CN106330806B - Fine frequency offset estimation method based on cyclic prefix and long training sequence field - Google Patents
Fine frequency offset estimation method based on cyclic prefix and long training sequence field Download PDFInfo
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- CN106330806B CN106330806B CN201610821495.3A CN201610821495A CN106330806B CN 106330806 B CN106330806 B CN 106330806B CN 201610821495 A CN201610821495 A CN 201610821495A CN 106330806 B CN106330806 B CN 106330806B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L27/00—Modulated-carrier systems
- H04L27/0014—Carrier regulation
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L27/00—Modulated-carrier systems
- H04L27/26—Systems using multi-frequency codes
- H04L27/2601—Multicarrier modulation systems
- H04L27/2647—Arrangements specific to the receiver only
- H04L27/2655—Synchronisation arrangements
- H04L27/2657—Carrier synchronisation
- H04L27/266—Fine or fractional frequency offset determination and synchronisation
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L27/00—Modulated-carrier systems
- H04L27/26—Systems using multi-frequency codes
- H04L27/2601—Multicarrier modulation systems
- H04L27/2647—Arrangements specific to the receiver only
- H04L27/2655—Synchronisation arrangements
- H04L27/2668—Details of algorithms
- H04L27/2673—Details of algorithms characterised by synchronisation parameters
- H04L27/2676—Blind, i.e. without using known symbols
- H04L27/2678—Blind, i.e. without using known symbols using cyclostationarities, e.g. cyclic prefix or postfix
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L27/00—Modulated-carrier systems
- H04L27/0014—Carrier regulation
- H04L2027/0024—Carrier regulation at the receiver end
- H04L2027/0026—Correction of carrier offset
Abstract
The invention provides a fine frequency offset estimation algorithm and a system based on a cyclic prefix and a long training sequence field, wherein the method carries out timing synchronization on received frame data and positions a 17 th data sampling point of the long training sequence field; delaying 64 data sampling points, and sequentially calculating the autocorrelation values of 80 sampling points from the 17 th sampling point; accumulating the calculated autocorrelation values of the 80 sampling points; estimating a frequency offset value by using the accumulated sum; the method solves the problems that the precision of fine frequency offset estimation only by using the cyclic prefix is low, and the multipath time delay is easily interfered by other symbols, reduces the calculation amount of DFT on the training sequence, reduces errors to a certain extent, and further improves the estimation precision.
Description
Technical Field
The invention relates to the field of wireless mobile communication transmission, in particular to a fine frequency offset estimation method based on a cyclic prefix and a long training sequence field.
Background
Since the 80 s in the 20 th century, Orthogonal Frequency Division Multiplexing (OFDM) technology has grown more and more mature and is widely applied in many fields. Such as asymmetric digital subscriber lines, wireless local loops, digital audio broadcasting, high definition television, and wireless local area networks. As the demand for communication datamation, broadband, personalization and mobility is increased, more researchers concentrate on research and development of the application of the OFDM technology in the mobile communication system.
The OFDM can be widely applied in various information transmission fields, and is mainly based on the fact that the OFDM has high spectrum efficiency, strong bandwidth expansibility, multipath fading resistance, flexible spectrum resource allocation and easy realization of a multi-antenna technology, but one OFDM symbol consists of a plurality of orthogonal subcarriers, the orthogonality of the subcarriers is greatly influenced by spectrum deviation, and the susceptibility to frequency deviation is a great defect of the OFDM technology, so how to eliminate the influence of frequency deviation on a system is very important.
OFDM multi-carrier systems have many advantages such as: the method can reduce intersymbol interference caused by time dispersion of a wireless channel, can utilize spectrum resources to the maximum extent, is a great advantage in a communication system with tense spectrum resources, supports different transmission rates realized in different subchannels, can be combined with a plurality of access modes to form an orthogonal frequency division multiple access system and the like. However, it is obvious that since an OFDM symbol is composed of a plurality of orthogonal subcarriers, the OFDM symbol is also sensitive to the influence of frequency deviation, and often has a high peak-to-average power ratio, which may cause the frequency spectrum of the signal to change, destroy the orthogonality of the subcarriers, and cause a great influence on the performance of the system.
