A self-interference suppression method based on MVDR combined with coordinate zeroing

Abstract

The present invention discloses a self-interference suppression method based on MVDR combined with coordinate zeroing, comprising receiving signal data through each array element, estimating the direction of arrival of a desired signal using a DOA algorithm; processing the signal data using an MVDR beamforming algorithm based on the direction of arrival of the desired signal; mapping the residual error signal data after array processing into a Walsh domain, and taking any code element therein as information for processing; performing amplitude truncation on the signal in the Walsh domain to suppress a strong self-interference component, and returning to the time domain through inverse mapping. The present invention determines whether to perform an amplitude truncation operation by utilizing the relationship between the signal after Walsh domain transformation and a defined threshold. When the Walsh domain signal is greater than or equal to the defined threshold, the strong self-interference component in the Walsh domain signal is truncated and reset to zero. When the Walsh domain signal is less than the defined threshold, the original value is retained. The present invention realizes efficient target signal extraction and interference suppression in the case of unknown target direction, thereby improving the overall suppression depth.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to a self-interference suppression method based on MVDR combined with coordinate zeroing. Background Art

[0002] Traditional self-interference suppression methods focus on the following four areas: First, passive suppression methods in the propagation domain typically rely on the installation of sound barriers or isolation structures to reduce transmit-receive coupling. However, these methods are highly dependent on the actual platform structure and have limited suppression effectiveness in close-range, strong self-interference scenarios. Second, self-interference cancellation methods in the analog domain use a filter structure to adjust the amplitude and phase of the transmitted signal before subtracting it, offering advantages such as good real-time performance and front-end linear protection. However, these methods require extremely high accuracy in signal synchronization and amplitude matching, resulting in high implementation complexity and difficult system debugging.

[0003] Existing digital-domain adaptive filtering methods (such as LMS and RLS) build interference channel models for online learning and cancellation, demonstrating strong suppression capabilities under certain conditions. However, these methods are highly dependent on the quality of the reference signal and often require a high-fidelity transmit signal from the power amplifier output to achieve optimal results. This limits their application in low-power systems or scenarios with limited reference paths. Finally, traditional spatial-domain algorithms, such as conventional beamforming and multi-channel correlation cancellation, primarily rely on array structures to independently achieve interference suppression, lacking coordination with other processing domains, limiting overall suppression performance. Summary of the Invention

[0004] In view of the above-mentioned prior art, the present invention provides a self-interference suppression method based on MVDR combined with coordinate zeroing, which mainly solves the technical problems existing in the above-mentioned background technology.

[0005] To achieve the above-mentioned purpose, the technical solution of the embodiment of the present invention is implemented as follows:

[0006] A self-interference suppression method based on MVDR combined with coordinate zeroing includes the following steps:

[0007] Step 1: Each array element receives signal data and uses a DOA algorithm to estimate the direction of arrival of a desired signal, where the desired signal includes a far-end desired signal.

[0008] Preferably, the remote desired signal is , the near-end interference signal is , the direction of arrival angle is and , through the remote desired signal and near-end interference signals Calculate the output sound pressure when the two signals are independent. The calculation formula is:

[0009]

[0010] in, for Moment The output sound pressure of the array element is For array element right Array response coefficient for directional signals, For array element right Array response coefficient for directional signals, For the The interference background noise received by the array element.

[0011] Step 2: Use the MVDR beamforming algorithm to process the signal data based on the desired signal direction of arrival;

[0012] Preferably, the remote desired signal and near-end interference signals Both use spread spectrum modulation, which is the time domain multiplication of the modulation symbol and the spread spectrum code chip pulse.

[0013] Preferably, the MVDR beamforming algorithm is used to process signal data based on the desired signal arrival direction, including: constructing a signal model, defining a direction vector and a direction matrix, and outputting a signal matrix; when the beam output power reaches a minimum, the MVDR algorithm ensures that the signal output power in the desired direction remains unchanged, and obtains the optimal weight of the MVDR by constructing a cost function. When the interference power is much greater than the ambient noise power, the matrix inversion lemma is used to simplify the calculation of the inverse matrix of the space-time correlation matrix, and finally, the received signal at the final receiving end is output by adding the target signal, interference signal, and residual ambient noise.

