Signal pilot frequency designing and capturing method oriented to large frequency offset scene

Abstract

The invention provides a signal pilot frequency design and capture method oriented to a large frequency offset scene, and the method comprises the steps: carrying out the front and back self-correlation processing of a received signal through a receiving end, obtaining a signal capture detection peak value, counteracting a frequency offset error term of the received signal in a signal self-correlation calculation process, and obtaining a signal capture detection peak value; only a fixed phase offset item caused by the frequency offset and the time interval of the repeated pilot frequency is left, and the fixed phase offset only influences the symbol polarity of the autocorrelation processing result and does not influence the autocorrelation amplitude. And the influence of frequency offset errors on signal acquisition is eliminated in principle. According to the method, the frequency offset error influence of the received signal is completely eliminated, the signal capturing performance under the low signal-to-noise ratio is greatly improved, and the stability and the communication quality of a communication system are improved. Under the condition that the calculation complexity is not increased, interference of frequency offset errors can be effectively avoided, and accurate signal capturing is achieved.

Description

Technical Field

[0001] The invention relates to the field of signal processing, in particular to a signal capturing method. Background Art

[0002] In the communication scenario with large frequency deviation, the conventional pilot design and signal capture method have high miss capture rate and poor capture performance, and cannot effectively achieve the purpose of signal capture and synchronization. In view of the signal capture problem in the communication scenario with large frequency deviation, the present invention proposes a new pilot design and signal capture algorithm.

[0003] The signal pilot is designed for the receiver to perform signal capture and carrier recovery. Usually, the signal pilot is a signal sequence known to both the transmitter and receiver. The receiver uses different capture methods to detect whether the pilot sequence is received, so as to determine whether the target signal has reached the receiver.

[0004] In existing communication systems, receivers often use the method of cross-correlating local pilot sequences with received pilot sequences for signal capture design. In order to combat large frequency offset errors, multiple short pilot cross-correlation superposition processing is often used in pilot design. The specific processing is as follows: the first step is to use the local pilot sequence to perform real-time conjugate correlation processing with the received signal; the second step is to add and process the internal correlation processing values ​​of a single pilot sequence, and take the absolute value and sum of the correlation values ​​of multiple pilots; the third step is to compare the sum of the multiple pilot sequences in step 2 with the set signal capture threshold value. If the sum is higher than the threshold value, it is considered that the signal is captured.

[0005] In addition, for some high signal-to-noise ratio communication systems, time domain energy detection methods are often used for signal capture and processing. Under the time domain energy detection algorithm, the receiver first sets an energy detection window of a specific length, then takes the absolute value of the amplitude of the received signal in the detection window and adds it to obtain the detection energy. Finally, it uses the energy difference between the front and rear detection windows to determine whether the signal has arrived.

[0006] The algorithm used in the current communication system is based on the cross-correlation accumulation of the local pilot sequence and the received signal. Since the local pilot sequence of the receiver does not have the frequency offset information in the received signal, the frequency offset error always exists and cannot be offset when the local pilot sequence is cross-correlated with the received sequence. As a result, the correlation values ​​of a single pilot sequence will offset each other due to the difference in instantaneous phase offset during the superposition processing, which will lead to signal leakage capture, and the signal leakage capture problem will not improve with the improvement of signal quality.

[0007] Although the signal capture algorithm based on signal time domain energy detection is not sensitive to frequency offset errors, it has high requirements for signal quality and can only be applied to high signal-to-noise ratio communication scenarios. When the signal quality is low, the time domain energy detection algorithm cannot effectively distinguish between valid signals and noise, and cannot meet the signal capture requirements in low signal-to-noise ratio communication application scenarios. Energy detection capture algorithms are rarely used in modern communication systems. Summary of the invention

[0008] In order to overcome the shortcomings of the prior art, the present invention provides a signal pilot design and capture method for large frequency offset scenarios, which can accurately detect and capture signals with large frequency offset errors under low signal-to-noise ratio. Compared with the classic pilot sequence cross-correlation signal detection algorithm, the proposed algorithm can effectively avoid the interference of frequency offset errors and achieve accurate signal capture while maintaining the same computational complexity.

