5G CFO estimation method based on triangular decomposition

Abstract

The invention discloses a 5G CFO estimation method based on triangular decomposition, which comprises the following steps of: establishing a wireless transceiving channel, estimating noise by combining a zero matrix source signal, performing triangular decomposition on a noise signal on the basis, and performing channel injection by taking a triangular decomposition result of the noise signal as a source signal so as to generate frequency deflection; the influence of carrier frequency deflection on the signals is conditionally estimated according to the difference of the output signals, and then the actual frequency offset is inversely calculated, so that the purposes of weakening the synchronization error and reducing the bit error rate of the 5G system are achieved, only one training sequence is needed, the inversion operation is simpler and more effective, the precision is relatively higher, and the sensitivity to noise is further reduced.

Description

Technical Field

[0001] The present invention relates to the field of 5G communication technology, and in particular to a 5G CFO estimation method based on triangular decomposition. Background Art

[0002] CFO (Carrier Frequency Offset) estimation in 5G systems is one of the OFDM (Orthogonal Frequency Division Multiplexing) synchronization technologies. OFDM transmits message data in parallel on its orthogonal subcarriers. Only when orthogonality is maintained can OFDM play its technical advantages, otherwise the system performance will be reduced due to the mutual interference ICI (Inter-Carrier Interference) between the subcarriers. The factors that affect OFDM orthogonality include STO and CFO. Therefore, it is very necessary to accurately estimate the CFO of the 5G system.

[0003] Chinese patent document CN105933262B discloses a "CFO estimation method based on dual training sequences". It includes the steps of establishing a transceiver model, adding dual training sequences, synthesizing received signals, capturing deflection factors, estimating CFO, etc.; adding two different training sequences to the initial signal, synthesizing different received signals, and thus completely canceling the influence of noise on frequency offset estimation. The above technical solution has high computational complexity and the input of multiple sequences affects the accuracy of deflection factor capture. Summary of the invention

[0004] The present invention mainly solves the technical problems that the original technical solution has high computational complexity and the accuracy of deflection factor capture is affected by inputting multiple sequences. A 5G CFO estimation method based on triangular decomposition is provided, a wireless transceiver channel is established, and the noise is estimated in combination with a zero-matrix source signal. On this basis, the noise signal is triangularly decomposed, and the triangular decomposition result of the noise signal is used as a source signal for channel injection, thereby generating a frequency deflection. The influence of the carrier frequency deflection on the signal is conditionally estimated according to the difference of the output signal, and then the actual frequency deviation is inversely calculated, thereby achieving the goal of weakening the synchronization error and reducing the bit error rate of the 5G system. Only one training sequence is required, and the inverse operation is simpler and more effective, the accuracy is relatively higher, and the sensitivity to noise is further reduced.

[0005] The above technical problem of the present invention is mainly solved by the following technical solution: The present invention comprises the following steps: S1. Establishing a wireless transceiver channel; S2. Estimating the noise by combining the zero matrix source signal; S3. Perform triangular decomposition on the noise signal; S4. The triangular decomposition result of the noise signal is used as a source signal to inject into the channel, thereby generating a frequency deflection; S5. Estimate the impact of carrier frequency deviation on the signal, and then reversely calculate the actual frequency deviation.

[0006] A wireless transceiver channel is established, and the noise is estimated in combination with the zero-matrix source signal. On this basis, the noise signal is triangularly decomposed, and the triangular decomposition result of the noise signal is used as the source signal for channel injection, thereby generating a frequency deflection. The influence of the carrier frequency deflection on the signal is conditionally estimated based on the difference in the output signal, and then the actual frequency deviation is inversely calculated, thereby achieving the goal of weakening the synchronization error and reducing the bit error rate of the 5G system. Only one training sequence is required, and the inverse operation is simpler and more effective, with relatively higher accuracy and further reduced sensitivity to noise.

[0007] Preferably, the step S1 sets the constant σ and the 5G carrier frequency deviation ε, calculates the length of the transmitted signal, and combines the time domain variables and the channel noise to obtain the signal deflection caused by the carrier frequency deviation. Calculate the length of the transmitted signal SL tr =power(σ,2), time domain variable n∈[0,SL tr -1], channel noise Nos ch (n), the signal deflection amount Sg caused by carrier frequency deviation CFO =Sg CFO (n,ε).

