CN117459354A - Self-adaptive equalization device, method, equipment and medium applied to PS-PAM system - Google Patents
Self-adaptive equalization device, method, equipment and medium applied to PS-PAM system Download PDFInfo
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- H—ELECTRICITY
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Abstract
The application provides an adaptive equalization apparatus, method, device and medium for PS-PAM system, comprising: the transmitting module is used for transmitting the pulse amplitude modulation signal based on probability shaping; the preprocessing module is connected with the transmitting module and is used for receiving and preprocessing the pulse amplitude modulation signal based on probability shaping; the self-adaptive equalization module comprises a CMA pre-equalization module and a DDLMS equalization module; and the demapping module is connected with the adaptive equalization module and is used for demapping and decoding the signals subjected to CMA pre-equalization and DDLMS equalization so as to obtain a bit sequence sent by the transmitting end. The self-adaptive equalization device, method, equipment and medium applied to the PS-PAM system have the following beneficial effects: the invention optimizes the error calculation part of the pre-equalization stage CMA method and the decision part of the DDLMS equalization stage. Compared with the problem that the traditional PAM4 equalization method fails in a probability shaping scene, the method is suitable for a probability shaping PAM4 communication system, and the error rate is reduced.
Description
Technical Field
The present disclosure relates to the field of communications technologies, and in particular, to an adaptive equalization apparatus, method, device, and medium applied to a PS-PAM system.
Background
In the direct alignment IMDD system, in order to improve the transmission effect, a higher order modulation format, such as PAM4 or PAM8, is used. But the adjustment granularity is too large to be beneficial to the system application. In coherent systems, probability shaping techniques are of great interest and the symbol rate can be adjusted more flexibly. In recent years, probability shaping technology is also started to be applied to an IMDD system, and better benefits are obtained, for example, compared with PAM8, PS-PAM8 is improved by about 1.2dB in system acceptance sensitivity.
The probability shaping technique may reduce the distance between the QAM modulation format and the shannon limit due to the shaping gain from the gaussian distribution. In order to further increase the transmission capacity of a communication system, probability shaping techniques have been widely studied and applied in coherent optical communication systems.
For intensity modulated direct detection systems, probability shaping techniques have not been applied on a large scale. On the one hand, the direct detection system is different from the coherent detection system in the limiting factors, and in the direct detection system, the gain of probability shaping is not as large as that of the coherent detection system. Another aspect is that some Digital Signal Processing (DSP) algorithms in direct detection systems may fail in a probability shaping scenario. For example, in the case of a relatively large shaping degree, the blind equalization method based on the Constant Modulus Algorithm (CMA) fails for PAM 4. Adaptive equalization algorithms based on decision feedback (DDLMS) also require appropriate corrections. Therefore, there is a need in the art for a solution that can adaptively equalize for probability shaping.
Disclosure of Invention
In view of the above-mentioned drawbacks of the prior art, it is an object of the present application to provide an adaptive equalization apparatus, method, device and medium for a PS-PAM system, for solving the technical problem how to provide an adaptive equalization capable for probability shaping.
To achieve the above and other related objects, a first aspect of the present application provides an adaptive equalization apparatus applied to a PS-PAM system, comprising: the transmitting module is used for transmitting the pulse amplitude modulation signal based on probability shaping; the preprocessing module is connected with the transmitting module and is used for receiving and preprocessing the pulse amplitude modulation signal based on probability shaping; the self-adaptive equalization module comprises a CMA pre-equalization module and a DDLMS equalization module; the CMA pre-equalization module is used for calculating a CMA pre-equalization error so as to update the tap coefficient of the filter once; the DDLMS equalization module is used for calculating DDLMS equalization errors so as to update the tap coefficients of the filter again; and the demapping module is connected with the adaptive equalization module and is used for demapping and decoding the signals subjected to CMA pre-equalization and DDLMS equalization so as to obtain a bit sequence sent by the transmitting end.
In some embodiments of the first aspect of the present application, the transmitting module calculates an optimal probability distribution result of each symbol of the PS-PAM signal with a pair distribution based on a preset probability distribution algorithm.
In some embodiments of the first aspect of the present application, the calculating manner of the preset probability distribution algorithm includes:
wherein x is a transmitting symbol corresponding to each level of the PS-PAM modulation signal; lambda is the shaping factor, lambda epsilon (0, 1); a is a coefficient associated with the level of the PAM modulated signal, where each negative level corresponds to the same a value and each positive level corresponds to the same a value.
In some embodiments of the first aspect of the present application, the preprocessing module includes a channel transmission module, a clipping module, and a clock data recovery module; the channel transmission module is connected with the transmitting module and is used for receiving the pulse amplitude modulation signal based on probability shaping; the amplitude limiting module is connected with the channel transmission module and is used for carrying out amplitude limiting processing on the pulse amplitude modulation signal based on probability shaping; the clock data recovery module is connected with the amplitude limiting module and is used for providing a clock signal so as to keep the receiving signal consistent with the sending signal.
