Communication receiving method for suppressing same-frequency interference based on zero-padding DFT (Discrete Fourier Transform)

Abstract

The invention discloses a communication receiving method for suppressing co-frequency interference based on zero-padding DFT (Discrete Fourier Transform), which relates to the technical field of communication and comprises the following steps of: establishing a receiving signal model x (m) containing multipath signals at an mth sampling moment; carrying out zero-padding DFT (Discrete Fourier Transform) on the received signal model x (m), establishing a beam vector S and a diagonal matrix T of the beam vector S, and constructing an equivalent relationship according to the beam vector S and the diagonal matrix T of the beam vector S; and solving a converted frequency vector a by using the beam vector S and the diagonal matrix T thereof, obtaining a frequency estimation value # imgabs0 # of the target, calculating an amplitude estimation value # imgabs2 # according to the frequency estimation value # imgabs1 # of the target, reconstructing a time domain sampling sequence s of a transmitted signal, and filtering. According to the invention, the same-frequency interference can be effectively suppressed, and the number of array elements required by a receiving array is smaller, so that the operand is greatly reduced, the estimation precision is higher, the conditions of high frequency domain information correlation and the like after zero-padding DFT are fully utilized, and compared with a traditional communication receiver, the precision is higher.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to a communication receiving method for suppressing co-channel interference based on zero-padding DFT transformation. Background Art

[0002] With the development of communication technology, wireless data transmission has been applied to various devices, such as mobile phones, Internet of Things devices, etc. Among them, suppressing the co-frequency interference of signals and extracting useful information is a key issue in improving communication quality in communication systems.

[0003] At present, co-channel interference is a common problem in the communication reception process. When the useful signal and the interference signal are at the same frequency, it is difficult for traditional reception methods to distinguish them. For example, in wireless communication, multiple users may use the same frequency band for communication, resulting in the signal received by the receiving end being subject to co-channel interference, thus affecting the correct demodulation and decoding of the signal.

[0004] Currently, no effective solution has been proposed for the problems in the related technologies. Summary of the invention

[0005] In view of the problems in the related art, the present invention proposes a communication receiving method for suppressing co-channel interference based on zero-padding DFT transform, which is used to solve the co-channel interference problem of wireless receivers and provide a higher-precision observation signal separation effect.

[0006] The technical solution of the present invention is achieved in this way:

[0007] A communication receiving method for suppressing co-channel interference based on zero-filling DFT transform comprises the following steps:

[0008] Establish a received signal model x(m) at the mth sampling time and including multipath signals;

[0009] Perform zero-padding DFT transformation on the received signal model x(m), establish the beam vector S and its diagonal matrix T, and construct an equivalent relationship based on the beam vector S and its diagonal matrix T;

[0010] Using the beam vector S and its diagonal matrix T, we can find the frequency vector a after conversion and obtain the target frequency estimate.

[0011] According to the frequency estimate of the target Calculate the amplitude estimate

[0012] Reconstruct the time domain sampling sequence s of the transmitted signal and filter it.

[0013] Furthermore, the step of establishing a received signal model x(m) at the mth sampling moment and including a multipath signal comprises the following steps:

[0014] Pre-calibrated at the mth sampling time, a typical receiving signal model with N antenna elements and H reaching the target number is expressed as:

[0015]

[0016] Where n = 1, 2, ..., N is the array element number index, h = 1, 2, ...H is the target number index; A h (m) is the amplitude of the hth received signal, is the phase of the hth received signal, d is the distance between two adjacent array elements, κ is the wavelength; q(n) is expressed as the variance is Zero-mean Gaussian white noise.

[0017] Furthermore, the step of constructing an equivalent relationship according to the beam vector S and its diagonal matrix T includes the following steps:

[0018] Calibrate the frequency of the hth received signal Performing zero-padding DFT transformation processing on the received signal s(m,n) includes the following steps:

[0019] Pad the receiver signal s(m,n) to M to obtain a zero-padding signal;

[0020] The Fourier transform of the zero-filled signal can be obtained:

[0021]

[0022] in,

[0023] Then the Fourier transform of s(m,n) is expressed as:

[0024]

[0025] So we get:

[0026] Construct beam vector S = [S(k1), S(k2), ..., S(k H )] T and the diagonal matrix of beam vectors T = diag[S(k1),S(k2),…,S(k H )];

[0027] Let a=[a1,a2,…,a H ] T , b (1) =[b0,b1,…,b H-1 ]T , b (2) =[b0,b1,…,b H-1 ] T ,

[0028]

[0029] Then we can get the following expression:

[0030] S+TW H a=W H-1 b (1) +W H-1 b (2) .

