Half-carrier frequency offset estimation method and system in OFDM (Orthogonal Frequency Division Multiplexing) system

Abstract

The invention provides a half-carrier frequency offset estimation method and system in an OFDM (Orthogonal Frequency Division Multiplexing) system, and the half-carrier frequency offset estimation method comprises the steps of baseband signal acquisition, CP (Cyclic Prefix) phase calculation, ambiguity judgment, phase ambiguity transfer, CP frequency offset estimation, integer frequency offset estimation and final frequency offset estimation, converting the cross-correlation phase deviation value into a single-peak structure to obtain a phase deviation of the single-peak structure, then counting a risk coefficient of the phase deviation falling into a fuzzy region, if the risk coefficient is greater than a set value, performing phase fuzzy transfer, performing phase fuzzy transfer on a scene falling into the fuzzy region to obtain a defuzzification-processed phase deviation, and finally obtaining the defuzzification-processed phase deviation. The invention further provides a system for estimating the frequency offset of the half carrier in the OFDM system. According to the method, a fuzzy region can be converted into superposition of two determined regions, and the problem that CP frequency offset estimation is unstable near the half-carrier frequency offset is well solved.

Description

Technical Field

[0001] This invention relates to the field of OFDM system communication testing technology, and in particular to a method and system for estimating half-carrier frequency offset in OFDM systems. Background Technology

[0002] In a conventional OFDM testing system, the frequency offset estimation scheme is as follows: Figure 1 As shown, it mainly consists of three modules, including coarse frequency offset estimation based on CP (Cyclic Prefix). The estimated range is [-1 / 2, 1 / 2]. (sub-carrier space), that is, within half the subcarrier width; then, frequency domain correlation is performed based on the known sequence, or integer multiples of frequency offset are calculated based on whether the power of the RE matches the target resource RE mapping. After integer multiples of the frequency offset and coarse frequency offset compensation (CP), the residual frequency offset in the signal is considered to be very small. At this point, a pilot sequence with high estimation accuracy is used for fine frequency offset estimation and tracking. However, this signal processing system has a risk: CP-based frequency offset estimation has an estimation range of half a subcarrier. When the frequency offset is just close to half a subcarrier, due to noise affecting the correlation results at the boundary of testing capabilities, the traditional CP-based frequency offset estimation calculation suffers from phase flipping when calculating the phase of the correlation results, leading to an incorrect final frequency offset estimation. Most existing OFDM signal testing instruments on the market have this problem; when the frequency offset is near half a subcarrier, the frequency offset estimation results are abnormal, and the test results fluctuate greatly.

[0003] Frequency offset estimation based on CP, such as Figure 2 As shown, the baseband signal received by the receiver is: , in Let be the length of the CP signal. Assume there is a frequency offset between the transmitters. Therefore, in the signal acquired in the time domain, there is an additional phase deviation at different time points t. The received signal at this time is:

[0004] Where h is the channel impulse response. For transmitting signal sequences, For the received signal sequence, The time-domain length of the OFDM symbol is j, where j is the imaginary factor. .

[0005] Within the time domain CP range, each sample pair The phase offset is:

[0006] Taking the LTE system as an example, when the carrier spacing is = 15000Hz, when the system frequency deviation At 5000Hz, the phase distribution of most sample points is in Near the amplitude. Following traditional frequency offset calculation methods, each time-domain sample is assumed to be independent and identically distributed. The resulting cross-correlation phase shift follows a Gaussian distribution. The mean of the phase shifts of all samples is used as the final expected phase difference shift, such as... Figure 3 As shown.

[0007] However, when When the phase value is Since the function for finding angles has a range of... ,by It is a periodic cycle, at this time The possible values ​​are still The problem of ambiguity is that when the frequency offset is -1 / 2 or 1 / 2 subcarrier spacing, there is phase ambiguity in the solution angle.

[0008] Taking the LTE system as an example, when the carrier spacing is = 15000Hz, when When the subcarrier size is half 7500Hz, the phase distribution is around 3.14 and -3.14. Figure 4 The upper subplot's horizontal axis represents the time-domain sample symbol index, and the vertical axis corresponds to the symbol's phase; the lower subplot's horizontal axis represents the symbol phase, and the vertical axis represents the phase histogram of the phase distribution (the probability density function of the phase distribution, i.e., the number of samples corresponding to different phases). Figure 4 It can be seen that the phase of the cross-correlation solution of some time-domain samples has been flipped. In the scenario where the frequency offset is close to half a subcarrier, the phase distribution of the cross-correlation of time-domain samples is obviously a bimodal structure rather than a Gaussian distribution. The traditional method of taking the mean as the expected value of the correlation phase will lead to an incorrect conclusion. For example, in the above example, the actual frequency offset is 7500Hz, and the calculated frequency offset after averaging the phase is around 0Hz.