In some embodiments of the first aspect of the present application, the CMA pre-equalization module is configured to calculate a CMA pre-equalization error to update the tap coefficients of the filter once, and the process includes: initializing and setting corresponding filter tap coefficients according to the self-adaptive filter tap length information; filtering the input signal based on the initially set filter tap coefficients to obtain a filtered output signal; and calculating a corresponding CMA pre-equalization error based on the filtered output signal, and updating the tap coefficient of the filter once according to the CMA pre-equalization error, the input signal before filtering and the output signal after filtering.
In some embodiments of the first aspect of the present application, the CMA equalization error calculating method includes:
wherein err is cma Representing CMA pre-equalization error; y represents the filtered output signal.
In some embodiments of the first aspect of the present application, the updating the tap coefficients of the filter once according to the CMA pre-equalization error, the pre-filtered input signal and the filtered output signal includes: introducing a coefficient updating step length; and taking the product of the coefficient updating step length and the CMA pre-equalization error, the input signal before filtering and the output signal after filtering as a coefficient updating part of one-time updating.
In some embodiments of the first aspect of the present application, the CMA pre-equalization module further performs the following after performing pre-equalization: selecting the number of PS-PAM transmitting symbols received in a preset period; calculating a mean square error value of an output signal of a CMA pre-equalization stage based on the number of PS-PAM transmission symbols in a preset period; after the calculated mean square error value exceeds a preset value, the method can enter DDLMS equalization.
In some embodiments of the first aspect of the present application, the calculating manner of the DDLMS equalization error includes: and determining a range in which the pre-equalized output signal falls according to comparison of the pre-equalized output signal and a plurality of parameter thresholds, and calculating a DDLMS equalization error corresponding to the range.
In some embodiments of the first aspect of the present application, the number of parameter thresholds includes a first parameter threshold, a second parameter threshold, and a third parameter threshold arranged in ascending order; and the second parameter threshold value and the variance of the shaping factor and the Gaussian white noise are in positive correlation.
In some embodiments of the first aspect of the present application, the DDLMS equalization error is calculated as follows:
wherein err is ddlms Represents DDLMS equalization error; y' represents the signal after CMA pre-equalization; lambda represents the shaping factor; delta 2 Representing the variance of gaussian white noise.
In some embodiments of the first aspect of the present application, the manner in which the DDLMS equalization module continues to update the filter tap coefficients according to the DDLMS equalization error includes: introducing a coefficient updating step length; and taking the product of the coefficient updating step length, the DDLMS equalization error and the input signal before filtering as a coefficient updating part updated again.
To achieve the above and other related objects, a second aspect of the present application provides an adaptive equalization method applied to a PS-PAM system, including: receiving and preprocessing a pulse amplitude modulation signal based on probability shaping; calculating a CMA pre-equalization error to update the filter tap coefficients once; and calculating DDLMS equalization error to update the filter tap coefficient again; and performing demapping and decoding processing on the signals subjected to CMA pre-equalization and DDLMS equalization to obtain a bit sequence sent by a transmitting end.
To achieve the above and other related objects, a third aspect of the present application provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the adaptive equalization method applied to a PS-PAM system.
To achieve the above and other related objects, a fourth aspect of the present application provides a computer apparatus, comprising: a processor and a memory; the memory is used for storing a computer program, and the processor is used for executing the computer program stored by the memory, so that the terminal executes the adaptive equalization method applied to the PS-PAM system.
As described above, the adaptive equalization device, method, apparatus and medium applied to PS-PAM system of the present application have the following beneficial effects: the invention optimizes the error calculation part of the pre-equalization stage CMA method and the decision part of the DDLMS equalization stage. Therefore, compared with the problem that the traditional PAM4 equalization method fails in a probability shaping scene, the PS-PAM system provided by the invention can be suitable for the probability shaping PAM4 communication system, effectively compensates inter-symbol crosstalk between symbols, and reduces the system Bit Error Rate (BER).
Drawings
Fig. 1 is a schematic structural diagram of an adaptive equalization apparatus applied to a PS-PAM system according to an embodiment of the present application.
Fig. 2 shows a probability distribution diagram of 4 levels of a PS-PAM4 modulated signal in an embodiment of the present application.
Fig. 3 is a schematic flow chart of CMA pre-equalization processing in an embodiment of the present application.
Fig. 4 is a schematic structural diagram of an adaptive filter according to an embodiment of the present application.
Fig. 5A shows a system bit error rate BER and received optical power curve for PS-PAM4 signals.
Fig. 5B shows a probability distribution histogram of PS-PAM after pre-equalization prior to improvement of the present invention.
Fig. 5C shows a probability distribution histogram of PS-PAM after pre-equalization modified according to the present invention.
Fig. 6 is a schematic flow chart of an adaptive equalization method applied to a PS-PAM system according to an embodiment of the present application.
Fig. 7 is a schematic structural diagram of a computer device according to an embodiment of the present application.
Detailed Description
Other advantages and effects of the present application will become apparent to those skilled in the art from the present disclosure, when the following description of the embodiments is taken in conjunction with the accompanying drawings. The present application may be embodied or carried out in other specific embodiments, and the details of the present application may be modified or changed from various points of view and applications without departing from the spirit of the present application. It should be noted that the following embodiments and features in the embodiments may be combined with each other without conflict.
