CN117676676A - Interference source region positioning method, device and storage medium - Google Patents
Interference source region positioning method, device and storage medium Download PDFInfo
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Abstract
The invention discloses a method, a device and a storage medium for locating an interference source area; the method comprises the following steps: determining at least one type of target interference cell cluster according to the interference degree of the cells; determining a suspected interference area in each target interference cell cluster according to the target interfered beam direction of each cell in each target interference cell cluster; and determining an interference source area according to the suspected interference areas in each target interference cell cluster by using a preset clustering ray intersection method.
Description
Technical Field
The present invention relates to the field of wireless communications, and in particular, to a method, an apparatus, and a storage medium for locating an interference source area.
Background
With the deployment of the fifth generation mobile communication technology (5G,5th Generation Mobile Communication Technology) site scale, the problem of external interference of a New air interface (NR) system is more serious, which affects the user perception such as the success rate of terminal access or handover, service rate, call quality, etc., and even large area network blocking and user complaints occur in part of the interference area, so that it is required to quickly and accurately locate the interference source.
Disclosure of Invention
In view of the foregoing, it is a primary object of the present invention to provide a method, an apparatus and a storage medium for locating an interference source region.
In order to achieve the above purpose, the technical scheme of the invention is realized as follows:
the embodiment of the invention provides a method for positioning an interference source region, which comprises the following steps:
determining at least one type of target interference cell cluster according to the interference degree of the cells;
determining a suspected interference area in each target interference cell cluster according to the target interfered beam direction of each cell in each target interference cell cluster;
and determining an interference source area according to the suspected interference areas in each target interference cell cluster by using a preset clustering ray intersection method.
In the above solution, the determining at least one type of target interference cell cluster according to the interference degree of the cell includes:
determining a cell with the interference degree exceeding a first threshold according to the interference degree of the cell;
carrying out cell clustering according to the longitude and latitude information of the cells with the interference degrees exceeding a first threshold value to obtain a target interference cell range;
performing correlation analysis on any two cells in the target interference cell range, and determining correlation coefficients of the any two cells;
And determining at least one type of target interference cell cluster according to the correlation coefficient of any two cells.
In the above solution, the performing correlation analysis on any two cells in the target interference cell range, and determining a correlation coefficient of the any two cells includes:
performing correlation analysis on interference physical resource blocks (PRB, physical Resource Block) of any two cells to determine correlation coefficients of any two cells;
correspondingly, determining at least one type of target interference cell cluster according to the correlation coefficient of any two cells comprises:
and determining that the two cells with the correlation coefficient exceeding a second threshold belong to the same type of target interference cell cluster.
In the above solution, the determining the suspected interference area in each target interference cell cluster according to the target interfered beam direction of each cell in each target interference cell cluster includes:
for each target interference cell cluster, determining an interference noise power average value under each wave beam of each cell according to a measurement report (MR, measurement Report) of each cell in each target interference cell cluster;
determining a target interfered beam direction of each cell according to the interference noise power average value under each beam of each cell;
And determining a suspected interference area in each target interference cell cluster according to the target interfered beam direction of each cell.
In the above solution, the determining the target interfered beam direction of each cell according to the average value of the interference noise power under each beam of each cell includes:
for a cell with a target beam, taking the vertical beam direction and the horizontal beam direction of the target beam as target interfered beam directions of the cell;
for a cell without a target beam, taking the antenna normal direction of the cell as the target interfered beam direction of the cell;
the target beam is a beam with the interference noise power average exceeding a third threshold.
In the above aspect, the number of the MRs is one or more;
in the case that the number of MRs is plural, determining the interference noise power average value under each beam of each cell according to the measurement report MR of each cell in each target interference cell cluster includes:
determining an interference noise power under said each beam of each cell of each MR record;
according to the weight of each MR, carrying out weighted summation on interference noise power under each wave beam to obtain a first result;
And carrying out average calculation according to the first result and the number of MR, and obtaining a second result serving as the interference noise power average value.
In the above solution, the determining the suspected interference area in each target interference cell cluster according to the target interfered beam direction of each cell includes:
according to the target interfered beam direction of each cell in each target interference type cluster, extending interference rays from the longitude and latitude of the cell to the coverage surface of the antenna;
and determining intersection points of interference rays of all cells in the target interference type cluster, and taking a range formed by the intersection points of the interference rays as a suspected interference area.
