CN116938655A

CN116938655A - Signal processing method, electronic device, and computer-readable storage medium

Info

Publication number: CN116938655A
Application number: CN202210360165.4A
Authority: CN
Inventors: 王永奔; 杨桃; 秦英凯; 陈雪; 王卫明
Original assignee: ZTE Corp; Beijing University of Posts and Telecommunications
Current assignee: ZTE Corp; Beijing University of Posts and Telecommunications
Priority date: 2022-04-06
Filing date: 2022-04-06
Publication date: 2023-10-24
Also published as: WO2023193518A1

Abstract

The embodiment of the application relates to the technical field of communication, and discloses a signal processing method, electronic equipment and a computer readable storage medium. The signal processing method comprises the following steps: extracting M times N training symbols in M training symbol blocks in a received signal, and removing signal modulation phases; the receiving signal is a training symbol block with the length of N, which is inserted into K effective signals at intervals when a transmitting end constructs a signal to be transmitted; performing phase difference operation on training symbols with the interval d in each training symbol block to obtain a group of complex sample values corresponding to the interval d, and adjusting the value of d to obtain a plurality of groups of complex sample values corresponding to different intervals; obtaining a rough frequency offset estimation value according to a plurality of groups of complex sample values; determining a frequency offset estimation range according to the frequency offset rough estimation value and a preset residual frequency difference value; according to the frequency offset estimation range, a frequency offset fine estimation value is obtained, and the accuracy and reliability of frequency offset estimation under the FTN system can be improved.

Description

Signal processing method, electronic device, and computer-readable storage medium

Technical Field

Embodiments of the present application relate to the field of communications technologies, and in particular, to a signal processing method, an electronic device, and a computer readable storage medium.

Background

In recent years, with the high-speed development of optical communication digital signal processing technology (Digital Signal Processing, DSP), a single-wave 200G/400G rate wavelength division multiplexing (Wavelength Division Multiplexing, WDM) coherent system has been practically deployed. Since the available frequencies of the c+l band of the optical fiber are almost fully utilized, conventional WDM systems relying only on increasing the number of multiplexing wavelengths or shrinking the channel spacing face physical bottlenecks that the system capacity is difficult to further increase. The ultra-Nyquist (FTN) rate optical transmission technology breaks through the orthogonal transmission criterion by compressing the symbol interval in the time domain or compressing the channel interval in the frequency domain, forms a multiplexing signal with higher spectral efficiency, the channel interval of which is smaller than the symbol rate and the transmission rate exceeds the Nyquist rate, and performs transmission damage equalization and compensation by means of the operation capability provided by the DSP technology, thereby having the characteristics of high efficiency, low cost, low power consumption and the like, and becoming the development direction of the next generation high-capacity coherent optical transmission technology with great potential.

However, as FTN system rates and spectral efficiency increase, the effect of phase noise introduced by laser frequency offset and linewidth on system performance becomes increasingly pronounced, severely limiting system performance. The high-speed high-order FTN modulation code pattern has low tolerance to phase noise, the system has higher requirements on stability and precision of frequency offset estimation, and intersymbol interference (Inter Symbol Interference, ISI) introduced by FTN strong filtering can further deteriorate the precision of the traditional frequency offset estimation algorithm, so that the precision and reliability of frequency offset estimation are not high under the FTN system.

Disclosure of Invention

The embodiment of the application mainly aims to provide a signal processing method, electronic equipment and a computer readable storage medium, so that the accuracy and reliability of frequency offset estimation under an FTN system can be improved.

To achieve at least the above object, an embodiment of the present application provides a signal processing method, including: extracting M times N training symbols in M training symbol blocks in a received signal, and removing signal modulation phases; the receiving signal is a training symbol block with the length of N, which is inserted into K effective signals at intervals when a transmitting end constructs a signal to be transmitted; performing phase difference operation on training symbols with an interval d in each training symbol block to obtain a group of complex sample values corresponding to the interval d, and adjusting the value of d to obtain a plurality of groups of complex sample values corresponding to different interval values; obtaining a rough frequency offset estimation value according to the plurality of groups of complex sample values; determining a frequency offset estimation range according to the frequency offset rough estimation value and a preset residual frequency difference value; and obtaining a frequency offset fine estimation value according to the frequency offset estimation range.

To achieve at least the above object, an embodiment of the present application further provides an electronic device, including: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the signal processing method described above.

To achieve at least the above object, an embodiment of the present application further provides a computer-readable storage medium storing a computer program that implements the above signal processing method when executed by a processor.

In the signal processing method provided by the embodiment of the application, M x N training symbols in M training symbol blocks in a received signal are firstly extracted, phase difference operation is carried out on the training symbols with the interval d in each training symbol block, a group of complex sample values corresponding to the interval d are obtained, and a plurality of groups of complex sample values corresponding to different interval values are obtained by adjusting the value d, so that a plurality of groups of complex sample values corresponding to different intervals for removing phase noise caused by line width are obtained, and the influence of the phase noise caused by line width on the performance of an FTN system is avoided. Then, according to the corresponding multiple groups of complex sample values at different intervals, firstly performing rough frequency offset estimation to obtain a rough frequency offset estimation value, and further combining the rough frequency offset estimation value with a preset residual frequency difference value to determine a frequency offset estimation range. And then, carrying out frequency offset fine estimation according to the frequency offset estimation range to obtain a frequency offset fine estimation value, thereby being beneficial to improving the accuracy and reliability of frequency offset estimation in the FTN system.

Drawings

FIG. 1 is a flow chart of a signal processing method mentioned in an embodiment of the present application;

fig. 2 is a schematic diagram of a frame structure of a received signal mentioned in an embodiment of the present application;

FIG. 3 is a flow chart of one implementation of step 103 mentioned in an embodiment of the present application;

FIG. 4 is a flow chart of one implementation of step 105 mentioned in an embodiment of the present application;

FIG. 5 is a cycle slip detection flow of reference phases of the effective signals mentioned in the embodiments of the present application;

FIG. 6 is a flow chart of one implementation of step 202 mentioned in an embodiment of the present application;

FIG. 7 is a flow chart of one implementation of determining whether a transition occurs in a reference phase of a training symbol block in accordance with an embodiment of the present application;

FIG. 8 is a flow chart of one implementation of cycle slip detection in step 204 as referred to in an embodiment of the present application;

FIG. 9 is a flow chart of one implementation of compensating for a reference phase at which a cycle slip occurs as mentioned in an embodiment of the present application;

fig. 10 is a flowchart of a carrier recovery method mentioned in the embodiment of the present application;

FIG. 11 is a graph of residual frequency offset versus frequency offset for FTN-PM-16QAM in accordance with an embodiment of the present application;

FIG. 12 is a graph of frequency offset magnitude versus estimated residual frequency offset for a fourth-order FFT frequency offset estimation algorithm referred to in an embodiment of the present application under FTN-PM-16 QAM;

FIG. 13 is a graph of estimated phase noise for the QPSK splitting algorithm mentioned in the embodiments of the present application under FTN-PM-16 QAM;

FIG. 14 is a graph of laser linewidth versus BER for FTN-PM-16QAM as referred to in an embodiment of the present application;

fig. 15 is a schematic structural diagram of an electronic device mentioned in an embodiment of the present application.

