A co-channel interference suppression method, device, medium and product

Abstract

The application provides a same-frequency interference suppression method, device, medium and product, and relates to the field of communication. The method comprises the following steps: analyzing air interface multi-channel IQ data in a 5G downlink signal of a target base station received by a receiving end array antenna, and obtaining a channel impulse response between the target base station and the receiving end; combining a wave arrival angle estimation algorithm and a multipath detection technology to extract channel characteristics of the channel impulse response, and taking a wave arrival direction corresponding to the channel characteristics of the strongest path as the wave arrival direction of the target base station; judging whether the wave arrival direction of the target base station at two time points is the same, and whether the range of the change of the wave arrival direction angle of the target base station is less than the beam coverage range; if yes, analyzing air interface multi-channel IQ data received by the receiving end array antenna at the next time point; and if no, adjusting the receiving end phased array beam direction according to the channel characteristics. The application not only enhances the target base station received signal strength and weakens the interference received signal strength, but also is simple to deploy and does not need to be tested in advance.

Description

Technical Field

[0001] This invention relates to the field of communications, and in particular to a method, device, medium, and product for suppressing co-channel interference. Background Technology

[0002] In wireless communication systems, co-channel interference refers to the phenomenon where signals at the same or very close frequencies interfere with each other, leading to a degraded communication quality. This interference exists in various wireless communication systems, including but not limited to mobile communications, wireless local area networks (Wi-Fi), cellular networks, and satellite communications. Co-channel interference is caused by factors such as limited wireless spectrum resources, spectrum reuse, and limitations in the signal processing capabilities of the receiving end. With the rapid growth in the number of mobile communication users and data demand, wireless spectrum resources are becoming increasingly scarce. Therefore, communication systems need to enable communication for more users within limited spectrum resources.

[0003] In cellular communication systems, to improve frequency utilization and increase system capacity, frequency reuse is generally used for data transmission. This results in many small geographical areas using the same frequency within the service area covered by the provider; these small geographical areas are therefore called co-frequency cells. The interference generated between these co-frequency cells is called co-frequency interference. As these small geographical areas continue to fragment, the service area of ​​the base station shrinks, and the frequency reuse factor increases, co-frequency interference eventually replaces man-made noise and other interference, becoming the primary constraint on cellular communication systems. At this point, the mobile radio environment changes from a noise-limited environment to an interference-limited environment.

[0004] In recent years, with the development of wireless communication technology, more and more emerging technologies have sprung up like mushrooms after rain. Currently, commonly used co-channel interference suppression technologies include multi-user detection and signal separation technologies, such as multi-user detection, which is used to distinguish signals from different interference sources, as shown in the patent with Chinese patent publication number CN116980066A published in 2023; spectrum allocation and dynamic power control technologies, such as the patent with Chinese patent publication number CN116260547A published in 2023; smart antenna system technologies, such as the patent with Chinese patent publication number CN110673116A published in 2019; and communication service quality information based on actual measurements, such as the patent with Chinese patent publication number CN114095111A published in 2022.

[0005] Co-channel interference suppression needs to move towards simplification, low cost, and high efficiency. However, methods using pure mathematical algorithms consume a lot of computing power and are difficult to deploy in practice. Methods based on quality of service information are simple and effective, but require prior line testing to obtain deployment information. Summary of the Invention

[0006] The purpose of this invention is to provide a method, device, medium, and product for suppressing co-channel interference, in order to solve the problems that existing co-channel interference suppression methods are difficult to deploy and require prior testing, and cannot effectively suppress co-channel interference signals.

[0007] To achieve the above objectives, the present invention provides the following solution:

[0008] A method for suppressing co-channel interference includes:

[0009] The air interface multi-channel in-phase orthogonal data received by the receiver array antenna from the target base station's 5G downlink signal are analyzed to obtain the channel impulse response between the target base station and the receiver.

[0010] The channel features of the channel impulse response are extracted by combining the arrival angle estimation algorithm and multipath detection technology, the strongest path channel feature is selected, and the arrival direction corresponding to the strongest path channel feature is taken as the arrival direction of the target base station; the path channel features include the time delay domain, spatial domain and energy domain.

[0011] Determine whether the incoming wave direction of the target base station at the current moment is the same as that of the target base station at the previous moment, and whether the range of change of the incoming wave direction angle of the target base station is less than the beam coverage area.

[0012] If the incoming wave direction of the target base station at the current moment is the same as that of the target base station at the previous moment, and the angle change range of the incoming wave direction of the target base station is less than the beam coverage range, analyze the air interface multi-channel in-phase orthogonal data received by the receiving array antenna at the next moment.

[0013] If the incoming wave direction of the target base station at the current moment is different from that of the target base station at the previous moment, or if the angle change range of the incoming wave direction of the target base station is not less than the beam coverage range, the beam direction of the phased array at the receiving end is adjusted according to the channel characteristics so that the beam direction of the phased array at the receiving end is aligned with the incoming wave direction of the target base station.

