, combined with the tap coefficient, the burst error start Sob position and the burst error end Eob position, the difference between the Euclidean distance of the original error sequence and the Euclidean distance of the corrected error sequence can be determined. There is no need to calculate the Euclidean distance of the original error sequence, nor is there any need to calculate the Euclidean distance of the corrected error sequence, which simplifies the calculation method and reduces the overhead of computing resources.

[0089] In a possible implementation manner, the equalized target signal is the target signal or the corrected target signal.

[0090] In a possible implementation, the difference ΔDist satisfies the following formula:

[0091]

[0092] Among them, e 1 represents the first error in the original error sequence, e i represents the ith error in the original error sequence, n represents the identifier of the burst error cutoff Eob position, and i=1, 2, ... n, sign is a sign function, representing a tap coefficient.

[0093] In a fifth aspect, an embodiment of the present application provides a signal transmission system, the system comprising a signal sending device and a signal receiving device:

[0094] The signal sending device is used to send a target signal to the signal receiving device;

[0095] The signal receiving device is used to execute the method provided in the first aspect, or execute the method provided in the second aspect.

[0096] In a sixth aspect, an embodiment of the present application provides a signal equalization device, including:

[0097] at least one memory for storing a program;

[0098] At least one processor is used to execute the program stored in the memory. When the program stored in the memory is executed, the processor is used to execute the method provided in the first aspect, or execute the method provided in the second aspect.

[0099] In a seventh aspect, an embodiment of the present application provides a signal equalization device, which runs computer program instructions to execute the method provided in the first aspect, or execute the method provided in the second aspect.

[0100] In one example, the device may include a processor, which may be coupled to a memory, read instructions in the memory and execute the method provided in the first aspect according to the instructions, or execute the method provided in the second aspect. The memory may be integrated in a chip or a processor, or may be independent of the chip or the processor.

[0101] In an eighth aspect, an embodiment of the present application provides a computer storage medium, wherein instructions are stored in the computer storage medium. When the instructions are executed on a computer, the computer executes the method provided in the first aspect, or executes the method provided in the second aspect.

[0102] In a ninth aspect, an embodiment of the present application provides a computer program product comprising instructions, which, when executed on a computer, causes the computer to execute the method provided in the first aspect, or to execute the method provided in the second aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0103] Figure 1 is a system architecture diagram of a signal transmission system provided in an embodiment of the present application;

[0104] Figure 2 It is a schematic diagram of an algorithm architecture of a dual signal receiving device in a signal transmission system provided by an embodiment of the present application;

[0105] Figure 3 It is a schematic diagram of an algorithm architecture of another signal receiving device in a signal transmission system provided in an embodiment of the present application;

[0106] Figure 4 It is a flow chart of a signal equalization method provided in an embodiment of the present application;

[0107] Figure 5a It is a schematic diagram of an algorithm architecture of a signal receiving device in a signal equalization algorithm based on a Viterbi sequence provided in an embodiment of the present application;

[0108] Figure 5b It is a schematic diagram of an algorithm architecture of a signal receiving device in another signal equalization algorithm based on a Viterbi sequence provided in an embodiment of the present application;

[0109] Figure 6a It is a schematic diagram of reducing the dimension of a branch path during a state transition of a signal provided by an embodiment of the present application;

[0110] Figure 6b It is a schematic diagram of a decision value in a state transition process of a signal provided by an embodiment of the present application;

[0111] Figure 6c is a schematic diagram of determining a maximum likelihood path provided by an embodiment of the present application;

[0112] Figure 6d is a schematic diagram of a central position of a decision value provided in an embodiment of the present application;

[0113] Figure 7 It is a schematic diagram of simulation results of the bit error rate after signal equalization based on the USSE algorithm provided in an embodiment of the present application;

[0114] Figure 8 is a flow chart of another signal equalization method provided in an embodiment of the present application;

[0115] Figure 9a It is a schematic diagram of an algorithm architecture of a signal receiving device in a signal equalization algorithm based on a non-Viterbi sequence provided in an embodiment of the present application;

[0116] Figure 9b It is a schematic diagram of an algorithm architecture of a signal receiving device in another non-Viterbi sequence-based signal equalization algorithm provided in an embodiment of the present application;

[0117] Fig.10 It is a flowchart of another signal equalization method provided in an embodiment of the present application;

[0118] Fig.11 is a structural schematic diagram of a signal equalization device provided in an embodiment of the present application;

[0119] Fig.12 is a structural schematic diagram of another signal equalization device provided in an embodiment of the present application;

[0120] Fig.13It is a structural diagram of a computing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0121] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0122] In the description of the embodiments of the present application, words such as "exemplary", "for example" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary", "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary", "for example" or "for example" is intended to present related concepts in a concrete way.

[0123] In the description of the embodiments of the present application, the term "and / or" is merely a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B may represent: A exists alone, B exists alone, and A and B exist at the same time. In addition, unless otherwise specified, the term "multiple" means two or more. For example, multiple systems refers to two or more systems, and multiple terminals refers to two or more terminals.

[0124] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "include", "comprises", "has" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0125] The signal transmission system generally includes a signal sending device and a signal receiving device, the signal sending device and the signal receiving device are communicatively connected via an interconnection link, and the signal sending device sends a signal to the signal receiving device via the interconnection link. For example, the signal transmission system may be an optical transmission system, and accordingly, the signal sending device may be an optical transmitter, the signal receiving device may be an optical receiver, and the interconnection link may be an optical link. Alternatively, the signal transmission system may be a wireless transmission system, and accordingly, the signal sending device may be a wireless sending device, the signal receiving device may be a wireless receiving device, and the interconnection link may be a wireless link, wherein the wireless receiving device may be a computer, a router, a switch, and other devices. The signal transmission system may also be a cable transmission system, and accordingly, the interconnection link may be a cable link. The signal transmission system may also be an optoelectronic transmission system, such as, the signal sending device may be a chip, and the signal receiving device may be an optical module.

[0126] In a signal transmission system, the interconnection link includes transmission media and transmission devices. For example, an optical link generally includes optical transmission media such as optical fibers, and may also include optical devices such as optical amplifiers and optical connectors, which is not limited in the embodiments of the present application.

[0127] For example, Figure 1 A schematic structural diagram of a signal transmission system provided in an embodiment of the present application is shown. Figure 1 Take the optical transmission system as an example. The signal transmission system includes a signal sending device 11 and a signal receiving device 12. The signal sending device 11 is connected to the signal receiving device 12 through an interconnection link 13. The signal sending device 11 includes a laser 111, a driver 112 and a modulator 113 connected in sequence, and the signal receiving device 12 includes a photoelectric conversion device (PD) 121, an analog-digital converter (ADC) 122 and a DSP chip 123 connected in sequence. The signal sending device 11 is connected to the signal receiving device 12 through the interconnection link 13, specifically, the modulator 113 is connected to the PD 121 through the interconnection link 13. The optical signal emitted by the laser 111 is driven by the driver 112 and then transmitted to the modulator 113. After the modulator 113 modulates the optical signal using the data to be sent, the modulated optical signal is sent to the signal receiving device 12 through the interconnection link 13, wherein the modulated optical signal carries the data to be sent. After the optical signal is transmitted to the signal receiving device 12, PD 121 converts the optical signal into an electrical signal. The electrical signal converted by PD 121 is an analog electrical signal. ADC 122 performs analog-to-digital conversion on the analog electrical signal to obtain a digital electrical signal. The chip processes the digital electrical signal to restore the data.

[0128] During the signal transmission process, due to the bandwidth limitations of various devices in the signal transmission system, link insertion loss, etc., the signal usually has ISI, which affects the signal quality. In order to ensure that the signal receiving device recovers the correct data from the received signal, the signal receiving device usually uses an equalization algorithm to equalize the signal after receiving the signal to eliminate or weaken the ISI of the signal. The current equalization algorithms include the Feed Forward Equalizer (FFE) algorithm, the Decision Feedback Equalizer (DFE) algorithm, the Maximum Likelihood Sequence Estkmatkon (MLSE) algorithm, the MAP (mapreduce) algorithm, etc. Compared with the FFE algorithm, the DFE algorithm, and the MAP algorithm, the MLSE algorithm has a lower bit error rate (BER) and consumes less resources. Therefore, the MLSE algorithm is usually used to equalize the signal. Among them, the process of equalizing the signal is usually performed by the chip in the signal receiving device.

