Timing error estimation method and device of Nyquist system

Abstract

The invention discloses a timing error estimation method and device for a Nyquist system. The method comprises the following steps: generating a random modulation signal; inserting zero into even bits of the random modulation signal to obtain an initial training sequence; generating a target communication frame based on the initial training sequence and the communication signal; sending the target communication frame to a receiving end of the Nyquist system; and sending the target communication frame to a receiving end, so that the receiving end extracts an initial training sequence in the target communication frame, performing data processing on the initial training sequence to obtain a target training sequence, and performing timing error estimation on the target communication frame based on the target training sequence and a target timing error detection algorithm to obtain a timing error estimation result. According to the method, the tolerance of a timing error detection algorithm to dispersion, polarization mode dispersion effect and differential group delay damage is enhanced, so that accurate timing error estimation can be provided under a complex channel condition, and the method can be widely applied to the technical field of data communication.

Description

Technical Field

[0001] The present application relates to the field of data communication technology, and in particular to a timing error estimation method and device for a Nyquist system. Background Art

[0002] In the related technology, there is a timing error estimation algorithm. In the optical communication system, timing error estimation is crucial to the accurate demodulation of the signal and the system performance. However, due to non-ideal factors such as dispersion effects, polarization mode dispersion and random polarization rotation in the optical fiber channel, the performance of the traditional timing error estimation algorithm is limited when facing these complex channel effects, which has a significant impact on the performance of the timing error estimation algorithm. These complex channel effects will cause the spectral correlation of the signal to decrease, thereby affecting the accurate estimation of the timing error.

[0003] In summary, the technical problems existing in the relevant technologies need to be improved. Summary of the invention

[0004] The embodiments of the present application aim to solve at least one of the technical problems in the related art to a certain extent. To this end, the main purpose of the embodiments of the present application is to propose a timing error estimation method and device for a Nyquist system, aiming to enhance the tolerance of the timing error detection algorithm to dispersion, polarization mode dispersion effect and differential group delay impairment, so as to provide accurate timing error estimation even under complex channel conditions.

[0005] To achieve the above object, an embodiment of the present application provides a timing error estimation method for a Nyquist system, which is applied to a transmitting end of the Nyquist system. The method includes the following steps:

[0006] generating a random modulation signal;

[0007] Inserting zeros into even-numbered bits of the random modulation signal to obtain an initial training sequence;

[0008] Based on the initial training sequence and the communication signal, generating a target communication frame;

[0009] The target communication frame is sent to the receiving end of the Nyquist system; so that the receiving end extracts the initial training sequence in the target communication frame, performs data processing on the initial training sequence to obtain a target training sequence, and performs timing error estimation on the target communication frame based on the target training sequence and a target timing error detection algorithm to obtain a timing error estimation result.

[0010] In some embodiments, generating a target communication frame based on the initial training sequence and the communication signal includes:

[0011] Splicing the initial training sequence and the communication signal to obtain a target spliced ​​signal;

[0012] Mapping the target splicing signal using a target signal mapping method to obtain a target mapping signal;

[0013] Performing Nyquist pulse shaping on the target mapping signal to obtain the target communication frame.

[0014] To achieve the above object, an embodiment of the present application provides a timing error estimation method for a Nyquist system, which is applied to a receiving end of the Nyquist system. The method includes the following steps:

[0015] Receiving a target communication frame sent by a transmitting end; wherein the target communication frame includes an initial training sequence and a communication signal;

[0016] Performing data extraction processing on the target communication frame to obtain the initial training sequence in the target communication frame;

[0017] Performing data processing on the initial training sequence to obtain a target training sequence;

[0018] Constructing a target cyclic autocorrelation function matrix based on the target training sequence;

[0019] Performing timing error estimation on the target communication frame based on the target cyclic autocorrelation function matrix and the target timing error detection algorithm to obtain a timing error estimation result;

[0020] The target communication frame is determined according to the timing error estimation method of the Nyquist system applied to the transmitting end of the Nyquist system.

[0021] In some embodiments, the performing data processing on the initial training sequence to obtain a target training sequence includes:

[0022] The initial training sequence is resampled using a target resampling rule to obtain the target training sequence; wherein the target training sequence is applied to a timing error detection unit in the receiving end.

[0023] In some embodiments, the signal representation form of the target communication frame at the receiving end is a discrete digital signal, and the step of constructing a target cyclic autocorrelation function matrix based on the target training sequence includes:

[0024] intercepting the target training sequence according to the target interception time length to obtain a target discrete digital signal;

[0025] generating a spectrum correlation function based on the target discrete digital signal;

[0026] Performing inverse Fourier transform processing on the spectrum correlation function to obtain an initial cyclic autocorrelation function;

[0027] Constructing an initial cyclic autocorrelation function matrix according to the initial cyclic autocorrelation function;

[0028] The target cyclic autocorrelation function matrix is ​​generated based on the initial cyclic autocorrelation function matrix.

[0029] In some embodiments, generating the target cyclic autocorrelation function matrix based on the initial cyclic autocorrelation function matrix includes:

[0030] The target cyclic autocorrelation function in the initial cyclic autocorrelation function matrix is ​​calculated using a target peak position formula to obtain the target cyclic autocorrelation function matrix at the target peak position.

[0031] In some embodiments, the target peak position formula is:

[0032]

[0033] Among them, τ represents the target peak position point, Expressed as the cyclic autocorrelation function of signal x and signal x, is represented as the circular autocorrelation function of signals x and y, and argmax is represented as an operator that returns the index of the maximum value.

[0034] In some embodiments, the performing timing error estimation on the target communication frame based on the target cyclic autocorrelation function matrix and the target timing error detection algorithm to obtain a timing error estimation result includes:

[0035] Based on the target cyclic autocorrelation function matrix, the timing error estimation formula in the target timing error detection algorithm is combined to estimate the timing error of the target communication frame to obtain the timing error estimation result; the timing error estimation formula is:

[0036]

[0037] in, is represented as the timing error, CAF is represented as the initial cyclic autocorrelation function matrix, CAF(τ) is represented as the target cyclic autocorrelation function matrix of the τth position point, SCF is represented as the spectrum correlation function matrix, det is represented as the operator for taking the matrix determinant, and -Im{·} is represented as the operator for taking the imaginary part of a complex number.

[0038] To achieve the above object, another aspect of an embodiment of the present application provides a timing error estimation device for a Nyquist system, which is applied to a transmitting end of the Nyquist system. The device includes the following modules:

[0039] A random modulation signal generation module, used for generating a random modulation signal;

[0040] An initial training sequence building module, used for inserting zeros into even-numbered bits of the random modulation signal to obtain an initial training sequence;

[0041] A target communication frame generation module, used for generating a target communication frame based on the initial training sequence and the communication signal;

[0042] The target communication frame sending module is used to send the target communication frame to the receiving end of the Nyquist system; so that the receiving end extracts the initial training sequence in the target communication frame, performs data processing on the initial training sequence to obtain a target training sequence, and estimates the timing error of the target communication frame based on the target training sequence and a target timing error detection algorithm to obtain a timing error estimation result.

