Nonlinear compensation method and device

Abstract

The invention provides a nonlinear compensation method and device, and relates to the field of signal processing. The calculation module is used for calculating a PBC expansion coefficient more accurately through hard value auxiliary data; and meanwhile, the target PBC expansion coefficient is determined in the offline stage, so that the algorithm complexity of nonlinear compensation can be reduced. The method comprises the steps of performing online PBC nonlinear compensation on a target signal according to a target compensation PBC expansion coefficient based on a disturbance theory, wherein the target PBC expansion coefficient is an optimized expansion coefficient determined through at least one group of soft value data and at least one group of corresponding hard value auxiliary data in an offline stage.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of signal processing, and in particular to a nonlinear compensation method and device. Background Art

[0002] In order to mitigate the nonlinear effects in optical fibers, various nonlinear compensation technologies assisted by digital signal processing (DSP) have been widely studied, such as digital back propagation (DBP), Volterra series filtering, and perturbation based compensation (PBC). At the application level, these methods have encountered the problem of balancing power consumption complexity and performance. It is difficult to obtain a large gain in nonlinear compensation under the condition of limited chip resources. At present, it is still necessary to find a low-power and high-performance nonlinear compensation algorithm.

[0003] For example, in the existing nonlinear compensation algorithm, the signal A after impulse generation is x，y (z=0, k) is transmitted through the channel and processed by oDSP to obtain the soft value symbol A at the receiving end x，y (z=L, k), and transmit it to the soft core or central processing unit (CPU) for online perturbation-based compensation (PBC) coefficient calculation to obtain the PBC expansion coefficient W(m, n). x，y (z=L, k) is transmitted to the online PBC correction module, and the PBC expansion coefficient W(m, n) output by the soft core or CPU module is used to complete the online correction. Finally, the output result is output to the completion judgment module, and after the judgment, it is output to the feedforward error correction (FEC) module to complete the entire signal transmission process.

[0004] In the existing nonlinear compensation algorithm, only the soft value symbols processed by the receiving end oDSP are used to calculate the PBC coefficients. However, the bit error rate (BER) of the soft value symbols themselves ultimately makes it impossible to rely solely on the soft value symbols to calculate the optimized PBC coefficients, resulting in the final PBC correction effect being unable to obtain sufficient nonlinear compensation gain. On the other hand, the framework adopted by the existing nonlinear compensation algorithm is a pure online calculation mode, and the algorithm complexity is relatively high. Summary of the invention

[0005] The embodiments of the present application provide a nonlinear compensation method and device, which can more accurately calculate the PBC expansion coefficient through hard value auxiliary data; at the same time, the target PBC expansion coefficient is determined in the offline stage, reducing the algorithm complexity of the nonlinear compensation.

[0006] In the first aspect, an embodiment of the present application provides a method for signal synchronization, the method comprising: performing digital signal processing on a target signal; performing online PBC nonlinear compensation on the target signal according to a target compensation PBC expansion coefficient based on perturbation theory, the target PBC expansion coefficient being an optimized expansion coefficient determined in an offline stage by at least one set of soft value data and corresponding at least one set of hard value auxiliary data.

[0007] In this possible implementation, the target PBC expansion coefficient is an optimized expansion coefficient determined based on the soft value data and the corresponding hard value auxiliary data. The target PBC expansion coefficient determined in combination with the hard value auxiliary data is more accurate, which improves the accuracy and efficiency of nonlinear compensation. At the same time, the target PBC expansion coefficient is determined by the nonlinear compensation device in the offline stage, and does not require online calculation, which reduces the amount of calculation in the online stage, reduces the complexity of online PBC nonlinear compensation, and improves the efficiency of online PBC nonlinear compensation.

[0008] In one possible implementation, after performing digital signal processing on the target signal and before performing online PBC nonlinear compensation on the target signal according to the target compensation PBC expansion coefficient based on perturbation theory, the method further includes: acquiring at least one set of first soft value data and corresponding first hard value auxiliary data, the first hard value auxiliary data being an auxiliary sequence of hard value data corresponding to the first soft value data; calculating at least one set of PBC coefficients corresponding to at least one set of first soft value data and corresponding first hard value auxiliary data; and determining the target PBC expansion coefficient based on at least one set of PBC coefficients.

[0009] In one possible implementation, the above-mentioned calculation of at least one set of PBC coefficients corresponding to at least one set of first soft value data and corresponding first hard value auxiliary data includes: calculating at least one set of PBC coefficients corresponding to at least one set of first soft value data and corresponding first hard value auxiliary data through an optimization algorithm; or calculating at least one set of PBC coefficients corresponding to at least one set of first soft value data and corresponding first hard value auxiliary data through a least mean square algorithm; or calculating at least one set of PBC coefficients corresponding to at least one set of first soft value data and corresponding first hard value auxiliary data through a least mean square algorithm, and the first hard value auxiliary data is approximate hard value auxiliary data.

[0010] In a possible implementation, the above-mentioned determining the target PBC expansion coefficient according to at least one group of PBC coefficients includes: determining the target PBC expansion coefficient according to at least one group of PBC coefficients through a feature extraction algorithm, and the target PBC expansion coefficient is the optimized PBC expansion coefficient.