[0129] With the rapid development of cloud computing, big data, the Internet of Things, artificial intelligence and other related industries, the amount of data has shown an explosive growth. High-speed link technology has become the basic technology for chip interconnection and interface, including electrical interconnection links and optical interconnection links. With the continuous increase in communication rate, the inter-symbol interference (ISI) of the interconnection link in the signal transmission system has become more and more serious, making it increasingly difficult for the bit error rate to meet communication requirements. At present, signal equalization can reduce inter-symbol interference so that the bit error rate meets communication requirements.

[0130] For example, Figure 2The schematic diagram of the architecture of a chip provided by the related art is shown. The chip includes a continuous time linear equalizer (CLTE), an ADC module, an FFE module and a DFE module, a clock data recovery (CDR) module, a least mean square (LMS) module and an MLSE module connected in sequence. The received analog signal is filtered by CLTE to obtain a filtered analog signal, thereby compensating the channel band of the analog signal. The ADC converts the filtered analog signal and converts the filtered signal into a digital signal. Among them, the CDR module can provide a clock signal to the ADC module so that the ADC module outputs a sampled digital signal. Here, the digital signal carries ISI, so the digital signal is equalized by the FFE module to obtain a first equalized signal. Among them, the LMS module is used to provide an equalization coefficient (c_ffe) to the FFE module. There is residual ISI in the first equalized signal. The DFE module re-equalizes the first equalized signal to obtain a second equalized signal (sys, err). At this time, the residual inter-symbol interference in the ISI in the second equalized signal is relatively small, and the bit error rate is also relatively low. The LMD module is also used to provide an equalization coefficient (c_dfe) to the DFE module according to the second equalized signal output by the DFE module, thereby realizing adaptive equalization. The MLSE module performs maximum likelihood sequence estimation based on the equalization coefficient of the DFE module and the first equalized signal to obtain the final data.

[0131] However, the feedback structure of the DFE equalizer will cause the link error to be transmitted, resulting in an increase in the total bit error rate. The SoB and EoB left over after the Precoding technology have become the main sources of link errors, affecting the further improvement of link quality. Although MLSE has a better equalization effect, this technical solution requires branch measurement and addition, comparison and selection operations, which has high computational complexity, large latency, and high power consumption. The processing speed cannot keep up with the real-time changes of the signal, which has a great impact on the low-overhead integration of SerDes. The complexity (chip area and power consumption) is more than 4-5 times that of the DFE solution, and the latency is as long as 80 beats, so it cannot be used in high-density, low-power, low-latency and other usage scenarios.

[0132] For example, Figure 3The schematic diagram of the architecture of a chip provided by the related art is shown. The chip includes an FFE module, a DFE module, an Ultra Simplified Error Correctkon (USEC) module, and a Forward Error Correctkon (FEC) decoding module connected in sequence. The signal received by the FFE module is equalized to obtain an equalized signal dfe_input. At this time, ISI still remains in the signal dfe_input. After the DFE module equalizes the signal dfe_input, an equalized signal dfe_output is obtained. The DFE module also sends the equalized signal dfe_output to the USEC module, and sends the decision level dfe_sliced_data and the equalization coefficient c_dfe of the DFE module to the USEC module. The USEC module includes two types of correction schemes, namely, an error detection and correction scheme based on EoBD detection SoB and an error detection and correction scheme based on SoBD detection EoB. Among them, when the tap coefficient α value is large, the error detection and correction scheme based on EoBD detection SoB is used. When the tap coefficient α value is small, the error detection and correction scheme based on SoBD detection EoB is used. USEC corrects the equalized signal dfe_output according to the decision level dfe_sliced_data and the equalization coefficient c_dfe of the DFE module to obtain soft judgment information and a corrected output sequence. Among them, the soft judgment information includes the error position and error probability. The error probability is the ratio of the decision error information to the distance between two adjacent levels (dlevel). The FEC decoding module uses the error position information to complete the correction of the corrected output sequence, and compares the Euclidean distance with the original sequence. Finally, the final decision sequence is determined according to the sequence with the smaller Euclidean distance. However, under the DFE architecture of USEC, the feedback structure of the equalizer will cause error transmission in the link. There is a high probability that the error transmission does not overflow, resulting in missed detection and loss of error detection and correction performance. This method requires setting threshold parameters, and there is a judgment error caused by an unsatisfactory threshold setting. At the same time, the final Euclidean distance comparison process requires more multipliers and adders, resulting in high power consumption of the device performing signal equalization.

[0133] Based on this, the embodiments of the present application provide a signal equalization method, device, system and storage medium. Among them, the method can determine the center position of the decision value corresponding to the branch path based on the amplitude of the target signal at two adjacent moments through the symmetry of the decision values ​​corresponding to multiple branch paths. Based on the center position corresponding to the decision value, the center measurement value of the target signal at the current moment is derived, so as to determine the distance between each decision value and the center position, and then the state transition path of the level state transition of the target signal from the starting moment to the current moment can be determined based on the center measurement value and the path cumulative measurement value at the previous moment, so as to complete the equalization of the target signal through the state transition path, wherein the path cumulative measurement can measure the path cumulative measurement value for measuring the sum of the Euclidean distances between the amplitude of the target signal and the decision value at different moments. Moreover, the target level state is the level state after dimensionality reduction, which simplifies the calculation process and reduces the overhead of computing resources.

[0134] Next, the signal equalization method provided in the embodiment of the present application is described in detail.

[0135] Figure 4 is a flow chart of a signal equalization method provided in an embodiment of the present application. The signal equalization method provided in an embodiment of the present application can be applied to Figure 1 The signal receiving device in the signal transmission system shown in FIG. Figure 5a and Figure 5b As shown, the signal equalization method provided in the embodiment of the present application can be applied to a USSE module in a chip of a signal receiving device.

[0136] like Figure 4 As shown, the signal equalization method provided in the embodiment of the present application includes S401 to S404.

[0137] S401, receiving a target signal sent by a signal sending device.

[0138] The signal sending device sends the target signal to the signal receiving device through the interconnection link. The target signal is used to carry data. However, since the interconnection link has inter-symbol interference on the target signal, it is necessary to perform equalization processing on the target signal sent by the signal sending device to reduce the bit error rate.

[0139] like Figure 5aAs shown, signal U is a signal sent by a signal sending device through an interconnected link. Here, after receiving signal U, the signal receiving device can also pre-process signal U through other modules, and then transmit the pre-processed signal U to the chip. For example, if the signal U sent by the signal receiving device is an optical signal, the optical signal needs to be converted into an electrical signal, and then the electrical signal is converted into a digital signal before the digital signal is transmitted to the chip. For another example, the signal U sent by the signal receiving device needs to be modulated and processed. Different architectures of signal transmission systems may have different pre-processing methods for signal U, which is not specifically limited in this application.

[0140] In a possible implementation, in order to ensure the accuracy of signal equalization, the signal U may be pre-equalized. Figure 5b As shown, the chip includes a pre-equalization module 510. The pre-equalization processing module is used to perform pre-equalization processing on the signal U' received by the chip to obtain a signal U. Figure 5b As shown, the pre-equalization processing module may include CLTE, ADC, FFE and CDR. Signal U' is an analog signal. CLTE filters the received signal U' to obtain a filtered analog signal, thereby compensating for the channel band of the analog signal. ADC converts the filtered analog signal and converts the filtered signal into a digital signal. Among them, the CDR module can provide a clock signal to the ADC module so that the ADC module outputs the sampled digital signal. Here, the digital signal carries ISI, so after the digital signal is equalized by the FFE module, an equalized signal is obtained. Among them, the LMS module is used to provide an equalization coefficient to the FFE module.

[0141] In a possible implementation, after the signal U is determined, the signal U may be filtered. For example, a 1+α filter is used to filter the signal U. α may represent a characteristic of a channel.

[0142] S402, according to the amplitude of the target signal at two adjacent moments, determine the coordinate values ​​of the center positions of the decision values ​​corresponding to the target signal on multiple branch paths, the multiple branch paths are the paths when the target level state is transferred at two adjacent moments, the two adjacent moments include the previous moment and the current moment, and the target level state is the level state after dimensionality reduction of multiple level states.

