Nonlinear equalization method, device, equipment and storage medium

Abstract

The present application discloses a nonlinear equalization method, device, equipment and storage medium, which relates to the field of communication technology. The method includes: obtaining the floating-point tap coefficients of the original equalizer, performing low-bit quantization on the floating-point tap coefficients to obtain integer tap coefficients; constructing a target equalizer based on the integer tap coefficients; and compensating the nonlinear distortion of the processed signal based on the target equalizer to obtain a restored signal. In the above manner, the tap coefficients of the equalizer are low-bit quantized, and the traditional floating-point numbers are converted into low-bit integer representations, which significantly reduces the storage space and computational complexity, and can optimize the hardware implementation efficiency and reduce power consumption while ensuring transmission performance.

Description

Technical Field

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

[0002] The intensity modulation / direct detection (IM / DD) system has become the preferred solution in short-distance optical communication systems due to its advantages such as small size, low cost, low power consumption and relatively simple system architecture. However, in the process of achieving high-capacity and long-distance transmission, the IM / DD system is prone to serious mixed linear and nonlinear damage due to factors such as frequency chirp, ISI (inter-symbol interference), dispersion and square-law direct detection combined with nonlinear effects, and the inherent nonlinearity of the transceiver. Nonlinear equalization technology is usually used to compensate for various linear and nonlinear distortions introduced during signal transmission to improve the transmission performance of the system. Commonly used equalization technologies include feedforward equalizer (FFE), decision feedback equalizer (DFE) and Volterra series-based equalizer. However, these equalizers require more storage space and computing resources in practical applications, and the hardware implementation is also relatively complex.

[0003] The above contents are only used to assist in understanding the technical solution of the present invention and do not constitute an admission that the above contents are prior art. Summary of the invention

[0004] The main purpose of the present application is to provide a nonlinear equalization method, device, equipment and storage medium, aiming to solve the technical problem that when using an equalizer to compensate for nonlinear distortion in the signal transmission process of an IM / DD system in the prior art, it takes up a lot of storage space and computing resources, and the hardware implementation is relatively complex.

[0005] To achieve the above object, the present application provides a nonlinear equalization method, the method comprising:

[0006] Obtaining floating-point tap coefficients of an original equalizer, and performing low-bit quantization on the floating-point tap coefficients to obtain integer tap coefficients;

[0007] constructing a target equalizer based on the integer tap coefficients;

[0008] The nonlinear distortion of the signal to be processed is compensated based on the target equalizer to obtain a restored signal.

[0009] In one embodiment, the low-bit quantization is low-bit uniform quantization, and the steps of obtaining floating-point tap coefficients of the original equalizer, performing low-bit quantization on the floating-point tap coefficients, and obtaining integer tap coefficients include:

[0010] The floating-point tap coefficients of the original equalizer are obtained, and low-bit uniform quantization is performed on the floating-point tap coefficients to obtain integer tap coefficients.

[0011] In one embodiment, the step of obtaining floating-point tap coefficients of an original equalizer and performing low-bit uniform quantization on the floating-point tap coefficients to obtain integer tap coefficients comprises:

[0012] Obtaining a low-order uniform quantization mapping relationship between a floating-point tap coefficient, a scale factor, a zero offset, a quantization bit number, and an integer tap coefficient;

[0013] The integer tap coefficient is determined based on the floating-point tap coefficient, the scale factor, the zero offset, the number of quantization bits, and the low-bit uniform quantization mapping relationship.

[0014] In one embodiment, the low-bit quantization is low-bit non-uniform quantization, and the steps of obtaining floating-point tap coefficients of the original equalizer, performing low-bit quantization on the floating-point tap coefficients, and obtaining integer tap coefficients include:

[0015] Determining coefficient quantization accuracy based on characteristic information of the signal to be processed;

[0016] The floating-point tap coefficients of the original equalizer are obtained, and based on the coefficient quantization accuracy, the floating-point tap coefficients are subjected to low-bit non-uniform quantization to obtain integer tap coefficients.

[0017] In one embodiment, the step of obtaining the floating-point tap coefficients of the original equalizer and performing low-bit non-uniform quantization on the floating-point tap coefficients based on the coefficient quantization accuracy to obtain integer tap coefficients includes:

[0018] Obtaining a low-order non-uniform quantization mapping relationship between a floating-point tap coefficient, a scale factor, a zero offset, a quantization bit number, and an integer tap coefficient;

[0019] The integer tap coefficient is determined based on the floating-point tap coefficient, the scale factor, the zero offset, the number of quantization bits, and the low-bit non-uniform quantization mapping relationship.

[0020] In one embodiment, the step of compensating the nonlinear distortion of the signal to be processed based on the target equalizer to obtain a restored signal comprises:

[0021] De-quantizing the integer tap coefficients to determine quantization coefficients of the target equalizer;

[0022] Based on the quantization coefficients, determining a nonlinear compensation relationship between the signal to be processed and the restored signal;

[0023] The restored signal is obtained based on the signal to be processed and the nonlinear compensation relationship.

