CN113162882B - Self-correlation OFDM symbol synchronization method based on conjugate antisymmetric training sequence - Google Patents
Self-correlation OFDM symbol synchronization method based on conjugate antisymmetric training sequence Download PDFInfo
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Abstract
The application discloses an autocorrelation OFDM symbol synchronization method based on a conjugate antisymmetric training sequence, which comprises the steps of carrying out IFFT on a complex PN sequence to generate a sequence U; generating a training sequence according to the sequence U; the transmitting end adds the training sequence into the data frame; the data frame is transmitted in a data transmission channel; a receiving end receives a data frame comprising a training sequence; the receiving end calculates the signal autocorrelation value; the receiving end calculates 1/2 value of the training sequence energy value; the receiving end normalizes the signal autocorrelation value by using the 1/2 value of the training sequence energy value to obtain a normalized value; and the receiving end carries out OFDM symbol synchronization according to the normalization value. The invention reasonably sets the training sequence structure by using the mirror sequence, the conjugate sequence and the opposite number sequence of the complex PN sequence, and improves the symbol timing synchronization precision and the optical signal transmission performance in the OFDM system.
Description
Technical Field
The invention belongs to the technical field of OFDM symbol timing synchronization, and relates to an autocorrelation OFDM symbol synchronization method based on a conjugate antisymmetric training sequence.
Background
An Orthogonal Frequency Division Multiplexing (OFDM) technique is proposed to maximize the transmission rate of a system and minimize Inter-carrier Interference (ICI) and Inter-Symbol Interference (ISI) caused by a Frequency selective channel. OFDM has several advantages over single carrier modulation, including the characteristics of resistance to frequency selective fading channels, simple and effective equalization, scalable high-speed transmission capability, efficient spectrum utilization, flexibility in subcarrier allocation, and adaptivity to carrier modulation.
In the OFDM system, IFFT (Inverse Fast Fourier Transform) and FFT (Fast Fourier Transform) are basic functions required for modulation and demodulation by a transmitter and a receiver, and in order to perform FFT modulation correctly on a receiving side of the system, it is necessary to sample transmitted OFDM symbols accurately, and the receiving side needs a function of symbol timing synchronization. The starting position of the OFDM symbol is judged in real time, so that the OFDM system can obtain a more accurate sampling value. In the existing OFDM system symbol timing synchronization algorithm, the initial position of an OFDM symbol is not accurately judged due to the problem of a peak platform in part of algorithms, and the symbol timing position is judged incorrectly due to a secondary peak in some algorithms.
Synchronization is a very important process for OFDM systems, and symbol timing synchronization maintains the orthogonality of subcarriers in OFDM. The purpose of symbol timing synchronization is to correctly determine the correct start position of the received OFDM symbol, i.e. the start position of the FFT window. The position of the FFT window is wrong, so that the orthogonality among the subcarriers is damaged, intersymbol interference is caused, and the transmission performance of the system is influenced. In order to implement OFDM symbol synchronization, the OFDM frame structure of the autocorrelation symbol synchronization algorithm based on the training sequence is shown in fig. 1.
The symbol timing synchronization algorithm of the existing OFDM system is introduced as follows:
1.1Schmidl & Cox algorithm
The Schmidl & Cox algorithm is a synchronization method based on a training sequence, which can be used for symbol timing synchronization, and the structure of the training sequence is shown in fig. 2. This training sequence is composed of two identical sequences of length N/2 in the time domain and remains unchanged after passing through the channel.
The algorithm transmits PN sequences on even carriers and zeros on odd carriers, so that two identical sequences are generated by IFFT conversion to the time domain. Schmidl proposes to perform symbol timing synchronization by using a sliding autocorrelation algorithm, and a symbol timing metric is obtained by calculating correlation values of a left N/2 sequence and a right N/2 sequence of a training sequence. The Schmidl & Cox algorithm calculates the correlation value of the OFDM signal at the receiving end by using a sliding window of length L. This window may slide over time, searching the left half of the training symbols in a correlated manner. The algorithm divides the sliding autocorrelation value by the right half symbol energy value to derive a timing metric. When the position of the sliding window is within the cyclic prefix, the timing metric gets a maximum value, and thus a "plateau" occurs, which may result in an inaccurate determination of the starting position of the OFDM symbol.