[0014] Step 3: Map the residual error signal data after array processing into the Walsh domain and select any code element as information for processing;

[0015] Preferably, the residual error signal data after array processing is mapped into the Walsh domain, and any code element therein is randomly selected as information for processing, specifically comprising: constructing a cyclic cross matrix, mapping the signal after array processing into the Walsh domain, and randomly selecting a code element as information for processing, that is, achieving signal mapping in the Walsh domain through matrix multiplication.

[0016] Step 4: Perform amplitude truncation on the signal in the Walsh domain to suppress the strong self-interference component, and then return it to the time domain through inverse mapping.

[0017] Preferably, a threshold η is defined to perform an amplitude truncation operation on the Walsh domain signal to suppress a strong self-interference component. When the Walsh domain signal is less than the defined threshold, the original value is retained. When the Walsh domain signal is greater than or equal to the defined threshold, it is determined to be strong self-interference and the strong self-interference component in the Walsh domain signal is truncated and set to zero.

[0018] The beneficial effects of the present invention are:

[0019] (1) This paper proposes a blind beamforming method that does not rely on the signal direction. Combining the MVDR algorithm with the coordinate zeroing technology, it can achieve efficient target signal extraction and interference suppression when the target direction is unknown.

[0020] (2) The present invention constructs a joint interference suppression mechanism of spatial domain filtering and code domain zeroing, uses MVDR to spatially filter the main interference direction, and combines coordinate zeroing to further suppress residual interference in the code domain, significantly improving the overall suppression depth;

[0021] (3) The present invention enhances the robustness of the system under strong interference and low signal-to-noise ratio conditions, and can still stably extract the target signal in an interference-dominated channel environment;

[0022] (4) The overall algorithm structure of the present invention is modular, with low computational complexity, which makes it easy to integrate and implement in low-power devices and suitable for deployment on resource-constrained platforms. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 A flow chart of a self-interference suppression method based on MVDR combined with coordinate zeroing provided in an embodiment of the present application;

[0024] Figure 2 A schematic diagram of the angle of received signals provided in an embodiment of the present application; DETAILED DESCRIPTION

[0025] The technical solution of the present invention is further elaborated in detail below in conjunction with the drawings and specific embodiments of the specification. Unless otherwise defined, all technical and scientific terms used in this embodiment have the same meaning as those commonly understood by those skilled in the art to which the present invention belongs. The terms used in the specification of the present invention in this embodiment are only for the purpose of describing specific embodiments and are not intended to limit the present invention. In the following description, reference is made to "some embodiments", which describes a subset of all possible embodiments, but it should be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments, and can be combined with each other without conflict.

[0026] In the following description, numerous specific details are provided to provide a more thorough understanding of the present invention. However, it will be apparent to those skilled in the art that the present invention may be practiced without one or more of these details. In other instances, certain technical features well known in the art are not described to avoid confusion with the present invention.

[0027] It should be understood that the present invention can be implemented in different forms and should not be interpreted as being limited to the embodiments proposed herein. On the contrary, providing these embodiments will make the disclosure thorough and complete, and will fully convey the scope of the present invention to those skilled in the art. And the purpose of the terms used herein is only to describe specific embodiments and is not intended to limit the present invention. When used herein, the singular forms "one", "an" and "said / the" are also intended to include plural forms, unless the context clearly indicates another way. It should also be understood that the terms "comprising" and / or "comprising" when used in this specification determine the presence of the features, integers, steps, operations, elements and / or parts, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, parts and / or groups. When used herein, the term "and / or" includes any and all combinations of the relevant listed items.

[0028] It should also be noted that when an element is referred to as being "fixed to" another element, it may be directly on the other element or there may be an intermediate element. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be an intermediate element. The terms "vertical", "horizontal", "inner", "outer", "left", "right" and similar expressions used in this embodiment are for illustrative purposes only and do not represent the only implementation method.

[0029] In order to fully understand the present invention, a detailed structure will be provided in the following description to illustrate the technical solution proposed by the present invention. Optional embodiments of the present invention are described in detail below. However, in addition to these detailed descriptions, the present invention may also have other implementations.

[0030] Example 1

[0031] The embodiments of the present invention refer to the attached Figure 1 , provides a self-interference suppression method based on MVDR combined with coordinate zeroing, comprising the following steps:

[0032] Step 1: The array element receives signal data and uses a DOA algorithm to estimate the direction of arrival of the desired signal, where the desired signal includes a far-end desired signal.