[0008] Preferably, the step S1 further comprises: the input signal length is SL tr The transmit signal S(n) is used to establish a receiving channel. Establishing a receiving channel T(n) = S(n)*Sg CFO +Nos ch (n).

[0009] Preferably, the step S2 specifically includes generating a source signal of a zero matrix, injecting the zero matrix signal into a wireless transceiver channel, and measuring the output signal T0(n). The source signal of the zero matrix is ​​generated, S0(n)=zeros(n), wherein zeros(·) represents a zero matrix generating function.

[0010] Preferably, the step S3 specifically includes performing triangular decomposition on the output signal T0(n) to obtain L(n) matrix and U(n) matrix respectively, satisfying T0(n)=L(n)*U(n).

[0011] Preferably, the step S4 specifically includes injecting L(n) as the input signal S(n) into the transceiver channel and measuring the output signal T1(n).

[0012] Preferably, the step S4 further comprises calculating the frequency deviation signal according to the U(n) matrix and the output signal T1(n). The triangular decomposition helps to greatly reduce the complexity of the matrix inversion operation; the frequency deviation signal F(n) is calculated as inv(L)*T1(n)-U(n), wherein inv(·) represents the matrix inversion operation.

[0013] Preferably, the step S5 of estimating the frequency offset CFO specifically includes calculating a discrete sum value according to the frequency offset signal, and then calculating and obtaining the actual frequency offset value ε′. Calculate Re CFO =log(Sm ch ), where log(·) represents the natural logarithm; the calculation process quantity ε′=Re CFO *SL tr / (PI*j*(SL tr -1)), where j represents the imaginary unit and PI represents the pi constant.

[0014] Preferably, the step S5 further comprises solving the real function of the actual frequency deviation value ε′, and finally obtaining the 5G carrier signal frequency deviation. CFO =RP(ε′), where RP(·) represents the function for solving the real part of an imaginary number.

[0015] The beneficial effects of the present invention are as follows: a wireless transceiver channel is established, the noise is estimated in combination with a zero-matrix source signal, and on this basis, the noise signal is triangularly decomposed, which helps to greatly reduce the complexity of the matrix inversion operation, and the triangular decomposition result of the noise signal is used as the source signal for channel injection, thereby generating a frequency deflection; the influence of the carrier frequency deflection on the signal is conditionally estimated according to the difference in the output signal, and then the actual frequency deviation is inversely calculated, thereby achieving the goal of weakening the synchronization error and reducing the bit error rate of the 5G system, only one training sequence is required, and the inversion operation is simpler and more effective, the accuracy is relatively higher, and the sensitivity to noise is further reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a circuit principle connection structure block diagram of the present invention.

[0017] Figure 2 This is an algorithm performance comparison chart of the present invention. DETAILED DESCRIPTION

[0018] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the technical solutions of the present application are further described in detail below through embodiments and in combination with the accompanying drawings. It should be understood that the specific implementation method described here is only an optimal embodiment of the present application, which is only used to explain the present application and does not limit the protection scope of the present application. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0019] The performance of 5G systems depends largely on the interference levels of ISI and ICI, which in turn depends on the orthogonality of OFDM symbols, which in turn depends on the impact of carrier frequency offset. Therefore, how to estimate and control carrier frequency offset becomes a very important task. To this end, many scholars have conducted active research on this, including the pilot-based Classen algorithm and the training symbol-based Moose algorithm.

[0020] LTE is a communication system currently being developed by 3GPP. By adopting the multi-channel method of OFDM (Orthogonal Frequency Division Multiplexing), the subcarriers overlap with each other, which greatly improves the spectrum efficiency of the system and is very suitable for high data rate wireless transmission. This is one of the reasons why LTE can greatly improve cell throughput compared to 2 / 3G technology.