[0143] The target signal has different amplitudes at different moments. For example, the amplitude of signal U changes at different moments. Exemplarily, the amplitudes of signal U at moments t1, t2, ..., tk, ..., tn can be expressed as u(t1), u(t2), u(t3), ..., u(tk), ..., u(tn), respectively. Here, two adjacent moments refer to the previous moment and the current moment. The previous moment and the current moment are relative. For example, if moment tk-1 is the previous moment, then tk is the current moment; tk is the previous moment, and tk+1 is the current moment. Wherein, k=1, 2, 3...n.

[0144] At different times, the level state of the modulated target signal is different. The target signal can form a branch path from one level state to another level state. For example, Figure 6a As shown, at each moment, there are four levels of the modulated target signal, and there are 16 branch paths 60 for the target signal to transfer from the level state at the moment tk-1 to the level state at the moment tk. Each branch path corresponds to a decision value. The decision value is used to determine the Euclidean distance from the level state at the previous moment to the level state at the current moment. The decision value of each path is determined based on the tap coefficient of the channel and the level state at the previous moment and the level state at the current moment. For example, Figure 6b As shown, BM16(11) represents the decision value of the branch path from the level state -3 at time tk-1 to the level state -3 at time tk, where BM16(11) = -3-3α. BM16(12) represents the decision value of the branch path from the level state -1 at time tk-1 to the level state -3 at time tk, BM16(12) = -1-3α, and so on, BM16(13) = 1-3α, BM16(14) = 3-3α, BM16(21) = -3-α, BM16(22) = -1-α, BM16(23) = 1-α, BM16(24) = 3-α, BM16(31) = -3+α, BM16(32) = -1+α, BM16(33) = 1+α, BM16(34) = 3+α, BM16(41) = -3+3α, BM16(42) = -1+3α, BM16(43) = 1+3α, BM16(44) = 3+3α.

[0145] The target level state is the level state after the multiple level states are reduced in dimension. In the embodiment of the present application, the target level state at time tk is the level state that is closest to the amplitude of the target signal at time tk among the multiple level states. For example, the amplitude of the target signal is -0.8, and the multiple level states are -3, -1, 1, 3. Then, the target level states are -1 and 1. The target level states at two adjacent moments are determined respectively according to the amplitude of the target signal at two adjacent moments. For example, Figure 6aAs shown, the amplitude of the target signal at time tk is -1.2, and the amplitude at tk-1 is -0.8. Then, at time tk, the target level states are -3 and -1, respectively, and at time tk-1, the target level states are -1 and 1.

[0146] When the level state is reduced in dimension, the branch paths are also reduced in dimension. In the embodiment of the present application, the multiple branch paths are the paths when the target level state is transferred at two adjacent moments, that is, the branch paths after dimension reduction. Figure 6a As shown, there are four branch paths for the target signal to transfer from the target level state at time tk-1 to the target level state at time tk, that is, there are four branch paths after dimensionality reduction, namely, branch path L11, branch path L12, branch path L21 and branch path L22. Figure 6b As shown, the decision value BM4(11) corresponding to the branch path L11 is BM4(11) = -3-α, the decision value BM4(12) corresponding to the branch path L12 is BM4(12) = -1-α, the decision value BM4(21) corresponding to the branch path L21 is BM4(21) = -3+α, and the decision value BM(22) corresponding to the branch path L22 is BM4(22) = -1+α.

[0147] The center position refers to the center position of the decision value, and the center position can be expressed as m+nα. Wherein, (m, n) is the coordinate value of the center position. In the embodiment of the present application, the step of determining the coordinate value of the center position shown in step 402 may specifically include the following steps: first, determine from multiple level states, the level state closest to the amplitude of the target signal at the current moment; and determine from multiple level states, the level state closest to the amplitude of the target signal at the previous moment; then, determine the first error between the amplitude of the target signal at the current moment and the level state closest to the amplitude of the target signal at the current moment; determine the second error between the amplitude of the target signal at the previous moment and the level state closest to the amplitude of the target signal at the previous moment; finally, determine the coordinate value of the center position according to the first error, the second error, the level state closest to the amplitude of the target signal at the previous moment, and the level state closest to the amplitude of the target signal at the previous moment.

[0148] The closest level state refers to the level state with the smallest error with the amplitude of the target signal. For example, the amplitude of the target signal at the current moment is -0.8, and the multiple level states are -3, -1, 1, and 3, then the level state closest to the target signal at the current moment is -1.

[0149] In the embodiment of the present application, the coordinate value (m, n) of the center position satisfies the following formula (1):

[0150] m=2*(sign(a+sign(e))+1)-2, n=2*(sign(a'+sign(e'))+1)-2 (1)

[0151] Wherein, sign is a sign function, a represents the level state closest to the amplitude of the target signal at the current moment, e represents the first error, a' represents the level state closest to the amplitude of the target signal at the previous moment, and e' represents the second error.

[0152] S403, determining the center metric value of the target signal at the current moment according to the coordinate value of the center position and the tap coefficient, the center metric value is used to measure the distance between the decision value and the center position, and the tap coefficient represents the characteristics of the channel formed by the interconnected links.

[0153] The central measurement value satisfies the following formula (2):

[0154] p=u-(m+nα) (2)

[0155] Among them, p represents the center measurement value at the current moment, u represents the amplitude of the target signal at the current moment, (m, n) represents the coordinate value of the center position, and α represents the tap coefficient.

[0156] S404, determining the state transition path of the target signal from the starting moment to the current moment according to the center metric value, the path cumulative metric value at the previous moment and the tap coefficient, wherein the path cumulative metric value is used to measure the sum of the Euclidean distances between the amplitude of the target signal and the decision value at different moments.

[0157] The path cumulative metric value is used to measure the sum of the Euclidean distances between the amplitude of the target signal and the decision value at different times, that is, to measure the sum of the Euclidean distances corresponding to the branch paths that the target signal passes through during the state transition from the starting time to the current time. Among them, the Euclidean distance refers to the Euclidean distance between the decision value corresponding to the branch path and the amplitude of the signal. For example, Figure 6aAs shown, the level states of the path through which the target signal transitions from time tk-1 to time tk+2 are respectively -1, -3, -1, and 1. Thus, there are three branch paths, namely, the branch path L11 formed from the level state -1 at time tk-1 to the level state -3 at time tk, the branch path L31 formed from the level state -3 at time tk to the level state -1 at time tk+1, and the branch path L41 formed from the level state -1 at time tk+1 to the level state 1 at time tk+2. Among them, the Euclidean distance corresponding to the branch path L11 is the Euclidean distance between the decision value -3-α corresponding to the branch path and the amplitude of the target signal at time tk. The Euclidean distance corresponding to the branch path L31 is the Euclidean distance between the decision value -1-3α corresponding to the branch path and the amplitude of the target signal at time tk+1. The Euclidean distance corresponding to the branch path L41 is the Euclidean distance between the decision value 1-α corresponding to the branch path and the amplitude of the target signal at time tk+2. Then, the cumulative metric value of the path at time tk+2 is the sum of the Euclidean distance corresponding to the branch path L11, the Euclidean distance corresponding to L31, and the Euclidean distance corresponding to L41.

[0158] The state transition path is the path along which the target signal transitions from the start time to the current time.

[0159] According to the center metric value, the cumulative path metric value of the previous moment and the tap coefficient, the path center metric value of the target signal at the current moment is determined. The path center metric value is used to measure the distance from the target signal to the center of the branch path; according to the path center metric value and the tap coefficient, the state transition path for the target signal to perform level state transition from the starting moment to the current moment is determined. Figure 6a As shown, the path formed by branch path L11, branch path L31 and branch path L41 is a state transition path, that is, when the target signal transitions from time tk-1 to time tk+2, the level states of the modulation of the target signal are -1, -3, -1, and 1 respectively.

[0160] In an embodiment of the present application, the step of determining the state transition path may include the following manner: first, according to the center metric value, the cumulative path metric value at the previous moment, and the tap coefficient, the path center metric value of the target signal at the current moment is determined, and the path center metric value is used to measure the distance from the target signal to the center of the branch path. Then, according to the path center metric value and the tap coefficient, the state transition path for the target signal to perform level state transition from the starting moment to the current moment is determined.

[0161] The path center metric is used to measure the distance from the target signal to the center of the branch path. Taking time tk as the current time, the path center metric c(tk) of the target signal at the current time satisfies the following formula (3):

[0162] c(tk)=pm(tk-1)+αp(tk) (3)

[0163] Among them, c(tk) represents the path center metric value at the current moment, pm(tk-1) represents the path center metric value at the previous moment, α represents the tap coefficient, and p(tk) represents the center metric value at the current moment. Here, the tk moment and tk-1 moment are only used to distinguish the current moment from the previous moment. This formula can be applied to the calculation of the path center metric value at any moment.