1.2Minn Algorithm
Although the Schmidl & Cox symbol timing synchronization algorithm has good reliability under a low Signal-to-Noise Ratio (SNR), the determination of the start position of the OFDM symbol is not accurate enough due to the existence of a correlation peak platform of timing metrics. Minn corrects the peak-to-plateau problem by modifying the structure of the training sequence, the new training symbol structure is AA-base:Sub>A, as shown in fig. 3,base:Sub>A representsbase:Sub>A sequence of length L = N/4, which is generated by IFFT modulation of an N/4 point PN sequence. The method proposed by Minn also obtains the timing metric by calculating the autocorrelation value of the training sequence loop structure. The Minn algorithm uses a pseudo-random sequence with an inverse relation, so that a timing measurement result can form a maximum value, and the problem of a peak platform in the Schmidl algorithm is solved. However, due to the particularity of the training sequence structure, a secondary peak is also brought beside the main peak of the timing metric, which can cause misjudgment on the timing position. In addition, when the signal-to-noise ratio of the signal is reduced or intersymbol crosstalk exists in signal transmission, the training sequence is interfered, and the secondary peak value is close to the main peak.
1.3Park algorithm
To solve the above problem, park et al propose a new symbol timing synchronization algorithm, which specially designs a new training sequence structure, as shown in fig. 4.
The new training sequence structure is composed of 4 parts, C is that PN sequence is obtained by IFFT modulation, its length is N/4; c is a conjugate sequence of C, and the length is N/4; d and C are mirror symmetry, and the length is also N/4. The left half part and the right half part of the structure of the Park algorithm training sequence are in mirror symmetry at respective middle points, and the first N/4 point sequence and the third N/4 point sequence are conjugate sequences, so that when the sliding window deviates from a correct position, a correlation value quickly falls down. Although the Park algorithm solves the problem of secondary peaks of the Minn algorithm, when the signal-to-noise ratio of a signal is reduced, the peak value of a main peak is lower. In addition, compared with a low-order modulation mode, the high-order QAM has wider application in an OFDM system due to high utilization rate of a system frequency band. However, as the modulation order increases, the euclidean distance between adjacent constellation points becomes significantly smaller, the anti-interference capability of the system is sharply reduced, and the application of the symbol synchronization algorithm is limited.
The Schmidl & Cox algorithm described above suffers from a peak-plateau problem; the Minn algorithm solves the problem of peak value platform, but the Minn algorithm has the problem of high secondary peak value; the Park algorithm does not have the problem of peak value platform, and also solves the problem that the Minn algorithm has high secondary peak value, but the Park algorithm has low main peak value.
Disclosure of Invention
In order to solve the defects in the prior art, the self-correlation OFDM symbol synchronization method based on the conjugate antisymmetric training sequence is provided, and the core lies in a training sequence structure and a symbol synchronization timing measurement method, and is a symbol timing synchronization technology which has the advantages of no peak platform problem, low secondary peak value and high main peak value.
In order to achieve the above purpose, the invention adopts the following technical scheme:
an autocorrelation OFDM symbol synchronization method based on a conjugate antisymmetric training sequence comprises the following steps:
step 1, performing IFFT on a complex PN sequence to generate a sequence U;
step 3, the transmitting end adds the training sequence into the data frame;
step 5, the receiving end receives a data frame comprising a training sequence;
step 6, the receiving end calculates the signal autocorrelation value P (n);
step 7, the receiving end calculates the 1/2 value R (n) of the training sequence energy value;
step 8, the receiving end normalizes the signal autocorrelation value P (n) by utilizing R (n) to obtain a normalized value M (n);
and 9, the receiving end carries out OFDM symbol synchronization according to the M (n).
The invention further comprises the following preferred embodiments:
preferably, in step 2, the training sequence generated by the sequence U consists of 8 partial sequences:
in turn is
U、U、-U'、U'、-U*、U*、-(U')*、-(U')*；
N is the length of the training sequence; u' is a mirror symmetric sequence of U; -U' is the inverse of the mirror symmetric sequence of U; u is a conjugated sequence of U; -U is the sequence of the inverse of the conjugate sequence of U; - (U ') is the sequence of the opposite of (U '), (U ') is the conjugate of the mirror symmetric sequence of U.
Preferably, in step 6, the signal autocorrelation value P (n) is calculated according to formula (1):
r (N) represents the nth signal data received, and N is the training sequence length.
Preferably, in step 7, R (n) is calculated according to formula (2):
preferably, in step 8, the signal autocorrelation value P (n) is normalized according to formula (3):
M(n)＝|P(n)| 2 /R 2 (n) (3)。
preferably, in step 9, the OFDM symbol synchronization position
Is obtained by the following formula:
the beneficial effect that this application reached:
1. the self-correlation OFDM symbol synchronization method based on the training sequence reasonably sets the training sequence structure by using the mirror sequence, the conjugate sequence and the opposite number sequence of the complex PN sequence, and reduces the correlation between the training sequence and the training sequence delay sequence.