It is noted that in the following description, reference is made to the accompanying drawings, which describe several embodiments of the present application. It is to be understood that other embodiments may be utilized and that mechanical, structural, electrical, and operational changes may be made without departing from the spirit and scope of the present application. The following detailed description is not to be taken in a limiting sense, and the scope of embodiments of the present application is defined only by the claims of the issued patent. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. Spatially relative terms, such as "upper," "lower," "left," "right," "lower," "upper," and the like, may be used herein to facilitate a description of one element or feature as illustrated in the figures relative to another element or feature.
In this application, unless specifically stated and limited otherwise, the terms "mounted," "connected," "secured," "held," and the like are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the terms in this application will be understood by those of ordinary skill in the art as the case may be.
Furthermore, as used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context indicates otherwise. It will be further understood that the terms "comprises," "comprising," "includes," and/or "including" specify the presence of stated features, operations, elements, components, items, categories, and/or groups, but do not preclude the presence, presence or addition of one or more other features, operations, elements, components, items, categories, and/or groups. The terms "or" and/or "as used herein are to be construed as inclusive, or meaning any one or any combination. Thus, "A, B or C" or "A, B and/or C" means "any of the following: a, A is as follows; b, a step of preparing a composite material; c, performing operation; a and B; a and C; b and C; A. b and C). An exception to this definition will occur only when a combination of elements, functions or operations are in some way inherently mutually exclusive.
In order to solve the problems in the background art, the present invention provides an adaptive equalization X that is intended to be applied to PS-PAM systems. Meanwhile, in order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions in the embodiments of the present invention will be further described in detail by the following examples with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Before explaining the present invention in further detail, terms and terminology involved in the embodiments of the present invention will be explained, and the terms and terminology involved in the embodiments of the present invention are applicable to the following explanation:
<1> probability shaping (Peobabilistic Shaping, PS): a novel modulation coding technology with low complexity and high flexibility; the principle of the probability shaping technology is that constellation points of the outer ring of the constellation are mapped onto constellation points close to the origin of the constellation with certain probability and rules and are transmitted.
<2> pam4 (4 Pulse Amplitude Modulation): the hot signal transmission technology, which is high-speed signal interconnection in the next generation data center, is widely applied to the transmission of electrical signals or optical signals of 200G/400G interfaces.
<3> intensity modulated direct detection system (IM-DD): envelope detection is directly carried out on the intensity-modulated optical carrier wireless signal, namely the original signal can be recovered by directly passing through the photoelectric detector; the optical fiber communication system is characterized in that the transmitting end modulates the intensity of an optical carrier by using a signal, and the receiving end directly detects the optical signal by using a monitor.
<4> sign of pam waveform: PAM waveforms start with ordinary digital data bits and have to be grouped into symbols before these 1 and 0's are mapped to amplitude multipliers. A symbol is a unit of transmission information containing one or more bits. In Amplitude Shift Keying (ASK), each symbol represents a binary 1 or a binary 0.
<5> cdr (Clock Data Recovery): clock data recovery is a key feature of high performance systems. Data recovery is a fundamental functional block of remote and dense wavelength division multiplexed optical networks, as well as high-speed inter-chip and backplane connections, and fibre channel, wireless and storage area networks.
<6> bit error rate (BER: biterror): is an index for measuring the accuracy of data transmission in a specified time, and the calculation mode is as follows: bit error rate = bit error in transmission/total number of codes transmitted 100%.
<7> cma (Constant Modulus Algorithm): the constant modulus blind equalization algorithm is one of the blind equalization algorithms.
<8> ddlms (direct decision least mean square): the minimum mean square error algorithm based on decision guidance is one of the blind equalization algorithms.
<9> shaping factor: representing the degree of probability shaping, the value interval is 0-1, and the larger the value is, the higher the shaping degree is.
<10> gaussian white noise (White Gaussian Noise): it means that the amplitude distribution follows a gaussian distribution and the power spectral density follows a uniformly distributed noise. White gaussian noise means that all frequency components from minus infinity to plus infinity are contained in a signal, and the weights of the frequency components in the signal are the same.
The embodiment of the invention provides an adaptive equalization method applied to a PS-PAM system, a device applied to the adaptive equalization method of the PS-PAM system and a storage medium storing an executable program for realizing the adaptive equalization method applied to the PS-PAM system. With respect to implementation of the adaptive equalization apparatus applied to the PS-PAM system, an exemplary implementation scenario of the adaptive equalization applied to the PS-PAM system will be described.
As shown in fig. 1, a schematic structural diagram of an adaptive equalization apparatus applied to a PS-PAM system in an embodiment of the present invention is shown. The adaptive equalization apparatus applied to the PS-PAM system described in this embodiment includes: a transmitting module 101, a preprocessing module 102, an adaptive equalization module 103 and a demapping module 104.
The transmitting module 101 is configured to transmit a pulse amplitude modulated signal based on probability shaping. It should be understood that the pulse amplitude modulated signal based on probability shaping may be simply referred to as a PS-PAM signal, including but not limited to a quaternary pulse amplitude modulated signal based on probability shaping PS-PAM4 or an octal pulse amplitude modulated signal based on probability shaping PS-PAM8, etc. For ease of description, the PS-PAM signal appearing hereinafter means a pulse amplitude modulation signal based on probability shaping, the PS-PAM4 signal means a quaternary pulse amplitude modulation signal based on probability shaping, and the PS-PAM8 signal means an octal pulse amplitude modulation signal based on probability shaping.
