WO2023193518A1 - 信号处理方法、电子设备和计算机可读存储介质 - Google Patents

信号处理方法、电子设备和计算机可读存储介质 Download PDF

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Publication number
WO2023193518A1
WO2023193518A1 PCT/CN2023/075277 CN2023075277W WO2023193518A1 WO 2023193518 A1 WO2023193518 A1 WO 2023193518A1 CN 2023075277 W CN2023075277 W CN 2023075277W WO 2023193518 A1 WO2023193518 A1 WO 2023193518A1
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Prior art keywords
training symbol
reference phase
frequency offset
symbol block
phase
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PCT/CN2023/075277
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English (en)
French (fr)
Inventor
王永奔
杨桃
秦英凯
陈雪
王卫明
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中兴通讯股份有限公司
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Publication of WO2023193518A1 publication Critical patent/WO2023193518A1/zh

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/0014—Carrier regulation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/0014—Carrier regulation
    • H04L2027/0024—Carrier regulation at the receiver end
    • H04L2027/0026—Correction of carrier offset

Definitions

  • Embodiments of the present application relate to the field of communication technology, and in particular to a signal processing method, electronic device, and computer-readable storage medium.
  • WDM Wavelength Division Multiplexing
  • Faster-than-Nyquist (FTN) rate optical transmission technology breaks the orthogonal transmission criterion by compressing the symbol interval in the time domain or compressing the channel interval in the frequency domain, resulting in a channel interval smaller than the symbol rate and a transmission rate
  • Multiplexing signals with higher spectral efficiency exceeding the Nyquist rate, and using the computing power provided by DSP technology to equalize and compensate for transmission impairments, has the characteristics of high efficiency, low cost, and low power consumption, becoming the next generation of large-capacity coherent Optical transmission technology has great potential for development.
  • the embodiments of the present application are intended to provide a signal processing method, electronic device, and computer-readable storage medium.
  • Embodiments of the present application provide a signal processing method, which includes: extracting M*N training symbols within M training symbol blocks in a received signal, and removing the signal modulation phase; wherein the received signal is a structural element of the transmitting end.
  • a training symbol block of length N is inserted every K valid signals; a phase difference operation is performed on the training symbols with an interval of d in each training symbol block, and a corresponding one when the interval is d is obtained.
  • a group of complex sample values and by adjusting the value of d, to obtain multiple groups of complex sample values corresponding to different intervals; according to the multiple groups of complex sample values, a rough estimate of the frequency offset is obtained; according to the frequency The rough estimation value and the preset residual frequency difference value are used to determine the frequency offset estimation range; based on the frequency offset estimation range, a fine frequency offset estimation value is obtained.
  • An embodiment of the present application also provides an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores information that can be executed by the at least one processor. Instructions, which are executed by the at least one processor, so that the at least one processor can execute the above-mentioned signal processing method.
  • Embodiments of the present application also provide a computer-readable storage medium that stores a computer program.
  • the computer program is executed by a processor, the above-mentioned signal processing method is implemented.
  • Figure 1 is a flow chart of the signal processing method mentioned in the embodiment of the present application.
  • Figure 2 is a schematic diagram of the frame structure of the received signal mentioned in the embodiment of the present application.
  • Figure 3 is a flow chart of an implementation manner of step 103 mentioned in the embodiment of this application.
  • Figure 4 is a flow chart of an implementation manner of step 105 mentioned in the embodiment of this application.
  • Figure 5 is the cycle slip detection process of the reference phase of the effective signal mentioned in the embodiment of the present application.
  • Figure 6 is a flow chart of an implementation manner of step 202 mentioned in the embodiment of this application.
  • Figure 7 is a flow chart of an implementation method for determining whether a jump occurs in the reference phase of the training symbol block mentioned in the embodiment of the present application;
  • Figure 8 is a flow chart of an implementation method of cycle slip detection in step 204 mentioned in the embodiment of this application;
  • Figure 9 is a flow chart of an implementation method for compensating the reference phase where a cycle slip occurs as mentioned in the embodiment of the present application;
  • Figure 10 is a flow chart of the carrier recovery method mentioned in the embodiment of this application.
  • Figure 11 is a graph showing the relationship between residual frequency offset and frequency offset of FTN-PM-16QAM mentioned in the embodiment of the present application.
  • Figure 12 is a graph showing the relationship between the frequency offset size and the estimated residual frequency offset of the fourth power FFT frequency offset estimation algorithm mentioned in the embodiment of this application under FTN-PM-16QAM;
  • Figure 13 is a graph of estimated phase noise under FTN-PM-16QAM by the QPSK segmentation algorithm mentioned in the embodiment of this application;
  • Figure 14 is a graph showing the relationship between the laser linewidth and BER of the FTN-PM-16QAM mentioned in the embodiment of this application;
  • Figure 15 is a schematic structural diagram of the electronic device mentioned in the embodiment of the present application.
  • Embodiments of the present application relate to a signal processing method applied to an electronic device.
  • the electronic device may be a signal receiving end.
  • the signal receiving end receives a signal sent by a transmitting end and processes the received signal.
  • the flow chart of the signal processing method in this embodiment can be seen in Figure 1, including:
  • Step 101 Extract M*N training symbols within the M training symbol blocks in the received signal, and remove the signal modulation phase; where, the received signal is that when the transmitting end constructs the signal to be sent, one is inserted every K valid signals.
  • Step 102 Perform phase difference calculation on the training symbols with an interval of d in each training symbol block to obtain a set of complex sample values corresponding to the interval of d, and adjust the value of d to obtain the values of different intervals. Corresponding sets of complex sample values.
  • Step 103 Obtain a rough estimate of the frequency offset based on multiple sets of complex sample values.
  • Step 104 Determine the frequency offset estimation range based on the rough estimate of the frequency offset and the preset residual frequency difference value.
  • Step 105 Obtain a fine frequency offset estimate based on the frequency offset estimation range.
  • the signal receiving end first extracts M*N training symbols within the M training symbol blocks in the received signal, and performs a phase difference operation on the training symbols with an interval of d in each training symbol block to obtain an interval of d.
  • a rough frequency offset estimate is first performed to obtain a rough estimate of the frequency offset, and then the frequency offset is determined by combining the rough estimate of the frequency offset with the preset residual frequency difference value. Estimate range. Then, according to the frequency offset estimation range, a fine frequency offset estimation is performed to obtain a fine frequency offset estimation value, which is beneficial to improving the accuracy and reliability of the frequency offset estimation under the FTN system.
  • step 101 when the transmitting end constructs the signal to be sent, a training symbol block of length N is inserted every K valid signals. That is, when the transmitting end constructs the data frame, a training symbol block of length N is inserted every K valid signals. is the training symbol block for N. Therefore, when the receiving end receives the signal sent by the transmitting end, it can extract a total of M*N training symbols within the M training symbol blocks in the received signal. Among them, M, N, and K are all integers greater than 1, and K is greater than N.
  • the schematic diagram of the frame structure of the received signal can be seen in Figure 2.
  • the training sequence in Figure 2 is a training symbol block of length N
  • the valid data in Figure 2 is K valid signals.
  • K is much larger than N.
  • the transmitting end can insert a training symbol block with a length of 8 every 512 valid signals, that is, 8 training symbols can be inserted every 512 valid signals. However, in actual implementation, this is not the limit.
  • removing the signal modulation phase can also be understood as: removing the original phase of the training symbol.
  • the method of removing the signal modulation phase may be: multiplying the extracted training symbol and the complex conjugate of the original training symbol to obtain a training symbol with the signal modulation phase removed.
  • TS p(lk) A*exp(j ⁇ s ) (1)
  • A represents the amplitude of the training symbol
  • ⁇ s represents the phase of the training symbol
  • 1 ⁇ l ⁇ M the amplitude of the training symbol
  • Formula (1) can be understood as the expression of the original training symbol.
  • R p(l,k) A*exp ⁇ j( ⁇ s +2 ⁇ fkT+ ⁇ L (k)) ⁇ +n(k) (2)
  • ⁇ f is the frequency offset generated by the local oscillator laser and the transmitter laser
  • 2 ⁇ fkT is the phase error component caused by the carrier frequency offset on the kth training symbol
  • T is the symbol period
  • ⁇ L represents the phase error introduced by the laser line width
  • n Represents amplifier spontaneous emission noise (Amplifier Spontaneous Emission Noise, ASE noise).
  • ASE noise is the phase noise caused by ASE, which conforms to Gaussian distribution and has a mean value of zero.
  • Formula (2) can be understood as the expression of the training symbols received by the receiver.
  • the signal modulation phase can be removed by multiplying the training symbol received by the receiving end by the complex conjugate of the original training symbol, and a training symbol with the signal modulation phase removed is obtained.
  • the expression of the training symbol that removes the signal modulation phase is shown in formula (3):
  • formula (3) can be expressed by the following formula (4): S p(l,k) ⁇ A 2 exp ⁇ j(2 ⁇ fkT+ ⁇ L (k)+ ⁇ n (k)) ⁇ (4)
  • ⁇ n is ASE noise, which conforms to Gaussian distribution and has a mean value of zero.
  • the receiving end performs phase difference calculation on the training symbols with an interval of d in each training symbol block to obtain a set of complex sample values corresponding to the interval of d, and adjusts the value of d to obtain different Multiple sets of complex sample values corresponding to interval values.
  • a group of complex sample values may include several complex sample values.
  • By adjusting the value of d multiple sets of complex sample values corresponding to different intervals can be obtained in sequence, and each interval d corresponds to a set of complex sample values.
  • phase noise introduced by the laser linewidth changes slowly relative to the symbol rate of the signal, its phase impact on several adjacent symbols can be regarded as the same. Therefore, it can be calculated by
  • the phase difference operation of training symbols at different intervals within each training symbol block is used to remove the influence of ⁇ L , and multiple complex samples with phase noise caused by line width removed are obtained.
  • the following formula (5) can be used to obtain a set of complex sample values corresponding to the interval d:
  • S p(l,k) is the expression of the k-th training symbol in the l-th training symbol block, is the expression of the complex conjugate of the k+dth training symbol in the lth training symbol block, ⁇ f is the frequency offset produced by the local oscillator laser and the transmitter laser, 2 ⁇ fkT is the carrier frequency offset caused to the kth training symbol Phase error component, T is the symbol period, ⁇ L represents the phase error introduced by the laser line width, ⁇ n is the phase noise caused by ASE, ⁇ n ' represents the difference in phase noise caused by ASE between two training symbols separated by d.
  • phase difference calculation can be performed on each adjacent training symbol separated by 0 training symbols.
  • phase difference calculation can be performed on any two training symbols separated by one training symbol.
  • phase difference operations can be performed on training symbols at different intervals within each training symbol block to obtain multiple sets of complex sample values corresponding to different intervals. Each interval can correspond to a group of complex sample values, and each group of complex sample values includes several complex sample values.
  • step 103 the receiving end performs a rough frequency offset estimate based on multiple sets of complex samples to obtain a rough frequency offset estimate.
  • step 103 can refer to Figure 3, including:
  • Step 1031 Perform an average operation on several complex means in each group of complex samples to obtain first complex means corresponding to values at different intervals.