Detailed Description

For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the embodiments of the present application will be described in detail below with reference to the accompanying drawings. However, it will be understood by those of ordinary skill in the art that in various embodiments of the present application, numerous specific details are set forth in order to provide a thorough understanding of the present application. However, the claimed technical solution of the present application can be realized without these technical details and various changes and modifications based on the following embodiments. The following embodiments are divided for convenience of description, and should not be construed as limiting the specific implementation of the present application, and the embodiments can be mutually combined and referred to without contradiction.

The embodiment of the application relates to a signal processing method which is applied to electronic equipment, wherein the electronic equipment can be a signal receiving end, and the signal receiving end receives a signal sent by a sending end and processes the received signal. The flow chart of the signal processing method in this embodiment may refer to fig. 1, which includes:

Step 101: extracting M times N training symbols in M training symbol blocks in a received signal, and removing signal modulation phases; when the receiving signal is a signal to be transmitted by a transmitting end, K effective signals are inserted into a training symbol block with the length of N at intervals.

Step 102: and performing phase difference operation on training symbols with the interval d in each training symbol block to obtain a group of complex sample values corresponding to the interval d, and obtaining a plurality of groups of complex sample values corresponding to different intervals by adjusting the value of d.

Step 103: and obtaining a frequency offset rough estimation value according to the plurality of groups of complex sample values.

Step 104: and determining a frequency offset estimation range according to the frequency offset rough estimation value and a preset residual frequency difference value.

Step 105: and obtaining a frequency offset fine estimation value according to the frequency offset estimation range.

In this embodiment, the signal receiving end firstly extracts m×n training symbols in M training symbol blocks in the received signal, performs phase difference operation on training symbols with a d interval in each training symbol block to obtain a set of complex sample values corresponding to the d interval, and adjusts the d value to obtain a plurality of sets of complex sample values corresponding to different intervals, which is favorable for obtaining a plurality of sets of complex sample values corresponding to different intervals for removing phase noise caused by line width, and avoids the influence of the phase noise caused by line width on FTN system performance. Then, according to the corresponding multiple groups of complex sample values in different interval values, firstly performing rough frequency offset estimation to obtain a rough frequency offset estimation value, and further combining the rough frequency offset estimation value with a preset residual frequency difference value to determine a frequency offset estimation range. And then, carrying out frequency offset fine estimation according to the frequency offset estimation range to obtain a frequency offset fine estimation value, thereby being beneficial to improving the accuracy and reliability of frequency offset estimation in the FTN system.

The implementation details of the signal processing method of this embodiment are specifically described below, and the following description is merely provided for understanding the implementation details, and is not necessary to implement this embodiment.

In step 101, when the transmitting end constructs a signal to be transmitted, each of K valid signals is inserted into a training symbol block with a length of N, that is, when the transmitting end constructs a data frame, each of K valid signals is inserted into a training symbol block with a length of N. Therefore, when the receiving end receives the signal sent by the sending end, M times N training symbols in M training symbol blocks in the received signal can be extracted. Wherein M, N, K is an integer greater than 1 and K is greater than N.

In some embodiments, the frame structure of the received signal can be shown in fig. 2, where the training sequence in fig. 2 is a training symbol block with a length of N, and the valid data in fig. 2 is K valid signals.

In some embodiments, K is much greater than N, and when the transmitting end performs data frame construction, a training symbol block with a length of 8 may be inserted into each 512 valid signals, i.e. 8 training symbols may be inserted into each 512 valid signals. However, in the specific implementation, this is not a limitation.

In some embodiments, removing the signal modulation phase can also be understood as: the original phase of the training symbols is removed. Optionally, the way to remove the modulation phase of the signal may be: the extracted training symbols are multiplied by the complex conjugate of the original training symbols to obtain training symbols from which the signal modulation phases are removed.

For example, the kth training symbol TS in the ith training symbol block _p(k,l) The expression of (2) is shown in formula (1):

TS _p(l.k) ＝A*exp(jθ _s ) (1)

wherein A represents the amplitude of training symbol, θ _s Representing the phase of training symbols, wherein l is more than or equal to 1 and less than or equal to M. Equation (1) can be understood as an expression of the original training symbol.

Assuming that m=100 and n=8, the receiving end first extracts 800 training symbol numbers R in 100 training symbol blocks in the received signal _P Performing frequency offset estimation, wherein the kth training symbol R in the ith training symbol block _P(l,k) The expression of (2) is shown in the formula:

R _p(l,k) ＝A*exp{j(θ _s +2πΔfkT+θ _L (k))}+n(k) (2)

wherein Deltaf is the frequency offset generated by the local oscillator laser and the transmitting end laser, 2pi Delta fkT is the phase error component of the carrier frequency offset to the kth training symbol, T is the symbol period, and theta _L Representing the phase error introduced by the linewidth of the laser, n represents the amplifier spontaneous emission noise (amplifier spontaneousemission noise, ASE noise). The ASE noise is phase noise caused by ASE, accords with Gaussian distribution, and the average value is zero. Equation (2) can be understood as an expression of the training symbol received by the receiving end.

The training symbol of which the signal modulation phase is removed can be obtained by multiplying the training symbol received by the receiving end with the complex conjugate of the original training symbol. The expression of the training symbols with the signal modulation phase removed is shown in formula (3):

since n (k) conforms to a gaussian distribution with zero mean, equation (3) can be expressed as equation (4) below:

S _p(l,k) ≈A ² exp{j(2πΔfkT+θ _L (k)+θ _n (k))} (4)

θ _n ASE noise accords with Gaussian distribution, and the average value is zero.

In step 102, the receiving end performs phase difference operation on the training symbols with the interval d in each training symbol block to obtain a set of complex sample values corresponding to the interval d, and adjusts the value of d to obtain a plurality of sets of complex sample values corresponding to different intervals. Wherein the different intervals may be set according to actual needs, for example, may comprise all possible training symbol intervals within each training symbol block. For example, when 8 training symbols are included in one training symbol block, the different intervals may include 7 intervals, which are respectively: d=1, 2 … … 7, which respectively indicate that 0 training symbols are separated, 1 training symbol … … is separated, and 6 training symbols are separated. When d=1, that is, when 0 training symbols are spaced, phase difference operation can be performed on two adjacent training symbols in each training symbol block, so as to obtain a set of complex sample values corresponding to d=1. Wherein a set of complex samples may comprise a number of complex samples. When d=2, i.e. 1 training symbol is spaced apart, a phase difference operation may be performed on two training symbols spaced apart by 1 training symbol in each training symbol block, to obtain a set of complex samples corresponding to d=2. By adjusting the value of d, a plurality of groups of complex sample values corresponding to different intervals of values can be obtained in turn, and each interval d corresponds to a group of complex sample values.

Since in high-speed optical transmission systems the phase noise introduced by the laser linewidth is slowly varying relative to the symbol rate of the signal, it is a phase of several adjacent symbols in front of and behindThe bit effects can be considered the same and thus θ can be removed by phase difference operations on training symbols of different spacing within each training symbol block _L The resulting effect results in complex samples of phase noise resulting from the removed line widths. For example, the following equation (5) may be used to obtain a set of complex samples corresponding to the interval d:

wherein ,S_p(l，k) For the expression of the kth training symbol in the ith training symbol block,for the expression of complex conjugate of the (k+d) th training symbol in the (l) th training symbol block, Δf is the frequency offset generated by the local oscillator laser and the originating laser, 2pi Δ fkT is the phase error component caused by carrier frequency offset to the (k) th training symbol, T is the symbol period, θ _L Represents the phase error, theta, introduced by the linewidth of the laser _n As phase noise due to ASE, θ _n ' represents the difference in phase noise due to two training symbols ASE with a spacing d. d=1 corresponds to a set of complex samples, d=2 corresponds to a set of complex samples, and d=n-1 corresponds to a set of complex samples, resulting in N-1 sets of complex samples.