In the above scheme, the determining the interference source area according to the suspected interference area in each target interference cell cluster by using a preset clustering ray intersection method includes:
and clustering the range formed by the suspected interference area by adopting the clustering ray intersection point method according to the longitude and latitude information of the suspected interference area, and determining an interference source area.
The embodiment of the invention provides an interference source region positioning device, which comprises:
the first processing module is used for determining at least one type of target interference cell cluster according to the interference degree of the cells;
The second processing module is used for determining a suspected interference area in each target interference cell cluster according to the target interfered beam direction of each cell in each target interference cell cluster;
and the third processing module is used for determining an interference source area according to the suspected interference areas in each target interference cell cluster by using a preset clustering ray intersection method.
In the above scheme, the first processing module is configured to determine, according to the interference degree of the cell, a cell whose interference degree exceeds a first threshold;
carrying out cell clustering according to the longitude and latitude information of the cells with the interference degrees exceeding a first threshold value to obtain a target interference cell range;
performing correlation analysis on any two cells in the target interference cell range, and determining correlation coefficients of the any two cells;
and determining at least one type of target interference cell cluster according to the correlation coefficient of any two cells.
In the above scheme, the first processing module is specifically configured to perform correlation analysis on interfering PRBs of any two cells, and determine a correlation coefficient of any two cells;
and determining that the two cells with the correlation coefficient exceeding a second threshold belong to the same type of target interference cell cluster.
In the above scheme, the second processing module is configured to determine, for each target interference cell cluster, an interference noise power average value under each beam of each cell according to an MR of each cell in each target interference cell cluster;
determining a target interfered beam direction of each cell according to the interference noise power average value under each beam of each cell;
and determining a suspected interference area in each target interference cell cluster according to the target interfered beam direction of each cell.
In the above solution, the second processing module is specifically configured to, for a cell in which a target beam exists, use a vertical beam direction and a horizontal beam direction of the target beam as a target interfered beam direction of the cell;
for a cell without a target beam, taking the antenna normal direction of the cell as the target interfered beam direction of the cell;
the target beam is a beam with the interference noise power average exceeding a third threshold.
In the above aspect, the number of the MRs is one or more;
in case the number of MRs is multiple, the second processing module is specifically configured to determine an interference noise power under each beam of each cell of each MR record;
According to the weight of each MR, carrying out weighted summation on interference noise power under each wave beam to obtain a first result;
and carrying out average calculation according to the first result and the number of MR, and obtaining a second result serving as the interference noise power average value.
In the above scheme, the second processing module is specifically configured to extend, according to a target interfered beam direction of each cell in each target interference type cluster, an interference ray from a longitude and latitude of the cell to an antenna coverage surface;
and determining intersection points of interference rays of all cells in the target interference type cluster, and taking a range formed by the intersection points of the interference rays as a suspected interference area.
In the above scheme, the third processing module is configured to cluster the range formed by the suspected interference area by using the method of clustering ray intersection points according to longitude and latitude information of the suspected interference area, and determine an interference source area.
The embodiment of the invention provides an interference source area positioning device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor realizes the steps of any one of the methods when executing the program.
Embodiments of the present invention also provide a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of any of the methods described above.
The embodiment of the invention provides a method, a device and a storage medium for locating an interference source region, wherein the method comprises the following steps: determining at least one type of target interference cell cluster according to the interference degree of the cells; determining a suspected interference area in each target interference cell cluster according to the target interfered beam direction of each cell in each target interference cell cluster; and determining an interference source area according to the suspected interference areas in each target interference cell cluster by using a preset clustering ray intersection method. Therefore, the suspected interference area of each target interference cell cluster is determined by making an intersection point on the target interfered beam direction (namely the strongest interfered beam direction) of each cell in the target interference cell cluster, the suspected interference areas of each target interference cell cluster are clustered, the interference source area is determined, the positioning accuracy and the interference checking efficiency of the interference source are improved, and the manpower and material resource consumption in the positioning process of the interference source is greatly reduced.
Drawings
Fig. 1 is a flow chart of an interference source region positioning method according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a frequency domain waveform of a plurality of interference types according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of the direction of the strongest interfering ray according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a suspected interference area provided in an embodiment of the present invention;
fig. 5 is a schematic diagram of a method for locating an interference source area according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of an interference source region positioning device according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of another positioning device for interference source area according to an embodiment of the present invention.