[0021] The problem is that OFDM can only perform well when each subcarrier maintains its orthogonality, and is very sensitive to synchronization errors. The TSI (Intern Symbol Interference) present in the multipath fading channel of the actual wireless environment will cause carrier frequency deviation CFO and symbol timing deviation STO (Symbol Timing Offset), resulting in increased bit error rate and reduced LTE system performance.

[0022] In addition, the slight frequency deviation between the transmitter carrier frequency and the receiver local oscillator, as well as the Doppler frequency shift caused by the relative motion of the communicating sender and receiver can also lead to the generation of CFO.

[0023] The above algorithms either cannot completely eliminate the influence of background noise, or the estimation process will use inverse operations, which will additionally increase the complexity of the algorithm.

[0024] The purpose of the present invention is to provide a 5G CFO estimation method based on triangular decomposition in order to ensure the orthogonality of OFDM subcarriers in an actual noisy channel, offset the influence of noise on carrier frequency deviation, further reduce synchronization errors, and improve the performance of the 5G system as much as possible.

[0025] In order to achieve the above-mentioned purpose, the present invention adopts the following technical scheme: a 5G CFO estimation method MTDCE (Matrix Trigonometric Decomposition based 5G CFO Estimation Algorithm) based on triangular decomposition, which uses the triangular decomposition result of the noise signal as the source signal for channel injection, thereby generating a frequency deflection; according to the difference of the output signal, the influence of the carrier frequency deflection on the signal is conditionally estimated, and then the actual frequency deviation is inversely calculated, so as to achieve the goal of weakening the synchronization error and reducing the bit error rate of the 5G system.

[0026] The present invention evaluates noise by proposing a zero matrix source signal, and then performs triangular decomposition on the noise signal, reinjects the decomposed sub-matrix as the source signal into the channel, and synthesizes the output signal with other triangular decomposed sub-matrices to eliminate the interference of background noise on the signal, thereby obtaining the deflection effect of the actual frequency deviation on the input signal, and then estimating the carrier frequency deviation in the actual channel.

[0027] Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow charts describe the operations (or steps) as sequential processes, many of the operations (or steps) therein can be implemented in parallel, concurrently, or simultaneously. In addition, the order of the operations can be rearranged. The process can be terminated when its operation is completed, but can also have additional steps not included in the drawings; the process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0028] The technical solution of the present invention is further specifically described below through embodiments and in conjunction with the accompanying drawings.

[0029] Embodiment: A 5G CFO estimation method based on triangular decomposition in this embodiment is as follows: Figure 1 As shown, the following steps are included: S1. Establish a wireless transceiver channel, set the constant σ and 5G carrier frequency deviation ε, calculate the length of the transmitted signal, and combine the time domain variables and channel noise to obtain the signal deflection caused by the carrier frequency deviation. Calculate the length of the transmitted signal SL tr =power(σ,2), time domain variable n∈[0,SL tr -1], channel noise Nos ch (n), the signal deflection amount Sg caused by carrier frequency deviation CFO =Sg CFO (n,ε).

[0030] It also includes the input signal length SL trThe transmit signal S(n) is used to establish a receiving channel. Establishing a receiving channel T(n) = S(n)*Sg CFO +Nos ch (n).

[0031] S2. Estimating the noise in combination with the zero matrix source signal, specifically including generating a zero matrix source signal, injecting the zero matrix signal into the wireless transceiver channel, and measuring the output signal T0(n). Generate a zero matrix source signal, S0(n) = zeros(n), where zeros(·) represents a zero matrix generating function.

[0032] S3. Perform triangular decomposition on the noise signal, specifically including performing triangular decomposition on the output signal T0(n) to obtain L(n) matrix and U(n) matrix respectively, satisfying T0(n)=L(n)*U(n).

[0033] S4. The triangular decomposition result of the noise signal is used as the source signal for channel injection, thereby generating a frequency deviation. Specifically, L(n) is injected into the transceiver channel as the input signal S(n), and the output signal T1(n) is measured. It also includes calculating the frequency deviation signal based on the U(n) matrix and the output signal T1(n). Triangular decomposition helps to greatly reduce the complexity of the matrix inversion operation; the frequency deviation signal F(n) is calculated as inv(L)*T1(n)-U(n), where inv(·) represents the matrix inversion operation.

