Symbol synchronization and frequency offset estimation method and system in OFDM system based on CHU sequence

Abstract

The present invention discloses a method and system for symbol synchronization and frequency offset estimation in an OFDM system based on a CHU sequence. The method comprises: a transmitting end obtains a conjugate symmetric original sequence based on CHU sequence splicing, and generates a conjugate antisymmetric training sequence based on the conjugate symmetric original sequence; the training sequence is added to a data frame of a transmission data signal and transmitted in a data transmission channel; a receiving end receives a data signal including the training sequence, calculates correlation values ​​of different data positions of the signal using a Schmidt strategy, a Minn strategy, and a symmetric structure training sequence synchronization strategy, calculates corresponding timing metrics based on the correlation values, and calculates a comprehensive timing metric based on the timing metrics calculated by each strategy; the receiving end performs symbol synchronization in the OFDM system based on the comprehensive timing metric value, and performs frequency offset estimation based on the correlation values ​​of the symbol synchronization positions. The present invention can achieve joint symbol and frequency synchronization with a high main peak value, a low secondary peak value, and no peak platform problem.

Description

Technical Field

[0001] The present invention belongs to the technical field of OFDM system synchronization and frequency offset estimation, and relates to a method and system for symbol synchronization and frequency offset estimation in an OFDM system based on a CHU sequence. Background Art

[0002] OFDM (Orthogonal Frequency Division Multiplexing) systems have attracted widespread attention due to their ability to effectively combat frequency-selective fading and narrowband interference, as well as their high spectrum resource utilization. OFDM is a multicarrier modulation technique that converts high-speed data signals into lower-speed sub-data streams, which are then modulated onto each subchannel for transmission. The orthogonality between the subcarriers in the system allows for subchannel spectrum overlap, thereby improving spectrum resource utilization.

[0003] However, OFDM systems are highly sensitive to symbol timing errors and frequency offsets. OFDM symbols, composed of multiple subcarriers, are susceptible to synchronization errors. Symbol timing synchronization errors cause inter-symbol interference (ISI). Carrier frequency offsets destroy the orthogonality between subcarriers, causing ICI and degrading system performance. Therefore, high-precision symbol and frequency synchronization must be achieved at the receiver, making symbol timing and carrier frequency synchronization crucial technologies in OFDM systems.

[0004] Synchronization technology is a critical issue for any communication system, and the performance of the synchronization algorithm directly impacts the performance of the entire communication system. Without an accurate synchronization algorithm, reliable data transmission is impossible. The performance of the synchronization algorithm directly impacts whether the receiver can accurately demodulate and recover the original data. Symbol timing synchronization involves the receiver using the synchronization algorithm to estimate the position of the OFDM data frame and accurately locate the FFT window. Existing symbol timing synchronization algorithms are categorized as autocorrelation and cross-correlation. Cross-correlation timing synchronization utilizes a pre-shared local sequence between the transmitter and receiver, offering excellent noise immunity and achieving good timing synchronization. However, it is highly sensitive to carrier frequency offset. Autocorrelation timing synchronization is unaffected by frequency offset, as the repeated or conjugate data sequences involved in the correlation operation experience the same frequency offset. However, synchronization performance is significantly affected by noise. Due to the complex hardware implementation of the iterative operation of the cross-correlation timing synchronization method, existing communication systems often use the autocorrelation symbol frequency synchronization algorithm based on a training sequence.

[0005] The carrier frequency offset is caused by the inconsistency between the signal laser at the transmitting end and the local oscillator frequency at the receiving end. The deviation of the carrier frequency between the transmitter and the receiver is a key factor affecting the performance of the OFDM system. In a single-carrier communication system, the symbol synchronization performance affects the system transmission performance. The carrier frequency offset will only cause a certain attenuation and phase rotation to the received signal, which can be solved by equalization and other methods. For OFDM multi-carrier systems that require strict orthogonality between subcarriers, carrier offset will cause inter-carrier interference (ICI), which will have a serious impact on system performance. Since the orthogonality between subcarriers is lost, increasing the signal transmission power cannot significantly improve the performance of the system. Therefore, both single-carrier communication systems and OFDM communication systems require accurate synchronization. Classic symbol and frequency synchronization algorithms include the Schmidl algorithm, the Minn algorithm, the Park algorithm, etc. In order to achieve symbol and frequency synchronization of the OFDM system, the OFDM frame structure based on the autocorrelation symbol and frequency synchronization algorithm of the training sequence is as follows. Figure 1 As shown. The Schmidl algorithm realizes symbol frequency synchronization based on the training sequence. The training sequence structure is as follows Figure 2 As shown. This training sequence is composed of two identical sequences of length N / 2 in the time domain. The receiving end of the Schmidl algorithm calculates the correlation value of the OFDM signal by using a sliding window of length L. This window can slide over time to calculate the autocorrelation value and timing metric of the data signal at different positions. The symbol timing metric method proposed by Schmidl is obtained by calculating the correlation value of the left N / 2 sequence and the right N / 2 sequence of the training sequence. When the position of the sliding window is within the cyclic prefix, the timing metric reaches the maximum value, so a "platform" will appear, which will lead to inaccurate judgment of the timing synchronization position. Based on the training sequence with a repetitive structure, the Schmidll algorithm can use the autocorrelation value of the symbol synchronization position to estimate the fractional part of the frequency offset (FO), but the use of the Schmidll algorithm may lead to a large error in the frequency offset estimation. The method for frequency offset estimation based on the autocorrelation value of the timing synchronization position of the Schmidl algorithm is as shown in formula (1):

[0006]

[0007] is the frequency deviation value, angle(P Sch (n)) is the autocorrelation value P of the synchronization position n Sch (n) Angle.

[0008] The Schmidl symbol timing synchronization strategy has good reliability under low signal-to-noise ratio (SNR), but the presence of peak platforms in the timing metric can reduce symbol frequency synchronization accuracy. Minn addresses the peak platform issue by modifying the structure of the training sequence.

[0009] The training sequence structure used by the Minn algorithm is [AA-AA], such as Figure 3 As shown, A represents a sequence with a length of L=N / 4, which is generated by IFFT modulation of an N / 4-point PN sequence. The method proposed by Minn also obtains timing measurement by calculating the autocorrelation value of the training sequence. The Minn algorithm uses pseudo-random sequences with opposite relationships, which can make the result of the timing measurement form a maximum value, solving the peak platform problem of the Schmidl algorithm. However, due to the particularity of the training sequence structure, secondary peak interference is caused, which may cause misjudgment of the timing position. In addition, when the signal-to-noise ratio decreases and the training sequence is interfered with, the secondary peak peak in the timing measurement will be close to the main peak peak. The Minn algorithm solves the peak platform problem, but the secondary peak interferes with the main peak, resulting in errors in symbol synchronization, and the frequency offset estimation based on the autocorrelation value of the symbol synchronization position also has deviations. The method for frequency offset estimation based on the autocorrelation value of the timing synchronization position of the Minn algorithm is as shown in formula (2).