[0011] In one possible implementation, after performing online PBC nonlinear compensation on the target signal according to the target perturbation theory-based compensation PBC expansion coefficient, the method further includes: making a judgment on the target signal after the online PBC nonlinear compensation; and if the judgment is passed, calculating the bit error rate of the target signal after the online PBC nonlinear compensation.

[0012] In the second aspect, an embodiment of the present application provides a nonlinear compensation device, which includes: a receiving end optical digital signal processor oDSP module and an online PBC correction module, wherein: the oDSP module is used to perform digital signal processing on the target signal; the online PBC correction module is used to perform online PBC nonlinear compensation on the target signal according to the target compensation PBC expansion coefficient based on perturbation theory, and the target PBC expansion coefficient is the optimized expansion coefficient determined in the offline stage by at least one set of soft value data and corresponding at least one set of hard value auxiliary data.

[0013] In one possible implementation, the nonlinear compensation device also includes a hard value input module and a soft core or CPU module, wherein: the hard value input module is used to obtain at least one set of first soft value data and corresponding first hard value auxiliary data, the first hard value auxiliary data is a hard value data auxiliary sequence corresponding to the first soft value data; the soft core or CPU module is used to calculate at least one set of PBC coefficients corresponding to at least one set of first soft value data and corresponding first hard value auxiliary data; the soft core or CPU module is also used to determine the target PBC expansion coefficient based on at least one set of PBC coefficients.

[0014] In one possible implementation, the soft core or CPU module is also used to: calculate at least one set of PBC coefficients corresponding to at least one set of first soft value data and corresponding first hard value auxiliary data through an optimization algorithm; or calculate at least one set of PBC coefficients corresponding to at least one set of first soft value data and corresponding first hard value auxiliary data through a least mean square algorithm; or calculate at least one set of PBC coefficients corresponding to at least one set of first soft value data and corresponding first hard value auxiliary data through a least mean square algorithm, and the first hard value auxiliary data is approximate hard value auxiliary data.

[0015] In a possible implementation, the soft core or CPU module is further used to: determine a target PBC expansion coefficient according to at least one set of PBC coefficients by using a feature extraction algorithm, where the target PBC expansion coefficient is the optimized PBC expansion coefficient.

[0016] In a possible implementation, the soft core or CPU module is further used to: make a decision on the target signal after the online PBC nonlinear compensation; and if the decision is passed, calculate the bit error rate of the target signal after the online PBC nonlinear compensation.

[0017] In the third aspect, an embodiment of the present application provides a nonlinear compensation device, which includes: a digital signal processing module, used to perform digital signal processing on a target signal; a PBC nonlinear compensation module, used to perform online PBC nonlinear compensation on the target signal according to a target compensation PBC expansion coefficient based on perturbation theory, wherein the target PBC expansion coefficient is an optimized expansion coefficient determined in an offline stage by at least one set of soft value data and corresponding at least one set of hard value auxiliary data.

[0018] In one possible implementation, the nonlinear compensation device also includes: an acquisition module, used to acquire at least one set of first soft value data and corresponding first hard value auxiliary data, the first hard value auxiliary data being a hard value data auxiliary sequence corresponding to the first soft value data; a first calculation module, used to calculate at least one set of PBC coefficients corresponding to at least one set of first soft value data and corresponding first hard value auxiliary data; and a determination module, used to determine a target PBC expansion coefficient based on at least one set of PBC coefficients.

[0019] In one possible implementation, the first calculation module is specifically used to: calculate at least one group of PBC coefficients corresponding to at least one group of first soft value data and corresponding first hard value auxiliary data through an optimization algorithm; or calculate at least one group of PBC coefficients corresponding to at least one group of first soft value data and corresponding first hard value auxiliary data through a least mean square algorithm; or calculate at least one group of PBC coefficients corresponding to at least one group of first soft value data and corresponding first hard value auxiliary data through a least mean square algorithm, and the first hard value auxiliary data is approximate hard value auxiliary data.

[0020] In a possible implementation, the determination module is specifically used to: determine a target PBC expansion coefficient according to at least one set of PBC coefficients by using a feature extraction algorithm, wherein the target PBC expansion coefficient is the optimized PBC expansion coefficient.

[0021] In a possible implementation, the nonlinear compensation device further includes: a decision module for making a decision on the target signal after the online PBC nonlinear compensation; and a second calculation module for calculating the bit error rate of the target signal after the online PBC nonlinear compensation if the decision is passed.

[0022] In a fourth aspect, an embodiment of the present application provides a nonlinear compensation device, comprising: a processor and a memory. The processor is coupled to the memory; the memory is used to store computer instructions, and the computer instructions are loaded and executed by the processor to enable the nonlinear compensation device to implement any one of the methods provided in the first aspect.

[0023] In a fifth aspect, an embodiment of the present application provides a chip, comprising: a processor and an interface circuit; the interface circuit is used to receive code instructions and transmit them to the processor; the processor is used to run the code instructions to execute any one of the methods provided in the first aspect.

[0024] In a sixth aspect, an embodiment of the present application provides a computer-readable storage medium, in which at least one computer program instruction is stored, and the computer program instruction is loaded and executed by a processor to implement any one of the methods provided in the first aspect above.

[0025] In a seventh aspect, an embodiment of the present application provides a computer program product, comprising computer execution instructions, which, when executed on a computer, enable the computer to execute any one of the methods provided in the first aspect.