[0014] Optionally, the air interface multi-channel in-phase orthogonal data in the 5G downlink signal of the target base station received by the receiving array antenna is analyzed to obtain the channel impulse response between the target base station and the receiving end, specifically including:

[0015] The receiving array antenna receives radio frequency signals in the environment and acquires air interface multi-channel in-phase orthogonal data from the 5G downlink signal of the target base station;

[0016] For each channel's air interface in-phase orthogonal data, orthogonal code division multiplexing is used to set the reference signals of different antenna ports on the same orthogonal code division multiplexing group time-frequency resources to obtain channel state information of multiple antennas at the same time-frequency position at the transmitting end;

[0017] Based on the channel state information, after radio frequency reception and orthogonal frequency division multiplexing demodulation at the receiving antenna, interference cancellation is performed on the reference signals of different antenna ports after aliasing within each orthogonal code division multiplexing group on the orthogonal frequency division multiplexing resource grid, and the channel impulse response between the target base station and the receiving end is extracted.

[0018] Optionally, the channel impulse response is:

[0019]

[0020] in, Let be the channel impulse response of antenna port p at time l, and n be the frequency domain length multiplexed within the current orthogonal code division multiplexing group; Let L be the channel frequency domain response at the k-th current orthogonal code division multiplexing group at time l; L is the length of the reference signal sequence.

[0021] Optionally, the channel features of the channel impulse response are extracted by combining the arrival angle estimation algorithm and multipath detection technology, and the strongest path channel features are selected, specifically including:

[0022] The channel impulse response is preprocessed to generate a preprocessed channel impulse response;

[0023] Construct the covariance matrix of the preprocessed impulse response, and determine the eigenvalues ​​and eigenvectors of the covariance matrix;

[0024] The eigenvalues ​​are sorted, and the sorted eigenvalues ​​are divided into large eigenvalues ​​and small eigenvalues. Based on the estimated source data, a first matrix is ​​constructed according to the eigenvectors corresponding to the large eigenvalues, and a second matrix is ​​constructed according to the eigenvectors corresponding to the small eigenvalues.

[0025] Using a multi-signal classification algorithm, a spatial spectrum is constructed based on the orthogonality of the first matrix and the second matrix;

[0026] Search for the spectral peaks of the spatial spectrum, use the angles corresponding to the spectral peaks as estimated values ​​of the incoming wave angle, and determine the strongest path channel characteristics.

[0027] Optionally, the covariance matrix R XX for:

[0028] R xx =E[XX H ] = AE[SS H A H +E[NN H ] = AR ss A H +R NN ;

[0029] Among them, RSS R is the autocorrelation matrix of the signal; NN Let E[XX] be the first noise autocorrelation matrix; H [ ] is the autocorrelation matrix of the first received signal, X is the received signal, H is the conjugate transpose operation; A is the array manifold matrix; E[SS H [] represents the second received signal autocorrelation matrix, and S represents the actual transmitted signal; E[NN] H ] is the second noise autocorrelation matrix, and N is additive white Gaussian noise.

[0030] Optionally, the spatial spectrum P MUSIC for:

[0031]

[0032] Among them, a H (θ) is the guide vector; θ is the angle; U N This is the noise matrix; This is the conjugate transpose of the noise matrix.

[0033] Optionally, the beam direction of the phased array at the receiving end is adjusted according to the channel characteristics so that the beam direction of the phased array at the receiving end is aligned with the direction of arrival of the target base station, specifically including:

[0034] The system acquires the incoming wave information at the current moment, the incoming wave information at the previous moment, and the angular resolution, delay judgment criteria, and amplitude judgment criteria of the phased array at the receiving end; the incoming wave information includes the incoming wave angle, delay, and amplitude.

[0035] Determine whether the absolute value of the difference between the current wave angle and the previous wave angle is greater than the angle resolution.

[0036] If so, update the incoming wave information of the current moment with the incoming wave information of the previous moment, so as to adjust the beam direction of the phased array at the receiving end, so that the beam direction of the phased array at the receiving end is aligned with the incoming wave direction of the target base station.

[0037] If not, save the incoming wave information at the current moment, use the incoming wave information at the current moment as the incoming wave information at the previous moment, use the incoming wave information at the next moment as the incoming wave information at the current moment, and return "determine whether the absolute value of the difference between the incoming wave angle at the current moment and the incoming wave angle at the previous moment is greater than the angle resolution".

[0038] A computer device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described co-channel interference suppression method.

[0039] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described method for suppressing co-channel interference.

[0040] A computer program product includes a computer program that, when executed by a processor, implements the above-described method for suppressing co-channel interference.