When d=1, the phase difference operation can be performed on the training symbols separated by 0 training symbols, that is, on each adjacent training symbol, by the above equation 5. When d=2, the phase difference calculation can be performed for any 2 training symbols each separated by 1 training symbol by the above equation 5. Similarly, the phase difference operation can be performed on the training symbols with different intervals in each training symbol block, so as to obtain a plurality of groups of complex sample values corresponding to different intervals. Wherein each interval may correspond to a set of complex samples, each set of complex samples comprising a number of complex samples.

In step 103, the receiving end performs rough frequency offset estimation according to the plurality of groups of complex sample values to obtain a rough frequency offset estimation value.

In some embodiments, the implementation of step 103 may refer to fig. 3, including:

step 1031: carrying out average operation on a plurality of complex average values in each group of complex sample values to obtain first complex average values respectively corresponding to different interval values;

step 1032: respectively taking amplitude angles of first complex averages corresponding to different interval values, and calculating to obtain initial frequency offset estimation values corresponding to different interval values;

step 1033: and obtaining a frequency offset rough estimation value according to the frequency offset estimation initial values respectively corresponding to the different interval values.

In this embodiment, by performing an average operation on a plurality of complex averages in each set of complex samples, it is beneficial to obtain complex averages corresponding to different interval values of a plurality of smoothed ASE noise, and combining the complex averages of the smoothed ASE noise is beneficial to improving accuracy of rough frequency offset estimation.

Because ASE noise obeys the characteristic that the mean value is zero, and meanwhile, in a high-speed optical transmission system, the frequency offset change between lasers has slow change characteristic relative to the symbol rate, and the frequency offset change is generally slower than the phase change introduced by the line width, the average operation can be carried out on a plurality of complex sample values in each group of complex mean values to obtain a complex mean value of smoothed ASE noise, and the influence of ASE noise on the frequency offset estimation value is smoothed by carrying out the average operation on training symbols in M training symbol blocks.

In step 1031, an average operation is performed on a plurality of complex averages in each set of complex sample values, so as to obtain a first complex average avg, which may be implemented by the following formula (6):

wherein Δf is a carrier frequency offset estimation value. When d=1, the average value of a plurality of complex sample values in a group of complex sample values corresponding to the interval d being 1 can be calculated according to the above formula (6) to be used as the first complex average value corresponding to the interval d=1, and when d=2, the average value of a plurality of complex sample values in a group of complex sample values corresponding to the interval d being 2 can be calculated according to the above formula (6) to be used as the first complex average value corresponding to the interval d=2.

Assuming that m=100 and n=8, the above formula (6) can be expressed as follows:

in step 1032, the receiving end respectively obtains the amplitude angles of the first complex averages corresponding to the values of different intervals, calculates to obtain the initial frequency offset estimation values corresponding to the different intervals, and each interval corresponds to one initial frequency offset estimation value. By taking the amplitude angle of the first complex average avg, the phase error component introduced by carrier frequency offset can be obtained, and then the frequency offset rough estimation value F1 is obtained through calculation. The frequency offset rough estimation value F1 can also be understood as a first-order frequency offset estimation result.

In some embodiments, the implementation of step 1033 may be: determining initial frequency offset estimation weights corresponding to different interval sampling values respectively according to 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 the plurality of groups of complex sample values; and obtaining a frequency offset rough estimation value according to the frequency offset estimation initial value weights respectively corresponding to different interval values and the frequency offset estimation initial values respectively corresponding to different interval values, thereby being beneficial to improving the accuracy and the stability of the frequency offset rough estimation. Wherein, the specific gravity of the complex sample value number in each complex sample value group to the complex sample value total number in the complex sample value group can be used as the frequency offset estimation initial value weight of the interval d corresponding to the complex sample value group. The total number of complex samples obtained based on a training symbol block comprising N training symbols is N (N-1)/2.

For example, when n=8, the interval d may be 1,2,3,4,5,6,7, and the number of complex samples in the corresponding set of complex samples at the interval d=1 is 7. The number of complex samples in the corresponding set of complex samples at interval d=2 is 6. The number of complex samples in the corresponding set of complex samples at interval d=3 is 5. The number of complex samples in the corresponding set of complex samples at interval d=4 is 4. The number of complex samples in the corresponding set of complex samples at interval d=5 is 3. The number of complex samples in the corresponding set of complex samples at interval d=6 is 2. The number of complex samples in the corresponding set of complex samples at interval d=7 is 1. The total number of complex values is 7+6+5+4+3+2+1=8× (8-1)/2=28. Based on the above, when d=1, the corresponding frequency offset estimation initial value weight is 7/28, when d=2, the corresponding frequency offset estimation initial value weight is 6/28, and so on, the corresponding frequency offset estimation initial value weight of each interval can be obtained. Finally, according to the initial value weight of the frequency offset estimation corresponding to each interval, carrying out weighted calculation on the initial value of the frequency offset estimation corresponding to each interval to obtain a weighted calculation result, wherein the weighted calculation result is the rough frequency offset estimation value.

In some embodiments, the initial frequency offset estimation weights corresponding to different intervals may be preset, for example, the initial frequency offset estimation weights corresponding to different intervals may be the same, but the embodiment is not limited thereto specifically.

In step 104, the receiving end determines a frequency offset estimation range according to the frequency offset rough estimation value and a preset residual frequency difference value. Wherein the residual frequency difference value is the maximum possible residual frequency offset value f of the FTN system _m . The frequency offset estimation range can be expressed as: [ F1-F _m ， F1+f _m ]MHz, e.g. f _m =100 MHz, the starting frequency point of the frequency offset estimation range is (F1-100 MHz), and the ending frequency point is (f1+100 MHz).

In step 105, the receiving end performs frequency offset fine estimation according to the frequency offset estimation range to obtain a frequency offset fine estimation value. In this embodiment, the frequency offset fine estimation may be performed by using CZT transformation, to obtain a frequency offset fine estimation value. Specifically, the second-order linear frequency modulation Z transformation CZT processing can be completed in an auxiliary mode according to the rough frequency deviation estimation value, namely the first-order frequency deviation estimation result, so that high-precision frequency deviation estimation is realized.

In some embodiments, the implementation of step 105 may refer to fig. 4, including:

step 1051: and determining a starting frequency point and an ending frequency point of the frequency offset estimation range.

Step 1052: and determining the number of the CZT output sequence points of the linear frequency modulation z transformation according to the starting frequency point, the ending frequency point and the preset frequency resolution.

Step 1053: and carrying out CZT on the received signal according to the number of CZT output sequence points to obtain a frequency offset fine estimation value.

In this embodiment, a start frequency point and an end frequency point of a frequency offset estimation range are determined, and then the accuracy of frequency offset estimation, that is, the frequency resolution, of CZT frequency offset is combined, so that the frequency offset estimation with high accuracy is facilitated to be finally realized for a system, and an accurate frequency offset fine estimation value is obtained.

In step 1051, the starting frequency point is the lower limit value of the frequency offset estimation range, and the ending frequency point is the upper limit value of the frequency offset estimation range.

In step 1052, the frequency resolution may be understood as the CZT frequency offset estimation accuracy, and the frequency resolution may be set according to practical needs, for example, may be 1.56MHz, however, the size of the frequency resolution is not specifically limited in this embodiment. And the receiving end determines the number of CZT output sequence points according to the starting frequency point, the ending frequency point and the preset frequency resolution.