[0009] Therefore, existing frequency offset estimation schemes suffer from phase ambiguity in solving sample cross-correlation when the frequency offset of the OFDM system is near the half-subcarrier spacing, making the calculation results completely unreliable.

[0010] The scheme mentioned in the patent application No. CN201110049869.1 and entitled "OFDM communication system frequency offset estimation method and device" can theoretically solve the problem of half-subcarrier frequency offset if a local mode is used to construct a half-subcarrier reference sequence, but the scheme has obvious defects, such as high complexity and dependence on known reference sequence; in many OFDM signal analysis scenarios, a signal segment is randomly captured, the reference sequence contained in the signal segment is not known, and the sequence is an identification object after frequency offset compensation, so the large frequency offset detection scheme based on reference sequence correlation cannot be implemented. SUMMARY

[0011] To solve the problems in the prior art, the application provides an OFDM system half-subcarrier frequency offset estimation method, and further provides an OFDM system half-subcarrier frequency offset estimation method system, which converts an uncertain frequency offset problem into a deterministic integer multiple frequency offset problem and a deterministic decimal frequency offset problem through signal processing techniques. First, the CP-based cross-correlation phase distribution is divided into a deterministic region and a fuzzy region through the distribution characteristics of the time domain sample phase, if the phase distribution statistically falls into the fuzzy region, the cross-correlation phase is superimposed with a half-subcarrier frequency offset, and the correlation phase is converted from the fuzzy region to the deterministic decimal frequency offset region and the deterministic integer multiple frequency offset region. Since there is no ambiguity in CP frequency offset estimation in the deterministic region, and there is also no ambiguity in integer multiple frequency offset estimation, the conversion of one fuzzy region into the superposition of two deterministic regions can well solve the instability problem of CP frequency offset estimation near the half-subcarrier frequency offset.

[0012] The OFDM system half-subcarrier frequency offset estimation method provided by the application comprises the following steps: S1: baseband signal acquisition: acquiring and obtaining a baseband signal from a receiver radio frequency digital inlet; S2: CP phase calculation: obtaining time domain CP data based on the baseband signal, and calculating a cross-correlation phase offset value of the time domain sample based on the CP data; S3: ambiguity judgment: converting the cross-correlation phase offset value into a single-peak structure to obtain a phase deviation of the single-peak structure, and then statistically calculating a risk coefficient of the phase deviation falling into a fuzzy region, if the risk coefficient is greater than a set value, step S4 is executed, otherwise, step S5 is executed, wherein the phase deviation estimation value range of the CP time domain sample is , For the deterministic region, and for the fuzzy region; S4: phase ambiguity transfer: performing phase ambiguity transfer on the scene falling into the fuzzy region to obtain a de-fuzzification processed phase deviation; S5: CP frequency offset estimation: based on the phase deviation after the deblurring processing or the phase deviation less than the set value, the statistical deviation is calculated, and then the decimal multiple frequency offset is calculated; S6: integer frequency offset estimation: the integer multiple frequency offset is calculated; S7: final frequency offset estimation: based on the decimal multiple frequency offset and the integer multiple frequency offset, the final frequency offset estimation value is obtained.

[0013] The application is further improved, in step S2, after the baseband signal is collected, the starting position of the OFDM symbol is obtained based on the CP sliding correlation, and the time domain CP data is obtained, The calculation formula of the cross-correlation phase offset value of the time domain sample based on the CP data is: , Wherein, is the received signal sequence, indicates taking the conjugate, is the OFDM symbol time domain length, is the length of the CP signal, and t is the time point.

[0014] The application is further improved, in step S3, the processing process of ambiguity judgment is: (1) taking the reference phase , the absolute value of the difference value of the CP time domain sample phase offset value and the reference phase is calculated, the center position is offset by half subcarrier interval, and the phase deviation is obtained: , After the offset processing, The distribution is always single-peak structure; (2) based on the threshold , the number of samples with the phase deviation less than the threshold is counted, and then the risk coefficient of the statistical phase deviation falling into the ambiguity area is calculated , wherein is the total number of samples participating in the phase deviation calculation.