[0033] In this embodiment, the signal is defined is the far-end desired signal, is the near-end interference signal, and For two different direction of arrival angles, assuming Direction of arrival angle is 30 degrees, Direction of arrival angle is 90 degrees, and the two signals are independent, then Moment The output sound pressure of the array element It can be expressed as:

[0034]

[0035] in, For array element right Array response coefficient for directional signals, For array element right Array response coefficient for directional signals, For the The interference background noise received by the array element is Gaussian white noise.

[0036] Step 2: Use the MVDR beamforming algorithm to process the signal data based on the desired signal direction of arrival;

[0037] In this embodiment, spread spectrum modulation is adopted for both the far-end desired signal and the near-end interference signal, which can be further expanded into a combination of corresponding modulation symbols and spread spectrum chip pulses. Therefore, the signal model is further clarified as follows:

[0038]

[0039] Among them, the symbol represents the convolution operation, 、 Respectively represent The near-end and far-end modulation symbols of symbol periods, and the spreading code sequences are respectively and Indicates that a single chip width ,in is the duration of a single symbol, and the delay of the far-end signal relative to the near-end signal is expressed as express, It is a chip shaping filter used to limit the signal bandwidth. is the chip period, For the chips, is the channel impulse response of the near-end signal, is the channel impulse response of the far-end signal, is additive white Gaussian noise.

[0040] Specifically, the direction vector It is represented by the direction of the incident plane wave incident on each array element, the direction vector It is defined in vector notation as:

[0041]

[0042] in, ) means there are 8 array elements in the column, each array element has a different position, representing the Array element pairs The response coefficient, represents the transpose symbol;

[0043] Direction Matrix It is represented by the direction of two incident plane waves incident on each array element, the direction matrix Defined in vector notation: The direction angle is and The inversion of the direction vector:

[0044]

[0045] Under plane wave conditions, for a uniform linear array:

[0046]

[0047] in: Expressed as the phase factor, is the phase difference parameter;

[0048]

[0049] Will Substituting in:

[0050]

[0051] in, is the array element spacing, is the speed of sound, is the signal wavelength, is the signal angular velocity. When the array element spacing is half the wavelength of the signal wave, then:

[0052]

[0053]

[0054] The weighted output signal of the matrix is :

[0055]

[0056] in is the weight vector, is the conjugate transpose of the weight vector:

[0057]

[0058] X is the signal matrix:

[0059]

[0060] in, is the receiving signal of the first and second signal sources;

[0061] Further, , for the first The waveform of a plane wave received by each array element.

[0062] Power corresponding to weighted output for:

[0063]

[0064] Where R is called the spatiotemporal correlation matrix:

[0065]

[0066] Where H represents the conjugate transpose, represents the ensemble mean.

[0067] In this embodiment, the MVDR algorithm minimizes the beam output power while ensuring that the signal output power in the desired direction remains unchanged. This can be expressed mathematically as follows:

[0068]

[0069]

[0070] First construct the cost function :

[0071]

[0072] Put the above formula Find the differential and set it to 0. Combined with the conditions, the optimal weight of MVDR is:

[0073]

[0074] in, is the inverse matrix of the spatiotemporal correlation matrix, is the direction vector The conjugate transpose of , the angular spectrum of the MVDR output is:

[0075]

[0076] When the interference power is much greater than the ambient noise power, the matrix inversion lemma can be used to Simplifying it:

[0077]

[0078] The square of the direction vector , is the ambient noise power, Represents received The power of the signal, is the unit matrix; the power of the interference signal in the output is:

[0079]

[0080] in, is the conjugate transpose of the MVDR weight vector. Since the uncorrelated interference power of the two signals is much greater than the desired signal power and the ambient noise power, we can obtain:

[0081]

[0082] in, is the number of array elements. Finally, the signal received by the receiver can be expressed as:

[0083]

[0084] in, is the residual environmental noise in the signal after being processed by the MVDR algorithm, let , the above formula can be simplified to:

[0085]

[0086] in, is the interference suppression coefficient, and the final received signal at the receiving end is obtained by adding the target signal, the interference signal and the residual environmental noise.

[0087] In this embodiment, when the signal direction is known, a more appropriate signal can be modified through beamforming to achieve better interference suppression in the first stage, thereby achieving a better cancellation effect. Examples include weighted summation beamforming, Bartlett beamforming, minimum mean square error beamforming, and minimum variance with multiple constraints.