[0009] The specific steps of the technical solution adopted by the present invention to solve its technical problem are as follows:

[0010] Step 1: Let x be the baseband signal generated by the transmitter. When there is a carrier frequency offset f e , when the carrier phase shifts φ, the received signal received by the receiver is Where w is Gaussian white noise, t represents the sampling time;

[0011] The pilot sequence at the transmitting end satisfies the signal sequence having two identical pilot signals P m ={p1,p2,...,p m}, two identical pilot signals are continuously inserted or filled with other data;

[0012] Step 2: At the receiving end, two signal sliding detection windows are set. The time length of a single sliding detection window and the length of the pilot signal are both △t. The signal in the sliding detection window moves forward one sampling point at a time. Let the current received signal be r(t). Each time the sampling signal in the sliding detection window moves forward, the signal in sliding detection window 1 is r(t). w1 (t) and the signal r in the sliding detection window 2 w2 (t) performing a conjugate correlation operation;

[0013] After obtaining c(t), the conjugate multiplication sequence in the sliding detection window is accumulated, and the absolute value of the superposition result is taken to obtain:

[0014]

[0015] Among them, c r That is, it is the capture correlation peak value obtained by the receiver using the pilot sequence processing, and t0 is the starting time of the sliding correlation calculation;

[0016] Step 3: Get the capture correlation peak c of the pilot sequence r After that, c r With the set capture threshold T cap Make comparisons;

[0017] Step 4: If c r >T cap , it means that a valid signal is captured; if c r ≤T cap , it means there is no valid signal at present, return to step 2 to continue signal search and capture processing.

[0018] In step 1, taking the continuous insertion of pilot as an example, the transmitted signal after the pilot is inserted is

[0019] tx={{P m},{P m},{D n}}, where D n ={d1,d2,...,d n} is the baseband user data sequence, and the two pilot signals received by the receiving end are as follows:

[0020]

[0021] Among them, r p1 and r p2 are the received pilot signal 1 and pilot signal 2 respectively; △t is the time interval between the two pilot signals, and is also the time length of a single pilot sequence in the repeated pilot continuous insertion mode; w1 and w2 are the Gaussian white noise contained in the two pilot signals respectively.

[0022] In step 2, the specific steps of the conjugate correlation operation are:

[0023] First, calculate the conjugate multiplication sequence c(t) of the signal within the window:

[0024]

[0025] in, Represents r w2 (t) is the conjugate; when the two repeated pilot sequences completely enter the sliding detection window, the pilot signal 1 enters the sliding detection window 1, and the pilot signal 2 enters the sliding detection window 2, that is, r w1 (t) = r p1 And r w2 (t) = r p2 , at this time, the conjugate multiplication of the two sliding detection window signals is calculated as follows:

[0026]

[0027] in, represents the Gaussian white noise term, which is ignored in the calculation because △t is a fixed value, so It can be regarded as a fixed phase deviation caused by the accumulation of frequency deviation over time. The fixed phase deviation has the same effect on all sampling points in the signal sequence and will not cause the problem of mutual cancellation during signal correlation accumulation. It can be seen that after the conjugate multiplication processing, the frequency deviation error term in the original received signal is eliminated. Therefore, the size of the subsequent signal capture correlation peak is no longer affected by the frequency deviation, but only related to the signal-to-noise ratio.

[0028] An electronic device comprises one or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs are configured to execute the method as described above.

[0029] A computer-readable storage medium stores program codes, and the program codes can be called by a processor to execute the method as described above.

[0030] The beneficial effect of the present invention is that in order to solve the problem of signal detection and capture difficulties in existing communication systems under low signal-to-noise ratio and large frequency offset error communication application scenarios, the present invention proposes a pilot autocorrelation signal capture algorithm based on repeated pilot design. This algorithm uses the receiving end to perform forward and backward autocorrelation processing on the received signal to obtain the signal capture detection peak. In the process of calculating the signal autocorrelation, the frequency offset error term of the received signal can be offset, and only the fixed phase offset term caused by the time interval between the frequency offset and the repeated pilot remains. The fixed phase offset only affects the sign polarity of the autocorrelation processing result, and has no effect on the autocorrelation amplitude itself. In addition, the calculation result of the autocorrelation must eventually be processed by taking the absolute value, so the influence of the fixed phase offset on the compliance polarity can also be ignored, thereby eliminating the influence of the frequency offset error on signal capture in principle. Therefore, the autocorrelation signal capture algorithm based on repeated pilot proposed in the present invention can completely eliminate the influence of the frequency offset error of the received signal, greatly improve the performance of signal capture under low signal-to-noise ratio, and improve the stability and communication quality of the communication system. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 This is the sending end repeated pilot design scheme proposed by the present invention.

[0032] Figure 2 It is a calculation flow chart of the present invention.

[0033] Figure 3 The figure is a comparison of the capture performance of the present invention and the traditional pilot correlation capture algorithm at a frequency offset of 3KHz.

[0034] Figure 4It is the capture probability of the scheme of the present invention at different frequency offsets under the signal-to-noise ratio of -1dB.