[0043] To achieve the above object, another aspect of an embodiment of the present application provides a timing error estimation device for a Nyquist system, which is applied to a receiving end of the Nyquist system. The device includes the following modules:

[0044] A target communication frame receiving module is used to receive a target communication frame sent by a transmitting end; wherein the target communication frame includes an initial training sequence and a communication signal;

[0045] An initial training sequence extraction module, used for performing data extraction processing on the target communication frame to obtain the initial training sequence in the target communication frame;

[0046] A target training sequence acquisition module is used to perform data processing on the initial training sequence to obtain a target training sequence;

[0047] A cyclic autocorrelation function matrix acquisition module, used to construct a target cyclic autocorrelation function matrix based on the target training sequence;

[0048] A timing error estimation module, used to perform timing error estimation on the target communication frame based on the target cyclic autocorrelation function matrix and the target timing error detection algorithm to obtain a timing error estimation result;

[0049] The target communication frame is determined according to the timing error estimation device of the Nyquist system applied to the transmitting end of the Nyquist system.

[0050] The embodiments of the present application include at least the following beneficial effects: The present application provides a timing error estimation method and device for a Nyquist system, which generates a random modulation signal; inserts zeros into the even bits of the random modulation signal to obtain an initial training sequence; generates a target communication frame based on the initial training sequence and the communication signal; and sends the target communication frame to the receiving end of the Nyquist system; so that the receiving end extracts the initial training sequence in the target communication frame, and performs data processing on the initial training sequence to obtain the target training sequence, and estimates the timing error of the target communication frame based on the target training sequence and the target timing error detection algorithm to obtain a timing error estimation result. The embodiments of the present application enhance the tolerance of the timing error detection algorithm to dispersion, polarization mode dispersion effect, and differential group delay damage by designing the training sequence of the RZ code at the transmitting end and sending it to the receiving end, thereby providing accurate timing error estimation even under complex channel conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 is a flowchart of steps when the timing error estimation method of the Nyquist system provided by the embodiment of the present application is applied to the transmitting end of the Nyquist system;

[0052] Figure 2 It is a schematic diagram of a process of constructing a communication frame based on a training sequence provided in an embodiment of the present application;

[0053] Figure 3 is a flowchart of steps when the timing error estimation method of the Nyquist system provided by the embodiment of the present application is applied to the receiving end of the Nyquist system;

[0054] Figure 4 is a schematic diagram of the timing error estimation algorithm flow provided in an embodiment of the present application;

[0055] Figure 5 It is a structural diagram of a timing error estimation device for a Nyquist system provided in an embodiment of the present application when applied to a transmitting end of the Nyquist system;

[0056] Figure 6 is a structural diagram of a timing error estimation device for a Nyquist system provided in an embodiment of the present application when applied to a receiving end of the Nyquist system;

[0057] Figure 7 It is a schematic diagram of the hardware structure of the electronic device provided in the embodiment of the present application. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is further described in detail below in conjunction with the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the embodiments of the present application. They are only examples of devices and methods consistent with some aspects of the embodiments of the present application as detailed in the attached claims.

[0059] It is understood that the terms "first", "second", etc. used in this application can be used to describe various concepts in this article, but unless otherwise specified, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another concept. For example, without departing from the scope of the embodiment of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the words "if" and "if" as used herein can be interpreted as "at the time of" or "when" or "in response to determination".

[0060] The terms "at least one", "multiple", "each", "any", etc. used in this application, at least one includes one, two or more, multiple includes two or more, each refers to each of the corresponding multiple, and any refers to any one of the multiple.

[0061] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0062] Before describing the embodiments of the present application in detail, some nouns and terms involved in the embodiments of the present application are first described. The nouns and terms involved in the embodiments of the present application are subject to the following interpretations:

[0063] (1) Coherent Optical Communication: Coherent optical communication is an advanced optical communication technology that uses lasers as light sources and uses coherent detection technology to improve signal reception sensitivity and transmission quality. In a coherent optical communication system, the signal at the transmitter modulates the optical carrier of the laser, while the receiver uses a local laser synchronized with the transmitter for coherent mixing to detect the amplitude and phase information of the transmitted signal. Coherent optical communication technology significantly improves the signal transmission distance and system capacity.

[0064] (2) Chromatic Dispersion (CD): Chromatic Dispersion refers to the phenomenon that the optical signal transmitted in the optical fiber is pulse-broadened due to the different light speeds of different wavelengths. Dispersion will distort the signal's time domain waveform, affect the integrity of the signal, and thus reduce the performance of the communication system. The dispersion effect includes material dispersion and waveguide dispersion, and is one of the damage factors that need to be considered and compensated in long-distance optical fiber communication systems.

[0065] (3) Nyquist System: Nyquist system refers to a signal sampling system that satisfies the Nyquist sampling theorem. According to the Nyquist sampling theorem, in order to avoid aliasing, the sampling frequency of the signal should be at least twice the highest frequency of the signal. In optical fiber communications, the Nyquist system usually refers to a digital signal processing system that can meet this condition. The Nyquist system can accurately reconstruct the original analog signal from the sampled data.

[0066] (4) Timing Error Estimation: Timing error estimation refers to the process of estimating the deviation between the sampling clock of the received signal and the actual clock of the signal in a digital communication system. Accurate timing error estimation is crucial for synchronous demodulation of the signal, which can ensure that the signal is sampled at the optimal time, thereby improving the accuracy of signal demodulation and the overall performance of the system.

[0067] (5) DSP technology (Digital Signal Processing Technology): DSP technology refers to the technology of using digital circuits or computers to process signals. In optical fiber communication systems, DSP technology is widely used in key links such as signal modulation, demodulation, equalization, dispersion compensation, and timing recovery. Through DSP technology, efficient signal processing can be achieved, system performance can be optimized, and transmission quality can be improved.

[0068] (6) Roll-off Factor (ROF): The roll-off factor is a parameter that describes the attenuation rate of the signal spectrum. It is used to filter the signal in a digital communication system to limit its bandwidth. A signal with a smaller roll-off factor has a slower attenuation edge, which means that the signal occupies a wider spectrum; while a signal with a larger roll-off factor has a faster attenuation edge and a narrower spectrum. The choice of roll-off factor affects the transmission efficiency and anti-interference ability of the system.

[0069] (7) Polarization Division Multiplexing (PDM): Polarization division multiplexing is a technology that improves the capacity of optical fiber communication systems. It uses the polarization characteristics of optical signals to achieve double the data transmission rate by simultaneously transmitting two orthogonal polarization state signals in the same optical fiber. Each polarization state can carry information independently, which is equivalent to two independent communication channels. Polarization division multiplexing technology can be combined with other multiplexing technologies (such as wavelength division multiplexing (WDM)) to further improve the system's spectrum efficiency and transmission capacity.

[0070] (8) Rotation of State of Polarization (RSOP) describes the change in the polarization state of an optical signal during transmission in an optical fiber. Due to the imperfection of the optical fiber and external environmental factors (such as temperature and stress), the polarization state of the optical signal may randomly rotate during transmission. This rotation affects the signal quality and the performance of coherent detection. Therefore, when designing an optical fiber communication system, it is necessary to consider the impact of polarization rotation and take corresponding compensation measures.

[0071] (9) Differential Group Delay (DGD) refers to the difference in arrival time caused by different path lengths of two orthogonal polarization states of optical signals transmitted in optical fiber due to birefringence in a polarization multiplexing system. DGD is a manifestation of polarization mode dispersion (PMD), which is an indicator to measure the difference in transmission speed of optical fiber for signals with different polarization states. DGD will cause signal pulse broadening, affecting signal integrity and the bit error rate performance of the system. In high-speed optical fiber communication systems, compensation of DGD is one of the key technologies to ensure signal quality.