[0024] In one embodiment, the quantization coefficients include forward quantization coefficients and feedback quantization coefficients, and the step of determining the nonlinear compensation relationship between the signal to be processed and the restored signal based on the quantization coefficients includes:

[0025] When the target equalizer is a Volterra decision feedback equalizer, determining a first corresponding relationship between the signal to be processed, the forward quantization coefficient and the first filtered signal based on the forward quantization coefficient;

[0026] Based on the feedback quantization coefficient, determining a second corresponding relationship between the feedback decision symbol, the feedback quantization coefficient and the second filtered signal;

[0027] Based on the first corresponding relationship and the second corresponding relationship, a nonlinear compensation relationship between the signal to be processed and the restored signal is determined.

[0028] In addition, to achieve the above purpose, the present application also proposes a nonlinear equalization device, which includes:

[0029] A low-bit quantization module is used to obtain floating-point tap coefficients of the original equalizer, and perform low-bit quantization on the floating-point tap coefficients to obtain integer tap coefficients;

[0030] An equalizer construction module, constructing a target equalizer based on the integer tap coefficients;

[0031] The signal processing module is used to compensate the nonlinear distortion of the signal to be processed based on the target equalizer to obtain a restored signal.

[0032] In addition, to achieve the above objectives, the present application also proposes a nonlinear equalization device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the nonlinear equalization method as described above.

[0033] In addition, to achieve the above purpose, the present invention also proposes a storage medium, which is a computer-readable storage medium and stores a computer program. When the computer program is executed by a processor, the steps of the nonlinear equalization method as described above are implemented.

[0034] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the steps of the nonlinear equalization method as described above are implemented.

[0035] The present application provides a nonlinear equalization method, which obtains the floating-point tap coefficients of the original equalizer, performs low-bit quantization on the floating-point tap coefficients to obtain integer tap coefficients; based on the integer tap coefficients, a target equalizer is constructed; based on the target equalizer, the nonlinear distortion of the processed signal is compensated to obtain a restored signal. The present application performs low-bit quantization on the tap coefficients of the equalizer, converts the traditional floating-point numbers into low-bit integer representations, significantly reduces the storage space and computational complexity, and the low-bit quantized equalizer performs nonlinear compensation on the input signal to restore the signal quality, which can optimize the hardware implementation efficiency and reduce power consumption while ensuring the transmission performance, and solves the technical problem that when using an equalizer to compensate for the nonlinear distortion in the IM / DD system signal transmission process, it takes up more storage space and computing resources, and the hardware implementation is more complex. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0037] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0038] Figure 1 This is a flow chart of the first embodiment of the nonlinear equalization method of the present application;

[0039] Figure 2 A schematic diagram of the overall architecture of the nonlinear equalization method provided in Embodiment 2 of the present application;

[0040] Figure 3 A schematic diagram of the V-DFE equalizer principle of the nonlinear equalization method provided in Example 2 of the present application;

[0041] Figure 4 A schematic diagram of the Volterra equalizer principle of the nonlinear equalization method provided in Example 2 of the present application;

[0042] Figure 5 This is a flow chart of Embodiment 2 of the nonlinear equalization method of the present application;

[0043] Figure 6 This is a flow chart of Embodiment 3 of the nonlinear equalization method of the present application;

[0044] Figure 7 This is a schematic diagram of the module structure of the nonlinear equalizer according to an embodiment of the present application;

[0045] Figure 8 Schematic diagram of the device structure of the hardware operating environment involved in the nonlinear equalization method in the embodiment of the present application.

[0046] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0047] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0048] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0049] The main solution of the embodiment of the present application is: obtain the floating-point tap coefficients of the original equalizer, perform low-bit quantization on the floating-point tap coefficients to obtain integer tap coefficients; construct a target equalizer based on the integer tap coefficients; compensate for the nonlinear distortion of the processed signal based on the target equalizer to obtain a restored signal.

[0050] With the rapid development of emerging technologies such as the Internet of Things, cloud computing, artificial intelligence, big data and 5G, not only has the number of data generation and processing tasks increased dramatically, but higher requirements have also been placed on data transmission. In optical fiber communication systems, short-distance data transmission has been widely used. Compared with traditional coherent detection systems, IM / DD systems have become the preferred solution in short-distance optical communication systems due to their small size, low cost, low power consumption and relatively simple system architecture. However, in the process of achieving high-capacity and long-distance transmission, IM / DD systems are prone to serious mixed linear and nonlinear damage due to factors such as frequency chirp, ISI, nonlinear effects caused by the combination of dispersion and square-law direct detection, and inherent nonlinearity of transceivers, thereby limiting the further improvement of the capacity and range of IM / DD transmission systems.

[0051] Nonlinear equalization technology is usually used to compensate for various linear and nonlinear distortions introduced during signal transmission to improve the transmission performance of the system. Commonly used nonlinear equalization technologies include feedforward equalizer, decision feedback equalizer and Volterra series-based equalizer. However, these equalizers require more storage space and computing resources in practical applications, and the hardware implementation is also relatively complex.