[0035] Figure 5 is the capture probability of the traditional cross-correlation pilot capture scheme at different frequency offsets under the signal-to-noise ratio of -1dB. DETAILED DESCRIPTION

[0036] The present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0037] Step 1: Let x be the baseband signal generated by the transmitter. When there is a carrier frequency offset f e , when the carrier phase shifts φ, the received signal received by the receiver is Where w is Gaussian white noise, t represents the sampling time;

[0038] The pilot sequence at the transmitting end satisfies the signal sequence having two identical pilot signals P m ={p1,p2,...,p m}, two identical pilot signals are inserted continuously, or other data is filled in between; taking the continuous insertion of pilot as an example, the transmitted signal after the pilot is inserted is tx = {{P m},{P m},{D n}}, where D n ={d1,d2,...,d n} is the baseband user data sequence, and the two pilot signals received by the receiving end are as follows:

[0039]

[0040] Among them, r p1 and r p2 are the received pilot signal 1 and pilot signal 2 respectively; △t is the time interval between the two pilot signals, and is also the time length of a single pilot sequence in the repeated pilot continuous insertion mode; w1 and w2 are the Gaussian white noise contained in the two pilot signals respectively;

[0041] Step 2: At the receiving end, two signal sliding detection windows are set. The time length of a single sliding detection window and the length of the pilot signal are both △t. The signal in the sliding detection window moves forward one sampling point at a time. Let the current received signal be r(t). Each time the sampling signal in the sliding detection window moves forward, the signal in sliding detection window 1 is r(t). w1 (t) and the signal r in the sliding detection window 2 w2 (t) performs conjugate correlation operation; first calculate the conjugate multiplication sequence c(t) of the signal in the window:

[0042]

[0043] in, Represents r w2 (t) is the conjugate; when the two repeated pilot sequences completely enter the sliding detection window, the pilot signal 1 enters the sliding detection window 1, and the pilot signal 2 enters the sliding detection window 2, that is, r w1 (t) = r p1 And r w2 (t) = r p2 , at this time, the conjugate multiplication of the two sliding detection window signals is calculated as follows:

[0044]

[0045] in, represents the Gaussian white noise term, which is ignored in the calculation because △t is a fixed value, so It is considered as a fixed phase deviation caused by the accumulation of frequency deviation over time, and the fixed phase deviation has the same effect on all sampling points in the signal sequence, and will not cause the problem of mutual cancellation when the signal correlation is accumulated. It can be seen that after the above conjugate multiplication process, the frequency deviation error term in the original received signal is eliminated, so the size of the subsequent signal capture correlation peak is no longer affected by the frequency deviation, but only related to the signal-to-noise ratio;

[0046] After obtaining c(t), the conjugate multiplication sequence in the sliding detection window is accumulated, and the absolute value of the superposition result is taken to obtain:

[0047]

[0048] Among them, c r That is, it is the capture correlation peak value obtained by the receiver using the pilot sequence processing, and t0 is the starting time of the sliding correlation calculation;

[0049] Step 3: Get the capture correlation peak c of the pilot sequence r After that, c r With the set capture threshold T cap Make comparisons;

[0050] Step 4: If c r >T cap , it means that a valid signal is captured; if c r ≤T cap , it means there is no valid signal at present, return to step 2 to continue signal search and capture processing.

[0051] In order to further illustrate the superiority of the present invention in signal capture in a communication system with large frequency offset error, a comparative simulation is conducted between the traditional algorithm and the algorithm proposed in the present invention. Examples of parameters set in the simulation are as follows: the length of a single pilot sequence is 256 modulation symbols, the number of pilot sequences is 2 segments, and the symbol rate is 16Msps.

[0052] The simulation first tested the acquisition performance comparison between the proposed signal acquisition algorithm based on repeated pilot autocorrelation and the classic local pilot cross-correlation algorithm under different signal-to-noise ratios under the condition of frequency offset error of 3KHz. The simulation results are shown in Figure 3 It can be seen that the algorithm proposed in the present invention can achieve 100% capture probability when the signal-to-noise ratio is greater than or equal to -1dB, while the traditional local pilot cross-correlation algorithm is affected by the frequency offset, which causes the algorithms to cancel each other out when the signal correlation is superimposed, and no obvious correlation peak can be obtained. Even if the signal-to-noise ratio is increased to 5dB, the signal capture probability does not exceed 1%.

[0053] Afterwards, the proposed signal acquisition algorithm based on repeated pilot autocorrelation and the classic local pilot cross-correlation algorithm were simulated and tested under the condition of low signal-to-noise ratio of -1dB. The acquisition performance was compared under different frequency offset errors. The simulation results are shown in the figure. Figure 4 , 5 As shown. Figure 4 It can be seen that the repetitive pilot autocorrelation signal acquisition algorithm proposed in the present invention is insensitive to frequency offset error, and can maintain a 100% acquisition probability within the test range of frequency offset error from 0KHz to 120KHz. Figure 5 It can be seen that the capture performance of the traditional local pilot cross-correlation capture algorithm is significantly affected by the frequency offset change. It can still guarantee 100% signal capture performance within the frequency offset error range of 0KHz to 2KHz; when the frequency offset error is greater than or equal to 3KHz, the signal capture probability drops to near zero.