[0010]

[0011] is the frequency deviation value, angle(P Minn (n)) is the autocorrelation value P at the synchronization position n Minn (n) Angle.

[0012] In order to solve the above problems, Park et al. proposed a new symbol timing synchronization algorithm and designed a new training sequence structure, such as Figure 4 As shown. The new training sequence structure consists of four parts: C is the complex PN sequence obtained by IFFT modulation, and its length is N / 4; C* is the conjugate sequence of C, and its length is N / 4; D is the symmetric sequence of C, and its length is also N / 4. The left and right halves of the Park algorithm training sequence structure are symmetric sequences at their respective midpoints. Due to the structure of the training sequence, the correlation value drops rapidly when the sliding window deviates from the correct position. The Park algorithm solves the problem of secondary peaks in the Minn algorithm. When the signal-to-noise ratio decreases, the synchronization accuracy decreases, resulting in errors in symbol timing and corresponding frequency offset estimation.

[0013] In summary, among the synchronization algorithms of existing OFDM systems, the Schmidl algorithm is not accurate enough in judging the synchronization position due to the peak platform problem, which may affect the frequency offset estimation based on the autocorrelation value of the timing measurement peak position, resulting in deviations in the frequency offset estimation. The Minn algorithm solves the peak platform problem, but has the problem of high secondary peak value. Due to the interference of the secondary peak, the synchronization position may be misjudged, resulting in errors in the subsequent frequency offset estimation, affecting the accuracy of the frequency offset estimation. The main peak of the Park algorithm is lower, and there is no peak platform problem, which also solves the problem of high secondary peak value of the Minn algorithm. However, when the OSNR (optical signal-to-noise ratio) decreases, the peak value of the main peak of the timing measurement of the Park algorithm decreases rapidly, resulting in a decrease in judgment accuracy and errors in symbol frequency synchronization.

[0014] Prior art document 1 (CN113162882A) provides an autocorrelation OFDM symbol synchronization method based on a conjugate antisymmetric training sequence. By using the mirror sequence, conjugate sequence and opposite sequence of the complex PN sequence to set the training sequence structure, the symbol timing synchronization accuracy in the OFDM system in high OSNR scenarios is significantly improved. However, the synchronization accuracy is low in low OSNR scenarios. Summary of the Invention

[0015] In order to address the deficiencies in the prior art, the present invention provides a method and system for symbol synchronization and frequency offset estimation in an OFDM system based on a CHU sequence. Constant amplitude zero autocorrelation sequences, especially CHU sequences, have obvious constant amplitude, ideal autocorrelation, and good cross-correlation characteristics. The present invention upgrades the training sequence structure, symbol synchronization timing measurement, and frequency offset estimation, fully extracts the characteristics of the training sequence, improves the accuracy of symbol synchronization and frequency offset estimation in the OFDM system, and realizes the joint synchronization of symbols and frequencies with high main peak peak value, low secondary peak peak value, and no peak platform problem, which can accurately perform symbol synchronization and frequency offset estimation in wireless communication systems and optical communication systems.

[0016] The present invention adopts the following technical solutions.

[0017] The first aspect of the present invention proposes a method for symbol synchronization and frequency offset estimation in an OFDM system based on a CHU sequence, comprising:

[0018] The transmitter obtains a conjugate symmetric original sequence U based on the CHU sequence concatenation, and generates a conjugate antisymmetric training sequence based on the conjugate symmetric original sequence U;

[0019] Adding the training sequence to a data frame of a signal in an OFDM system, and transmitting the data signal including the training sequence in a data transmission channel;

[0020] The receiving end receives a data signal including a training sequence, and respectively uses a Schmidt strategy, a Minn strategy, and a symmetric structure training sequence synchronization strategy to calculate correlation values ​​of different data positions of the data signal based on the training sequence structure, calculates corresponding timing metric values ​​based on the correlation values, and calculates a comprehensive timing metric value based on the timing metric values ​​calculated by each strategy;

[0021] The receiving end performs symbol synchronization of the OFDM system based on the comprehensive timing measurement value and performs frequency offset estimation based on the correlation value of the symbol synchronization position.

[0022] Preferably, the expression for obtaining the conjugated symmetric original sequence U based on CHU sequence splicing is:

[0023] U=[CHU conj(CHU ')] (3)

[0024] Where U represents the conjugate symmetric original sequence of length N / 8, CHU represents the CHU sequence of N / 16 points, N is the training sequence length, CHU' represents the symmetric sequence of the CHU sequence, and conj represents the conjugate of the sequence;

[0025] The first variable in the CHU sequence is:

[0026]

[0027] Wherein, L is the length of the CHU sequence; r is an integer coprime with L; l = 0, 1…, L-1.

[0028] Preferably, a conjugate antisymmetric training sequence is generated based on the conjugate symmetric original sequence U:

[0029] [-U,-U,-U*,U*,-U*,U*,U,U];

[0030] Among them, -U is the opposite number sequence of U, U* is the conjugate sequence of U, and -U* is the conjugate opposite number sequence of U.

[0031] Preferably, the Schmidt strategy uses formula (8) to add a negative number and a conjugate operator to the training sequence position corresponding to the nth data position of the received data signal, and calculates the correlation value P of the sequence obtained by adding the negative number and the conjugate operator based on the repetitive structure of [U,U,U*,U*,U,U,U*,U*] Sch (n), and calculate the timing metric value M by combining formulas (9) and (10) Sch (n):

[0032]

[0033] in,

[0034] PSch (n) represents the correlation value of the nth data position in the data signal obtained using the Schmidt strategy;

[0035] Uc(m) and Uc(m+N / 2) are the m-th and m+N / 2-th data of the pre-shared local sequence [U,U,U*,U*,U*,U*,U,U];

[0036] r(n+m) and r(n+m+N / 2) respectively represent the n+m and n+m+N / 2th data in the training sequence position corresponding to the nth data position in the data signal received by the receiving end;

[0037] R Sch (n) is used for P Sch (n) coefficient for normalization;

[0038] M Sch (n) represents the timing metric value of the nth data position in the data signal obtained using the Schmidt strategy;

[0039] m is the relative position variable relative to n.