[0041] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0042] CIR extraction is performed on 5G downlink signals to obtain the channel characteristics between the target base station and the receiving mobile terminal, eliminating the influence of interference signals. Then, the DOA algorithm and multipath detection technology are used to extract channel parameters from the CIR to obtain the strongest path channel characteristics. Finally, the phased array beam direction of the receiving end is adjusted according to the strongest path channel characteristics to achieve real-time tracking. The phased array beam direction is aligned with the direction of arrival of the target base station to enhance the signal in that direction of arrival and suppress signals from other directions (interference). This not only enhances the received signal strength of the target base station and weakens the received interference signal strength, but also has simple deployment and does not require prior testing.

[0043] This invention does not require prior testing of the target scene to obtain the arrival angle information of base station signals at different locations. It only requires deploying an array antenna in actual application and obtaining DOA estimation in real time through a mobile terminal to feed back to the phased array to change the beam direction. The deployment is simple. Attached Figure Description

[0044] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0045] Figure 1 For terminal design drawings;

[0046] Figure 2 This is a flowchart of the co-channel interference suppression method provided in Embodiment 1 of the present invention;

[0047] Figure 3 This is a flowchart of obtaining multipath channel features based on MUSIC and multipath detection;

[0048] Figure 4 This is a schematic diagram of a uniform array antenna model;

[0049] Figure 5 This is a complete data processing flowchart in the C algorithm module;

[0050] Figure 6 A flowchart for handover determination based on channel characteristics;

[0051] Figure 7 This is a schematic diagram of an actual switching scenario;

[0052] Figure 8 This is a flowchart of co-channel interference suppression provided in Example 2. Detailed Implementation

[0053] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0054] The purpose of this invention is to provide a method, device, medium, and product for suppressing co-channel interference, which not only enhances the received signal strength of the target base station and weakens the received signal strength of the interference signal, but also is simple to deploy and does not require prior testing.

[0055] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0056] Example 1

[0057] The terminal design diagram of this invention is as follows: Figure 1 As shown, A1 is an array antenna, which is a linear array used to receive radio frequency signals from the environment and output positioning information. D is the control terminal, and B and F are both adjustable attenuators. D controls B and F to adjust their attenuation values. C is the algorithm module. The input IQ signal is processed by the C algorithm module to output the current target base station's location information, which is then transmitted to the control module D, and finally to E. E is a phased array antenna that performs beam switching after acquiring the location information from D, providing the user with the input radio frequency signal.

[0058] like Figure 2 As shown, the present invention provides a method for suppressing co-channel interference, comprising:

[0059] Step 201: Analyze the air interface multi-channel in-phase orthogonal data in the 5G downlink signal of the target base station received by the receiving array antenna, and obtain the channel impulse response between the target base station and the receiving end.

[0060] In practical applications, step 201 specifically includes: receiving radio frequency signals in the environment using the array antenna at the receiving end, and acquiring air interface multi-channel in-phase orthogonal data in the 5G downlink signal of the target base station; for each channel's air interface in-phase orthogonal data, using orthogonal code division multiplexing, setting the reference signals of different antenna ports on the same orthogonal code division multiplexing group time-frequency resources, and acquiring channel state information of the same time-frequency position of multiple antennas at the transmitting end; based on the channel state information, after radio frequency reception and orthogonal frequency division multiplexing demodulation by the receiving antenna, interference cancellation is performed on the reference signals of different antenna ports after aliasing in each orthogonal code division multiplexing group on the orthogonal frequency division multiplexing resource grid, and the channel impulse response between the target base station and the receiving end is extracted.

[0061] Furthermore, a passive channel measurement platform is used to conduct channel detection and data parsing.

[0062] The deployment of 5G base stations enables the reception of signals from 5G base stations in a wireless environment; these signals are called downlink signals. Passive channel data acquisition involves receiving radio frequency signals and performing operations such as synchronization, demodulation, and frequency domain resource extraction for 5G downlink signals to eliminate interference and obtain the channel impulse response between the receiving terminal and the target base station. This process is referred to as Channel Impulse Response (CIR) analysis below.

[0063] The downlink signals currently available for obtaining CIR include the demodulation reference signal (DMRS) in the downlink physical broadcast channel (PBCH), downlink physical control channel (PDCCH), and downlink physical shared channel (PDSCH), as well as the separately existing channel state information reference signal (CSIRS).

[0064] Before testing, it is necessary to determine the carrier frequency for receiving 5G public network signals, and pre-set the spacing of the antenna array and the arrangement of the array according to the carrier frequency. The terminal receives radio frequency signals from the environment through array antenna A1, obtains multi-channel in-phase / quadrature data (IQ), and then inputs it into the C algorithm module to perform CIR decoding on the in-phase / quadrature data (IQ) of each channel. Finally, the IQ data of the corresponding channel is converted into CIR to eliminate the influence of interference sources, including other base stations.