In step 1053, the receiving end performs CZT on the received signal according to the number of CZT output sequence points, to obtain a frequency offset fine estimation value. Assuming that the number of CZT output sequence points is 128, the receiving end can perform 128-point CZT conversion on the received signal after the power of t to obtain a frequency offset fine estimation value F2. In this embodiment, t may be 4, that is, the receiving end may perform 128-point CZT transformation on the received signal after the power of 4 to obtain the frequency offset fine estimation value F2.

In some embodiments, after step 105, a cycle slip detection procedure of the reference phase of the effective signal may be further included, referring to fig. 5, the cycle slip detection procedure includes:

step 201: and carrying out frequency offset compensation on the training symbol block and the effective signal according to the frequency offset fine estimation value to obtain the training symbol block after frequency offset compensation and the effective signal after frequency offset compensation.

Step 202: and determining the reference phase of the training symbol block according to the training symbol block after the frequency offset compensation.

Step 203: and determining the reference phase of the effective signal according to the effective signal after the frequency offset compensation.

Step 204: and performing cycle slip detection of the reference phase of the effective signal according to the reference phase of the training symbol block and the reference phase of the effective signal.

Step 205: when the reference phase of the effective signal is determined to generate cycle slip, the reference phase generated by the cycle slip is compensated.

In this embodiment, based on the frequency offset compensated training symbol block and the effective signal, it is beneficial to accurately obtain the reference phases of the training symbol block and the effective signal. The frequency offset estimation and the phase offset estimation can multiplex the same group of periodic training symbols, which is beneficial to reducing the complexity of an algorithm and realizing the efficient detection of the cycle slip of an effective signal.

In step 201, the receiving end may perform frequency offset compensation on the received signal according to the frequency offset fine estimation value, that is, perform frequency offset compensation on each training symbol and each effective signal in the received signal.

In step 202, the receiving end determines reference phases of M training symbol blocks extracted from the received signal according to the training symbol blocks after the frequency offset compensation.

In some embodiments, the implementation of step 202 may refer to fig. 6, including:

step 2021: and removing the signal modulation phase of the training symbol in the training symbol block after the frequency offset compensation to obtain the training symbol block with the signal modulation phase removed.

Step 2022: and carrying out average operation on training symbols in the training symbol block from which the signal modulation phase is removed, and obtaining a second complex number average value.

Step 2023: and obtaining the reference phase of the training symbol block according to the second complex average value.

In this embodiment, by performing an average operation on training symbols in the training symbol block from which the signal modulation phase is removed, a second complex average value of the smoothed ASE noise is advantageously obtained, and the reference phase of the training symbol block can be accurately obtained by combining the second complex average value.

In step 2021, the training symbols may be frequency offset compensated and then phase-shifted with respect to the original training symbols to remove the signal modulation phase. However, the method of removing the signal modulation phase in the present embodiment is not particularly limited, and the removal of the signal modulation phase may be performed by a method other than the phase difference operation in a specific implementation.

In some embodiments, the phase difference operation is performed on the training symbol after the frequency offset compensation and the original training symbol to remove the signal modulation phase, which can be achieved by multiplying the frequency offset compensated training symbol with the complex conjugate of the original training symbol. For example, the training symbol after frequency offset compensation is denoted as R' _p The kth training symbol R in the kth training symbol block after frequency offset compensation _P ’ _(l,k) The expression of (2) is shown in formula (7):

R' _p(k,l) ＝exp{j(θ _s (k)+θ _L (k)+θ _n (k))} (7)

wherein ,θ_s (k) For the modulation phase of the kth training symbol, θ _L Represents the phase error, theta, introduced by the linewidth of the laser _n Indicating ASE noise. Can pass through R _P ’ _(l,k) And the original training symbol TS _p(k,l) The complex conjugate multiplication of (2) can accurately remove the signal modulation phase. The signal modulation phase may be removed by the following equation (8) to obtain a training symbol block from which the signal modulation phase is removed:

in step 2022, the receiving end performs an average operation on the training symbols in the training symbol block from which the signal modulation phase is removed, to obtain a second complex average value.

Since the ASE noise obeys the characteristic that the mean value is zero, the second complex mean value of the smoothed ASE noise can be obtained by performing an average operation on N training symbols in the current training symbol block by the following formula (9):

In some embodiments, the implementation of step 2023 may be: obtaining an amplitude angle of the second complex average value, obtaining an undeployed reference phase according to the amplitude angle obtained by the second complex average value, and performing unwrapping operation on the undeployed reference phase according to the target reference phase and a preset phase range to obtain an unwrapped reference phase of a training symbol block; wherein the target reference phase is an expanded reference phase of a training symbol block adjacent to and preceding the training symbol block. In particular, the undeployed reference phase can be understood as: reference phases that have not undergone a unwrapping operation, the unwrapped reference phases can be interpreted as: reference phase of the over-unwind operation is performed. The preset phase range is as follows: the phase estimation may estimate a phase range, such as 2pi.

In this embodiment, considering that the phase estimation can only estimate the carrier phase within a certain range, the unwrapped reference phase is unwrapped to unwrap the reference phase, which is beneficial to avoiding the problem of phase ambiguity of the reference phase.

In some embodiments, according to the target reference phase and the preset phase range, performing a unwrapped reference phase unwrapping operation to obtain an unwrapped reference phase of the training symbol block, including:

The unwrapped reference phase of the first training symbol block is obtained by the following equation (10):

wherein ,for undeployed reference phase, +.>The reference phase may be a reference phase which is already developed and can be used as a reference, or may be a developed reference phase of a training symbol block immediately preceding the first training symbol block, i.e., a developed reference phase of the first-1 training symbol block. R is a predetermined phase range, < >>For the expanded reference phase of the current training symbol block, round is a downward rounding function. L is more than or equal to 1 and less than or equal to M.

In some embodiments, after step 202, further comprising: sequentially taking each frequency offset compensated training symbol block as a current training symbol block, and determining whether jump occurs in the reference phase of the current training symbol block; and under the condition that the jump occurs in the reference phase of the current training symbol block, compensating the reference phase with the jump, and obtaining the reference phase after the jump compensation. The corresponding step 204 may be: and performing cycle slip detection on the reference phase of the effective signal according to the reference phase of the current training symbol block after the jump compensation and the reference phase of the effective signal.

In this embodiment, for the training symbol blocks after frequency offset compensation, whether the reference phases of the training symbol blocks are hopped is detected, and the hops in the reference phases are compensated in a targeted manner, so that the accuracy of the subsequent cycle slip detection is improved, and the reliability of phase offset estimation is improved.

In some embodiments, the training symbol blocks after frequency offset compensation sequentially enter a sliding window with a length of L, wherein L is the length of m training symbol blocks, and m is greater than 1; an implementation of determining whether a jump occurs in the reference phase of the current training symbol block may refer to fig. 7, including:

step 301: a first phase difference value of the reference phase of the first training symbol block and the last training symbol block within the sliding window is calculated.

Step 302: and under the condition that the absolute value of the first phase difference value is smaller than a preset jump threshold value, determining that no jump occurs in the reference phase of the current training symbol block.

Step 303: and under the condition that the absolute value of the first phase difference value is larger than a preset jump threshold value, determining that jump 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 length of the sliding window can be set to 2, namely 2 training symbol blocks can be accommodated in the sliding window. However, in a specific implementation, the length of the sliding window may be greater than 2, which is not specifically limited in this embodiment. The current training symbol block is the last training symbol block in the sliding window.