[0040] Preferably, the Minn strategy uses formula (11) to add a negative number and a conjugate operator to the training sequence position corresponding to the nth data position of the received data signal, and calculates the correlation value P of the sequence obtained by adding the negative number and the conjugate operator based on the cyclic repetition structure of [U,U,U,U,-U,-U,-U] Minn (n), and calculate the timing metric value M by combining formulas (12) and (13) Minn (n):

[0041]

[0042] Among them, P Minn (n) represents the correlation value of the nth data position in the data signal obtained using the Minn strategy;

[0043] Uc(m), Uc(m+(k-1)N / 8), Uc(m+N / 4+(k-1)N / 8), Uc(m+N / 2+(k-1)N / 8), and Uc(m+3N / 4+(k-1)N / 8) are the m-th, m+(k-1)N / 8, m+N / 4+(k-1)N / 8, m+N / 2+(k-1)N / 8, and m+3N / 4+(k-1)N / 8 data of the pre-shared local sequence [U,U,U*,U*,U*,U*,U,U];

[0044] r(n+m), r(n+m+(k-1)N / 8), r(n+m+N / 4+(k-1)N / 8), r(n+m+N / 2+(k-1)N / 8), and r(n+m+3N / 4+(k-1)N / 8) respectively represent the n+m, n+m+(k-1)N / 8, n+m+N / 4+(k-1)N / 8, and n+m+3N / 4+(k-1)N / 8 data in the training sequence position corresponding to the n-th data position in the data signal received by the receiving end;

[0045] R Minn (n) is used for P Minn (n) coefficient for normalization;

[0046] M Minn (n) represents the timing metric value of the nth data position in the data signal obtained using the Minn strategy;

[0047] k is the control variable, and m is the relative position variable relative to n.

[0048] Preferably, the symmetric structure training sequence synchronization strategy uses formula (5) to calculate the correlation value P of the sequence in the training sequence position corresponding to the nth data position of the received data signal based on the antisymmetric structure of [-U,-U,-U*,U*,-U*,U*,U,U] Sym (n), and calculate the timing metric value M by combining formulas (6) and (7) Sym (n):

[0049]

[0050] Among them, P Sym (n) represents the correlation value of the nth data position in the data signal obtained by using the symmetrical structure training sequence synchronization strategy;

[0051] Uc(m), Uc(N / 2+1-m), and Uc(m+N / 2) are the m-th, N / 2+1-m-th, and m+N / 2-th data of the local sequence [U,U,U*,U*,U*,U*,U] pre-shared between the transmitter and receiver;

[0052] r(n+1-m) and r(n+m) respectively represent the n+1-m and n+m-th data in the training sequence position corresponding to the n-th data position in the data signal received by the receiving end;

[0053] R Sym (n) is used for P Sym (n) coefficient for normalization;

[0054] M Sym(n) represents the timing metric value of the nth data position in the data signal obtained by using the symmetrical structure training sequence synchronization strategy;

[0055] k is the control variable, and m is the relative position variable relative to n.

[0056] Preferably, the formula for calculating the comprehensive timing metric value based on the timing metric values ​​calculated by each strategy is:

[0057]

[0058] Where M(n) is the comprehensive timing metric value;

[0059] M Sch (n) represents the timing metric value of the nth data position of the data signal obtained using the Schmidt strategy;

[0060] M Minn (n) represents the timing metric value of the nth data position of the data signal obtained using the Minn strategy;

[0061] M Sym (n+N / 2) represents the timing metric value of the n+N / 2th data position of the data signal obtained by adopting the symmetrical structure training sequence synchronization strategy.

[0062] Preferably, the formula for performing symbol synchronization based on the integrated timing metric value is:

[0063]

[0064] Where M(n) is the comprehensive timing metric value; is the symbol synchronization position, and argmax(·) indicates the maximum value.

[0065] Preferably, the frequency offset estimation is performed based on the correlation value of the symbol synchronization position, and the formula is as follows:

[0066]

[0067] in, is the frequency offset estimate;

[0068] Indicates the symbol synchronization position obtained using the Schmidl strategy The correlation value of

[0069] Indicates the symbol synchronization position obtained using the Minn strategy The correlation value of

[0070] Indicates the first The relevant value of each data position;

[0071] angle(·) represents the corresponding angle.

[0072] A second aspect of the present invention provides a symbol synchronization and frequency offset estimation system in an OFDM system based on a CHU sequence, comprising:

[0073] A sequence generation module is used for the transmitter to obtain a conjugate symmetric original sequence U based on the CHU sequence concatenation, and to generate a conjugate antisymmetric training sequence based on the conjugate symmetric original sequence U;

[0074] A data transmission module, configured to add the training sequence to a data frame of a signal in an OFDM system, wherein the data signal including the training sequence is transmitted in a data transmission channel;

[0075] a calculation module, configured to receive a data signal including a training sequence at a receiving end, calculate correlation values ​​of different data positions of the data signal based on the training sequence structure using a Schmidt strategy, a Minn strategy, and a symmetric structure training sequence synchronization strategy, calculate corresponding timing metric values ​​based on the correlation values, and calculate a comprehensive timing metric value based on the timing metric values ​​calculated by each strategy;

[0076] The synchronization module is used for performing symbol synchronization of the OFDM system based on the comprehensive timing measurement value at the receiving end, and performing frequency offset estimation based on the correlation value of the symbol synchronization position.

[0077] Compared with the prior art, the beneficial effects of the present invention include at least:

[0078] 1. Training sequence structure used for symbol synchronization and frequency offset estimation in OFDM systems based on CHU sequences:

[0079] The present invention obtains a conjugated symmetric original sequence U based on CHU sequence splicing, and generates a conjugated antisymmetric training sequence based on the conjugated symmetric original sequence U. By combining the original sequence U and the conjugated sequence and the opposite sequence of the original sequence, the training sequence structure is reasonably set. When the sliding window deviates from the correct position, the correlation decreases rapidly.

[0080] The training sequence structure of the present invention conforms to the characteristics of Schmidt and Minn cyclic repetition structures, as well as the characteristics of symmetrical training sequences. The proposed training sequence structure, combined with a corresponding timing metric strategy, eliminates interference from secondary peaks at ±N / 4 positions. When the symbol synchronization position of the OFDM system obtained by symbol synchronization is within the guard interval, the peak plateau effect is eliminated. When the signal-to-noise ratio decreases, the training sequence maintains autocorrelation performance, and the main peak is less affected by the reduced signal-to-noise ratio.

[0081] The present invention arranges the training sequence, and after the receiving end receives the training sequence, it converts the training sequence through an operator to achieve a training sequence that meets the training sequence structure characteristics of multiple classic algorithms. The characteristics of the training sequence can be fully extracted, and the accuracy of symbol synchronization can be improved, especially the synchronization accuracy in low OSNR scenarios.