[0031] Further, the step of obtaining the frequency estimate of the target The following steps are involved:

[0032] Take H Fourier transform sample points to construct the beam vector S1 = [S(k1), S(k2), ..., S(k H )] T , and the diagonal matrix of beam vectors T1 = diag[S(k1),S(k2),…,S(k H )];

[0033]

[0034] and

[0035]

[0036] We get expression (a):

[0037]

[0038] Take 2H sample points different from the one selected in the first point Then we can get expressions (b) and (c) by the same logic:

[0039]

[0040] According to formula (a), formula (b) and formula (c), we have:

[0041]

[0042] We can get:

[0043] a=C -1 D

[0044] in,

[0045] By We can get:

[0046]

[0047] Obtain

[0048] Further, the step of calculating the amplitude estimate The following steps are involved:

[0049] Pad the receiver signal s(m,n) to M with zeros to obtain a zero-padding signal s′(m,n);

[0050] Performing Fourier transform on the zero-filled signal s′(m,n) yields:

[0051]

[0052] Take any two S′(k) values ​​S′(k1), S′(k1),…, S′(k H ), the above formula can be rewritten into matrix form:

[0053]

[0054] The obtained frequency estimate Substituting into the above formula, we can get the amplitude estimate of the received signal Assuming the phase is 0, it is expressed as:

[0055]

[0056] Furthermore, the step of reconstructing the time domain sampling sequence s of the transmitted signal and filtering it comprises the following steps:

[0057] According to the snapshot information at time m, the time domain sampling information of each signal at this time is estimated, which is expressed as:

[0058] By estimating the amplitude and phase information of the incident signal at each moment in turn, the time domain sampling sequence s of each incident signal can be reconstructed. h (m), m = 0, 1, ...;

[0059] In order to further optimize the time domain waveform s p (m), enhance its anti-noise effect, and restore the s p The (m) sequence is shaped by passing it through a Butterworth low-pass filter.

[0060] Beneficial effects of the present invention:

[0061] 1. The present invention can effectively suppress co-channel interference. The receiving method for suppressing co-channel interference proposed by the present invention is based on zero-filled DFT transformation, which has a positive effect on 5G network construction, WIFI interconnection, Internet of Vehicles, Internet of Ships, and Internet of Things, and enhances the anti-interference capability of the receiver.

[0062] 2. The present invention has a low computational complexity. Compared with a traditional communication receiver, the receiving array in the present invention requires fewer array elements, so the computational complexity is greatly reduced.

[0063] 3. The present invention has higher estimation accuracy. Its receiving method for suppressing co-channel interference is based on zero-padded DFT transformation, which makes full use of the strong correlation of frequency domain information after zero-padded DFT transformation. Compared with traditional communication receivers, its accuracy is higher. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0065] Figure 1 It is a flow chart of a communication receiving method for suppressing co-channel interference based on zero-padding DFT transformation according to an embodiment of the present invention;

[0066] Figure 2 The figure is a diagram showing the recovery effect of a received signal by a communication receiving method for suppressing co-channel interference based on zero-padding DFT transformation according to an embodiment of the present invention. DETAILED DESCRIPTION

[0067] The following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field belong to the scope of protection of the present invention.

[0068] According to an embodiment of the present invention, a communication receiving method for suppressing co-channel interference based on zero-padding DFT transformation is provided.

[0069] like Figure 1 As shown, according to an embodiment of the present invention, a communication receiving method for suppressing co-channel interference based on zero-padding DFT transformation includes the following steps:

[0070] Step S1, establishing a received signal model x(m) at the mth sampling time and including a multipath signal;

[0071] The steps include:

[0072] Pre-calibrated at the mth sampling time, a typical receiving signal model with N antenna elements and H reaching the target number is expressed as:

[0073]

[0074] Where n = 1, 2, ..., N is the array element number index, h = 1, 2, ...H is the target number index; A h (m) is the amplitude of the hth received signal, is the phase of the hth received signal, d is the distance between two adjacent array elements, κ is the wavelength; q(n) is expressed as the variance is Zero-mean Gaussian white noise.

[0075] Step S2: Perform zero-padding DFT transformation processing on the received signal model x(m), establish the beam vector S and its diagonal matrix T, and construct an equivalent relationship based on the beam vector S and its diagonal matrix T;

[0076] Among them, constructing an equivalent relationship according to the beam vector S and its diagonal matrix T includes the following steps:

[0077] Calibrate the frequency of the hth received signal Performing zero-padding DFT transformation processing on the received signal s(m,n) includes the following steps:

[0078] Step S201: pad the receiver signal s(m,n) to M with zeros to obtain a zero-padded signal;

[0079] Step S202: Perform Fourier transform on the zero-filled signal to obtain:

[0080]

[0081] in, Rewriting the above formula into a polynomial form, the Fourier transform of s(m,n) can be further written as:

[0082]

[0083] So we get:

[0084] Construct beam vector S = [S(k1), S(k2), ..., S(k H )] T and the diagonal matrix of beam vectors T = diag[S(k1),S(k2),…,S(k H )].

