A MIMO-OFDM time-frequency synchronization method for UAVs with strong multipath channels

Abstract

The present invention belongs to the field of unmanned aerial vehicle data transmission, and is a MIMO-OFDM time-frequency synchronization method suitable for unmanned aerial vehicle strong multipath channels. It includes: (1) determining the number of transmitting antennas, the length of the preamble code and the pseudo-random sequence; (2) using the pseudo-random sequence to generate a multi-antenna transmission preamble code sequence; (3) using the multi-antenna preamble code to generate a transmission data frame; (4) correlating the preamble code sequence before and after for coarse time synchronization; (5) performing fractional frequency offset estimation and compensating the received data; (6) calculating the two-dimensional metric function of integer frequency offset estimation and fine time synchronization; (7) jointly performing the strongest path search and integer frequency offset estimation; (8) searching based on the strongest path to obtain a fine synchronization result. The present invention designs an orthogonal preamble sequence independent of the number of antennas at the transmitting end of the unmanned aerial vehicle MIMO-OFDM communication system. The coarse synchronization and fine synchronization algorithms at the receiving end are adapted to multipath channels, are not affected by frequency offset, have a large frequency offset estimation range, and can achieve good synchronization performance.

Description

Technical Field

[0001] The present invention belongs to the field of unmanned aerial vehicle data transmission, and further relates to a MIMO-OFDM system transmitting end orthogonal preamble sequence design and a receiving end high-precision time-frequency synchronization method suitable for unmanned aerial vehicle strong multipath channels. Background Art

[0002] The uplink and downlink data transmission of UAV is the only link between it and the ground operator. Uplink transmission refers to the data transmission of various types of control, relay, etc. from the ground station to the UAV, and downlink transmission refers to the data transmission of telemetry, payload, etc. from the UAV to the ground station. Usually, the uplink and downlink transmission channels can be regarded as line-of-sight additive white Gaussian noise channels. However, when the UAV has a long range and a low transmission elevation angle, the signal transmission not only has a large Doppler frequency shift, but also has multiple reflection paths, and the channel exhibits Rician multipath characteristics; for the transmission channel of beyond-line-of-sight or severely obstructed UAVs, since there is no obvious direct path, the probability density of the received signal amplitude obeys the Rayleigh distribution.

[0003] The multipath effect seriously affects the reliability of drone data transmission, resulting in a significant decrease in drone mission capabilities. Orthogonal frequency division multiplexing (OFDM) technology has high spectrum utilization and anti-multipath capabilities. In recent years, its application in drone transmission links has attracted much attention. Combining it with MIMO technology further improves its anti-multipath capability and can be applied to drone uplink and downlink data transmission under strong multipath channels. In MIMO-OFDM communication systems, the performance of the synchronization method is the key to affecting the communication system's reception performance, and even whether it can be received correctly.

[0004] Depending on whether data assistance is used, it is divided into blind synchronization method and data-assisted synchronization method: the blind synchronization method does not require the addition of additional auxiliary data, and its advantage is high data transmission efficiency. However, due to its large amount of calculation and poor performance, it is not suitable for real-time and bursty wireless communication systems; the data-assisted synchronization method uses the known structural characteristics of the training sequence or leading symbol to extract the synchronization information in the signal. Compared with the blind synchronization method, it has much smaller calculation amount, faster synchronization speed and higher accuracy, and is more suitable for the real-time data transmission needs of drones.

[0005] There are two main classical data-assisted MIMO-OFDM system synchronization methods: one is the Mody algorithm, also known as the EPSP algorithm; the other is the Schenk algorithm. Among them, the main idea of ​​the Mody algorithm is to insert periodic time-domain orthogonal preamble codes at the same time-frequency position of each antenna. Coarse time synchronization uses the periodicity of the signal to perform delay autocorrelation and estimate the fractional frequency offset; then the integer frequency offset is estimated in the frequency domain. Its shortcomings are: since the integer frequency offset estimation depends on the result of coarse time synchronization, and the timing deviation of coarse time synchronization is large in multipath and low signal-to-noise ratio environments, it will cause errors in integer frequency offset estimation.