[0015] The application is further improved, in step S4, the processing formula of phase ambiguity transfer is: .

[0016] The application is further improved, in step S5, based on the phase deviation after the deblurring processing , the method for calculating the decimal multiple frequency offset is: , Wherein, ​W represents the width of one subcarrier in an OFDM system, is the statistical bias, that is, the expected value of the cross-correlation phase in the CP time domain, t is the sample serial number.

[0017] The application is further improved, in step S6, the sequence correlation method or the PRB power offset method is used to calculate the integer multiple frequency offset .

[0018] The application also provides an OFDM system half-subcarrier frequency offset estimation system for implementing the OFDM system half-subcarrier frequency offset estimation method, and the system comprises: A baseband signal acquisition module is used to collect and acquire a baseband signal from a receiver radio frequency digital inlet; A CP phase calculation module is used to obtain time domain CP data based on the baseband signal, and calculate a cross-correlation phase offset value of a time domain sample based on the CP data; A ambiguity judgment module is used to convert the cross-correlation phase offset value into a single-peak structure, obtain a phase bias of the single-peak structure, and then statistically determine a risk coefficient of the phase bias falling into an ambiguity region, if the risk coefficient is greater than a set value, step S4 is executed, otherwise, step S5 is executed, wherein the phase bias estimation range of the CP time domain sample is , is the determined region, and is the ambiguity region; A phase ambiguity transfer module is used to perform phase ambiguity transfer on a scene falling into the ambiguity region, and obtain a de-ambiguized phase bias ; A CP frequency offset estimation module is used to calculate a statistical bias based on the de-ambiguized phase bias or the phase bias with a risk coefficient less than a set value, and further calculate a decimal multiple frequency offset ; An integer frequency offset estimation module is used to calculate an integer multiple frequency offset ; A final frequency offset estimation module is used to obtain a final frequency offset estimation value based on the decimal multiple frequency offset and the integer multiple frequency offset .

[0019] Compared with the prior art, the present application has the advantages that: the present application converts an uncertain frequency offset problem into a certain integer multiple frequency offset problem and a certain decimal multiple frequency offset problem through signal processing techniques. The CP-based cross-correlation phase distribution is divided into a certain region and a fuzzy region through the distribution characteristics of the time domain sample phase. If the phase distribution falls into the fuzzy region statistically, the cross-correlation phase is superimposed with a half-carrier frequency offset to convert the correlation phase from the fuzzy region to the certain decimal frequency offset region and the certain integer multiple frequency offset region. Since there is no ambiguity in the CP frequency offset estimation in the certain region, the same is true for the integer multiple frequency offset estimation. Thus, the problem of instability of the CP frequency offset estimation near the half-carrier frequency offset can be well solved by converting one fuzzy region into the superposition of two certain regions.

[0020] Based on the frequency offset estimation scheme provided by the present application, the existing communication system basically does not need to be changed. Only the algorithm in the frequency offset estimation part is upgraded, the phase ambiguity problem of the CP frequency offset estimation can be solved, and the stability and reliability of the OFDM signal frequency offset estimation are effectively enhanced. BRIEF DESCRIPTION OF DRAWINGS

[0021] Figure 1 Flow chart of the existing frequency offset estimation method; Figure 2 Structure diagram of the received OFDM symbol; Figure 3 Structure diagram of the CP time domain sample cross-correlation phase distribution when there is no phase ambiguity; Figure 4 Structure diagram of the CP time domain sample cross-correlation phase distribution when there is phase ambiguity; Figure 5 Flow chart of the method of the present application; Figure 6 Structure diagram of the CP time domain sample cross-correlation phase fuzzy region division; Figure 7 Structure diagram of the method for converting the phase in the fuzzy region into the phase in the certain region; Figure 8 Structure diagram of the frequency offset CFO estimation results under different frequency offsets when the signal-to-noise ratio SNR is 10 dB; Figure 9 Structure diagram of the frequency offset CFO estimation error under different multiple frequency offsets when the signal-to-noise ratio SNR is 10 dB; Figure 10 Flow chart of the frequency offset estimation method in the cellular measurement system. DETAILED DESCRIPTION

[0022] The present application will be further described in detail below in combination with the drawings and embodiments.