[0026] The technical effects brought about by any implementation method in the second to seventh aspects can refer to the technical effects brought about by the corresponding implementation method in the first aspect, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 A schematic diagram of a scenario of a nonlinear compensation method;

[0028] Figure 2 A schematic diagram of a scenario of a nonlinear compensation method provided in an embodiment of the present application;

[0029] Figure 3 A schematic diagram of the architecture of a nonlinear compensation device provided in an embodiment of the present application;

[0030] Figure 4a A schematic diagram of an offline scenario of a nonlinear compensation method provided in an embodiment of the present application;

[0031] Figure 4b A schematic diagram of an online scenario of a nonlinear compensation method provided in an embodiment of the present application;

[0032] Figure 5 A schematic diagram of a flow chart of a nonlinear compensation method provided in an embodiment of the present application;

[0033] Figure 6 A schematic diagram of another nonlinear compensation method provided in an embodiment of the present application;

[0034] Figure 7 A schematic diagram of another nonlinear compensation method provided in an embodiment of the present application;

[0035] Figure 8 A schematic diagram of another nonlinear compensation method provided in an embodiment of the present application;

[0036] Fig. 9 A schematic diagram of the structure of a nonlinear compensation device provided in an embodiment of the present application;

[0037] Fig.10 A schematic diagram of the structure of another nonlinear compensation device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0038] In the description of this application, unless otherwise specified, " / " indicates that the objects associated with each other are in an "or" relationship, for example, A / B can represent A or B; "and / or" in this application is merely a description of the association relationship between associated objects, indicating that three relationships may exist, for example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural.

[0039] In the description of this application, unless otherwise specified, "plurality" means two or more than two. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0040] In addition, in order to clearly describe the technical solutions of the embodiments of the present application, in the embodiments of the present application, words such as "first" and "second" are used to distinguish the same items or similar items with substantially the same functions and effects. Those skilled in the art can understand that words such as "first" and "second" do not limit the quantity and execution order, and words such as "first" and "second" do not necessarily limit the difference.

[0041] In the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" 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" or "for example" is intended to present related concepts in a concrete way for easy understanding.

[0042] It is understood that the "embodiment" mentioned throughout the specification means that the specific features, structures or characteristics related to the embodiment are included in at least one embodiment of the present application. Therefore, the various embodiments in the entire specification do not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner. It is understood that in various embodiments of the present application, the size of the sequence number of each process does not mean the order of execution, and 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 embodiment of the present application.

[0043] It can be understood that some optional features in the embodiments of the present application may be implemented independently in certain scenarios without relying on other features, such as the solution on which they are currently based, to solve corresponding technical problems and achieve corresponding effects, or may be combined with other features according to needs in certain scenarios. Accordingly, the devices provided in the embodiments of the present application may also realize these features or functions accordingly, which will not be elaborated here.

[0044] In this application, unless otherwise specified, the same or similar parts between the various embodiments can refer to each other. In this application, if there is no special description or logical conflict between the various embodiments, the terms and / or descriptions between different embodiments are consistent and can be referenced to each other, and different embodiments can be combined to form new embodiments according to their inherent logical relationships. The following implementation methods of this application do not constitute a limitation on the scope of protection of this application.

[0045] Gilder's Law states that in the next 25 years, the bandwidth of the backbone network will double every 6 months, which is three times the growth rate of computing power predicted by Moore's Law. The growth of communication network demand for bandwidth still follows Gilder's Law, and the demand for single-fiber capacity is increasing day by day, from 100Gb / s, 200Gb / s to 400Gb / s and 800Gb / s. With the exponential growth of single-fiber capacity, the transmission distance must still remain long, and the nonlinear effect of optical fiber has become the core issue in long-distance high-speed transmission scenarios.

[0046] In order to mitigate the nonlinear effects in optical fibers, various nonlinear compensation technologies assisted by digital signal processing (DSP) have been widely studied, such as digital back propagation (DBP), Volterra series filtering, and perturbation based compensation (PBC). At the application level, these methods have encountered the problem of balancing power consumption complexity and performance. It is difficult to obtain a large gain in nonlinear compensation under the condition of limited chip resources. At present, it is still necessary to find a low-power and high-performance nonlinear compensation algorithm.

[0047] For compensation based on disturbance theory, assuming the transmitting signal is A x，y (z=0, t)={A x，y (z=0, k)} k＝1，...，M The signal after processing by the optical digital signal processor (oDSP) at the receiving end is A x，y (z=L,t)={A x，y (z=L, k)} k＝1，...，M Where M is the number of matches. First, assume that the PBC-corrected signal after L km of transmission can be expressed as: Where W(m, n) is the PBC expansion coefficient to be determined, T x，y (m, n) is the PBC expansion term, which can be expressed as:

[0048] The subscripts x and y represent x polarization and y polarization respectively. x，y (z=0, t)={A x，y (z=0, k)} k＝1，…，M Unknown, so the receiving end signal A is required x，y (z=L,t)={A x，y (z=L, k)} k＝1，…，M Signal after judgment To replace the sending signal, so in actual use It can be expressed as:

[0049]

[0050] By applying the least squares method (LS) or the least squares mean square method (LMS), the PBC weight W (m, n) can be obtained. Therefore, the online PBC correction in actual use can be expressed as:

[0051]

[0052] like Figure 1 As shown, for example, in the existing nonlinear compensation algorithm, the signal A after impulse generation is x，y (z=0, k) is transmitted through the channel and processed by oDSP to obtain the soft value symbol A at the receiving end x，y (z=L, k), and transmit it to the soft core or central processing unit (CPU) for online PBC coefficient calculation to obtain the PBC expansion coefficient W(m, n). x，y (z=L, k) is transmitted to the online PBC correction module, and the PBC expansion coefficient W(m, n) output by the soft core or CPU module is used to complete the online correction. Finally, the output result is output to the completion judgment module, and after the judgment, it is output to the forward error correction (FEC) module to complete the entire signal transmission process.