[0088] Step 3: Map the residual error signal data after array processing into the Walsh domain and select any code element as information for processing;

[0089] In this embodiment, in order to further eliminate the residual self-interference component and protect the far-end signal from obvious loss, it is proposed to map the residual error signal to the Walsh domain for processing. Specifically, a circulant cross matrix is ​​constructed. , the array processed signal Mapped into the Walsh domain, any A code element As information, it is processed to obtain , that is, the signal is mapped in the Walsh domain through matrix multiplication to optimize the interference elimination effect:

[0090]

[0091] matrix The structure of the spreading code The cyclic shift is formed, and its mathematical expression is:

[0092]

[0093] Step 4: Perform amplitude truncation on the signal in the Walsh domain to suppress the strong self-interference component, and then return it to the time domain through inverse mapping.

[0094] In this embodiment, the energy of the near-end residual self-interference signal is effectively concentrated and enhanced through the Walsh domain cyclic interleaving operation, while the energy of the far-end signal, which has a weak correlation with the near-end spreading code, remains dispersed and is not significantly enhanced. Utilizing this characteristic, a threshold η can be defined to perform amplitude truncation on the Walsh domain signal to suppress the strong self-interference component:

[0095]

[0096] When the Walsh domain signal When the Walsh domain signal is less than the defined threshold η, the original value is retained. When it is greater than or equal to the defined threshold η, it is determined to be strong self-interference and the strong self-interference component in the Walsh domain signal is truncated and set to zero. Based on the maximum value of the cross-correlation function and the conservative estimation of the channel response, it is ensured that the far-end signal is not excessively weakened.

[0097] Specifically, to avoid the weakening effect of the threshold processing on the desired far-end signal and to facilitate threshold setting in an actual system, this embodiment assumes that the channel impulse response is normalized and changes slowly. Therefore, the convolution term can be approximately maximized, thereby obtaining a concise and conservative threshold estimate. The value of the threshold η must meet the following constraints:

[0098]

[0099] Where, represents the modulation symbol of the far-end signal, Represents the cross-correlation function between the near-end and far-end spreading code chips, and performs convolution operation. The cross-correlation function is specifically defined as:

[0100]

[0101] Represents the cross-correlation operation between signals. The signal after coordinate zeroing can be returned to the time domain through inverse mapping, which can further suppress the local self-interference signal and can be expressed as: , thereby improving the subsequent demodulation performance of the far-end signal.

[0102] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included in the scope of protection of the present invention. The scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A self-interference suppression method based on MVDR combined with coordinate zeroing, characterized in that: The following steps are involved: Step 1: Each array element receives signal data and uses a DOA algorithm to estimate the direction of arrival of a desired signal, where the desired signal includes a far-end desired signal. Step 2: Use the MVDR beamforming algorithm to process the signal data based on the desired signal direction of arrival; Step 3: Map the residual error signal data after array processing into the Walsh domain, and select the code elements one by one as information for processing; Step 4: Perform amplitude truncation on the signal in the Walsh domain to suppress the strong self-interference component, and then return it to the time domain through inverse mapping.

2. The self-interference suppression method based on MVDR combined with coordinate zeroing according to claim 1, characterized in that: Define the far-end expected signal as , the near-end interference signal is , the direction of arrival angle is and , through the far-end desired signal and near-end interference signals Calculate the output sound pressure when the two signals are independent. The calculation formula is: in, for Moment The output sound pressure of the array element is For array element right Array response coefficient for directional signals, For array element right Array response coefficient for directional signals, For the The interference background noise received by the array element.

3. The self-interference suppression method based on MVDR combined with coordinate zeroing according to claim 2, characterized in that: Expected signal at the far end and near-end interference signals Both use spread spectrum modulation, which is the time domain multiplication of the modulation symbol and the spread spectrum code chip pulse.