[0072] (10) Single Sample per Symbol (SPS). In digital signal processing and communication systems, SPS is a sampling strategy that refers to collecting only one sample in each symbol period. This strategy is very useful in some high-speed communication systems, especially in systems that use Nyquist pulse shaping. In digital communications, signals usually need to be digitized, which involves converting continuous analog signals into discrete digital signals. This process is called sampling, and the sampling rate refers to the number of samples per unit time. Traditional sampling strategies may require multiple samples per symbol period to ensure signal integrity and accuracy; however, the 1-SPS strategy only samples once in a symbol period, which can reduce the number of samples, thereby reducing hardware complexity and power consumption. SPS is particularly useful in high-speed optical communication systems because these systems need to process very high data rates. By using Nyquist pulse shaping, spectrum resources can be effectively utilized, and SPS further reduces the required sampling rate, making system design more efficient.

[0073] At present, with the continuous growth of the demand for Internet and data communication, optical communication systems have become the backbone of modern communication networks due to their advantages such as high bandwidth, low loss and anti-electromagnetic interference. Especially in high-speed coherent optical communication systems, ultra-high-speed data transmission can be achieved by using advanced modulation formats and digital signal processing technologies. Coherent detection technology in coherent optical communication systems can provide higher signal detection sensitivity and can accurately measure the amplitude and phase of optical signals, which is crucial for achieving high-speed transmission and improving signal quality; DSP technology plays a core role in coherent optical communication systems, which can perform necessary processing on received optical signals, including symbol rate estimation, carrier frequency offset correction, dispersion compensation and adaptive equalization of signals. In optical communication systems, timing error estimation is crucial for accurate signal demodulation and system performance. However, due to non-ideal factors such as dispersion effect (CD), polarization mode dispersion (PMD) and random polarization rotation (RSOP) in optical fiber channels, the performance of traditional timing error estimation algorithms is limited when facing these complex channel effects, which has a significant impact on the performance of timing error estimation algorithms. These effects will reduce the spectral correlation of signals, thereby affecting the accurate estimation of timing errors.

[0074] For example, the relevant timing error estimation algorithms have insufficient tolerance when processing Nyquist signals with low roll-off factors, which limits their application in practical optical communication systems, because practical systems may have lower roll-off factors due to various factors (such as device characteristics, transmission distance, pursuit of higher spectral efficiency, etc.). In addition, traditional timing error estimation methods are sensitive to chromatic dispersion (CD), polarization mode dispersion (PMD) effects and differential group delay (DGD) impairments in optical fiber channels, which may lead to algorithm performance degradation in the presence of these effects.

[0075] In view of this, the embodiment of the present application provides a timing error estimation method and device for the Nyquist system, which generates a random modulation signal; inserts zeros into the even bits of the random modulation signal to obtain an initial training sequence; generates a target communication frame based on the initial training sequence and the communication signal; and sends the target communication frame to the receiving end of the Nyquist system; so that the receiving end extracts the initial training sequence in the target communication frame, and performs data processing on the initial training sequence to obtain the target training sequence, and estimates the timing error of the target communication frame based on the target training sequence and the target timing error detection algorithm to obtain the timing error estimation result. The embodiment of the present application enhances the tolerance of the timing error detection algorithm to dispersion, polarization mode dispersion effect and differential group delay damage by designing the training sequence of the RZ code at the transmitting end and sending it to the receiving end, thereby providing accurate timing error estimation under complex channel conditions.

[0076] The timing error estimation method of the Nyquist system provided in the embodiment of the present application relates to the field of data communication technology. The timing error estimation method of the Nyquist system provided in the embodiment of the present application can be applied to a terminal, can also be applied to a server, and can also be software running in a terminal or a server. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, and a car terminal, etc., but is not limited to this; the server side can be configured as an independent physical server, or a server cluster or distributed system composed of multiple physical servers, and can also be configured to provide cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN (Content Delivery Network, content distribution network) and cloud servers for basic cloud computing services such as big data and artificial intelligence platforms, and the server can also be a node server in a blockchain network; the software can be an application of the timing error estimation method for the Nyquist system, etc., but is not limited to the above forms.

[0077] The present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld devices or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronic devices, network PCs (Personal Computers, personal computers), minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc. The present application can be described in the general context of computer executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application can also be practiced in distributed computing environments, in which tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0078] See also Figure 1 , Figure 1 is an optional step flow chart of a timing error estimation method for a Nyquist system provided in an embodiment of the present application, which is applied to a transmitting end of a Nyquist system. Figure 1 The method may include but is not limited to steps S101 to S104.

[0079] Step S101, generating a random modulation signal;

[0080] Among them, the transmitter of the Nyquist system is a component of the system, which is responsible for encoding and modulating information (such as data, voice, etc.) and sending it to the receiver of the Nyquist system.

[0081] As for the random modulation signal, in the embodiment of the present application, it is a random QPSK (Quadrature Phase ShiftKeying) signal.

[0082] In a specific implementation, by generating a random modulation signal at the transmitting end of the Nyquist system, the signal characteristics in the actual communication environment can be better simulated to improve the robustness of the entire communication system.

[0083] Step S102, inserting zeros into even bits of the random modulation signal to obtain an initial training sequence;

[0084] The initial training sequence is obtained by inserting zeros into the even bits of the random modulated signal, and is used to help the receiving end perform operations such as synchronization, channel estimation, and equalization.

[0085] In the specific implementation, a random QPSK signal is generated at the transmitting end, and zeros are inserted into the even bits of the random QPSK signal to form a training sequence with a block size of 512 bits, which is the same as X polarization and Y polarization. Among them, X polarization and Y polarization refer to two different polarization directions of electromagnetic waves, that is, they can bring two signal components.

[0086] Step S103, generating a target communication frame based on the initial training sequence and the communication signal;

[0087] In some embodiments, step S103 may include: splicing the initial training sequence and the communication signal to obtain a target spliced ​​signal; mapping the target spliced ​​signal using a target signal mapping method to obtain a target mapping signal; performing Nyquist pulse shaping on the target mapping signal to obtain a target communication frame.

[0088] The communication signal is the actual data signal to be sent, which contains the information that the user needs to transmit, such as text, audio, video or any other form of data. In the communication system, these data are usually encoded and modulated, ready to be transmitted through a physical medium. It should be noted that the communication signal to be sent to the receiving end can be other modulated signals, but the signal used to construct the initial training sequence is only a QPSK signal.

[0089] The splicing operation is a process of splicing an initial training sequence and a communication signal to obtain a target spliced ​​signal, where the target spliced ​​signal includes the training sequence and a communication signal for transmitting actual data.

[0090] In a specific implementation, the target signal mapping method may adopt a 16QAM (Quadrature Amplitude Modulation) mapping method.

[0091] Nyquist pulse shaping is a signal processing technique used to design the waveform of the transmitted signal so that it meets the Nyquist criterion in the frequency domain, so that the original data can be restored without error at the receiving end. Nyquist pulse shaping can ensure that there is no interference between symbols of the signal and its spectrum is within the bandwidth limit.

[0092] The target communication frame is the data finally sent to the receiving end, including the training sequence and the communication signal to be sent.

[0093] See also Figure 2 , Figure 2is a flow chart of constructing a communication frame based on a training sequence provided in an embodiment of the present application; in order to improve the tolerance of optical communication channel damage in the Nyquist system, an embodiment of the present application designs a training sequence for TED (Timing Error Detection), such as Figure 2 As shown in the Tx-DSP (Transmitter Digital Signal Processing) module, a random QPSK signal is first generated at the transmitter; then zeros are inserted into the even bits of the random QPSK signal to form a training sequence with a block size of 512 bits, which is the same as X polarization and Y polarization. For example, Figure 2 As shown, "0" is inserted between the random QPSK signals "1+li" and "1+li"; then the training sequence and the communication signal to be sent (such as Figure 2 The target splicing signal is obtained by splicing the PRBS (Pseudo-Random Binary Sequence) sequence in the target splicing signal; then the target splicing signal is mapped by a 16QAM mapping method to obtain a target mapping signal; finally, the target mapping signal is subjected to Nyquist pulse shaping to obtain a target communication frame.