In this embodiment, by introducing the sliding window, the training symbol blocks after frequency offset compensation sequentially enter the sliding window with the length of L, so that the accuracy of jump detection can be improved.

In step 301, the receiving end may calculate, in real time, a first phase difference value of reference phases of a first training symbol block and a last training symbol block in the current sliding window. The first phase difference value may be expressed as: phi (L) -phi (l+L-1), wherein phi (L) is the reference phase of the first training symbol block in the sliding window and phi (l+L-1) is the reference phase of the last training symbol block in the sliding window.

When the length L of the sliding window is 2, the first phase difference value can be understood as the phase difference value of 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 comprises a training symbol block adjacent to and before the current training symbol block and/or a training symbol block adjacent to and after the current training symbol block.

In step 302, the preset jump threshold value may be set according to actual needs, for example, may be set to pi/4. When the absolute value of the first phase difference value is smaller than the preset jump threshold value Then confirmAnd determining that no jump occurs in the reference phase of the training symbol block, and sliding the sliding window backwards by the length of one training symbol block to continue to perform jump detection.

In step 303, assuming that the preset jump threshold is pi/4, when the absolute value of the first phase difference value is greater than the preset jump thresholdA jump in the reference phase of the training symbol block is determined.

In step 303, in case a jump in the reference phase occurs, the jump in the reference phase may be compensated for according to the first phase difference value.

In some embodiments, compensating for the hopped reference phase includes: if the first phase difference value is less than 0, the reference phase at which the jump will occur is reducedAnd obtaining the compensated reference phase. If the first phase difference value is greater than 0, the reference phase to which the jump will occur is increased +.>Obtaining a compensated reference phase; wherein (1)>The jump angle corresponding to the training symbol may be 2pi, for example.

That is, if phi (L) -phi (l+L-1)<0, then the reference phase is reduced after phi (l+L)Phi (l+l-1) is replaced by phi (l+l-2), i.e., phi (l+l-1) =phi (l+l-2); if phi (L) -phi (l+L-1)>0, then increase the reference phase after phi (l+L) >Phi (l+L-1) is replaced by phi (l+L-2), i.e., phi (l+L-1) =phi (l+L-2).

In this embodiment, detection and compensation of the jump in the reference phase are completed, so that the subsequent cycle-slip detection of the reference phase on the basis of the reference phase without jump is facilitated.

In some embodiments, the flow chart of cycle slip detection in step 204 may refer to fig. 8, including:

step 2041: sequentially taking each frequency offset compensated training symbol block as a current training symbol block, and determining a reference phase of a target effective signal adjacent to the current training symbol block; wherein the target valid signal comprises: the first effective signal is K/2 effective signals positioned before the current training symbol block, and/or the second effective signal is K/2 effective signals positioned after the current training symbol block.

Step 2042: and determining whether cycle slip occurs in the reference phase of the target effective signal according to a second phase difference value between the reference phase of the target effective signal and the reference phase of the current training symbol block.

In this embodiment, 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 signal of the half length adjacent to the reference phase of the reference phase, and the second phase difference value of the reference phase and the reference phase of the effective signal of the half length adjacent to the reference phase of the effective signal of the training symbol block is calculated to realize efficient detection of cycle slips of the effective signal.

Referring to fig. 2, one cycle slip detection period includes one training symbol block and K/2 effective signals adjacent to the training symbol block in front and behind. Wherein K/2 effective signals adjacent to the training symbol block can be understood as target effective signals adjacent to the training symbol block. In this embodiment, a single valid data block is divided into front and rear parts, i.e., K valid signals are divided into front K/2 valid signals and rear K/2 valid signals. And comparing the reference phase phi (l) of the current training symbol block with the reference phases theta (K) of K/2 effective signals adjacent to the reference phase phi (l) from front to back, calculating the phase difference value of the reference phase phi (l) and the phases theta (K) of the K/2 effective signals before and back of the training symbol block, and detecting whether cycle slip occurs or not based on the phase difference value.

In step 2041, a quadrature phase shift keying (Quadrature Phase Shift Keying, QPSK) partitioning algorithm may be used to perform phase estimation on the effective signal to obtain a reference phase of the target effective signal.

In some embodiments, in order to avoid phase ambiguity problems with the reference phase, a unwrapping operation may be performed to unwrap the reference phase of the target effective signal, such as unwrapping the reference phase by equation 11 below, considering that the phase estimate can only estimate carrier phases over a range:

wherein ,is the undeployed reference phase,>is the already developed reference phase which can be used as a reference, R represents the phase range which can be estimated by the phase estimation, where R is +.>round is a round-down function. Based on the obtained reference phase θ (k) of the effective signal after phase unwrapping, subsequent cycle slip detection and compensation are performed.

In step 2042, if the absolute value of the second phase difference value is smaller than the preset cycle slip detection threshold, determining that the reference phase of the target effective signal does not cycle slip; and if the absolute value of the second phase difference value is larger than a preset cycle slip detection threshold, determining that the reference phase of the target effective signal is cycle slip. The preset cycle-slip detection threshold may be determined according to a modulation mode of a received signal, the cycle-slip thresholds corresponding to different modulation modes may be different, and taking QPSK and 16QAM as examples, the cycle-slip threshold may be pi/4, however, the specific size of the cycle-slip detection threshold is not specifically limited in this embodiment.

In some casesIn an embodiment, the preset cycle slip detection threshold is pi/4. During the detection process, if the absolute value of the second phase difference value is smaller than the cycle slip detection threshold, i.eAnd determining that the reference phase of the target effective signal does not cycle slip, and detecting according to the effective signal data. If the absolute value of the second phase difference exceeds the cycle slip detection threshold, i.e Determining that the reference phase of the target effective signal is cycle-shifted and locating the current position of the target effective signal theta' (k) as the starting point CS of the next cycle-shift _star ＝k'。

In some embodiments, in step 205, the method for compensating the reference phase where the cycle slip occurs may refer to fig. 9, including:

step 2051: and taking the position of the target effective signal as the cycle slip starting point position.

Step 2052: determining a cycle slip termination position according to the Zhou Tiaoqi point position; wherein the cycle slip termination position is the position of the previous effective signal of the first effective signal meeting the preset condition after the Zhou Tiaoqi point position, and the absolute value of the difference value between the reference phase of the effective signal meeting the preset condition and the reference phase of the training symbol block is smaller than the cycle slip detection threshold;

step 2053: and compensating the reference phase of the cycle slip according to the cycle slip starting point position and the cycle slip ending position.

In this embodiment, when detecting occurrence of a cycle slip, the complete process of the cycle slip can be located, the detection is continued according to the valid signal sequence, and the cycle slip start position CS is recorded _star The position of the first effective signal meeting the preset condition is the absolute value of the phase difference value between the reference phase of the effective signal meeting the preset condition and the reference phase of the training symbol block before the effective signal meeting the preset condition is smaller than the cycle slip detection threshold, namely Locating the position of an effective signal preceding the position as the next cycle slip end position CS _end ＝k”-1。

In some embodiments, the implementation of step 2053 may be: a center point position between the cycle slip start position and the cycle slip end position is determined. And determining a third phase difference value between the reference phase corresponding to the center point position and the reference phase of the training symbol block. If the third phase difference value is larger than 0, reducing the reference phase corresponding to the cycle slip starting point position to the cycle slip end point position by alpha; if the third phase difference value is smaller than 0, increasing the reference phase corresponding to the cycle slip starting point position to the cycle slip end point position by alpha; wherein, alpha is the cycle slip angle corresponding to the modulation mode of the received signal. The cycle slip compensation mode in the embodiment is beneficial to improving the accuracy and rationality of cycle slip compensation.