Frequency offset is generally caused by three reasons:
in practice, the crystal oscillator frequencies of the transmitter and the receiver generating the carrier waves cannot be completely consistent, which causes a certain deviation of the carrier frequencies of the transmitter and the receiver for modulation and demodulation, breaks the orthogonality of the sub-carrier waves, and has an additive effect on the phase, thereby causing serious influence on the system.
The transmitter and receiver are not directly stationary, but rather have relative velocities, which cause doppler shifts, producing frequency offsets.
The crystal oscillators of the digital-to-analog converter of the transmitter and the analog-to-digital converter of the receiver cannot have the same sampling frequency, which in turn causes the sampling interval of the signal to deviate, and the deviation accumulated to a certain extent can have serious influence on the system.
The frequency deviation of the subcarrier frequency deviation is divided into integer frequency deviation and decimal frequency deviation, the integer frequency deviation refers to the frequency deviation value generated by the system and is larger than the subcarrier interval, for the frequency deviation, the coarse frequency deviation, namely the integer frequency deviation value estimation algorithm is needed to be used for estimation, the decimal frequency deviation refers to the frequency deviation value which is smaller, generally in the range of the subcarrier interval, the decimal frequency deviation algorithm is small in estimation range but higher in precision, and the frequency deviation estimation is often carried out by combining the integer frequency deviation value estimation algorithm and the decimal frequency deviation estimation compensation in the frequency deviation estimation and compensation of the system. Fractional frequency offset results in orthogonality between subcarriers, while integer frequency offset results in cyclic shift and phase rotation of the symbol sequence of the received OFDM signal. The frequency offset estimation can be divided into a frequency offset estimation algorithm in a time domain and a frequency offset estimation algorithm in a frequency domain, and the carrier frequency offset can seriously affect the communication performance of a wireless communication system, so that the signal cannot be normally transmitted due to service interruption. The frequency deviation with the frequency deviation value smaller than the subcarrier interval is called decimal frequency deviation, the decimal frequency deviation algorithm has a small estimation range and higher precision, and the frequency deviation value is not large under the general condition, so the invention mainly discusses the fine frequency deviation.
Moreover, the frequency offset estimation only by using the cyclic prefix is easily influenced by multipath, and has lower precision, the problem of cyclic prefix pollution can be solved by combining the cyclic prefix and the long training sequence, and the estimation algorithm has higher precision compared with the traditional estimation algorithm only using a long training sequence field. As shown in fig. 1, the data frame structure of 802.11a includes a preamble field, a signaling field, a service field, and a data field, and a trailer and padding. The preamble includes a Short training Sequence (STF), a Long training sequence (LTF), and a signaling Field. The short training sequence is ten repeated symbols and the long training sequence contains a cyclic prefix, a long training sequence field 1 and a long training sequence field 2. Long training sequence 1 and sequence 2 are repeated sequence fields. The 802.11a protocol specifies that an OFDM symbol has 64 data samples, that the long training sequence has 160 data samples, that the cyclic prefix has 32, and that the long training field 1 and field 2 are 64, respectively. The invention uses the relation among the cyclic prefix of the long training sequence, the training sequence field 1 and the sequence field 2 to complete the fine frequency offset synchronization; the 802.11n data frame structure contains a legacy preamble that is identical to the 802.11a data frame structure.
Disclosure of Invention
The invention provides a fine frequency offset estimation method based on a cyclic prefix and a long training sequence field, and the algorithm can improve the frequency synchronization precision of the existing wireless communication system.
Still another object of the present invention is to provide a fine frequency offset estimation system based on cyclic prefix and long training sequence field.
In order to achieve the technical effects, the technical scheme of the invention is as follows:
a fine frequency offset estimation method based on cyclic prefix and long training sequence field includes the following steps:
s1: carrying out timing synchronization on received frame data, and positioning to a 17 th data sampling point of a long training sequence field;
s2: delaying 64 data sampling points, and sequentially calculating the autocorrelation values of 80 sampling points from the 17 th sampling point;
s3: accumulating the calculated autocorrelation values of the 80 sampling points;
s4: the frequency offset value is estimated using the accumulated sum.