[0052] The present application provides a solution, which performs low-bit quantization on the tap coefficients of the equalizer, converts traditional floating-point numbers into low-bit integer representation, significantly reduces storage space and computational complexity, and uses the low-bit quantized equalizer to perform nonlinear compensation on the input signal to restore signal quality. It is possible to optimize hardware implementation efficiency and reduce power consumption while ensuring transmission performance, and solves the technical problem that when using an equalizer to compensate for nonlinear distortion in the signal transmission process of an IM / DD system, a large amount of storage space and computing resources are required, and the hardware implementation is relatively complex.

[0053] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device, a nonlinear equalizer device, etc. that can realize the above functions, and this embodiment does not specifically limit this. The following takes a nonlinear equalizer device as an example to illustrate this embodiment and the following embodiments.

[0054] The present application embodiment provides a nonlinear equalization method, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the nonlinear equalization method of the present application.

[0055] In this embodiment, the nonlinear equalization method includes steps S10 to S30:

[0056] Step S10, obtaining floating-point tap coefficients of the original equalizer, and performing low-bit quantization on the floating-point tap coefficients to obtain integer tap coefficients;

[0057] It should be noted that the original equalizer refers to the traditional equalizer used in the IM / DD system, which can be an FFE equalizer, a DFE equalizer, a Volterra equalizer, etc. This embodiment does not specifically limit this and is selected according to actual needs. Generally speaking, different equalizers use different tap coefficients. The floating-point tap coefficient refers to the tap coefficient represented by a floating-point number (FP), and the integer tap coefficient refers to the tap coefficient represented by an integer, which can be obtained by quantizing the floating-point tap coefficient. In this embodiment, a low-bit quantization method is adopted, and the integer tap coefficient is a tap coefficient represented by a low-bit integer.

[0058] It is understandable that the tap coefficients of traditional equalizers are generally represented by floating-point numbers, which usually require 32 or 64 bits of data storage space. That is, floating-point tap coefficients require a large amount of storage space and computing resources. Especially for high-order nonlinear equalizers, a large number of tap coefficients significantly increases the storage cost and hardware complexity.

[0059] Therefore, this embodiment performs low-bit quantization on the tap coefficients of the equalizer, converts traditional floating-point numbers into low-bit integer representation, and reduces storage space and computational complexity.

[0060] Step S20, constructing a target equalizer based on the integer tap coefficients;

[0061] It should be noted that the target equalizer refers to the target equalizer obtained after low-bit quantization of the tap coefficients, which may be an FFE equalizer, a DFE equalizer, a Volterra equalizer, etc. This embodiment does not specifically limit this and is determined according to the selected original equalizer.

[0062] It can be understood that integer tap coefficients are used instead of original floating-point tap coefficients to construct the corresponding target equalizer. At this time, the target equalizer is a low-bit quantized equalizer, which has converted floating-point numbers into integers for calculation and storage, greatly reducing storage space.

[0063] Step S30, compensating the nonlinear distortion of the signal to be processed based on the target equalizer to obtain a restored signal;

[0064] It should be noted that the signal to be processed refers to the signal to be input into the target equalizer, and the restored signal refers to the signal to be processed after the quality is restored.

[0065] Understandably, reference Figure 2 , the electrical signal is processed by pulse amplitude modulation, and the optical signal is emitted by the directly modulated laser. The optical receiving end of the IM / DD system converts the optical signal into an electrical signal through a photodetector, and performs preliminary processing on the signal through an analog front-end circuit. When the signal is processed in the DSP (Digital Signal Processor), the corresponding signal to be processed is input into the target equalizer. During the transmission of the optical signal in the optical fiber, due to the frequency chirp and dispersion effects, the signal is gradually distorted by nonlinearity. The target equalizer is used to compensate for the nonlinear distortion of the signal to be processed and restore the signal quality. The equalized signal is decoded and the restored data signal is output, that is, the data is recovered.

[0066] In a feasible implementation, step S30 may include steps S301 to S303:

[0067] Step S301, dequantizing the integer tap coefficients to determine the quantization coefficients of the target equalizer;

[0068] It should be noted that the quantization coefficient refers to the coefficient of the nonlinear filter used by the target equalizer to process the processed signal, and can also be considered as the kernel of each order of the target equalizer. When the target equalizer compensates for the nonlinear distortion of the processed signal, in order to use integer tap coefficients, it is necessary to perform an inverse quantization operation to restore the approximate value of the original floating-point tap coefficient.

[0069] Step S302, determining a nonlinear compensation relationship between the signal to be processed and the restored signal based on the quantization coefficient;

[0070] It should be noted that the nonlinear compensation relationship between the signal to be processed and the restored signal is the calculation relationship used by the target equalizer to compensate for the nonlinear distortion of the signal to be processed. Generally speaking, different target equalizers use different nonlinear compensation relationships.