[0034] S5. Estimate the effect of carrier frequency deflection on the signal, and then calculate the actual frequency deviation. Specifically, calculate the discrete sum value according to the frequency deviation signal, and then calculate the actual frequency deviation value ε′. Calculate the discrete sum value Calculate Re CFO =log(Sm ch ), where log(·) represents the natural logarithm; the calculation process quantity ε′=Re CFO *SL tr / (PI*j*(SL tr -1)), where j represents the imaginary unit and PI represents the pi constant.

[0035] It also includes solving the real part function of the actual frequency deviation value ε′, and finally obtaining the 5G carrier signal frequency deviation. The 5G carrier signal frequency deviation Sg is obtained. CFO =RP(ε′), where RP(·) represents the function for solving the real part of an imaginary number.

[0036] A wireless transceiver channel is established, and the noise is estimated in combination with the zero-matrix source signal. On this basis, the noise signal is triangularly decomposed, and the triangular decomposition result of the noise signal is used as the source signal for channel injection, thereby generating a frequency deflection. The influence of the carrier frequency deflection on the signal is conditionally estimated based on the difference in the output signal, and then the actual frequency deviation is inversely calculated, thereby achieving the goal of weakening the synchronization error and reducing the bit error rate of the 5G system. Only one training sequence is required, and the inverse operation is simpler and more effective, with relatively higher accuracy and further reduced sensitivity to noise.

[0037] Example 2 The present invention comprises the following steps: (1-1): Establish a wireless transceiver channel; (1-2): Noise signal evaluation: (1-3): Triangular decomposition of noise signal; (1-4): Estimation of frequency offset CFO; Preferably, step (1-1) comprises the following steps: (2-1): Set constant σ, 5G carrier frequency deviation ε; calculate the transmission signal length SL tr =power(σ,2), where power(·) represents the power function; the time domain variable n∈[0,SL tr -1], channel noise Nos ch (n), the signal deflection amount Sg caused by carrier frequency deviation CFO =Sg CFO (n,ε); (2-2): The input signal length is SL tr The transmission S(n) establishes the receiving channel T(n) = S(n)*Sg CFO +Nos ch (n); Preferably, step (1-2) comprises the following steps: Generate a zero matrix source signal, S0(n)=zeros(n), where zeros(·) represents a zero matrix generating function; inject the zero matrix signal into the wireless transceiver channel, and measure the output signal T0(n); Preferably, step (1-3) comprises the following steps: (4-1): The output signal T0(n) measured above is triangularly decomposed to obtain L(n) matrix and U(n) matrix respectively, satisfying T0(n)=L(n)*U(n); (4-2): Inject L(n) as the input signal S(n) into the transceiver channel and measure the output signal T1(n); (4-3): Triangular decomposition helps to greatly reduce the complexity of matrix inversion operation; calculate the frequency deviation signal F(n) = inv(L)*T1(n)-U(n), where inv(·) represents the matrix inversion operation; Preferably, step (1-4) comprises the following steps: (5-1): Calculate the discrete sum (5-2): Calculate Re CFO =log(Sm ch ), where log(·) represents the natural logarithm; the calculation process quantity ε′=Re CFO *SL tr / (PI*j*(SL tr -1)), where j represents the imaginary unit and PI represents the pi constant; (5-3): Finally, the 5G carrier signal frequency deviation Sg is obtained CFO =RP(ε′), where RP(·) represents the function for solving the real part of an imaginary number; Starting from establishing a wireless transceiver channel, the noise is estimated in combination with the zero-matrix source signal. On this basis, the noise signal is triangularly decomposed, and the triangular decomposition result of the noise signal is used as the source signal for channel injection, thereby generating a frequency deflection. According to the difference in the output signal, the influence of the carrier frequency deflection on the signal is conditionally estimated, and then the actual frequency deviation is inversely calculated, thereby achieving the goal of weakening the synchronization error and reducing the bit error rate of the 5G system. Only one training sequence is required, and the inverse operation is simpler and more effective, with relatively higher accuracy and further reduced sensitivity to noise.

