A method and system for half-carrier frequency offset estimation in an OFDM system

Abstract

The application provides a half-carrier frequency offset estimation method and system in an OFDM system. The half-carrier frequency offset estimation method comprises the steps of baseband signal acquisition, CP phase calculation, ambiguity judgment, phase ambiguity transfer, CP frequency offset estimation, integer frequency offset estimation and final frequency offset estimation. In the ambiguity judgment step, the cross-correlation phase offset value is converted into a single-peak structure, the phase deviation of the single-peak structure is obtained, and then the risk coefficient of the phase deviation falling into the ambiguity region is calculated. If the risk coefficient is greater than a set value, the phase ambiguity transfer is performed, the phase ambiguity transfer is performed on the scene falling into the ambiguity region, the de-ambiguity processed phase deviation is obtained, and then the decimal multiple frequency offset is calculated. The application also provides a half-carrier frequency offset estimation system in an OFDM system. The application can convert the ambiguity region into the superposition of two determined regions, and well solves the instability problem of the CP frequency offset estimation near the half-carrier frequency offset.

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

[0004] Within the time domain CP range, each sample pair The phase offset is:

[0005] 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.

[0006] 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.

[0007] Taking the LTE system as an example, when the carrier spacing is = 15000Hz, when When the subcarrier size is half a 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.

[0008] 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.

[0009] The scheme mentioned in the patent application with application number CN201110049869.1, entitled "A Method and Apparatus for Estimating Frequency Offset in OFDM Communication Systems," theoretically can handle the problem of half-subcarrier frequency offset if a half-carrier reference sequence is constructed using a local template. However, this scheme has obvious drawbacks: high complexity and reliance on a known reference sequence. In many OFDM signal analysis scenarios, a signal segment is randomly selected, and the reference sequence contained in this signal segment is not known. This sequence is the object to be identified after frequency offset compensation. In this case, a large frequency offset detection scheme based on reference sequence correlation cannot be implemented. Summary of the Invention

[0010] To address the problems in existing technologies, this invention provides a method for estimating half-carrier frequency offset in an OFDM system, and also provides a system for implementing this method. Through signal processing techniques, an uncertain frequency offset problem is transformed into a deterministic integer multiple frequency offset problem and a deterministic fractional multiple frequency offset problem. First, based on the distribution characteristics of the time-domain sample phases, the cross-correlation phase distribution based on CP is divided into deterministic and fuzzy regions. If the phase distribution statistically falls into the fuzzy region, the half-carrier frequency offset is superimposed on the cross-correlation phases, transforming the correlated phases from the fuzzy region to the deterministic fractional frequency offset region and the deterministic integer multiple frequency offset region. Since CP frequency offset estimation is unambiguous in the deterministic region, and similarly, integer multiple frequency offset estimation is also unambiguous, this transformation of a fuzzy region into the superposition of two deterministic regions effectively solves the problem of instability in CP frequency offset estimation near the half-carrier frequency offset.

[0011] The half-carrier frequency offset estimation method in the OFDM system of this invention includes the following steps: S1: Baseband signal acquisition: Acquire and obtain the baseband signal from the receiver's RF digital input; S2: CP phase calculation: Based on the baseband signal, obtain time-domain CP data, and calculate the cross-correlation phase offset value of the time-domain samples based on the CP data; S3: Fuzzy judgment: Convert the cross-correlation phase offset value to a single-peak structure, and obtain the phase deviation of the single-peak structure. Then, the phase deviation is statistically analyzed. The risk coefficient for falling into the fuzzy region is determined. If the risk coefficient is greater than a set value, step S4 is executed; otherwise, step S5 is executed. The estimated range of the phase deviation for the CP time-domain sample is... , To determine the area, and The region is blurred. S4: Phase Blur Transfer: Perform phase blur transfer on the scene falling into the blur region to obtain the deblurred phase deviation. ; S5: CP frequency offset estimation: based on phase deviation after defuzzification. If the risk coefficient is less than the set value, calculate the statistical deviation, and then calculate the fractional octet frequency deviation. ; S6: Integer Frequency Offset Estimation: Calculate integer multiples of frequency offset ; S7: Final Frequency Offset Estimation: Based on fractional and integer multiples of the frequency offset, the final frequency offset estimate is obtained. .