[0082] 2. Calculate the correlation value and timing metric of the cross-correlation and auto-correlation combination corresponding to symbol synchronization based on the training sequence of the CHU sequence:

[0083] The present invention employs the Schmidt algorithm, the Minn algorithm, and the symmetrical structure training sequence synchronization strategy to calculate correlation values ​​for different signal data positions in the proposed training sequence. The corresponding timing metric values ​​are then calculated based on the correlation values. A composite timing metric value is then calculated based on the timing metric values ​​calculated by each strategy. This combines the advantages of multiple strategies and fully extracts the characteristics of the training sequence. Compared to strategies based on repetitive structure training sequences, such as the Schmidt algorithm and the Minn algorithm, the present invention achieves higher synchronization position determination accuracy at high OSNRs. Compared to synchronization strategies based on symmetrical structure training sequences, the present invention achieves higher synchronization position determination accuracy at low OSNRs.

[0084] The present invention inherits the advantages of the cross-correlation and autocorrelation symbol synchronization methods, has high accuracy in symbol synchronization and frequency deviation estimation, and is conducive to hardware implementation. The present invention inherits the high main peak peak value and strong anti-interference ability of the Minn algorithm and the Schmidl strategy at low OSNR, and inherits the advantages of the synchronization strategy based on the symmetrical structure training sequence at high OSNR symbol synchronization accuracy, low secondary peak peak value, and high main peak peak value; the present invention solves the problem of possible errors in the peak platform and frequency deviation of the Schmidl algorithm; solves the problem of errors in the secondary peak interference of the Minn algorithm and frequency deviation estimation; solves the problem of low symbol frequency synchronization accuracy of the synchronization strategy based on the symmetrical structure training sequence at low OSNR. Compared with the method of realizing symbol frequency synchronization based on a single timing metric calculation strategy, the present invention can more fully extract the characteristics of the training sequence and has higher symbol synchronization and frequency deviation estimation accuracy. Therefore, the application of the present invention can improve the comprehensive performance of the communication system.

[0085] 3. Frequency offset estimation based on the training sequence of the CHU sequence:

[0086] Multiple frequency offset estimates are obtained based on the phases of multiple correlation values ​​calculated using different correlation value calculation strategies for the training sequence, and the average value of the multiple frequency offset estimates is calculated to obtain a comprehensive frequency offset estimation value, thereby improving the frequency offset estimation accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0087] Figure 1 is the OFDM frame structure used for symbol synchronization;

[0088] Figure 2 is the training sequence structure of the Schmidl algorithm;

[0089] Figure 3 is the training sequence structure of the Minn algorithm;

[0090] Figure 4 is the training sequence structure of the Park algorithm;

[0091] Figure 5 The training sequence structure proposed by the present invention;

[0092] Figure 6 The present invention is a flowchart of a method for symbol synchronization and frequency offset estimation in an OFDM system based on a CHU sequence. DETAILED DESCRIPTION

[0093] To more clearly illustrate the purpose, technical solutions, and advantages of the present invention, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. The embodiments described in this application are only part of the embodiments of the present invention, not all of them. Based on the spirit of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0094] Embodiment 1 of the present invention provides a method for joint symbol and frequency synchronization in an OFDM system based on a CHU sequence, which specifically includes the following steps:

[0095] Step 1: The transmitter obtains a conjugate symmetric original sequence U based on the CHU sequence concatenation, and generates a conjugate antisymmetric training sequence based on the conjugate symmetric original sequence U;

[0096] In specific implementation, the single-carrier communication system is sensitive to symbol synchronization errors. The OFDM system is sensitive to symbol synchronization errors and frequency offsets. When there is a synchronization error or frequency offset, inter-carrier interference (ICI) or inter-symbol interference (ISI) will occur, resulting in reduced system performance. Therefore, it is very important for the communication system to maintain accurate synchronization. The training sequence used in the method proposed in the present invention is composed of the original number sequence U and the conjugate sequence and the opposite number sequence of U, and a conjugate symmetric sequence composed of the CHU sequence is used as the original number sequence U to perform symbol synchronization and frequency offset estimation, such as Figure 5 shown.

[0097] The training sequence proposed in the present invention consists of eight parts. U represents a sequence of length N / 8, generated by concatenating N / 16 CHU sequences. -U is the reciprocal sequence of U, U* is the conjugate sequence of U, and -U* is the reciprocal sequence of the conjugate sequence of U, i.e., a conjugate reciprocal sequence. The training sequence structure of the method proposed in the present invention is a conjugate antisymmetric sequence.

[0098] Figure 5 In the left half of the structure shown, the first and third N / 8-point sequences are symmetric; in the right half, the first and third N / 8-point sequences are antisymmetric; and in the right half, the first and second N / 8-point sequences are opposite. By using the original, conjugate, and opposite sequences of sequence U and properly configuring the training sequence structure, the correlation value of the training sequence drops rapidly when the sliding window deviates from its correct position. When the signal-to-noise ratio (SNR) of the optical fiber channel decreases, the training sequence maintains its correlation value, and the main peak is less affected by the reduced SNR.

[0099] Furthermore, the present invention uses the CHU sequence to conjugate the original symmetric sequence U as the original sequence of the training sequence structure used in the method proposed by the present invention. The expression of the U sequence is:

[0100] U=[CHU conj(CHU ')] (3)

[0101] Among them, the CHU sequence is an N / 16 point sequence, ' represents the symmetric operator of the sequence, and the function expression for generating the CHU sequence is,

[0102]

[0103] Wherein, L is the length of the CHU sequence; r is an integer coprime with L; l is a sequence value variable, l = 0, 1…, L-1.

[0104] Step 2: adding the training sequence to a data frame of a signal in an OFDM system, and transmitting the data signal including the training sequence in a data transmission channel;

[0105] Step 3: The receiving end receives a data signal including a training sequence, and calculates correlation values ​​of different data positions of the data signal based on the training sequence structure using the Schmidt strategy, the Minn strategy, and the symmetric structure training sequence synchronization strategy, respectively. Based on the correlation values, corresponding timing metrics are calculated, and a comprehensive timing metric is calculated based on the timing metrics calculated using the above strategies.