Further, the specific processes of the steps S1-S2 are as follows:
positioning to a symbol starting time point of a preamble length training sequence field of received frame data through symbol timing, wherein the time delay between a cyclic prefix and a repetitive symbol corresponding to a long training sequence 1 is 64 sampling points, the time delay between the repetitive symbols corresponding to the long training sequence 1 and a long training sequence 2 is also 64 data sampling point lengths, performing time delay autocorrelation with a data point delayed by 64 sampling points from a 17 th data sampling point of the long training sequence, and sequentially performing time delay autocorrelation calculation of 80 points in sequence.
Preferably, the algorithm for estimating the frequency offset value in step S4 adopts a coordinate rotation numerical calculation algorithm.
A fine frequency offset estimation system based on a cyclic prefix and a long training sequence field, comprising:
the delay autocorrelation calculating module consists of an FIFO and a multiplier, wherein the FIFO consists of a static random memory unit and is used as a data buffer, the depth is set to be 64, and the delay operation of 64-point data is completed; firstly, initializing FIFO to 0, when the current data enters FIFO with the depth of 64 points, delaying 64 points of data, synchronously outputting the current data and the delayed data to a multiplier to perform complex multiplication operation, ensuring the synchronous output of the same position of a long training sequence, and realizing the calculation function of delayed autocorrelation;
the autocorrelation value accumulation module is composed of an adder and a register, firstly, the register is initialized with a value of 0, autocorrelation values output by the time delay autocorrelation module and current values temporarily stored in the register are simultaneously input into the adder for addition, the addition results are temporarily stored in the register until the accumulation of 80 time delay autocorrelation values is completed, and the accumulation results are input into the frequency offset estimation module;
and the frequency offset estimation module is used for performing arc tangent function calculation on the accumulation result by using a coordinate rotation digital calculation algorithm so as to complete the calculation of estimating the frequency offset value.
Furthermore, the self-correlation module adopts a first-in first-out queue to realize synchronous output of the corresponding position of the long training sequence, and further performs self-correlation calculation of the corresponding sampling point.
Compared with the prior art, the technical scheme of the invention has the beneficial effects that:
the invention carries on timing synchronization to the received frame data, positions to the 17 th data sampling point of the long training sequence field; delaying 64 data sampling points, and sequentially calculating the autocorrelation values of 80 sampling points from the 17 th sampling point; accumulating the calculated autocorrelation values of the 80 sampling points; estimating a frequency offset value by using the accumulated sum; the method solves the problems that the precision of fine frequency offset estimation only by using the cyclic prefix is low, and the multipath time delay is easily interfered by other symbols, reduces the calculation amount of DFT on the training sequence, reduces errors to a certain extent, and further improves the estimation precision.
Drawings
FIG. 1 is a block diagram of a frame of data of 802.11 a;
FIG. 2 is a flow chart of the algorithm of the present invention;
FIG. 3 is a block diagram of the system of the present invention;
fig. 4 is a schematic diagram of signal transmission and reception.
Detailed Description
The drawings are for illustrative purposes only and are not to be construed as limiting the patent;
for the purpose of better illustrating the embodiments, certain features of the drawings may be omitted, enlarged or reduced, and do not represent the size of an actual product;
it will be understood by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted.
The technical solution of the present invention is further described below with reference to the accompanying drawings and examples.
Example 1
The signal source signal is processed by a series of processing of a transmitting terminal to form a signal x (t), and after the signal x (t) is subjected to up-conversion, a complex baseband signal transmitted by a transmitter is as follows:
ft denotes a transmission carrier frequency. Because there is a difference between the sampling periods of the transmitter and the receiver, the receiving carrier frequency of the receiver is set to fr, and the complex baseband signal received after the signal is down-converted is:
w (t) represents gaussian noise, because each module in the communication system can only process digital signals, and the down-converted signals are subjected to analog-to-digital conversion to obtain discrete expressions of received signals:
f delta represents that the signal passes through a channel, and then is subjected to analog-to-digital conversion, and normalization processing is carried out on the frequency offset estimation value in the formula (3) relative to the frequency offset value generated by the transmitted signal:
if f Δ ═ ε × Δ f, ε is the normalized frequency offset, Δ f is the subcarrier spacing, and Δ f ═ 312.5KHz, Ts ═ 0.05us is set as the sampling period, and N ═ 64 according to the IEEE 802.11N WLAN PHY layer standard, then equation (4) can be further simplified as follows:
the algorithm of the invention comprises the following steps:
positioning to the symbol start time point of the preamble length training sequence field through symbol timing, assuming that the 17 th point of the cyclic prefix corresponds to time D, the delay between the cyclic prefix and the repeated symbol corresponding to the long training sequence 1 is 64 sampling points, and the delay between the repeated symbols corresponding to the long training sequence 1 and the long training sequence 2 is also 64 data sampling points in length. Therefore, the time delay autocorrelation is carried out on the data points delayed by 64 sampling points from the 17 th data sampling point of the long training sequence, and the time delay autocorrelation calculation of 80 points is carried out sequentially.