[0038] Therefore, the present invention can estimate the channel noise, and the noise sub-matrix can be obtained through triangular decomposition; the channel output signal can be measured by injecting the sub-matrix into the channel; the frequency deviation signal can be obtained by combining other sub-matrices of the triangular decomposition, and then the frequency deviation can be estimated; the present invention does not require a training sequence, and can use the triangular decomposition method of the matrix to simplify the amount of calculation as much as possible.

[0039] Example 3 like Figure 1 The embodiment shown is a 5G CFO estimation method based on triangular decomposition, including the steps of establishing a wireless transceiver channel, channel noise evaluation, triangular decomposition of the noise signal, and estimating frequency offset CFO.

[0040] Step 1: Establish a wireless transceiver channel; Step 1-1: Set constant σ, 5G carrier frequency offset ε; calculate the transmission signal length SL tr =power(σ,2), where power(·) represents the power function; the time domain variable n∈[0,SL tr-1], channel noise Nos ch (n), the signal deflection amount Sg caused by carrier frequency deviation CFO =Sg CFO (n,ε); Step 1-2: Input signal length is SL tr The transmission S(n) establishes the receiving channel T(n) = S(n)*Sg CFO +Nos ch (n); Step 2: Channel noise assessment; Generate a zero matrix source signal, S0(n)=zeros(n), where zeros(·) represents a zero matrix generating function; inject the zero matrix signal into the wireless transceiver channel, and measure the output signal T0(n); Step 3: triangular decomposition of noise signal; Step 3-1: Perform triangular decomposition on the output signal T0(n) measured above to obtain L(n) matrix and U(n) matrix respectively, satisfying T0(n)=L(n)*U(n); Step 3-2: Inject L(n) as the input signal S(n) into the transceiver channel and measure the output signal T1(n); Step 3-3: Triangular decomposition helps to greatly reduce the complexity of matrix inversion operation; calculate the frequency deviation signal F(n) = inv(L)*T1(n)-U(n), where inv(·) represents the matrix inversion operation; Step 4: Estimate frequency offset CFO Step 4-1: Calculate the discrete sum value Step 4-2: Calculate Re CFO =log(Sm ch ), where log(·) represents the natural logarithm; the calculation process quantity ε′=Re CFO *SL tr / (PI*j*(SL tr -1)), where j represents the imaginary unit and PI represents the pi constant; Step 4-3: Finally, the 5G carrier signal frequency deviation Sg is obtained CFO =RP(ε′), where RP(·) represents the function for solving the real part of an imaginary number; The present invention is specifically described below by taking σ=2 as an example, and typical basic data are shown in Table 1: Table 1 Typical basic data table Serial number project data 1 Signal-to-Noise Ratio (SNR) 20 2 Noise signal AWGN The 5G CFO estimation method based on triangular decomposition described in this example includes the steps of establishing a wireless transceiver channel, evaluating channel noise, triangular decomposing noise signals, estimating frequency offset CFO, etc.

[0041] Step 1: Establish a wireless transceiver channel; Step 1-1: Calculate the length of the transmitted signal SL tr =power(σ,2)=4 Time domain variable n∈[0,3], channel noise Nos ch (n), the signal deflection amount Sg caused by carrier frequency deviation CFO =Sg CFO (n,ε), using additive white Gaussian noise to generate the channel noise signal Nos ch (n)=awgn(rand(2,2)+i*rand(2,2),SNR) =[0.9487+1.0046i,0.2572+0.851i; 1.0702+0.4i,1.0708 +0.2572i] Step 1-2: Input signal length is SL tr The transmission S(n) establishes the receiving channel T(n) = S(n)*Sg CFO +Nos ch (n); Step 2: Channel noise assessment; Generates source signal for zero matrix S0(n)=zeros(n)=[0,0;0,0] Inject the zero matrix signal into the above wireless transceiver channel and measure the output signal T0(n). T0(n)=[0.9487+1.0046i,0.2572+0.851i; 1.0702+0.4i,1.0708+0.2572i] Step 3: triangular decomposition of noise signal; Step 3-1: Perform triangular decomposition on the output signal T0(n) measured above. [L(n),U(n)]=lu(T0(n)) get L(n)=[1,0;0.7422-0.3644i,1] U(n)=[0.9487+1.0046i,0.2572+0.851i; 0,0.5698-0.2807i] Step 3-2: Inject L(n) as the input signal S(n) into the transceiver channel and measure the output signal T1(n). T1(n)=[1.9487+1.0046i,1.2572+0.8603i; 2.8123+0.0542i,2.816 -0.0725i] Step 3-3: Calculate the frequency deviation signal F(n)=inv(L)*T1(n)-U(n) =[1,1+0.0093i;0.9998+0.0185i,0.9996+0.0278i] Step 4: Estimate frequency offset CFO Step 4-1: Calculate the discrete sum value Step 4-2: Calculation Re CFO =log(Sm ch )=-0.0001+0.0139i Calculate process quantity Step 4-3: Finally, the 5G carrier signal frequency deviation Sg is obtained CFO =RP(ε′)=0.0059.

