A 5G CFO estimation method based on ideal channel

Abstract

The application discloses a 5G CFO estimation method based on an ideal channel, solves the problem that an existing method is complicated in algorithm and high in hardware requirement, and comprises the following steps: randomly generating a source signal and a noise signal with a set length; constructing a double-channel model comprising a normal channel and an ideal channel; obtaining a unitary matrix input signal according to the source signal, injecting the input signal into the double-channel model, calculating a received difference signal according to the double-channel model, and obtaining a target received signal by complex processing of the difference signal; synthesizing a deflection signal according to the target received signal and the input signal; marking a deflection variable, and measuring and calculating a carrier signal frequency offset. The application effectively avoids the interference of the noise signal, can obtain the deflection signal through simple superposition operation, can directly obtain the carrier signal offset according to the property of the unitary matrix, and further captures the carrier frequency offset, and the method is simple in operation, low in algorithm complexity, and simple, reliable and practical.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of 5G communication, in particular to a 5G CFO estimation method based on ideal channel. BACKGROUND

[0002] In theory, the 5G transmitter and receiver will generate the same frequency carrier, but the carrier frequency will be difficult to keep consistent due to the inherent physical characteristics of the oscillator, which is the frequency offset, which will produce the carrier frequency offset CFO. CFO will affect the timing synchronization of the symbol, causing ISI and ICI interference, affecting the orthogonality of OFDM, and increasing the bit error rate of the 5G system.

[0003] To this end, the author has publicly authorized a CFO estimation method based on double training sequence TTSE on December 14, 2018, with patent number ZL201610349050.X, by adding double training sequence, using double signals generated by noise channel to synthesize to capture the frequency offset factor, and then finally get the estimated CFO. TTSE can eliminate the influence of background noise with the help of double training sequence, but at the same time there are some problems: first, matrix inversion operation will be used in the process of estimating CFO, which will increase the complexity of the algorithm; second, double training sequence also improves the transmission requirements of the transmitted signal. Therefore, the present application designs a 5G CFO estimation method based on ideal channel, which simulates background noise by designing ideal channel, avoids noise interference by simple signal superposition, and can also obtain non-inverse operation input signal by singular value solution; by acquiring the received signal, the CFO is captured by the displacement of the deflection factor.

[0004] The Chinese invention patent with patent number ZL201610349050.X and the name of a CFO estimation method based on double training sequence TTSE, its scheme is to add double training sequence, use double signals generated by noise channel to synthesize to capture the frequency offset factor, and then finally get the estimated CFO. TTSE can eliminate the influence of background noise with the help of double training sequence, but at the same time there are some problems: first, matrix inversion operation will be used in the process of estimating CFO, which will increase the complexity of the algorithm; second, double training sequence also improves the transmission requirements of the transmitted signal. SUMMARY

[0005] The present application mainly solves the problems of complex algorithm and high hardware requirement of the existing method, and provides a 5G CFO estimation method based on ideal channel. By designing an ideal channel, background noise is simulated, noise interference is avoided by simple signal superposition, and the input signal of non-inverse operation is obtained by singular value solution. By means of the displacement of the deflection factor, the CFO is captured. In the actual noise channel, the orthogonality of each subcarrier of OFDM is ensured, the influence of noise on carrier frequency offset is offset, the synchronization error is further reduced, and the performance of 5G system is improved as much as possible.

[0006] The above technical problems of the present application are mainly solved by the following technical scheme: a 5G CFO estimation method based on ideal channel, comprising the following steps:

[0007] Step one: randomly generate source signals and noise signals of a certain length;

[0008] Step two: construct a double-channel model including normal channel and ideal channel;

[0009] Step three: obtain unitary matrix input signal according to source signal, inject input signal into double-channel model, calculate received difference signal according to double-channel model, and obtain target received signal by complex processing of difference signal;

[0010] Step four: synthesize deflection signal according to target received signal and input signal;

[0011] Step five: mark deflection variable and measure carrier signal frequency offset.

[0012] The present application obtains unitary matrix input signal by singular value solution of source signal, constructs normal channel and ideal channel without noise, avoids noise interference by mutual superposition of output signals, and then obtains complex deflection signal. According to the specificity of complex deflection signal, the actual carrier frequency offset is directly estimated, the synchronization error is weakened, and the purpose of reducing the error rate of 5G system is achieved. The present application effectively avoids the interference of noise signal, and the deflection signal can be obtained by simple superposition operation. According to the property of unitary matrix, the carrier signal deviation can be directly obtained, and then the carrier frequency deviation is captured. The method is simple in operation, low in algorithm complexity, simple, reliable and practical.