In the embodiment of the present invention, the transmitting module 101 calculates an optimal probability distribution result of each symbol of the PS-PAM signal with a pair distribution based on a preset probability distribution algorithm.
Further, the preset probability distribution algorithm includes the following steps:
wherein x is a transmitting symbol corresponding to each level of the PS-PAM modulation signal; lambda is the shaping factor, lambda epsilon (0, 1); a is a coefficient associated with the level of the PAM modulated signal, where each negative level corresponds to the same a value and each positive level corresponds to the same a value.
By way of example, the following description will take the procedure of the optimal probability distribution of each symbol of the PS-PAM4 modulation signal as an example, and the 4 levels of the PS-PAM4 modulation signal correspond to the transmitted symbols-3, -1, +1, +3 in order from small to large, and the optimal probability distribution is calculated as follows:
when the symbol bit x= -3 or x= -1 is transmitted, the value of the coefficient a is 1; and when the symbol x= +1 or x= +3 is transmitted, the value of the coefficient a is 3. For example, the rounding factor λ=0.24, then the probability distribution of 4 levels of the PS-PAM4 modulated signal is shown in fig. 2, where the transmission symbols x= -3, x= -1 are calculated to have a corresponding probability value of 0.436, and the transmission symbols x= +1, x= +3 are calculated to have a corresponding probability value of 0.0634.
It is worth noting that the above examples are provided for illustrative purposes and should not be construed as limiting. For example, the PS-PAM modulation signal can be a PS-PAM4 modulation signal or a PS-PAM8 modulation signal; the PS-PAM4 modulated signal corresponds to 4 levels and the PS-PAM8 modulated signal corresponds to 8 levels. The value of λ is not limited to 0.24 in the above example, and practically any value in the range of (0, 1) can be taken.
In the embodiment of the present invention, the preprocessing module 102 specifically includes a channel transmission module 102A, a clipping module 102B and a clock data recovery module 102C. The channel transmission module 102A is connected to the transmitting module 101 for receiving the pulse amplitude modulated signal based on probability shaping. The limiting module 102B is connected to the channel transmission module 102A, and the limiting module 102B may be, for example, a limiter, which is a circuit capable of flattening the signal voltage amplitude according to a limited range, and is used to limit the output signal amplitude within a certain range, that is, when the input voltage exceeds or falls below a certain reference value, the output voltage is limited to a certain level and no longer varies with the input voltage; taking the PS-PAM4 symbol as an example, represented by different voltage levels, three voltage threshold changing slicers are required to detect PAM4 different amplitude levels. The clock data recovery module 102C is connected to the clipping module 102B, and the clock data recovery module 102C may employ a baud rate clock data recovery Circuit (CDR), such as a CDR based on a Mueller-Mueller phase detector or a CDR based on a minimum mean square error phase monitor.
In the embodiment of the present invention, the adaptive equalization module 103 includes a CMA pre-equalization module 103A and a DDLMS equalization module 103B, which will be explained and illustrated below.
The CMA pre-equalization module 103A is connected to the preprocessing module 102 to receive the preprocessed PS-PAM4 signal and perform CMA pre-equalization processing. Note that CMA (Constant Modulus Algorithm) is a constant modulus blind equalization algorithm. In high-speed wireless communication, serious intersymbol interference can be generated at a receiving end due to the influence of channel fading, multipath propagation and the like, so that the error rate of a system is increased; in order to overcome intersymbol interference and improve the performance of the system, an equalization technique is adopted at the receiving end, including an adaptive equalization technique based on a training sequence or a blind equalization technique without using a training sequence.
In this embodiment, the CMA pre-equalization process is shown in fig. 3, and includes the following steps:
step S31: and initializing and setting corresponding filter tap coefficients according to the adaptive filter tap length information.
It should be understood that an adaptive filter is a filter that uses an adaptive algorithm to change the parameters and structure of the filter according to environmental changes. For ease of understanding by those skilled in the art, the principle of the adaptive filter is described in connection with fig. 4: the input signal x (n) passes through a parameter-adjustable digital filter to generate an output signal y (n), the output signal y (n) is compared with the expected signal d (n) to form an error signal e (n), the filter parameters are adjusted through an adaptive algorithm, and finally the mean square value of e (n) is minimized. The adaptive filter can automatically adjust the filter parameters at the current time by using the results of the filter parameters obtained at the previous time to adapt to the unknown or time-varying statistical characteristics of the signal and noise, thereby realizing optimal filtering. The adaptive filter does not need prior knowledge about the input signal, has small calculation amount and is suitable for real-time processing.
Step S32: and filtering the input signal based on the initially set filter tap coefficients to obtain a filtered output signal.
In some examples, the filtering process is performed on the input signal based on the initial filter tap coefficients to obtain a filtered output signal, and the process includes: and (3) performing linear convolution calculation on the time domain discrete input signal x (n) and the filter tap coefficient h (n), wherein a convolution result y (n) is the filtered output signal. The mode of linear convolution calculation of the time domain discrete input signal x (n) and the filter tap coefficient h (n) is as follows:
wherein y represents the filtered output signal; x represents the input signal before filtering; h represents the filter tap coefficients.