[0012] In a further improvement to this invention, in step S2, after acquiring the baseband signal, the starting position of the OFDM symbol is obtained based on CP sliding correlation, and time-domain CP data is obtained. Calculate the cross-correlation phase shift value of time-domain samples based on CP data. The calculation formula is: , in, For the received signal sequence, Indicates taking the conjugate. The time domain length of the OFDM symbol. t represents the length of the CP signal and t represents the time point.

[0013] The present invention is further improved in that the fuzzyness judgment process in step S3 is as follows: (1) Take the reference phase Calculate the absolute value of the difference between the CP time-domain sample phase offset and the reference phase, and perform a half-subcarrier interval offset on the center position to obtain the phase deviation. : , After offset processing The distribution always exhibits a unimodal structure; (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. , This represents the total number of samples used in the phase deviation calculation.

[0014] In a further improvement to this invention, the formula for phase fuzzy transfer in step S4 is as follows: .

[0015] The present invention is further improved in that, in step S5, the phase deviation is based on the deblurring process. Calculate the fractional octave frequency offset The method is as follows: , in, This represents the width of a subcarrier in an OFDM system. t represents the statistical bias, which is the expected value of the cross-correlation phase in the CP time domain, and t represents the sample number.

[0016] In a further improvement to this invention, in step S6, the integer multiples of the frequency offset are calculated using either the sequence correlation method or the PRB power offset method. .

[0017] The present invention also provides a half-carrier frequency offset estimation system in an OFDM system, for implementing the half-carrier frequency offset estimation method in the OFDM system, comprising: Baseband signal acquisition module: used to acquire and obtain baseband signals from the receiver's RF digital input; CP phase calculation module: used to obtain time-domain CP data based on the baseband signal, and calculate the cross-correlation phase offset value of the time-domain samples based on the CP data; The fuzziness determination module is used to convert the cross-correlation phase offset value into a single-peak structure, thereby obtaining the phase deviation of the single-peak structure. Then, the phase deviation is statistically analyzed. The risk coefficient for falling into the fuzzy region is determined. If the risk coefficient is greater than a set value, step S4 is executed; otherwise, step S5 is executed. The estimated range of the phase deviation for the CP time-domain sample is... , To determine the area, and The region is blurred. Phase blur transfer module: Used to perform phase blur transfer on scenes falling into blur regions, obtaining the deblurred 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: used to calculate integer multiples of frequency offset. ; Final frequency offset estimation module: Used to obtain the final frequency offset estimate based on fractional and integer multiples of the frequency offset. .

[0018] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention transforms an uncertain frequency offset problem into a deterministic integer multiple frequency offset problem and a deterministic fractional multiple frequency offset problem through signal processing techniques. First, based on the distribution characteristics of the time-domain sample phase, the cross-correlation phase distribution based on CP is divided into deterministic and fuzzy regions. If the phase distribution statistically falls into the fuzzy region, then a half-carrier frequency offset is superimposed on the cross-correlation phase, transforming the correlated phase from the fuzzy region to the deterministic fractional frequency offset region and the deterministic integer multiple frequency offset region. Since there is no fuzziness in the CP frequency offset estimation in the deterministic region, and similarly, there is no fuzziness in the integer multiple frequency offset estimation, thus, by transforming a fuzzy region into the superposition of two deterministic regions, the problem of instability in CP frequency offset estimation near the half-carrier frequency offset can be effectively solved.