[0106] Further preferably, the present invention uses a symbol synchronization method and a timing metric calculation method combining cross-correlation and autocorrelation, specifically as follows:

[0107] The symmetric structure training sequence synchronization strategy uses formula (5) to calculate the correlation value P of the sequence in the training sequence position corresponding to the nth data position of the received data signal based on the antisymmetric structure of [-U,-U,-U*,U*,-U*,U*,U,U] Sym (n), and calculate the timing metric value M by combining formulas (6) and (7) Sym(n), as follows:

[0108]

[0109] Where Uc(n) is the nth data in the local sequence [U,U,U*,U*,U*,U*,U,U] pre-shared between the transmitter and receiver. Uc(m), Uc(N / 2+1-m), and Uc(m+N / 2) are the mth, N / 2+1-mth, and m+N / 2th data in the local sequence.

[0110] r(n) represents the nth signal data received, r(n+1-m) and r(n+m) represent the n+1-m and n+mth data received by the receiving end respectively.

[0111] P Sym (n) represents the correlation value of the nth data position of the signal obtained by adopting the symmetric structure training sequence synchronization strategy, which is obtained by the correlation value of the product of the left half sequence and the local sequence and the product of the right half sequence and the local sequence.

[0112] R Sym (n) represents half of the energy value of the sequence in the training sequence position corresponding to the nth data position of the signal obtained by using the symmetrical structure training sequence synchronization strategy, which is used for P Sym (n) coefficient for normalization;

[0113] M Sym (n) represents the timing metric value of the nth data position of the signal obtained by using the symmetrical structure training sequence synchronization strategy. The symbol position obtained by the timing metric value of the symmetrical structure training sequence synchronization strategy is the middle position of the training sequence.

[0114] Based on the above symmetric structure training sequence synchronization strategy, the correlation value P of the -N / 4 position of the symbol synchronization position Sym In (n), since the first and second parts of the training sequence are the same, and the third and fourth parts are opposite sequences, the correlation value calculation method based on formula (5) is obtained The value is lower.

[0115] If the cyclic prefix is ​​filled with signal data, based on the correlation value calculation method of formula (5), the signal data and the training sequence r(n+m), N / 4+1<=m<=N / 2 have no correlation, that is, The value of is low, and the correlation value and timing metric value of the -N / 4 position of the symbol synchronization position are low.

[0116] Based on the symmetric structure training sequence synchronization strategy, the correlation value P of the symbol synchronization position +N / 4 position SymIn (n), since the 5th and 6th parts of the training sequence are opposite sequences, and the 7th and 8th parts are the same, the correlation value calculation method based on formula (5) is obtained The value is lower.

[0117] In addition, the training sequence r(n+m), N / 4+1<=m<=N / 2 has no correlation with the signal data, and the correlation value calculation method based on formula (5) is obtained

[0118] The lower the value of , the lower the correlation value and timing metric value at the +N / 4 position of the symbol synchronization position. Due to the combination of the training sequence and the timing metric method, the correlation value at the ±N / 4 position of the symbol synchronization position is low, solving the problem of secondary peak interference at the ±N / 4 position in synchronization strategies based on symmetrical training sequences. Furthermore, due to the good cross-correlation of the CHU sequence, the symbol synchronization and timing metric values ​​at positions other than the ±N / 4 position of the symbol synchronization position are low.

[0119] Further preferably, when the Schmidl strategy or the Minn strategy is used to calculate the timing metric value of the received data signal, the sequence is converted into a training sequence structure of [U,U,U*,U*,U,U,U*,U*] or [U,U,U,U,-U,-U,-U,-U] by adding an opposite number or a conjugate operator to a specific interval of the training sequence position corresponding to the n-th data position of the received signal. This conforms to the training sequence structure of the Schmidl algorithm or the Minn algorithm. Therefore, the Schmidl and Minn timing metric calculation methods can be applied. Based on the Schmidl and Minn training sequence structures, a timing metric calculation method combining cross-correlation and autocorrelation is applied, as follows:

[0120] The Schmidt strategy uses formula (8) to add the opposite number and the conjugate operator to the training sequence position corresponding to the nth data position of the received data signal, and calculates the correlation value P of the sequence obtained by adding the opposite number and the conjugate operator based on the repeated structure of [U,U,U*,U*,U,U,U*,U*] Sch (n), and calculate the timing metric value M by combining formulas (9) and (10) Sch (n):

[0121]

[0122] The Minn strategy uses formula (11) to add the opposite number and the conjugate operator to the training sequence position corresponding to the nth data position of the received data signal, and calculates the correlation value P of the sequence obtained by adding the opposite number and the conjugate operator based on the cyclic repetition structure of [U,U,U,U,-U,-U,-U] Minn(n), and calculate the timing metric value M by combining formulas (12) and (13) Minn (n):

[0123]

[0124] The method proposed in the present invention calculates the timing metric based on the characteristics that the training sequence conforms to Schmidl, Minn and symmetric structure training sequence structures.

[0125] P Sch (n) or P Minn (n) represents the correlation value of the nth signal data position calculated by the timing metric strategy of the Schmidl algorithm or the Minn algorithm.

[0126] R Sch (n) and R Minn (n) is half of the sequence energy value in the training sequence position corresponding to the nth data position, is the coefficient used for normalization processing, and the correlation value P Sch (n) or P Minn (n) Through R Sch (n) or R Minn The symbol position obtained by the timing metric values ​​of the Schmidl strategy and the Minn strategy is the starting position of the training sequence.

[0127] M Sch (n), M Minn (n), M Sym (n) are the timing metrics of the nth data position obtained by the Schmidl strategy, Minn strategy, and symmetric structure training sequence strategy, respectively.

[0128] For the above Minn strategy, the correlation value P at the -N / 4 position of the symbol synchronization position is Minn In (n), since the product of the 3rd and 5th parts of the training sequence is equal to the product of the 4th and 6th parts, the correlation value calculation method based on formula (11) is obtained The value of is low. If the cyclic prefix is ​​filled with signal data, the signal data and the training sequence have no correlation, and the correlation value calculation method based on formula (11) is obtained The value of is low, and the correlation value and timing metric value of the -N / 4 position of the symbol synchronization position are low.

[0129] For the Minn strategy, the correlation value P at the +N / 4 position of the symbol synchronization position Minn In (n), since the product of the 3rd and 5th parts of the training sequence is equal to the product of the 4th and 6th parts, the correlation value calculation method based on formula (11) is obtained The value of is low. In addition, there is no correlation between the signal data and the training sequence. The correlation value calculation method based on formula (11) is obtained The lower the value of , the lower the correlation value and timing metric value at the +N / 4 position of the symbol synchronization position. Due to the combination of the training sequence and the timing metric method, the correlation value at the ±N / 4 position of the symbol synchronization position is low, solving the problem of secondary peak interference at the ±N / 4 position of the symbol synchronization position in the Minn strategy. In addition, due to the good cross-correlation properties of the CHU sequence, the symbol synchronization and timing metric values ​​at positions other than the ±N / 4 position of the symbol synchronization position are low.