The present embodiment compensates for the detected cycle slip after the occurrence of the cycle slip is detected. In the present embodiment, the center point position CS of the detected cycle slip is used _mid Determining cycle slip direction and cycle slip compensation value as reference, wherein CS _mid ＝(CS _star +CS _end )/2。

If θ (CS) _mid )-φ(l)>0, then from cycle slip start CS _star To cycle slip endpoint CS _end The phase corresponding to the position of (a) is reduced by alpha;

if θ (CS) _mid )-φ(l)<0, then from cycle slip start CS _star To cycle slip endpoint CS _end The phase corresponding to the position of (a) is increased by alpha. In the cycle slip compensation process, α is a cycle slip angle corresponding to a modulation mode of a received signal, and for each modulation mode, a constellation diagram of a transmitted signal (a received signal for a signal receiving end) is fixed, the constellation diagram rotates about an origin by a certain angle α, and the magnitude of α is the cycle slip angle. In other words. The value of α is obtained by rotating the constellation of the signal about the origin to the minimum angle when the constellation coincides with itself, for example, in the case of a modulation scheme using QPSK or 16QAM, the cycle slip angle α isIn the case of 8PSK modulation scheme, the cycle slip angle is +.>The specific Zhou Tiaojiao degrees may vary depending on the modulation scheme.

In some embodiments, the signal processing method may be specifically a method for recovering a carrier in the received signal, i.e. a carrier recovery method. The flow chart of the carrier recovery method may refer to fig. 10, which includes:

step 401: and extracting M-N training symbols in M training symbol blocks in the received signal, and removing the signal modulation phase.

Step 402: and performing phase difference operation on training symbols with different intervals in each training symbol block to obtain a plurality of complex sample values corresponding to the different intervals.

Step 403: and respectively carrying out average operation on a plurality of complex sample values corresponding to different intervals to obtain complex average values corresponding to different intervals of a plurality of smoothed ASE noise, respectively taking amplitude angles of the complex average values, respectively calculating to obtain a plurality of frequency offset estimation initial values, determining weights of the frequency offset estimation initial values corresponding to different intervals according to the proportion of the number of the complex sample values corresponding to different intervals to the total number of the complex sample values, and obtaining a final frequency offset rough estimation value based on the weights of the frequency offset estimation initial values.

Step 404: and determining a frequency offset estimation range according to the frequency offset rough estimation value and a preset residual frequency difference value, obtaining a frequency offset fine estimation value by carrying out CZT conversion on the received signal in a cubic direction according to the frequency offset estimation range, and carrying out frequency offset compensation on the effective signal and the training symbol according to the frequency offset fine estimation value.

Step 405: and extracting training symbols in the received signal after frequency offset compensation, and removing signal modulation phases.

Step 406: and carrying out average operation on training symbols in the current training symbol block, taking an amplitude angle, and obtaining a reference phase through unwrapping.

Step 407: and calculating and comparing the deviation between the reference phase difference value of the current training symbol block and the training symbol blocks adjacent to the current training symbol block and the jump threshold value, and detecting and compensating the jump of the reference phase of the current training symbol block based on the deviation.

Step 408: and calculating the difference value between the reference phase of the current training symbol block and the reference phases of the K/2 effective signals before and after symbol by symbol, comparing the difference value with a cycle slip detection threshold, and judging whether cycle slip occurs or not.

Step 409: and positioning the occurrence position of the cycle slip, and determining the cycle slip direction and the cycle slip compensation value.

Step 410: compensating for cycle slip occurring in the reference phase.

In this embodiment, not only can highly reliable frequency offset estimation be realized with less training overhead, but also skip cycles can be effectively detected/suppressed. On the premise of using only the same group of training symbols, the high-precision frequency offset estimation can be realized by combining the second-order CZT, and the algorithm complexity is far smaller than that of the traditional fourth-order FFT algorithm with the same precision. Meanwhile, when phase deviation estimation cycle slip is detected and compensated, even if cycle slip occurs for a plurality of times in a single detection period, reliable detection of cycle slip can be realized, and the method has strong practical application value. The following describes the advantages of the present embodiment in terms of frequency offset estimation and phase offset estimation in detail:

in terms of frequency offset estimation: taking different symbol intervals in each training symbol block to make difference with less expenditure (for example, 8 training symbols are inserted into 512 effective signals, which is lower than 1.6%), obtaining phase difference values caused by frequency deviation of a plurality of groups of different symbol intervals, averaging, and improving smooth noise effect; further, a plurality of training symbol blocks are taken for average operation, so that the smooth noise capability is improved again, and the stability of rough frequency offset estimation is ensured. Optionally, based on the first-stage frequency offset rough estimation value and the plus-minus 100MHz range, the frequency offset rough estimation value is used as the second-stage frequency offset fine estimation range, and finally, the frequency offset estimation result with high reliability and high precision (the residual frequency offset is not more than 2 MHz) is realized.

In terms of phase offset estimation: calculating the difference value between the reference phase of the current training symbol block and the reference phases of the front and rear adjacent training symbol blocks, detecting and compensating the jump of the reference phase of the current training symbol block by comparing the difference value with the deviation of the jump threshold value, wherein the reference phase obtained by the current training symbol block is only used as the reference for cycle-jump detection of the front and rear adjacent half-length effective signal phase, and the absolute value of the difference value of the estimated value of the half-length effective signal phase of the reference phase, which is adjacent to the front and rear adjacent half-length effective signal phase of the affiliated training symbol block, is sequentially and continuously compared with a preset cycle-jump judging threshold value, so that the efficient detection of the effective signal cycle-jump is realized (the cycle-jump in one training symbol block can be stably detected for a plurality of times).

In this embodiment, the frequency offset estimation and the phase offset estimation multiplex the same group of periodic training symbols, the frequency offset estimation and the second-order CZT are combined to realize high-precision frequency offset estimation, and the algorithm complexity is far less than that of the traditional fourth-order FFT algorithm (about 8%) with the same precision. Meanwhile, when phase offset estimation cycle slip is detected and compensated, the cycle slip of the reference phase can be detected and corrected, and reliable detection and correction can still be realized when cycle slip occurs for a plurality of times within a half length of an effective signal. The method and the device have the advantages of strong practicability, high frequency offset estimation precision, strong cycle slip detection capability, simplicity in implementation, low signal processing requirements and the like. The method solves the problem that the traditional carrier phase offset estimation algorithm (VVPE, BPS and the like) in the FTN system can generate serious cycle slip, and also solves the problem that the performance, complexity, spectrum efficiency and the like of the traditional carrier recovery method are difficult to consider.

FIG. 11 is a graph of residual frequency offset versus frequency offset for FTN-PM-16 QAM. Under the back-to-back condition of light, a three-carrier 128GBaud FTN-16QAM system is simulated, the acceleration factor is 1/0.9/0.85, OSNR=24dB, the laser linewidth is 100KHz, the training symbol insertion format is 8/512, the overhead is 1.56%, the training symbol length required by rough estimation is 3500, wherein key parameters of a CZT algorithm are as follows: the number of CZT points is 128, the number of data samples is 897, the CZT searching range is [ F1-100, F1+100]/MHz, and the searching precision is 1.56MHz. As shown in FIG. 11, in the Nyquist system and the FTN system with acceleration factors of 0.9 and 0.85, the method provided by the embodiment of the application can stabilize residual frequency offset at about 3M within the frequency offset range of [ -1.6 and 1.6] GHz, and the estimation accuracy is effectively improved.