  • Step 1032 Take the argument angles of the first complex means corresponding to different interval values, and calculate the initial frequency offset estimation values corresponding to different interval values.
  • Step 1033 Obtain a rough estimate of the frequency offset based on the initial frequency offset estimates corresponding to different interval values.
  • step 1031 several complex means in each group of complex samples are averaged, and the first complex mean avg can be obtained through the following formula (6):
  • ⁇ f is the estimated value of carrier frequency offset.
  • the corresponding first complex mean value can be obtained for all interval values.
  • the receiving end takes the argument angles of the first complex means corresponding to different interval values, and calculates the initial frequency offset estimation values corresponding to different intervals, and each interval corresponds to an initial frequency offset estimation value.
  • the argument angle of the first complex mean avg the phase error component introduced by the carrier frequency offset can be obtained, and then a rough estimate of the frequency offset F1 can be obtained through calculation.
  • the rough frequency offset estimate value F1 can also be understood as the first-order frequency offset estimation result.
  • step 1033 may be implemented as follows: based on the proportion of the number of complex samples in each group of complex samples to the total number of complex samples in multiple groups of complex samples, determine the values corresponding to different intervals. Frequency offset estimation initial value weight; according to the frequency offset estimation initial value weight corresponding to different interval values and the frequency offset estimation initial value corresponding to different interval values, a rough estimate of frequency offset can be obtained, which is beneficial to improving the accuracy of the rough frequency offset estimate. accuracy and stability.
  • the proportion of the number of complex sample values in each group of complex sample values to the total number of complex sample values in multiple groups of complex sample values can be used as the initial weight of the frequency offset estimation of the interval d corresponding to the group of complex sample values.
  • the total number of complex samples obtained based on a training symbol block including N training symbols is N(N-1)/2.
  • the frequency corresponding to each interval can be obtained. Partial estimation of initial value weights.
  • a weighted calculation is performed on the initial value of the frequency offset estimate corresponding to each interval to obtain a weighted calculation result.
  • the weighted calculation result is a rough estimate of the frequency offset.
  • the initial value weights of frequency offset estimates corresponding to different intervals can also be preset.
  • the initial value weights of frequency offset estimates corresponding to different intervals can also be the same. However, this embodiment does not limit this.
  • the receiving end determines the frequency offset estimation range based on the rough frequency offset estimate and the preset residual frequency difference value.
  • the residual frequency difference value is the maximum possible residual frequency offset value f m of the FTN system.
  • step 105 the receiving end performs a fine frequency offset estimation according to the frequency offset estimation range to obtain a frequency offset fine estimation value.
  • CZT transform can be used to perform fine frequency offset estimation to obtain a fine frequency offset estimate.
  • the second-order linear frequency modulation Z-transform CZT process can be assisted to complete the second-order chirp Z-transform CZT process based on the rough estimate of the frequency offset, that is, the first-order frequency offset estimation result, to achieve high-precision frequency offset estimation.
  • step 105 can refer to Figure 4, including:
  • Step 1051 Determine the starting frequency point and the ending frequency point of the frequency offset estimation range.
  • Step 1052 Determine the number of linear frequency modulation z-transform CZT output sequence points according to the starting frequency point, the ending frequency point and the preset frequency resolution.
  • Step 1053 Perform CZT on the received signal according to the CZT output sequence points to obtain a fine estimate of the frequency offset.
  • the starting frequency point and the ending frequency point of the frequency offset estimation range are determined, and then combined with the CZT frequency offset estimation accuracy, that is, the frequency resolution, which is conducive to the final realization of high-precision frequency offset estimation for the system, and an accurate Fine estimate of frequency offset.
  • the starting frequency point is the lower limit of the frequency offset estimation range
  • the end frequency point is the upper limit of the frequency offset estimation range
  • the frequency resolution can also be understood as the CZT frequency offset estimation accuracy.
  • the frequency resolution can be set according to actual needs, for example, it can be 1.56 MHz. However, this embodiment does not limit the frequency resolution.
  • the receiving end determines the number of CZT output sequence points based on the start frequency point, end frequency point and preset frequency resolution.
  • step 1053 the receiving end performs CZT on the received signal according to the CZT output sequence points to obtain a fine estimate of the frequency offset.
  • the receiving end can perform a 128-point CZT transform on the received signal raised to the power of t to obtain a fine estimate of the frequency offset.
  • t can be selected according to actual needs. In this embodiment, t can be 4, that is, the receiving end can perform a 128-point CZT transform on the received signal raised to the fourth power to obtain a fine estimate of the frequency offset F2.
  • a cycle slip detection process of the reference phase of the effective signal may also be included.
  • the cycle slip detection process includes:
  • Step 201 Perform frequency offset compensation on the training symbol block and the effective signal according to the frequency offset fine estimation value, and obtain the frequency offset compensated training symbol block and the frequency offset compensated effective signal.
  • Step 202 Determine the reference phase of the training symbol block based on the frequency offset compensated training symbol block.
  • Step 203 Determine the reference phase of the effective signal based on the effective signal after frequency offset compensation.
  • Step 204 Perform cycle slip detection on the reference phase of the effective signal based on the reference phase of the training symbol block and the reference phase of the effective signal.
  • Step 205 When it is determined that a cycle slip occurs in the reference phase of the effective signal, compensate the reference phase in which the cycle slip occurs.
  • Frequency offset estimation and phase offset estimation can reuse the same set of periodic training symbols, which is beneficial to reducing algorithm complexity and achieving efficient detection of effective signal cycle slips.
  • the receiving end can perform frequency offset compensation on the received signal according to the fine frequency offset estimation value, that is, perform frequency offset compensation on each training symbol and each effective signal in the received signal.
  • step 202 the receiving end determines the reference phases of the M training symbol blocks extracted from the received signal based on the frequency offset compensated training symbol blocks.
  • step 202 can refer to Figure 6, including:
  • Step 2021 Remove the signal modulation phase of the training symbols in the frequency offset compensated training symbol block to obtain a training symbol block with the signal modulation phase removed.
  • Step 2022 Perform an average operation on the training symbols in the training symbol block with the signal modulation phase removed to obtain a second complex mean.
  • Step 2023 Obtain the reference phase of the training symbol block according to the second complex mean value.
  • the reference phase of the training symbol block can be accurately obtained .
  • the signal modulation phase can be removed by performing a phase difference operation on the training symbol after frequency offset compensation and the original training symbol.
  • the method for removing the signal modulation phase is not limited in this embodiment. In actual implementation, methods other than phase difference calculation may also be used to remove the signal modulation phase.
  • performing a phase difference operation on the training symbols after frequency offset compensation and the original training symbols to remove the signal modulation phase can be achieved by multiplying the frequency offset compensated training symbols by the complex conjugate of the original training symbols.
  • the training symbol after frequency offset compensation is denoted as R′ p
  • ⁇ s (k) is the modulation phase of the k-th training symbol
  • ⁇ L represents the phase error introduced by the laser line width
  • ⁇ n represents the ASE noise.
  • step 2022 the receiving end performs an average operation on the training symbols in the training symbol block that removes the signal modulation phase to obtain a second complex average.
  • the N training symbols in the current training symbol block can be calculated through the following formula (9): Perform an average operation on the symbol to obtain the second complex mean of the smoothed ASE noise:
  • step 2023 can be implemented by: taking the argument angle of the second complex mean, obtaining the unexpanded reference phase based on the argument taken for the second complex mean, and obtaining the unexpanded reference phase based on the target reference phase and the preset phase. range, perform a dewinding operation on the unexpanded reference phase to obtain the expanded reference phase of the training symbol block; wherein, the target reference phase is the training symbol block adjacent to the training symbol block and located before the training symbol block.
  • the unfolded reference phase can be understood as: a reference phase that has not undergone an unwinding operation, and the unrolled reference phase can be understood as: a reference phase that has undergone an unwinding operation.
  • the preset phase range is: the phase range that can be estimated by phase estimation, for example, it can be 2 ⁇ .
  • phase estimation can only estimate the carrier phase within a certain range
  • unwinding the reference phase by unwinding the reference phase is helpful to avoid phase ambiguity problems in the reference phase.
  • the unrolled reference phase is unwrapped to obtain the unfolded reference phase of the training symbol block, including:
  • is the target reference phase that is, the expanded reference phase that can be used as a benchmark, or it can be the expanded reference phase of a training symbol block immediately before the l-th training symbol block, that is, the expansion of the l-1th training symbol block the subsequent reference phase.
  • R is the preset phase range
  • round is the downward rounding function. 1 ⁇ l ⁇ M.
  • the method further includes: sequentially using each frequency offset compensated training symbol block as the current training symbol block, and determining whether a jump occurs in the reference phase of the current training symbol block; When a jump occurs in the reference phase of the symbol block, the reference phase where the jump occurs is compensated to obtain a reference phase after the jump compensation.
  • the corresponding step 204 may be: performing cycle slip detection on the reference phase of the effective signal based on the jump-compensated reference phase of the current training symbol block and the reference phase of the effective signal.
  • the frequency offset compensated training symbol blocks sequentially enter a sliding window of length L, L is the length of m training symbol blocks, and m is greater than 1; determine whether a jump occurs in the reference phase of the current training symbol block
  • L is the length of m training symbol blocks, and m is greater than 1; determine whether a jump occurs in the reference phase of the current training symbol block
  • Step 301 Calculate the first phase difference between the reference phases of the first training symbol block and the last training symbol block within the sliding window.
  • Step 302 When the absolute value of the first phase difference value is less than the preset hopping threshold, determine that no hopping occurs in the reference phase of the current training symbol block.
  • Step 303 When the absolute value of the first phase difference value is greater than the preset hopping threshold, determine that a hopping occurs in the reference phase of the current training symbol block.
  • the length of the sliding window can be set according to actual needs, and the minimum can be set to 2, that is, 2 training symbol blocks can be accommodated in the sliding window.
  • the length of the sliding window may also be greater than 2, which is not limited in this embodiment.
  • the current training symbol block is the last training symbol block in the sliding window.
  • the training symbol blocks after frequency offset compensation are sequentially entered into a sliding window of length L, which can improve the accuracy of hopping detection.
  • the receiving end may calculate in real time the first phase difference value between the reference phases of the first training symbol block and the last training symbol block within the current sliding window.
  • the first phase difference value can be expressed as: ⁇ (l)- ⁇ (l+L-1), where ⁇ (l) is the reference phase of the first training symbol block in the sliding window, ⁇ (l+L-1 ) is the reference phase of the last training symbol block in the sliding window.
  • the first phase difference value can be understood as the phase difference value between the reference phase of the current training symbol block and the reference phase of the target training symbol block; wherein, the target training symbol block includes the current training symbol block and the reference phase of the target training symbol block.
  • the preset jump threshold value can be set according to actual needs, for example, it can be set to ⁇ /4.
  • step 303 assuming that the preset jump threshold value is ⁇ /4, when the absolute value of the first phase difference value is greater than the preset jump threshold value, that is, Then it is determined that a jump occurs in the reference phase of the training symbol block.