[0054] It can be seen from the above comparison results that the signal capture algorithm based on repeated pilot autocorrelation proposed in the present invention effectively solves the signal capture problem under large frequency offset errors, and has better signal capture performance in low signal-to-noise ratio and large frequency offset scenarios, effectively improves the signal quality and reliability, and improves the performance of the communication system.

[0055] The present invention is based on a transmitting end pilot design scheme of repeated pilot. The transmitting end pilot adopts a double pulse insertion form, and each pilot sequence in the transmitting signal is followed by a corresponding repeated pilot. A signal capture algorithm based on the autocorrelation of the pilot sequence of the received signal. The receiving end does not need to save the local pilot, and uses the set signal sliding detection window to perform sliding autocorrelation processing on the signal entering the sliding detection window, and compares the absolute value of the autocorrelation peak of the signal in the sliding detection window with the signal detection decision threshold. If the peak is greater than the threshold, the signal capture is completed.

Claims

1. A signal pilot design and acquisition method for large frequency offset scenarios, characterized in that The steps include: Step 1: Let x be the baseband signal generated by the transmitter. When there is a carrier frequency offset f e , when the carrier phase shifts φ, the received signal received by the receiver is Where w is Gaussian white noise, t represents the sampling time; The pilot sequence at the transmitting end satisfies the signal sequence having two identical pilot signals P m ={p1,p2,...,p m }, two identical pilot signals are continuously inserted or filled with other data; Step 2: At the receiving end, two signal sliding detection windows are set. The time length of a single sliding detection window and the length of the pilot signal are both △t. The signal in the sliding detection window moves forward one sampling point at a time. Let the current received signal be r(t). Each time the sampling signal in the sliding detection window moves forward, the signal in sliding detection window 1 is r(t). w1 (t) and the signal r in the sliding detection window 2 w2 (t) performing a conjugate correlation operation; After obtaining c(t), the conjugate multiplication sequence in the sliding detection window is accumulated, and the absolute value of the superposition result is taken to obtain: Among them, c r That is, it is the capture correlation peak value obtained by the receiver using the pilot sequence processing, and t0 is the starting time of the sliding correlation calculation; Step 3: Get the capture correlation peak c of the pilot sequence r After that, c r With the set capture threshold T cap Make comparisons; Step 4: If c r >T cap , it means that a valid signal is captured; if c r ≤T cap , it means there is no valid signal at present, return to step 2 to continue signal search and capture processing.

2. The signal pilot design and acquisition method for large frequency offset scenarios according to claim 1, characterized in that: In step 1, taking the continuous insertion of pilot as an example, the transmission signal after the pilot is inserted is tx = {{P m },{P m },{D n }}, where D n ={d1,d2,...,d n } is the baseband user data sequence, and the two pilot signals received by the receiving end are as follows: Among them, r p1 and r p2 are the received pilot signal 1 and pilot signal 2 respectively; △t is the time interval between the two pilot signals, and is also the time length of a single pilot sequence in the repeated pilot continuous insertion mode; w1 and w2 are the Gaussian white noise contained in the two pilot signals respectively.

3. The signal pilot design and acquisition method for large frequency offset scenarios according to claim 1, characterized in that: In step 2, the specific steps of the conjugate correlation operation are: First, calculate the conjugate multiplication sequence c(t) of the signal within the window: in, Represents r w2 (t) is the conjugate; when the two repeated pilot sequences completely enter the sliding detection window, the pilot signal 1 enters the sliding detection window 1, and the pilot signal 2 enters the sliding detection window 2, that is, r w1 (t) = r p1 And r w2 (t) = r p2 , at this time, the conjugate multiplication of the two sliding detection window signals is calculated as follows: in, represents the Gaussian white noise term, which is ignored in the calculation because △t is a fixed value, so It is regarded as a fixed phase deviation caused by the accumulation of frequency deviation over time. The fixed phase deviation has the same effect on all sampling points in the signal sequence and will not cause the problem of mutual cancellation during signal correlation accumulation. After conjugate multiplication, the frequency deviation error term in the original received signal is eliminated. Therefore, the size of the subsequent signal capture correlation peak is no longer affected by the frequency deviation, but only related to the signal-to-noise ratio.

4. An electronic device, characterized in that: include: one or more processors; Memory; One or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs are configured to execute the method according to any one of claims 1 to 3.

5. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores program codes, and the program codes can be called by a processor to execute the method according to any one of claims 1 to 3.

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