[0023] As Figure 5As shown, the half-carrier frequency offset estimation method in the OFDM system of the present application comprises the following steps: S1: baseband signal acquisition: collecting and obtaining a baseband signal from a receiver radio frequency digital inlet; S2: CP phase calculation: based on the baseband signal, obtaining time domain CP data, and calculating the cross-correlation phase offset value of the time domain sample based on the CP data; S3: ambiguity judgment: converting the cross-correlation phase offset value into a single-peak structure to obtain the phase deviation of the single-peak structure, and then counting the risk coefficient of the phase deviation falling into the ambiguity region. If the risk coefficient is greater than a set value, step S4 is executed, otherwise, step S5 is executed, wherein the phase deviation estimation range of the CP time domain sample is , The determination region is and The ambiguity region is S4: phase ambiguity transfer: performing phase ambiguity transfer on the scene falling into the ambiguity region to obtain the phase deviation after deblurring processing; S5: CP frequency offset estimation: based on the phase deviation after deblurring processing or the phase deviation with a risk coefficient less than a set value, calculating the statistical deviation, and then calculating the fractional frequency offset; S6: integer frequency offset estimation: calculating the integer frequency offset; S7: final frequency offset estimation: based on the fractional frequency offset and the integer frequency offset, obtaining the final frequency offset estimation value.

[0024] After obtaining the final frequency offset estimation value, the subsequent pilot frequency offset fine estimation, data demodulation and RF index evaluation and other conventional processing procedures can be performed.

[0025] In step S2, after collecting the baseband signal, the starting position of the OFDM symbol is obtained based on CP sliding correlation, and the time domain CP data is obtained, the cross-correlation phase offset value of the time domain sample is calculated based on the CP data The calculation formula is: , Wherein, is the received signal sequence, represents taking the conjugate, is the OFDM symbol time domain length, is the length of the CP signal, and t is the time point.

[0026] In step S3, the processing process of the ambiguity judgment of the present application is: (1) taking the reference phase , calculating the absolute value of the difference value of the CP time domain sample phase offset value and the reference phase, offsetting the center position by half subcarrier interval to obtain the phase deviation : , After the offset processing, The distribution is always unimodal structure; (2) based on threshold , the number of samples of the phase deviation Less than the threshold , and then calculate the risk coefficient of the statistical phase deviation falling into the ambiguous area , wherein The total number of samples participating in the phase deviation calculation.

[0027] In step S4, the processing formula of phase ambiguity transfer is: .

[0028] As shown in Figure 6 And Figure 7 , because the CP time domain sample mutual phase difference estimation range is , the CP frequency offset estimation is unstable near the half carrier frequency offset, therefore, the sample phase difference is divided into two parts, Is the determination area, the remaining area And Is the ambiguous area. If the cross-correlation phase falls into the deterministic area statistically, the traditional method can obtain a certain non-ambiguous frequency offset estimation result. If the phase falls into the non-deterministic area statistically, the result is unreliable, and needs to be converted; for example, if the sample cross-correlation phase difference is , , the estimation result is unreliable, and for The sample is offset by half subcarrier offset ; for The sample is offset by half subcarrier offset , here And Is equivalent, because the sign phase period is . In this way, And Is converted to a half subcarrier phase offset plus And ; because And There is a half subcarrier frequency offset, superimposed with a half subcarrier offset to get an integer multiple of subcarrier frequency offset , And Convert to CP frequency offset determination area, get the estimation value in the range of At this time, based on the traditional method, a certain decimal multiple frequency offset value can be obtained.

[0029] The present application is also taken as an example of LTE, assuming that the frequency offset is 7400 Hz, and the CP sample phase difference falls into the ambiguity region; all samples are subjected to half-carrier offset, obtaining a frequency offset of 7400+7500 Hz = 14000 Hz -100 Hz, that is, converting the frequency offset of 7400 Hz into an integer multiple of frequency and a decimal multiple of frequency offset of -100 Hz; both the integer multiple of frequency offset and the decimal multiple of frequency offset of -100 Hz can be determined and estimated by a traditional method, thereby eliminating the uncertainty of the CP frequency offset estimation result in this scenario.

[0030] In step S5, based on the phase deviation after de-ambiguity processing , the method for calculating the decimal multiple frequency offset is as follows: , wherein, represents the width of one subcarrier in the OFDM system, is a statistical deviation, that is, the expected value of the cross-correlation phase in the CP time domain, and t is the sample serial number.

[0031] In step S6, a traditional method, such as the sequence correlation method or the PRB power offset method, is used to calculate the integer multiple frequency offset .