[0053] In the existing nonlinear compensation algorithm, only the soft value symbols processed by the receiving end oDSP are used, and the PBC coefficients are calculated by LSM or LS. However, the bit error rate (BER) of the soft value symbols themselves ultimately makes it impossible to rely solely on the soft value symbols to calculate the optimized PBC coefficients, resulting in the final PBC correction effect being unable to obtain sufficient nonlinear compensation gain. On the other hand, the framework adopted by the existing nonlinear compensation algorithm is a pure online calculation mode, and the algorithm complexity is relatively high.

[0054] Based on this, Figure 2 As shown, an embodiment of the present application provides a method for nonlinear compensation, the method comprising: performing digital signal processing on a target signal; performing online PBC nonlinear compensation on the target signal according to a target compensation PBC expansion coefficient based on perturbation theory, the target PBC expansion coefficient being an optimized expansion coefficient determined in an offline stage by at least one set of soft value data and corresponding at least one set of hard value auxiliary data.

[0055] The nonlinear compensation method provided in the embodiment of the present application can be applied to Figure 3 The nonlinear compensation device shown in the figure comprises a receiving end optical digital signal processor oDSP module, a hard value input module, a soft core or CPU module and an online PBC correction module, and corresponding interfaces, including a soft core or CPU hard value input interface, a soft core or CPU soft value input interface, a soft core or CPU output interface, an online PBC correction module soft value input interface, and an online PBC correction module PBC coefficient input interface, wherein:

[0056] The oDSP module is used to output soft value data after digital signal processing.

[0057] The hard value input module is used to provide hard value auxiliary data and provide hard value sequence auxiliary calculation to the soft core or CPU module.

[0058] The soft core or CPU module is used to calculate the PBC coefficient offline by using an optimization algorithm based on the physical theory of optical fiber transmission, and extract features to obtain the optimized PBC coefficient. The soft core or CPU module can obtain hard value data through the soft core or CPU hard value input interface, obtain soft value data through the soft core or CPU soft value input interface, and output the optimized PBC coefficient through the soft core or CPU output interface.

[0059] The online PBC correction module is used to complete nonlinear compensation after receiving the PBC coefficient. The online PBC correction module can obtain soft value data through the online PBC correction module soft value input interface, and can also obtain the optimized PBC coefficient through the online PBC correction module PBC coefficient input interface.

[0060] Specifically, Figure 4a As shown, in the offline stage, the soft core or CPU module receives the soft core signal processed by the receiving end oDSP and the corresponding hard value input, and calculates a set of PBC expansion coefficients W (m, n) using an optimization algorithm based on the physical theory of optical fiber transmission. After at least one calculation, at least one set of PBC expansion coefficients is obtained, and the optimized PBC expansion coefficients can be obtained by aligning and extracting features. And provide it to the online PBC correction module.

[0061] like Figure 4b As shown in the figure, in the online stage, the optical signal is input into the online PBC correction module after being transmitted by optical fiber and linearly compensated by the receiving end oDSP, and the optimized PBC expansion coefficient input in the offline stage is combined. Complete the correction of the signal, realize nonlinear compensation, then output it to the judgment module, and finally input it to the FEC module to complete the online optical communication process.

[0062] It is understandable that in the embodiments of the present application, the execution subject may execute some or all of the steps in the embodiments of the present application, and these steps or operations are only examples. The embodiments of the present application may also execute other operations or variations of various operations. In addition, the various steps may be executed in different orders presented in the embodiments of the present application, and it is possible that not all operations in the embodiments of the present application need to be executed.

[0063] It should be noted that the message names between the devices or the names of the parameters in the messages in the following embodiments of the present application are only examples, and other names may be used in the specific implementation, and the embodiments of the present application do not specifically limit this.

[0064] like Figure 5 As shown, a nonlinear compensation method provided by an embodiment of the present application comprises the following steps:

[0065] In the offline stage, the nonlinear compensation method provided in the embodiment of the present application can perform the following steps:

[0066] 501. Perform oDSP processing on the target signal.

[0067] After acquiring the target signal, the nonlinear compensation device performs oDSP processing on the received target signal.

[0068] In the embodiment of the present application, the nonlinear compensation device can transmit the target signal processed by oDSP to the online PBC correction module. For example, the pulse signal generated by the pulse is pulse shaped and transmitted to the oDSP module through the optical fiber. The oDSP module determines the first soft value data after processing by matched filter, clock domain crossing (CDC), equalization, phase recovery, etc.

[0069] 502. Acquire first soft value data and first hard value auxiliary data.