[0006] In the Schenk algorithm, the preambles of each transmitting antenna are two identical synchronization sequences, and the preambles of each transmitting antenna do not overlap in time, that is, they are time orthogonal. Delay autocorrelation is used for coarse time synchronization and frequency synchronization, and cross-correlation is used for fine time synchronization. Its shortcomings are: as the number of antennas increases, the resources occupied by the preamble code also increase exponentially, and the cross-correlation is affected by the frequency offset, which will cause timing deviation, and the frequency offset estimation range is small.

[0007] In the synchronization of MIMO-OFDM systems, in addition to time-frequency synchronization, it is also necessary to consider how to distinguish the signals of multiple transmitting antennas. For data-assisted synchronization methods, the training sequences or preamble symbols from different transmitting antennas must be uniquely identifiable, which requires the transmitter to design the preamble sequence to achieve both high spectral efficiency and high-precision time-frequency synchronization performance. Summary of the invention

[0008] The present invention proposes a MIMO-OFDM time-frequency synchronization method suitable for unmanned aerial vehicle strong multipath channels, including preamble code generation, time synchronization and frequency synchronization methods, aiming to overcome the shortcomings of the above-mentioned data-assisted MIMO-OFDM synchronization method.

[0009] The technical solution adopted by the present invention is:

[0010] A MIMO-OFDM time-frequency synchronization method suitable for a strong multipath channel of an unmanned aerial vehicle is implemented in a MIMO-OFDM system and specifically includes the following steps:

[0011] (1) At the transmitting end, determine the number of transmitting antennas , preamble length and a pseudo-random sequence for preamble sequence generation ,in for An integer multiple of =1,2,…, ;

[0012] (2) Using pseudo-random sequences generate The preamble sequence used by the transmitting antennas includes two identical Long Sequence , =1,2,…, , i represents the i-th transmitting antenna;

[0013] (3) Put two Combination as the first The preamble sequence used by the transmitting antenna is placed at the head of the data to be sent to generate a sending data frame;

[0014] (4) At the receiving end, the transmitted data frame containing the preamble sequence is received, and the two identical The long sequence is correlated before and after for coarse time synchronization, and the correlation results of all receiving antennas are summed to obtain the metric function of coarse timing synchronization. , find the command Maximum , which is the rough synchronization result ;

[0015] (5) Based on the coarse synchronization results Using the correlation function to obtain the fractional frequency deviation estimation result , and use Compensating the received signal;

[0016] (6) After compensating for the fractional frequency offset, the received signal on each receiving antenna is correlated in the time-frequency domain, and the correlation results of all receiving antennas are combined by maximum ratio to obtain a two-dimensional metric function for integer frequency offset estimation and precise time synchronization. , and All are integers;

[0017] (7) Combine the strongest path search and integer frequency offset estimation, that is, the search command The largest and , get the strongest diameter position and integer frequency offset estimation ;

[0018] (8) The strongest diameter position Forward search on the time axis is performed at the origin. Under a given threshold, let The smallest value exceeding the threshold This is the result of fine synchronization .

[0019] Furthermore, the specific process of step (2) is as follows:

[0020] Using pseudo-random sequences generate The preamble sequence used by the transmitting antenna is The preamble sequence for the transmitting antennas consists of two identical sequences Composition, of which:

[0021] a i ( n ) = IFFT [ A i ( k )], k = 1 , 2 ,..., N L ;

[0022] , is a non-negative integer;

[0023] In the formula, =1,2,…, , is the number of IFFT points, The symbol is rounded down, that is, the preamble codes of each transmitting antenna overlap in the time domain and are orthogonal in the frequency domain.