[0042] Starting from establishing a wireless transceiver channel, the noise is estimated in combination with the zero-matrix source signal. On this basis, the noise signal is triangularly decomposed, and the triangular decomposition result of the noise signal is used as the source signal for channel injection, thereby generating a frequency deflection. According to the difference in the output signal, the influence of the carrier frequency deflection on the signal is conditionally estimated, and then the actual frequency deviation is inversely calculated, thereby achieving the goal of weakening the synchronization error and reducing the bit error rate of the 5G system. Only one training sequence is required, and the inverse operation is simpler and more effective, with relatively higher accuracy and further reduced sensitivity to noise.

[0043] Simulation experiment: The MTDCE method of the present invention and the previous TTSE algorithm based on dual training sequences were simulated on the MATLAB platform. Figure 2 shown.

[0044] CFO carrier frequency deviation estimation in 5G system belongs to one of the OFDM orthogonal frequency division multiplexing synchronization technologies. OFDM transmits message data in parallel on its orthogonal subcarriers. Only when orthogonality is maintained can OFDM play its technical advantages, otherwise the system performance will be reduced due to the mutual interference ICI (Inter-Carrier Interference) between the subcarriers. The factors that affect OFDM orthogonality include STO and CFO. Therefore, it is very necessary to accurately estimate the CFO of the 5G system.

[0045] To this end, the author publicly authorized a CFO estimation method based on dual training sequences, TTSE, as early as December 14, 2018, with the patent number ZL201610349050.X. By adding dual training sequences, the dual signals generated by the noise channel are synthesized to capture the frequency deflection factor, and finally the estimated CFO is obtained. The TTSE method based on sequence difference is relatively simple and can further eliminate the influence of background noise, but there are two problems: first, the complexity of the inverse operation for random source signals is high; second, two sequences need to be input for training; these factors will affect the accuracy of deflection factor capture.

[0046] To this end, the present invention designs a 5G CFO estimation method based on triangular decomposition. Starting from establishing a wireless transceiver channel, the noise is estimated in combination with a zero-matrix source signal. On this basis, the noise signal is triangularly decomposed, and the decomposed sub-matrix is ​​used as the source signal to capture the actual carrier frequency deviation. Compared with TTSE, this method only requires one training sequence, and the inverse operation is simpler and more effective, the accuracy is relatively higher, and the sensitivity to noise is further reduced.

[0047] In order to achieve the above-mentioned purpose, the present invention adopts the following technical scheme: a 5G CFO estimation method MTDCE (Matrix Trigonometric Decomposition based 5G CFO Estimation Algorithm) based on triangular decomposition, which uses the triangular decomposition result of the noise signal as the source signal for channel injection, thereby generating a frequency deflection; according to the difference of the output signal, the influence of the carrier frequency deflection on the signal is conditionally estimated, and then the actual frequency deviation is inversely calculated, so as to achieve the goal of weakening the synchronization error and reducing the bit error rate of the 5G system.