Detailed Description
As mentioned above, it is important to locate the source of the disturbance quickly and accurately. In the related art, the interference checking method mainly includes: visual positioning and three-point interference positioning.
There are two kinds of visual positioning methods, one is to analyze the signal strength indication (RSSI, received Signal Strength Indicator) data received by the base station in the uplink by using the MapInfo tool, visually display the base station sector with high interference, and find the intersection of these sectors, so as to determine the approximate interference area. Another way is to observe the change of the uplink RSSI value by changing the directional antenna direction of the base station, and the antenna direction when the RSSI value is maximum may be the potential direction of interference. The three-point positioning method is to search an interference source through a geometric principle, and the common method is to firstly search a three-point positioning area, connect a directional antenna by using a frequency spectrograph to search one point near the interference area for 360-degree test, find the strongest interference direction, then search a second point along the direction until finding a point with interference intensity smaller than the direction in the opposite direction of the direction, the point is the second point, select a third point to test on a perpendicular bisector of the first two points, find the area with the largest interference intensity of the three points, successively approximate the area by using the directional antenna of the frequency spectrograph, find the strongest interference intensity position and position the interference source.
The visual positioning method judges the approximate interference area by visually displaying the intersection range of the high-interference base station sectors on the map, but in practice, the situation that the high-interference sectors are more may exist, if the intersection ranges of the sectors are scattered, the range where the interference source is located is difficult to determine. By changing the direction of the directional antenna of the base station and observing the engineering interference positioning method of the RSSI value change, only the direction of the potential interference source can be found, and the specific position of the interference still needs to be further checked. Although the three-point positioning method can position the approximate interference position, the checking process is time-consuming and labor-consuming, and the positioning efficiency is low.
Based on the above, the method provided by the embodiment of the invention determines at least one type of target interference cell cluster according to the interference degree of the cells; determining a suspected interference area in each target interference cell cluster according to the target interfered beam direction of each cell in each target interference cell cluster; and determining an interference source area according to the suspected interference areas in each target interference cell cluster by using a preset clustering ray intersection method.
The present invention will be described in further detail with reference to examples.
Fig. 1 is a flow chart of an interference source region positioning method according to an embodiment of the present invention; as shown in fig. 1, the method includes:
Step 101, determining at least one type of target interference cell cluster according to the interference degree of the cells;
102, determining a suspected interference area in each target interference cell cluster according to the target interfered beam direction of each cell in each target interference cell cluster;
and step 103, determining an interference source area according to the suspected interference areas in each target interference cell cluster by using a preset clustering ray intersection method.
The method may be applied to network devices, e.g. base stations, which may be base stations in GSM or CDMA (BTS, base Transceiver Station), in WCDMA (NB, nodeB), in LTE (eNB or e-NodeB, evolutional Node B), other base stations in the future, etc.
In some embodiments, the determining at least one type of target interfering cell cluster according to the interfered degree of the cells includes:
determining a cell with the interference degree exceeding a first threshold according to the interference degree of the cell;
carrying out cell clustering according to the longitude and latitude information of the cells with the interference degrees exceeding a first threshold value to obtain a target interference cell range;
Performing correlation analysis on any two cells in the target interference cell range, and determining correlation coefficients of the any two cells;
and determining at least one type of target interference cell cluster according to the correlation coefficient of any two cells.
Considering that the interference degree of the cell by the interference source can be represented on the interference level value of the frequency domain physical resource block (PRB, physical Resource Block), the average interference level value of the PRB on the whole bandwidth of the system can be used for representing the interference degree. The first threshold value can be set based on actual application scenes and actual requirements.
In some embodiments, the performing correlation analysis on any two cells in the target interference cell range, and determining the correlation coefficient of the any two cells includes:
performing correlation analysis on the interfering PRB of any two cells to determine the correlation coefficient of any two cells;
correspondingly, determining at least one type of target interference cell cluster according to the correlation coefficient of any two cells comprises:
and determining that the two cells with the correlation coefficient exceeding a second threshold belong to the same type of target interference cell cluster.
The second threshold may be set based on an actual application scenario and an actual requirement.