Calculate the time delay autocorrelation sum of these 80 points:
substituting formula (5) for formula (7) to obtain:
since the signal is uncorrelated with gaussian noise and there is also no correlation between gaussian noise signals, the cross-correlation function of the signal and noise is equal to zero and the autocorrelation function between gaussian noise is also zero, so Y can be written as:
estimating the fine frequency offset using equation (10):
fig. 4 is a structural diagram of the system of the present invention, and the hardware structure is composed of three modules, namely a delay autocorrelation calculating module, an autocorrelation value accumulating module and a frequency offset estimating module. The delay autocorrelation calculating module consists of a FIFO and a multiplier. The FIFO is composed of static random access memory units, is used as a data buffer, has the depth of 64 and can complete the delay operation of 64 point data. Firstly, initializing FIFO to 0, entering the current data into FIFO with the depth of 64, delaying 64 point data, synchronously outputting the current data and the delayed data to a multiplier to perform complex multiplication operation, thus ensuring the synchronous output of the same position of the long training sequence and realizing the calculation function of delayed autocorrelation.
The autocorrelation value accumulation module is composed of an adder and a register, firstly, the register is initialized with 0 value, the autocorrelation value output by the time delay autocorrelation module and the current value temporarily stored in the register are simultaneously input into the adder for addition, the addition result is temporarily stored in the register until the accumulation of 80 time delay autocorrelation values is completed, and the final accumulation result is input into the frequency offset estimation module.
The essence of estimating the frequency offset value is to calculate the arctangent function, as can be seen from equation (10). And the frequency offset estimation module calculates an arc tangent function by using a CORDIC algorithm so as to estimate the frequency offset value. The CORDIC algorithm is also called coordinate rotation digital calculation algorithm, and utilizes the thought of dichotomy to obtain the final accumulated angle value, namely the estimated arctangent value, by changing the ordinate value of the coordinate point. The specific principle is as follows:
and (4) obtaining the autocorrelation summation Y of 80 points by the formula (9), wherein Y is a complex number, the imaginary part value of Y is taken as the ordinate point of the rectangular coordinate, and the real part value is taken as the abscissa point. Recall that the angle value of the arctangent to be estimated is phi. Rotating the vector D (im (Y), Re (Y)) by theta (k is 0) 45 degrees clockwise, checking the ordinate value of the new coordinate after rotation, if the value of the ordinate is greater than zero, indicating that phi is greater than 45 degrees, and continuing to rotate the vector D by theta (k) degrees clockwise. If the value of the ordinate is smaller than zero, indicating that phi is smaller than 45 degrees, the vector D is continuously rotated by theta (k) degrees in the counterclockwise direction. The angle of each subsequent rotation follows | tan [ θ (k) ] | 2-k, where k is 1,2, … …. The angle value corresponding to 2-k can be realized by a lookup table, and the addition of the absolute value indicates that the angle can be positive or negative, namely corresponding to clockwise or counterclockwise rotation. For the k-th rotation, the calculation method is as follows:
(a+bi)(cos[θ(k)]+sin[θ(k)]i)＝cos[θ(k)]×[a tan[θ(k)]b+i×(tan[θ(k)]a+b)]
wherein cos [ theta (k) ] can also be saved by a lookup table method. The rotation makes the value of the ordinate approach 0 continuously, and in practice, the value of the ordinate is only required to be smaller than a certain precision value. And accumulating the angle values of the multiple rotations, wherein the accumulated result is the angle value of the arctan function to be calculated. Obviously, the CORDIC algorithm can calculate the arctan value by means of shifting and adding and subtracting, and avoids complex multiplication operations.