[0164] In an embodiment of the present application, when determining the path center metric value, the specific steps for determining the state transition path include: first, determining the comparison result by comparing the path center metric value and the tap coefficient; then, based on the comparison result, determining multiple maximum likelihood paths from multiple branch paths; then, based on the comparison result, determining the path cumulative metric value at the current moment; finally, determining the state transition path based on the path cumulative metric value and the multiple maximum likelihood paths.

[0165] Among them, each target level state to the current moment corresponds to a maximum likelihood path. The judgment method of the maximum likelihood path to different target level states is different. For the target level state with a smaller value at the current moment, compare the size between the path center metric value and the negative number of the tap coefficient, that is, compare the size of c and -α. If c<-α, the branch path formed by the target level state with a smaller value at the previous moment to the target level state at the current moment is the maximum likelihood path. Otherwise, the branch path formed by the target level state with a larger value at the previous moment to the target level state at the current moment is the maximum likelihood path. For the target level state with a larger value at the current moment, compare the size between the path center metric value and the tap coefficient, that is, compare the size of c and α. If c>α, the branch path formed by the target level state with a larger value at the previous moment to the target level state at the current moment is the maximum likelihood path. Otherwise, the branch path formed by the target level state with a smaller value at the previous moment to the target level state at the current moment is the maximum likelihood path.

[0166] For example, Figure 6c As shown, the path of the signal U from time tk-1 to time tk includes four branch paths, including a branch path L11 formed from the level state -1 at time tk-1 to the level state -3 at time tk, a branch path L12 formed from the level state -1 at time tk-1 to the level state -1 at time tk, a branch path L21 formed from the level state 1 at time tk-1 to the level state -3 at time tk, and a branch path L22 formed from the level state 1 at time tk-1 to the level state -1 at time tk.

[0167] Among them, at time tk-1, the target level states include -1 and 1, level state -1 is the target level state with a smaller value at time tk-1, recorded as high bit 0, and level state 1 is the target level state with a larger value at time tk-1, recorded as low bit 1. The branch path formed from the high bit at time tk-1 to the high bit at time tk is recorded as BM00, that is, branch path L11, and the branch path formed from the low bit at time tk-1 to the high bit at time tk is BM10, that is, branch path L21; for the high bit in BM4, compare the size of c and -α. If c<-α, select the branch path represented by BM00 as the maximum likelihood path, otherwise select the branch path represented by BM10 as the maximum likelihood path;

[0168] At time tk, the target level states include -3 and -1. Level state -3 is the target level state with a smaller value at time tk, recorded as high bit 0, and level state -1 is the target level state with a larger value at time tk, recorded as low bit 1. The branch path formed from the high bit at time tk-1 to the low bit at time tk is recorded as BM01, that is, branch path L12; the branch path formed from the low bit at time tk-1 to the low bit at time tk is BM11, that is, branch path L22. For the low bit in BM4, compare the size of c and α. If c>α, select the branch path represented by BM11 as the maximum likelihood path, otherwise select the branch path represented by BM01 as the maximum likelihood path.

[0169] After determining multiple maximum likelihood paths, the path cumulative metric value at the current moment is determined according to the comparison result, and the state transition path is determined according to the path cumulative metric value and the multiple maximum likelihood paths.

[0170] For different branch paths, the path cumulative metric values ​​are different. For example, Figure 6c As shown, if the maximum likelihood path is the branch path BM00, the path cumulative metric pm(tk) at the current time tk is =p(tk)+α. If the maximum likelihood path is the branch path BM01, the path cumulative metric pm(tk) at the current time tk is =p(tk)+c. If the maximum likelihood path is the branch path BM10, the path cumulative metric pm(tk) at the current time tk is =p(tk)-c. If the maximum likelihood path is the branch path BM11, the path cumulative metric pm(tk) at the current time tk is =p(tk)-α.

[0171] In the embodiment of the present application, when the time tk is the current time, the path cumulative metric value pm(tk) at the current time satisfies the following formula (4):

[0172]

[0173] Among them, p represents the center metric value at the current moment, and c represents the cumulative path metric value at the current moment.

[0174] According to the sign value of the path cumulative metric pm[t] at the current moment, the final maximum likelihood path is determined from multiple maximum likelihood paths. The final maximum likelihood path is selected according to the sign of pm(tk), and then the decision value of the starting moment of the state transition path is output according to the final maximum likelihood path. If pm(tk) is negative, the maximum likelihood path of the target level state with a smaller value at the current moment is selected as the final maximum likelihood path. If pm(tk) is positive, the maximum likelihood path of the target level state with a larger value at the current moment is selected as the final maximum likelihood path.

[0175] Based on the above solution, a system link simulation test was conducted on 16 different real channels, and the bit error rates (BER) of DFE, traditional MLSE and the simplified equalization algorithm (USSE) based on Viterbi sequence estimation in this embodiment were compared. Figure 7 As shown, for different channels, the results of the embodiment of the present application are similar to those of the traditional MLSE, and are about one order of magnitude higher than the results of the DFE, indicating that the algorithm performance of the embodiment of the present application is comparable to that of the traditional MLSE. However, compared with the traditional MLSE algorithm, the embodiment of the present application can reduce the overhead of multipliers, adders, and comparators, and the algorithm complexity is reduced, thereby reducing the delay of signal transmission and the overhead of computing resources.

[0176] In this way, on the basis of dimensionality reduction, the maximum likelihood path can be determined without calculating the Euclidean distance between each branch path and the signal. Only the symmetry between the decision values ​​can be used to introduce the center position, thereby obtaining the path center measurement value through a simple calculation method. By comparing the relationship between the path center measurement value and the tap coefficient, the maximum likelihood path can be determined, thereby reducing the algorithm delay and the overhead of computing resources.

[0177] In the above example process, the Euclidean distance is not directly calculated, but the maximum likelihood path is determined only by comparing the path center metric and α. In order to prove that the scheme of determining the maximum likelihood path in this scheme can reduce the cost of computing resources, the derivation process of this scheme is described below.

[0178] First, according to the calculation formula of the central metric value p = u-(m+nα), it can be known that the amplitude of signal U is u = p+(m+nα); then, substitute the amplitude of signal U and the simplified BM4(ij) into the calculation formula of the Euclidean distance. Among them, the Euclidean distance between signal U and BM4 is X = (u-BM4(ij)) 2 .

[0179] After calculating the Euclidean distance, the common terms in the Euclidean distance are eliminated respectively, thereby obtaining the simplified Euclidean distance corresponding to each BM4. Figure 6d Taking the BM4 after dimensionality reduction as an example, the simplified BM4(11) = -1-α, the simplified BM4(12) = 1-α, the simplified BM4(21) = -1+α, and the simplified BM4(12) = 1+α. In this way, the Euclidean distance between the decision value BM4(11) and the signal U is α+(1+α)p, the Euclidean distance between the decision value BM4(12) and the signal U is -α-(1-α)p, the Euclidean distance between the decision value BM4(21) and the signal U is -α+(1-α)p, and the Euclidean distance between the decision value BM4(22) and the signal U is α-(1+α)p.

[0180] Based on the simplified Euclidean distance and the cumulative metric of the path at the previous moment, the decision criterion of the maximum likelihood path is simplified, so that the maximum likelihood path can be determined only by comparing the path center metric c and the tap coefficient α.

[0181] For example, Figure 6c As shown, for branch path BM00 and branch path BM10, when the sum of the path cumulative metric value at the current moment and the Euclidean distance corresponding to branch path BM00 is less than the Euclidean distance corresponding to branch path BM10, the maximum likelihood path is branch path BM00 in branch path BM00 and branch path BM10. Among them, the sum of the path cumulative metric value at the previous moment and the Euclidean distance corresponding to branch path BM00 can be expressed as pm[tk-1]+(α+(1+α)p), and the Euclidean distance corresponding to branch path BM10 is -α+(1-α)p, then when pm[tk-1]+(α+(1+α)p)<-α+(1-α)p, the maximum likelihood path is branch path BM00, otherwise, the maximum likelihood path is branch path BM10. After simplifying the inequality pm[tk-1]+(α+(1+α)p)<-α+(1-α)p, the decision condition of the maximum likelihood path is obtained, that is, c<-α, the maximum likelihood path is the branch path BM00, that is, the branch path L11; c>-α, the maximum likelihood path is the branch path BM10, that is, the branch path L21.