[0130] In the classic Schmidl strategy, a part of the end of the training sequence is often used as the prefix of the data frame. For the training sequence structure and Schmidl strategy of this patent, when the OFDM symbol position obtained by symbol synchronization is within the protection interval, the obtained training sequence data is not a cyclic shift of the training sequence, eliminating the peak platform effect. In addition, the timing metric values ​​of the Schmidl, Minn and symmetric structure training sequence synchronization strategies that deviate from the correct symbol synchronization position are low, and the secondary peaks of the above strategies appear at different positions, so the mean amplitude of the timing metric of the above strategies that deviate from the correct symbol synchronization position is low. Near the correct symbol synchronization position, Schmidl, Minn and symmetric structure training sequence synchronization strategies have timing metrics of different shapes and higher values ​​of timing metrics, so the mean value of the timing metric of the above strategies is higher at the correct symbol synchronization position and there is no platform problem.

[0131] More preferably, in order to Sch (n), M Minn (n), M Sym (n) linear addition, it is necessary to consider that the symbol synchronization position obtained by different strategies is offset from the starting position of the training sequence. The symbol synchronization position of the Schmidl and Minn strategies is the starting position of the training sequence, and the symbol synchronization position obtained by the symbol synchronization strategy based on the symmetric structure training sequence is the middle position of the training sequence. Therefore, in order to linearly add the timing metrics of different strategies, when using the timing metric M of the symmetric structure training sequence Sym (n), the timing metric of n+N / 2 data positions needs to be used, that is, M Sym (n+N / 2), align the synchronization position.

[0132] The comprehensive timing metric M(n) is given by M Sch (n), M Minn (n), M Sym The arithmetic mean of (n+N / 2) is obtained as follows:

[0133]

[0134] Where M(n) is the comprehensive timing metric value;

[0135] M Sch (n) represents the timing metric value of the nth data position in the data signal obtained using the Schmidt strategy;

[0136] M Minn (n) represents the timing metric value of the nth data position in the data signal obtained using the Minn strategy;

[0137] M Sym (n+N / 2) represents the timing metric value of the n+N / 2th data position in the data signal obtained by adopting the symmetrical structure training sequence synchronization strategy.

[0138] Step 4: The receiver performs symbol synchronization of the OFDM system based on the integrated timing metric value and estimates the frequency offset based on the correlation value of the symbol synchronization position, as follows:

[0139]

[0140] Where M(n) is the comprehensive timing metric value; is the symbol synchronization position, and argmax(·) indicates the maximum value.

[0141] Further preferably, the method further comprises: performing frequency offset estimation based on a correlation value of the symbol synchronization position:

[0142] The training sequence structure proposed by the present invention conforms to the characteristics of Schmidl, Minn and symmetric structure training sequence structures. The frequency offset estimation of the present invention The estimated value that can be calculated using the corresponding frequency offset estimation strategy and The frequency offset estimation obtained by different strategies is defined as follows:

[0143]

[0144] in, is the frequency offset estimate;

[0145] Indicates the symbol synchronization position obtained using the Schmidl strategy The correlation value of

[0146] Indicates the symbol synchronization position obtained using the Minn strategy The correlation value of

[0147] Represents the correlation value of the symmetrical structure training sequence, that is, the first The relevant value of each data location. and The range is [-ππ], the fractional part of the frequency offset estimation method proposed in the present invention The range is [-0.5 0.5].

[0148] In summary, if Figure 6 As shown, the implementation steps of the method proposed in the present invention for symbol synchronization and frequency offset estimation are as follows:

[0149] 1) Use formula (4) to generate an N / 16-point CHU sequence.

[0150] 2) Use formula (3) to splice the CHU sequence into the conjugate symmetric original sequence U.

[0151] 3) Based on the sequence U, Figure 5 The training sequence shown consists of 8 parts, where U represents a sequence of length N / 8. -U is the reciprocal sequence of U, U* is the conjugate sequence of U, and -U* is the reciprocal conjugate sequence of U. The structure of the above training sequence is a conjugate antisymmetric sequence.

[0152] 4) The sending end adds the training sequence to the data frame, and the data frame is transmitted in the data transmission channel.

[0153] 5) The receiving end receives the data frame including the training sequence.

[0154] When calculating the timing metric value of a received data signal, the sequence is converted to [U,U,-U,-U*,U*,-U*,U*,U,U] or [U,U,U,U,U,-U,-U,-U,-U] by adding an opposite number or a conjugate operator to a specific interval of the expected training sequence [-U,-U,-U,-U*,U*,-U*,U*], conforming to the training sequence structure of the Schmidl algorithm or the Minn algorithm. Therefore, the method of the present invention can calculate correlation values ​​and timing metrics using a timing metric method that combines cross-correlation and autocorrelation based on the Schmidl strategy, the Minn strategy, and the synchronization strategy of the symmetrically structured training sequence.

[0155] 6) The receiving end uses a timing measurement method combining cross-correlation and autocorrelation based on the training sequence structure of the Schmidl strategy, and calculates the correlation value and timing measurement value of different data positions of the data signal based on formulas (8)-(10).

[0156] 7) The receiving end uses the timing measurement method combining cross-correlation and autocorrelation based on the training sequence structure of the Minn strategy to calculate the correlation value and timing measurement value of different data positions of the data signal based on formulas (11)-(13).

[0157] 8) The receiving end uses a timing measurement method combining cross-correlation and autocorrelation based on the synchronization strategy of the symmetrical structure training sequence, and calculates the correlation value and timing measurement value of different data positions of the data signal based on formulas (5)-(7).

[0158] 9) The receiving end calculates the comprehensive timing measurement value of the method of the present invention based on formula (14).

[0159] 10) The receiving end performs symbol synchronization based on the timing measurement of the signal, and the symbol synchronization position From formula (15), we can see that the maximum position of the timing metric value is the position of the training sequence. Based on the position of the training sequence, we can get the synchronization position of the data frame and achieve symbol synchronization of the data signal.

[0160] 11) The receiving end estimates the frequency offset based on the correlation value of the symbol synchronization position using formula (20).