The correlation analysis may be performed by any correlation analysis method, for example, a spearman (Spearman Correlation Similarity) correlation method, to obtain spearman correlation coefficients; alternatively, a Pearson correlation analysis method may be used to obtain Pearson correlation coefficients. The method employed for correlation analysis is not limited here.
Specifically, cells with PRB average interference level larger than an interference threshold on the whole bandwidth of the system are screened out, and the cells are regarded as high-interference cells; and determining a high-interference cell range, namely a target interference cell range, by adopting a clustering algorithm (for example, a DBSCAN algorithm) according to the cell longitude and latitude information of the high-interference cell. Sparse interference areas containing only a small number of cells are not considered here. After the target interference cell range (which can be understood as a rough interference range) is screened, correlation analysis is performed on interference PRBs between every two cells in the target interference cell range, and a correlation coefficient between every two cells is obtained. The larger the correlation coefficient is, the more the interference types of every two cells are the same, so that the two cells with the correlation coefficient larger than the second threshold are considered to be the same in interference type, namely, the two cells are considered to belong to the same type of target interference cell cluster.
As shown in fig. 2, fig. 2 is a schematic diagram of a frequency domain waveform of a plurality of interference types according to an embodiment of the present invention, where the interference types include, but are not limited to: LTE D frequency interference, wireless bridge or video monitoring interference, NR system internal interference, intelligent street lamp interference, broadcast television signal interference, router interference and the like. It can be seen that different interference types have different frequency domain waveform characteristics, so that cells with the same interference type can be determined by performing correlation analysis on inter-cell interference PRBs; by analyzing the interference frequency domain characteristics of these cells, the interference type of the cells can be identified, thereby determining a set of cells of the same interference type.
Based on the method, the cells in the range of the target interference cells are subjected to interference type distinction, one or more target interference cell clusters are obtained, and the interference types of the cells in each target interference cell cluster are the same.
In practical application, the number of cells included in some interference cell clusters is considered to be too small, so that the influence on interference is small, and the interference cell clusters can be further screened.
Based on this, in some embodiments, the method further comprises:
determining the number of cells included in each target interference cell cluster;
And determining target interference cell clusters with the number of cells exceeding a number threshold value as target interference cell clusters finally analyzed.
In some embodiments, the determining the suspected interference area in each target interference cell cluster according to the target interfered beam direction of each cell in each target interference cell cluster includes:
for each target interference cell cluster, determining an interference noise power average value under each wave beam of each cell according to a measurement report (MR, measurement Report) of each cell in each target interference cell cluster;
determining a target interfered beam direction of each cell according to the interference noise power average value under each beam of each cell;
and determining a suspected interference area in each target interference cell cluster according to the target interfered beam direction of each cell.
In some embodiments, determining the target interfered beam direction of each cell according to the interference noise power average value under each beam of each cell includes:
for a cell with a target beam, taking the vertical beam direction and the horizontal beam direction of the target beam as target interfered beam directions of the cell;
For a cell without a target beam, taking the antenna normal direction of the cell as the target interfered beam direction of the cell;
the target beam is a beam with the interference noise power average exceeding a third threshold. The third threshold may be set based on an actual application scenario and an application requirement, and represents a threshold of interference noise.
Wherein the measurement report includes information of at least one of:
reference signal received power (ScRSRP, service cell Reference Signal Receiving Power) of the serving cell;
reference signal to noise ratio (ScSINR, service cell Signal to Interference plus Noise Ratio) of the serving cell;
beam identification numbers (ID, identity document) occupied by terminals in the serving cell;
physical cell identity of the serving cell (scpi, service cell Physical Cell ID).
Here, according to a Physical Cell ID (PCI) of each second Cell in the target interfering Cell cluster, scRSRP, scSINR of the second cells of the same interference type, a beam identification number (ID, identity document) occupied by a terminal in a serving Cell, and scpi may be screened out from measurement report data.
The signal-to-noise ratio of the reference signal is calculated by dividing the received power of the reference signal by the interference noise power and converting the divided power into dB. And the ScRSRP and the ScSINR are known measurement results in the MR data, and the interference noise power of the second cell can be calculated according to a reference signal to noise ratio formula. I.e. interference noise power = ScRSRP/ScSINR.