  • step 303 if a jump occurs in the reference phase, the jump in the reference phase may be compensated according to the first phase difference value.
  • compensating the reference phase that has jumped includes: if the first phase difference value is less than 0, then reducing the reference phase that has jumped. Get the compensated reference phase. If the first phase difference value is greater than 0, the reference phase where the transition occurs is increased. Obtain the compensated reference phase; where, is the jump angle corresponding to the training symbol, for example, it can be 2 ⁇ .
  • the detection and compensation of jumps in the reference phase are completed to facilitate the subsequent cycle slip detection of the reference phase of the effective signal based on the non-jump reference phase.
  • the flow chart of cycle slip detection in step 204 can be referred to Figure 8, including:
  • Step 2041 Use each frequency offset compensated training symbol block in turn as the current training symbol block to determine the reference phase of the target effective signal adjacent to the current training symbol block; wherein the target effective signal includes: the first effective signal and /or a second valid signal, the first valid signal is K/2 valid signals located before the current training symbol block, and the second valid signal is K/2 valid signals located after the current training symbol block.
  • Step 2042 Determine whether a cycle slip occurs in the reference phase of the target effective signal based on the second phase difference between the reference phase of the target effective signal and the reference phase of the current training symbol block.
  • the reference phase of the current training symbol block is used as a reference for cycle slip detection of the reference phase of the effective signals of half the length before and after it.
  • a cycle slip detection period includes a training symbol block and K/2 valid signals adjacent to the training symbol block.
  • the K/2 effective signals adjacent to the training symbol block can be understood as target effective signals adjacent to the training symbol block.
  • a single valid data block is divided into two parts, that is, the K valid signals are divided into the first K/2 valid signals and the last K/2 valid signals.
  • the phase difference value of the two effective signal phases ⁇ (k) is used to detect whether a cycle slip occurs based on the phase difference value.
  • a Quadrature Phase Shift Keying (QPSK) segmentation algorithm may be used to perform segmentation.
  • the effective signal is phase estimated to obtain the reference phase of the target effective signal.
  • a dewinding operation can be performed to unfold the reference phase of the target effective signal.
  • the following formula 11 can be used Expand the reference phase:
  • step 2042 if the absolute value of the second phase difference value is less than the preset cycle slip detection threshold, it is determined that no cycle slip occurs in the reference phase of the target effective signal; if the absolute value of the second phase difference value is greater than the preset cycle slip
  • the detection threshold determines the cycle slip of the reference phase of the target effective signal.
  • the preset cycle slip detection threshold can be determined according to the modulation method of the received signal. Different modulation methods may have different cycle slip thresholds. Taking QPSK and 16QAM as examples, the cycle slip threshold value can be ⁇ /4. However, this embodiment does not limit the size of the cycle slip detection threshold.
  • the preset cycle slip detection threshold is ⁇ /4.
  • step 205 the method of compensating the reference phase where a cycle slip occurs can be referred to Figure 9, including:
  • Step 2051 Use the position of the target valid signal as the starting point of the cycle slip.
  • Step 2052 Determine the end position of the cycle slip based on the starting position of the cycle slip; where the end position of the cycle slip is the position of the previous valid signal after the starting position of the cycle slip that satisfies the preset conditions.
  • the absolute value of the difference between the reference phase of the effective signal and the reference phase of the training symbol block is less than the cycle slip detection threshold.
  • Step 2053 Compensate the reference phase where the cycle slip occurs based on the cycle slip starting position and the cycle slip ending position.
  • the complete process of the cycle slip can be located, detection continues in the order of valid signals, and the first valid signal that meets the preset conditions after the starting point of the cycle slip CS star is recorded.
  • step 2053 may be implemented by: determining the center point position between the cycle slip starting position and the cycle slip ending position. Determine a third phase difference between the reference phase corresponding to the center point position and the reference phase of the training symbol block.
  • the reference phase corresponding to the cycle slip starting position to the cycle slip end position will be reduced by ⁇ ; if the third phase difference value is less than 0, the reference phase will be reduced from the cycle slip starting position to the cycle slip end position.
  • the corresponding reference phase is increased by ⁇ ; where ⁇ is the cycle slip angle corresponding to the modulation mode of the received signal.
  • the detected cycle slip is compensated.
  • ⁇ is the cycle slip angle corresponding to the modulation method of the received signal.
  • the constellation diagram of the transmitted signal for the signal receiving end, the received signal
  • This constellation The figure rotates at a certain angle ⁇ about the origin, and the size of ⁇ is the cycle slip angle.
  • the value of ⁇ is obtained by rotating the constellation diagram of the signal about the origin to the minimum angle when it coincides with itself, for example
  • the cycle slip angle ⁇ is
  • the cycle slip angle is The cycle slip angle may be different depending on different modulation methods.
  • the signal processing method may be a method of recovering the carrier in the received signal, that is, a carrier recovery method.
  • a carrier recovery method The flow chart of the carrier recovery method can be seen in Figure 10, including:
  • Step 401 Extract M*N training symbols within M training symbol blocks in the received signal, and remove the signal modulation phase.
  • Step 402 Yes
  • the training symbols at different intervals in each training symbol block are subjected to phase difference operations to obtain several complex sample values corresponding to different intervals.
  • Step 403 Perform averaging operations on several complex sample values corresponding to different intervals to obtain multiple complex mean values corresponding to different intervals of the smoothed ASE noise, take the arguments of the multiple complex mean values respectively, and calculate multiple frequency values respectively.
  • To estimate the initial value of the partial estimate determine the weight of the initial value of the frequency offset estimate corresponding to different intervals based on the proportion of the number of complex sample values corresponding to different intervals to the total number of complex sample values, and obtain the final value based on the weight of each initial value of the frequency offset estimate. Rough estimate of frequency offset.
  • Step 404 Determine the frequency offset estimation range based on the rough frequency offset estimate and the preset residual frequency difference value. According to the frequency offset estimation range, perform the fourth power CZT transform on the received signal to obtain the frequency offset fine estimate. The fine estimate performs frequency offset compensation on the effective signal and training symbols.
  • Step 405 Extract the training symbols in the received signal after frequency offset compensation, and remove the signal modulation phase.
  • Step 406 Perform an average operation on the training symbols in the current training symbol block, take the argument angle, and obtain the reference phase through deconvolution.
  • Step 407 Calculate and compare the deviation between the reference phase difference value of the current training symbol block and its adjacent training symbol blocks and the jump threshold value, and detect and compensate the jump of the reference phase of the current training symbol block based on the deviation.
  • Step 408 Calculate the difference between the reference phase of the current training symbol block and the reference phases of the K/2 valid signals before and after symbol by symbol, and compare it with the cycle slip detection threshold to determine whether a cycle slip occurs.
  • Step 409 Locate the location where the cycle slip occurs, and determine the cycle slip direction and cycle slip compensation value.
  • Step 410 Compensate for cycle slips occurring in the reference phase.
  • frequency offset estimation with less overhead (for example, 512 effective signals are inserted into 8 training symbols, the overhead is less than 1.6%), different symbol intervals are used for difference in each training symbol block, and multiple sets of different symbol intervals are obtained.
  • the phase difference values caused by frequency offset are averaged to improve the noise smoothing effect; multiple training symbol blocks are averaged to further improve the noise smoothing ability and ensure the stability of rough frequency offset estimation.
  • a highly reliable and high-precision frequency offset estimate residual frequency offset does not exceed 2 MHz
  • phase offset estimation calculate the difference between the reference phase of the current training symbol block and the reference phase of the adjacent training symbol blocks, and detect and compensate the reference phase of the current training symbol block by comparing the difference with the deviation of the jump threshold value.
  • Phase jump, and the reference phase obtained from the current training symbol block is only used as a reference for cycle slip detection of the adjacent half-length effective signal phases.
  • the absolute value of the difference is continuously compared with the preset cycle slip determination threshold in order to achieve efficient detection of effective signal cycle slips (multiple cycle slips within a training symbol block can also be detected stably).
  • frequency offset estimation and phase offset estimation reuse the same set of periodic training symbols.
  • Frequency offset estimation combined with second-order CZT can achieve high-precision frequency offset estimation, and the algorithm complexity is much smaller than the traditional fourth-power FFT with the same accuracy. algorithm (about 8%).
  • detecting and compensating phase offset estimation When counting cycle slips, not only can the jump of the reference phase be detected and corrected, but also reliable detection and correction can be achieved even if multiple cycle slips occur within half the length of the effective signal.
  • This embodiment has the advantages of strong practicability, high frequency offset estimation accuracy, strong cycle slip detection capability, simple implementation, and low signal processing requirements. It solves the serious cycle slip problem that will occur in traditional carrier phase offset estimation algorithms (VVPE, BPS, etc.) in FTN systems. It also solves the problems of performance, complexity and spectrum efficiency of traditional carrier recovery methods that are difficult to balance.
  • Figure 11 is a graph showing the relationship between residual frequency offset and frequency offset of FTN-PM-16QAM.
  • the training symbol length is 3500, among which the key parameters of the CZT algorithm are: the number of CZT points is 128, the number of data samples is 897, the CZT search range is [F1-100, F1+100]/MHz, and the search accuracy is 1.56MHz.
  • the method provided by the embodiment of the present application can stabilize the residual frequency offset within the frequency offset range of [-1.6, 1.6] GHz. At around 3M, this embodiment effectively improves the estimation accuracy.
  • the residual frequency offset of the method provided in this embodiment is smaller than the fourth power FFT frequency offset estimation algorithm, and The complexity is only 8% of the latter.
  • Figure 13 is a comparison curve of phase noise tracking performance between the embodiment of the present application and the QPSK segmentation algorithm.
  • a three-carrier 128GBaud PM-16QAM system is simulated under optical back-to-back conditions, the acceleration factor is 0.85, the laser linewidth is 100kHz, and the estimated block length of this QPSK segmentation algorithm is 128.
  • the QPSK segmentation algorithm is affected by severe ISI, and it is estimated that there is a serious cycle slip phenomenon in the phase noise curve, and the method provided by the embodiment of the present application can effectively detect and compensate Cycle slip phenomenon caused by severe ISI.
  • Figure 14 is a graph showing the relationship between laser linewidth and BER of FTN-PM-16QAM.
  • the three-carrier 128GBaud PM-16QAM system is simulated, the acceleration factor is 0.95/0.9/0.85, the laser linewidth is 100kHz, and the OSNR is 23-27dB.
  • the 1dB OSNR cost (compared to the OSNR corresponding to 0 line width) corresponding to ⁇ v*Ts (the product of line width and symbol period) as the line width indicator, and conduct a simulation analysis of the algorithm's line width tolerance. The results are shown in Figure 14.
  • the acceleration factor decreases, inter-symbol crosstalk becomes more severe and the system is more susceptible to phase noise, so the line width tolerance decreases.
  • the maximum line widths that 1dB OSNR can tolerate in the 128GBaud system are 2.2MHz, 3.2MHz, and 4.5MHz.
  • the embodiments of the present application can effectively detect and compensate for cycle slips under acceleration factors such as 0.85, and have excellent line width tolerance.