[0094] Step S104, sending the target communication frame to the receiving end of the Nyquist system; so that the receiving end extracts the initial training sequence in the target communication frame, performs data processing on the initial training sequence to obtain a target training sequence, and performs timing error estimation on the target communication frame based on the target training sequence and a target timing error detection algorithm to obtain a timing error estimation result.

[0095] As for the receiving end, similar to the transmitting end, it is a component of the Nyquist system, responsible for receiving the signal transmitted from the transmitting end and converting it back to the original data. In a specific implementation, the receiving end can be selected as an oscilloscope.

[0096] At the receiving end, it is necessary to extract the target communication frame received by the receiving end to obtain the initial training sequence, and then perform data processing on the initial training sequence to obtain the target training sequence. In the specific implementation, at the receiver side, a frame of data is first resampled to the target baud rate (2-SPS) for frame synchronization to extract the initial training sequence; after the initial training sequence is extracted, the initial training sequence is resampled to obtain the 1-SPS target training sequence, so that the low baud rate symbol (1-SPS target training sequence) can be obtained and applied to the subsequent clock error detection algorithm unit (also called the timing error detection unit).

[0097] As for the target timing error detection algorithm, it is a timing error estimation algorithm designed using second-order cyclic statistics, which can more effectively handle the robustness of the timing error detection algorithm to dispersion effects, polarization mode dispersion and differential group delay.

[0098] Steps S101 to S104 shown in the embodiment of the present application are to generate a random modulation signal; insert zeros into the even bits of the random modulation signal to obtain an initial training sequence; generate a target communication frame based on the initial training sequence and the communication signal; send the target communication frame to the receiving end of the Nyquist system; so that the receiving end extracts the initial training sequence in the target communication frame, and performs data processing on the initial training sequence to obtain the target training sequence, and estimates the timing error of the target communication frame based on the target training sequence and the target timing error detection algorithm to obtain the timing error estimation result. The embodiment of the present application enhances the tolerance of the timing error detection algorithm to dispersion, polarization mode dispersion effect and differential group delay damage by designing the training sequence of the RZ code at the transmitting end and sending it to the receiving end, thereby providing accurate timing error estimation even under complex channel conditions.

[0099] See also Figure 3 , Figure 3 is an optional step flow chart of a timing error estimation method for a Nyquist system provided in an embodiment of the present application, which is applied to a receiving end of a Nyquist system. Figure 3 The method may include but is not limited to steps S301 to S305.

[0100] Step S301, receiving a target communication frame sent by a transmitting end; wherein the target communication frame includes an initial training sequence and a communication signal;

[0101] Among them, the transmitter of the Nyquist system is a component of the system. The transmitter is responsible for encoding and modulating information (such as data, voice, etc.) and sending it to the receiver of the Nyquist system. The steps completed at the transmitter include: first, a random QPSK signal is generated at the transmitter; then, zeros are inserted into the even bits of the random QPSK signal to form a training sequence with a block size of 512 bits; then, the training sequence and the communication signal to be sent are spliced ​​to obtain the target spliced ​​signal; then, the target spliced ​​signal is mapped using the 16QAM mapping method to obtain the target mapped signal; finally, the target mapped signal is subjected to Nyquist pulse shaping to obtain the target communication frame, so as to transmit the target communication frame to the receiver through the optical communication channel.

[0102] Among them, the target communication frame is based on Figure 1 The target communication frame contains the initial training sequence and the communication signal.

[0103] As for the receiving end, similar to the transmitting end, it is a component of the Nyquist system, responsible for receiving the signal transmitted from the transmitting end and converting it back to the original data for relevant processing. In a specific implementation, the receiving end can be selected as an oscilloscope.

[0104] At the receiving end, it is necessary to extract the target communication frame received by the receiving end to obtain the initial training sequence, and then perform data processing on the initial training sequence to obtain the target training sequence. In the specific implementation, at the receiver side, a frame of data is first resampled to the target baud rate (2-SPS) for frame synchronization to extract the initial training sequence; after the initial training sequence is extracted, the initial training sequence is resampled to obtain the 1-SPS target training sequence, so that the low baud rate symbol (1-SPS target training sequence) can be obtained and applied to the subsequent clock error detection algorithm unit (also called the timing error detection unit).

[0105] Step S302, performing data extraction processing on the target communication frame to obtain the initial training sequence in the target communication frame;

[0106] The signal representation form of the target communication frame at the receiving end is a discrete digital signal.

[0107] In a specific implementation, at the receiving end side (Receive Digital Signal Processing, referred to as Rx-DSP module), after the oscilloscope (receiving end device) obtains the orthogonally polarized discrete digital signal x and discrete digital signal y in the target communication frame, a frame of data is resampled to the target baud rate (2-SPS) for frame synchronization to extract the initial training sequence. Specifically, the discrete digital signal x and the discrete digital signal y are first subjected to matched filtering, and then the signal data after matched filtering is resampled once, and then the initial training sequence (2-SPS) can be obtained. It should be noted that the training sequence obtained by resampling here is the initial training sequence of 2-SPS.

[0108] Among them, matched filtering is an optimal linear filtering technology used to maximize the signal-to-noise ratio of the signal under a given noise background, thereby increasing the detection probability of the signal.

[0109] Step S303, performing data processing on the initial training sequence to obtain a target training sequence;

[0110] In some embodiments, step S303 may include: resampling the initial training sequence using a target resampling rule to obtain a target training sequence; wherein the target training sequence is applied to a timing error detection unit in a receiving end.

[0111] For the target resampling rule, the initial training sequence is resampled to obtain a 1-SPS target training sequence, that is, after the receiving end discards the even bits of the training sequence, a 1-SPS training sequence can be obtained and applied to the timing error detection unit. The target training sequence is a 1-SPS training sequence.

[0112] The timing error detection unit is a key component of the receiving end. Its main function is to detect the timing error in the received signal and adjust the sampling clock accordingly to ensure that the data is sampled at the optimal time, thereby reducing the bit error caused by inaccurate sampling time.

[0113] In a specific implementation, after the initial training sequence is extracted, the initial training sequence is resampled twice to obtain a 1-SPS target training sequence, so that a low baud rate symbol (1-SPS target training sequence) can be obtained and applied to a subsequent clock error detection algorithm unit (also called a timing error detection unit). It should be noted that the training sequence obtained by resampling here is a 1-SPS target training sequence.

[0114] It is worth mentioning that the training sequence after Nyquist pulse shaping at the transmitter is a special RZ (Return-to-Zero) code. Among them, the return-to-zero code (RZ Code) is a digital signal encoding method in which the middle of each code element (bit) returns to the zero level, which means that during the duration of the code element, the signal starts from the zero level, jumps to a non-zero level (usually a positive level or a negative level), and then returns to the zero level in the middle of the code element. This encoding method can reduce inter-symbol interference and is used in communication systems to improve signal distinguishability and timing information. In the Nyquist system, the use of return-to-zero code can better perform frame synchronization and clock recovery.