[0071] In a feasible implementation, step S301 may include steps A11 to A13:

[0072] Step A11, when the target equalizer is a Volterra decision feedback equalizer, based on the forward quantization coefficient, determining a first corresponding relationship between the signal to be processed, the forward quantization coefficient and the first filtered signal;

[0073] It should be noted that the Volterra Decision Feedback Equalizer (V-DFE) is an equalizer that combines the Volterra equalizer with the decision feedback equalizer (DFE) to compensate for nonlinear and linear distortion in IM / DD systems. The V-DFE equalizer uses the Volterra series (an extended Taylor series) to process the nonlinear distortion of the IM / DD system, and uses the decision feedback part to reduce inter-symbol interference (ISI), thereby improving the performance of the system. The Volterra decision feedback equalizer consists of two parts: a forward filter and a feedback filter. The forward filter uses the Volterra series to describe the linear and nonlinear behavior of the system, and the feedback filter uses a third-order Volterra model to eliminate inter-symbol interference.

[0074] It can be understood that when the target equalizer is a Volterra decision feedback equalizer, the quantization coefficient includes a forward quantization coefficient and a feedback quantization coefficient, the forward quantization coefficient is the quantization coefficient used by the forward filter, and the feedback quantization coefficient is the quantization coefficient used by the feedback filter. The first filtered signal is the signal data output by the forward filter.

[0075] It should be noted that the first corresponding relationship between the signal to be processed, the forward quantization coefficient and the first filtered signal can be considered as a calculation relationship used by the forward filter to process the input signal to be processed, that is, a calculation relationship of the first filtered signal, as shown below:

[0076]

[0077] In the formula, represents the forward quantization coefficients, which are used to capture linear and nonlinear effects in the input signal. Represents the system memory length, which determines how much historical input the system can capture. The larger the memory length, the better it can capture the impact of the system's historical input on the current output. Indicates a signal to be processed. represents the first filtered signal.

[0078] Step A12, determining a second corresponding relationship between the feedback decision symbol, the feedback quantization coefficient and the second filtered signal based on the feedback quantization coefficient;

[0079] It can be understood that the feedback decision symbol refers to the decided symbol at the feedback moment. The second filtered signal is the signal data output by the feedback filter. The second corresponding relationship between the feedback decision symbol, the feedback quantization coefficient and the second filtered signal can be considered as the calculation relationship used by the feedback filter to process the input feedback decision symbol, that is, the calculation relationship of the second filtered signal, as shown below:

[0080]

[0081] In the formula, represents the feedback quantization coefficient, that is, the Volterra kernel function of the feedback filter, which is used to describe the linear and nonlinear interference in the decided symbols. and Indicates the system memory length, Represents the feedback decision symbol, represents the second filtered signal.

[0082] Step A13: determining a nonlinear compensation relationship between the signal to be processed and the restored signal based on the first corresponding relationship and the second corresponding relationship.

[0083] It should be noted that the reference Figure 3 , when the target equalizer is a Volterra decision feedback equalizer, the nonlinear compensation relationship between the signal to be processed and the restored signal can be expressed as a combination of a forward filter and a feedback filter, that is, the nonlinear compensation relationship is equal to the subtraction of the first corresponding relationship and the second corresponding relationship, as shown below:

[0084]

[0085] In the formula, Indicates the recovery signal. represents the first filtered signal, represents the second filtered signal.

[0086] In another feasible implementation, step S301 may include steps B11 to B12:

[0087] B11, when the target equalizer is a Volterra equalizer, determining a third corresponding relationship between the signal to be processed, the nonlinear quantization coefficient and the restored signal based on the nonlinear quantization coefficient;

[0088] It should be noted that the Volterra equalizer is a tool for compensating distortion in nonlinear systems, and is particularly suitable for nonlinear compensation problems in optical fiber communications. It is based on the Volterra series and can capture the nonlinear behavior and memory effects of the system. The Volterra equalizer can describe and compensate for nonlinear distortion by introducing high-order terms. The nonlinear quantization coefficient is the quantization coefficient used by the nonlinear filter contained in the Volterra equalizer, and can also be considered as the kernel of each order of Volterra. The third correspondence between the signal to be processed, the nonlinear quantization coefficient and the restored signal is the calculation relationship used by the nonlinear filter to process the input signal to be processed.

[0089] It can be understood that, in this embodiment, by using a third-order quantized Volterra equalizer, a third-order nonlinear expansion can be performed on the input signal to capture higher-order nonlinear effects and compensate for more complex nonlinear effects. At this time, the third corresponding relationship is as follows:

[0090]

[0091] In the formula, Indicates a signal to be processed. Indicates the recovery signal. Represents the nonlinear quantization coefficients, which are Volterra's first-order kernel, second-order kernel, and third-order kernel.

[0092] B12: Use the third corresponding relationship as a nonlinear compensation relationship between the signal to be processed and the restored signal.

[0093] Understandably, reference Figure 4 , when the target equalizer is a Volterra equalizer, the nonlinear compensation relationship between the signal to be processed and the restored signal can be expressed using the third corresponding relationship.

[0094] Step S303: obtaining the restored signal based on the signal to be processed and the nonlinear compensation relationship.

[0095] It should be noted that the relevant data is substituted into the nonlinear compensation relationship between the signal to be processed and the restored signal, thereby obtaining the corresponding restored signal.