  • the embodiment of the present application also provides an electronic device, as shown in Figure 15, including at least one processor 501; and a memory 502 communicatively connected to the at least one processor 501; wherein the memory 502 stores information that can be processed by at least one
  • the instructions executed by the processor 501 are executed by at least one processor 501, so that the at least one processor 501 can execute the signal processing method in the above embodiment.
  • the memory 502 and the processor 501 are connected using a bus.
  • the bus may include any number of interconnected buses and bridges.
  • the bus connects various circuits of one or more processors 501 and the memory 502 together.
  • the bus can also connect various other circuits together such as peripherals, voltage regulators, and power management circuits, which are all well known in the art and therefore will not be described in detail herein.
  • the bus interface provides the interface between the bus and the transceiver.
  • the transceiver can be one component or multiple components, such as multiple interfaces.
  • Receivers and transmitters provide units for communicating with various other devices over a transmission medium.
  • the data processed by the processor 501 is transmitted on the wireless medium through the antenna, and the antenna also receives the data and transmits the data to the processor 501.
  • Processor 501 is responsible for managing the bus and general processing, and may also provide a variety of functions, including timing, peripheral interfaces, voltage regulation, power management, and other control functions.
  • the memory 502 may be used to store data used by the processor 501 when performing operations.
  • Embodiments of the present application also provide a computer-readable storage medium storing a computer program.
  • the above method embodiments are implemented when the computer program is executed by the processor.
  • M*N training symbols within the M training symbol blocks in the received signal are first extracted, and phase difference operations are performed on the training symbols spaced d apart within each training symbol block to obtain A set of complex sample values corresponding to an interval of d, and by adjusting the value of d, multiple sets of complex sample values corresponding to different interval values are obtained, which is beneficial to obtaining a set of complex sample values corresponding to different intervals for removing phase noise caused by line width.
  • Multiple sets of complex samples avoid the impact of phase noise introduced by line width on FTN system performance.
  • a rough frequency offset estimate is first performed to obtain a rough estimate of the frequency offset, and then the frequency offset is determined by combining the rough estimate of the frequency offset with the preset residual frequency difference value. Estimate range. Then, according to the frequency offset estimation range, a fine frequency offset estimation is performed to obtain a fine frequency offset estimation value, which is beneficial to improving the accuracy and reliability of the frequency offset estimation under the FTN system.
  • the program is stored in a storage medium and includes several instructions to cause a device ( It may be a microcontroller, a chip, etc.) or a processor (processor) that executes all or part of the steps of the methods described in various embodiments of this application.
  • the aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disk or optical disk and other media that can store program code. .

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Abstract

本申请实施例公开了一种信号处理方法、电子设备和计算机可读存储介质。信号处理方法包括：提取接收信号中M个训练符号块内的M*N个训练符号，并去除信号调制相位（101）；其中，所述接收信号为发送端在构造要发送的信号时，每间隔K个有效信号插入一个长度为N的训练符号块；对每个训练符号块内的间隔为d的训练符号进行相位差运算，得到间隔为d时对应的一组复数样值，并通过调整d的取值，以得到不同间隔取值时对应的多组复数样值（102）；根据多组复数样值，得到频偏粗略估计值（103）；根据所述频偏粗略估计值和预设的残余频差值，确定频偏估计范围（104）；根据所述频偏估计范围，得到频偏精细估计值（105）。

Description

信号处理方法、电子设备和计算机可读存储介质
相关申请的交叉引用
本申请基于申请号为202210360165.4，申请日为2022年04月06日的中国专利申请提出，并要求该中国专利申请的优先权，该中国专利申请的全部内容在此引入本申请作为参考。
技术领域
本申请实施例涉及通信技术领域，特别涉及一种信号处理方法、电子设备和计算机可读存储介质。
背景技术
近年来，随着光通信数字信号处理技术(Digital Signal Processing，DSP)的高速发展，单波200G/400G速率的波分复用(Wavelength Division Multiplexing，WDM)相干系统已被实际部署。由于光纤C+L波段可用频率几乎被完全利用，仅依靠增加复用波长数目或缩小信道间隔的传统WDM系统面临着系统容量难以进一步提升的物理瓶颈。超奈奎斯特(Faster-than-Nyquist，FTN)速率光传输技术，通过在时域压缩符号间隔或在频域压缩信道间隔，打破正交传输准则，形成信道间隔小于码元速率、传输速率超过奈奎斯特速率的更高频谱效率的复用信号，并借助DSP技术提供的运算能力进行传输损伤均衡与补偿，具有高效率、低成本、低功耗等特点，成为下一代大容量相干光传输技术极具潜力的发展方向。
然而，随着FTN系统速率和频谱效率升高，激光器频偏和线宽引入的相位噪声对系统性能的影响愈加凸显，这严重限制着系统性能。高速高阶FTN调制码型对相位噪声容忍性低，系统对频偏估计的稳定性和精度要求更高，且FTN强滤波引入的码间串扰(Inter Symbol Interference，ISI)也会进一步劣化传统频偏估计算法精度，使得在FTN系统下频偏估计的精度和可靠性不高。
发明内容
本申请实施例旨在提出一种信号处理方法、电子设备和计算机可读存储介质。
本申请实施例提供了一种信号处理方法，包括：提取接收信号中M个训练符号块内的M*N个训练符号，并去除信号调制相位；其中，所述接收信号为发送端在构造要发送的信号时，每间隔K个有效信号插入一个长度为N的训练符号块；对每个所述训练符号块内的间隔为d的训练符号进行相位差运算，得到间隔为d时对应的一组复数样值，并通过调整所述d的取值，以得到不同间隔取值时对应的多组复数样值；根据所述多组复数样值，得到频偏粗略估计值；根据所述频偏粗略估计值和预设的残余频差值，确定频偏估计范围；根据所述频偏估计范围，得到频偏精细估计值。