[0070] In the offline stage (ie, the offline side), the nonlinear compensation device can obtain first soft value data and first hard value auxiliary data, where the first soft value data is the soft value data processed by oDSP, and the first hard value auxiliary data is the hard value data auxiliary sequence corresponding to the first soft value data.

[0071] Specifically, Figure X As shown, the nonlinear compensation device can process the first soft value data A after being processed by the oDSP module. x，y (z=L, k) is input into the soft core or CPU module through the soft value input interface of the soft core or CPU, and the first hard value auxiliary data A provided by the hard value input module is input into the soft core or CPU module. x，y (z=L, k) is input into the soft core or CPU module through the soft value input interface.

[0072] In the embodiment of the present application, the nonlinear compensation device may obtain a set of first soft value data and first hard value auxiliary data, or may obtain multiple sets of first soft value data and first hard value auxiliary data. Subsequently, the at least one set of first soft value data and first hard value auxiliary data is subjected to the same processing, without specific limitation.

[0073] In the embodiment of the present application, the first hard value data may be approximate Tx data, FEC return data and external light sensor channel input data obtained after processing by the oDSP module, and may also be other data, such as Tx data directly obtained by the transmitting end.

[0074] In the embodiment of the present application, the soft value data and the hard value auxiliary data can be transmitted to the nonlinear compensation device in the form of signals, that is, they can be understood as the form of soft value signals and hard value auxiliary signals. For example, the pulse signal generated by the pulse is pulse shaped and transmitted to the oDSP module through the optical fiber. The oDSP module determines the first soft value data after processing by matched filter, clock domain crossing (CDC), equalization, phase recovery, etc.

[0075] 503. Calculate the PBC coefficient.

[0076] The nonlinear compensation device determines the perturbation-based compensation (PBC) coefficient corresponding to each set of transmitting end data (ie, the first soft value data and the first hard value auxiliary data) offline by using an optimization algorithm based on the physical theory of optical fiber transmission.

[0077] In an embodiment of the present application, the optimization algorithm includes a loss function based on the characteristics of soft-judgment FEC and NLSE; or a loss function designed by a physical information neural network (PINN). In addition, it can also be other optimization algorithms, such as a weighted least squares weight function designed based on channel transmission distortion and constellation spacing, which is not limited here.

[0078] In a possible implementation, the nonlinear compensation method can be applied to a WDM dual-polarization scenario at a high speed of 80 GBaud or more over 1000 km, and the transmitting signal can adopt a QAM modulation format.

[0079] like Figure 6 As shown, the nonlinear compensation device can first convert at least one group of soft value symbols A processed by oDSP into x，y (z=L,k) and its corresponding originating symbol A x，y (z=0, k) cooperates with the optimization module in the soft core or CPU offline PBC optimization, and uses the optimization algorithm to calculate a series (or a group) of corresponding PBC expansion coefficients W (m, n).

[0080] In another possible implementation, the nonlinear compensation method can be applied to high-speed 80GBaud or above over 1000km, WDM dual-polarization scenarios, and the transmitting signal can adopt QAM modulation format.

[0081] like Figure 7 As shown, the nonlinear compensation device can first convert at least one group of soft value symbols A processed by oDSP into x，y (z=L,k) and its corresponding originating symbol A x，y (z=0, k) is input into the soft core or CPU module, and then at least one corresponding set of PBC expansion coefficients W(m, n) is calculated by a traditional least mean square (LMS) algorithm.

[0082] In another possible implementation, the nonlinear compensation method can be applied to high-speed 80GBaud or above over 1000km, WDM dual-polarization scenarios, and the transmitting signal can adopt QAM modulation format.

[0083] like Figure 8 As shown, the nonlinear compensation device can first convert at least one group of soft value symbols A processed by oDSP into x，y (z=L,k) and its approximate origin symbol A x，y (z = 0, k) is input into the soft core or CPU module, and the approximate origin symbol A x，y (z=0, k) is a hard value symbol with a bit error rate, and then at least one corresponding set of PBC expansion coefficients W(m, n) is calculated by a traditional LMS algorithm.

[0084] In the embodiment of the present application, the PBC coefficient can be calculated in various ways, such as Figure 6 The method shown in FIG. 1 is to calculate the PBC coefficients for nonlinear compensation by means of hard value assistance, optimization modules and hierarchical architecture; or Figure 7 In the manner shown, the PBC coefficients are calculated by hard value assistance and hierarchical architecture to perform nonlinear compensation; Figure 8 In the manner shown, the PBC coefficients are calculated by means of approximate hard value assistance and a hierarchical architecture to perform nonlinear compensation; the specifics are not limited here.

[0085] 504. Determine the expansion coefficient after optimization.

[0086] The nonlinear compensation device determines the target PBC expansion coefficient through a feature extraction algorithm based on at least one set of PBC coefficients. The target PBC expansion coefficient is the optimized PBC expansion coefficient.

[0087] Specifically, after determining at least one set of PBC coefficients, the nonlinear compensation device can extract features from them through a feature extraction algorithm, thereby determining the target expansion coefficients after optimization.

[0088] In the embodiment of the present application, after determining the optimal expansion coefficient, the nonlinear compensation device can transmit the target expansion coefficient to the online PBC correction module through the soft core or the CPU output interface.