Fig. 12 is a graph showing the bias estimation performance of the fourth-side FFT frequency offset estimation algorithm according to the embodiment of the present application. Simulating a three-carrier 128GBaud FTN-16QAM system under the back-to-back condition, wherein the acceleration factor is 0.9, OSNR=24 dB, the linewidth of a laser is 100KHz, the training symbol insertion format is 8/512, the overhead is 1.56%, the training symbol length required by rough estimation is 3500, and key parameters of a CZT algorithm are as follows: the number of CZT points is 128, the number of data samples is 897, the CZT searching range is [ F1-100, F1+100]/MHz, and the searching precision is 1.56MHz; the number of the four-side FFT frequency offset estimation algorithm points is 16384, and the estimation accuracy is 1.9MHz. As shown in fig. 12, in the FTN system with an acceleration factor of 0.9, in the frequency offset range of [ -1.6,1.6] ghz, the residual frequency offset of the method provided in this embodiment is smaller than that of the fourth-order FFT frequency offset estimation algorithm, and the complexity is only 8% of that of the latter.

Fig. 13 is a phase noise tracking performance comparison curve of the QPSK splitting algorithm and the embodiment of the present application. The three-carrier 128GBaud PM-16QAM system is simulated under the back-to-back condition, the acceleration factor is 0.85, the linewidth of a laser is 100kHz, and the estimated block length of the QPSK segmentation algorithm is 128. As shown in fig. 13, in the FTN system with the acceleration factor of 0.85, the QPSK splitting algorithm is affected by severe ISI, and a severe cycle slip phenomenon exists in the estimated phase noise curve, and the method provided by the embodiment of the present application can effectively detect and compensate the cycle slip phenomenon caused by the severe ISI.

FIG. 14 is a graph of laser linewidth versus BER for FTN-PM-16 QAM. Under the back-to-back condition of light, the three-carrier 128GBaud PM-16QAM system is simulated, the acceleration factor is 0.95/0.9/0.85, the linewidth of the laser is 100kHz, and the OSNR takes 23-27dB for simulation. Simulation analysis of algorithm linewidth tolerance was performed by defining Δv×ts (product of linewidth and symbol period) corresponding to 1dB OSNR cost (compared with OSNR corresponding to 0 linewidth) as a linewidth index, and the result is shown in fig. 14. As the acceleration factor decreases, inter-code crosstalk becomes more severe, and the system is more susceptible to phase noise, so line width tolerance decreases. The maximum line width that can be tolerated by 1dBOSNR under 128GBaud system is 2.2MHz, 3.2MHz and 4.5MHz when the acceleration factors are 0.85, 0.9 and 0.95. The embodiment of the application can effectively detect and compensate cycle slip under acceleration factors of 0.85 and the like, and has excellent line width tolerance.

It should be noted that, the foregoing examples in the embodiments of the present application are all illustrative for easy understanding, and do not limit the technical solution of the present application.

The above steps of the methods are divided, for clarity of description, and may be combined into one step or split into multiple steps when implemented, so long as they include the same logic relationship, and they are all within the protection scope of this patent; it is within the scope of this patent to add insignificant modifications to the algorithm or flow or introduce insignificant designs, but not to alter the core design of its algorithm and flow.

The embodiment of the application also provides an electronic device, as shown in fig. 15, including at least one processor 501; and a memory 502 communicatively coupled to the at least one processor 501; the memory 502 stores instructions executable by the at least one processor 501, and the instructions are executed by the at least one processor 501, so that the at least one processor 501 can execute the signal processing method in the above embodiment.

Where the memory 502 and the processor 501 are connected by a bus, the bus may comprise any number of interconnected buses and bridges, the buses connecting the various circuits of the one or more processors 501 and the memory 502 together. The bus may also connect together various other circuits such as peripherals, voltage regulators, and power management circuits, which are well known in the art, and therefore, will not be described any further herein. The bus interface provides an interface between the bus and the transceiver. The transceiver may be one element or may be a plurality of elements, such as a plurality of receivers and transmitters, providing a means for communicating with various other apparatus over a transmission medium. The data processed by the processor 501 is transmitted over a wireless medium via an antenna, which further receives the data and transmits the data to the processor 501.

The processor 501 is responsible for managing the bus and general processing and may also provide various functions including timing, peripheral interfaces, voltage regulation, power management, and other control functions. And memory 502 may be used to store data used by processor 501 in performing operations.

The embodiment of the application also provides a computer readable storage medium which stores a computer program. The computer program, when executed by a processor, implements the method embodiments described above.

That is, it will be understood by those skilled in the art that all or part of the steps in implementing the methods of the embodiments described above may be implemented by a program stored in a storage medium, including a plurality of instructions for causing a device (which may be a single-chip microcomputer, a chip or the like) or a processor (processor) to perform all or part of the steps in the methods of the embodiments of the application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.

It will be understood by those of ordinary skill in the art that the foregoing embodiments are specific examples of implementations of the application and that various changes in form and details may be made therein for practical use without departing from the spirit and scope of the application.

Claims

1. A signal processing method, comprising:

extracting M times N training symbols in M training symbol blocks in a received signal, and removing signal modulation phases; when the receiving signal is a signal to be transmitted by a transmitting end, inserting a training symbol block with the length of N into each K effective signals at intervals, wherein M, N, K is an integer greater than 1, and K is greater than N;

performing phase difference operation on training symbols with an interval d in each training symbol block to obtain a group of complex sample values corresponding to the interval d, and adjusting the value of d to obtain a plurality of groups of complex sample values corresponding to different interval values;

obtaining a rough frequency offset estimation value according to the plurality of groups of complex sample values;

determining a frequency offset estimation range according to the frequency offset rough estimation value and a preset residual frequency difference value;

and obtaining a frequency offset fine estimation value according to the frequency offset estimation range.

2. The signal processing method according to claim 1, wherein the obtaining the frequency offset fine estimation value according to the frequency offset estimation range includes:

determining a starting frequency point and an ending frequency point of the frequency offset estimation range;

determining the number of CZT output sequence points of the linear frequency modulation z transformation according to the starting frequency point, the ending frequency point and the preset frequency resolution;

And according to the number of CZT output sequence points, CZT is carried out on the received signal, and a frequency offset fine estimation value is obtained.

3. The signal processing method of claim 1, wherein said obtaining a coarse estimate of frequency offset from said plurality of sets of complex samples comprises:

carrying out average operation on a plurality of complex average values in each group of complex sample values to obtain first complex average values respectively corresponding to different interval values;

respectively taking amplitude angles of first complex averages corresponding to the different interval values, and calculating to obtain initial frequency offset estimation values corresponding to the different interval values;

and obtaining a rough frequency offset estimation value according to the frequency offset estimation initial values respectively corresponding to the different interval values.

4. The signal processing method according to claim 3, wherein the obtaining the frequency offset rough estimate according to the frequency offset estimate corresponding to the different interval values includes:

determining initial frequency offset estimation weights corresponding to different interval values respectively according to 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 the plurality of groups of complex sample values;

and obtaining a frequency offset rough estimation value according to the frequency offset estimation initial value weights respectively corresponding to the different interval values and the frequency offset estimation initial values respectively corresponding to the different interval values.