本申请实施例还提供了一种电子设备，包括：至少一个处理器；以及，与所述至少一个处理器通信连接的存储器；其中，所述存储器存储有可被所述至少一个处理器执行的指令，所述指令被所述至少一个处理器执行，以使所述至少一个处理器能够执行上述的信号处理方法。
本申请实施例还提供了一种计算机可读存储介质，存储有计算机程序，所述计算机程序被处理器执行时实现上述的信号处理方法。
附图说明
图1是本申请实施例中提到的信号处理方法的流程图；
图2是本申请实施例中提到的接收信号的帧结构的示意图；
图3是本申请实施例中提到的步骤103的一种实现方式的流程图；
图4是本申请实施例中提到的步骤105的一种实现方式的流程图；
图5是本申请实施例中提到的有效信号的参考相位的周跳检测流程；
图6是本申请实施例中提到的步骤202的一种实现方式的流程图；
图7是本申请实施例中提到的确定训练符号块的参考相位中是否发生跳变的一种实现方式的流程图；
图8是本申请实施例中提到的步骤204中周跳检测的一种实现方式的流程图；
图9是本申请实施例中提到的对发生周跳的参考相位进行补偿的一种实现方式的流程图；
图10是本申请实施例中提到的载波恢复方法的流程图；
图11是本申请实施例中提到的FTN-PM-16QAM的残余频偏与频偏的关系曲线图；
图12是本申请实施例中提到的四次方FFT频偏估计算法在FTN-PM-16QAM下频偏大小与估计残余频偏关系曲线图；
图13是本申请实施例中提到的QPSK分割算法在FTN-PM-16QAM下估计相位噪声曲线图；
图14是本申请实施例中提到的FTN-PM-16QAM的激光器线宽与BER关系曲线图；
图15是本申请实施例中提到的电子设备的结构示意图。
具体实施方式
为使本申请实施例的目的、技术方案和优点更加清楚，下面将结合附图对本申请的各实施例进行详细的阐述。然而，本领域的普通技术人员可以理解，在本申请各实施例中，为了使读者更好地理解本申请而提出了许多技术细节。但是，即使没有这些技术细节和基于以下各实施例的种种变化和修改，也可以实现本申请所要求保护的技术方案。以下各个实施例的划分是为了描述方便，不应对本申请的实现方式构成任何限定，各个实施例在不矛盾的前提下可以相互结合相互引用。
本申请的实施例涉及一种信号处理方法，应用于电子设备，该电子设备可以为信号接收端，信号接收端接收发送端所发送的信号，并对接收的信号进行处理。本实施例中的信号处理方法的流程图可以参阅图1，包括：
步骤101：提取接收信号中M个训练符号块内的M*N个训练符号，并去除信号调制相位；其中，接收信号为发送端在构造要发送的信号时，每间隔K个有效信号插入一个长度为N的训练符号块。
步骤102：对每个训练符号块内的间隔为d的训练符号进行相位差运算，得到间隔为d时对应的一组复数样值，并通过调整d的取值，以得到不同间隔取值时对应的多组复数样值。
步骤103：根据多组复数样值，得到频偏粗略估计值。
步骤104：根据频偏粗略估计值和预设的残余频差值，确定频偏估计范围。
步骤105：根据频偏估计范围，得到频偏精细估计值。
本实施例中，信号接收端先提取接收信号中M个训练符号块内的M*N个训练符号，对每个训练符号块内的间隔为d的训练符号进行相位差运算，得到间隔为d时对应的一组复数样值，并通过调整d的取值，以得到不同间隔取值时对应的多组复数样值，有利于得到去除线宽所致相位噪声的不同间隔对应的多组复数样值，避免线宽引入的相位噪声对FTN系统性能的影响。然后，根据不同间隔取值时对应的多组复数样值，先进行粗略的频偏估计，得到频偏粗略估计值，再结合频偏粗略估计值和预设的残余频差值，确定频偏估计范围。接着，根据频偏估计范围，进行频偏精细估计，得到频偏精细估计值，有利于提高FTN系统下频偏估计的精度和可靠性。
下面对本实施例的信号处理方法的实现细节进行说明，以下内容仅为方便理解提供的实现细节，并非实施本方案的必须。
在步骤101中，发送端在构造要发送的信号时，每间隔K个有效信号插入一个长度为N的训练符号块，即发送端在进行数据帧构造时，每间隔K个有效信号插入一个长度为N的训练符号块。从而，接收端在接收到发送端发送的信号时，可以提取接收信号中的M个训练符号块内的共M*N个训练符号。其中，M、N、K均为大于1的整数，且K大于N。
在一些实施例中，接收信号的帧结构的示意图可以参阅图2，图2中的训练序列即为一个长度为N的训练符号块，图2中的有效数据即为K个有效信号。
在一些实施例中，K远大于N，发送端在进行数据帧构造时，可以每间隔512个有效信号插入一个长度为8的训练符号块，即每间隔512个有效信号插入8个训练符号。然而，在实际实现中，并不以此为限。
在一些实施例中，去除信号调制相位也可以理解为：去除训练符号的原始相位。在一示例中，去除信号调制相位的方式可以为：将提取的训练符号与原始训练符号的复共轭相乘，以得到去除信号调制相位的训练符号。
比如，第l个训练符号块中的第k个训练符号TSp(k,l)的表达式如公式(1)所示：
TSp(l.k)＝A*exp(jθs)         (1)
其中，A代表训练符号的幅度，θs代表训练符号的相位，1≤l≤M。公式(1)可以理解为原始训练符号的表达式。
假设，M＝100，N＝8，则接收端首先提取接收信号中100个训练符号块内的800个训练符号RP进行频偏估计，第l个训练符号块中的第k个训练符号RP(l,k)的表达式如公式(2)所示：
Rp(l,k)＝A*exp{j(θs+2πΔfkT+θL(k))}+n(k)        (2)
其中，Δf为本振激光器和发送端激光器产生的频偏，2πΔfkT为载波频偏对第k个训练符号造成的相位误差分量，T为符号周期，θL表示激光器线宽引入的相位误差，n代表放大器自发辐射噪声(Amplifier Spontaneous Emission Noise，ASE噪声)。ASE噪声即ASE所致的相位噪声，符合高斯分布，均值为零。公式(2)可以理解为接收端接收的训练符号的表达式。
通过将接收端接收的训练符号与原始训练符号的复共轭相乘可以去除信号调制相位，得到去除信号调制相位的训练符号。去除信号调制相位的训练符号的表达式如公式(3)所示：
由于n(k)符合均值为零的高斯分布，则公式(3)可以用如下公式(4)表示：
Sp(l,k)≈A2exp{j(2πΔfkT+θL(k)+θn(k))}        (4)
θn为ASE噪声，符合高斯分布，均值为零。
在步骤102中，接收端对每个训练符号块内的间隔为d的训练符号进行相位差运算，得到间隔为d时对应的一组复数样值，并通过调整d的取值，以得到不同间隔取值时对应的多组复数样值。其中，不同间隔可以根据实际需要设置，比如可以包括每个训练符号块内的所有可能的训练符号间隔。比如，当一个训练符号块内包括8个训练符号时，不同间隔可以包括7种间隔，分别为：d＝1、2……7，这分别表明间隔了0个训练符号、间隔了1个训练符号……和间隔了6个训练符号。当d＝1时，即间隔了0个训练符号时，可以对每个训练符号块内相邻的两个训练符号进行相位差运算，得到d＝1时对应的一组复数样值。其中，一组复数样值可以包括若干个复数样值。当d＝2，即间隔了1个训练符号时，可以对每个训练符号块内间隔了1个训练符号的两个训练符号进行相位差运算，得到d＝2时对应的一组复数样值。通过调整d的取值，可以依次得到不同间隔取值时对应的多组复数样值，每种间隔d对应一组复数样值。
由于在高速光传输系统中，激光器线宽引入的相位噪声相对于信号的符号速率来说是慢变的，其对前后若干个相邻符号的相位影响可以视为相同，因此，可以通过对每个训练符号块内不同间隔的训练符号的相位差运算，来去除θL产生的影响，得到多个已去除线宽所致相位噪声的复数样值。比如，可以采用如下公式(5)，得到间隔为d时对应的一组复数样值：
其中，Sp(l，k)为第l个训练符号块中的第k个训练符号的表达式，为第l个训练符号块中的第k+d个训练符号的复共轭的表达式，Δf为本振激光器和发端激光器产生的频偏，2πΔfkT为载波频偏对第k个训练符号造成的相位误差分量，T为符号周期，θL表示激光器线宽引入的相位误差，θn为ASE所致的相位噪声，θn’表示间隔为d的两个训练符号ASE所致相位噪声之差。d＝1时对应一组复数样值，d＝2时对应一组复数样值，d＝N-1时对应一组复数样值，最终得到N-1组复数样值。
当d＝1时，通过上述公式5，可以对间隔了0个训练符号，即对各相邻训练符号进行相位差运算。当d＝2时，通过上述公式5，可以对各间隔了1个训练符号的任意2个训练符号进行相位差运算。以此类推，可以对每个训练符号块内的不同间隔的训练符号进行相位差运算，得到不同间隔对应的多组复数样值。其中，每一种间隔可以对应一组复数样值，每组复数样值包括若干个复数样值。
在步骤103中，接收端根据多组复数样值，进行粗略的频偏估计，得到频偏粗略估计值。
在一些实施例中，步骤103的实现方式可以参阅图3，包括：
步骤1031：对每组复数样值中的若干个复数均值进行平均运算，得不同间隔取值分别对应的第一复数均值。
步骤1032：对不同间隔取值分别对应的第一复数均值分别取幅角，计算得到不同间隔取值分别对应的频偏估计初值。
步骤1033：根据不同间隔取值分别对应的频偏估计初值，得到频偏粗略估计值。
本实施例中，通过对每组复数样值中的若干个复数均值进行平均运算，有利于得到多个已平滑ASE噪声的不同间隔取值对应的复数均值，结合该已平滑ASE噪声的复数均值有利于提高频偏粗略估计的准确性。
由于ASE噪声服从均值为零的特性，同时在高速光传输系统中，激光器之间频偏变化相对于符号速率来说同样存在慢变特性，且频偏变化通常比线宽引入的相位变化更为缓慢，因此，可以对所述每组复数均值中的若干个复数样值进行平均运算，得到一个已平滑ASE噪声的复数均值，通过对M个训练符号块内的训练符号进行平均运算，来平滑ASE噪声对频偏估值的影响。
在步骤1031中，对每组复数样值中的若干个复数均值进行平均运算，得到第一复数均值avg可以通过如下公式(6)实现：
其中，Δf为载波频偏估计值。当d＝1时，根据上述公式(6)可以计算得到间隔d为1时对应的一组复数样值中的若干个复数样值的平均值，以作为间隔取值d＝1对应的第一复数均值，当d＝2时，根据上述公式(6)可以计算得到间隔d为2时对应的一组复数样值中的若干个复数样值的平均值，以作为间隔取值d＝2对应的第一复数均值。以此类推，可以得到所有间隔取值下对应的第一复数均值。
假设，M＝100，N＝8，则上述公式(6)可以表示如下：
在步骤1032中，接收端对不同间隔取值对应的第一复数均值分别取幅角，计算得到不同间隔分别对应的频偏估计初值，每个间隔对应一个频偏估计初值。通过对第一复数均值avg取幅角，就可以得到由于载波频偏引入的相位误差分量，再经过计算得到频偏粗略估计值F1。其中，频偏粗略估计值F1也可以理解为一阶频偏估计结果。
在一些实施例中，步骤1033的实现方式可以为：根据每组复数样值中的复数样值个数占多组复数样值中的复数样值总数的比重，确定不同间隔取值分别对应的频偏估计初值权重；根据不同间隔取值分别对应的频偏估计初值权重和不同间隔取值分别对应的频偏估计初值，得到频偏粗略估计值，有利于提高频偏粗略估计的准确性和稳定性。其中，可以将每组复数样值中的复数样值个数占多组复数样值中的复数样值总数的比重作为该组复数样值对应的间隔d的频偏估计初值权重。基于一个包括N个训练符号的训练符号块得到的复数样值总数为N(N-1)/2。
