Method for suppressing co-frequency interference of WCDMA system satellite signals based on array signal processing

Abstract

The application provides a WCDMA system satellite signal co-frequency interference suppression method based on array signal processing, and belongs to the field of WCDMA system satellite signal co-frequency interference suppression. The application comprises: interference detection on received WCDMA digital signals to determine whether there is interference at present; using array channel correction, array data reconstruction and other technologies to pretreat the signals determined to have interference; using the pretreated signals to perform interference suppression. The application adopts the interference suppression technology of array signal processing, and under the condition of not performing channel estimation, uses the characteristics of array signals, combines multiple time domain signal taps, and adaptively suppresses interference signals, so as to achieve the purpose of suppressing multiple interference signals of different directions and intensities, and meanwhile, the signal noise ratio is not reduced.

Description

Technical Field

[0001] This invention relates to the field of co-channel interference suppression of WCDMA satellite signals, and more particularly to a method for co-channel interference suppression of WCDMA satellite signals based on array signal processing. Background Technology

[0002] WCDMA satellite signals are commonly used in satellite communications, and terrestrial third-generation mobile communication technologies also use WCDMA signals. Therefore, satellite signals are frequently interfered with by ground base station signals or mobile phone signals, and these interfering signals often operate in the same frequency band as the WCDMA satellite signals. Due to the long distance between the satellite and the ground receiver in satellite communication, the satellite signal received by the ground receiver is weak and more susceptible to interference from nearby WCDMA signals operating in the same frequency band. Interference with WCDMA satellite signals significantly increases the bit error rate during decoding by the ground receiving station, leading to reduced communication efficiency or even communication failure. Therefore, a new method is needed to address co-channel interference with WCDMA satellite signals, ensuring accurate reception and decoding of WCDMA satellite signals by the ground receiving station. The most common method for suppressing co-channel interference in WCDMA systems in existing technologies is multi-user detection (MSD). Interference cancellation detectors in MSD are an important means of solving co-channel multiple access interference. The basic idea is to feed back the decision symbol to the receiver, reconstruct each interfering signal at the receiver, and subtract the reconstructed interference from the received signal. Serial interference cancellation can effectively solve the problem of co-channel multiple access interference in WCDMA systems. However, the power of co-channel multiple access interference in terrestrial systems is relatively small compared to the target signal. For strong interference signals with high power, traditional serial interference cancellation methods are not ideal. Summary of the Invention

[0003] To address the limitations of traditional WCDMA interference cancellation methods in terms of accuracy and poor suppression of interference from WCDMA satellite signals with low target signal power and high interfering signal power, this invention provides a co-channel interference suppression method for WCDMA satellite signals based on array signal processing. This method employs interference suppression calculations using array signal processing, eliminating the need for channel estimation, and can simultaneously suppress interference signals from multiple incoming directions with varying intensities, thus possessing high application value.

[0004] The technical solution adopted in this invention is:

[0005] A method for suppressing co-channel interference of WCDMA satellite signals based on array signal processing includes the following steps:

[0006] (1) Perform interference detection on the received WCDMA digital signal to determine whether there is interference;

[0007] (2) Preprocess the received signal using array channel correction, array data reconstruction and tapping methods;

[0008] (3) Use the preprocessed signal from step (2) to perform adaptive interference suppression.

[0009] Furthermore, the specific method of step (1) is as follows:

[0010] (101) Perform FFT processing to convert the received WCDMA digital signal from the time domain signal to the frequency domain signal;

[0011] (102) Using the frequency domain signal in step (101), the detection threshold and judgment condition are obtained by constant false alarm rate detection method;

[0012] (103) Using the detection threshold and judgment conditions in step (102), determine whether there is an interference signal in the frequency domain signal of step (101).

[0013] Furthermore, the specific method of step (2) is as follows:

[0014] (201) Perform channel correction on the received array signal. Let the input array signal be s = [s1, s2, ..., s2]. M ] T Where M is the number of array elements, and the channel calibration coefficient a = [a1, a2, ..., a M ] T The calibrated signal x is represented as x = s × a; where a is a complex vector, and x = [x1, x2, ..., x...]. M ] T ;