5. The signal processing method according to any one of claims 1 to 4, further comprising, after the obtaining of the frequency offset fine estimation value:

according to the frequency offset fine estimation value, performing frequency offset compensation on the training symbol block and the effective signal to obtain a training symbol block after frequency offset compensation and an effective signal after frequency offset compensation;

determining a reference phase of the training symbol block according to the frequency offset compensated training symbol block;

determining a reference phase of the effective signal according to the effective signal after the frequency offset compensation;

performing cycle slip detection of the reference phase of the effective signal according to the reference phase of the training symbol block and the reference phase of the effective signal;

and when the reference phase of the effective signal is determined to generate cycle slip, compensating the reference phase generated by the cycle slip.

6. The method according to claim 5, wherein determining the reference phase of the training symbol block based on the frequency offset compensated training symbol block comprises:

removing the signal modulation phase of the training symbol in the training symbol block after the frequency offset compensation to obtain a training symbol block with the signal modulation phase removed;

Carrying out average operation on training symbols in the training symbol block from which the signal modulation phase is removed to obtain a second complex average value;

and determining the reference phase of the training symbol block according to the second complex average value.

7. The signal processing method according to claim 6, wherein the obtaining the reference phase of the training symbol block according to the second complex average value includes:

obtaining an amplitude angle of the second complex average value;

obtaining an undeployed reference phase according to the amplitude angle obtained from the second complex average value;

according to the target reference phase and a preset phase range, performing a unwrapping operation on the undeployed reference phase to obtain an unwrapped reference phase of the training symbol block; wherein the target reference phase is an expanded reference phase of a training symbol block adjacent to and preceding the training symbol block.

8. The signal processing method according to claim 7, wherein the step of performing a unwrapping operation on the undeployed reference phases according to the target reference phases and a preset phase range to obtain the unwrapped reference phases of the training symbol block includes:

The unwrapped reference phase of the first training symbol block is obtained by the following formula:

wherein ,for the undeployed reference phase, +.>For the target reference phase, R is the preset phase range, +.>And l is more than or equal to 1 and less than or equal to M for the unfolded reference phase of the first training symbol block.

9. The signal processing method according to any one of claims 5 to 8, further comprising, after said determining a reference phase of said training symbol block from said frequency offset compensated training symbol block:

sequentially taking each frequency offset compensated training symbol block as a current training symbol block, and determining whether jump occurs in the reference phase of the current training symbol block;

under the condition that jump occurs in the reference phase of the current training symbol block, compensating the reference phase with jump, and obtaining the reference phase after jump compensation;

the cycle slip detection of the reference phase of the effective signal according to the reference phase of the training symbol block and the reference phase of the effective signal comprises the following steps:

and performing cycle slip detection on the reference phase of the effective signal according to the reference phase of the current training symbol block after the jump compensation and the reference phase of the effective signal.

10. The signal processing method according to claim 9, wherein the frequency offset compensated training symbol blocks sequentially enter a sliding window with a length L, where L is the length of m training symbol blocks, and m is greater than 1;

the determining whether a jump occurs in the reference phase of the current training symbol block includes:

calculating a first phase difference value of a reference phase of a first training symbol block and a last training symbol block in the sliding window;

under the condition that the absolute value of the first phase difference value is smaller than a preset jump threshold value, determining that jump does not occur in the reference phase of the current training symbol block;

determining that jump occurs in the reference phase of the current training symbol block under the condition that the absolute value of the first phase difference value is larger than a preset jump threshold value;

wherein the current training symbol block is the last training symbol block in the sliding window.

11. The signal processing method of claim 10, wherein compensating for the hopped reference phase comprises:

if the first phase difference value is smaller than 0, the reference phase where jump occurs is reducedObtaining a compensated reference phase;

If the first phase difference value is greater than 0, the reference phase at which the jump occurs is increasedObtaining a compensated reference phase;

wherein ,and the jump angle corresponding to the training symbol is obtained.

12. The signal processing method according to claim 5, wherein the performing cycle-slip detection of 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 includes:

sequentially taking each frequency offset compensated training symbol block as a current training symbol block, and determining a reference phase of a target effective signal adjacent to the current training symbol block; wherein the target valid signal comprises: a first effective signal and/or a second effective signal, wherein the first effective signal is K/2 effective signals positioned before the current training symbol block, and the second effective signal is K/2 effective signals positioned after the current training symbol block;

and determining whether cycle slip occurs to the reference phase of the target effective signal according to a second phase difference value of the reference phase of the target effective signal and the reference phase of the current training symbol block.

13. The method according to claim 12, wherein the determining whether the reference phase of the target effective signal is cycle-hopped based on the second phase difference value of the reference phase of the target effective signal and the reference phase of the current training symbol block, comprises:

If the absolute value of the second phase difference value is smaller than a preset cycle slip detection threshold, determining that the reference phase of the target effective signal does not cycle slip;

and if the absolute value of the second phase difference value is larger than a preset cycle slip detection threshold, determining that the reference phase of the target effective signal is cycle slip.

14. The signal processing method according to claim 12 or 13, wherein the compensating for the reference phase at which the cycle slip occurs includes:

taking the position of the target effective signal as a cycle slip starting point position;

determining a cycle slip ending position according to the cycle slip starting point position; the cycle slip termination position is the position of the previous effective signal of the first effective signal meeting the preset condition after the Zhou Tiaoqi point position, and the absolute value of the difference value between the reference phase of the effective signal meeting the preset condition and the reference phase of the current training symbol block is smaller than the cycle slip detection threshold;

and compensating the reference phase of the cycle slip according to the cycle slip starting point position and the cycle slip ending position.

15. The signal processing method according to claim 14, wherein the compensating the reference phase at which the cycle slip occurs based on the cycle slip start position and the cycle slip end position includes:

Determining a center point position between the cycle slip start position and the cycle slip end position;

determining a third phase difference value between the reference phase corresponding to the center point position and the reference phase of the current training symbol block;

if the third phase difference value is larger than 0, reducing the reference phase corresponding to the cycle slip starting point position to the cycle slip ending point position by alpha;

if the third phase difference value is smaller than 0, increasing the reference phase corresponding to the cycle slip starting point position to the cycle slip ending point position by alpha;

and alpha is a cycle slip angle corresponding to the modulation mode of the received signal.

16. The signal processing method according to any one of claims 1 to 4, wherein said performing a phase difference operation on training symbols with a spacing d in each of said training symbol blocks to obtain a set of complex samples corresponding to the spacing d comprises:

obtaining a plurality of complex sample values corresponding to different intervals by the following formula:

wherein ,S_p(l，k) For the expression of the kth training symbol in the ith training symbol block,for the expression of complex conjugate of the (k+d) th training symbol in the (l) th training symbol block, Δf is the frequency offset generated by the local oscillator laser and the originating laser, 2pi Δ fkT is the phase error component caused by carrier frequency offset to the (k) th training symbol, T is the symbol period, θ _L Represents the phase error, theta, introduced by the linewidth of the laser _n As phase noise due to ASE, θ _n ' represents the difference in phase noise due to two training symbols ASE with a spacing d.

17. An electronic device, comprising: at least one processor; the method comprises the steps of,

a memory communicatively coupled to the at least one processor; wherein,

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the signal processing method of any one of claims 1 to 16.

18. A computer readable storage medium storing a computer program, characterized in that the computer program, when executed by a processor, implements the signal processing method of any one of claims 1 to 16.