Wherein the number of MRs is one or more; in the case that the number of MRs is plural, determining the interference noise power average value under each beam of each cell according to the measurement report MR of each cell in each target interference cell cluster includes:
determining an interference noise power under said each beam of each cell of each MR record;
according to the weight of each MR, carrying out weighted summation on interference noise power under each wave beam to obtain a first result;
and carrying out average calculation according to the first result and the number of MR, and obtaining a second result serving as the interference noise power average value.
Specifically, after the interference noise power corresponding to all MR data (scrrp and scsnr) under each beam ID of each cell in the target interference cell cluster is calculated, the weighted summation is performed on all the interference noise powers under the beam ID, and then the weighted summation is divided by the number of MR data under the beam ID, so that the interference noise power average under the beam ID can be obtained.
Then, find the beam ID-index ni with the interference noise power average higher than the interference noise threshold (i.e. the third threshold) under all beam IDs in the cell MAX . IndexNI may be used for the beam parameters page in the Northbound interface specification table if found MAX Searching a vertical beam direction and a horizontal beam direction of the beam as indexes, and using the direction as a target interfered beam direction (namely, the strongest interfered beam direction) of an interference cell; otherwise, the interfering cell antenna normal direction is considered to be the target interfered beam direction (i.e., the strongest interfered beam direction).
In some embodiments, the determining the suspected interference area in each target interference cell cluster according to the target interfered beam direction of each cell includes:
according to the target interfered beam direction of each cell in each target interference type cluster, extending interference rays from the longitude and latitude of the cell to the coverage surface of the antenna;
and determining intersection points of interference rays of all cells in the target interference type cluster, and taking a range formed by the intersection points of the interference rays as a suspected interference area.
FIG. 3 is a schematic diagram of the direction of the strongest interfering ray according to an embodiment of the present invention; as shown in fig. 3, the strongest interference ray is determined by taking the direction of the strongest interfered beam of the cell as a ray, and the range formed by the intersection point of the strongest interference ray is used as the suspected interference area.
As shown in fig. 4, fig. 4 is a schematic diagram illustrating a range formed by intersections of strongest interfering rays as a suspected interference region.
In some embodiments, determining an interference source area according to the suspected interference area in each target interference cell cluster by using a preset clustering ray intersection method includes:
and clustering the range formed by the suspected interference area by adopting a clustering ray intersection method according to the longitude and latitude information of the suspected interference area (namely the range formed by the intersection point), and determining an interference source area.
Here, the method for clustering intersection points of rays may be an Artificial Intelligence (AI) algorithm, such as a Density-based clustering algorithm (DBSCAN, density-Based Spatial Clustering of Applications with Noise), by which the range formed by intersection points is clustered to obtain an interference source region and coarsely locate an interference range.
According to the method provided by the embodiment of the invention, firstly, the same type of high-interference cell cluster (namely the target interference cell cluster) is found out according to the interference correlation among the high-interference cells; then, calculating interference noise power average values of different beam directions in each cell in the high-interference cell cluster, and finding out the strongest interfered beam direction of the cell; and finally, taking the strongest interfered beam direction of each cell in the high-interference cell cluster as a ray, clustering ray intersection points through an AI algorithm, and positioning an interference source region. The method solves the problem that the real interference source area is difficult to determine when the intersection range of the high interference sectors is scattered. According to the method provided by the embodiment of the invention, on one hand, the strongest interference direction of the cell is deduced by utilizing the existing beam measurement information in the MR without changing the antenna direction, and the difficulty of positioning the interference direction is reduced. On the other hand, the strongest interference direction of the interference cells of the same type is used as an intersection point, a suspected interference area is determined, and then an interference source area is calculated by combining an AI algorithm, so that the positioning accuracy and the interference checking efficiency of the interference source are improved, and the consumption of manpower and material resources in the positioning process of the interference source is greatly reduced.
Fig. 5 is a schematic diagram of an interference area positioning method according to an embodiment of the present invention, as shown in fig. 5, where the method includes:
step 501, determining a high-interference cell range by clustering according to the interference intensity and longitude and latitude information.
Here, considering that the interference degree of the cell by the interference source can be represented on the interference level value of the frequency domain PRB, firstly, screening out cells with the average PRB interference level larger than the interference threshold on the whole bandwidth of the system, and considering the cells as high-interference cells; and determining the range of the high-interference cell by adopting a clustering algorithm (for example, DBSCAN algorithm) according to the longitude and latitude information of the cell, wherein a sparse interference area only comprising a small number of cells is not considered.