比如，当N＝8时，间隔d的取值可以为1,2,3,4,5,6,7，间隔d＝1时对应的一组复数样值中的复数样值个数为7。间隔d＝2时对应的一组复数样值中的复数样值个数为6。间隔d＝3时对应的一组复数样值中的复数样值个数为5。间隔d＝4时对应的一组复数样值中的复数样值个数为4。间隔d＝5时对应的一组复数样值中的复数样值个数为3。间隔d＝6时对应的一组复数样值中的复数样值个数为2。间隔d＝7时对应的一组复数样值中的复数样值个数为1。复数样值总数为7+6+5+4+3+2+1＝8×(8-1)/2＝28。基于此，可以得到d＝1时，对应的频偏估计初值权重为7/28，d＝2时，对应的频偏估计初值权重为6/28，依次类推可以得到各个间隔对应的频偏估计初值权重。最终，根据各个间隔对应的频偏估计初值权重，对各个间隔对应的频偏估计初值进行加权计算，得到加权计算后的结果，该加权计算后的结果即为频偏粗略估计值。
在一些实施例中，不同间隔对应的频偏估计初值权重也可以预先设置好，比如，不同间隔对应的频偏估计初值权重也可以相同，然而本实施例对此不做限定。
在步骤104中，接收端根据频偏粗略估计值和预设的残余频差值，确定频偏估计范围。其中，残余频差值为FTN系统最大可能的残余频偏值fm。频偏估计范围可以表示为：[F1-fm，F1+fm]MHz，比如，fm＝100MHz，则频偏估计范围的起始频率点为(F1-100)MHz，结束频率点为(F1+100)MHz。
在步骤105中，接收端根据频偏估计范围，进行频偏精细估计，得到频偏精细估计值。本实施例中可以采用CZT变换进行频偏精细估计，得到频偏精细估计值。在一示例中，可以根据频偏粗略估计值，即一阶频偏估计结果，辅助完成二阶线性调频Z变换CZT处理，实现高精度的频偏估计。
在一些实施例中，步骤105的实现方式可以参阅图4，包括：
步骤1051：确定频偏估计范围的起始频率点和结束频率点。
步骤1052：根据起始频率点、结束频率点和预设的频率分辨率，确定线性调频z变换CZT输出序列点数。
步骤1053：根据CZT输出序列点数，对接收信号进行CZT，得到频偏精细估计值。
本实施例中，确定频偏估计范围的起始频率点和结束频率点，然后结合CZT频偏估计精度，即频率分辨率，有利于为系统最终实现的高精度的频偏估计，得到准确的频偏精细估计值。
在步骤1051中，起始频率点即为频偏估计范围的下限值，结束频率点为频偏估计范围的上限值。
在步骤1052中，频率分辨率也可以理解为CZT频偏估计精度，频率分辨率可以根据实际需要进行设置，比如可以为1.56MHz，然而本实施例对频率分辨率的大小不做限定。接收端根据起始频率点、结束频率点和预设的频率分辨率，确定CZT输出序列点数。
在步骤1053中，接收端根据CZT输出序列点数，对接收信号进行CZT，得到频偏精细估计值。假设CZT输出序列点数为128，则接收端可以对t次方后的接收信号进行128点CZT变换，得到频偏精细估计 值F2。其中，t可以根据实际需要选择，本实施例中t可以取4，即接收端可以对4次方后的接收信号进行128点CZT变换，得到频偏精细估计值F2。
在一些实施例中，在步骤105之后，还可以包括有效信号的参考相位的周跳检测流程，参阅图5，该周跳检测流程包括：
步骤201：根据频偏精细估计值，对训练符号块和有效信号进行频偏补偿，得到频偏补偿后的训练符号块和频偏补偿后的有效信号。
步骤202：根据频偏补偿后的训练符号块，确定训练符号块的参考相位。
步骤203：根据频偏补偿后的有效信号，确定有效信号的参考相位。
步骤204：根据训练符号块的参考相位和有效信号的参考相位，进行有效信号的参考相位的周跳检测。
步骤205：在确定有效信号的参考相位发生周跳时，对发生周跳的参考相位进行补偿。
本实施例中，基于频偏补偿后的训练符号块和有效信号，有利于准确得到训练符号块和有效信号的参考相位。频偏估计和相偏估计可以复用同一组周期性训练符号，有利于降低算法复杂度，实现有效信号周跳的高效检测。
在步骤201中，接收端可以根据频偏精细估计值对接收信号进行频偏补偿，即对接收信号中的各个训练符号和各个有效信号进行频偏补偿。
在步骤202中，接收端根据频偏补偿后的训练符号块，确定从接收信号中提取的M个训练符号块的参考相位。
在一些实施例中，步骤202的实现方式可以参阅图6，包括：
步骤2021：去除频偏补偿后的训练符号块内的训练符号的信号调制相位，得到去除信号调制相位的训练符号块。
步骤2022：对去除信号调制相位的训练符号块内的训练符号进行平均运算，得到第二复数均值。
步骤2023：根据第二复数均值，得到训练符号块的参考相位。
本实施例中，通过对去除信号调制相位的训练符号块内的训练符号进行平均运算，有利于得到已平滑ASE噪声的第二复数均值，结合第二复数均值可以准确得到训练符号块的参考相位。
在步骤2021中，可以通过对训练符号经频偏补偿后与原始训练符号进行相位差运算以去除信号调制相位。然而，本实施例中对去除信号调制相位的方式不做限定，在实际实现中也可以采用除相位差运算以外的方式进行信号调制相位的去除。
在一些实施例中，对训练符号经频偏补偿后与原始训练符号进行相位差运算以去除信号调制相位，可以通过将经频偏补偿后的训练符号与原始训练符号的复共轭相乘实现。比如，频偏补偿后的训练符号记为R′p，频偏补偿后的第l个训练符号块中的第k个训练符号的表达式如公式(7)所示：
R'p(k,l)＝exp{j(θs(k)+θL(k)+θn(k))}           (7)
其中，θs(k)为第k个训练符号的调制相位，θL表示激光器线宽引入的相位误差，θn表示ASE噪声。可以通过与原始训练符号TSp(k,l)的复共轭相乘可以精确的去除信号调制相位。可以通过如下公式(8)去除信号调制相位，得到去除信号调制相位的训练符号块：
在步骤2022中，接收端对去除信号调制相位的训练符号块内的训练符号进行平均运算，得到第二复数均值。
由于ASE噪声服从均值为零的特性，因此可以通过如下公式(9)对当前一个训练符号块内的N个训 练符号进行平均运算，得到已平滑ASE噪声的第二复数均值：
在一些实施例中，步骤2023的实现方式可以为：对第二复数均值取幅角，根据对第二复数均值取的幅角，得到未展开的参考相位，根据目标参考相位和预设的相位范围，对未展开的参考相位进行解卷绕操作，得到训练符号块的展开后的参考相位；其中，目标参考相位为与训练符号块相邻且位于所述训练符号块之前的训练符号块的展开后的参考相位。在一示例中，未展开的参考相位可以理解为：未进行过解卷绕操作的参考相位，展开后的参考相位可以理解为：进行过解卷绕操作的参考相位。预设的相位范围为：相位估计可以估计的相位范围，比如可以为2π。
本实施例中，考虑到相位估计只能估计一定范围内的载波相位，通过对未展开的参考相位进行解卷绕操作，以展开参考相位，有利于避免参考相位出现相位模糊问题。
在一些实施例中，根据目标参考相位和预设的相位范围，对未展开的参考相位进行解卷绕操作，得到训练符号块的展开后的参考相位，包括：
通过如下公式(10)得到第l个训练符号块的展开后的参考相位：
其中，为未展开的参考相位，为目标参考相位，即可以作为基准的已经展开的参考相位，也可以立即为第l个训练符号块之前的一个训练符号块的展开后的参考相位，即第l-1个训练符号块的展开后的参考相位。R为预设的相位范围，为当前的训练符号块的展开后的参考相位，round为向下取整函数。1≤l≤M。
在一些实施例中，在步骤202之后，还包括：依次将每个频偏补偿后的训练符号块，作为当前训练符号块，确定当前训练符号块的参考相位中是否发生跳变；在当前训练符号块的参考相位中发生跳变的情况下，对发生跳变的参考相位进行补偿，得到跳变补偿后的参考相位。对应的步骤204可以为：根据当前训练符号块的跳变补偿后的参考相位和有效信号的参考相位，进行有效信号的参考相位的周跳检测。
本实施例中，针对频偏补偿后的训练符号块，进行各个训练符号块的参考相位是否发生跳变的检测，并对参考相位中的跳变进行针对性的补偿，有利于提高后续周跳检测的准确性，从而提高相偏估计的可靠性。
在一些实施例中，频偏补偿后的训练符号块依次进入长度为L的滑动窗口，L为m个训练符号块的长度，m大于1；确定当前训练符号块的参考相位中是否发生跳变的实现方式可以参阅图7，包括：
步骤301：计算滑动窗口内的第一个训练符号块与最后一个训练符号块的参考相位的第一相位差值。
步骤302：在第一相位差值的绝对值小于预设的跳变门限值的情况下，确定当前训练符号块的参考相位中未发生跳变。
步骤303：在第一相位差值的绝对值大于预设的跳变门限值的情况下，确定当前训练符号块的参考相位中发生跳变。
其中，滑动窗口的长度可以根据实际需要设置，最小可以设置为2，即滑动窗口内可以容纳2个训练符号块。然而，在实现中，滑动窗口的长度也可以大于2，本实施例对此不做限定。当前训练符号块为所述滑动窗口中的最后一个训练符号块。
本实施例中，通过引入滑动窗口，使得频偏补偿后的训练符号块依次进入长度为L的滑动窗口，可以提高跳变检测的准确性。
在步骤301中，接收端可以实时计算当前的滑动窗口内第一个训练符号块与最后一个训练符号块的参考相位的第一相位差值。第一相位差值可以表示为：φ(l)-φ(l+L-1)，其中，φ(l)为滑动窗口内第一个训练符号块的参考相位，φ(l+L-1)为滑动窗口内最后一个训练符号块的参考相位。
当滑动窗口的长度L为2时，第一相位差值可以理解为当前训练符号块的参考相位和目标训练符号块的参考相位的相位差值；其中，目标训练符号块包括与当前的训练符号块相邻且位于当前训练符号块之前的训练符号块和\或与当前训练符号块相邻且位于当前的训练符号块之后的训练符号块。
在步骤302中，预设的跳变门限值可以根据实际需要进行设置，比如可以设置为π/4。
当第一相位差值的绝对值小于预设的跳变门限值即则确定训练符号块的参考相位中未发生跳变，滑动窗口向后滑动一个训练符号块的长度，继续进行跳变检测。
在步骤303中，假设预设的跳变门限值为π/4，当第一相位差值的绝对值大于预设的跳变门限值即则确定训练符号块的参考相位中发生跳变。
在步骤303中，在参考相位中发生跳变的情况下，可以根据第一相位差值对参考相位中的跳变进行补偿。
在一些实施例中，对发生跳变的参考相位进行补偿，包括：若第一相位差值小于0，则将发生跳变的参考相位减小得到补偿后的参考相位。若第一相位差值大于0，则将发生跳变的参考相位增加得到补偿后的参考相位；其中，为训练符号对应的跳变角度，比如可以为2π。
也就是说，若φ(l)-φ(l+L-1)＜0，则将φ(l+L)之后参考相位减小用φ(l+L-2)替换φ(l+L-1)，即φ(l+L-1)＝φ(l+L-2)；若φ(l)-φ(l+L-1)＞0，则将φ(l+L)之后参考相位增加用φ(l+L-2)替换φ(l+L-1)，即φ(l+L-1)＝φ(l+L-2)。
本实施例中，完成参考相位中跳变的检测和补偿，便于后续基于无跳变参考相位对有效信号进行参考相位的周跳检测。
在一些实施例中，步骤204中周跳检测的流程图可以参阅图8，包括：
步骤2041：依次将每个频偏补偿后的训练符号块，作为当前训练符号块，确定与当前训练符号块相邻的目标有效信号的参考相位；其中，目标有效信号包括：第一有效信号和/或第二有效信号，第一有效信号为位于当前训练符号块之前的K/2个有效信号，第二有效信号为位于当前训练符号块之后的K/2个有效信号。
步骤2042：根据目标有效信号的参考相位和当前训练符号块的参考相位的第二相位差值，确定目标有效信号的参考相位是否发生周跳。
本实施例中，当前训练符号块的参考相位作为其前后相邻一半长度的有效信号的参考相位的周跳检测的参考，通过计算参考相位与所属训练符号块前后相邻的一半长度的有效信号的参考相位的第二相位差值，以实现有效信号周跳的高效检测。
参考图2，一个周跳检测周期包括一个训练符号块和与该训练符号块前后相邻的K/2个有效信号。其中，与该训练符号块前后相邻的K/2个有效信号既可以理解为与训练符号块相邻的目标有效信号。本实施例中，将单个有效数据块分为前后两部分，即，将K个有效信号分为前K/2个有效信号和后K/2个有效信号。将当前训练符号块的参考相位φ(l)与其前后相邻的K/2个有效信号的参考相位θ(k)逐符号进行比较，计算参考相位φ(l)与所属训练符号块前后K/2个有效信号相位θ(k)的相位差值，基于该相位差值检测是否发生周跳。