[0115] The embodiment of the present application designs a special RZ code as a training sequence, which has a high tolerance for Nyquist pulse shaping systems or small roll-off factors (ROF<0.2), which is particularly important for actual optical communication systems. Since Nyquist shaping will seriously affect the sideband information integrity of the signal, the timing error algorithm based on sideband correlation will usually fail. The embodiment of the present application enhances the algorithm's tolerance to dispersion, polarization mode dispersion effects and differential group delay damage by designing a training sequence of the RZ code, thereby providing accurate timing error estimation even under complex channel conditions.

[0116] Step S304, constructing a target cyclic autocorrelation function matrix based on the target training sequence;

[0117] In some embodiments, step S304 may include: intercepting the target training sequence according to the target interception time length to obtain a target discrete digital signal; generating a spectrum correlation function based on the target discrete digital signal; performing inverse Fourier transform processing on the spectrum correlation function to obtain an initial cyclic autocorrelation function; constructing an initial cyclic autocorrelation function matrix based on the initial cyclic autocorrelation function; and generating a target cyclic autocorrelation function matrix based on the initial cyclic autocorrelation function matrix.

[0118] In some specific embodiments, generating a target cyclic autocorrelation function matrix based on an initial cyclic autocorrelation function matrix may include: using a target peak position formula to calculate the target cyclic autocorrelation function in the initial cyclic autocorrelation function matrix to obtain a target cyclic autocorrelation function matrix at a target peak position.

[0119] The target interception time length is a specified time length used to intercept a portion of data from the target training sequence, and the intercepted portion of data is used for subsequent function processing. The target discrete digital signal is a signal portion intercepted from the target training sequence with a target interception time length, and the target discrete digital signal is represented by signal spectrum X and signal spectrum Y.

[0120] The Spectral Correlation Function (SCF) is a function used to describe the autocorrelation of a signal in the frequency domain, which can be obtained by performing Fourier transform on the signal and calculating its autocorrelation.

[0121] For the inverse Fourier transform process, it is the inverse process of Fourier transform, which is used to convert the frequency domain signal back to the time domain. In this step, the spectrum correlation function converts the frequency domain signal back to the time domain through the inverse Fourier transform process, and a cyclic autocorrelation function (Cyclic Autocorrelation Function, referred to as CAF) can be obtained. Among them, the initial cyclic autocorrelation function is the time domain autocorrelation function obtained by the spectrum correlation function after the inverse Fourier transform process, which is used to construct the initial cyclic autocorrelation function matrix, wherein the initial cyclic autocorrelation function matrix includes multiple cyclic autocorrelation functions, each function corresponding to a different cyclic shift of the signal.

[0122] In the specific implementation, the calculation process of the cyclic autocorrelation function (CAF) matrix and the spectral correlation function (SCF) matrix in the cyclic correlation theory is as follows:

[0123] After the oscilloscope at the receiving end obtains the orthogonally polarized discrete digital signal x and discrete digital signal y in the target communication frame sent by the transmitting end, the discrete digital signal x and discrete digital signal y are first matched filtered and resampled to obtain a 1-SPS target training sequence, and then the target training sequence is signal intercepted according to the interception threshold with an interception time length of W to obtain the signal spectrum X and the signal spectrum Y. It should be noted that x and y in the original orthogonally polarized discrete digital signal x and discrete digital signal y are lowercase letters, and X and Y in the signal spectrum X and signal spectrum Y obtained after signal interception of the target training sequence are uppercase letters. Here, x, y, X and Y are case-sensitive, and different parameters represent different meanings.

[0124] Among them, the signal spectrum X and the signal spectrum Y are used to calculate four cyclic periodogram functions. The cyclic periodogram function can be regarded as an estimate of the spectrum correlation function (SCF). The four cyclic periodogram functions (P xx , P xy , P yx , P yy ) is calculated as follows:

[0125]

[0126] Among them, X and Y in the formula are the signal spectra obtained by intercepting the target training sequence, α is the cycle frequency, and f is the frequency. The above-mentioned cyclic periodogram function can be regarded as an estimate of the spectrum correlation function (SCF). The spectrum correlation function (SCF) matrix corresponding to the spectrum correlation function (SCF) can be calculated through the above four cyclic periodogram functions. The expression of the spectrum correlation function matrix SCF(f) is:

[0127]

[0128] It is worth mentioning that the calculation expressions of the above-mentioned cyclic periodogram functions are all obtained by multiplying two parameters, that is, a second-order cyclic statistic is used. The embodiment of the present application adopts a second-order cyclic statistic to design a timing error estimation algorithm, which can more effectively handle the robustness of the timing error detection algorithm for chromatic dispersion (CD), polarization mode dispersion (PMD) effect and differential group delay (DGD) damage in the optical fiber channel.

[0129] Therefore, the cyclic autocorrelation function (CAF) can be estimated by using its inverse Fourier transform, and the four CAF functions can be written in matrix form, that is, the CAF matrix of the two-polarization multiplexed signal is constructed. The CAF matrix of the two-polarization multiplexed signal contains four variables {CAFxx, CAFxy, CAFyx, CAFyy}, which is convenient for studying the influence of polarization effect on SCF and CAF.

[0130] There are two methods for calculating CAF sequences. One method is to perform inverse Fourier transform on the spectral correlation function (SCF) obtained by periodogram estimation to obtain the cyclic autocorrelation function (CAF); the other method is to directly calculate in the time domain according to the definition of the cyclic autocorrelation function (CAF).

[0131] After the CAF sequence is generated, the delay module is used to determine the delay n according to the peak position calculated by the target peak position formula; then, the first value of the delayed CAF sequence is used to form a CAF matrix.

[0132] For example, you can use The inverse Fourier transform of the cyclic autocorrelation function (CAF) is obtained The same is true for the inverse Fourier transform of other matrix parameters. Considering polarization multiplexing (signal spectrum X polarization and signal spectrum Y polarization), the final CAF matrix (i.e., target cyclic autocorrelation function matrix) is as follows:

[0133]

[0134] Before the delay module calculates the peak position according to the target peak position formula, the CAF matrix is ​​expressed as That is, the initial cyclic autocorrelation function matrix.

[0135] Optionally, the target peak position formula is used to calculate a formula for a target cyclic autocorrelation function at a specific peak position, where the target position where the expected peak appears in the cyclic autocorrelation function is usually related to the timing information of the signal.

[0136] Optionally, the target peak position formula is:

[0137]

[0138] Among them, τ represents the target peak position point, Expressed as the cyclic autocorrelation function of signal x and signal x, is represented as the circular autocorrelation function of signals x and y, and argmax is represented as an operator that returns the index of the maximum value.

[0139] Step S305, performing timing error estimation on the target communication frame based on the target cyclic autocorrelation function matrix and the target timing error detection algorithm to obtain a timing error estimation result;

[0140] In some embodiments, step S305 may include: based on the target cyclic autocorrelation function matrix, in combination with the timing error estimation formula in the target timing error detection algorithm, performing timing error estimation on the target communication frame to obtain a timing error estimation result; the timing error estimation formula is:

[0141]

[0142] in, is represented as the timing error, CAF is represented as the initial cyclic autocorrelation function matrix, CAF(τ) is represented as the target cyclic autocorrelation function matrix of the τth position point, SCF is represented as the spectrum correlation function matrix, det is represented as the operator for taking the matrix determinant, and -Im{·} is represented as the operator for taking the imaginary part of a complex number.

[0143] The number of CAFs is equal to the number of signal points involved in the timing error estimation operation, and IFFT (SCF) is represented by performing an inverse Fourier transform on each matrix element in the SCF.