Step 502, determining high-interference cell clusters with the same interference type according to interference PRB correlation analysis;
here, in the range of the high interference cells selected, correlation analysis (for example, spearman Correlation Similarity) is performed on the interfering PRBs between every two cells, and the cell interference types with the correlation coefficient greater than the threshold M are considered to be the same.
The cells in the high-interference cell range are divided into a plurality of high-interference cell clusters (namely a cell set) according to the interference types, and the interference types of the cells in each high-interference cell cluster are the same.
Step 503, screening out MR data of high interference cell clusters with the same interference type;
specifically, step 503 includes: and screening the MR data of the cells with the same interference type from the MR data according to the physical cell identification codes of the cells in the high-interference cell cluster.
The MR data includes: reference signal received power of the serving cell (abbreviated as ScRSRP), reference signal to noise ratio of the serving cell (abbreviated as ScSINR), beam ID occupied by the user of the serving cell, and physical cell identification code (abbreviated as scpi) information of the serving cell.
The signal-to-noise ratio of the reference signal is calculated by dividing the received power of the reference signal by the interference noise power and converting the divided power into dB. The ScRSRP and the ScSINR are known measurement results in the MR data, and the interference noise power of the serving cell can be calculated according to a signal-to-noise ratio formula.
Step 504, searching whether beams with interference noise power average value higher than a threshold L exist in each cell in the high-interference cell cluster; if there are beams with the interference noise power average value higher than the threshold L in the interference cells, step 505 is entered, and if there are no beams with the interference noise power average value higher than the threshold L in the interference cells, step 506 is entered.
Specifically, step 504 includes:
Calculating interference noise power corresponding to all MR data (ScRSRP and ScSINR) under each beam ID of each cell in a high-interference cell cluster, carrying out weighted summation on all interference noise power under the beam ID, and dividing the weighted summation by the number of MR under the beam ID to obtain an interference noise power average value under the beam ID;
searching a beam ID-IndexNIMAX (L is configured according to actual conditions) with the interference noise power average value higher than an interference noise threshold L under all beam IDs in each cell;
if there is a beam with an interference noise power average higher than the interference noise threshold L in the interfering cell, step 505 will be entered, otherwise step 506 is entered.
Step 505, using the found beam direction as the strongest interference ray direction of the interference cell;
in practical application, the vertical beam direction and the horizontal beam direction of the beam can be searched by using IndexNIMAX as an index on a beam parameter page in the north interface technical specification table, and the direction is used as the strongest interference ray direction (corresponding to the target interfered beam direction) of the interference cell, as shown in the strongest interference ray direction in fig. 3;
step 506, taking the normal direction of the antenna of the interference cell as the direction of the strongest interference ray;
step 507, intersecting the strongest interference rays of each cell in the high-interference cell cluster to determine a suspected interference area;
Here, all cells with the same interference type in the high-interference cell cluster extend the strongest interference rays from the longitude and latitude of the cell to the coverage of the antenna by using the direction of the strongest interference rays of the cells, and the range formed by the intersection point of the strongest interference rays of all cells in the high-interference cell cluster is a suspected interference area, as shown in fig. 4.
Step 508, coarsely positioning the range of the interference source.
Here, according to longitude and latitude information of the intersection point of the strongest interference ray, an AI algorithm (e.g., DBSCAN) is adopted to cluster the intersection point, so as to form an area where the suspected interference source is located, and roughly locate the range of the interference source.
The method provided by the embodiment of the invention solves the problem that the real interference source area is difficult to determine when the intersection range of the high-interference sectors is scattered, and in practical application, the identification accuracy of the interference type is more than 90%, the identification efficiency is 650 stations/s, so that the interference checking efficiency can be greatly improved, and the consumption of manpower and material resources is reduced.