[0013] As a preferred scheme, step one specifically includes the following process:

[0014] (1-1): set constant n, 5G carrier frequency offset ε, calculate the length N of the transmitted signal,

[0015] N=power(n,2),

[0016] wherein power(·) represents a power function, a time domain variable n∈[0,N-1], a deflection signal caused by a carrier frequency offset δ=δ(n,ε);

[0017] (1-2): Randomly generate a source signal and a noise signal with a length of N. Denoted as a source signal s(n) and a noise signal w(n).

[0018] As a preferred solution, the double-channel model constructed in step two includes a 5G transmission signal model based on background noise and a 5G ideal channel model without background noise.

[0019] The 5G transmission signal model based on background noise is y(n)=x(n)*δ(n,ε)+w(n); the 5G ideal channel model without background noise is z(n)=x(n)+w(n); x(n) is an input signal.

[0020] As a preferred solution, obtaining the unitary matrix input signal in step three includes:

[0021] Perform singular value decomposition on the source signal to obtain [U,S,V]=svd(s), and take the obtained U(n) as the input signal, wherein svd(·) represents a singular value decomposition function of a matrix, and s represents a source signal. The obtained U(n) is taken as the input signal, x(n)=U(n). By injecting a unitary matrix at the input end, the signal deflection is measured, and the noise signal can be suppressed.

[0022] As a preferred solution, obtaining the target received signal in step three includes:

[0023] Obtain a received difference signal by the difference between the two channel models; the received difference signal g(n)=y(n)-z(n).

[0024] On the basis of the difference signal, perform complex processing, and add the difference signal and the input signal to obtain the target received signal. The target received signal q(n)=g(n)+x(n).

[0025] As a preferred solution, the specific process of step four includes:

[0026] Conjugate transpose the input signal to obtain a transposed input signal, and calculate the product of the transposed input signal and the target received signal to obtain a deflection signal;

[0027] Conjugate transpose the input signal x(n) to obtain a transposed input signal x * (n); calculate the deflection signal dt(n)=x * (n)*q(n)=x * (n)*(y(n)-z(n)+x(n)).

[0028] The superposition signal is obtained by superimposing the deflection signals, and the superposition component is obtained by dividing the superposition signal by the length value N. The superposition component dss(n) = ds(n) / N.

[0029] As a preferred solution, the step five of marking the deflection variable process includes:

[0030] (5-1): Calculate the deflection real number, and obtain the deflection coefficient according to the product of the deflection real number and the imaginary number;

[0031] Calculate the deflection real number Wherein, PI represents the constant of the circumference; calculate the deflection coefficient R t =R*j, wherein, j represents the imaginary unit;

[0032] (5-2): Calculate the logarithm of the superposition component to obtain the deflection superposition signal, and decouple the deflection superposition signal to obtain the intermediate variable about the frequency offset.

[0033] Calculate the deflection superposition signal γ(n) = log(dss(n)), wherein, log(·) represents the natural logarithm function;

[0034] Decouple γ(n) to obtain the intermediate variable Δ = γ(n) / R t .

[0035] As a preferred solution, the step five of measuring the carrier signal frequency offset process includes:

[0036] Calculate the real part of the intermediate variable to obtain the 5G carrier signal frequency offset.

[0037] The 5G carrier signal frequency offset ε = Re(Δ), wherein, Re(·) represents the real part of the solution.

[0038] Therefore, the advantages of the present application are: effectively avoiding the interference of noise signal, the deflection signal can be obtained by simple superposition operation, the carrier signal deviation can be directly obtained according to the properties of unitary matrix, and then the carrier frequency deviation is captured, the method operation is simple, the algorithm complexity is low, and the method is simple, reliable and practical. BRIEF DESCRIPTION OF DRAWINGS

[0039] Figure 1 is a flowchart of the present application;

[0040] Figure 2 is a performance comparison chart of the present application and other algorithms. DETAILED DESCRIPTION

[0041] The technical solutions of the present application will be further specifically described below by examples, and combined with the drawings.

[0042] Embodiment:

[0043] The embodiment is a 5G CFO estimation method based on an ideal channel, as shown in the following steps: Figure 1

[0044] Step one: randomly generate source signals and noise signals of a set length; the specific process includes the following steps:

[0045] (1-1): set a constant n, 5G carrier frequency offset ε, and calculate the length N of the transmitted signal,

[0046] N = power(n, 2),

[0047] where power(·) represents the power function, the time domain variable n ∈ [0, N-1], and the deflection signal δ = δ(n, ε) caused by the carrier frequency offset;

[0048] (1-2): randomly generate a source signal s(n) and a noise signal w(n) of length N.

[0049] Step two: build a double-channel model including a normal channel and an ideal channel; respectively,

[0050] The 5G transmission signal model based on background noise is:

[0051] y(n) = x(n) * δ(n, ε) + w(n);

[0052] The 5G ideal channel model without background noise is:

[0053] z(n) = x(n) + w(n); x(n) is the input signal.