在步骤2041中，可以采用正交相移键控(Quadrature Phase Shift Keying，QPSK)分割算法进行对 有效信号进行相位估计，得到目标有效信号的参考相位。
在一些实施例中，考虑到相位估计只能估计一定范围内的载波相位，为了避免参考相位出现相位模糊问题，可以进行解卷绕操作，展开目标有效信号的参考相位，比如可以通过如下公式11展开参考相位：
其中，是未展开的参考相位，是可以作为基准的已经展开的参考相位，R代表相位估计可以估计的相位范围，此时R为round为向下取整函数。基于此得到相位展开后的有效信号的参考相位θ(k)，进行后续的周跳检测和补偿。
在步骤2042中，若第二相位差值的绝对值小于预设的周跳检测门限，确定目标有效信号的参考相位未发生周跳；若第二相位差值的绝对值大于预设的周跳检测门限，确定目标有效信号的参考相位发生周跳。其中，预设的周跳检测门限可以根据接收信号的调制方式来确定，不同的调制方式对应的周跳门限可能不同，以QPSK、16QAM为例，周跳门限值可采用π/4，然而，本实施例对周跳检测门限的大小不做限定。
在一些实施例中，预设的周跳检测门限为π/4。在检测过程中，如果第二相位差值的绝对值小于周跳检测门限，即则确定目标有效信号的参考相位未发生周跳，继续按有效信号数据进行检测。如果第二相位差值的绝对值超过周跳检测门限，即则确定目标有效信号的参考相位发生周跳，并定位当前目标有效信号θ′(k)位置为该次周跳起点CSstar＝k'。
在一些实施例中，步骤205中，对发生周跳的参考相位进行补偿的方式，可以参阅图9，包括：
步骤2051：将目标有效信号所处的位置作为周跳起点位置。
步骤2052：根据周跳起点位置，确定周跳终止位置；其中，周跳终止位置为周跳起点位置之后的第一个满足预设条件的有效信号的前一个有效信号的位置，满足预设条件的有效信号的参考相位与训练符号块的参考相位的差值的绝对值小于周跳检测门限。
步骤2053：根据周跳起点位置和周跳终止位置，对发生周跳的参考相位进行补偿。
在本实施例中，当检测到周跳发生时，可以定位该次周跳的完整过程，继续按有效信号顺序进行检测，记录周跳起点位置CSstar后第一个满足预设条件的有效信号的位置，该满足预设条件的有效信号的参考相位与位于该满足预设条件的有效信号之前的训练符号块的参考相位的相位差值的绝对值小于周跳检测门限，即定位该位置前一位即位于该位置之前的一个有效信号的位置为该次周跳终点位置CSend＝k”-1。
在一些实施例中，步骤2053的实现方式可以为：确定周跳起点位置和周跳终止位置之间的中心点位置。确定中心点位置对应的参考相位与训练符号块的参考相位的第三相位差值。
若第三相位差值大于0，则将从周跳起点位置到周跳终点位置对应的参考相位减小α；若第三相位差值小于0，则将从周跳起点位置到周跳终点位置对应的参考相位增加α；其中，α为接收信号的调制方式对应的周跳角度。本实施例中的周跳补偿方式，有利于提高周跳补偿的准确性和合理性。
本实施例在检测到周跳发生后，对检测到的周跳进行补偿。本实施例中以所检测到周跳的中心点位置CSmid为基准，确定周跳方向和周跳补偿值，其中，CSmid＝(CSstar+CSend)/2。
若θ(CSmid)-φ(l)＞0，则将从周跳起点CSstar到周跳终点CSend的位置对应的相位减小α；
若θ(CSmid)-φ(l)＜0，则将从周跳起点CSstar到周跳终点CSend的位置对应的相位增加α。
上述周跳补偿过程中α为接收信号调制方式对应的周跳角度，对于每一种调制方式而言，其发送信号(对于信号接收端而言为接收信号)的星座图是固定的，该星座图关于原点呈某一角度α旋转不变，这个α的大小即周跳角度。换言之。将信号的星座图关于原点旋转成与自身重合时的最小角度即得到α的值，例如 对于信号采用QPSK或16QAM的调制方式的情形，周跳角度α为而对于发送信号采用8PSK的调制方式的情形，周跳角度为周跳角度根据不同的调制方式可能不同。
在一些实施例中，信号处理方法可以为对接收信号中的载波进行恢复的方法，即载波恢复方法。该载波恢复方法的流程图可以参阅图10，包括：
步骤401：提取接收信号中M个训练符号块内的M*N训练符号，并去除信号调制相位。步骤402：对
每个训练符号块内的不同间隔的训练符号进行相位差运算，得到不同间隔对应的若干个复数样值。
步骤403：对不同间隔对应的若干个复数样值分别进行平均运算，得到多个已平滑ASE噪声的不同间隔对应的复数均值，并对多个复数均值分别取幅角，分别计算得到多个频偏估计初值，根据不同间隔对应的复数样值的个数占复数样值总数的比重，确定不同间隔对应的频偏估计初值的权重，基于各频偏估计初值的权重求得最终的频偏粗略估计值。
步骤404：根据频偏粗略估计值和预设的残余频差值，确定频偏估计范围，根据频偏估计范围，对接收信号经过四次方CZT变换得到频偏精细估计值，并根据频偏精细估计值对有效信号和训练符号进行频偏补偿。
步骤405：提取频偏补偿后接收信号中的训练符号，并去除信号调制相位。
步骤406：对当前训练符号块内的训练符号进行平均运算，取幅角，经过解卷绕获得参考相位。
步骤407：计算并比较当前训练符号块及与其前后相邻的训练符号块的参考相位差值与跳变门限值的偏差，基于该偏差检测和补偿当前训练符号块的参考相位的跳变。
步骤408：逐符号计算当前训练符号块的参考相位与前后K/2个有效信号的参考相位的差值，并与周跳检测门限比较，判断是否发生周跳。
步骤409：定位周跳发生位置，确定周跳方向和周跳补偿值。
步骤410：补偿参考相位中发生的周跳。
本实施例中，不仅能以较少的训练开销实现高可靠的频偏估计，还能有效检测/抑制周跳。仅使用同一组训练符号的前提下，结合二阶CZT能够实现高精度频偏估计，且算法复杂度远小于同等精度的传统四次方FFT算法。同时，在检测和补偿相偏估计周跳时，即使在单个检测周期内发生多次周跳，仍然能够实现周跳的可靠检测，具有很强的实际应用价值。下面对本实施例在频偏估计方面和相偏估计方面的优势进行说明。
在频偏估计方面：以较少开销(如512个有效信号插8个训练符号，开销低于1.6％)，对每个训练符号块内取不同符号间隔作差，得到多组不同符号间隔的频偏所致相位差值并取平均，提升平滑噪声效果；取多个训练符号块作平均运算，再次提高平滑噪声能力，保证粗略频偏估计的稳定性。在一实施例中，基于第一级频偏粗略估计值和正负100MHz范围，作为第二级频偏精细估计范围，最终实现高可靠、高精度(残余频偏不超过2MHz)的频偏估计结果。
在相偏估计方面：对当前训练符号块的参考相位和前后相邻训练符号块的参考相位计算差值，通过比较差值和跳变门限值的偏差，检测和补偿当前训练符号块的参考相位的跳变，且当前训练符号块所得参考相位只作为前后相邻一半长度有效信号相位的周跳检测的参考，通过计算参考相位与所属训练符号块前后相邻的一半长度有效信号相位估计值的差值绝对值与预设周跳判定门限依次连续比较，以实现有效信号周跳的高效检测(一个训练符号块内多次周跳也能稳定检测)。
本实施例中，频偏估计和相偏估计复用同一组周期性训练符号，频偏估计结合二阶CZT能够实现高精度频偏估计，且算法复杂度远小于同等精度的传统四次方FFT算法(约8％)。同时，在检测和补偿相偏估 计周跳时，不仅能检测和纠正参考相位的跳变，且在有效信号一半长度内发生多次周跳仍然能够实现可靠检测和纠正。本实施例具有实用性强、频偏估计精度高、周跳检测能力强、实现简单、信号处理要求低等优点。解决了FTN系统中传统载波相偏估计算法(VVPE、BPS等)将发生严重的周跳问题，还解决了传统的载波恢复方法的性能、复杂度以及频谱效率等难以兼顾的问题。
图11为FTN-PM-16QAM的残余频偏与频偏的关系曲线图。在光背靠背条件下，仿真三载波128GBaud FTN-16QAM系统，加速因子1/0.9/0.85，OSNR＝24dB，激光器线宽100KHz，训练符号插入格式为8/512，开销为1.56％，粗估计所需的训练符号长度为3500，其中CZT算法关键参数：CZT点数为128，数据样值数为897，CZT搜索范围为[F1-100,F1+100]/MHz，搜索精度为1.56MHz。如图11所示，在奈奎斯特系统和加速因子为0.9、0.85的FTN系统中，本申请实施例提供的方法在[-1.6,1.6]GHz频偏范围内，残余频偏都能稳定在3M左右，本实施例有效的提高了估计精度。
图12为本申请实施例与四次方FFT频偏估计算法估偏性能对比曲线。在光背靠背条件下仿真三载波128GBaud FTN-16QAM系统，加速因子0.9，OSNR＝24dB，激光器线宽100KHz，训练符号插入格式为8/512，开销为1.56％，粗估计所需的训练符号长度为3500，其中CZT算法关键参数：CZT点数为128，数据样值数为897，CZT搜索范围为[F1-100,F1+100]/MHz，搜索精度为1.56MHz；四次方FFT频偏估计算法点数为16384，估计精度为1.9MHz。如图12所示，在加速因子为0.9的FTN系统中，在[-1.6,1.6]GHz频偏范围内，本实施例提供的方法残余频偏要小于四次方FFT频偏估计算法，且复杂度仅为后者的8％。
图13为本申请实施例与QPSK分割算法的相位噪声追踪性能对比曲线。在光背靠背条件下仿真三载波128GBaud PM-16QAM系统，加速因子0.85，激光器线宽为100kHz，本QPSK分割算法估计块长为128。如图13所示，在加速因子为0.85的FTN系统中，QPSK分割算法受到严重ISI的影响，估计相位噪声曲线中存在严重的周跳现象，而本申请实施例提供的方法能够有效检测和补偿严重ISI导致的周跳现象。
图14为FTN-PM-16QAM的激光器线宽与BER关系曲线图。在光背靠背条件下，仿真三载波128GBaud PM-16QAM系统，加速因子0.95/0.9/0.85，激光器线宽为100kHz，OSNR取23-27dB的仿真条件下进行仿真。定义1dB OSNR代价(与0线宽对应的OSNR相比)对应Δv*Ts(线宽与符号周期乘积)为线宽指标，进行算法线宽容忍度的仿真分析，结果如图14所示。随着加速因子的降低，码间串扰更严重，系统更容易受相位噪声的影响，因此线宽容忍度降低。加速因子为0.85、0.9、0.95时，其在128GBaud系统下1dB OSNR能容忍的最大线宽为2.2MHz、3.2MHz和4.5MHz。本申请实施例在0.85等加速因子下都能有效检测和补偿周跳，并具有优秀的线宽容忍度。
需要说明的是，本申请实施例中的上述各示例均为为方便理解进行的举例说明，并不对本申请的技术方案构成限定。
上面各种方法的步骤划分，只是为了描述清楚，实现时可以合并为一个步骤或者对某些步骤进行拆分，分解为多个步骤，只要包括相同的逻辑关系，都在本专利的保护范围内；对算法中或者流程中添加无关紧要的修改或者引入无关紧要的设计，但不改变其算法和流程的核心设计都在该专利的保护范围内。
本申请实施例还提供了一种电子设备，如图15所示，包括至少一个处理器501；以及，与至少一个处理器501通信连接的存储器502；其中，存储器502存储有可被至少一个处理器501执行的指令，指令被至少一个处理器501执行，以使至少一个处理器501能够执行上述实施例中的信号处理方法。