[0089] In the embodiment of the present application, steps 503 and 504 in the offline stage can be understood to be executed by the module on the offline side, or can be the target PBC expansion coefficient determined in advance.

[0090] In the online stage, the nonlinear compensation method provided in the embodiment of the present application may perform the following steps:

[0091] 505. Perform online PBC nonlinear compensation according to the optimized expansion coefficient.

[0092] The nonlinear compensation device is based on the optimized expansion coefficient The target signal is subjected to online PBC nonlinear compensation, which can be understood as PBC correction.

[0093] In a possible implementation, the nonlinear compensation device of the embodiment of the present application may further perform the following steps when performing online PBC nonlinear compensation:

[0094] 506. Determine the target signal and calculate the bit error rate.

[0095] After completing the online PBC nonlinear compensation, the nonlinear compensation device then makes a decision on the target signal after the online PBC nonlinear compensation.

[0096] After completing the judgment, the non-linear compensation device can also calculate the bit error rate BER of the target signal after the online PBC non-linear compensation.

[0097] In the embodiment of the present application, the target PBC expansion coefficient is an optimized expansion coefficient determined according to the soft value data and the corresponding hard value auxiliary data. The target PBC expansion coefficient determined in combination with the hard value auxiliary data is more accurate, which improves the accuracy and efficiency of nonlinear compensation. At the same time, the target PBC expansion coefficient is determined by the nonlinear compensation device in the offline stage, and does not require online calculation, which reduces the amount of calculation in the online stage, reduces the complexity of online PBC nonlinear compensation, and improves the efficiency of online PBC nonlinear compensation.

[0098] The embodiment of the present application provides a nonlinear compensation device 900. In the embodiment of the present application, the nonlinear compensation device 900 can be divided into functional modules according to the above method example. For example, each functional module can be divided according to each function, or two or more functions can be integrated into one processing module. The above integrated module can be implemented in the form of hardware or in the form of software functional modules. It should be noted that the division of modules in the embodiment of the present invention is schematic and is only a logical function division. There may be other division methods in actual implementation.

[0099] In the case of dividing each functional module into corresponding functional modules, Fig. 9 FIG. 8 is a schematic diagram showing a possible structure of the nonlinear compensation device 900 involved in the above embodiment. Fig. 9 As shown, the nonlinear compensation device 900 includes:

[0100] The digital signal processing module 901 is used to perform digital signal processing on the target signal; for example, in step 501, oDSP processing is performed on the received target signal.

[0101] The acquisition module 902 is used to acquire at least one set of first soft value data and corresponding first hard value auxiliary data, where the first hard value auxiliary data is a hard value data auxiliary sequence corresponding to the first soft value data; for example, step 502, acquiring first soft value data and first hard value auxiliary data.

[0102] The first calculation module 903 is used to calculate at least one set of PBC coefficients corresponding to the at least one set of first soft value data and the corresponding first hard value auxiliary data; for example, step 503, calculating the PBC coefficients.

[0103] In a possible implementation, the first calculation module 903 is specifically used to: calculate at least one group of PBC coefficients corresponding to the at least one group of first soft value data and the corresponding first hard value auxiliary data by using an optimization algorithm; or

[0104] Calculate at least one set of PBC coefficients corresponding to the at least one set of first soft value data and the corresponding first hard value auxiliary data by using a least mean square algorithm; or

[0105] At least one set of PBC coefficients corresponding to the at least one set of first soft value data and the corresponding first hard value auxiliary data are calculated by the least mean square algorithm, wherein the first hard value auxiliary data is approximate hard value auxiliary data. For example, step 502, calculate the PBC coefficients.

[0106] The determination module 904 is used to determine the target PBC expansion coefficient according to the at least one set of PBC coefficients. For example, step 504 determines the optimized expansion coefficient.

[0107] In a possible implementation, the determination module 904 is specifically used to: determine the target PBC expansion coefficient according to the at least one set of PBC coefficients by using a feature extraction algorithm, wherein the target PBC expansion coefficient is the optimized PBC expansion coefficient. For example, step 503, determining the optimized expansion coefficient.

[0108] The PBC nonlinear compensation module 905 is used to perform online PBC nonlinear compensation on the target signal according to the target compensation PBC expansion coefficient based on the disturbance theory, wherein the target PBC expansion coefficient is the optimized expansion coefficient determined in the offline stage by at least one set of soft value data and at least one set of corresponding hard value auxiliary data. For example, in step 505, online PBC nonlinear compensation is performed according to the optimized expansion coefficient.

[0109] The decision module 906 is used to make a decision on the target signal after the online PBC nonlinear compensation; for example, in step 506, the target signal is decided and the bit error rate is calculated.

[0110] The second calculation module 907 is used to calculate the bit error rate of the target signal after the online PBC nonlinear compensation when the judgment is passed. For example, in step 506, the target signal is judged and the bit error rate is calculated.

[0111] Each module of the above-mentioned nonlinear compensation device can also be used to execute other actions in the above-mentioned method embodiment. All relevant contents of each step involved in the above-mentioned method embodiment can be referred to the functional description of the corresponding functional module, which will not be repeated here.

[0112] Fig.10 It is a schematic diagram of the structure of a nonlinear compensation device provided in an embodiment of the present application. The nonlinear compensation device 1000 may include one or more central processing units (CPU) 1001 and a memory 1005. The memory 1005 stores one or more application programs or data.