[0065] During channel data parsing, the impact of multiple antennas at the transmitting end must be considered, and interference cancellation must be performed. For the downlink reference signal on the base station side, orthogonal code division multiplexing (CDM) is typically used to map the reference signals from different antenna ports onto the same set of time-frequency resources to obtain accurate channel state information at the same time-frequency location of multiple antennas at the transmitting end. Therefore, after the receiver completes radio frequency reception and orthogonal frequency division multiplexing (OFDM) demodulation, interference cancellation must be performed on the OFDM resource grid for the aliased reference signals from different antenna ports within each CDM group to extract the reference signals from different antenna ports and obtain multi-antenna channel information.

[0066] Frequency domain channel measurement is performed using orthogonal codes as follows:

[0067]

[0068] in, Let p be the channel frequency domain response of the k-th current orthogonal code division multiplexing group at time l, and p be the transmitting antenna port. , respectively, represent the offset values ​​of the subcarriers within the CDM group relative to the starting time-frequency position of the CDM; m and n represent the time-domain and frequency-domain lengths of a single CDM group, respectively; Y is the reference signal extracted after demodulation at the receiver, and I is the local standard reference signal. Equation (1) treats the CDM group as a whole, maintains the equal spacing of the reference signal, completes the elimination of the multiplexed signals of the remaining antennas, and thus completes the extraction of the frequency domain response of multiple antennas at the same time-frequency position. Equation (2) can be used to calculate the CIR corresponding to antenna port p at time l, where L is the length of the reference signal sequence.

[0069]

[0070] in, Let be the channel impulse response of antenna port p at time l, and n be the frequency domain length multiplexed within the current orthogonal code division multiplexing group; Let be the channel frequency domain response of the k-th current orthogonal code division multiplexing group at time l.

[0071] Step 201 eliminates interference signals in the multi-channel in-phase orthogonal data of the air interface and directly extracts the channel impulse response between the target base station and the receiver.

[0072] Step 202: Combine the arrival angle estimation algorithm and multipath detection technology to extract the channel features of the channel impulse response, screen out the strongest path channel features, and take the arrival direction corresponding to the strongest path channel features as the arrival direction of the target base station; the path channel features include the time delay domain, spatial domain and energy domain.

[0073] In practical applications, step 202 specifically includes: preprocessing the channel impulse response to generate a preprocessed channel impulse response; constructing the covariance matrix of the preprocessed channel impulse response and determining the eigenvalues ​​and eigenvectors of the covariance matrix; sorting the eigenvalues ​​into large and small eigenvalues, and constructing a first matrix based on the eigenvectors corresponding to the large eigenvalues ​​and a second matrix based on the eigenvectors corresponding to the small eigenvalues ​​according to the estimated source data; constructing a spatial spectrum based on the orthogonality of the first and second matrices using a multi-signal classification algorithm; searching for spectral peaks in the spatial spectrum, using the angles corresponding to the spectral peaks as estimated arrival angles, and determining the strongest path channel characteristics.

[0074] Furthermore, unlike traditional radar signal processing, using the DOA estimation algorithm to process the channel impulse response can directly obtain the multipath arrival angle information of the target base station's transmitted signal. At the same time, multipath detection of the CIR can obtain multipath arrival delay and energy information. The multipath detection algorithm is described in the author's paper "Multi-Frequency Channel Measurement and Characteristic Analysis in Forested Scenario for Emergency Rescue" published in December 2023. Combining the two algorithms can obtain complete information on the multipath arrival angle.

[0075] The DOA algorithm can employ classic subspace-based classification algorithms, such as the classic Multiple Signal Classification (MUSIC) algorithm and the Estimation Signal Parameter via Rotational Invariance Techniques (ESPRIT) algorithm, or iterative Space-Alternating Generalized Expectation-maximization (SAGE) algorithm.

[0076] This invention can achieve co-channel interference suppression using a relatively low-precision MUSIC algorithm. Other algorithms can also be considered, but their complexity is relatively high. Figure 3 The flowchart for obtaining multipath channel features based on MUSIC and multipath detection is as follows: Figure 3 As shown.

[0077] Taking an array antenna as an example, the specific process of the MUSIC algorithm is described; other array types are similar.

[0078] The model of a uniform linear array (ULA) antenna is as follows: Figure 4 As shown.

[0079] The signal model of ULA is then:

[0080] X(t)=AS(t)+N(t) (3)

[0081] Where X(t) is the array data, A is the array manifold matrix, S(t) is the spatial signal, and N(t) is the noise. The array manifold matrix A is represented by equation (4).

[0082]

[0083] in, a(θ i ) is the steering vector; θ is the angle; j is the imaginary unit; λ is the wavelength; N is the number of sources; M is the number of array antennas; d is the spacing between adjacent arrays; i is the index of different sources; and the covariance matrix of X(t) is represented by formula (5).