[0024] Furthermore, the metric function of coarse time synchronization in step (4) is It is expressed as:

[0025] ;

[0026] ;

[0027] ;

[0028] In the formula, is the position of the signal sampling point at the receiving end, is the number of receiving antennas, For the The receiving signal of the receiving antenna;

[0029] Rough synchronization results Obtained by the following formula:

[0030] .

[0031] Furthermore, the specific process of step (6) is as follows:

[0032] set up Long sliding window, received signal after compensating for fractional frequency offset by Centered and Within the radius, each time the window slides one bit, the data in the window is Point FFT transformation and cyclic shift of the pseudo-random sequence in step 1 Perform cross-correlation and perform maximum ratio merging on the calculation results of all receiving antennas to obtain a two-dimensional metric function for integer frequency offset estimation and precise time synchronization :

[0033] ;

[0034] ;

[0035] In the formula, and are integers and , , is any integer greater than the absolute value of the actual frequency deviation.

[0036] Furthermore, the specific process of step (8) is as follows:

[0037] The strongest diameter position The length of the time axis is Forward search, under a given threshold, let Exceeding the minimum threshold This is the result of fine synchronization , the formula is as follows:

[0038] ;

[0039] In the formula, is the search threshold, based on the size of the strongest path. ∈(0,1) is the threshold coefficient, which is used to adjust the size of the threshold. is the length of the forward search.

[0040] The advantages of the present invention compared with the prior art are:

[0041] (1) The preamble sequence designed by the present invention is orthogonal in the time-frequency domain, suitable for MIMO systems, and is not affected by the number of transmitting antennas. It also ensures that the signals are independent of each other at the receiving end, achieving better synchronization performance.

[0042] (2) In the synchronization method of the present invention, coarse time synchronization and fine time synchronization are not affected by frequency deviation.

[0043] (3) The synchronization method of the present invention has a wide range of frequency offset estimation, and has a wide bandwidth. Hz system, the frequency deviation estimation range can theoretically reach .

[0044] (4) The synchronization method of the present invention is suitable for a multipath channel environment and has good precision time synchronization performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 It is a flow chart of the steps of the present invention.

[0046] Figure 2It is a schematic diagram of the preamble sequence designed by the present invention.

[0047] Figure 3 It is a simulation result diagram of the coarse synchronization correct capture probability of the method of the present invention and the traditional method.

[0048] Figure 4 It is a diagram of frequency synchronization root mean square error simulation results of the method of the present invention and the traditional method.

[0049] Figure 5 It is a simulation result diagram of the root mean square error of precise time synchronization of the method of the present invention and the traditional method. DETAILED DESCRIPTION

[0050] The present invention proposes a new MIMO-OFDM time-frequency synchronization method suitable for unmanned aerial vehicle strong multipath channels, including preamble code generation, time synchronization and frequency synchronization methods, aiming to overcome the shortcomings of the above-mentioned centralized MIMO-OFDM synchronization method.

[0051] The MIMO-OFDM time-frequency synchronization method proposed in the present invention is divided into two parts: the transmitting end and the receiving end. Figure 1 , specifically including the following steps:

[0052] On the sending side:

[0053] Step 1: Determine the number of transmit antennas , preamble length and pseudo-random sequence ( =1,2,…, ).in for An integer multiple of The elements belong to the finite set of symbols or .

[0054] Step 2: Design the multi-transmit antenna preamble sequence. Figure 2 , No. The preamble of the transmitting antenna consists of two identical sequences ( =1,2,…, ), wherein:

[0055] a i ( n ) = IFFT [ A i ( k )], k = 1 , 2 ,..., N L

[0056] , is a non-negative integer

[0057] in is the number of IFFT transformation points, The symbol is rounded down, that is, the preamble codes of each transmitting antenna overlap in the time domain and are orthogonal in the frequency domain.

[0058] Step 3: Put the two Combination as the first The preamble code used by the root transmitting antenna, each antenna puts the preamble code sequence at the head of the data to be sent to generate a sending data frame.