[0019] Based on the frequency offset estimation scheme provided by this invention, no changes are required to the existing communication system. Only by upgrading the algorithm in the frequency offset estimation part, the problem of phase ambiguity in CP frequency offset estimation can be solved, which effectively enhances the stability and reliability of OFDM signal frequency offset estimation. Attached Figure Description

[0020] Figure 1 Here is a flowchart of an existing frequency offset estimation method; Figure 2 A schematic diagram of the received OFDM symbol structure; Figure 3 This is a schematic diagram of the cross-correlation phase distribution of CP time-domain samples when there is no phase ambiguity. Figure 4 This is a schematic diagram of the cross-correlation phase distribution of CP time-domain samples when phase ambiguity exists; Figure 5 This is a flowchart of the method of the present invention; Figure 6 A schematic diagram illustrating the delineation of phase ambiguity regions in the cross-correlation of CP time-domain samples; Figure 7 A schematic diagram illustrating the method for converting phase in a fuzzy region to phase in a definite region. Figure 8 This is a schematic diagram showing the frequency offset CFO estimation results at different frequency offsets when the signal-to-noise ratio (SNR) is 10dB. Figure 9 A schematic diagram showing the CFO estimation error of the lower frequency offset at different octaves when the signal-to-noise ratio (SNR) is 10dB. Figure 10 This is a flowchart of the frequency offset estimation method in a cellular measurement and testing system. Detailed Implementation

[0021] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments.

[0022] like Figure 5As shown, the half-carrier frequency offset estimation method in the OFDM system of the present invention includes the following steps: S1: Baseband signal acquisition: Acquire and obtain the baseband signal from the receiver's RF digital input; S2: CP phase calculation: Based on the baseband signal, obtain time-domain CP data, and calculate the cross-correlation phase offset value of the time-domain samples based on the CP data; S3: Fuzzy judgment: Convert the cross-correlation phase offset value to a single-peak structure, and obtain the phase deviation of the single-peak structure. Then, the phase deviation is statistically analyzed. The risk coefficient for falling into the fuzzy region is determined. If the risk coefficient is greater than a set value, step S4 is executed; otherwise, step S5 is executed. The estimated range of the phase deviation for the CP time-domain sample is... , To determine the area, and The region is blurred. S4: Phase Blur Transfer: Perform phase blur transfer on the scene falling into the blur region to obtain the deblurred phase deviation. ; S5: CP frequency offset estimation: based on phase deviation after defuzzification. If the risk coefficient is less than the set value, calculate the statistical deviation, and then calculate the fractional octet frequency deviation. ; S6: Integer Frequency Offset Estimation: Calculate integer multiples of frequency offset ; S7: Final Frequency Offset Estimation: Based on fractional and integer multiples of the frequency offset, the final frequency offset estimate is obtained. .

[0023] Once the final frequency offset estimate is obtained, the routine processing steps such as pilot frequency offset fine estimation, data demodulation, and RF index evaluation can be carried out.

[0024] In step S2, after acquiring 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. Calculate the cross-correlation phase shift value of time-domain samples based on CP data. The calculation formula is: , in, For the received signal sequence, Indicates taking the conjugate. The time domain length of the OFDM symbol. t represents the length of the CP signal and t represents the time point.

[0025] In step S3, the fuzzyness determination process of the present invention is as follows: Take reference phase Calculate the absolute value of the difference between the CP time-domain sample phase offset and the reference phase, and perform a half-subcarrier interval offset on the center position to obtain the phase deviation. : After offset processing, The distribution always exhibits a unimodal structure; (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. , This represents the total number of samples used in the phase deviation calculation.

[0026] In step S4, the formula for phase fuzzy transfer is as follows: .

[0027] like Figure 6 and Figure 7 As shown, since the estimated range of the positional differences between CP time-domain samples is Since CP frequency offset estimation is unstable near the half-carrier frequency offset, this invention divides the sample phase difference into two parts. The range for deterministic estimation, also called the deterministic region, is the remaining region. and This is the fuzzy region. If the cross-correlation phase statistically falls into the deterministic region, a definite unfuzzy frequency offset estimate can be obtained based on traditional methods. If the phase statistically falls into the indeterminate region, the result is unreliable and requires transformation; for example, if the sample cross-correlation phase difference is... , The estimation results are unreliable. The sample is offset by half a subcarrier offset. ;right The sample is offset by half a subcarrier offset. ,here and They are equivalent because the symbol phase period is In this way, and Convert to a half-carrier phase offset plus and ;because and The subcarrier frequency offset is inherently half-carrier frequency offset; adding a half-carrier offset results in an integer multiple of the subcarrier frequency offset. , and After switching to the region with a defined CP frequency offset, a definite result is obtained. The estimated value is within the range, and at this point, a deterministic fractional frequency offset value can be obtained based on traditional methods.