[0161] Embodiment 2 of the present invention provides a symbol synchronization and frequency offset estimation system in an OFDM system based on a CHU sequence, including:

[0162] A sequence generation module is used for the transmitter to obtain a conjugate symmetric original sequence U based on the CHU sequence concatenation, and to generate a conjugate antisymmetric training sequence based on the conjugate symmetric original sequence U;

[0163] A data transmission module, configured to add the training sequence to a data frame of a signal in an OFDM system, wherein the data signal including the training sequence is transmitted in a data transmission channel;

[0164] a calculation module, configured to receive a data signal including a training sequence at a receiving end, calculate correlation values ​​of different data positions of the data signal based on the training sequence structure using a Schmidt strategy, a Minn strategy, and a symmetric structure training sequence synchronization strategy, calculate corresponding timing metric values ​​based on the correlation values, and calculate a comprehensive timing metric value based on the timing metric values ​​calculated by each strategy;

[0165] The synchronization module is used for performing symbol synchronization of the OFDM system based on the comprehensive timing measurement value at the receiving end, and performing frequency offset estimation based on the correlation value of the symbol synchronization position.

[0166] Embodiment 3 of the present invention provides a terminal, including a processor and a storage medium; the storage medium is used to store instructions; the processor operates based on the instructions to execute the steps of the method.

[0167] Embodiment 4 of the present invention provides a computer-readable storage medium having a computer program stored thereon, and the stored program implements the steps of the method when executed by a processor.

[0168] Compared with the prior art, the beneficial effects of the present invention include at least:

[0169] 1. Training sequence structure used for symbol synchronization and frequency offset estimation in OFDM systems based on CHU sequences:

[0170] The present invention obtains a conjugate symmetric original sequence U based on CHU sequence splicing, and generates a conjugate antisymmetric training sequence based on the conjugate symmetric original sequence U. By combining the original sequence U and its conjugate sequence and inverse sequence, a reasonable training sequence structure is set. In this way, the correlation values ​​of different parts of the training sequence decrease rapidly when the sliding window deviates from the correct position.

[0171] The training sequence structure of the present invention conforms to the characteristics of Schmidt and Minn cyclic repetition structures, as well as the characteristics of symmetrical training sequences. The proposed training sequence structure, combined with a corresponding timing metric strategy, eliminates interference from secondary peaks at ±N / 4 positions. When the OFDM symbol synchronization position obtained by symbol synchronization is within the guard interval, the peak plateau effect is eliminated. When the signal-to-noise ratio decreases, the training sequence maintains autocorrelation performance, and the main peak is less affected by the reduced signal-to-noise ratio.

[0172] After receiving the training sequence, the receiving end of the present invention converts the training sequence through an operator to achieve a training sequence that meets the training sequence structure characteristics of multiple classic algorithms. It can fully extract the characteristics of the training sequence and improve the accuracy of symbol synchronization, especially the synchronization accuracy in low OSNR scenarios.

[0173] 2. Calculate the correlation value and timing metric of the cross-correlation and auto-correlation combination corresponding to symbol synchronization based on the training sequence of the CHU sequence:

[0174] The present invention uses the Schmidt strategy, the Minn strategy, and the symmetrical structure training sequence synchronization strategy to calculate correlation values ​​at different data positions in the proposed training sequence. The corresponding timing metrics are then calculated based on the correlation values. A combined timing metric is then calculated based on the timing metrics calculated by each strategy. By combining the advantages of multiple strategies, the characteristics of the training sequence can be fully extracted. Compared with strategies such as Schmidt and Minn, which are based on repetitive structure training sequences, the present invention achieves higher synchronization accuracy at high OSNRs and higher synchronization accuracy at low OSNRs compared to strategies based on symmetrical structure training sequences.

[0175] The present invention inherits the advantages of the cross-correlation and autocorrelation symbol synchronization methods, has high symbol synchronization accuracy, and is conducive to hardware implementation.

[0176] The present invention inherits the advantages of the Minn and Schmidl strategies, which have high main peak values ​​and strong anti-interference capabilities at low OSNRs, and inherits the advantages of the symmetrical structure training sequence synchronization strategy, which has high symbol synchronization accuracy, low secondary peak values, and high main peak values ​​at high OSNRs. The present invention solves the problem of large errors in peak platform and frequency offset estimation in the Schmidl strategy; solves the problem of errors in secondary peak interference with main peak and frequency offset estimation in the Minn strategy; and solves the problem of low symbol frequency synchronization accuracy at low OSNRs in the symmetrical structure training sequence synchronization strategy. Compared with symbol synchronization strategies based on a single timing metric calculation method, the present invention can more fully extract the characteristics of the training sequence and has higher symbol synchronization accuracy. Therefore, the application of the present invention can improve the overall performance of the communication system.

[0177] 3. Frequency offset estimation based on the training sequence of the CHU sequence:

[0178] Multiple frequency offset estimates are obtained based on multiple correlation values ​​calculated using different correlation value calculation strategies for the training sequence, and the average value of the multiple frequency offset estimates is calculated to obtain a comprehensive frequency offset estimate, thereby improving the accuracy of the frequency offset estimation.

[0179] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention shall fall within the scope of protection of the claims of the present invention.

Claims

1. A method for symbol synchronization and frequency offset estimation in an OFDM system based on a CHU sequence, characterized in that: include: The transmitter obtains a conjugate symmetric original sequence U based on the CHU sequence concatenation, and generates a conjugate antisymmetric training sequence based on the conjugate symmetric original sequence U; Adding the training sequence to a data frame of a signal in an OFDM system, and transmitting the data signal including the training sequence in a data transmission channel; The receiving end receives a data signal including a training sequence, and respectively uses a Schmidt strategy, a Minn strategy, and a symmetric structure training sequence synchronization strategy to calculate correlation values ​​of different data positions of the data signal based on the training sequence structure, calculates corresponding timing metric values ​​based on the correlation values, and calculates a comprehensive timing metric value based on the timing metric values ​​calculated by each strategy; The receiver performs symbol synchronization of the OFDM system based on the integrated timing metric value and frequency offset estimation based on the correlation value of the symbol synchronization position; The frequency offset estimation is performed based on the correlation value of the symbol synchronization position, and the formula is as follows: in, is the frequency offset estimate; Indicates the symbol synchronization position obtained using the Schmidl strategy The correlation value of Indicates the symbol synchronization position obtained using the Minn strategy The correlation value of Indicates the first The correlation value of each data position; angle(·) represents the corresponding angle; N is the training sequence length.

2. The method for symbol synchronization and frequency offset estimation in an OFDM system based on a CHU sequence according to claim 1, wherein: The expression of the conjugated symmetric original sequence U obtained by splicing the CHU sequence is: U=[CHU conj(CHU')] (3) Where U represents the conjugate symmetric original sequence of length N / 8, CHU represents the CHU sequence of N / 16 points, N is the training sequence length, CHU' represents the symmetric sequence of the CHU sequence, and conj represents the conjugate of the sequence; The first variable in the CHU sequence is: Wherein, L is the length of the CHU sequence; r is an integer coprime with L; l = 0, 1…, L-1.