[0054] Step three: obtain the unitary matrix input signal according to the source signal, inject the input signal into the double-channel model, calculate the received difference signal according to the double-channel model, and obtain the target received signal by complex processing of the difference signal; the specific process includes:

[0055] (3-1): singular value decomposition is performed on the source signal s(n) to obtain [U, S, V] = svd(s), and the obtained U(n) is used as the input signal, x(n) = U(n), where svd(·) represents the singular value decomposition function of the matrix.

[0056] (3-2): inject the input signal into the double-channel model to calculate the received difference signal g(n) = y(n) - z(n);

[0057] (3-3): obtain the target received signal q(n) = g(n) + x(n) by complex processing based on the difference signal.

[0058] Step four: synthesize the deflection signal according to the target received signal and the input signal; the specific process includes:​

[0059] (4-1) : the input signal x(n) is conjugate transposed to obtain the transposed input signal x * (n), and the deflection signal dt(n) = x * (n) * q(n) = x * (n) * (y(n) - z(n) + x(n)) is calculated.

[0060] (4-2) : the superposition signal of the deflection signal is solved The superposition component dss(n) = ds(n) / N is solved.

[0061] Step five: the deflection variable is marked, and the carrier signal frequency offset is calculated. Specifically, it includes:

[0062] (5-1) : the deflection real number is calculated, where PI represents the constant of the circumference; the deflection coefficient R t = R * j, where j represents the imaginary unit;

[0063] (5-2) : the deflection superposition signal γ(n) = log(dss(n)) is calculated, where log(·) represents the natural logarithm function, and dss(n) is the superposition component;

[0064] (5-3) : γ(n) is decoupled to obtain the intermediate variable Δ = γ(n) / R t about the frequency offset;

[0065] (5-4) : the 5G carrier signal frequency offset ε = Re(Δ) is calculated, where Re(·) represents the real part of the solution number.

[0066] The following will illustrate the implementation of the embodiment with specific examples. Taking n = 2 as an example, the typical basic data is shown in Table 1:

[0067] Serial number Item Data 1 Signal-to-noise ratio (SNR) 15 2 Noise signal AWGN

[0068] Table 1

[0069] A 5G CFO estimation method based on ideal channel, including the following steps:

[0070] (1-1) : the length of the transmitted signal N = power(n, 2) = 4 is calculated, the time domain variable n ∈ [0, 3], and the deflection signal δ = δ(n, ε) caused by the carrier frequency offset;

[0071] (1-2) : a source signal with a length of N is randomly generated

[0072] s(n) = rand(2, 2) + i * rand(2, 2)

[0073] = [0.1869 + 0.7094i, 0.4456 + 0.2760i; 0.4898 + 0.7547i, 0.6463 + 0.6797i]

[0074] and noise signal

[0075] w(n) = awgn(rand(2,2) + i*rand(2,2), 15)

[0076] = [0.6964 + 0.2641i, 0.8784 + 0.1373i; 0.0763 + 0.0158i, -0.1834 + 0.8628i].

[0077] Step two: build a double-channel model, including

[0078] 5G transmission signal model based on background noise:

[0079] y(n) = x(n)*delta(n, epsilon) + w(n);

[0080] 5G ideal channel model without background noise:

[0081] z(n) = x(n) + w(n); x(n) is the input signal.

[0082] (3-1): singular value decomposition is performed on the source signal s(n) to obtain [U, S, V] = svd(s), and U(n) obtained is taken as the input signal,

[0083] x(n) = U(n)

[0084] = [-0.2264 - 0.5143i, 0.4342 - 0.7041i; -0.3885 - 0.7303i, -0.2587 + 0.4989i].

[0085] (3-2): inject the input signal into the double-channel model, and calculate the received difference signal

[0086] g(n) = y(n) - z(n)

[0087] = [0.4441 - 0.6979i, -0.2079 - 0.5065i; -0.2657 + 0.4951i, -0.3938 - 0.7386i];

[0088] (3-3): composite processing is performed on the difference signal to obtain the target received signal

[0089] q(n) = g(n) + x(n)

[0090] = [0.2177 - 1.2122i, 0.2262 - 1.2106i; -0.6542 - 0.2351i, -0.6525 - 0.2398i].

[0091] (4-1): The input signal x(n) is conjugate transposed to obtain the transposed input signal

[0092] x * (n) = [-0.2264 + 0.5143i, -0.3885 + 0.7303i; 0.4342 + 0.7041i, -0.2587 - 0.4989i].