[0113] The memory 1005 may be a volatile storage or a persistent storage. The program stored in the memory 1005 may include one or more modules, each of which may include a series of instruction operations in the nonlinear compensation device. Furthermore, the central processor 1001 may be configured to communicate with the memory 1005 and execute a series of instruction operations in the memory 1005 on the nonlinear compensation device 1000.

[0114] The central processing unit 1001 is used to execute the computer program in the memory 1005, so that the nonlinear compensation device 1000 is used to perform: digital signal processing on the target signal; online PBC nonlinear compensation on the target signal according to the target compensation PBC expansion coefficient based on the disturbance theory, and the target PBC expansion coefficient is the optimized expansion coefficient determined by at least one set of soft value data and corresponding at least one set of hard value auxiliary data in the offline stage. For specific implementation methods, please refer to Figure 5 Steps 501-506 in the illustrated embodiment are not described in detail here.

[0115] The nonlinear compensation device 1000 may also include one or more power supplies 1002, one or more wired or wireless network interfaces 1003, one or more input and output interfaces 1004, and / or one or more operating systems, such as Windows ServerTM, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, etc.

[0116] The nonlinear compensation device 1000 can perform the aforementioned Figure 5 The operations performed by the nonlinear compensation device in the illustrated embodiment will not be described in detail herein.

[0117] The present application also provides a computer program product including instructions. The computer program product may be a software or program product including instructions that can be run on the plug-in result multiplexing device or stored in any available medium. When the computer program product is run on the plug-in result multiplexing device, the nonlinear compensation device performs the aforementioned Figure 5 The nonlinear compensation method implemented in the illustrated embodiment.

[0118] The embodiment of the present application also provides a computer-readable storage medium. The computer-readable storage medium can be any available medium that can be stored by the cache server or a data storage device such as a data center that contains one or more available media. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a DVD), or a semiconductor medium (for example, a solid-state hard disk). The computer-readable storage medium includes instructions that instruct the nonlinear compensation device to perform the aforementioned Figure 5 The nonlinear compensation method implemented in the illustrated embodiment.

[0119] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using a software program, 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 loading and executing computer program instructions on a computer, all or part of the processes (or functions) of the embodiments of the present application are implemented. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. Computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, computer instructions can be transmitted from a website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (digital subscriber line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server, data center, etc. that contains one or more servers that can be integrated with a medium. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a DVD), or a semiconductor medium (eg, a solid state disk (SSD)), etc. In the embodiment of the present application, the computer may include the above device.

[0120] Although the present application is described herein in conjunction with various embodiments, in the process of implementing the claimed application, those skilled in the art may understand and implement other changes to the disclosed embodiments by viewing the drawings, the disclosure, and the appended claims. In the claims, the word "comprising" does not exclude other components or steps, and "one" or "an" does not exclude multiple situations. A single processor or other unit may implement several functions listed in the claims. Certain measures are recorded in different dependent claims, but this does not mean that these measures cannot be combined to produce good results.

Claims

1. A nonlinear compensation method, characterized in that: The method comprises: Performing digital signal processing on the target signal; The target signal is subjected to online PBC nonlinear compensation according to the target perturbation theory-based compensation PBC expansion coefficient, wherein the target PBC expansion coefficient is an optimized expansion coefficient determined in an offline stage by at least one set of soft value data and corresponding at least one set of hard value auxiliary data.

2. The method according to claim 1, characterized in that Before performing online PBC nonlinear compensation on the target signal according to the target perturbation theory-based compensation PBC expansion coefficient, and after performing digital signal processing on the target signal, the method further includes: Acquire at least one set of first soft value data and corresponding first hard value auxiliary data, wherein the first hard value auxiliary data is an auxiliary sequence of hard value data corresponding to the first soft value data; calculating at least one set of PBC coefficients corresponding to the at least one set of first soft value data and the corresponding first hard value auxiliary data; A target PBC expansion coefficient is determined based on the at least one set of PBC coefficients.

3. The method according to claim 2, characterized in that The calculating of at least one set of PBC coefficients corresponding to the at least one set of first soft value data and the corresponding first hard value auxiliary data comprises: Calculate at least one set of PBC coefficients corresponding to the at least one set of first soft value data and the corresponding first hard value auxiliary data by an optimization algorithm; or Calculate at least one set of PBC coefficients corresponding to the at least one set of first soft value data and the corresponding first hard value auxiliary data by using a least mean square algorithm; or At least one set of PBC coefficients corresponding to the at least one set of first soft value data and the corresponding first hard value auxiliary data are calculated by a least mean square algorithm, wherein the first hard value auxiliary data is approximate hard value auxiliary data.

4. The method according to claim 3, characterized in that The step of determining a target PBC expansion coefficient according to the at least one set of PBC coefficients comprises: A target PBC expansion coefficient is determined according to the at least one group of PBC coefficients by a feature extraction algorithm, wherein the target PBC expansion coefficient is the optimized PBC expansion coefficient.

5. The method according to any one of claims 1 to 4, characterized in that: After performing online PBC nonlinear compensation on the target signal according to the target perturbation theory-based compensation PBC expansion coefficient, the method further includes: Determine the target signal after online PBC nonlinear compensation; In the case of passing the judgment, the bit error rate of the target signal after online PBC nonlinear compensation is calculated.