[0028] This invention still uses LTE as an example, assuming a frequency offset of 7400Hz, and the CP sample phase difference falling into the ambiguity region; by performing a half-carrier offset on all samples, the frequency offset is obtained as 7400 + 7500Hz = -100Hz, that is, converting the 7400Hz frequency offset to a... The integer multiples of the frequency and the fractional multiples of the frequency offset at -100Hz are both determined using traditional methods, thus eliminating the uncertainty of the CP frequency offset estimation results in this scenario.

[0029] In step S5, based on the phase deviation after deblurring... Calculate the fractional octave frequency offset The method is as follows: , in, This represents the width of a subcarrier in an OFDM system. t represents the statistical bias, which is the expected value of the cross-correlation phase in the CP time domain, and t represents the sample number.

[0030] In step S6, traditional methods, such as sequence correlation or PRB power offset, are used to calculate integer multiples of frequency offset. .

[0031] The present invention also provides a half-carrier frequency offset estimation system in an OFDM system, for implementing the half-carrier frequency offset estimation method in the OFDM system, comprising: Baseband signal acquisition module: used to acquire and obtain baseband signals from the receiver's RF digital input; CP phase calculation module: used to obtain time-domain CP data based on the baseband signal, and calculate the cross-correlation phase offset value of the time-domain samples based on the CP data; The fuzziness determination module is used to convert the cross-correlation phase offset value into a single-peak structure, thereby obtaining the phase deviation of the single-peak structure. Then, the phase deviation is statistically analyzed. The risk coefficient for falling into the fuzzy region is determined. If the risk coefficient is greater than a set value, step S4 is executed; otherwise, step S5 is executed. The estimated range of the phase deviation for the CP time-domain sample is... , To determine the area, and The region is blurred. Phase blur transfer module: Used to perform phase blur transfer on scenes falling into blur regions, obtaining the deblurred 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: used to calculate integer multiples of frequency offset. ; Final frequency offset estimation module: Used to obtain the final frequency offset estimate based on fractional and integer multiples of the frequency offset. .

[0032] Compared with existing technologies, the frequency offset estimation scheme provided by this invention requires virtually no modification to existing communication systems. The problem of phase ambiguity in CP frequency offset estimation can be solved simply by upgrading the algorithm in the frequency offset estimation part, effectively enhancing the stability and reliability of OFDM signal frequency offset estimation.

[0033] To verify the effectiveness of this invention, a comparative experiment was conducted with traditional frequency offset estimation methods. The experimental results are as follows: Figure 8 and Figure 9 As shown. The signal-to-noise ratio of the received signal is 10dB, and the carrier frequency offset is from... The frequency offset estimation begins to decrease from 7500Hz, based on traditional methods and the phase ambiguity removal method used in this invention. The final result is as follows: Figure 8 As shown, from Figure 8 It is evident that traditional methods cannot accurately estimate the frequency offset value near half a subcarrier. As the frequency offset gradually increases near half a subcarrier, the estimation performance gradually improves. However, based on the method of this invention, the estimated frequency offset can always follow the theoretical frequency offset value existing in the system quite well. Figure 9 The error is the normalized error of the two frequency offset estimation methods. The traditional method has a relative error of more than 15% relative to the frequency offset of half a subcarrier. In the LTE comprehensive test system, this exceeds the range of subsequent fine frequency offset tracking based on pilot signals, which will cause the frequency offset correction link of the entire test system to fail. However, the method based on this invention has a relative frequency offset error of no more than 3%, which is within the range of subsequent frequency offset tracking capability based on pilot signals.

[0034] like Figure 10 As shown, as an application embodiment of the present invention, the half-carrier frequency offset estimation method of the present invention is applied to a cellular comprehensive measurement system to perform coarse estimation of CP frequency offset.

[0035] 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.