[0032] The present application also provides an OFDM system half-carrier frequency offset estimation system for implementing the OFDM system half-carrier frequency offset estimation method, comprising: a baseband signal acquisition module for collecting and obtaining a baseband signal from a receiver radio frequency digital inlet; a CP phase calculation module for obtaining time domain CP data based on the baseband signal, and calculating the cross-correlation phase offset value of the time domain sample based on the CP data; an ambiguity judgment module for converting the cross-correlation phase offset value into a single-peak structure to obtain the phase deviation of the single-peak structure, then statistically calculating the risk coefficient of the phase deviation falling into the ambiguity region, if the risk coefficient is greater than a set value, executing step S4, otherwise, executing step S5, wherein the phase deviation estimation range of the CP time domain sample is , is the determination region, and is the ambiguity region; a phase ambiguity transfer module for performing phase ambiguity transfer on the scenario falling into the ambiguity region to obtain the de-ambiguity processed phase deviation ; a CP frequency offset estimation module for calculating the decimal multiple frequency offset ​Or the phase deviation of the risk coefficient is less than the set value, the statistical deviation is calculated, and then the decimal multiple frequency deviation is calculated ; Integer frequency deviation estimation module: for calculating integer multiple frequency deviation ; Final frequency deviation estimation module: for obtaining a final frequency deviation estimation value based on the decimal multiple frequency deviation and the integer multiple frequency deviation .

[0033] Compared with the prior art, the frequency deviation estimation scheme based on the application can basically not make any changes to the existing communication system, and can solve the phase ambiguity problem of CP frequency deviation estimation by upgrading the algorithm in the frequency deviation estimation part, thereby effectively enhancing the stability and reliability of OFDM signal frequency deviation estimation.

[0034] In order to verify the effectiveness of the application, the application is compared with a traditional frequency deviation estimation method, and the experimental results are shown in Figure 8 and Figure 9 . The signal-to-noise ratio of the received signal is 10dB, the carrier frequency deviation starts to decrease from , the final results obtained by the frequency deviation estimation based on the traditional method and the deambiguating method used in the application are shown in Figure 8 , and it can be seen from Figure 8 that the traditional method cannot accurately estimate the frequency deviation value near half a subcarrier, and the estimation performance gradually improves as the frequency deviation gradually increases away from half a subcarrier; but the method based on the application can always better follow the theoretical frequency deviation value existing in the system. Figure 9 is the normalized error of the two frequency deviation estimation methods, the relative error of the traditional method near half a subcarrier is much larger than 15%, which exceeds the subsequent fine frequency deviation tracking range based on the pilot signal in the LTE test system, and will cause the frequency deviation correction link of the entire test system to fail; and the relative frequency deviation error based on the application is not more than 3%, and the error is within the subsequent frequency deviation tracking ability range based on the pilot.

[0035] As shown in Figure 10 , as an application embodiment of the application, the half-subcarrier frequency deviation estimation method of the application is applied to the CP frequency deviation coarse estimation in a cellular test system.

[0036] Current mainstream communication equipment such as LTE and NR use the CP-OFDM transmission scheme. Among the equipment used for RF testing of the transceivers of these devices, such as comprehensive test instruments, most instruments use non-signaling test schemes. Since the frequency offset estimation range of pilot symbols is very small, the estimation and compensation in the coarse frequency offset estimation stage are based on CP time-domain samples. At this time, the CP frequency offset estimation error is required to be within the allowable range of pilot symbol frequency offset estimation error. That is, there are certain requirements for the CP frequency offset estimation error. Therefore, the ability to achieve accurate frequency offset estimation based on the CP information of OFDM symbols becomes a more important part of the entire test system, which determines the final test stability and reliability.

[0037] Based on the current sampled baseband segment signal, the starting position of the OFDM symbol is obtained based on the CP, and then the position of the CP data is obtained. Coarse frequency offset estimation and compensation are performed based on the CP time-domain data to ensure that the residual frequency offset is within the range of subsequent pilot-based frequency offset estimation. If the frequency offset error estimated by CP is large, subsequent pilot frequency offset tracking will fail, and the entire test result will become unstable. Currently, many instrument systems experience unstable test performance when the frequency offset is near half a subcarrier due to large CP frequency offset estimation errors. However, the method provided by this invention can... A relatively accurate frequency offset estimation is achieved throughout the entire region, meeting the requirements for subsequent pilot-based fine frequency offset tracking and obtaining stable test results.