The same or similar reference numerals correspond to the same or similar parts;
the positional relationships depicted in the drawings are for illustrative purposes only and are not to be construed as limiting the present patent;
it should be understood that the above-described embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the claims of the present invention.
Claims (2)
1. A fine frequency offset estimation method based on a cyclic prefix and a long training sequence field is characterized by comprising the following steps:
s1: carrying out timing synchronization on received frame data, and positioning to a 17 th data sampling point of a long training sequence field;
s2: delaying 64 data sampling points, and sequentially calculating the autocorrelation values of 80 sampling points from the 17 th sampling point;
s3: accumulating the calculated autocorrelation values of the 80 sampling points;
s4: estimating a frequency offset value by using the accumulated sum;
the specific process of the steps S1-S2 is as follows:
positioning to a symbol starting time point of a preamble length training sequence field of received frame data through symbol timing, wherein the time delay between a cyclic prefix and a repetitive symbol corresponding to a long training sequence 1 is 64 sampling points, the time delay between the repetitive symbols corresponding to the long training sequence 1 and a long training sequence 2 is also 64 data sampling point lengths, performing time delay autocorrelation on data points delayed by 64 sampling points from a 17 th data sampling point of the long training sequence, and sequentially performing time delay autocorrelation calculation of 80 points;
the algorithm for estimating the frequency offset value in the step S4 adopts a coordinate rotation numerical calculation algorithm;
the fine frequency offset estimation method based on the cyclic prefix and the long training sequence field is applied to a fine frequency offset estimation system based on the cyclic prefix and the long training sequence field, and the system comprises the following steps:
the delay autocorrelation calculating module consists of an FIFO and a multiplier, wherein the FIFO consists of a static random memory unit and is used as a data buffer, the depth is set to be 64, and the delay operation of 64-point data is completed; firstly, initializing FIFO to 0, when the current data enters FIFO with the depth of 64 points, delaying 64 points of data, synchronously outputting the current data and the delayed data to a multiplier to perform complex multiplication operation, ensuring the synchronous output of the same position of a long training sequence, and realizing the calculation function of delayed autocorrelation;
the autocorrelation value accumulation module is composed of an adder and a register, firstly, the register is initialized with a value of 0, autocorrelation values output by the time delay autocorrelation module and current values temporarily stored in the register are simultaneously input into the adder for addition, the addition results are temporarily stored in the register until the accumulation of 80 time delay autocorrelation values is completed, and the accumulation results are input into the frequency offset estimation module;
and the frequency offset estimation module is used for performing arc tangent function calculation on the accumulation result by using a coordinate rotation digital calculation algorithm so as to complete the calculation of estimating the frequency offset value.
2. The fine frequency offset estimation method based on cyclic prefix and long training sequence field according to claim 1, wherein the auto-correlation module employs a first-in first-out queue to achieve synchronous output of corresponding positions of the long training sequence, and further performs auto-correlation calculation of corresponding sampling points.
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| CN107612860B (en) * | 2017-08-25 | 2020-06-23 | 西安电子科技大学 | Synchronization and downsampling estimation method suitable for 802.11ac receiver |
| CN110113276B (en) * | 2018-02-01 | 2021-12-07 | 珠海全志科技股份有限公司 | OFDM frequency offset estimation method, system and device based on IEEE802.11 |
| CN110224963B (en) * | 2019-04-30 | 2020-03-24 | 高拓讯达（北京）科技有限公司 | Method and device for determining symbol timing synchronization position and storage medium |
| CN112866160B (en) * | 2020-12-30 | 2023-09-01 | 中电科思仪科技(安徽)有限公司 | Method and device for analyzing high-order modulation OFDMA-WLAN signal under large bandwidth |
| CN114598584B (en) * | 2022-04-28 | 2022-08-26 | 为准（北京）电子科技有限公司 | Fine frequency offset estimation method and device in wireless communication system |
| CN115412417B (en) * | 2022-07-19 | 2024-04-02 | 深圳市联平半导体有限公司 | Carrier initial phase determining method, device, terminal and storage medium |
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