[0059] On the receiving end:

[0060] Step 4: Receive the transmitted data frame containing the preamble sequence, and use the two identical The long sequence is correlated before and after to perform coarse time synchronization, and the correlation results of all receiving antennas are summed. The metric function of coarse time synchronization can be expressed as:

[0061]

[0062]

[0063]

[0064] in, is the position of the signal sampling point at the receiving end, is the number of receiving antennas, For the The received signal of the root receiving antenna;

[0065] The result of coarse time synchronization is obtained by the following formula:

[0066] .

[0067] Step 5: Use the correlation result of (4) , the fractional frequency deviation estimation result is obtained by the following formula:

[0068]

[0069] The result of fractional frequency deviation in equation (7) is used to calculate the received signal To compensate for the fractional frequency deviation, the received signal is .

[0070] Step 6: Setup Long sliding window, when receiving signal by Centered and Within the radius, each time the window slides one bit, the data in the window is Point FFT transformation and cyclic shift of the pseudo-random sequence in step 1 Perform cross-correlation and perform maximum ratio merging on the calculation results of multiple antennas to obtain a two-dimensional metric function for integer frequency offset estimation and precise time synchronization :

[0071]

[0072]

[0073] in , are integers and , , is any integer greater than the absolute value of the actual frequency deviation.

[0074] Step 7: Combine the strongest path search and integer frequency offset estimation to find the strongest path position and integer frequency offset estimation Obtained by the following formula:

[0075] .

[0076] Step 8: Search for the first path, at the location of the strongest path Based on the forward search, the result of precise time synchronization It can be obtained by the following formula:

[0077]

[0078] in, is the search threshold, based on the size of the strongest path. ∈(0,1) is the threshold coefficient, which is used to adjust the size of the threshold. is the length of the forward search.

[0079] The implementation principle of the present invention is:

[0080] The present invention is a method for MIMO-OFDM synchronization using a preamble code, comprising: at a transmitting end, the preamble codes of each antenna are mutually orthogonal in the frequency domain to distinguish different transmitting antennas; at a receiving end, two repeated sequences in the preamble code are used for delayed autocorrelation to perform coarse time synchronization and fractional frequency offset estimation, after compensating for the fractional frequency offset, a sliding window fast Fourier transform is performed within a certain range with the result of the coarse time synchronization as the center, and then cross-correlated with the cyclic shift of the local sequence is performed to traverse possible integer frequency offsets, so as to perform a two-dimensional search in the time domain and the frequency offset, and a first path is forward searched along the time domain based on the strongest path, so as to synchronously complete the integer frequency offset estimation and the fine time synchronization.

[0081] Combine the following Figure 3-5 The effects of the present invention are further described.

[0082] The following is a comparison of simulation results between the synchronization method of the present invention and the traditional method. It should be noted that the parameters in the simulation do not affect the generality of the present invention.

[0083] Figure 3 , Figure 4 and Figure 5 The simulation parameters are: two-transmit and two-receive MIMO-OFDM model, that is, =2, =2; the preamble length is 2048, =1024, threshold coefficient =0.3, =6. The simulation comparison test shows that the synchronization method of the present invention and the traditional method perform well under the non-line-of-sight transmission multipath channel (referred to as multipath channel). The normalized frequency deviation range is , the transmission environment is relatively harsh and the frequency deviation is large.

[0084] Figure 3 This is a simulation result diagram of the accuracy probability of coarse time synchronization under a multipath channel. It can be seen that the method of the present invention can capture data frames with a higher correct probability when the signal-to-noise ratio is -9dB, compared with the Mody method and the Schenk method, which is superior to the two traditional methods.

[0085] Figure 4 This is a simulation result diagram of frequency synchronization RMSE under a multipath channel. It can be seen that the Schenk method has the worst performance because it cannot correctly estimate the large frequency deviation due to its small frequency deviation estimation range. Although the Mody method meets the requirements in terms of frequency deviation estimation range, its performance is far inferior to that of the method of the present invention.