It should be noted that, beamforming is a signal preprocessing technique based on an antenna array, and a beam with directivity is generated by adjusting a weighting coefficient of each array element in the antenna array, so that an obvious array gain can be obtained. The 5G band is higher and the coverage is smaller, and in order to enhance the coverage, a large-scale antenna (Massive MIMO) technology has been developed. The 5G network adopts different beams aiming at different channels, and is divided into a Single Side Band (SSB) broadcast channel beam and a channel state information (CSI, channel State Information) service channel beam, wherein the two beams are transmitted by using static beams, so that the lobes, azimuth angles and downward inclination angles of the antennas can be adjusted, and the accurate coverage of specific scenes is realized. The base station transmits a plurality of beam training signals to the terminal at different time domain or frequency domain positions, each beam training signal corresponds to a beam, the beams cover different directions, and the different beams are indicated by beam IDs. The terminal detects the beam training signal, determines the ID of the selected beam according to the detection result, and feeds back the indication information of the selected beam to the base station; the base station determines a beam for transmitting data information according to the indication information about the selected beam fed back by the terminal. In the 5G network, the terminal performs measurement reporting based on the synchronous signal, and the base station performs cell selection, reselection, power control and beam management according to the measurement result. The terminal may be configured to perform measurement on the SSB-RS or may be configured to perform measurement on the CSI-RS, generate a measurement report based on the measurement result, and then report the measurement report to the base station.
Fig. 6 is a schematic structural diagram of an interference source region positioning device according to an embodiment of the present invention; as shown in fig. 6, the apparatus includes:
the first processing module is used for determining at least one type of target interference cell cluster according to the interference degree of the cells;
the second processing module is used for determining a suspected interference area in each target interference cell cluster according to the target interfered beam direction of each cell in each target interference cell cluster;
and the third processing module is used for determining an interference source area according to the suspected interference areas in each target interference cell cluster by using a preset clustering ray intersection method.
It should be noted that: in the foregoing embodiment, when implementing the corresponding method for locating an interference source area, only the division of the program modules is used for illustration, and in practical application, the processing allocation may be completed by different program modules according to needs, that is, the internal structure of the server is divided into different program modules, so as to complete all or part of the processing described above. In addition, the apparatus provided in the foregoing embodiments and the embodiments of the corresponding methods belong to the same concept, and specific implementation processes of the apparatus and the embodiments of the methods are detailed in the method embodiments, which are not described herein again.
Fig. 7 is a schematic structural diagram of an apparatus for positioning an interference source region according to an embodiment of the present invention, as shown in fig. 7, the apparatus 70 for positioning an interference source region includes: a processor 701 and a memory 702 for storing a computer program capable of running on the processor; the processor 701 is configured to execute, when executing the computer program: determining at least one type of target interference cell cluster according to the interference degree of the cells; determining a suspected interference area in each target interference cell cluster according to the target interfered beam direction of each cell in each target interference cell cluster; and determining an interference source area according to the suspected interference areas in each target interference cell cluster by using a preset clustering ray intersection method. Specifically, the method shown in fig. 1 may be executed by the interference source region positioning device, which belongs to the same concept as the embodiment of the interference source region positioning method shown in fig. 1, and detailed implementation processes of the method embodiment are described in the method embodiment, which is not repeated here.
In practical application, the interference source region positioning device 70 may further include: at least one network interface 703. The various components of the disturbance source zone location device 70 are coupled together by a bus system 704. It is appreciated that bus system 704 is used to enable connected communications between these components. The bus system 704 includes a power bus, a control bus, and a status signal bus in addition to the data bus. But for clarity of illustration, the various buses are labeled as bus system 704 in fig. 7. The number of the processors 701 may be at least one. The network interface 703 is used to interfere with wired or wireless communication between the source region locator device 70 and other devices.
The memory 702 in embodiments of the present invention is used to store various types of data to support the operation of the interferer zone-positioning device 70.
The method disclosed in the above embodiment of the present invention may be applied to the processor 701 or implemented by the processor 701. The processor 701 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in the processor 701 or by instructions in the form of software. The Processor 701 may be a general purpose Processor, a DiGital Signal Processor (DSP), or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. The processor 701 may implement or perform the methods, steps, and logic blocks disclosed in embodiments of the present invention. The general purpose processor may be a microprocessor or any conventional processor or the like. The steps of the method disclosed in the embodiment of the invention can be directly embodied in the hardware of the decoding processor or can be implemented by combining hardware and software modules in the decoding processor. The software modules may be located in a storage medium in a memory 702. The processor 701 reads information in the memory 702 and, in combination with its hardware, performs the steps of the method as described above.