[0144] The target timing error detection algorithm is also called the timing error detection algorithm based on the training sequence (i.e., the Return-to-Zero Timing Error Detection, or RZ-TED algorithm for short). It is an algorithm used by the timing error detection unit in the receiving end to detect and estimate the timing error in the received signal. It includes a timing error estimation formula.

[0145] in, The influence of dispersion effect on CAF matrix clock adjustment can be quantified, and then the timing error can be extracted. Using this method, the timing error estimation algorithm can tolerate the influence of dispersion, polarization mode dispersion effect and differential group delay even in the Nyquist system with a roll-off factor close to zero.

[0146] The timing error estimation result is the output of the timing error estimation process, which gives the clock offset of the received signal relative to the transmitted signal.

[0147] See also Figure 4 , Figure 4 is a schematic diagram of the timing error estimation algorithm flow provided in the embodiment of the present application; Figure 4 As shown, the specific implementation process of the timing error estimation algorithm includes the following steps 1 to 5:

[0148] Step 1: First, the orthogonally polarized discrete digital signal x and discrete digital signal y in the target communication frame are collected by the oscilloscope at the receiving end; then, the discrete digital signal x and the discrete digital signal y are matched filtered and resampled to obtain a 1-SPS target training sequence, and then the target training sequence is signal intercepted according to a interception threshold with an interception time length of W to obtain a signal spectrum X and a signal spectrum Y.

[0149] Step 2: Calculate four cyclic periodogram functions (P xx , P xy , P yx , P yy ), the cyclic periodogram function can be regarded as an estimate of the spectral correlation function (SCF). The spectral correlation function matrix corresponding to the spectral correlation function can be calculated through the calculation expressions of the above four cyclic periodogram functions:

[0150] Step 3: Perform an inverse Fourier transform on the spectral correlation function in the spectral correlation function matrix to obtain the corresponding cyclic autocorrelation function. The initial cyclic autocorrelation function matrix can be constructed based on the cyclic autocorrelation function obtained by the inverse Fourier transform.

[0151] Step 4: Since a 1024-point signal can obtain a 1024-point CAF, we can obtain and The point with the maximum absolute value of the sum of squares is obtained. The specific value of is a positive integer.

[0152] That is, the embodiment of the present application considers polarization multiplexing (signal spectrum X polarization and signal spectrum Y polarization). After the CAF sequence is generated, the function of the delay module is to determine the delay amount n according to the peak position calculated by the target peak position formula; then, the first value of the delayed cyclic autocorrelation function (CAF) sequence is used to form a cyclic autocorrelation function (CAF) matrix, and the final CAF matrix (i.e., the target cyclic autocorrelation function matrix) is: This matrix takes into account the influence of dispersion effect on CAF matrix clock modulation.

[0153] Step 5: According to the timing error estimation formula in the target timing error detection algorithm Calculate the timing error.

[0154] Steps S301 to S305 shown in the embodiment of the present application are generated by generating a random modulation signal; inserting zeros in the even bits of the random modulation signal to obtain an initial training sequence; generating a target communication frame based on the initial training sequence and the communication signal; sending the target communication frame to the receiving end of the Nyquist system; so that the receiving end extracts the initial training sequence in the target communication frame, and performs data processing on the initial training sequence to obtain the target training sequence, and estimates the timing error of the target communication frame based on the target training sequence and the target timing error detection algorithm to obtain the timing error estimation result. The embodiment of the present application enhances the tolerance of the timing error detection algorithm to dispersion, polarization mode dispersion effect and differential group delay damage by designing the training sequence of the RZ code at the transmitting end and sending it to the receiving end, thereby providing accurate timing error estimation under complex channel conditions. At the same time, the timing error estimation algorithm is designed using second-order cyclic statistics, which can more effectively handle the robustness of the timing error detection algorithm to dispersion (CD), polarization mode dispersion (PMD) effect and differential group delay (DGD) damage in the optical fiber channel, so as to achieve accurate estimation of the timing error.

[0155] In order to explain the principle of the technical solution of the present invention in detail, the overall process of the present invention is described below in combination with some specific embodiments. It is easy to understand that the following is an explanation of the technical principle of the present invention and cannot be regarded as a limitation of the present invention.

[0156] The general process of the timing error estimation method of the Nyquist system provided in the embodiment of the present application includes two parts: a transmitting end and a receiving end. The specific implementation process is as follows:

[0157] (1) The steps completed at the transmitting end include: firstly, generating a random QPSK signal at the transmitting end; then, inserting zeros into the even bits of the random QPSK signal to form a training sequence with a block size of 512 bits; then, splicing the training sequence and the communication signal to be sent to obtain a target spliced ​​signal; then, mapping the target spliced ​​signal using a 16QAM mapping method to obtain a target mapped signal; finally, performing Nyquist pulse shaping on the target mapped signal to obtain a target communication frame, so as to transmit the target communication frame to the receiving end through an optical communication channel.

[0158] (2) The steps completed at the receiving end include: 1) firstly, the oscilloscope at the receiving end is used to collect the orthogonally polarized discrete digital signals x and discrete digital signals y in the target communication frame; then, the discrete digital signals x and discrete digital signals y are matched filtered and resampled to obtain a 1-SPS target training sequence, and then the target training sequence is signal intercepted according to the interception threshold with an interception time length of W to obtain the signal spectrum X and signal spectrum Y. 2) Four cyclic periodogram functions (P xx , P xy, P yx , P yy ), the cyclic periodogram function can be regarded as an estimate of the spectral correlation function (SCF). The spectral correlation function matrix SCF(f) corresponding to the spectral correlation function can be calculated through the calculation expressions of the above four cyclic periodogram functions. 3) The corresponding cyclic autocorrelation function can be obtained by inverse Fourier transforming the spectral correlation function in the spectral correlation function matrix. The initial cyclic autocorrelation function matrix can be constructed based on the cyclic autocorrelation function obtained by inverse Fourier transform. 4) Since a 1024-point signal can obtain a 1024-point CAF, by traversing and The number of points where the maximum absolute value of the square sum is located, and the specific value of τ is a positive integer. That is, the embodiment of the present application takes into account polarization multiplexing (signal spectrum X polarization and signal spectrum Y polarization). After the CAF sequence is generated, the function of the delay module is to determine the delay amount n according to the peak position calculated by the target peak position formula; then, the first value of the delayed cyclic autocorrelation function (CAF) sequence is used to construct a cyclic autocorrelation function (CAF) matrix, and the final CAF matrix (that is, the target cyclic autocorrelation function matrix) CAF (τ) is obtained. This matrix takes into account the influence of dispersion effects on the CAF matrix clock adjustment. 5) According to the timing error estimation formula Calculate the timing error.

[0159] The RZ-TED timing error estimation algorithm provided in the embodiment of the present application has very small jitter under various optical fiber environmental conditions, and has a high tolerance for dispersion effects, polarization effects, differential group delay, low signal-to-noise ratio, etc., highlighting the robustness and adaptability of the RZ-TED timing error estimation algorithm proposed in the embodiment of the present application, which is of great practical significance for improving the performance and reliability of coherent optical communication systems, especially when facing extreme channel conditions.

[0160] It should be noted that this embodiment only briefly illustrates the general process of the timing error estimation method of the Nyquist system. The detailed description of each step can refer to the relevant content in the aforementioned embodiment and will not be repeated here. It can be understood that the present invention is not limited to this.