[0036] Based on the current sampled baseband segment signal, the starting position of the OFDM symbol is obtained based on the CP (Pilot-Cost Interchange) signal, thus determining the position of the CP data. Coarse frequency offset estimation and compensation are then performed based on the CP time-domain data to ensure the residual frequency offset remains within the range of subsequent pilot-based frequency offset estimation. If the frequency offset error in the CP estimation is large, subsequent pilot frequency offset tracking fails, and the entire test result becomes unstable. Currently, many instrument systems experience unstable test performance when the frequency offset is near half a subcarrier due to excessively large CP frequency offset estimation errors. However, the method provided by this invention can achieve a range within [-1 / 2, 1 / 2]. 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.

[0037] 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 estimating half-carrier frequency offset in an OFDM system, characterized in that, Includes the following steps: S1: Baseband signal acquisition: Acquire and obtain the baseband signal from the receiver's RF digital input; S2: CP phase calculation: Based on the baseband signal, obtain time-domain CP data, and calculate the cross-correlation phase offset value of the time-domain samples based on the CP data; S3: Fuzzy judgment: Convert the cross-correlation phase offset value to a single-peak structure, and obtain the phase deviation of the single-peak structure. Then, the phase deviation is statistically analyzed. The risk coefficient for falling into the fuzzy region is determined. If the risk coefficient is greater than a set value, step S4 is executed; otherwise, step S5 is executed. The estimated range of the phase deviation for the CP time-domain sample is... ,in To determine the area, and The region is blurred. S4: Phase ambiguity transfer: The phase deviation falling into the ambiguity region is shifted by half a subcarrier offset and transferred to a defined region to obtain the deambigued phase deviation. ; S5: CP frequency offset estimation: based on the phase deviation after defuzzification. If the risk coefficient is less than the set value, calculate the statistical deviation, and then calculate the fractional octet frequency deviation. ; S6: Integer Frequency Offset Estimation: Calculate integer multiples of frequency offset ; S7: Final Frequency Offset Estimation: Based on fractional and integer multiples of the frequency offset, the final frequency offset estimate is obtained. , In step S3, the risk coefficient The calculation formula is: ,in, The total number of samples used in the phase deviation calculation. Phase deviation Less than the threshold The number of samples.

2. The method for estimating half-carrier frequency offset in an OFDM system according to claim 1, characterized in that: In step S2, after acquiring the baseband signal, 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 estimating half-carrier frequency offset in an OFDM system according to claim 1, characterized in that: In step S3, the process for handling fuzzy judgment is as follows: (1) Take the reference phase Calculate the absolute value of the difference between the CP time-domain sample phase offset and the reference phase, and perform a half-subcarrier interval offset on the center position to obtain the phase deviation. : ， After offset processing The distribution always exhibits a unimodal structure; (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. .

4. The method for estimating half-carrier frequency offset in an OFDM system according to claim 3, characterized in that: In step S4, the formula for phase fuzzy transfer is as follows: .

5. The method for estimating half-carrier frequency offset in an 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: ， in, This represents the width of a subcarrier in an OFDM system. t represents the statistical bias, which is the expected value of the cross-correlation phase in the CP time domain, and t represents the sample number.

6. The method for estimating half-carrier frequency offset in an OFDM system according to claim 5, characterized in that: In step S6, the integer multiples of the frequency offset are calculated using either the sequence correlation method or the PRB power offset method. .

7. A half-carrier frequency offset estimation system in an OFDM system, used to implement the half-carrier frequency offset estimation method in an OFDM system according to any one of claims 1-6, characterized in that, include: Baseband signal acquisition module: used to acquire and obtain baseband signals from the receiver's RF digital input; CP phase calculation module: used to obtain time-domain CP data based on the baseband signal, and calculate the cross-correlation phase offset value of the time-domain samples based on the CP data; The fuzziness determination module is used to convert the cross-correlation phase offset value into a single-peak structure, thereby obtaining the phase deviation of the single-peak structure. Then, the phase deviation is statistically analyzed. The risk coefficient of falling into the fuzzy region, where the estimated range of phase deviation for CP time-domain samples is... , To determine the area, and The region is blurred. Phase blur transfer module: Used to perform phase blur transfer on scenes falling into blur regions, obtaining the deblurred 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: used to calculate integer multiples of frequency offset. ; Final frequency offset estimation module: Used to obtain the final frequency offset estimate based on fractional and integer multiples of the frequency offset. .

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