[0096] This embodiment provides a nonlinear equalization method, which obtains the floating-point tap coefficients of the original equalizer, performs low-bit quantization on the floating-point tap coefficients to obtain integer tap coefficients; constructs a target equalizer based on the integer tap coefficients; and compensates for the nonlinear distortion of the processed signal based on the target equalizer to obtain a restored signal. This embodiment performs low-bit quantization on the tap coefficients of the equalizer, converts traditional floating-point numbers into low-bit integer representation, significantly reduces storage space and computational complexity, and uses the low-bit quantized equalizer to perform nonlinear compensation on the input signal to restore signal quality, which can optimize hardware implementation efficiency and reduce power consumption while ensuring transmission performance.

[0097] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can refer to the above introduction, and will not be repeated later. Figure 5 , step S10 may include step S101:

[0098] Step S101, obtaining floating-point tap coefficients of an original equalizer, and performing low-bit uniform quantization on the floating-point tap coefficients to obtain integer tap coefficients;

[0099] It should be noted that this embodiment uses a low-bit uniform quantization method to process the floating-point tap coefficients, and the step size used for quantization in this process is the same.

[0100] In a feasible implementation, step S101 may include: obtaining a low-order uniform quantization mapping relationship between a floating-point tap coefficient, a scale factor, a zero-point offset, a number of quantization bits and an integer tap coefficient; and determining the integer tap coefficient based on the floating-point tap coefficient, the scale factor, the zero-point offset, the number of quantization bits and the low-order uniform quantization mapping relationship.

[0101] It should be noted that the low-bit uniform quantization mapping relationship between the floating-point tap coefficient, the scale factor, the zero offset, the number of quantization bits and the integer tap coefficient is the calculation relationship used by the low-bit uniform quantization, as shown below:

[0102]

[0103] In the formula, Represents the integer tap coefficients obtained by low-bit uniform quantization, represents the floating point tap coefficients, represents the scale factor, Indicates the number of quantization bits, Indicates the zero point offset. In this embodiment , Indicates the nearest integer operation. Represents a function that limits the value to a specified range. .

[0104] It can be understood that the scale factor is related to the maximum value of the floating-point tap coefficient, the minimum value of the floating-point tap coefficient, and the number of quantization bits. The calculation relationship is as follows:

[0105]

[0106] In the formula, represents the scale factor, Indicates the number of quantization bits, Indicates the maximum value of the floating-point tap coefficient, Represents the minimum value of a floating-point tap coefficient.

[0107] It should be understood that by substituting the floating-point tap coefficient, scale factor, zero offset, and number of quantization bits into the above low-bit uniform quantization mapping relationship, the integer tap coefficient obtained through low-bit uniform quantization can be calculated.

[0108] Furthermore, the integer tap coefficients obtained by low-bit uniform quantization are used to perform inverse quantization using the following calculation relationship:

[0109]

[0110] In the formula, represents the value obtained by dequantization, Represents the integer tap coefficients obtained by low-bit uniform quantization, represents the floating point tap coefficients, represents the scale factor, Indicates zero point offset. After dequantization Due to rounding, it does not exactly match .

[0111] This embodiment provides a nonlinear equalization method, which obtains the floating-point tap coefficients of the original equalizer, performs low-bit uniform quantization on the floating-point tap coefficients to obtain integer tap coefficients; constructs a target equalizer based on the integer tap coefficients; and compensates for the nonlinear distortion of the processed signal based on the target equalizer to obtain a restored signal. This embodiment performs low-bit uniform quantization on the tap coefficients of the equalizer, converts traditional floating-point numbers into low-bit integer representation, significantly reduces storage space and computational complexity, and uses the low-bit quantized equalizer to perform nonlinear compensation on the input signal to restore signal quality, which can optimize hardware implementation efficiency and reduce power consumption while ensuring transmission performance.

[0112] Based on the first embodiment of the present application, in the third embodiment of the present application, the same or similar contents as those in the above embodiment can refer to the above introduction, and will not be repeated later. Figure 6 , step S10 may include steps S101'~S102':

[0113] Step S101', determining coefficient quantization accuracy based on characteristic information of the signal to be processed;

[0114] It should be noted that the characteristic information of the signal to be processed refers to the characteristics of the signal to be processed, such as: importance, criticality, complexity, etc., which is not specifically limited in this embodiment. The coefficient quantization accuracy is the accuracy of the tap coefficient when low-bit quantization is performed. In this embodiment, the quantization accuracy is adaptively adjusted according to the characteristics of the signal to be processed.

[0115] Step S102', obtaining floating-point tap coefficients of the original equalizer, and performing low-bit non-uniform quantization on the floating-point tap coefficients based on the coefficient quantization accuracy to obtain integer tap coefficients.

[0116] In a feasible implementation, step S102' may include: obtaining a low-order non-uniform quantization mapping relationship between floating-point tap coefficients, scale factors, zero-point offsets, number of quantization bits and integer tap coefficients; and determining the integer tap coefficients based on the floating-point tap coefficients, scale factors, zero-point offsets, number of quantization bits and the low-order non-uniform quantization mapping relationship.