[0182] For branch paths BM01 and BM11, when the sum of the path cumulative metric at the current moment and the Euclidean distance corresponding to branch path BM01 is less than the Euclidean distance corresponding to branch path BM11, the maximum likelihood path is branch path BM01 in branch path BM01 and branch path BM11. Among them, the sum of the path cumulative metric at the previous moment and the Euclidean distance corresponding to branch path BM01 can be expressed as pm[tk-1]-α-(1-α)p, and the Euclidean distance corresponding to branch path BM11 is α-(1+α)p. Then when pm[tk-1]-α-(1-α)p<α-(1+α)p, the maximum likelihood path is branch path BM01, otherwise, the maximum likelihood path is branch path BM11. After simplifying the inequality pm[tk-1]-α-(1-α)p<α-(1+α)p, the decision condition of the maximum likelihood path is obtained, that is, when c<α, the maximum likelihood path is the branch path BM01, that is, the branch path L12, and when c>α, the maximum likelihood path is the branch path BM11, that is, the branch path L22.

[0183] According to the above derivation process, it can be seen that two maximum likelihood paths can be determined from BM4 only by comparing the path center metric value c and the tap coefficient α. The operation method is simple and there is no need to determine the maximum likelihood path by calculating the Euclidean distance, which reduces the overhead of computing resources.

[0184] The above is a signal equalization method based on the Viterbi algorithm provided in the embodiment of the present application. Next, a signal equalization algorithm based on non-Viterbi provided in the embodiment of the present application is described in detail.

[0185] Figure 8 is a flow chart of a signal equalization method provided in an embodiment of the present application. The signal equalization method provided in an embodiment of the present application can be applied to Figure 1 The signal receiving device in the signal transmission system shown in FIG. 4 is a signal receiving device in the signal transmission system shown in FIG. 4 . For example, the signal equalization method provided in the embodiment of the present application can be applied to Figure 9a and Figure 9b The USSE module in the chip shown.

[0186] like Figure 8 As shown, the signal equalization method provided in the embodiment of the present application may include S801 to S804.

[0187] S801, receiving a target signal sent by a signal sending device, where the target signal includes amplitudes at different times.

[0188] The signal sending device sends the target signal to the signal receiving device through the interconnection link. The target signal is used to carry data. However, since the interconnection link has inter-symbol interference on the target signal, it is necessary to perform equalization processing on the target signal sent by the signal sending device to reduce the bit error rate.

[0189] like Figure 9a As shown, signal U is a signal sent by a signal sending device through an interconnected link. Here, after receiving signal U, the signal receiving device can also pre-process signal U through other modules, and then transmit the pre-processed signal U to the chip. For example, if the signal U sent by the signal receiving device is an optical signal, the optical signal needs to be converted into an electrical signal, and then the electrical signal is converted into a digital signal before the digital signal is transmitted to the chip. For another example, the signal U sent by the signal receiving device needs to be modulated and processed. Different architectures of signal transmission systems may have different pre-processing methods for signal U, which is not specifically limited in this application.

[0190] In a possible implementation, in order to ensure the accuracy of signal equalization, the signal U may be pre-equalized. Figure 9b As shown, the chip includes a pre-equalization module 510. The pre-equalization processing module is used to perform pre-equalization processing on the signal U' received by the chip to obtain a signal U. Figure 9b As shown, the pre-equalization processing module may include CLTE, ADC, FFE and CDR. Signal U' is an analog signal. CLTE filters the received signal U' to obtain a filtered analog signal, thereby compensating for the channel band of the analog signal. ADC converts the filtered analog signal and converts the filtered signal into a digital signal. Among them, the CDR module can provide a clock signal to the ADC module so that the ADC module outputs the sampled digital signal. Here, the digital signal carries ISI, so after the digital signal is equalized by the FFE module, an equalized signal is obtained. Among them, the LMS module is used to provide an equalization coefficient to the FFE module.

[0191] S802, when burst error detection is started, determine the original error sequence of the target signal where a burst error occurs, the original error sequence includes multiple error values ​​of the target signal from the burst error start position Sob to the burst error end position Eob, each of the multiple error values ​​is the error between the amplitude of the target signal and the level state of the modulated target signal.

[0192] After receiving the signal, the chip will perform burst error detection. The chip includes a burst error detection module for burst error detection, such as Figure 9a The Start of Burst-error Detection (SoBD) module and the End of Burst-error Detection (EoBD) module are shown, so as to perform SoBD burst error detection and / or EoBD burst error detection during the signal equalization process.

[0193] The target signal forms multiple error values ​​from the Sob position to the Eob position, and each of the multiple error values ​​is the error between the amplitude of the target signal and the level state of the modulated target signal. The level state of the modulated target signal may refer to the level state that is closest to the amplitude of the target signal among the multiple level states. For example, the level state of the target signal adjusted at each moment includes multiple, namely -3, -1, 1 and 3. Among them, the amplitude of the target signal at the current moment is -0.8, then the level state of the modulated target signal is -1. After the burst error detection module detects the target signal, it sends the original error sequence to the USSE module.

[0194] The Sob position refers to the position where the amplitude of the target signal begins to change suddenly and significantly, and the Eob position refers to the position where the amplitude of the target signal ends changing significantly.

[0195] S803, calculating the difference between the Euclidean distance of the original error sequence and the Euclidean distance of the corrected error sequence according to the original error sequence, wherein the tap coefficient represents the characteristics of the channel formed by the interconnected links.

[0196] The corrected error sequence refers to the error between the level state of the corrected target signal and the modulated target signal of the target signal after the target signal is corrected.

[0197] In the embodiment of the present application, the difference ΔDist between the Euclidean distance of the original error sequence and the Euclidean distance of the corrected error sequence satisfies the following formula (5):

[0198] ΔDist=f(e i ) (5)

[0199] Among them, f(e i ) represents the i-th error e in the original error sequence i Related functions.

[0200] Next, the derivation process of the above formula (5) is described in detail.

[0201] Euclidean distance d of the original error sequence 1 The following formula (6) is satisfied:

[0202]

[0203] Among them, e i Represents the i-th error in the original error sequence, i=1, 2, 3, ..., n, wherein 1 represents the identifier of the burst error start Sob position, and n represents the identifier of the burst error end Eob position.

[0204] The Euclidean distance d of the corrected error sequence 2 The following formula (7) is satisfied:

[0205]

[0206] Among them, E i Represents the i-th error in the original error sequence, i = 1, 2, 3, ..., n.

[0207] In the case where the burst error detection is SoBD burst error detection, the i-th corrected error E in the corrected error sequence i The following formula (8) is satisfied:

[0208]

[0209] Among them, e 1 represents the first error in the original error sequence, e i represents the i-th error in the original error sequence, n represents the identifier of the burst error cutoff Eob position, and i=1, 2, ... n, sign is the sign function, and α represents the tap coefficient.

[0210] In some embodiments, when the burst error detection is a SoBD burst error detection, the i-th corrected error E in the corrected error sequence i The following formula (9) is satisfied:

[0211]

[0212] Among them, e 1 represents the first error in the original error sequence, e i represents the i-th error in the original error sequence, n represents the identifier of the burst error cutoff Eob position, and i=1, 2, ... n, sign is the sign function, and α represents the tap coefficient.

[0213] The difference ΔDist between the Euclidean distance of the original error sequence and the Euclidean distance of the corrected error sequence satisfies the following formula (10):

[0214]

[0215] According to the above formulas (6) to (9), formula (10) can be simplified so that the difference ΔDist is the i-th error e in the original error sequence i Related functions.

[0216] As a possible implementation method, after simplification, the difference ΔDist satisfies the following formula (11):

[0217]

[0218] Among them, e 1 represents the first error in the original error sequence, e i represents the i-th error in the original error sequence, n represents the identifier of the burst error cutoff Eob position, and i=1, 2, ... n, sign is the sign function, and α represents the tap coefficient.

[0219] Here, formula (11) only represents a calculation formula for the difference ΔDist obtained by a simplification method, and the calculation formula for the difference ΔDist can also be obtained by simplifying in other simplification methods. The embodiment of the present application does not specifically limit the method for simplifying formula (10).