Step S33: and calculating a corresponding CMA pre-equalization error based on the filtered output signal, and updating the tap coefficient of the filter once according to the CMA pre-equalization error, the input signal before filtering and the output signal after filtering.
In some examples, the computing the corresponding CMA pre-equalization error based on the filtered output signal includes:
wherein err is cma Representing CMA pre-equalization error; y represents the filtered output signal.
In some examples, updating the filter tap coefficients according to the CMA pre-equalization error, pre-filtered input signal, and filtered output signal includes: introducing a coefficient updating step length; and taking the product of the coefficient updating step length and the CMA pre-equalization error, the input signal before filtering and the output signal after filtering as a coefficient updating part.
Illustratively, the CMA pre-equalization stage updates the filter tap coefficients as follows:
h′＝h+u·err cma x.y; formula (4)
Where h' represents the filter tap coefficient after one update, h represents the filter tap coefficient before update, u represents the coefficient update step size, x represents the input signal before filtering, and y represents the output signal after filtering.
Preferably, the CMA pre-equalization module 103A further performs the following after performing pre-equalization: selecting the number of PS-PAM transmitting symbols received in a preset period; calculating a mean square error value of an output signal of a CMA pre-equalization stage based on the number of PS-PAM transmission symbols in a preset period; after the calculated mean square error value exceeds a preset value, the method can enter DDLMS equalization.
Illustratively: firstly, a period is set, the number of received PS-PAM4 transmission symbols in the period is n (for example, n is 1024 or other, preferably), and a mean square error value MSE of an output signal of a CMA pre-equalization stage is calculated as follows:
After calculating a mean square error value MSE, comparing the MSE with a preset threshold; if the MSE is smaller than the preset threshold, the CMA pre-equalization is not achieved to the expected effect, and the CMA pre-equalization still needs to be continued, and the next stage should not be directly switched; if the MSE is greater than or equal to the preset threshold, then the CMA pre-equalization is completed and the next stage may be switched.
The DDLMS equalizing module 103B is connected to the CMA pre-equalizing module 103A, and is configured to receive the signal after CMA pre-equalization and calculate a corresponding DDLMS equalizing error according to the signal, so as to update the tap coefficient of the filter again according to the DDLMS equalizing error. It should be understood that DDLMS (direct decision least mean square) is a blind equalization algorithm, meaning a decision directed based minimum mean square error algorithm, which does not require a training sequence.
In some examples, DDLMS equalization module 103B receives the CMA pre-equalized signal and calculates a corresponding DDLMS equalization error therefrom, the process comprising: and determining a range in which the pre-equalized output signal falls according to comparison of the pre-equalized output signal and a plurality of parameter thresholds, and calculating a DDLMS equalization error corresponding to the range.
Further, the plurality of parameter thresholds comprise a first parameter threshold, a second parameter threshold and a third parameter threshold which are arranged in ascending order; and the second parameter threshold value and the variance of the shaping factor and the Gaussian white noise are in positive correlation.
Illustratively, calculating the error of the output signal in the DDLMS equalization stage uses the following formula:
wherein err is ddlms Represents DDLMS equalization error; y' represents the signal after CMA pre-equalization; lambda represents the shaping factor; delta 2 Representing the variance of gaussian white noise.
In some examples, the manner in which the DDLMS equalization module 103B continues to update the filter tap coefficients based on the DDLMS equalization error includes:
h″＝h′+u·err ddlms x; formula (7)
Where h "represents the filter tap coefficients updated again, h' represents the filter tap coefficients updated once, u represents the coefficient update step size, and x represents the input signal before filtering.
The demapping module 104 is connected to the adaptive equalization module 103, and specifically connected to the DDLMS equalization module 103B in the adaptive equalization module 103, and is configured to demap and decode the signal after CMA pre-equalization and DDLMS equalization to obtain a bit sequence sent by the transmitting end.
The structure and implementation process of the adaptive equalization device applied to the PS-PAM system provided in the embodiment of the present invention are described in detail above, and compared with the conventional PAM4 adaptive equalization scheme, the error calculation portion of the pre-equalization stage CMA method is optimized, and the decision portion of the DDLMS equalization stage is optimized. Therefore, compared with the problem that the traditional PAM4 equalization method fails in a probability shaping scene, the PS-PAM system provided by the invention can be suitable for the probability shaping PAM4 communication system, effectively compensates inter-symbol crosstalk between symbols, and reduces the system Bit Error Rate (BER). It should be noted that, the technical scheme of the invention does not mechanically combine the two technologies of probability shaping and adaptive equalization, but rather, the invention is specially aimed at the original adaptive equalization algorithm in order to be applied to a probability shaping system, and the error calculation mode in the method is adaptively and optimally adjusted.
Further, in order to facilitate a better understanding of the technical solution of the present invention by a person skilled in the art, and also to clearly illustrate the technical effects of the technical solution of the present invention, the following description refers to the technical effects of the technical solution of the present invention with reference to fig. 5A, 5B, and 5C.
FIG. 5A shows a system bit error rate BER and received optical power curve of a PS-PAM4 signal; FIG. 5B shows a probability distribution histogram of PS-PAM after pre-equalization prior to improvement of the present invention; fig. 5C shows a probability distribution histogram of PS-PAM after pre-equalization modified in accordance with the present invention.