[0117] It should be noted that this embodiment uses low-bit non-uniform quantization to process the floating-point tap coefficients. In this process, the step size used for quantization is uneven and can be determined according to actual needs. The low-bit non-uniform quantization mapping relationship between the floating-point tap coefficients, scale factors, zero offsets, quantization bits and integer tap coefficients, that is, the calculation relationship used by the low-bit non-uniform quantization, is as follows:

[0118]

[0119] In the formula, Represents the integer tap coefficients obtained by low-bit non-uniform quantization, represents the floating point tap coefficients, represents the scale factor, Indicates the number of quantization bits, Indicates the zero point offset. In this embodiment , Indicates the nearest integer operation. Represents a function that limits the value to a specified range. .

[0120] It can be understood that the scale factor is related to the maximum value of the floating-point tap coefficient, the minimum value of the floating-point tap coefficient, and the number of quantization bits. The calculation relationship is as follows:

[0121]

[0122] In the formula, represents the scale factor, Indicates the number of quantization bits, Indicates the maximum value of the floating-point tap coefficient, Represents the minimum value of a floating-point tap coefficient.

[0123] It should be understood that by substituting the floating-point tap coefficient, scale factor, zero offset, and quantization bit number into the above low-bit non-uniform quantization mapping relationship, the integer tap coefficient obtained by low-bit non-uniform quantization can be calculated. Compared with low-bit uniform quantization, the use of low-bit non-uniform quantization can use higher precision on key tap coefficients, thereby maintaining excellent system performance under low-bit quantization.

[0124] For example, for a Volterra equalizer, if 9-bit quantization (coefficient quantization accuracy) is used, the storage space can be reduced by 71.9%; for a V-DFE equalizer, if 11-bit quantization (coefficient quantization accuracy) is used, the storage space can be reduced by 65.6%.

[0125] Furthermore, the integer tap coefficients obtained by low-bit non-uniform quantization are used to perform inverse quantization using the following calculation relationship:

[0126]

[0127] In the formula, represents the value obtained by dequantization, Represents the integer tap coefficients obtained by low-bit non-uniform quantization, represents the floating point tap coefficients, represents the scale factor, Indicates zero point offset. After dequantization Due to rounding, it does not exactly match .

[0128] This embodiment provides a nonlinear equalization method, which determines the coefficient quantization accuracy based on the characteristic information of the signal to be processed; obtains the floating-point tap coefficients of the original equalizer, and performs low-bit non-uniform quantization on the floating-point tap coefficients based on the coefficient quantization accuracy to obtain integer tap coefficients; constructs a target equalizer based on the integer tap coefficients; and compensates for the nonlinear distortion of the signal to be processed based on the target equalizer to obtain a restored signal. This embodiment performs low-bit non-uniform quantization on the tap coefficients of the equalizer, converts traditional floating-point numbers into low-bit integer representation, has higher precision on the tap coefficients, and significantly reduces storage space and computational complexity. The low-bit quantized equalizer performs nonlinear compensation on the input signal to restore signal quality, which can optimize hardware implementation efficiency and reduce power consumption while ensuring transmission performance.

[0129] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the nonlinear equalization method of the present application. More simple transformations based on this technical concept are all within the protection scope of the present application.

[0130] The present application also provides a nonlinear equalization device, please refer to Figure 7 , the nonlinear equalization device comprises:

[0131] The low-bit quantization module 10 is used to obtain the floating-point tap coefficients of the original equalizer, and perform low-bit quantization on the floating-point tap coefficients to obtain integer tap coefficients.

[0132] The equalizer construction module 20 constructs a target equalizer based on the integer tap coefficients.

[0133] The signal processing module 30 is used to compensate the nonlinear distortion of the signal to be processed based on the target equalizer to obtain a restored signal.

[0134] In a feasible implementation, the low-bit quantization is low-bit uniform quantization, and the low-bit quantization module 10 is also used to obtain floating-point tap coefficients of the original equalizer, perform low-bit uniform quantization on the floating-point tap coefficients, and obtain integer tap coefficients.

[0135] In a feasible implementation manner, the low-bit quantization module 10 is further used to obtain a low-bit uniform quantization mapping relationship between floating-point tap coefficients, scale factors, zero offsets, quantization bit numbers, and integer tap coefficients;

[0136] The integer tap coefficient is determined based on the floating-point tap coefficient, the scale factor, the zero offset, the number of quantization bits, and the low-bit uniform quantization mapping relationship.

[0137] In a feasible implementation manner, the low-bit quantization is low-bit non-uniform quantization, and the low-bit quantization module 10 is further used to determine coefficient quantization accuracy based on characteristic information of the signal to be processed;

[0138] The floating-point tap coefficients of the original equalizer are obtained, and based on the coefficient quantization accuracy, the floating-point tap coefficients are subjected to low-bit non-uniform quantization to obtain integer tap coefficients.

[0139] In a feasible implementation manner, the low-bit quantization module 10 is further used to obtain a low-bit non-uniform quantization mapping relationship between floating-point tap coefficients, scale factors, zero-point offsets, quantization bit numbers, and integer tap coefficients;

[0140] The integer tap coefficient is determined based on the floating-point tap coefficient, the scale factor, the zero offset, the number of quantization bits, and the low-bit non-uniform quantization mapping relationship.