[0220] like Fig.10 As shown, the flowchart of non-Viterbi sequence estimation implemented by the above formula (11) is shown. 1 To e n Represents n error values ​​in the original error sequence. The overhead of multipliers, adders and comparators are all reduced. Taking PAM4 as an example, compared with the conventional algorithm, there is no need to calculate the difference in the Euclidean distance between the original error sequence and the corrected error sequence. The solution provided by the embodiment of the present invention can reduce the overhead of multipliers, adders and comparators, greatly reducing the delay and overhead of the algorithm.

[0221] S804: Determine the equalized target signal according to the difference.

[0222] In the embodiment of the present application, the equalized signal is the original target signal, or the corrected target signal.

[0223] If the difference is greater than or equal to 0, then the correction of the target signal is invalid, and the target signal can be output. If the difference is less than 0, then the correction of the target signal is valid, and the corrected target signal is output.

[0224] It should be noted that the original error sequence, the corrected error sequence, and the corrected target signal involved in the embodiments of the present application are all pre-calculated by the decision module.

[0225] Based on the same concept as the embodiment of the method of the present application, the embodiment of the present application also provides a signal equalization device. The signal equalization device includes several modules, each of which is used to execute each step in the personal information identification method provided in the embodiment of the present application, and the division of the modules is not limited here. The technicians in the relevant field can clearly understand that in practical applications, the various steps in the signal equalization method provided in the embodiment of the present application can be assigned to different modules as needed, that is, the internal structure of the device is divided into different modules to complete all or part of the functions described above. Each module in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more modules can be integrated in one unit, and the above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of each module are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present application. The specific working process of the module in the above-mentioned device can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0226] For example, the signal equalization device is used to perform Figure 4 The signal equalization method provided in the corresponding embodiment, Fig.11 Schematic diagram of the structure of the signal equalization device provided in the embodiment of the present application. The signal equalization device provided in the embodiment of the present application can be applied to Figure 1 The signal receiving device in the signal transmission system shown in FIG. Figure 5a and Figure 5b As shown, the signal equalization device provided in the embodiment of the present application can be applied to the USSE module in the chip of the signal receiving device. Fig.11 As shown, the signal equalization device provided in the embodiment of the present application includes:

[0227] A receiving module 1101 receives a target signal sent by a signal sending device;

[0228] The first determination module 1102 is used to determine the coordinate values ​​of the center positions of the decision values ​​of the target signal corresponding to each of the multiple branch paths according to the amplitude of the target signal at two adjacent moments, the multiple branch paths are paths when the target level state is transferred at two adjacent moments, the two adjacent moments include the previous moment and the current moment, and the target level state is the level state after the multiple level states are reduced in dimension;

[0229] A second determination module 1103 is used to determine a center metric value of the target signal at a current moment according to the coordinate value of the center position and the tap coefficient, where the center metric value is used to measure the distance between the decision value and the center position, and the tap coefficient represents a characteristic of a channel formed by the interconnected links;

[0230] The third determination module 1104 is used to determine the state transition path of the level state transition of the target signal from the starting moment to the current moment based on the central measurement value, the path cumulative measurement value at the previous moment and the tap coefficient, wherein the path cumulative measurement value is used to measure the sum of the Euclidean distances between the amplitude of the target signal and the decision value at different moments.

[0231] In a possible implementation manner, the third determining module is configured to:

[0232] Determine the path center metric value of the target signal at the current moment according to the center metric value, the path cumulative metric value at the previous moment, and the tap coefficient. The path center metric value is used to measure the distance from the target signal to the center of the branch path.

[0233] According to the path center metric value and the tap coefficient, a state transition path for the target signal to perform level state transition from the starting time to the current time is determined.

[0234] 16. The device according to claim 15, characterized in that the path center metric value of the target signal satisfies the following formula:

[0235] c(tk)=pm(tk-1)+αp(tk);

[0236] Among them, c(tk) represents the path center metric value at time tk, pm(tk-1) represents the path center metric value at time tk-1, α represents the tap coefficient, and p(tk) represents the center metric value at time tk.

[0237] In a possible implementation manner, the third determining module is configured to:

[0238] Determine a comparison result by comparing the path center metric value and the tap coefficient;

[0239] According to the comparison result, a plurality of maximum likelihood paths are determined from the plurality of branch paths;

[0240] According to the comparison result, the cumulative metric value of the path at the current moment is determined;

[0241] A state transition path is determined according to the path accumulated metric value and the multiple maximum likelihood paths.

[0242] In a possible implementation, the state transition path is a path with the smallest sum of Euclidean distances among multiple maximum likelihood paths.

[0243] In a possible implementation manner, the first determining module is configured to:

[0244] Determine, from multiple level states, a level state that is closest to the amplitude of the target signal at the current moment;

[0245] Determine, from a plurality of level states, a level state that is closest to the amplitude of the target signal at a previous moment;

[0246] Determine a first error between the amplitude of the target signal at the current moment and a level state closest to the amplitude of the target signal at the current moment;

[0247] Determine a second error between the amplitude of the target signal at a previous moment and a level state closest to the amplitude of the target signal at the previous moment;

[0248] The coordinate value of the center position is determined according to the first error, the second error, the level state closest to the amplitude of the target signal at the previous moment, and the level state closest to the amplitude of the target signal at the previous moment.

[0249] In a possible implementation, the coordinate values ​​(m, n) of the center position satisfy the following formula: m=2*(sign(a+sign(e))+1)-2, n=2*(sign(a'+sign(e'))+1)-2;

[0250] Among them, sign is the sign function, a represents the level state closest to the amplitude of the target signal at the current moment, e represents the first error, a' represents the level state closest to the amplitude of the target signal at the previous moment, e' represents the second error, and sign is the sign function.

[0251] In a possible implementation, the central metric value satisfies the following formula: p(tk)=u(tk)-(m+nα);

[0252] Among them, p(tk) represents the center measurement value at time tk, u(tk) represents the amplitude of the target signal at time tk, (m, n) represents the coordinate value of the center position, and α represents the tap coefficient.

[0253] According to the embodiment of the present application, according to this scheme, through the symmetry of the decision values ​​corresponding to the multiple branch paths, the center position of the decision value corresponding to the branch path can be determined based on the amplitude of the target signal at two adjacent moments. Based on the center position corresponding to the decision value, the center measurement value of the target signal at the current moment is derived, so as to determine the distance between each decision value and the center position, and then the state transition path of the level state transition of the target signal from the starting moment to the current moment can be determined based on the center measurement value and the path cumulative measurement value at the previous moment, so as to complete the equalization of the target signal through the state transition path, wherein the path cumulative measurement can measure the path cumulative measurement value for measuring the sum of the Euclidean distances between the amplitude of the target signal and the decision value at different moments. Moreover, the target level state is the level state after dimensionality reduction, which simplifies the calculation process, reduces the overhead of computing resources and the delay of the equalization process.

[0254] In another exemplary embodiment, the signal equalization device is used to perform Figure 8 The signal equalization method provided in the corresponding embodiment, Fig.12 Schematic diagram of the structure of the signal equalization device provided in the embodiment of the present application. The signal equalization device provided in the embodiment of the present application can be applied to Figure 1 The signal receiving device in the signal transmission system shown in FIG. Figure 9a and Figure 9b As shown, the signal equalization device provided in the embodiment of the present application can be applied to the USSE module in the chip of the signal receiving device. Fig.12 As shown, the signal equalization device provided in the embodiment of the present application includes:

[0255] A receiving module 1201 is used to receive a target signal sent by a signal sending device, where the target signal includes amplitudes at different times;

[0256] The error value determination module 1202 is used to determine the original error sequence of the target signal having a burst error when the burst error detection is started, the original error sequence includes a plurality of error values ​​formed by the target signal from the burst error start position Sob to the burst error end position Eob, each of the plurality of error values ​​is an error between the amplitude of the target signal and the level state of the modulated target signal, and the tap coefficient represents the characteristics of the channel formed by the interconnected link;

[0257] A calculation module 1203 is used to calculate the difference between the Euclidean distance of the original error sequence and the Euclidean distance of the corrected error sequence according to the original error sequence, the tap coefficient, the burst error start position Sob and the burst error end position Eob;

[0258] The signal determination module 1204 is used to determine the equalized target signal according to the size of the difference.