6. A nonlinear compensation device, characterized in that: The nonlinear compensation device is used to implement the method described in any one of claims 1 to 5, and the nonlinear compensation device comprises: a receiving end optical digital signal processor oDSP module and an online PBC correction module, wherein: The oDSP module is used to perform digital signal processing on the target signal; The online PBC correction module is used to perform online PBC nonlinear compensation on the target signal according to the target compensation PBC expansion coefficient based on disturbance theory, and the target PBC expansion coefficient is the optimized expansion coefficient determined in the offline stage through at least one set of soft value data and corresponding at least one set of hard value auxiliary data.

7. The nonlinear compensation device according to claim 6, characterized in that: The nonlinear compensation device also includes a hard value input module and a soft core or CPU module, wherein: a hard value input module, configured to obtain at least one set of first soft value data and corresponding first hard value auxiliary data, wherein the first hard value auxiliary data is an auxiliary sequence of hard value data corresponding to the first soft value data; a soft core or CPU module for calculating at least one set of PBC coefficients corresponding to the at least one set of first soft value data and the corresponding first hard value auxiliary data; The soft core or CPU module is further used to determine the target PBC expansion coefficient according to the at least one set of PBC coefficients.

8. The nonlinear compensation device according to claim 7, characterized in that: The soft core or CPU module is also used for: Calculate at least one set of PBC coefficients corresponding to the at least one set of first soft value data and the corresponding first hard value auxiliary data by an optimization algorithm; or Calculating at least one set of PBC coefficients corresponding to the at least one set of first soft value data and the corresponding first hard value auxiliary data by a least mean square algorithm; or At least one set of PBC coefficients corresponding to the at least one set of first soft value data and the corresponding first hard value auxiliary data are calculated by a least mean square algorithm, wherein the first hard value auxiliary data is approximate hard value auxiliary data.

9. The nonlinear compensation device according to claim 8, characterized in that: The soft core or CPU module is also used for: A target PBC expansion coefficient is determined according to the at least one group of PBC coefficients by a feature extraction algorithm, wherein the target PBC expansion coefficient is the optimized PBC expansion coefficient.

10. The nonlinear compensation device according to any one of claims 6 to 9, characterized in that: The soft core or CPU module is also used for: Determine the target signal after online PBC nonlinear compensation; In the case of passing the judgment, the bit error rate of the target signal after online PBC nonlinear compensation is calculated.

11. A nonlinear compensation device, characterized in that: The nonlinear compensation device comprises: A digital signal processing module, used for performing digital signal processing on a target signal; The PBC nonlinear compensation module is used to perform online PBC nonlinear compensation on the target signal according to the target compensation PBC expansion coefficient based on the disturbance theory, wherein the target PBC expansion coefficient is the optimized expansion coefficient determined in the offline stage by at least one set of soft value data and corresponding at least one set of hard value auxiliary data.

12. The nonlinear compensation device according to claim 11, characterized in that: The nonlinear compensation device further comprises: an acquisition module, configured to acquire at least one set of first soft value data and corresponding first hard value auxiliary data, wherein the first hard value auxiliary data is an auxiliary sequence of hard value data corresponding to the first soft value data; A first calculation module, configured to calculate at least one set of PBC coefficients corresponding to the at least one set of first soft value data and the corresponding first hard value auxiliary data; The determination module is used to determine the target PBC expansion coefficient according to the at least one set of PBC coefficients.

13. The nonlinear compensation device according to claim 12, characterized in that: The first calculation module is specifically used for: Calculate at least one set of PBC coefficients corresponding to the at least one set of first soft value data and the corresponding first hard value auxiliary data by an optimization algorithm; or Calculating at least one set of PBC coefficients corresponding to the at least one set of first soft value data and the corresponding first hard value auxiliary data by a least mean square algorithm; or At least one set of PBC coefficients corresponding to the at least one set of first soft value data and the corresponding first hard value auxiliary data are calculated by a least mean square algorithm, wherein the first hard value auxiliary data is approximate hard value auxiliary data.

14. The nonlinear compensation device according to claim 13, characterized in that: The determination module is specifically used for: A target PBC expansion coefficient is determined according to the at least one group of PBC coefficients by a feature extraction algorithm, wherein the target PBC expansion coefficient is the optimized PBC expansion coefficient.

15. The nonlinear compensation device according to any one of claims 11 to 14, characterized in that: The nonlinear compensation device further comprises: A decision module, used for making a decision on the target signal after online PBC nonlinear compensation; The second calculation module is used to calculate the bit error rate of the target signal after the online PBC nonlinear compensation when the judgment is passed.

16. A nonlinear compensation device, characterized in that: The nonlinear compensation device comprises a processor and a memory; the processor is coupled to the memory; the memory is used to store computer instructions, and the computer instructions are loaded and executed by the processor to enable the nonlinear compensation device to implement the method according to any one of claims 1-8.

17. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores at least one computer program instruction, and the computer program instruction is loaded and executed by a processor to implement the method according to any one of claims 1 to 5.

18. A computer program product, characterized in that The computer program product comprises computer-executable instructions. When the computer-executable instructions are executed on a computer, the computer is configured to implement the method according to any one of claims 1 to 5.

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