2. The training sequence is a conjugate antisymmetric sequence, when the signal-to-noise ratio of an optical signal is reduced, the training sequence can keep autocorrelation performance, the influence of the reduction of the signal-to-noise ratio of the optical signal on the main peak value is low, and the method can accurately perform OFDM symbol synchronization.
3. By the method and the device, the symbol timing synchronization precision and the optical signal transmission performance in the OFDM system can be improved.
4. Compared with the Schmidl & Cox algorithm, the method solves the problem of a peak platform; the secondary peak value is lower relative to the Minn algorithm; the main peak value is higher relative to the Park algorithm.
Drawings
Fig. 1 is a schematic diagram of an OFDM frame structure for symbol synchronization;
FIG. 2 is a schematic diagram of the training sequence structure of the Schmidl & Cox algorithm;
FIG. 3 is a schematic diagram of a training sequence structure of the Minn algorithm;
FIG. 4 is a schematic diagram of a training sequence structure of the Park algorithm;
FIG. 5 is a diagram illustrating the structure of a training sequence of the method of the present invention;
fig. 6 is a flow chart of the training sequence based autocorrelation OFDM symbol synchronization method of the present invention.
Detailed Description
The present application is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present application is not limited thereby.
As shown in fig. 6, an autocorrelation OFDM symbol synchronization method based on a conjugated antisymmetric training sequence of the present application includes the following steps:
step 1, performing IFFT on a complex PN sequence to generate a sequence U;
OFDM systems are very sensitive to synchronization errors, which, when present, can generate inter-carrier interference (ICI) and inter-symbol interference (ISI), resulting in reduced system performance, and thus it is very important for OFDM systems to maintain accurate synchronization. The Schmidl & Cox algorithm can cause the inaccurate judgment of the initial position of the OFDM symbol due to the problem of a peak platform; the peak value height of the secondary peak of the Minn algorithm may make an error judgment on the symbol timing position; when the signal-to-noise ratio of the signal is reduced, the main peak of the Park algorithm is reduced, and the judgment error of the symbol timing position is increased. The invention provides a symbol synchronization method based on a conjugate sequence, a phase reversal sequence and a mirror sequence of a PN sequence, which is an autocorrelation OFDM symbol synchronization method based on a training sequence, and the problems are considered for the selection of the training sequence: (1) autocorrelation of training sequence: the ideal autocorrelation performance is that the autocorrelation value of the sequence is 1, and the autocorrelation value of the delayed sequence of the sequence is 0. (2) length of training sequence: generally, the longer the training sequence is, the higher the computation complexity is, the better the synchronization performance is, so a balance between the algorithm complexity and the synchronization performance is needed. (3) position of training sequence construction: constructing a training sequence in a time domain, wherein the sequence is subjected to IFFT (inverse fast Fourier transform), and the sequence has good autocorrelation performance; (4) When the signal-to-noise ratio of the signal is reduced, the training sequence can keep the autocorrelation performance. The training sequence structure of the present invention is shown in FIG. 5.
According to fig. 5, the training sequence structure of the present invention is composed of 8 parts, U represents a sequence with a length of L = N/8, which is generated by IFFT modulating an N/8-point complex PN sequence, and N is the length of the training sequence;
-U is the inverse of U, U' is the mirror symmetric sequence of U, and U is the conjugate sequence of U. -U 'is the sequence of the inverse of the mirror-symmetric sequence of U, -U is the sequence of the inverse of the conjugate sequence of U, (U') is the conjugate sequence of the mirror-symmetric sequence of U, and- (U ') is the sequence of the inverse of (U').
The structure of the training sequence is a conjugate antisymmetric sequence. The first N/8 point sequence and the third N/8 point sequence in the left half part are in mirror image opposite number symmetry; the first N/8 point sequence and the third N/8 point sequence in the right half part are mirror image sequences; the first N/8-point sequence and the second N/8-point sequence in the right half part are opposite sequences.
By using the mirror image sequence, the conjugate sequence and the opposite number sequence of the sequence U, the training sequence structure is reasonably set, and when the sliding window deviates from the correct position, the correlation value quickly falls. When the signal-to-noise ratio of the signal is reduced, the training sequence can keep the autocorrelation performance, and the influence of the reduction of the signal-to-noise ratio on the main peak value is lower.
Step 3, the transmitting end adds the training sequence into the data frame;
step 5, the receiving end receives the data frame comprising the training sequence;
step 6, the receiving end calculates the signal autocorrelation value P (n);
step 7, the receiving end calculates the 1/2 value R (n) of the training sequence energy value;
step 8, the receiving end normalizes the signal autocorrelation value P (n) by utilizing R (n) to obtain a normalized value M (n);
the timing metric of steps 6-8 is defined as follows:
M(n)＝|P(n)| 2 /R 2 (n) (3)
r (n) represents the nth signal data received, P (n) represents the autocorrelation value of the training sequence, and is obtained by calculating the correlation value of the left half sequence and the right half sequence of the training sequence;
m is a relative position value of data of m positions adjacent to the nth signal data;
r (n) represents 1/2 of the training sequence energy value and is used for carrying out normalization processing on the autocorrelation value of the training sequence.