[0161] The embodiment of the present application provides a timing error estimation method and device for a Nyquist system, which generates a random modulation signal; inserts zeros into the even bits of the random modulation signal to obtain an initial training sequence; generates a target communication frame based on the initial training sequence and the communication signal; and sends the target communication frame to the receiving end of the Nyquist system; so that the receiving end extracts the initial training sequence in the target communication frame, performs data processing on the initial training sequence to obtain the target training sequence, and estimates the timing error of the target communication frame based on the target training sequence and the target timing error detection algorithm to obtain the timing error estimation result. The embodiment of the present application enhances the tolerance of the timing error detection algorithm to dispersion, polarization mode dispersion effect and differential group delay damage by designing the training sequence of the RZ code at the transmitting end and sending it to the receiving end, thereby providing accurate timing error estimation under complex channel conditions. At the same time, the timing error estimation algorithm is designed by using the second-order cyclic statistics, which can more effectively handle the robustness of the timing error detection algorithm to dispersion (CD), polarization mode dispersion (PMD) effect and differential group delay (DGD) damage in the optical fiber channel, so as to achieve accurate estimation of the timing error.

[0162] The timing error estimation algorithm proposed in the embodiment of the present application can effectively tolerate the dispersion and polarization effects in the system, and provides a timing synchronization solution for the optical communication system in an actual complex channel environment. The timing error estimation algorithm of the embodiment of the present application specifically includes the following key points:

[0163] (1) Application of cyclostationary theory: The embodiment of the present application adopts second-order cyclic statistics to design a timing error estimation algorithm, which can more effectively handle the robustness of the timing error detection algorithm to chromatic dispersion (CD), polarization mode dispersion (PMD) effects and differential group delay (DGD) damage in the optical fiber channel.

[0164] (2) Adaptability of the Nyquist system (tolerance to small roll-off factors): The timing error estimation algorithm provided in the embodiment of the present application specifically designs a special RZ code as a training sequence, which has a high tolerance to the Nyquist pulse shaping system or a small roll-off factor (ROF<0.2), which is particularly important for actual optical communication systems.

[0165] (3) Tolerance to polarization effects: The timing error estimation algorithm provided in the embodiments of the present application is specially designed to have a high tolerance to chromatic dispersion (CD), polarization mode dispersion (PMD) effects and differential group delay (DGD) damage in the optical fiber channel. This is particularly important for actual optical communication systems because these effects can seriously affect the integrity of the signal and the accurate estimation of the timing error.

[0166] (4) Transparency of format and system parameters: The timing error estimation algorithm provided in the embodiment of the present application does not depend on specific modulation formats or system parameters, and provides a universal solution that can be adapted to Nyquist systems and non-Nyquist coherent fiber communication scenarios. It provides a timing synchronization solution for optical communication systems in actual complex channel environments, and can be applied to different signal modulation formats and system configurations.

[0167] In summary, the embodiments of the present application provide an efficient, accurate and adaptable technical solution with broad application prospects and practical value. Specifically, the timing error estimation algorithm based on high-order cyclic statistics is specially designed to deal with the timing error estimation problem in the severely band-limited Nyquist system, and can more effectively handle the bandwidth-limited situation of the signal. The timing error estimation algorithm provided by the embodiment of the present application utilizes the relevant characteristics of the special training sequence (RZ code) itself to extract the timing error information, which means that even when the spectrum information of the signal is limited, the timing error estimation algorithm provided by the embodiment of the present application can still maintain high performance and accuracy. Moreover, in optical communication systems, dispersion and polarization effects are the main factors affecting signal integrity. The timing error estimation algorithm provided by the embodiment of the present application takes these channel effects into consideration during design, and uses cyclic statistics to reduce the negative impact of error estimation during dispersion and polarization rotation. By designing the training sequence of the RZ code and applying the second-order cyclic statistics, the tolerance of the timing error estimation algorithm to the dispersion, polarization mode dispersion effect and differential group delay damage in the optical fiber channel is enhanced, so that accurate timing error estimation can be provided under complex channel conditions, and the tolerance to low roll-off factor signals can be improved, so that the algorithm can run stably under a wider range of system parameters. That is, the timing error estimation algorithm provided in the embodiment of the present application can effectively tolerate the dispersion and polarization rotation effects, while reducing the complexity of the algorithm, thereby improving the calculation efficiency and improving the adaptability of the system to different channel conditions.

[0168] See also Figure 5 , Figure 5 : is a schematic diagram of the structure of the timing error estimation device of the Nyquist system provided in an embodiment of the present application when it is applied to the transmitting end of the Nyquist system, and the device includes the following modules:

[0169] A random modulation signal generating module 501, used to generate a random modulation signal;

[0170] An initial training sequence building module 502 is used to insert zeros into even bits of the random modulation signal to obtain an initial training sequence;

[0171] A target communication frame generation module 503 is used to generate a target communication frame based on the initial training sequence and the communication signal;

[0172] The target communication frame sending module 504 is used to send the target communication frame to the receiving end of the Nyquist system; so that the receiving end extracts the initial training sequence in the target communication frame, performs data processing on the initial training sequence to obtain a target training sequence, and estimates the timing error of the target communication frame based on the target training sequence and a target timing error detection algorithm to obtain a timing error estimation result.

[0173] See also Figure 6 , Figure 6 : is a schematic diagram of the structure of the timing error estimation device of the Nyquist system provided in an embodiment of the present application when it is applied to the receiving end of the Nyquist system. The device includes the following modules:

[0174] The target communication frame receiving module 601 is used to receive the target communication frame sent by the transmitting end; wherein the target communication frame includes an initial training sequence and a communication signal;

[0175] An initial training sequence extraction module 602 is used to perform data extraction processing on the target communication frame to obtain the initial training sequence in the target communication frame;

[0176] A target training sequence acquisition module 603 is used to perform data processing on the initial training sequence to obtain a target training sequence;

[0177] A cyclic autocorrelation function matrix acquisition module 604 is used to construct a target cyclic autocorrelation function matrix based on the target training sequence;

[0178] A timing error estimation module 605 is used to perform timing error estimation on the target communication frame based on the target cyclic autocorrelation function matrix and the target timing error detection algorithm to obtain a timing error estimation result;

[0179] Wherein, the target communication frame is based on Figure 5 The timing error estimation device of the Nyquist system is determined.

[0180] It can be understood that the contents of the above method embodiments are all applicable to the present device embodiments, the functions specifically implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0181] The embodiment of the present application also provides an electronic device, the electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the timing error estimation method of the Nyquist system when executing the computer program. The electronic device can be any intelligent terminal including a tablet computer, a car computer, etc.

[0182] It can be understood that the contents of the above method embodiments are all applicable to the present device embodiments, the functions specifically implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0183] See also Figure 7 , Figure 7 The hardware structure of an electronic device of another embodiment is illustrated, and the electronic device includes:

[0184] The processor 701 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (Application Specific Integrated Circuit, ASIC for short), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application;

[0185] The memory 702 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 702 can store an operating system and other application programs. When the technical solution provided in the embodiment of this specification is implemented by software or firmware, the relevant program code is stored in the memory 702, and the processor 701 calls and executes the timing error estimation method of the Nyquist system of the embodiment of the present application;

[0186] Input / output interface 703, used to implement information input and output;

[0187] Communication interface 704, used to realize communication interaction between the device and other devices, which can be realized through wired mode (such as USB, network cable, etc.) or wireless mode (such as mobile network, WIFI, Bluetooth, etc.);

[0188] A bus 705 that transmits information between the various components of the device (e.g., the processor 701, the memory 702, the input / output interface 703, and the communication interface 704);

[0189] The processor 701 , the memory 702 , the input / output interface 703 and the communication interface 704 are connected to each other in communication within the device via a bus 705 .