[0085] Let a=[a1,a2,…,a H ]T , b (1) =[b0,b1,…,b H-1 ] T , b (2) =[b0,b1,…,b H-1 ] T ,

[0086]

[0087]

[0088] Then we can get the following expression:

[0089] S+TW H a=W H-1 b (1) +W H-1 b (2) .

[0090] Step S3: Use the beam vector S and its diagonal matrix T to find the frequency vector a after conversion and obtain the target frequency estimate

[0091] Step S301: Take H Fourier transform sample points to construct a beam vector S1 = [S(k1), S(k2), ..., S(k H )] T , and the diagonal matrix of beam vectors T1 = diag[S(k1),S(k2),…,S(k H )];

[0092]

[0093] and

[0094]

[0095] We get expression (a):

[0096]

[0097] Step S302: Take 2H sample points different from the first point selected Then we can get expressions (b) and (c) by the same logic:

[0098]

[0099] Step S303, according to formula (a), formula (b) and formula (c), we have:

[0100]

[0101] We can get:

[0102] a=C -1 D

[0103] in, By We can get:

[0104]

[0105] After factoring the right side of the above equation, we can get α h Estimated value You can get

[0106]

[0107] Step S4: Estimated value based on the frequency of the target Calculate the amplitude estimate The steps include:

[0108] Step S401, pad the receiver signal s(m,n) to M with zeros to obtain a zero-padded signal s′(m,n); Step S402, perform Fourier transform on the zero-padded signal s′(m,n) to obtain:

[0109]

[0110] Take any two S′(k) values ​​S′(k1), S′(k1),…, S′(k H ), the above formula can be rewritten into matrix form:

[0111] Step S404: The obtained frequency estimation value Substituting into the above formula, we can get the amplitude estimate of the received signal Assuming the phase is 0, it is expressed as:

[0112]

[0113] Step S5: Reconstruct the time domain sampling sequence s of the transmitted signal and filter it.

[0114] Step S501, based on the snapshot information at time m, estimate the time domain sampling information of each signal at this time, expressed as:

[0115] Step S502, sequentially estimate the amplitude and phase information of the incident signal at each moment, and reconstruct the time domain sampling sequence s of each incident signal. h (m),m=0,1,…。

[0116] Step S503, in order to further optimize the time domain waveform s p(m), enhance its anti-noise effect, and restore the s p The (m) sequence is shaped by passing it through a Butterworth low-pass filter.

[0117] In addition, under a simulation condition, the details are as follows:

[0118] The wireless transmission signal is a linear frequency modulation wave with a sampling frequency of 50MHz. There are two target signals. The simulated noise background is Gaussian white noise, and the signal-to-noise ratio is 40dB.

[0119] Assume that the receiving noise of the receiver is independent and identically distributed zero-mean Gaussian white noise. is the angle estimate of the h-th target signal, is the estimated value of the amplitude of the nth target signal.

[0120] In this technical solution, under the above simulation conditions, the number of antennas is set to 16, the incident angle difference is 1 degree, the signal-to-noise ratio is 40dB, and zero padding is performed to 8N during zero-padding DFT calculation to obtain a comparison chart of the restored signal and the original signal. The results are as follows Figure 2 shown.

[0121] Specifically, from Figure 2 It can be seen that when the number of targets is 2, the signal restored by the present invention is highly consistent with the original signal, but the image has slight defects. After passing through a Butterworth low-pass filter, we can see that the defects of the restored signal can be well removed and there is basically no difference with the original signal. Therefore, it can be proved that the present invention can basically avoid co-channel interference and restore the transmission signal.

[0122] In summary, with the help of the above technical solution of the present invention, the following effects can be achieved:

[0123] 1. The present invention can effectively suppress co-channel interference. The receiving method for suppressing co-channel interference proposed by the present invention is based on zero-filled DFT transformation, which has a positive effect on 5G network construction, WIFI interconnection, Internet of Vehicles, Internet of Ships, and Internet of Things, and enhances the anti-interference capability of the receiver.

[0124] 2. The present invention has a low computational complexity. Compared with a traditional communication receiver, the receiving array in the present invention requires fewer array elements, so the computational complexity is greatly reduced.