3. The method for symbol synchronization and frequency offset estimation in an OFDM system based on a CHU sequence according to claim 2, wherein: Generate a conjugate antisymmetric training sequence based on the conjugate symmetric original sequence U: [-U,-U,-U*,U*,-U*,U*,U,U]; Among them, -U is the opposite number sequence of U, U* is the conjugate sequence of U, and -U* is the conjugate opposite number sequence of U.

4. The method for symbol synchronization and frequency offset estimation in an OFDM system based on a CHU sequence according to claim 3, wherein: The Schmidt strategy uses formula (8) to add the opposite number and the conjugate operator to the training sequence position corresponding to the nth data position of the received data signal, and calculates the correlation value P of the sequence obtained by adding the opposite number and the conjugate operator based on the repeated structure of [U,U,U*,U*,U,U,U*,U*] Sch (n), and calculate the timing metric value M by combining formulas (9) and (10) Sch (n): in, P Sch (n) represents the correlation value of the nth data position in the data signal obtained using the Schmidt strategy; Uc(m) and Uc(m+N / 2) are the m-th and m+N / 2-th data of the pre-shared local sequence [U,U,U*,U*,U*,U*,U,U]; r(n+m) and r(n+m+N / 2) respectively represent the n+m and n+m+N / 2th data in the training sequence position corresponding to the nth data position in the data signal received by the receiving end; R Sch (n) is used for P Sch (n) coefficient for normalization; M Sch (n) represents the timing metric value of the nth data position in the data signal obtained using the Schmidt strategy; m is the relative position variable relative to n.

5. The method for symbol synchronization and frequency offset estimation in an OFDM system based on a CHU sequence according to claim 3, wherein: The Minn strategy uses formula (11) to add the opposite number and the conjugate operator to the training sequence position corresponding to the nth data position of the received data signal, and calculates the correlation value P of the sequence obtained by adding the opposite number and the conjugate operator based on the cyclic repetition structure of [U,U,U,U,-U,-U,-U] Minn (n), and calculate the timing metric value M by combining formulas (12) and (13) Minn (n): Among them, P Minn (n) represents the correlation value of the nth data position in the data signal obtained using the Minn strategy; Uc(m), Uc(m+(k-1)N / 8), Uc(m+N / 4+(k-1)N / 8), Uc(m+N / 2+(k-1)N / 8), and Uc(m+3N / 4+(k-1)N / 8) are the m-th, m+(k-1)N / 8, m+N / 4+(k-1)N / 8, m+N / 2+(k-1)N / 8, and m+3N / 4+(k-1)N / 8 data of the pre-shared local sequence [U,U,U*,U*,U*,U*,U,U]; r(n+m), r(n+m+(k-1)N / 8), r(n+m+N / 4+(k-1)N / 8), r(n+m+N / 2+(k-1)N / 8) and r(n+m+3N / 4+(k-1)N / 8) represent the n+m and n+mth positions of the training sequence corresponding to the nth data position in the data signal received by the receiving end. n+m+(k-1)N / 8, n+m+N / 4+(k-1)N / 8, n+m+N / 2+(k-1)N / 8, n+m+3N / 4+(k-1)N / 8 data; R Minn (n) is used for P Minn (n) coefficient for normalization; M Minn (n) represents the timing metric value of the nth data position in the data signal obtained using the Minn strategy; k is the control variable, and m is the relative position variable relative to n.

6. The method for symbol synchronization and frequency offset estimation in an OFDM system based on a CHU sequence according to claim 3, wherein: The symmetric structure training sequence synchronization strategy uses formula (5) to calculate the correlation value P of the sequence in the training sequence position corresponding to the nth data position of the received data signal based on the antisymmetric structure of [-U,-U,-U*,U*,-U*,U*,U,U] Sym (n), and calculate the timing metric value M by combining formulas (6) and (7) Sym (n): Among them, P Sym (n) represents the correlation value of the nth data position in the data signal obtained by using the symmetrical structure training sequence synchronization strategy; Uc(N / 2+1-m) and Uc(m+N / 2) are the N / 2+1-m and m+N / 2th data of the local sequence [U,U,U*,U*,U*,U*,U] pre-shared between the transmitter and receiver; r(n+1-m) and r(n+m) respectively represent the n+1-m and n+m-th data in the training sequence position corresponding to the n-th data position in the data signal received by the receiving end; R Sym (n) is used for P Sym (n) coefficient for normalization; M Sym (n) represents the timing metric value of the nth data position in the data signal obtained by using the symmetrical structure training sequence synchronization strategy; m is the relative position variable relative to n.

7. The method for symbol synchronization and frequency offset estimation in an OFDM system based on a CHU sequence according to claim 1, wherein: The formula for calculating the comprehensive timing metric value based on the timing metric values ​​calculated by each strategy is: Where M(n) is the comprehensive timing metric value; M Sch (n) represents the timing metric value of the nth data position of the data signal obtained using the Schmidt strategy; M Minn (n) represents the timing metric value of the nth data position of the data signal obtained using the Minn strategy; M Sym (n+N / 2) represents the timing metric value of the n+N / 2th data position of the data signal obtained by adopting the symmetrical structure training sequence synchronization strategy.

8. The method for symbol synchronization and frequency offset estimation in an OFDM system based on a CHU sequence according to claim 1, wherein: The formula for symbol synchronization based on the integrated timing metric value is: Where M(n) is the comprehensive timing metric value; is the symbol synchronization position, and argmax(·) indicates the maximum value.

9. A symbol synchronization and frequency offset estimation system in an OFDM system based on a CHU sequence, using the method according to any one of claims 1 to 8, characterized in that: The system comprises: A sequence generation module is used for the transmitter to obtain a conjugate symmetric original sequence U based on the CHU sequence concatenation, and to generate a conjugate antisymmetric training sequence based on the conjugate symmetric original sequence U; A data transmission module, configured to add the training sequence to a data frame of a signal in an OFDM system, wherein the data signal including the training sequence is transmitted in a data transmission channel; a calculation module, configured to receive a data signal including a training sequence at a receiving end, calculate correlation values ​​of different data positions of the data signal based on the training sequence structure using a Schmidt strategy, a Minn strategy, and a symmetric structure training sequence synchronization strategy, calculate corresponding timing metric values ​​based on the correlation values, and calculate a comprehensive timing metric value based on the timing metric values ​​calculated by each strategy; The synchronization module is used for performing symbol synchronization of the OFDM system based on the comprehensive timing measurement value at the receiving end, and performing frequency offset estimation based on the correlation value of the symbol synchronization position.

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