[0084] R xx =E[XX H ] = AE[SS H A H +E[NN H ] = AR ss A H +R NN (5)

[0085] Among them, R SS R is the autocorrelation matrix of the signal; NN Let E[XX] be the first noise autocorrelation matrix; H [ ] is the autocorrelation matrix of the first received signal, X is the received signal, H is the conjugate transpose operation; A is the array manifold matrix; E[SS H [] represents the second received signal autocorrelation matrix, and S represents the actual transmitted signal; E[NN] H ] is the second noise autocorrelation matrix, and N is additive white Gaussian noise.

[0086] By analyzing R XX The eigenvalues ​​are sorted as follows: β1≥β2≥…≥β N ≥β N+1 =…β M =σ, and the noise matrix U is formed by pairing the eigenvectors corresponding to the large eigenvalues ​​according to the estimated number of information sources. S The small eigenvalues ​​correspond to the eigenvectors that form the noise matrix U. N The MUSIC algorithm utilizes U S and U N The orthogonality is used to construct a spatial spectrum, and then the estimated value of DOA is obtained through spectral peak search. Based on the orthogonality, we have:

[0087] a H (θ)U N =0 (6)

[0088] Equation (6) does not hold under non-ideal conditions. According to spatial spectrum theory, the spectral function is obtained as follows:

[0089]

[0090] Among them, a H (θ) is the guide vector; θ is the angle; This is the conjugate transpose of the noise matrix.

[0091] Since the signal subspace and noise subspace are orthogonal, the MUSIC spatial spectrum will have a maximum when 0 equals the incident angle of the signal. Therefore, it is only necessary to search for spectral peaks within the range of e, and the angles corresponding to the spectral peaks are the estimated values ​​of DOA.

[0092] After using the MUSIC algorithm for DOA estimation, the receiver angle distribution spectrum of the channel between the target base station and the terminal was obtained. The angle spectrum obtained by the MUSIC algorithm reflects the energy intensity information of incoming waves from different directions. Then, the angle spectrum is searched for peaks to obtain the strongest incoming wave direction information. The complete data processing flow in the C algorithm module is as follows: Figure 5 As shown.

[0093] Step 203: Determine whether the incoming wave direction of the target base station at the current moment is the same as that of the target base station at the previous moment, and whether the angle change range of the incoming wave direction of the target base station is less than the beam coverage range. If yes, proceed to step 204; otherwise, proceed to step 205.

[0094] Step 204: Analyze the next moment's air interface multi-channel in-phase orthogonal data received by the receiving array antenna.

[0095] Step 205: Adjust the beam direction of the phased array at the receiving end according to the channel characteristics, so that the beam direction of the phased array at the receiving end is aligned with the incoming wave direction of the target base station.

[0096] In practical applications, step 205 specifically includes: acquiring the incoming wave information at the current moment, the incoming wave information at the previous moment, and the angular resolution, delay judgment standard, and amplitude judgment standard of the receiving phased array; the incoming wave information includes the incoming wave angle, delay, and amplitude; determining whether the absolute value of the difference between the incoming wave angle at the current moment and the incoming wave angle at the previous moment is greater than the angular resolution; if yes, updating the incoming wave information at the current moment with the incoming wave information from the previous moment to adjust the beam direction of the receiving phased array so that the beam direction of the receiving phased array is aligned with the incoming wave direction of the target base station; if no, saving the incoming wave information at the current moment, using the incoming wave information at the current moment as the incoming wave information from the previous moment, using the incoming wave information from the next moment as the incoming wave information from the current moment, and returning "determining whether the absolute value of the difference between the incoming wave angle at the current moment and the incoming wave angle at the previous moment is greater than the angular resolution".

[0097] Furthermore, in mobile communication scenarios, there are Line of Sight (LOS) and Non-Line of Sight (NLOS) wireless transmission scenarios. The direct path may be interrupted by obstacles that suddenly appear in the dynamic environment, thus turning the LOS scenario into an NLOS scenario. Switching according to the direction of the strongest path can maximize the received signal energy in real time. When the main path reappears or enters the next target base station, the beam needs to be switched accordingly. Therefore, the method based on determining the direction of the strongest wave of arrival does not need to distinguish between LOS and NLOS situations; it only needs to align the phased array beam with the direction of the strongest wave of arrival to obtain the maximum received signal strength under the current channel propagation environment. In addition to changes in the propagation scenario, there are also cases of inter-cell handover. The principle is the same as above; by switching to the direction of the strongest wave of arrival, the best reception effect can be obtained. Since the passive channel detection and analysis (CIR) has already implemented the function of selecting target base stations, it is only necessary to compare and select the strongest wave of arrival channel characteristics information of the CIR to achieve coverage enhancement for the target base station. The current incoming channel characteristic information output from algorithm module C is input into control module D. Control module D stores the incoming channel characteristic information from the previous moment. Module D can be implemented using a software radio module. Figure 6 The flowchart for handover determination based on channel characteristics is as follows: Figure 6 As shown.