[0038] The specific embodiments described above are preferred embodiments of the present invention and are not intended to limit the specific scope of the present invention. The scope of the present invention includes, but is not limited to, these specific embodiments. All equivalent changes made in accordance with the present invention are within the protection scope of the present invention.

Claims

1. A method for half-carrier frequency offset estimation in an OFDM system, characterized in that, The method comprises the following steps: S1: baseband signal acquisition: collecting and obtaining baseband signals from the receiver radio frequency digital entrance; S2: CP phase calculation: based on the baseband signal, obtaining time domain CP data, and calculating the cross-correlation phase offset value of the time domain sample based on the CP data; S3: ambiguity judgment: convert the cross-correlation phase offset value into a single peak structure, and obtain the phase deviation of the single peak structure Then, the phase deviation is counted The risk coefficient falling into the ambiguity region, if the risk coefficient is greater than a set value, step S4 is executed, otherwise, step S5 is executed, wherein the phase deviation estimation range of the CP time domain sample is Wherein The determination region is And The ambiguity region is S4: Phase ambiguity transfer: phase ambiguity transfer is performed on the scene falling into the ambiguity area to obtain the phase deviation after deblurring ; S5: CP frequency offset estimation: calculate the phase deviation based on the de-blurring processing or the phase deviation with a risk coefficient less than a set value, calculate the statistical deviation, and then calculate the decimal frequency offset ; S6: Integer frequency offset estimation: Compute integer multiple frequency offset ; S7: Final frequency offset estimation: based on the fractional frequency offset and the integer frequency offset, the final frequency offset estimation value is obtained .

2. The method for half-carrier frequency offset estimation in OFDM system according to claim 1, characterized in that: In step S2, after the baseband signal is collected, the starting position of the OFDM symbol is obtained based on the CP sliding correlation, and the time domain CP data is obtained.

3. The method for half-carrier frequency offset estimation in OFDM system according to claim 1, characterized in that: In step S3, the processing process of ambiguity judgment is as follows: (1) Take the reference phase , calculate the absolute value of the difference between the CP time domain sample phase offset value and the reference phase, offset the center position by half subcarrier spacing, and obtain the phase deviation : ， After the offset processing, The distribution of the particle size is always unimodal. (2) Threshold-based Statistical phase deviation Less than the threshold The number of samples is used to calculate the statistical risk coefficient of phase deviation falling into the fuzzy region. ,in This represents the total number of samples used in the phase deviation calculation.

4. The method for half-carrier frequency offset estimation in OFDM system according to claim 3, characterized in that: In step S4, the processing formula of phase blur transfer is: .

5. The method for half-carrier frequency offset estimation in OFDM system according to claim 4, characterized in that: In step S5, based on the phase deviation after deblurring... Calculate the fractional octave frequency offset The method is as follows: ， ， wherein denotes the width of one subcarrier in the OFDM system, is the statistical bias, i.e. the expected value of the cross-correlation phase for the CP time domain, and t is the sample number.

6. The method for half-carrier frequency offset estimation in OFDM system according to claim 5, characterized in that: In step S6, the sequence correlation method or the PRB power offset method is used to calculate the integer frequency offset .

7. A system for semi-carrier frequency offset estimation in an OFDM system for implementing the method for semi-carrier frequency offset estimation in an OFDM system according to any one of claims 1 to 6, characterized in that It comprises: a baseband signal acquisition module: used for collecting and obtaining baseband signals from the receiver radio frequency digital entrance; a CP phase calculation module: used for obtaining time domain CP data based on the baseband signal, and calculating the cross-correlation phase offset value of the time domain sample based on the CP data; Ambiguity judgment module: used for converting the cross-correlation phase offset value into a single peak structure, and obtaining the phase deviation of the single peak structure Then, the phase deviation is counted The risk coefficient falling into the ambiguity area, wherein the phase deviation estimation range of the CP time domain sample is Wherein To determine the area, And The ambiguity area; Phase blur transfer module: used for phase blur transfer to the scene falling into the blur area, to get the deblurring processing phase deviation ; CP frequency offset estimation module: used for phase offset based on defuzzification processing If the risk coefficient is less than the set value, calculate the statistical deviation, and then calculate the fractional octet frequency deviation. ; integer frequency offset estimation module: for calculating integer multiple frequency offset ; Final frequency offset estimation module: used for obtaining a final frequency offset estimation value based on the fractional frequency offset and the integral frequency offset .

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