In the above example, given a system bit error rate BER and a received optical power curve of 56GBd uniform PAM4 signal and a corresponding PS-PAM4 signal of 78.8GBd when the shaping factor is 0.24, the net rates of both are 112Gb/s, and the performance improvement of PS-PAM4 compared to uniform PAM4 is 1.2dB under the error correction threshold corresponding to KP4 (corresponding to 1.00E-4 on the ordinate of fig. 5A), the difference between the two is about 1.2dB, referring to the point on the ps_pam+the equalization curve corresponding to 1.00E-4 on the ordinate of fig. 5A, and the point on the corresponding uniform pam4+cma equalization curve. Whereas if a conventional CMA equalization scheme is employed, PS-PAM4 cannot converge due to algorithm failure.
It should be noted that: the adaptive equalization apparatus applied to the PS-PAM system provided in the above embodiment is only exemplified by the division of the above program modules when the adaptive equalization apparatus applied to the PS-PAM system is performed, and in practical application, the process allocation may be performed by different program modules according to needs, that is, the internal structure of the apparatus is divided into different program modules to complete all or part of the processes described above.
As shown in fig. 6, a flow chart of an adaptive equalization method applied to a PS-PAM system in an embodiment of the present invention is shown, and the adaptive equalization apparatus applied above includes the following steps:
step S61: a pulse amplitude modulated signal based on probability shaping is received and preprocessed.
In some examples, the method further comprises: and calculating to obtain the optimal probability distribution result of each symbol of the PS-PAM signal with the paired distribution based on a preset probability distribution algorithm.
Further, the calculation mode of the preset probability distribution algorithm comprises：Wherein x is a transmitting symbol corresponding to each level of the PS-PAM modulation signal; lambda is the shaping factor, lambda epsilon (0, 1); a is a coefficient associated with the level of the PAM modulated signal, where each negative level corresponds to the same a value and each positive level corresponds to the same a value.
In some examples, preprocessing includes: performing amplitude limiting processing on the pulse amplitude modulation signal based on probability shaping; a clock signal is provided to keep the received signal consistent with the transmitted signal.
Step S62: calculating a CMA pre-equalization error to update the filter tap coefficients once; and calculating DDLMS equalization error to update the filter tap coefficients again.
In some examples, the calculating CMA pre-equalization errors to update the filter tap coefficients once includes: initializing and setting corresponding filter tap coefficients according to the self-adaptive filter tap length information; filtering the input signal based on the initially set filter tap coefficients to obtain a filtered output signal; and calculating a corresponding CMA pre-equalization error based on the filtered output signal, and updating the tap coefficient of the filter once according to the CMA pre-equalization error, the input signal before filtering and the output signal after filtering.
Further, the calculating method of the CMA equalization error includes:wherein err is cma Representing CMA pre-equalization error; y represents the filtered output signal.
In some examples, updating the filter tap coefficients once based on the CMA pre-equalization error, the pre-filtered input signal, and the filtered output signal includes: introducing a coefficient updating step length; and taking the product of the coefficient updating step length and the CMA pre-equalization error, the input signal before filtering and the output signal after filtering as a coefficient updating part of one-time updating.
In some examples, the CMA pre-equalization module also performs the following after performing pre-equalization: selecting the number of PS-PAM transmitting symbols received in a preset period; calculating a mean square error value of an output signal of a CMA pre-equalization stage based on the number of PS-PAM transmission symbols in a preset period; after the calculated mean square error value exceeds a preset value, the method can enter DDLMS equalization.
In some examples, the calculation method of the DDLMS equalization error includes: and determining a range in which the pre-equalized output signal falls according to comparison of the pre-equalized output signal and a plurality of parameter thresholds, and calculating a DDLMS equalization error corresponding to the range.
The parameter thresholds comprise a first parameter threshold, a second parameter threshold and a third parameter threshold which are arranged in ascending order; and the second parameter threshold value and the variance of the shaping factor and the Gaussian white noise are in positive correlation.
Illustratively, the DDLMS equalization error is calculated as follows:
wherein err is ddlms Represents DDLMS equalization error; y' represents the signal after CMA pre-equalization; lambda represents the shaping factor; delta 2 Representing the variance of gaussian white noise.
In some examples, the manner in which the DDLMS equalization module continues to update the filter tap coefficients based on the DDLMS equalization error includes: introducing a coefficient updating step length; and taking the product of the coefficient updating step length, the DDLMS equalization error and the input signal before filtering as a coefficient updating part updated again.
Step S63: and performing demapping and decoding processing on the signals subjected to CMA pre-equalization and DDLMS equalization to obtain a bit sequence sent by a transmitting end.
It should be noted that, the implementation manner and principle of the adaptive equalization method applied to the PS-PAM system provided in the embodiment of the present invention are similar to those of the adaptive equalization device applied to the PS-PAM system, and belong to the same technical concept, so that the description is omitted.