[0125] 3. The present invention has higher estimation accuracy. Its receiving method for suppressing co-channel interference is based on zero-padded DFT transformation, which makes full use of the strong correlation of frequency domain information after zero-padded DFT transformation. Compared with traditional communication receivers, its accuracy is higher.

[0126] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. After considering the disclosure of the specification and the examples, those skilled in the art will easily think of other embodiments of the present disclosure. This application is intended to cover any modification, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the art that are not disclosed in the present disclosure. The specification and the examples are only regarded as exemplary, and the true scope and spirit of the present disclosure are indicated by the claims.

[0127] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A communication receiving method for suppressing co-channel interference based on zero-filling DFT transform, characterized in that: The following steps are involved: Establish a received signal model x(m) at the mth sampling time and including multipath signals; Perform zero-padding DFT transformation on the received signal model x(m), establish the beam vector S and its diagonal matrix T, and construct an equivalent relationship based on the beam vector S and its diagonal matrix T; Using the beam vector S and its diagonal matrix T, we can find the frequency vector a after conversion and obtain the target frequency estimate. According to the frequency estimate of the target Calculate the amplitude estimate Reconstruct the time domain sampling sequence s of the transmitted signal and filter it.

2. The communication receiving method for suppressing co-channel interference based on zero-filled DFT transform according to claim 1, characterized in that: The step of establishing a received signal model x(m) at the mth sampling moment and including a multipath signal comprises the following steps: Pre-calibrated at the mth sampling time, a typical receiving signal model with N antenna elements and H reaching the target number is expressed as: Where n = 1, 2, N is the array element number index, h = 1, 2, H is the target number index; A h (m) is the amplitude of the hth received signal, is the phase of the hth received signal, d is the distance between two adjacent array elements, κ is the wavelength; q(n) is expressed as the variance is Zero-mean Gaussian white noise.

3. The communication receiving method for suppressing co-channel interference based on zero-padding DFT transform according to claim 1, characterized in that: The step of constructing an equivalent relationship according to the beam vector S and its diagonal matrix T includes the following steps: Calibrate the frequency of the hth received signal Performing zero-padding DFT transformation processing on the received signal s(m,n) includes the following steps: Pad the receiver signal s(m,n) to M to obtain a zero-padding signal; The Fourier transform of the zero-filled signal can be obtained: in, Then the Fourier transform of s(m,n) is expressed as: So we get: Construct beam vector S = [S(k1), S(k2),, S(k H )] T and the diagonal matrix of beam vectors T = diag[S(k1),S(k2),,S(k H )]; Let a = [a1, a2,, a H T , b (1) = [b0, b1,, b H-1 T , b (2) = [b0, b1,, b H-1 T ,​​​ Then we can get the following expression: S+TW H a=W H-1 b (1) +W H-1 b (2) 。 4. The communication receiving method for suppressing co-channel interference based on zero-filled DFT transform according to claim 1, characterized in that: Step 1 to obtain the target frequency estimate The following steps are involved: Take H Fourier transform sample points to construct the beam vector S1 = [S(k1), S(k2),, S(k H )] T , and the diagonal matrix of beam vectors T1 = diag[S(k1),S(k2),,S(k H )]; and We get expression (a): Take 2H sample points different from the one selected in the first point Then we can get expressions (b) and (c) by the same logic: According to formula (a), formula (b) and formula (c), we have: We can get: a=C -1 D in, By We can get: Obtain 5. The communication receiving method for suppressing co-channel interference based on zero-filled DFT transform according to claim 1, characterized in that: Calculate the amplitude estimate as described in step The following steps are involved: Pad the receiver signal s(m,n) to M with zeros to obtain a zero-padding signal s′(m,n); Performing Fourier transform on the zero-filled signal s′(m,n) yields: Take any two S′(k) values ​​S′(k1),S′(k1),,S′(k H ), the above formula can be rewritten into matrix form: The obtained frequency estimate Substituting into the above formula, we can get the amplitude estimate of the received signal Assuming the phase is 0, it is expressed as:

6. The communication receiving method for suppressing co-channel interference based on zero-filled DFT transform according to claim 1, characterized in that: The step of reconstructing the time domain sampling sequence s of the transmitted signal and filtering it comprises the following steps: According to the snapshot information at time m, the time domain sampling information of each signal at this time is estimated, which is expressed as: By estimating the amplitude and phase information of the incident signal at each moment in turn, the time domain sampling sequence s of each incident signal can be reconstructed. h (m),m=0,1,; In order to further optimize the time domain waveform s p (m), enhance its anti-noise effect, and restore the s p The (m) sequence is shaped by passing it through a Butterworth low-pass filter.

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