[0093] The deflection signal is calculated

[0094] dt(n) = x * (n) * q(n) = x * (n) * (y(n) - z(n) + x(n))

[0095] = [1.0000 - 0.0000i, 1.0000 + 0.0071i; 0.9999 + 0.0141i, 0.9998 + 0.0212i].

[0096] (4-2): The superposition signal of the deflection signal is solved

[0097]

[0098] The superposition component is solved

[0099] (5-1): The deflection real number is calculated The deflection coefficient R is calculated t = R * j = 0 + 2.3562i.

[0100] (5-2): The deflection superposition signal γ(n) = log(dss(n)) = -0.0000 + 0.0106i is calculated.

[0101] (5-3): The γ(n) is decoupled to obtain the intermediate variable about frequency offset

[0102]

[0103] (5-4): The 5G carrier signal frequency offset amount ε = Re(Δ) = 0.0045 is calculated.

[0104] Simulation experiment:

[0105] The method of the present application (referred to as ICCCE) is compared with the TTSE based on double training sequence and the Classen estimation algorithm based on pilot in terms of algorithm performance by MATLAB platform simulation, as shown in Figure 2

[0106] It can be seen from the comparison result that ICCCE has smaller minimum mean square error (MSE) than Classen method under the same signal-to-noise ratio (SNR), and the algorithm performance of ICCCE and TTSE is basically flat in the case of low SNR, but the performance of ICCCE shows a clear upward trend as the cell environment improves, and is better than TTSE, mainly because the latter introduces more complex inverse operation. At the same time, the mean square error jitter of ICCCE and TTSE is relatively slightly larger than that of Classen.

[0107] The specific embodiments described herein are merely illustrative of the spirit of the present application. Those skilled in the art of the present application can make various modifications or supplements to the described specific embodiments or replace them with similar ways, without departing from the spirit of the present application or exceeding the scope defined by the appended claims.​

Claims

1. A 5G CFO estimation method based on an ideal channel, characterized in that: Includes the following steps: Step 1: Randomly generate source signal and noise signal of a set length; Step 2: Construct a dual-channel model including a normal channel and an ideal channel; Normal channel = source signal * deflection signal + noise signal Ideal channel = source signal + noise signal; Step 3: Obtain the unitary matrix input signal based on the source signal, inject the input signal into the dual-channel model, calculate the received difference signal based on the dual-channel model, and add the difference signal to the input signal to obtain the target received signal; Step 4: Synthesize the deflection signal based on the target received signal and the input signal; Step 5: Mark the deflection variables and calculate the carrier signal frequency offset.

2. The 5G CFO estimation method based on an ideal channel according to claim 1, characterized in that: Step 1 in detail Includes the following processes: (1-1): Set a constant n, 5G carrier frequency offset, and calculate the transmitted signal length N. N = power(n, 2) Where power(·) represents the power function, the time-domain variable n∈[0,N-1], and the deflection signal δ=δ(n,ε) caused by the carrier frequency offset; (1-2): Randomly generate source signal and noise signal of length N.

3. The 5G CFO estimation method based on an ideal channel according to claim 1, characterized in that: The dual-channel model constructed in step two includes a 5G transmission signal model based on background noise and a 5G ideal channel model without background noise.

4. The 5G CFO estimation method based on an ideal channel according to claim 1, characterized in that: Step three involves obtaining the unitary matrix input signal, including: Perform singular value decomposition on the source signal to obtain [U,S,V]=svd(s), and use the obtained U(n) as the input signal, where svd(·) represents the singular value decomposition function of the matrix and s represents the source signal.

5. A 5G CFO estimation method based on an ideal channel according to claim 1, 2, 3, or 4, characterized in that: Step three, obtaining the target received signal, includes: The received difference signal is obtained by phase difference between the two channel models; Composite processing is performed on the difference signal.

6. The 5G CFO estimation method based on an ideal channel according to claim 1, characterized in that: Step four includes the following specific steps: The input signal is transposed by its conjugate to obtain the transposed input signal, and the deflection signal is obtained by multiplying the transposed input signal by the target received signal. The deflection signals are superimposed to obtain a superimposed signal, and the superimposed signal is divided by the length value N to obtain the superimposed component.

7. A 5G CFO estimation method based on an ideal channel according to claim 6, characterized in that the steps are... The five-stage labeling and deflection variable process includes: (5-1): Calculate the real number of the deflection, and obtain the deflection coefficient by multiplying the real number of the deflection by the imaginary number; (5-2): Obtain the deflection superposition signal by taking the logarithm of the superposition components, and decouple the deflection superposition signal to obtain the intermediate variable about the frequency offset.

8. A 5G CFO estimation method based on an ideal channel according to claim 7, characterized in that... Step five, the process of calculating the carrier signal frequency offset, includes: Solving for the real part of the intermediate variable yields the frequency offset of the 5G carrier signal.

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