[0259] In a possible implementation manner, the equalized target signal is the target signal or the corrected target signal.

[0260] In a possible implementation, the difference ΔDist satisfies the following formula:

[0261]

[0262] Among them, e 1 represents the first error in the original error sequence, e i represents the i-th error in the original error sequence, n represents the identifier of the burst error cutoff Eob position, and i=1, 2, ... n, sign is the sign function, and represents the tap coefficient.

[0263] According to an embodiment of the present application, based on the original error sequence, combined with the tap coefficient, the burst error start Sob position and the burst error end Eob position, the difference between the Euclidean distance of the original error sequence and the Euclidean distance of the corrected error sequence can be determined. There is no need to calculate the Euclidean distance of the original error sequence, nor is there any need to calculate the Euclidean distance of the corrected error sequence, which simplifies the calculation method and reduces the overhead of computing resources.

[0264] Based on the same concept as the method embodiment of the present application, the embodiment of the present application further provides a computing device. The computing device may be a signal sending device or a signal receiving device.

[0265] Fig.13 It is a structural diagram of a computing device provided in an embodiment of the present application.

[0266] like Fig.13 As shown, computing device 1300 includes a processor 1301 , a memory 1302 , and a communication interface 1303 .

[0267] The processor 1301 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.

[0268] Among them, the non-volatile memory can be a read-only memory (ROM), a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable programmable read-only memory (EEPROM) or a flash memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous connection dynamic random access memory (SLDRAM) and direct memory bus random access memory (DR RAM).

[0269] For example, a computer program may be stored in the memory 1302, and the processor 1301 implements the steps in the above method embodiment when executing the computer program. Alternatively, the processor 1301 implements the functions of each module in the above device embodiment when executing the computer program. For example, the computer program may be divided into one or more modules / units, and the one or more modules / units may be a series of computer program instruction segments that can perform specific functions. The one or more modules / units are stored in the memory 1302 and executed by the processor 1301 to complete the present application. For example, a computer program may be divided into multiple modules, such as the modules in the device described above.

[0270] The communication interface 1303 is used to send and receive data, for example, to send data processed by the processor 1301 to other computing devices, or to receive data sent by other computing devices.

[0271] Of course, to simplify, Fig.13Only some of the components of the computing device 1300 related to the present application are shown, and components such as buses, input / output interfaces, etc. are omitted. In addition, according to specific application situations, the computing device 1300 may also include any other appropriate components. In addition, the computing device may be a desktop computer, a notebook, a palm computer, a cloud server, and other computing devices. Those skilled in the art will understand that Fig.13 This is only an example of the computing device 1300 and does not constitute a limitation of the computing device. It may include more or fewer components than shown in the figure, or combine certain components, or different components. For example, the computing device may also include an input device, an output device, a network access device, a bus, etc. For example, the input device may be a microphone array, and may also include, for example, a keyboard, a mouse, etc. For example, the output device may output various information to the outside, and may include, for example, a display, a speaker, a printer, a communication network and a remote output device connected thereto, etc.

[0272] In addition to the above methods, apparatuses and computing devices, embodiments of the present application may also provide a computer program product, which includes computer program instructions, which, when executed by a processor, cause the processor to execute the steps in the methods of various embodiments of the present application described in the above "Method" section of this specification. Wherein, the computer program product can be written in any combination of one or more programming languages ​​to perform computer program code for performing the operation of the embodiments of the present application, and the programming language includes an object-oriented programming language, such as Java, C++, etc., and also includes a conventional procedural programming language, such as "C" language or similar programming language. Wherein, the computer program code can be in source code form, object code form, executable file or some intermediate form, etc. The computer program code can be executed completely on the user computing device, partially on the user device, as an independent software package, partially on the user computing device, partially on the remote computing device, or completely on the remote computing device or server.

[0273] In addition, the embodiment of the present application may also provide a computer-readable storage medium on which computer program instructions are stored, and the computer program instructions, when executed by the processor, cause the processor to perform the steps in the display control method according to various embodiments of the present application described in the "Method" section of the present specification. The computer-readable storage medium may adopt any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may, for example, include but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or devices, or any combination of the above. More specific examples of readable storage media (non-exhaustive list) include: an electrical connection with one or more wires, a portable disk, 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. It should be noted that the content contained in the computer-readable medium may be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electrical carrier signals and telecommunication signals.

[0274] The method steps in the embodiments of the present application can be implemented by hardware or by a processor executing software instructions. The software instructions can be composed of corresponding software modules, and the software modules can be stored in random access memory (RAM), flash memory, read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), registers, hard disks, mobile hard disks, CD-ROMs, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an ASIC.

[0275] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions may be transmitted from a website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid state disk (SSD)), etc.

[0276] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0277] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0278] The basic principles of the present application are described above in conjunction with specific embodiments. However, it should be noted that the advantages, strengths, effects, etc. mentioned in the present application are only examples and not limitations, and it cannot be considered that these advantages, strengths, effects, etc. are required by each embodiment of the present application. In addition, the specific details disclosed above are only for the purpose of illustration and ease of understanding, not for limitation, and the above details do not limit the present application to being implemented by adopting the above specific details.

[0279] The block diagrams of the devices, apparatuses, equipment, and systems involved in this application are only illustrative examples and are not intended to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagram. As will be appreciated by those skilled in the art, these devices, apparatuses, equipment, and systems can be connected, arranged, and configured in any manner. Words such as "including", "comprising", "having", etc. are open words, referring to "including but not limited to", and can be used interchangeably with them. The words "or" and "and" used here refer to the words "and / or" and can be used interchangeably with them, unless the context clearly indicates otherwise. The words "such as" used here refer to the phrase "such as but not limited to", and can be used interchangeably with them.

[0280] It should also be noted that in the apparatus, device and method of the present application, each component or each step can be decomposed and / or recombined. Such decomposition and / or recombination should be regarded as equivalent solutions of the present application.

[0281] The above description has been given for the purpose of illustration and description. In addition, this description is not intended to limit the embodiments of the present application to the forms disclosed herein. Although multiple example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, changes, additions and sub-combinations thereof.

[0282] It should be understood that the various numerical numbers involved in the embodiments of the present application are only used for the convenience of description and are not used to limit the scope of the embodiments of the present application.

Claims

1. A signal equalization method, characterized in that: A signal receiving device applied to a signal transmission system, wherein the signal transmission system comprises a signal sending device and the signal receiving device communicatively connected via an interconnection link, comprising: receiving a target signal sent by the signal sending device; Determine, according to the amplitude of the target signal at two adjacent moments, the coordinate values ​​of the center positions of the decision values ​​of the target signal corresponding to the plurality of branch paths, the plurality of branch paths being paths when the target level state is transferred at the two adjacent moments, the two adjacent moments including the previous moment and the current moment, the target level state being the level state after the dimensionality reduction of the plurality of level states; Determine, according to the coordinate value of the center position and the tap coefficient, a center metric value of the target signal at the current moment, wherein the center metric value is used to measure the distance between the decision value and the center position, and the tap coefficient represents the characteristics of the channel formed by the interconnected link; According to the central measurement value, the path cumulative measurement value at the previous moment and the tap coefficient, the state transition path of the level state transition of the target signal from the starting moment to the current moment is determined, wherein the path cumulative measurement value is used to measure the sum of the Euclidean distances between the amplitude of the target signal and the decision value at different moments.

2. The method according to claim 1, characterized in that: The step of determining a state transition path of a level state transition of the target signal from a starting time to the current time according to the center metric value, the path cumulative metric value at the previous time, and the tap coefficient comprises: Determine the path center metric value of the target signal at the current moment according to the center metric value, the path cumulative metric value at the previous moment and the tap coefficient, wherein the path center metric value is used to measure the distance from the target signal to the center of the branch path; A state transition path for the target signal to perform level state transition from the starting time to the current time is determined according to the path center metric value and the tap coefficient.

3. The method according to claim 2, characterized in that The path center metric value of the target signal satisfies the following formula: c(tk)=pm(tk-1)+αp(tk); Among them, c(tk) represents the path center metric value at time tk, pm(tk-1) represents the path center metric value at time tk-1, α represents the tap coefficient, and p(tk) represents the center metric value at time tk.