Referring to fig. 7, referring to a hardware structure of a computer device, an optional hardware structure schematic diagram of a computer device 700 provided in an embodiment of the present invention may be shown, where the terminal 700 may be a mobile phone, a computer device, a tablet device, a personal digital processing device, a factory background processing device, etc. The computer device 700 includes: at least one processor 701, memory 702, at least one network interface 704, and a user interface 706. The various components in the device are coupled together by a bus system 705. It is to be appreciated that the bus system 705 is employed to facilitate connection communications between these components. The bus system 705 includes a power bus, a control bus, and a status signal bus in addition to the data bus. But for clarity of illustration the various buses are labeled as bus systems in fig. 7.
The user interface 706 may include, among other things, a display, keyboard, mouse, trackball, click gun, keys, buttons, touch pad, or touch screen, etc.
It is to be appreciated that the memory 702 can be either volatile memory or nonvolatile memory, and can include both volatile and nonvolatile memory. The nonvolatile Memory may be a Read Only Memory (ROM), a programmable Read Only Memory (PROM, programmable Read-Only Memory), which serves as an external cache, among others. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM, static Random Access Memory), synchronous static random access memory (SSRAM, synchronous Static Random Access Memory). The memory described by embodiments of the present invention is intended to comprise, without being limited to, these and any other suitable types of memory.
The memory 702 in embodiments of the invention is used to store various categories of data to support the operation of the computer device 700. Examples of such data include: any executable programs for operating on the computer device 700, such as the operating system 7021 and application programs 7022; the operating system 7021 contains various system programs, such as a framework layer, a core library layer, a driver layer, etc., for implementing various basic services and handling hardware-based tasks. The application programs 7022 may include various application programs such as a media player (MediaPlayer), a Browser (Browser), and the like for implementing various application services. The adaptive equalization method applied to the PS-PAM system provided by the embodiment of the present invention may be included in the application 7022.
The method disclosed in the above embodiment of the present invention may be applied to the processor 701 or implemented by the processor 701. The processor 701 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in the processor 701 or by instructions in the form of software. The processor 701 may be a general purpose processor, a digital signal processor (DSP, digital Signal Processor), or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. The processor 701 may implement or perform the methods, steps, and logic blocks disclosed in embodiments of the present invention. The general purpose processor 701 may be a microprocessor or any conventional processor or the like. The steps of the accessory optimization method provided by the embodiment of the invention can be directly embodied as the execution completion of the hardware decoding processor or the execution completion of the hardware and software module combination execution in the decoding processor. The software modules may be located in a storage medium having memory and a processor reading information from the memory and performing the steps of the method in combination with hardware.
In an exemplary embodiment, the computer device 700 may be implemented by one or more application specific integrated circuits (ASIC, application Specific Integrated Circuit), DSPs, programmable logic devices (PLDs, programmable Logic Device), complex programmable logic devices (CPLDs, complex Programmable LogicDevice) for performing the aforementioned methods.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the method embodiments described above may be performed by computer program related hardware. The aforementioned computer program may be stored in a computer readable storage medium. The program, when executed, performs steps including the method embodiments described above; and the aforementioned storage medium includes: various media that can store program code, such as ROM, RAM, magnetic or optical disks.
In the embodiments provided herein, the computer-readable storage medium may include read-only memory, random-access memory, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, flash memory, U-disk, removable hard disk, or any other medium that can be used to store desired program code in the form of instructions or data structures and that can be accessed by a computer. In addition, any connection is properly termed a computer-readable medium. For example, if the instructions are transmitted from a website, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, digital Subscriber Line (DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. It should be understood, however, that computer-readable and data storage media do not include connections, carrier waves, signals, or other transitory media, but are intended to be directed to non-transitory, tangible storage media. Disk and disc, as used herein, includes Compact Disc (CD), laser disc, optical disc, digital Versatile Disc (DVD), floppy disk and blu-ray disc where disks usually reproduce data magnetically, while discs reproduce data optically with lasers.
In summary, the present application provides an adaptive equalization method, apparatus, terminal and medium for a PS-PAM system, where the present invention optimizes the error calculation portion of the CMA method in the pre-equalization stage and optimizes the decision portion of the DDLMS equalization stage. Therefore, compared with the problem that the traditional PAM4 equalization method fails in a probability shaping scene, the PS-PAM system provided by the invention can be suitable for the probability shaping PAM4 communication system, effectively compensates inter-symbol crosstalk between symbols, and reduces the system Bit Error Rate (BER). Therefore, the method effectively overcomes various defects in the prior art and has high industrial utilization value.
The foregoing embodiments are merely illustrative of the principles of the present application and their effectiveness, and are not intended to limit the application. Modifications and variations may be made to the above-described embodiments by those of ordinary skill in the art without departing from the spirit and scope of the present application. Accordingly, it is intended that all equivalent modifications and variations which may be accomplished by persons skilled in the art without departing from the spirit and technical spirit of the disclosure be covered by the claims of this application.
Claims (15)
1. An adaptive equalization apparatus for use in a PS-PAM system, comprising:
The transmitting module is used for transmitting the pulse amplitude modulation signal based on probability shaping;
the preprocessing module is connected with the transmitting module and is used for receiving and preprocessing the pulse amplitude modulation signal based on probability shaping;
the self-adaptive equalization module comprises a CMA pre-equalization module and a DDLMS equalization module; the CMA pre-equalization module is used for calculating a CMA pre-equalization error so as to update the tap coefficient of the filter once; the DDLMS equalization module is used for calculating DDLMS equalization errors so as to update the tap coefficients of the filter again;
and the demapping module is connected with the adaptive equalization module and is used for demapping and decoding the signals subjected to CMA pre-equalization and DDLMS equalization so as to obtain a bit sequence sent by the transmitting end.