[0048] The present invention evaluates noise by proposing a zero matrix source signal, and then performs triangular decomposition on the noise signal, reinjects the decomposed sub-matrix as the source signal into the channel, and synthesizes the output signal with other triangular decomposed sub-matrices to eliminate the interference of background noise on the signal, thereby obtaining the deflection effect of the actual frequency deviation on the input signal, and then estimating the carrier frequency deviation in the actual channel.

[0049] From the comparison results, it can be seen that under the same signal-to-noise ratio (SNR), the MTDCE and TTSE methods have a smaller minimum mean square error (MSE) than the TTSE algorithm. The reason is that MTDCE performs LU decomposition on the noise and uses the obtained L matrix to inject the source signal. Compared with TTSE, which uses ordinary source signals, the difference is that when locking the frequency deviation signal, the source signal needs to be inverted, and LU decomposition helps to greatly reduce the complexity of the inverse operation, thereby improving the accuracy of CFO estimation. In addition, TTSE needs to inject two training sequences, while MTDCE only needs one training sequence, and the training method is simpler. As reflected in the simulation results, MTDCE has better performance in the presence of noise.

[0050] The specific embodiments described herein are merely examples of the spirit of the present invention. The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be construed as limiting the scope of the present application. It should be noted that a technician in the technical field to which the present application belongs may make various modifications or supplements to the described specific embodiments or replace them in a similar manner, but will not deviate from the spirit of the present application or exceed the scope defined in the attached claims. For a person of ordinary skill in the art, multiple variations and improvements may also be made without departing from the concept of the present application. Therefore, the scope of protection of the present application shall be subject to the attached claims.

Claims

1. A 5G CFO estimation method based on triangular decomposition, characterized in that: The following steps are involved: S1. Establish a wireless transceiver channel; S2. Estimating the noise by combining the zero matrix source signal; S3. Perform triangular decomposition on the noise signal; S4. The triangular decomposition result of the noise signal is used as a source signal to inject into the channel, thereby generating a frequency deflection; S5. Estimate the impact of carrier frequency deviation on the signal, and then reversely calculate the actual frequency deviation.

2. The 5G CFO estimation method based on triangular decomposition according to claim 1, characterized in that: The step S1 sets the constant σ and the 5G carrier frequency deviation ε, calculates the length of the transmitted signal, and obtains the signal deflection amount caused by the carrier frequency deviation by combining the time domain variables and the channel noise.

3. The 5G CFO estimation method based on triangular decomposition according to claim 2, characterized in that: The step S1 also includes: the input signal length is SL tr The transmitted signal S(n) is used to establish a receiving channel.

4. The 5G CFO estimation method based on triangular decomposition according to claim 1, characterized in that: The step S2 specifically includes generating a zero matrix source signal, injecting the zero matrix signal into a wireless transceiver channel, and measuring the output signal T0(n).

5. The 5G CFO estimation method based on triangular decomposition according to claim 4, characterized in that: The step S3 specifically includes performing triangular decomposition on the output signal T0(n) to obtain an L(n) matrix and a U(n) matrix respectively.

6. The 5G CFO estimation method based on triangular decomposition according to claim 5, characterized in that: The step S4 specifically includes injecting L(n) as the input signal S(n) into the transceiver channel and measuring the output signal T1(n).

7. The 5G CFO estimation method based on triangular decomposition according to claim 6, characterized in that: The step S4 also includes calculating a frequency deviation signal according to the U(n) matrix and the output signal T1(n).

8. The 5G CFO estimation method based on triangular decomposition according to claim 7, characterized in that: The step S5 of estimating the frequency offset CFO specifically includes calculating a discrete sum value according to the frequency offset signal, and then calculating to obtain an actual frequency offset value ε′.

9. The 5G CFO estimation method based on triangular decomposition according to claim 8, characterized in that: The step S5 also includes solving the real function of the actual frequency deviation value ε′ to finally obtain the frequency deviation of the 5G carrier signal.

10. A 5G CFO estimation method based on triangular decomposition according to claim 5, 6 or 7, characterized in that: The L(n) matrix is ​​combined with the output signal T1(n) to perform an inversion operation, and triangular decomposition is used to reduce the complexity of the matrix inversion operation.

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