[0141] In a feasible implementation manner, the signal processing module 30 is further configured to perform inverse quantization on the integer tap coefficients to determine the quantization coefficients of the target equalizer;

[0142] Based on the quantization coefficients, determining a nonlinear compensation relationship between the signal to be processed and the restored signal;

[0143] The restored signal is obtained based on the signal to be processed and the nonlinear compensation relationship.

[0144] In a feasible implementation manner, the quantization coefficient includes a forward quantization coefficient and a feedback quantization coefficient, and the signal processing module 30 is further used to determine a first corresponding relationship between the signal to be processed, the forward quantization coefficient and the first filtered signal based on the forward quantization coefficient when the target equalizer is a Volterra decision feedback equalizer;

[0145] Based on the feedback quantization coefficient, determining a second corresponding relationship between the feedback decision symbol, the feedback quantization coefficient and the second filtered signal;

[0146] Based on the first corresponding relationship and the second corresponding relationship, a nonlinear compensation relationship between the signal to be processed and the restored signal is determined.

[0147] The nonlinear equalization device provided by the present application adopts the nonlinear equalization method in the above embodiment, which can solve the technical problem that when using an equalizer to compensate for nonlinear distortion in the signal transmission process of the IM / DD system, more storage space and computing resources are required, and the hardware implementation is relatively complex. Compared with the prior art, the beneficial effects of the nonlinear equalization device provided by the present application are the same as the beneficial effects of the nonlinear equalization method provided by the above embodiment, and other technical features in the nonlinear equalization device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0148] The present application provides a nonlinear equalization device, which includes: at least one processor; and a memory connected to the at least one processor in communication; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the nonlinear equalization method in the above-mentioned embodiment 1.

[0149] Reference below Figure 8 , which shows a schematic diagram of the structure of a nonlinear equalizer device suitable for implementing the embodiment of the present application. The nonlinear equalizer device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 8 The nonlinear equalization device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0150] like Figure 8As shown, the nonlinear equalization device may include a processing device 1001 (such as a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the nonlinear equalization device are also stored. The processing device 1001, ROM1002 and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the nonlinear equalization device to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows a nonlinear equalization device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or have alternatively.

[0151] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0152] The nonlinear equalization device provided by the present application adopts the nonlinear equalization method in the above embodiment, which can solve the technical problem that when using an equalizer to compensate for nonlinear distortion in the signal transmission process of the IM / DD system, more storage space and computing resources are required, and the hardware implementation is relatively complex. Compared with the prior art, the beneficial effects of the nonlinear equalization device provided by the present application are the same as the beneficial effects of the nonlinear equalization method provided by the above embodiment, and other technical features in the nonlinear equalization device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0153] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0154] The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0155] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the nonlinear equalization method in the above-mentioned embodiment.

[0156] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM: Random Access Memory), a read-only memory (ROM: Read Only Memory), an erasable programmable read-only memory (EPROM: Erasable Programmable Read Only Memory or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM: CD-Read Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency: Radio Frequency), etc., or any suitable combination of the above.

[0157] The computer-readable storage medium may be included in the nonlinear equalizer device; or may exist independently without being assembled into the nonlinear equalizer device.

[0158] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by a nonlinear equalizer device, the nonlinear equalizer device: obtains floating-point tap coefficients of an original equalizer, performs low-bit quantization on the floating-point tap coefficients to obtain integer tap coefficients; constructs a target equalizer based on the integer tap coefficients; and compensates for the nonlinear distortion of a processed signal based on the target equalizer to obtain a restored signal.

[0159] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0160] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0161] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0162] The readable storage medium provided by the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned nonlinear equalization method, and can solve the technical problem that when using an equalizer to compensate for nonlinear distortion in the IM / DD system signal transmission process, it takes up more storage space and computing resources, and the hardware implementation is more complicated. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as the beneficial effects of the nonlinear equalization method provided by the above-mentioned embodiment, and will not be repeated here.

[0163] The present application also provides a computer program product, including a computer program, which implements the steps of the above-mentioned nonlinear equalization method when executed by a processor.

[0164] The computer program product provided by the present application can solve the technical problem that when using an equalizer to compensate for nonlinear distortion in the signal transmission process of an IM / DD system, a large amount of storage space and computing resources are required, and the hardware implementation is relatively complex. Compared with the prior art, the beneficial effects of the computer program product provided by the present application are the same as the beneficial effects of the nonlinear equalization method provided by the above embodiment, and will not be described in detail here.