2. The adaptive equalization apparatus for a PS-PAM system of claim 1, wherein the transmitting module calculates an optimal probability distribution result for each symbol of the PS-PAM signal distributed in pairs based on a preset probability distribution algorithm.
3. The adaptive equalization apparatus for PS-PAM system according to claim 2, wherein the calculation method of the preset probability distribution algorithm comprises:
Wherein x is a transmitting symbol corresponding to each level of the PS-PAM modulation signal; lambda is the shaping factor, lambda epsilon (0, 1); a is a coefficient associated with the level of the PAM modulated signal, where each negative level corresponds to the same a value and each positive level corresponds to the same a value.
4. The adaptive equalization apparatus for a PS-PAM system of claim 1, wherein the preprocessing module comprises a channel transmission module, a clipping module, and a clock data recovery module; the channel transmission module is connected with the transmitting module and is used for receiving the pulse amplitude modulation signal based on probability shaping; the amplitude limiting module is connected with the channel transmission module and is used for carrying out amplitude limiting processing on the pulse amplitude modulation signal based on probability shaping; the clock data recovery module is connected with the amplitude limiting module and is used for providing a clock signal so as to keep the receiving signal consistent with the sending signal.
5. The adaptive equalization apparatus for a PS-PAM system of claim 1, wherein the CMA pre-equalization module is configured to calculate a CMA pre-equalization error to update the filter tap coefficients once, the process comprising:
initializing and setting corresponding filter tap coefficients according to the self-adaptive filter tap length information;
Filtering the input signal based on the initially set filter tap coefficients to obtain a filtered output signal;
and calculating a corresponding CMA pre-equalization error based on the filtered output signal, and updating the tap coefficient of the filter once according to the CMA pre-equalization error, the input signal before filtering and the output signal after filtering.
6. The adaptive equalization apparatus for a PS-PAM system of claim 5, wherein the means for calculating the CMA equalization error comprises:
wherein err is cma Representing CMA pre-equalization error; y represents the filtered output signal.
7. The adaptive equalization apparatus for a PS-PAM system of claim 5, wherein the means for updating the filter tap coefficients once based on the CMA pre-equalization error, the pre-filtered input signal and the filtered output signal comprises: introducing a coefficient updating step length; and taking the product of the coefficient updating step length and the CMA pre-equalization error, the input signal before filtering and the output signal after filtering as a coefficient updating part of one-time updating.
8. The adaptive equalization apparatus of claim 1 applied to a PS-PAM system, wherein the CMA pre-equalization module further performs the following after performing pre-equalization: selecting the number of PS-PAM transmitting symbols received in a preset period; calculating a mean square error value of an output signal of a CMA pre-equalization stage based on the number of PS-PAM transmission symbols in a preset period; after the calculated mean square error value exceeds a preset value, the method can enter DDLMS equalization.
9. The adaptive equalization apparatus for PS-PAM system according to claim 1, wherein the means for calculating the DDLMS equalization error comprises: and determining a range in which the pre-equalized output signal falls according to comparison of the pre-equalized output signal and a plurality of parameter thresholds, and calculating a DDLMS equalization error corresponding to the range.
10. The adaptive equalization apparatus of claim 9, wherein the plurality of parameter thresholds comprises a first parameter threshold, a second parameter threshold, and a third parameter threshold arranged in ascending order; and the second parameter threshold value and the variance of the shaping factor and the Gaussian white noise are in positive correlation.
11. The adaptive equalization apparatus for PS-PAM system according to claim 9 or 10, wherein the DDLMS equalization error is calculated as follows:
wherein err is ddlms Represents DDLMS equalization error; y' represents the signal after CMA pre-equalization; lambda represents the shaping factor; delta 2 Representing the variance of gaussian white noise.
12. The adaptive equalization apparatus for a PS-PAM system of claim 1, wherein the means for continuously updating the filter tap coefficients by the DDLMS equalization module according to the DDLMS equalization error comprises: introducing a coefficient updating step length; and taking the product of the coefficient updating step length, the DDLMS equalization error and the input signal before filtering as a coefficient updating part updated again.
13. An adaptive equalization method applied to a PS-PAM system, comprising:
receiving and preprocessing a pulse amplitude modulation signal based on probability shaping;
calculating a CMA pre-equalization error to update the filter tap coefficients once; and calculating DDLMS equalization error to update the filter tap coefficient again;
and performing demapping and decoding processing on the signals subjected to CMA pre-equalization and DDLMS equalization to obtain a bit sequence sent by a transmitting end.
14. A computer readable storage medium having stored thereon a computer program, which when executed by a processor implements the adaptive equalization method applied to PS-PAM system of claim 13.
15. A computer device, comprising: a processor and a memory;
the memory is used for storing a computer program;
the processor is configured to execute the computer program stored in the memory, so that the terminal performs the adaptive equalization method applied to the PS-PAM system according to claim 13.
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