[0015] (202) Beam pointing is performed on the calibrated signal x from step (201), where the first channel is the beamforming channel, and the other M-1 channels are beam difference channels; assuming the satellite signal arrival angle is θ, the receiving array is a uniform linear array with M elements and the element spacing is d, and the steering vector is A, then Where λ is the wavelength of the WCDMA satellite signal; the beam and channel are represented as y1 = A H *x, where the superscript H denotes the conjugate transpose, and the m-th beam difference channel is represented as y. m =A(m-1)'*x(m-1)-A(m)'*x(m), m=2,3,...,M, where the superscript ' indicates the conjugate transpose, A(m) represents the m-th element of A, and x(m) represents the m-th element of x;

[0016] (203) Using the beam difference channel data y in (202) mBy adding time taps, we obtain the data of the tapped delay line. The data vector after tapping is represented as Y. m =[y m,0 ,y m,1 ,y m,2 ,...,y m,P ] T In each item's subscript, m represents the m-channel of the difference beam, P represents the number of time-domain taps, and the data vector of all tap delay lines is represented as follows:

[0017] Furthermore, the specific method of step (3) is as follows:

[0018] (301) Calculate the autocorrelation matrix R using the data vector Y of the tapped delay line in step (2):

[0019] R = E{Y(2:end)*Y H (2:end)}

[0020] Where E{*} represents the statistical average, and Y(2:end) represents the second to last elements of the Y vector;

[0021] (302) Calculate the cross-correlation vector C:

[0022] C=E{Y(2:end)*Y'(1)}

[0023] (303) Calculate the optimal weight vector W using the autocorrelation matrix R and cross-correlation vector C from steps (301) and (302):

[0024] W=R -1 *C

[0025] The optimal weight vector for adaptive interference suppression is obtained:

[0026]

[0027] in:

[0028] W m =[w m,1 ,w m,2 ,...,w m,P ] T m=1

[0029] W m =[w m,0 ,w m,1 ,...,w m,P ] T m≠1

[0030] W m Each item in the table is an adaptive weighting coefficient;

[0031] (304) Using the optimal weight vector from step (303), calculate the output signal for interference suppression:

[0032] y o =y1-W H *Y(2:end).

[0033] Compared with the prior art, the present invention has the following advantages:

[0034] 1. This invention can suppress co-channel interference signals without the need for channel estimation;

[0035] 2. This invention can simultaneously suppress multiple co-frequency interference signals from multiple directions;

[0036] 3. The method of the present invention suppresses interference while minimizing signal-to-noise ratio loss.

[0037] In summary, this invention employs interference suppression technology using array signal processing. Without performing channel estimation, it utilizes the characteristics of array signals and combines multiple time-domain signal taps to adaptively suppress interference signals, thereby achieving the goal of suppressing interference signals with multiple incoming directions and different intensities, without reducing the signal-to-noise ratio. Attached Figure Description

[0038] Figure 1 This is a schematic diagram of the interference suppression structure of the present invention.

[0039] Figure 2 This is a block diagram of the interference detection section.

[0040] Figure 3 This is a schematic diagram for interference detection.

[0041] Figure 4 This is a schematic diagram of the preprocessing section.

[0042] Figure 5 This is a schematic diagram of an arbitrary channel tap delay line structure.

[0043] Figure 6 This is a schematic diagram of the interference suppression part.

[0044] Figure 7 The image shows the spectrum of the simulation data before and after interference suppression.

[0045] Figure 8 The spectrum diagrams are before and after actual data interference suppression. Detailed Implementation

[0046] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0047] A method for suppressing co-channel interference of WCDMA satellite signals based on array signal processing includes the following steps:

[0048] (1) Perform interference detection on the received WCDMA digital signal to determine whether there is interference;

[0049] (2) Use array channel correction, array data reconstruction and other techniques to preprocess signals that are judged to have interference;

[0050] (3) Use the preprocessed signal from step (2) to suppress interference.

[0051] The method for determining whether there is interference in the received signal in step (1) is as follows:

[0052] First, the received signal is processed by FFT to convert the received WCDMA time-domain signal into a frequency-domain signal.

[0053] Then, using the obtained signal spectrum, the detection threshold and judgment conditions are calculated.

[0054] Finally, using the obtained detection threshold and judgment conditions, the frequency domain signal is judged to determine whether there is an interference signal.

[0055] The specific method for preprocessing the signal in step (2) is as follows:

[0056] First, channel correction is performed on the received array signal containing interference. Let the input array signal be s = [s1, s2, ..., s]. M ] T Where M is the number of array elements, and the channel calibration coefficient a = [a1, a2, ..., a M ] T The calibrated signal x can be expressed as x = s × a, where a is a complex number and x = [x1, x2, ..., x]. M ] T .