4. The self-interference suppression method based on MVDR combined with coordinate zeroing according to claim 3, characterized in that: The method of processing signal data using the MVDR beamforming algorithm based on the desired signal direction of arrival includes: constructing a signal model, defining a direction vector and a direction matrix, and outputting a signal matrix; The signal model is expressed as: Among them, the symbol represents the convolution operation, 、 Respectively represent The near-end and far-end modulation symbols of symbol periods, and the spreading code sequences are respectively and Indicates that a single chip width , is the duration of a single symbol, and the delay of the far-end signal relative to the near-end signal is expressed as express, is the chip shaping filter, is the chip period, For the chips, is the channel impulse response of the near-end signal, is the channel impulse response of the far-end signal, is additive Gaussian white noise; The direction vector and direction matrix are defined as follows: It is represented by the direction of the incident plane wave incident on each array element, the direction vector It is defined in vector notation as: in, ) means there are 8 array elements in the column, each array element has a different position, representing the Array element pairs The response coefficient, represents the transpose symbol; Direction Matrix It is represented by the direction of two incident plane waves incident on each array element, the direction matrix Defined in vector notation: The direction angle is and The inversion of the direction vector: Under plane wave conditions, for a uniform linear array: in: Expressed as the phase factor, is the phase difference parameter; Will Substituting in: in, is the array element spacing, is the speed of sound, is the signal wavelength, is the signal angular velocity. When the array element spacing is half the wavelength of the signal wave, then: The output signal matrix is: The weighted output signal of the matrix is : in is the weight vector, is the conjugate transpose of the weight vector: X is the signal matrix: in, is the receiving signal of the first and second signal sources; , for the first The waveform of a plane wave received by each array element; Power corresponding to weighted output for: Where R is called the spatiotemporal correlation matrix: Where H represents the conjugate transpose, represents the ensemble mean.

5. The self-interference suppression method based on MVDR combined with coordinate zeroing according to claim 4, characterized in that: The processing of signal data using the MVDR beamforming algorithm based on the desired signal arrival direction further includes: when the beam output power reaches a minimum, the MVDR algorithm ensures that the signal output power in the desired direction remains unchanged, which can be mathematically expressed as: By constructing the cost function : Put the above formula Find the differential and set it to 0. Combined with the conditions, the optimal weight of MVDR is: in, is the inverse matrix of the spatiotemporal correlation matrix, is the direction vector The conjugate transpose of , the angular spectrum of the MVDR output is: When the interference power is much greater than the ambient noise power, the matrix inversion lemma can be used to Simplifying it: The square of the direction vector , is the ambient noise power, Represents received The power of the signal, is the unit matrix; the power of the interference signal in the output is: in, is the conjugate transpose of the MVDR weight vector. Since the uncorrelated interference power of the two signals is much greater than the desired signal power and the ambient noise power, we can obtain: in, is the number of array elements. Finally, the signal received by the receiver can be expressed as: in, is the residual environmental noise in the signal after being processed by the MVDR algorithm, let , the above formula can be simplified to: in, is the interference suppression coefficient, which is the sum of the target signal, interference signal, and residual ambient noise to output the final received signal at the receiving end.

6. The self-interference suppression method based on MVDR combined with coordinate zeroing according to claim 5, characterized in that: The residual error signal data after array processing is mapped into the Walsh domain, and any code element is selected as information for processing, specifically including: constructing a cyclic cross matrix , the array processed signal Mapped into the Walsh domain, any A code element As information, it is processed to obtain , expressed as: matrix The structure of the spreading code The cyclic shift is formed, and its mathematical expression is: That is, the mapping of the signal in the Walsh domain is achieved through matrix multiplication.

7. The self-interference suppression method based on MVDR combined with coordinate zeroing according to claim 6, characterized in that: Through the cyclic crossover operation in the Walsh domain, the energy of the near-end residual self-interference signal is effectively concentrated and enhanced, while the energy of the far-end signal with weak correlation with the near-end spreading code remains dispersed and is not enhanced.

8. The self-interference suppression method based on MVDR combined with coordinate zeroing according to claim 7, characterized in that: Define the threshold η to perform amplitude truncation on the Walsh domain signal to suppress the strong self-interference component: When the Walsh domain signal When the Walsh domain signal is less than the defined threshold η, the original value is retained. When it is greater than or equal to the defined threshold η, it is determined to be strong self-interference and the strong self-interference component in the Walsh domain signal is truncated and set to zero.

9. The self-interference suppression method based on MVDR combined with coordinate zeroing according to claim 8, characterized in that: The value of the threshold η satisfies the following constraints: Where, represents the modulation symbol of the far-end signal, Represents the cross-correlation function between the near-end and far-end spreading code chips, and performs convolution operation. The cross-correlation function is specifically defined as: Represents the cross-correlation operation between signals. The signal after coordinate zeroing can be returned to the time domain through inverse mapping to suppress the local self-interference signal, which can be expressed as: 。

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