[0190] An embodiment of the present application further provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the timing error estimation method of the Nyquist system is implemented.

[0191] It can be understood that the contents of the above method embodiments are all applicable to the present storage medium embodiments, the functions specifically implemented by the present storage medium embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0192] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0193] The timing error estimation method of the Nyquist system, the timing error estimation device of the Nyquist system, the electronic device and the storage medium provided in the embodiment of the present application generate a random modulation signal; insert zeros into the even bits of the random modulation signal to obtain an initial training sequence; generate a target communication frame based on the initial training sequence and the communication signal; send the target communication frame to the receiving end of the Nyquist system; so that the receiving end extracts the initial training sequence in the target communication frame, performs data processing on the initial training sequence to obtain the target training sequence, and performs timing error estimation on the target communication frame based on the target training sequence and the target timing error detection algorithm to obtain a timing error estimation result. The embodiment of the present application enhances the tolerance of the timing error detection algorithm to dispersion, polarization mode dispersion effect and differential group delay damage by designing the training sequence of the RZ code at the transmitting end and sending it to the receiving end, thereby providing accurate timing error estimation even under complex channel conditions.

[0194] The embodiments described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application and do not constitute a limitation on the technical solutions provided in the embodiments of the present application. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0195] Those skilled in the art will appreciate that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than shown in the figures, or a combination of certain steps, or different steps.

[0196] The device embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separated, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0197] Those skilled in the art will appreciate that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices may be implemented as software, firmware, hardware, or a suitable combination thereof.

[0198] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0199] It should be understood that in the present application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0200] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the above units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0201] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0202] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0203] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including multiple instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, referred to as ROM), random access memory (Random Access Memory, referred to as RAM), disk or optical disk and other media that can store programs.

[0204] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but the scope of the rights of the present invention is not limited thereto. Any modification, equivalent substitution and improvement made by a person skilled in the art without departing from the scope and essence of the present invention should be within the scope of the rights of the present invention.

Claims

1. A timing error estimation method for a Nyquist system, characterized in that: Applied to the transmitting end of the Nyquist system, the method comprises the following steps: generating a random modulation signal; Inserting zeros into even-numbered bits of the random modulation signal to obtain an initial training sequence; Based on the initial training sequence and the communication signal, generating a target communication frame; The target communication frame is sent to the receiving end of the Nyquist system; so that the receiving end extracts the initial training sequence in the target communication frame, performs data processing on the initial training sequence to obtain a target training sequence, and performs timing error estimation on the target communication frame based on the target training sequence and a target timing error detection algorithm to obtain a timing error estimation result.

2. The method according to claim 1, characterized in that The generating a target communication frame based on the initial training sequence and the communication signal comprises: Splicing the initial training sequence and the communication signal to obtain a target spliced ​​signal; Mapping the target splicing signal using a target signal mapping method to obtain a target mapping signal; Performing Nyquist pulse shaping on the target mapping signal to obtain the target communication frame.

3. A timing error estimation method for a Nyquist system, characterized in that: Applied to the receiving end of the Nyquist system, the method comprises the following steps: Receiving a target communication frame sent by a transmitting end; wherein the target communication frame includes an initial training sequence and a communication signal; Performing data extraction processing on the target communication frame to obtain the initial training sequence in the target communication frame; Performing data processing on the initial training sequence to obtain a target training sequence; Constructing a target cyclic autocorrelation function matrix based on the target training sequence; Performing timing error estimation on the target communication frame based on the target cyclic autocorrelation function matrix and the target timing error detection algorithm to obtain a timing error estimation result; Wherein, the target communication frame is determined according to the timing error estimation method of the Nyquist system according to any one of claims 1-2.

4. The method according to claim 3, characterized in that The performing data processing on the initial training sequence to obtain a target training sequence includes: The initial training sequence is resampled using a target resampling rule to obtain the target training sequence; wherein the target training sequence is applied to a timing error detection unit in the receiving end.

5. The method according to claim 3, characterized in that: The signal representation form of the target communication frame at the receiving end is a discrete digital signal, and constructing a target cyclic autocorrelation function matrix based on the target training sequence includes: intercepting the target training sequence according to the target interception time length to obtain a target discrete digital signal; generating a spectrum correlation function based on the target discrete digital signal; Performing inverse Fourier transform processing on the spectrum correlation function to obtain an initial cyclic autocorrelation function; Constructing an initial cyclic autocorrelation function matrix according to the initial cyclic autocorrelation function; The target cyclic autocorrelation function matrix is ​​generated based on the initial cyclic autocorrelation function matrix.

6. The method according to claim 5, characterized in that The generating the target cyclic autocorrelation function matrix based on the initial cyclic autocorrelation function matrix comprises: The target cyclic autocorrelation function in the initial cyclic autocorrelation function matrix is ​​calculated using a target peak position formula to obtain the target cyclic autocorrelation function matrix at the target peak position.

7. The method according to claim 6, characterized in that The target peak position formula is: Among them, τ represents the target peak position point, Expressed as the cyclic autocorrelation function of signal x and signal x, is represented as the circular autocorrelation function of signals x and y, and argmax is represented as an operator that returns the index of the maximum value.

8. The method according to claim 3, characterized in that The performing timing error estimation on the target communication frame based on the target cyclic autocorrelation function matrix and the target timing error detection algorithm to obtain a timing error estimation result includes: Based on the target cyclic autocorrelation function matrix, the timing error estimation formula in the target timing error detection algorithm is combined to estimate the timing error of the target communication frame to obtain the timing error estimation result; the timing error estimation formula is: in, is represented as the timing error, CAF is represented as the initial cyclic autocorrelation function matrix, CAF(τ) is represented as the target cyclic autocorrelation function matrix of the τth position point, SCF is represented as the spectrum correlation function matrix, det is represented as the operator for taking the matrix determinant, and -Im{·} is represented as the operator for taking the imaginary part of a complex number.

9. A timing error estimation device for a Nyquist system, characterized in that: Applied to the transmitting end of the Nyquist system, the device comprises the following modules: A random modulation signal generation module, used for generating a random modulation signal; An initial training sequence building module, used for inserting zeros into even-numbered bits of the random modulation signal to obtain an initial training sequence; A target communication frame generation module, used for generating a target communication frame based on the initial training sequence and the communication signal; The target communication frame sending module is used to send the target communication frame to the receiving end of the Nyquist system; so that the receiving end extracts the initial training sequence in the target communication frame, performs data processing on the initial training sequence to obtain a target training sequence, and estimates the timing error of the target communication frame based on the target training sequence and a target timing error detection algorithm to obtain a timing error estimation result.

10. A timing error estimation device for a Nyquist system, characterized in that: Applied to the receiving end of the Nyquist system, the device comprises the following modules: A target communication frame receiving module is used to receive a target communication frame sent by a transmitting end; wherein the target communication frame includes an initial training sequence and a communication signal; An initial training sequence extraction module, used for performing data extraction processing on the target communication frame to obtain the initial training sequence in the target communication frame; A target training sequence acquisition module is used to perform data processing on the initial training sequence to obtain a target training sequence; A cyclic autocorrelation function matrix acquisition module, used to construct a target cyclic autocorrelation function matrix based on the target training sequence; A timing error estimation module, used to perform timing error estimation on the target communication frame based on the target cyclic autocorrelation function matrix and the target timing error detection algorithm to obtain a timing error estimation result; Wherein, the target communication frame is determined according to the timing error estimation device of the Nyquist system described in claim 9.

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