[0057] Then, the calibrated signal x is beam-pointed, with the first channel being the beam difference channel and the other (M-1) channels being the beam difference channels.

[0058] Assuming the satellite signal's direction of arrival is θ, the array is a uniform linear array with M elements and an element spacing of d, and the steering vector is A, then: Where λ is the wavelength of the WCDMA satellite signal. The beam and channel can be represented as y1 = A. H *x. Where 'H' denotes the conjugate transpose. The m-th difference channel (m = 2, 3, ..., M) is represented as: y m=A(m-1)'*x(m-1)-A(m)'*x(m). Where ''' denotes the conjugate transpose, A(m) represents the m-th element of A, and x(m) represents the m-th element of x.

[0059] Finally, for the beam difference data y m Tap the curve to obtain the data for the tapped delay line. The data vector after tapping is represented as: Y m =[y m,0 ,y m,1 ,y m,2 ,...,y m,P ] T The data vectors of all tapped delay lines are represented as follows:

[0060] The interference suppression method in step (3) is as follows:

[0061] The adaptive weight vector W is calculated using the data Y after the tapped delay line in step (2). The specific calculation method is as follows:

[0062] ① Calculate the autocorrelation matrix R, which is calculated as R = E{Y(2:end)*Y} H (2:end)}.

[0063] ② Calculate the cross-correlation vector C, which is calculated as C = E{Y(2:end)*Y'(1)}.

[0064] ③ Calculate the optimal weight vector W. The calculation equation is: W = R -1 *C, then we obtain the optimal weight vector for adaptive interference suppression:

[0065] in:

[0066] W m =[w m,1 ,w m,2 ,...,w m,P ] T m=1,W m =[w m,0 ,w m,1 ,...,w m,P ] T ,m≠1.

[0067] The optimal weight vector W is used to calculate the output signal for interference suppression. The specific calculation equation is as follows:

[0068] y o =y1-W H *Y(2:end).

[0069] Here is a more specific example:

[0070] Reference Figure 1 This is a structural diagram of a WCDMA satellite signal co-channel interference suppression method based on array signal processing, where the input signal D... m This represents the signal of channel m, where m = 1, 2, ..., M. It can be seen that it mainly includes three parts: interference decision, signal preprocessing, and interference suppression. Specifically, it includes the following steps:

[0071] Step 1: Perform interference detection on the received WCRMA digital signal to determine whether interference exists.

[0072] Step 2: Use array channel correction, array data reconstruction and other techniques to preprocess the signals that are identified as having interference;

[0073] Step 3: Use the preprocessed signal from step (2) to suppress interference;

[0074] refer to Figure 2 , Figure 3 The interference detection method in step 1 is as follows:

[0075] The received signal is processed using FFT to convert the received WCDMA time-domain signal into a frequency-domain signal. Using the obtained signal spectrum, a detection threshold and judgment condition are calculated. The detection threshold and judgment condition are then used to evaluate the frequency-domain signal to determine whether interference signals are present.

[0076] refer to Figure 4 , Figure 5 The preprocessing method in step 2 is as follows:

[0077] Channel correction is performed on the received array signal that contains interference. Let the input array signal be s = [s1, s2, ..., s]. M ] T Where M is the number of array elements, and the channel calibration coefficient a = [a1, a2, ..., a M ] T The calibrated signal x can be represented as x = s × a, where a is a complex matrix and x = [x1, x2, ..., x]. M ] T .

[0078] The calibrated signal x is beam-directed, with the first channel serving as the beamforming channel and the other (M-1) channels as beam difference channels. Assuming the satellite signal's direction of arrival angle is θ, the array is a uniform linear array with M elements and an element spacing of d, and the steering vector is A, then: Where λ is the wavelength of the WCDMA satellite signal.

[0079] The beam and channel can be represented as y1 = AH *x. Where 'H' represents the conjugate transpose.

[0080] The m-th difference channel (m = 2, 3, ..., M) is represented as: y m =A(m-1)'*x(m-1)-A(m)'*x(m). Where ''' denotes the conjugate transpose, A(m) represents the m-th element of A, and x(m) represents the m-th element of x.

[0081] For beam difference data y m Tap the line to obtain the data of the tap delay line.

[0082] The data vector after tapping is represented as: Y m =[y m,0 ,y m,1 ,y m,2 ,...,y m,P ] T .