其中，存储器502和处理器501采用总线方式连接，总线可以包括任意数量的互联的总线和桥，总线将一个或多个处理器501和存储器502的各种电路连接在一起。总线还可以将诸如外围设备、稳压器和功率管理电路等之类的各种其他电路连接在一起，这些都是本领域所公知的，因此，本文不再对其进行详细描述。总线接口在总线和收发机之间提供接口。收发机可以是一个元件，也可以是多个元件，比如多个接 收器和发送器，提供用于在传输介质上与各种其他装置通信的单元。经处理器501处理的数据通过天线在无线介质上进行传输，并且，天线还接收数据并将数据传送给处理器501。
处理器501负责管理总线和通常的处理，还可以提供各种功能，包括定时、外围接口、电压调节、电源管理以及其他控制功能。而存储器502可以被用于存储处理器501在执行操作时所使用的数据。
本申请实施例还提供了一种计算机可读存储介质，存储有计算机程序。计算机程序被处理器执行时实现上述方法实施例。
本申请实施例提供的信号处理方法中，先提取接收信号中M个训练符号块内的M*N个训练符号，对每个训练符号块内的间隔为d的训练符号进行相位差运算，得到间隔为d时对应的一组复数样值，并通过调整d的取值，以得到不同间隔取值时对应的多组复数样值，有利于得到去除线宽所致相位噪声的不同间隔对应的多组复数样值，避免线宽引入的相位噪声对FTN系统性能的影响。然后，根据不同间隔取值时对应的多组复数样值，先进行粗略的频偏估计，得到频偏粗略估计值，再结合频偏粗略估计值和预设的残余频差值，确定频偏估计范围。接着，根据频偏估计范围，进行频偏精细估计，得到频偏精细估计值，有利于提高FTN系统下频偏估计的精度和可靠性。
即，本领域技术人员可以理解，实现上述实施例方法中的全部或部分步骤是可以通过程序来指令相关的硬件来完成，该程序存储在一个存储介质中，包括若干指令用以使得一个设备(可以是单片机，芯片等)或处理器(processor)执行本申请各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、磁碟或者光盘等各种可以存储程序代码的介质。
本领域的普通技术人员可以理解，上述各实施方式是实现本申请的不同实施例，而在实际应用中，可以在形式上和细节上对其作各种改变，而不偏离本申请的精神和范围。

Claims (18)

  1. 一种信号处理方法，包括：
    提取接收信号中M个训练符号块内的M*N个训练符号，并去除信号调制相位；其中，所述接收信号为发送端在构造要发送的信号时，每间隔K个有效信号插入一个长度为N的训练符号块，M、N、K均为大于1的整数，且K大于N；
    对每个所述训练符号块内的间隔为d的训练符号进行相位差运算，得到间隔为d时对应的一组复数样值，并通过调整所述d的取值，以得到不同间隔取值时对应的多组复数样值；
    根据所述多组复数样值，得到频偏粗略估计值；
    根据所述频偏粗略估计值和预设的残余频差值，确定频偏估计范围；
    根据所述频偏估计范围，得到频偏精细估计值。
  2. 根据权利要求1所述的信号处理方法，其中，所述根据所述频偏估计范围，得到频偏精细估计值，包括：
    确定所述频偏估计范围的起始频率点和结束频率点；
    根据所述起始频率点、所述结束频率点和预设的频率分辨率，确定线性调频z变换CZT输出序列点数；
    根据所述CZT输出序列点数，对所述接收信号进行CZT，得到频偏精细估计值。
  3. 根据权利要求1所述的信号处理方法，其中，所述根据所述多组复数样值，得到频偏粗略估计值，包括：
    对每组所述复数样值中的若干个复数均值进行平均运算，得到所述不同间隔取值分别对应的第一复数均值；
    对所述不同间隔取值分别对应的第一复数均值分别取幅角，计算得到所述不同间隔取值分别对应的频偏估计初值；
    根据所述不同间隔取值分别对应的频偏估计初值，得到频偏粗略估计值。
  4. 根据权利要求3所述的信号处理方法，其中，所述根据所述不同间隔取值分别对应的频偏估计初值，得到频偏粗略估计值，包括：
    根据每组所述复数样值中的复数样值个数占所述多组复数样值中的复数样值总数的比重，确定所述不同间隔取值分别对应的频偏估计初值权重；
    根据所述不同间隔取值分别对应的频偏估计初值权重和不同间隔取值分别对应的频偏估计初值，得到频偏粗略估计值。
  5. 根据权利要求1至4任一项所述的信号处理方法，其中，在所述得到频偏精细估计值之后，还包括：
    根据所述频偏精细估计值，对所述训练符号块和所述有效信号进行频偏补偿，得到频偏补偿后的训练符号块和频偏补偿后的有效信号；
    根据所述频偏补偿后的训练符号块，确定所述训练符号块的参考相位；
    根据所述频偏补偿后的有效信号，确定所述有效信号的参考相位；
    根据所述训练符号块的参考相位和所述有效信号的参考相位，进行所述有效信号的参考相位的周跳检测；
    在确定所述有效信号的参考相位发生周跳时，对发生周跳的参考相位进行补偿。
  6. 根据权利要求5所述的信号处理方法，其中，所述根据所述频偏补偿后的训练符号块，确定所述训练符号块的参考相位，包括：
    去除所述频偏补偿后的训练符号块内的训练符号的信号调制相位，得到去除信号调制相位的训练符号块；
    对所述去除信号调制相位的训练符号块内的训练符号进行平均运算，得到第二复数均值；
    根据所述第二复数均值，确定所述训练符号块的参考相位。
  7. 根据权利要求6所述的信号处理方法，其中，所述根据所述第二复数均值，得到所述训练符号块的参考相位，包括：
    对所述第二复数均值取幅角；
    根据对所述第二复数均值取的幅角，得到未展开的参考相位；
    根据目标参考相位和预设的相位范围，对所述未展开的参考相位进行解卷绕操作，得到所述训练符号块的展开后的参考相位；其中，所述目标参考相位为与所述训练符号块相邻且位于所述训练符号块之前的训练符号块的展开后的参考相位。
  8. 根据权利要求7所述的信号处理方法，其中，所述根据目标参考相位和预设的相位范围，对所述未展开的参考相位进行解卷绕操作，得到所述训练符号块的展开后的参考相位，包括：
    通过如下公式得到第l个训练符号块的展开后的参考相位：
    其中，为所述未展开的参考相位，为所述目标参考相位，R为所述预设的相位范围，为所述第l个训练符号块的展开后的参考相位，1≤l≤M。
  9. 根据权利要求5至8任一项所述的信号处理方法，其中，在所述根据所述频偏补偿后的训练符号块，确定所述训练符号块的参考相位之后，还包括：
    依次将每个所述频偏补偿后的训练符号块，作为当前训练符号块，确定所述当前训练符号块的参考相位中是否发生跳变；
    在所述当前训练符号块的参考相位中发生跳变的情况下，对发生跳变的参考相位进行补偿，得到跳变补偿后的参考相位；
    所述根据所述训练符号块的参考相位和所述有效信号的参考相位，进行所述有效信号的参考相位的周跳检测，包括：
    根据所述当前训练符号块的所述跳变补偿后的参考相位和所述有效信号的参考相位，进行所述有效信号的参考相位的周跳检测。
  10. 根据权利要求9所述的信号处理方法，其中，所述频偏补偿后的训练符号块依次进入长度为L的滑动窗口，所述L为m个训练符号块的长度，m大于1；
    所述确定所述当前训练符号块的参考相位中是否发生跳变，包括：
    计算所述滑动窗口内的第一个训练符号块与最后一个训练符号块的参考相位的第一相位差值；
    在所述第一相位差值的绝对值小于预设的跳变门限值的情况下，确定所述当前训练符号块的参考相位中未发生跳变；
    在所述第一相位差值的绝对值大于预设的跳变门限值的情况下，确定所述当前训练符号块的参考相位中发生跳变；
    其中，所述当前训练符号块为所述滑动窗口中的最后一个训练符号块。
  11. 根据权利要求10所述的信号处理方法，其中，所述对发生跳变的参考相位进行补偿，包括：
    若所述第一相位差值小于0，则将发生跳变的参考相位减小得到补偿后的参考相位；
    若所述第一相位差值大于0，则将发生跳变的参考相位增加得到补偿后的参考相位；
    其中，为所述训练符号对应的跳变角度。
  12. 根据权利要求5所述的信号处理方法，其中，所述根据所述训练符号块的参考相位和所述有效信号的参考相位，进行所述有效信号的参考相位的周跳检测，包括：
    依次将每个所述频偏补偿后的训练符号块，作为当前训练符号块，确定与所述当前训练符号块相邻的目标有效信号的参考相位；其中，所述目标有效信号包括：第一有效信号和/或第二有效信号，所述第一有效信号为位于所述当前训练符号块之前的K/2个有效信号，所述第二有效信号为位于所述当前训练符号块之后的K/2个有效信号；
    根据所述目标有效信号的参考相位和所述当前训练符号块的参考相位的第二相位差值，确定所述目标有效信号的参考相位是否发生周跳。
  13. 根据权利要求12所述的信号处理方法，其中，所述根据所述目标有效信号的参考相位和所述当前训练符号块的参考相位的第二相位差值，确定所述目标有效信号的参考相位是否发生周跳，包括：
    若所述第二相位差值的绝对值小于预设的周跳检测门限，确定所述目标有效信号的参考相位未发生周跳；
    若所述第二相位差值的绝对值大于预设的周跳检测门限，确定所述目标有效信号的参考相位发生周跳。
  14. 根据权利要求12或13所述的信号处理方法，其中，所述对发生周跳的参考相位进行补偿，包括：
    将所述目标有效信号所处的位置作为周跳起点位置；
    根据所述周跳起点位置，确定周跳终止位置；其中，所述周跳终止位置为所述周跳起点位置之后的第一个满足预设条件的有效信号的前一个有效信号的位置，所述满足预设条件的有效信号的参考相位与所述当前训练符号块的参考相位的差值的绝对值小于所述周跳检测门限；
    根据所述周跳起点位置和所述周跳终止位置，对发生周跳的参考相位进行补偿。
  15. 根据权利要求14所述的信号处理方法，其中，所述根据所述周跳起点位置和所述周跳终止位置，对发生周跳的参考相位进行补偿，包括：
    确定所述周跳起点位置和所述周跳终止位置之间的中心点位置；
    确定所述中心点位置对应的参考相位与所述当前训练符号块的参考相位的第三相位差值；
    若所述第三相位差值大于0，则将从所述周跳起点位置到所述周跳终点位置对应的参考相位减小α；
    若所述第三相位差值小于0，则将从所述周跳起点位置到所述周跳终点位置对应的参考相位增加α；
    其中，α为所述接收信号的调制方式对应的周跳角度。
  16. 根据权利要求1至4任一项所述的信号处理方法，其中，所述对每个所述训练符号块内的间隔为d的训练符号进行相位差运算，得到间隔为d时对应的一组复数样值，包括：
    通过如下公式，得到不同间隔对应的若干个复数样值：
    其中，Sp(l，k)为第l个训练符号块中的第k个训练符号的表达式，为第l个训练符号块中的第k+d个训练符号的复共轭的表达式，Δf为本振激光器和发端激光器产生的频偏，2πΔfkT为载波频偏对第k个训练符号造成的相位误差分量，T为符号周期，θL表示激光器线宽引入的相位误差，θn为ASE所致的相位噪声，θn’表示间隔为d的两个训练符号ASE所致相位噪声之差。
  17. 一种电子设备，包括：至少一个处理器；以及，
    与所述至少一个处理器通信连接的存储器；其中，
    所述存储器存储有可被所述至少一个处理器执行的指令，所述指令被所述至少一个处理器执行，以使所述至少一个处理器能够执行如权利要求1至16中任一所述的信号处理方法。
  18. 一种计算机可读存储介质，存储有计算机程序，其中，所述计算机程序被处理器执行时实现权利要求1至16中任一所述的信号处理方法。
PCT/CN2023/075277 2022-04-06 2023-02-09 信号处理方法、电子设备和计算机可读存储介质 WO2023193518A1 (zh)

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