[0098] Figure 6 In this context, θ”, τ”, and A” represent the arrival angle, delay, and amplitude at the current moment, while θ’, τ’, and A’ represent the arrival angle, delay, and amplitude stored in module D at the previous moment. Δθ, Δτ, and ΔA represent the phased array angular resolution, delay judgment standard, and amplitude judgment standard. The phased array angular resolution is set according to the actual engineering configuration, such as 5°. The delay judgment standard is determined according to the actual scenario, such as 100ns. The amplitude judgment standard is the same as above, and can be set to an empirical value of 15dB, etc., based on the difference between LOS and NLOS.

[0099] In summary, this invention not only updates the beam direction based on channel characteristics but also records changes in the propagation environment. As the mobile terminal's location changes, the beam direction is dynamically determined and adjusted. Figure 7 This is a schematic diagram of an actual switching scenario, such as... Figure 7 As shown, as the terminal moves, the beam direction will switch from base station E to base station F.

[0100] The D control module outputs the updated channel characteristic information to the E phased array (which is the phased array antenna used to track the base station). The E phased array then adjusts its beam direction based on the channel characteristic information. The phased array beam has a certain gain; when deviating from the effective beam range, the gain is relatively small. When the beam is aligned with the target base station, the energy of the target signal is amplified, while the energy of the interference signal is relatively weakened. In the co-channel interference area of ​​a co-channel network at the cell edge, the signal strength is similar, and the attrition is sufficient to enhance the target signal while weakening the interference signal. The mobile environment causes Doppler frequency shift in each path, and the multipath environment leads to a certain expansion of the Doppler spectrum. When this invention is used, the energy of the strongest path (LOS path or strongest multipath) is amplified, while the energy of the multipath is weakened, significantly reducing the Doppler expansion. This weakens time-selective fading, effectively reduces signal distortion caused by inter-symbol interference, and effectively improves the stability of the mobile communication system.

[0101] 1. This invention is simple to deploy. It only requires deploying an active phased array and an array antenna at the receiving end. It does not require any changes to the resource allocation of the existing communication system to achieve the purpose of suppressing co-channel interference. At the same time, it can also record changes in the channel propagation environment.

[0102] 2. By using a passive channel measurement platform to conduct detection and analysis, the CIR of 5G downlink signals is processed and obtained. The DOA algorithm is used to process the CIR to obtain the real-time direction of arrival. There is no need to set up a transmitter or conduct pre-tests to obtain route coverage information. It can achieve the purpose of dynamically analyzing the location of the target base station and performing beam tracking.

[0103] 3. The data parsing and DOA algorithm are simple and have high real-time performance. Furthermore, the DOA algorithm does not require high resolution complexity. Reducing the resolution of the DOA algorithm can also achieve the purpose of enhancing the signal energy of the target cell, which is highly efficient.

[0104] In summary, this invention does not require spectrum replanning. It utilizes existing base station deployment resources and leverages 5G downlink signals for real-time target base station location, demonstrating excellent applicability in areas with 5G coverage. It is not differentiated by cell type or specific scenario, exhibiting strong universality. It only requires the deployment of an active phased array and array antenna at the receiving end. The array antenna receives radio frequency signals to determine the direction of arrival, and real-time tracking is achieved by switching the phased array beam direction at the receiving end. This not only enhances the target base station's signal reception and reduces interference signals but also simplifies deployment, requires no prior testing, and offers real-time performance and high efficiency.

[0105] Example 2

[0106] An improvement is made to the co-channel interference suppression method provided in Example 1. Figure 8The flowchart for co-channel interference suppression provided in Example 2 is as follows: Figure 8 As shown, the specific steps include:

[0107] S1: Utilize a passive channel measurement platform to perform channel detection and data parsing. Parse the air interface IQ data received by the receiving array antenna to obtain the CIR between the target base station and the receiving terminal, thus eliminating the influence of interference sources.

[0108] S2: Combining DOA estimation algorithm, multipath detection method and CIR to extract channel features, obtain spatial domain, time delay domain and energy domain information, and then extract the strongest path channel features and identify them as the strongest path direction arrival angle information of the base station.

[0109] S3: Compare the incoming wave direction of the base station at the current moment with the incoming wave direction of the base station at the previous moment. If the identified base stations are the same and the angle change range of the incoming wave direction is less than the beam coverage range, return to S1; if the identified base stations are different, or the angle change range of the incoming wave direction exceeds the beam coverage range, proceed to the next step.

[0110] S4: Output the base station direction information to the phased array antenna for beam switching. After the switching is completed, return to S1 to perform the co-channel interference suppression process at the next moment.