Step 9, the receiving end carries out OFDM symbol synchronization according to M (n), and OFDM symbol synchronization position
Is obtained by the following formula:
the maximum position of the autocorrelation value is the midpoint of the training sequence, the position of the training sequence is judged, the OFDM symbol is judged according to the training sequence, and OFDM symbol synchronization is carried out.
The invention discloses a training sequence-based autocorrelation OFDM symbol synchronization method, which comprises the following steps: training sequence structure; performing IFFT modulation on the preset sequence to obtain a U sequence; calculating a sliding autocorrelation sum value; a timing measurement method; an OFDM symbol synchronization method. The key point is an OFDM symbol synchronous training sequence structure based on a complex PN sequence; a timing measurement method based on a complex PN sequence OFDM symbol synchronization training sequence structure.
The invention reasonably sets the training sequence structure by using the mirror sequence, the conjugate sequence and the opposite number sequence of the complex PN sequence, and reduces the correlation between the training sequence and the training sequence delay sequence. The whole training sequence is a conjugate anti-symmetric sequence, when the signal-to-noise ratio of a signal is reduced, the training sequence can keep autocorrelation performance, and the influence of the reduction of the signal-to-noise ratio on the main peak value is low. The invention can accurately carry out OFDM symbol synchronization, can improve the symbol timing synchronization precision and the signal transmission performance in the OFDM system, and solves the problem of a peak value platform compared with the Schmidl & Cox algorithm; the secondary peak value is lower relative to the Minn algorithm; the main peak value is higher relative to the Park algorithm. The invention can improve the symbol timing synchronization precision and the signal transmission performance in the OFDM system.
The present applicant has described and illustrated embodiments of the present invention in detail with reference to the accompanying drawings, but it should be understood by those skilled in the art that the above embodiments are only preferred embodiments of the present invention, and the detailed description is only for the purpose of helping the reader to better understand the spirit of the present invention, and not for the purpose of limiting the scope of the present invention, and on the contrary, any modifications or modifications based on the spirit of the present invention should fall within the scope of the present invention.
Claims (5)
1. An autocorrelation OFDM symbol synchronization method based on a conjugate antisymmetric training sequence is characterized in that:
the method comprises the following steps:
step 1, performing IFFT on a complex PN sequence to generate a sequence U;
step 2, generating a training sequence according to the sequence U, wherein the training sequence sequentially comprises U, U, -U ', - (U');
u' is a mirror symmetric sequence of U; -U' is the opposite sequence of the mirror symmetric sequence of U; u is a conjugated sequence of U; -U is the sequence of the inverse of the conjugate sequence of U; - (U ') is the sequence of the opposite of (U '), (U ') is the conjugate of the mirror symmetric sequence of U;
step 3, the transmitting end adds the training sequence into the data frame;
step 4, the data frame is transmitted in the data transmission channel;
step 5, the receiving end receives the data frame comprising the training sequence;
step 6, the receiving end calculates a signal autocorrelation value P (n) according to the structure of the training sequence;
step 7, the receiving end calculates 1/2 value R (N) of the training sequence energy value aiming at the N/2 training sequence;
step 8, the receiving end normalizes the signal autocorrelation value P (n) by utilizing R (n) to obtain a normalized value M (n);
and 9, the receiving end carries out OFDM symbol synchronization according to M (n).
2. The method of claim 1, wherein the method comprises the steps of:
in step 6, the signal autocorrelation value P (n) is calculated according to the formula (1):
r (N) represents the nth signal data received, and N is the length of the training sequence;
m is a relative position value of data of m positions adjacent to the nth signal data.
3. The method of claim 2, wherein the method comprises the steps of:
in step 7, R (n) is calculated according to formula (2):
4. the method of claim 3, wherein the method comprises the steps of:
in step 8, the signal autocorrelation value P (n) is normalized according to the formula (3):
M(n)＝|P(n)| 2 /R 2 (n) (3)。
5. the method of claim 4, wherein the method comprises the steps of:
in step 9, OFDM symbol synchronization position
Is obtained by the following formula:
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| CN114584449B (en) * | 2022-03-03 | 2023-03-21 | 电子科技大学 | Improved M-part timing synchronization and frequency offset method based on CAZAC sequence |
| CN115913860B (en) * | 2022-11-18 | 2024-06-21 | 泰山学院 | Synchronization method, system and readable storage medium suitable for mobile video transmission |
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