4. The method according to claim 2, characterized in that: The step of determining a state transition path for the target signal to perform level state transition from the starting time to the current time according to the path center metric value and the tap coefficient comprises: Determine a comparison result by comparing the path center metric value and the tap coefficient; Determining a plurality of maximum likelihood paths from the plurality of branch paths according to the comparison result; Determine the cumulative metric value of the path at the current moment according to the comparison result; The state transition path is determined according to the path accumulated metric value and the multiple maximum likelihood paths.

5. The method according to any one of claims 1 to 4, characterized in that: The step of determining the coordinate values ​​of the center positions of the decision values ​​of the target signal corresponding to the plurality of branch paths according to the amplitudes of the target signal at two adjacent moments includes: Determine, from a plurality of level states, a level state that is closest to the amplitude of the target signal at the current moment; Determine, from the multiple level states, a level state that is closest to the amplitude of the target signal at the previous moment; Determine a first error between the amplitude of the target signal at the current moment and the level state closest to the amplitude of the target signal at the current moment; Determine a second error between the amplitude of the target signal at the previous moment and the level state closest to the amplitude of the target signal at the previous moment; The coordinate value of the center position is determined according to the first error, the second error, the level state closest to the amplitude of the target signal at the previous moment, and the level state closest to the amplitude of the target signal at the previous moment.

6. The method according to claim 5, characterized in that The coordinate values ​​(m, n) of the center position satisfy the following formula: m=2*(sign(a+sign(e))+1)-2, n=2*(sign(a'+sign(e'))+1)-2; Among them, sign is a sign function, a represents the level state closest to the amplitude of the target signal at the current moment, e represents the first error, a' represents the level state closest to the amplitude of the target signal at the previous moment, and e' represents the second error.

7. The method according to any one of claims 1 to 4, characterized in that: The central metric value satisfies the following formula: p = u - (m + nα); Among them, p represents the center measurement value at the current moment, u represents the amplitude of the target signal at the current moment, (m, n) represents the coordinate value of the center position, and α represents the tap coefficient.

8. A signal equalization method, characterized in that: A signal receiving device applied to a signal transmission system, wherein the signal transmission system comprises a signal sending device and the signal receiving device communicatively connected via an interconnection link, comprising: receiving a target signal sent by the signal sending device, wherein the target signal includes amplitudes at different times; In the case where burst error detection is started, determining an original error sequence of the target signal having a burst error, the original error sequence comprising a plurality of error values ​​of the target signal formed from a burst error start position Sob to a burst error end position Eob, each of the plurality of error values ​​being an error between an amplitude of the target signal and a level state of the target signal modulated; According to the original error sequence, calculating the difference between the Euclidean distance of the original error sequence and the Euclidean distance of the corrected error sequence; According to the size of the difference, the target signal after equalization is determined.

9. The method according to claim 8, characterized in that The equalized target signal is the target signal or the corrected target signal.

10. A signal equalization device, characterized in that: A signal receiving device applied to a signal transmission system, wherein the signal transmission system comprises a signal sending device and the signal receiving device communicatively connected via an interconnection link, comprising: A receiving module, receiving a target signal sent by the signal sending device; A first determining device is used to determine the coordinate values ​​of the center positions of the decision values ​​of the target signal corresponding to the multiple branch paths respectively according to the amplitudes of the target signal at two adjacent moments, the multiple branch paths are paths when the target level state is transferred at the two adjacent moments, the two adjacent moments include the previous moment and the current moment, and the target level state is the level state after the dimension reduction of the multiple level states; a second determining means for determining a center metric value of the target signal at the current moment according to the coordinate value of the center position and the tap coefficient, wherein the center metric value is used to measure the distance between the decision value and the center position, and the tap coefficient represents the characteristics of the channel formed by the interconnected links; The third determination device is used to determine the state transition path of the level state transition of the target signal from the starting moment to the current moment based on the central measurement value, the path cumulative measurement value at the previous moment and the tap coefficient, wherein the path cumulative measurement value is used to measure the sum of the Euclidean distances between the amplitude of the target signal and the decision value at different moments.

11. The device according to claim 10, characterized in that The third determining means is used for: Determine the path center metric value of the target signal at the current moment according to the center metric value, the path cumulative metric value at the previous moment and the tap coefficient, wherein the path center metric value is used to measure the distance from the target signal to the center of the branch path; A state transition path for the target signal to perform level state transition from the starting time to the current time is determined according to the path center metric value and the tap coefficient.

12. The device according to claim 11, characterized in that The path center metric value of the target signal satisfies the following formula: c(tk)=pm(tk-1)+αp(tk); Among them, c(tk) represents the path center metric value at time tk, pm(tk-1) represents the path center metric value at time tk-1, α represents the tap coefficient, and p(tk) represents the center metric value at time tk.

13. The device according to claim 11, characterized in that The third determining means is used for: Determine a comparison result by comparing the path center metric value and the tap coefficient; Determining a plurality of maximum likelihood paths from the plurality of branch paths according to the comparison result; Determine the cumulative metric value of the path at the current moment according to the comparison result; The state transition path is determined according to the path accumulated metric value and the multiple maximum likelihood paths.

14. The device according to any one of claims 10 to 13, characterized in that: The first determining device is used to: Determine, from a plurality of level states, a level state that is closest to the amplitude of the target signal at the current moment; Determine, from the multiple level states, a level state that is closest to the amplitude of the target signal at the previous moment; Determine a first error between the amplitude of the target signal at the current moment and the level state closest to the amplitude of the target signal at the current moment; Determine a second error between the amplitude of the target signal at the previous moment and the level state closest to the amplitude of the target signal at the previous moment; The coordinate value of the center position is determined according to the first error, the second error, the level state closest to the amplitude of the target signal at the previous moment, and the level state closest to the amplitude of the target signal at the previous moment.

15. The device according to claim 14, characterized in that The coordinate values ​​(m, n) of the center position satisfy the following formula: m=2*(sign(a+sign(e))+1)-2, n=2*(sign(a'+sign(e'))+1)-2; Among them, sign is a sign function, a represents the level state closest to the amplitude of the target signal at the current moment, e represents the first error, a' represents the level state closest to the amplitude of the target signal at the previous moment, e' represents the second error, and sign is a sign function.

16. The device according to any one of claims 10 to 13, characterized in that: The central metric value satisfies the following formula: p(tk)=u(tk)-(m+nα); Among them, p(tk) represents the center measurement value at time tk, u(tk) represents the amplitude of the target signal at time tk, (m, n) represents the coordinate value of the center position, and α represents the tap coefficient.

17. A signal equalization device, characterized in that: A signal receiving device applied to a signal transmission system, wherein the signal transmission system comprises a signal sending device and the signal receiving device communicatively connected via an interconnection link, comprising: A receiving module, used to receive a target signal sent by the signal sending device, wherein the target signal includes amplitudes at different times; an error value determination module, configured to determine, when burst error detection is enabled, an original error sequence of a burst error occurring in the target signal, wherein the original error sequence includes a plurality of error values ​​formed from a burst error start position Sob to a burst error end position Eob of the target signal, each of the plurality of error values ​​being an error between an amplitude of the target signal and a level state of the target signal modulated; A calculation module, used for calculating the difference between the Euclidean distance of the original error sequence and the Euclidean distance of the corrected error sequence according to the original error sequence, the tap coefficient, the burst error start Sob position and the burst error end Eob position; The signal determination module is used to determine the equalized target signal according to the size of the difference.

18. The device according to claim 17, characterized in that The equalized target signal is the target signal or the corrected target signal.

19. A signal transmission system, characterized in that: The system comprises a signal sending device and a signal receiving device: The signal sending device is used to send a target signal to the signal receiving device; The signal receiving device is used to execute the method according to any one of claims 1 to 7, or the method according to claim 8 or 9.

20. A signal equalization device, characterized in that: include: at least one memory for storing a program; At least one processor is used to execute the program stored in the memory. When the program stored in the memory is executed, the processor is used to execute the method according to any one of claims 1 to 7, or execute the method according to claim 8 or 9.

21. A signal equalization device, characterized in that: The device runs computer program instructions to perform the method according to any one of claims 1 to 7, or to perform the method according to claim 8 or 9.

22. A computer storage medium, characterized in that The computer storage medium stores instructions, and when the instructions are executed on a computer, the computer executes the method according to any one of claims 1 to 7, or executes the method according to claim 8 or 9.

23. A computer program product comprising instructions, characterized in that When the instructions are executed on a computer, the computer is caused to execute the method as described in any one of claims 1 to 7, or execute the method as described in claim 8 or 9.

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