[0111] The beam is switched to the angle of arrival of the target base station extracted in the previous steps at the current moment. After the switch, the purpose of enhancing the incoming signal of the target base station and suppressing signals from other directions has been achieved (i.e., suppressing co-channel interference).

[0112] This invention utilizes passive channel detection technology to extract the Channel Identifier (CIR) of 5G downlink signals, eliminating interference from other sources. It then employs the Direction of Array (DOA) algorithm and multipath detection technology to extract multipath channel features from the CIR, obtaining the strongest path's delay, spatial, and energy domain characteristics. Finally, the receiver's phased array beam direction is adjusted based on the strongest path's channel characteristics to suppress co-channel interference. This invention uses 5G downlink signal analysis technology for real-time target base station location, applicable to all 5G base station deployment areas, regardless of cell type or specific scenario, exhibiting strong versatility. Furthermore, it eliminates the need for spectrum replanning; by modifying the receiver's phased array beam direction within existing communication planning and deployment, real-time tracking is achieved. This not only enhances the target base station's received signal and weakens interference signals but also simplifies deployment without prior testing.

[0113] Example 3

[0114] A computer device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the co-channel interference suppression method of Embodiment 1.

[0115] Example 4

[0116] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the co-channel interference suppression method of Embodiment 1.

[0117] Example 5

[0118] A computer program product includes a computer program that, when executed by a processor, implements the co-channel interference suppression method of Embodiment 1.

[0119] Example 6

[0120] A computer device, which may be a database, includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage medium. The database stores pending transactions. The I / O interfaces facilitate information exchange between the processor and external devices. The communication interface enables communication with external terminals via a network connection. When executed by the processor, the computer program implements the co-channel interference suppression method described in Embodiment 1.

[0121] It should be noted that the object information (including but not limited to object device information, object personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this invention are all information and data authorized by the object or fully authorized by all parties, and the collection, use and processing of related data must comply with relevant laws, regulations and standards.

[0122] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided by this invention can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided by this invention may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided by this invention may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, etc., and are not limited to these.

[0123] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0124] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for suppressing co-channel interference, characterized in that, include: The air interface multi-channel in-phase orthogonal data received by the receiver array antenna from the target base station's 5G downlink signal are analyzed to obtain the channel impulse response between the target base station and the receiver; the channel impulse response is: in, Let be the channel impulse response of antenna port p at time l, and n be the frequency domain length multiplexed within the current orthogonal code division multiplexing group; Let L be the channel frequency domain response of the k-th current orthogonal code division multiplexing group at time l; L is the length of the reference signal sequence. Frequency domain channel measurement is performed using orthogonal codes as follows: in, Let p be the channel frequency domain response of the k-th current orthogonal code division multiplexing group at time l, and p be the transmitting antenna port. , respectively, are the offset values ​​of the subcarriers within the CDM group relative to the starting time-frequency position of the CDM; m and n are the time-domain and frequency-domain lengths of a single CDM group, respectively; Y is the reference signal extracted after demodulation at the receiver, and I is the local standard reference signal; The channel features of the channel impulse response are extracted by combining the arrival angle estimation algorithm and multipath detection technology, the strongest path channel feature is selected, and the arrival direction corresponding to the strongest path channel feature is taken as the arrival direction of the target base station; the path channel features include the time delay domain, spatial domain and energy domain. Determine whether the incoming wave direction of the target base station at the current moment is the same as that of the target base station at the previous moment, and whether the range of change of the incoming wave direction angle of the target base station is less than the beam coverage area. If the incoming wave direction of the target base station at the current moment is the same as that of the target base station at the previous moment, and the angle change range of the incoming wave direction of the target base station is less than the beam coverage range, analyze the air interface multi-channel in-phase orthogonal data received by the receiving array antenna at the next moment. If the incoming wave direction of the target base station at the current moment is different from that of the target base station at the previous moment, or if the angle change range of the incoming wave direction of the target base station is not less than the beam coverage range, the beam direction of the phased array at the receiving end is adjusted according to the channel characteristics to achieve real-time tracking, so that the beam direction of the phased array at the receiving end is aligned with the incoming wave direction of the target base station, thereby enhancing the signal of the incoming wave direction and suppressing interference signals. In practical applications, array antennas are deployed and DOA estimation is obtained in real time through mobile terminals and fed back to the phased array to change the beam direction. In mobile communication scenarios, there are both line-of-sight (LOS) and non-line-of-sight (NLOS) wireless transmission scenarios. The direct path may be blocked by obstacles that suddenly appear in the dynamic environment, causing interruption. In this case, the LOS scenario becomes an NLOS scenario. Switching according to the direction of the strongest path achieves the goal of maximizing the received signal energy in real time. When the blocked main path reappears or enters the next target base station, the beam needs to be switched accordingly. Therefore, the method based on determining the direction of the strongest wave of arrival does not need to distinguish between LOS and NLOS situations. It is only necessary to align the phased array beam with the direction of the strongest wave of arrival to obtain the maximum received signal strength under the current channel propagation environment. In addition to changes in the propagation scenario, there are also cases of inter-area handover. By switching to the direction of the strongest wave of arrival, the best reception effect can be obtained. Since the passive channel detection and analysis (CIR) has already implemented the function of selecting target base stations, it is only necessary to compare and select the strongest wave of arrival channel feature information of the CIR to achieve coverage enhancement of the target base station. Adjusting the beam direction of the phased array at the receiver according to the channel characteristics, so that the beam direction of the phased array at the receiver is aligned with the direction of arrival of the target base station, specifically includes: The system acquires the incoming wave information at the current moment, the incoming wave information at the previous moment, and the angular resolution, delay judgment criteria, and amplitude judgment criteria of the phased array at the receiving end; the incoming wave information includes the incoming wave angle, delay, and amplitude. Determine whether the absolute value of the difference between the current wave angle and the previous wave angle is greater than the angle resolution. If so, update the incoming wave information of the current moment with the incoming wave information of the previous moment, so as to adjust the beam direction of the phased array at the receiving end, so that the beam direction of the phased array at the receiving end is aligned with the incoming wave direction of the target base station. If not, save the incoming wave information at the current moment, use the incoming wave information at the current moment as the incoming wave information at the previous moment, use the incoming wave information at the next moment as the incoming wave information at the current moment, and return "determine whether the absolute value of the difference between the incoming wave angle at the current moment and the incoming wave angle at the previous moment is greater than the angle resolution".