[0165] The above are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect application in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A nonlinear equalization method, characterized in that: The method comprises: Obtaining floating-point tap coefficients of an original equalizer, and performing low-bit quantization on the floating-point tap coefficients to obtain integer tap coefficients; constructing a target equalizer based on the integer tap coefficients; Compensating the nonlinear distortion of the signal to be processed based on the target equalizer to obtain a restored signal; The step of compensating the nonlinear distortion of the signal to be processed based on the target equalizer to obtain a restored signal comprises: De-quantizing the integer tap coefficients to determine quantization coefficients of the target equalizer; Based on the quantization coefficients, determining a nonlinear compensation relationship between the signal to be processed and the restored signal; Based on the signal to be processed and the nonlinear compensation relationship, obtaining the restored signal; When the target equalizer is a Volterra decision feedback equalizer, the quantization coefficient includes a forward quantization coefficient and a feedback quantization coefficient, and the step of determining the nonlinear compensation relationship between the signal to be processed and the restored signal based on the quantization coefficient includes: Based on the forward quantization coefficient, determine a first corresponding relationship between the signal to be processed, the forward quantization coefficient and the first filtered signal; based on the feedback quantization coefficient, determine a second corresponding relationship between the feedback decision symbol, the feedback quantization coefficient and the second filtered signal; based on the first corresponding relationship and the second corresponding relationship, determine a nonlinear compensation relationship between the signal to be processed and the restored signal; When the target equalizer is a Volterra equalizer, the quantization coefficient includes a nonlinear quantization coefficient, and the step of determining the nonlinear compensation relationship between the to-be-processed signal and the restored signal based on the quantization coefficient includes: Based on the nonlinear quantization coefficient, a third corresponding relationship between the signal to be processed, the nonlinear quantization coefficient and the restored signal is determined, and the third corresponding relationship is used as a nonlinear compensation relationship between the signal to be processed and the restored signal.

2. The method according to claim 1, characterized in that The low-bit quantization is low-bit uniform quantization, and the steps of obtaining floating-point tap coefficients of the original equalizer, performing low-bit quantization on the floating-point tap coefficients, and obtaining integer tap coefficients include: The floating-point tap coefficients of the original equalizer are obtained, and low-bit uniform quantization is performed on the floating-point tap coefficients to obtain integer tap coefficients.

3. The method according to claim 2, characterized in that The step of obtaining the floating-point tap coefficients of the original equalizer and performing low-bit uniform quantization on the floating-point tap coefficients to obtain integer tap coefficients comprises: Obtaining a low-order uniform quantization mapping relationship between a floating-point tap coefficient, a scale factor, a zero offset, a quantization bit number, and an integer tap coefficient; The integer tap coefficient is determined based on the floating-point tap coefficient, the scale factor, the zero offset, the number of quantization bits, and the low-bit uniform quantization mapping relationship.

4. The method according to claim 1, characterized in that The low-bit quantization is low-bit non-uniform quantization, and the steps of obtaining floating-point tap coefficients of the original equalizer, performing low-bit quantization on the floating-point tap coefficients, and obtaining integer tap coefficients include: Determining coefficient quantization accuracy based on characteristic information of the signal to be processed; The floating-point tap coefficients of the original equalizer are obtained, and based on the coefficient quantization accuracy, the floating-point tap coefficients are subjected to low-bit non-uniform quantization to obtain integer tap coefficients.

5. The method according to claim 4, characterized in that The step of obtaining the floating-point tap coefficients of the original equalizer and performing low-bit non-uniform quantization on the floating-point tap coefficients based on the coefficient quantization accuracy to obtain integer tap coefficients comprises: Obtaining a low-order non-uniform quantization mapping relationship between a floating-point tap coefficient, a scale factor, a zero offset, a quantization bit number, and an integer tap coefficient; The integer tap coefficient is determined based on the floating-point tap coefficient, the scale factor, the zero offset, the number of quantization bits, and the low-bit non-uniform quantization mapping relationship.

6. A nonlinear equalization device, characterized in that: The device comprises: A low-bit quantization module is used to obtain floating-point tap coefficients of the original equalizer, and perform low-bit quantization on the floating-point tap coefficients to obtain integer tap coefficients; An equalizer construction module, constructing a target equalizer based on the integer tap coefficients; A signal processing module, used for compensating the nonlinear distortion of the signal to be processed based on the target equalizer to obtain a restored signal; The signal processing module is further used to perform inverse quantization on the integer tap coefficients to determine the quantization coefficients of the target equalizer; Based on the quantization coefficients, determining a nonlinear compensation relationship between the signal to be processed and the restored signal; Based on the signal to be processed and the nonlinear compensation relationship, obtaining the restored signal; The signal processing module is further used to determine, when the target equalizer is a Volterra decision feedback equalizer, a first corresponding relationship between the signal to be processed, the forward quantization coefficient and the first filtered signal based on the forward quantization coefficient, determine a second corresponding relationship between the feedback decision symbol, the feedback quantization coefficient and the second filtered signal based on the feedback quantization coefficient, and determine a nonlinear compensation relationship between the signal to be processed and the restored signal based on the first corresponding relationship and the second corresponding relationship; When the target equalizer is a Volterra equalizer, a third corresponding relationship between the signal to be processed, the nonlinear quantization coefficient and the restored signal is determined based on the nonlinear quantization coefficient, and the third corresponding relationship is used as the nonlinear compensation relationship between the signal to be processed and the restored signal.

7. A nonlinear equalization device, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the nonlinear equalization method according to any one of claims 1 to 5.

8. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the nonlinear equalization method according to any one of claims 1 to 5 are implemented.

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