[0086] Figure 5It is a simulation result diagram of the RMSE of precise time synchronization under a multipath channel. It can be seen that the precise time synchronization RMSE of the synchronization method of the present invention is better than that of the other two traditional methods, which means that the present invention can more effectively locate the first path position of the received signal, that is, the precise synchronization position.

Claims

1. A MIMO-OFDM time-frequency synchronization method suitable for strong multipath channels of unmanned aerial vehicles, characterized in that: The method is implemented in a MIMO-OFDM system and specifically includes the following steps: (1) At the transmitting end, determine the number of transmitting antennas , preamble length and a pseudo-random sequence for preamble sequence generation ,in for An integer multiple of =1,2,…, ; (2) Using pseudo-random sequences generate The preamble sequence used by the transmitting antennas includes two identical Long Sequence , =1,2,…, , i represents the i-th transmitting antenna; (3) Put two Combination as the first The preamble sequence used by the transmitting antenna is placed at the head of the data to be sent to generate a sending data frame; (4) At the receiving end, the transmitted data frame containing the preamble sequence is received, and the two identical The long sequence is correlated before and after for coarse time synchronization, and the correlation results of all receiving antennas are summed to obtain the metric function of coarse timing synchronization. , find the command Maximum , which is the rough synchronization result ; (5) Based on the coarse synchronization results Using the correlation function to obtain the fractional frequency deviation estimation result , and use Compensating the received signal; (6) After compensating for the fractional frequency offset, the received signal on each receiving antenna is correlated in the time-frequency domain, and the correlation results of all receiving antennas are combined by maximum ratio to obtain a two-dimensional metric function for integer frequency offset estimation and precise time synchronization. , and All are integers; (7) Combine the strongest path search and integer frequency offset estimation, that is, the search command The largest and , get the strongest diameter position and integer frequency offset estimation ; (8) The strongest diameter position Forward search on the time axis is performed at the origin. Under a given threshold, let The minimum value exceeding the threshold This is the result of fine synchronization ; The specific process of step (2) is as follows: Using pseudo-random sequences generate The preamble sequence used by the transmitting antenna is The preamble sequence for the transmitting antennas consists of two identical sequences Composition, of which: , is a non-negative integer In the formula, =1,2,…, , is the number of IFFT points, is the rounding down operator symbol, that is, the preamble codes of each transmitting antenna overlap in the time domain and are orthogonal in the frequency domain; The specific process of step (6) is as follows: set up Long sliding window, received signal after compensating for fractional frequency offset by Centered and Within the radius, each time the window slides one bit, the data in the window is Point FFT transformation and cyclic shift of the pseudo-random sequence in step 1 Perform cross-correlation and perform maximum ratio merging on the calculation results of all receiving antennas to obtain a two-dimensional metric function for integer frequency offset estimation and precise time synchronization : In the formula, and are integers and , , is any integer greater than the absolute value of the actual frequency deviation.

2. The MIMO-OFDM time-frequency synchronization method applicable to multipath channels according to claim 1, characterized in that: The metric function for coarse time synchronization in step (4) is It is expressed as: In the formula, is the position of the signal sampling point at the receiving end, is the number of receiving antennas, For the The receiving signal of the receiving antenna; Rough synchronization results Obtained by the following formula: 。 3. The MIMO-OFDM time-frequency synchronization method applicable to multipath channels according to claim 1, characterized in that: The specific process of step (8) is as follows: The strongest diameter position The length of the time axis is Forward search, under a given threshold, let Exceeding the minimum threshold This is the result of fine synchronization , the formula is as follows: In the formula, is the search threshold, based on the size of the strongest path. ∈(0,1) is the threshold coefficient, which is used to adjust the size of the threshold. is the length of the forward search.

Images