2. The method for suppressing co-channel interference according to claim 1, characterized in that, The air interface multi-channel in-phase orthogonal data in the 5G downlink signal received by the receiver array antenna from the target base station are analyzed to obtain the channel impulse response between the target base station and the receiver. Specifically, this includes: The receiving array antenna receives radio frequency signals in the environment and acquires air interface multi-channel in-phase orthogonal data from the 5G downlink signal of the target base station; For each channel's air interface in-phase orthogonal data, orthogonal code division multiplexing is used to set the reference signals of different antenna ports on the same orthogonal code division multiplexing group time-frequency resources to obtain channel state information of multiple antennas at the same time-frequency position at the transmitting end; Based on the channel state information, after radio frequency reception and orthogonal frequency division multiplexing demodulation at the receiving antenna, interference cancellation is performed on the reference signals of different antenna ports after aliasing within each orthogonal code division multiplexing group on the orthogonal frequency division multiplexing resource grid, and the channel impulse response between the target base station and the receiving end is extracted.

3. The method for suppressing co-channel interference according to claim 1, characterized in that, By combining the arrival angle estimation algorithm and multipath detection technology, the channel features of the channel impulse response are extracted, and the strongest path channel features are selected, specifically including: The channel impulse response is preprocessed to generate a preprocessed channel impulse response; Construct the covariance matrix of the preprocessed impulse response, and determine the eigenvalues ​​and eigenvectors of the covariance matrix; The eigenvalues ​​are sorted, and the sorted eigenvalues ​​are divided into large eigenvalues ​​and small eigenvalues. Based on the estimated source data, a first matrix is ​​constructed according to the eigenvectors corresponding to the large eigenvalues, and a second matrix is ​​constructed according to the eigenvectors corresponding to the small eigenvalues. Using a multi-signal classification algorithm, a spatial spectrum is constructed based on the orthogonality of the first matrix and the second matrix; Search for the spectral peaks of the spatial spectrum, use the angles corresponding to the spectral peaks as estimated values ​​of the incoming wave angle, and determine the strongest path channel characteristics.

4. The method for suppressing co-channel interference according to claim 3, characterized in that, The covariance matrix R XX for: R xx =E[XX H ]=AE[SS H ]A H +E[NN H ]=AR ss A H +R NN ; Among them, R SS R is the autocorrelation matrix of the signal; NN Let E[XX] be the first noise autocorrelation matrix; H [ ] is the autocorrelation matrix of the first received signal, X is the received signal, H is the conjugate transpose operation; A is the array manifold matrix; E[SS H [] represents the second received signal autocorrelation matrix, and S represents the actual transmitted signal; E[NN] H ] is the second noise autocorrelation matrix, and N is additive white Gaussian noise.

5. The method for suppressing co-channel interference according to claim 3, characterized in that, The spatial spectrum P MUSIC for: Among them, a H (θ) is the guide vector; θ is the angle; U N Let U be the noise matrix; U is the conjugate transpose of the noise matrix.

6. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the co-channel interference suppression method according to any one of claims 1-5.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the co-channel interference suppression method according to any one of claims 1-5.

8. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the co-channel interference suppression method according to any one of claims 1-5.

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