[0083] The data vector of all tapped delay lines is represented as follows:

[0084] refer to Figure 6 The specific method for interference suppression in step 3 is as follows:

[0085] The adaptive weight vector W is calculated using the data Y after the tapped delay line in step (2). The specific calculation method is as follows:

[0086] ① Calculate the autocorrelation matrix R, which is calculated as R = E{Y(2:end)*Y} H (2:end)}.

[0087] ② Calculate the cross-correlation vector C, which is calculated as C = E{Y(2:end)*Y'(1)}.

[0088] ③ Calculate the optimal weight vector W. The calculation equation is: W = R -1 *C, then we obtain the optimal weight vector for adaptive interference suppression:

[0089]

[0090] in,

[0091] W m =[w m,1 ,w m,2 ,...,w m,P ] T m=1

[0092] W m =[w m,0 ,w m,1,...,w m,P ] T ,m≠1.

[0093] The optimal weight vector W is used to calculate the output signal for interference suppression. The specific calculation equation is y. o =y1-W H *Y(2:end).

[0094] refer to Figure 7 The image shows the effect of interference suppression before and after simulation data. The red dashed line represents the received signal spectrum before interference suppression, and the blue dashed line represents the signal spectrum after interference suppression. Interference signals that are significantly higher than the noise floor are effectively suppressed. (Reference) Figure 8 The image shows the effect before and after interference with real data.

[0095] In summary, this method first performs FFT transformation on the received array signal, then performs interference detection on the frequency domain signal; performs channel calibration on the array signal with interference, and then performs array data reconstruction, including beam sum calculation, beam difference calculation, and tapping each reconstructed data to obtain tapped delay lines; uses the tapped delay line data to obtain an adaptive weight vector; finally, subtracts the tapped data weighted by the adaptive weight vector from the interfering array signal to obtain the interference-suppressed signal.

[0096] The WCDMA satellite signal interference cancellation method designed in this invention can suppress interference from WCDMA satellite signals with low target signal power and high interfering signal power without channel estimation. Furthermore, this invention can simultaneously suppress multiple co-channel interference signals of various types, with minimal loss in signal-to-noise ratio.

Claims

1. A method for suppressing co-channel interference of WCDMA satellite signals based on array signal processing, characterized in that, Includes the following steps: (1) Perform interference detection on the received WCDMA digital signal to determine whether interference exists; (2) Preprocess the received signal using array channel correction, array data reconstruction, and tapping methods; the specific method is as follows: (201) Perform channel correction on the received array signal, assuming the input array signal is... Where M is the number of array elements and the channel calibration coefficient. The calibrated signal Represented as ;in For complex vectors, ; (202) The calibrated signal from step (201) Beam pointing is performed, with the first channel being the beamforming channel and the other M-1 channels being beam difference channels; assuming the satellite signal's direction of arrival angle is... The receiving array is a uniform linear array with M elements and an element spacing of d. Let the steering vector be... ,but ,in The wavelength of the WCDMA satellite signal is given; the beam and channel are represented as... The superscript H indicates the conjugate transpose, and the m-th beam difference channel is represented as... , superscript This indicates the conjugate transpose. express The One element, express The One element; (203) Using the beam difference channel data in (202) By adding time taps, we obtain the data of the tapped delay line. The data vector after tapping is represented as follows: In each item's subscript, m represents the m-channel of the difference beam, P represents the number of time-domain taps, and the data vector of all tap delay lines is represented as follows: ; (3) Adaptive interference suppression is performed using the preprocessed signal from step (2); the specific method is as follows: (301) Calculate the autocorrelation matrix R using the data vector Y of the tapped delay line in step (2): in, To obtain the statistical average, This represents the second to the last element of the Y vector; (302) Calculate the cross-correlation vector C: (303) Calculate the optimal weight vector W using the autocorrelation matrix R and cross-correlation vector C from steps (301) and (302): The optimal weight vector for adaptive interference suppression is obtained: in: W m Each item in the table is an adaptive weighting coefficient; (304) Using the optimal weight vector from step (303), calculate the output signal for interference suppression: 。 2. The WCDMA satellite signal co-channel interference suppression method based on array signal processing according to claim 1, characterized in that, The specific method of step (1) is as follows: (101) Perform FFT processing to convert the received WCDMA digital signal from the time domain signal to the frequency domain signal; (102) Using the frequency domain signal in step (101), the detection threshold and judgment condition are obtained by constant false alarm rate detection method; (103) Using the detection threshold and judgment conditions in step (102), determine whether there is an interference signal in the frequency domain signal of step (101).

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