In an exemplary embodiment, the interferer zone-positioning device 70 may be implemented by one or more application-specific integrated circuits (ASIC, application Specific Integrated Circuit), DSPs, programmable logic devices (PLDs, programmable Logic Device), complex programmable logic devices (CPLDs, complex Programmable Logic Device), field-programmable gate arrays (FPGAs, field-Programmable Gate Array), general purpose processors, controllers, microcontrollers (MCUs, micro Controller Unit), microprocessors (microprocessors), or other electronic components for performing the aforementioned methods.
The embodiment of the invention also provides a computer readable storage medium, on which a computer program is stored; the computer program, when executed by a processor, performs: determining at least one type of target interference cell cluster according to the interference degree of the cells; determining a suspected interference area in each target interference cell cluster according to the target interfered beam direction of each cell in each target interference cell cluster; and determining an interference source area according to the suspected interference areas in each target interference cell cluster by using a preset clustering ray intersection method. Specifically, the computer program may also execute the method shown in fig. 1, which belongs to the same concept as the embodiment of the interference source region positioning method shown in fig. 1, and the detailed implementation process of the method embodiment is detailed in the method embodiment, which is not repeated herein.
In the several embodiments provided in this application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above described device embodiments are only illustrative, e.g. the division of the units is only one logical function division, and there may be other divisions in practice, such as: multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. In addition, the various components shown or discussed may be coupled or directly coupled or communicatively coupled to each other via some interface, whether indirectly coupled or communicatively coupled to devices or units, whether electrically, mechanically, or otherwise.
The units described as separate units may or may not be physically separate, and units displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units; some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present invention may be integrated in one processing unit, or each unit may be separately used as one unit, or two or more units may be integrated in one unit; the integrated units may be implemented in hardware or in hardware plus software functional units.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the above method embodiments may be implemented by hardware associated with program instructions, and the foregoing program may be stored in a computer readable storage medium, where the program when executed performs steps including the above method embodiments; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk or an optical disk, or the like, which can store program codes.
Alternatively, the above-described integrated units of the present invention may be stored in a computer-readable storage medium if implemented in the form of software functional modules and sold or used as separate products. Based on such understanding, the technical solutions of the embodiments of the present invention may be embodied in essence or a part contributing to the prior art in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, ROM, RAM, magnetic or optical disk, or other medium capable of storing program code.
It should be noted that: "first," "second," etc. are used to distinguish similar objects and not necessarily to describe a particular order or sequence.
In addition, the embodiments described in the present application may be arbitrarily combined without any collision.
The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (11)
1. A method for locating an interference source region, the method comprising:
determining at least one type of target interference cell cluster according to the interference degree of the cells;
determining a suspected interference area in each target interference cell cluster according to the target interfered beam direction of each cell in each target interference cell cluster;
and determining an interference source area according to the suspected interference areas in each target interference cell cluster by using a preset clustering ray intersection method.
2. The method of claim 1, wherein the determining at least one type of target interfering cell cluster according to the degree of interference of the cells comprises:
determining a cell with the interference degree exceeding a first threshold according to the interference degree of the cell;
carrying out cell clustering according to the longitude and latitude information of the cells with the interference degrees exceeding a first threshold value to obtain a target interference cell range;
performing correlation analysis on any two cells in the target interference cell range, and determining correlation coefficients of the any two cells;
and determining at least one type of target interference cell cluster according to the correlation coefficient of any two cells.
3. The method according to claim 2, wherein the performing correlation analysis on any two cells in the target interference cell range, and determining the correlation coefficient of the any two cells, includes:
performing correlation analysis on interfering Physical Resource Blocks (PRBs) of any two cells to determine correlation coefficients of any two cells;
correspondingly, determining at least one type of target interference cell cluster according to the correlation coefficient of any two cells comprises:
And determining that the two cells with the correlation coefficient exceeding a second threshold belong to the same type of target interference cell cluster.
4. The method of claim 1, wherein the determining the suspected interference area in each target interfering cell cluster according to the target interfered beam direction of each cell in each target interfering cell cluster comprises:
for each target interference cell cluster, determining an interference noise power average value under each wave beam of each cell according to the measurement report MR of each cell in each target interference cell cluster;
determining a target interfered beam direction of each cell according to the interference noise power average value under each beam of each cell;
and determining a suspected interference area in each target interference cell cluster according to the target interfered beam direction of each cell.
5. The method of claim 4, wherein said determining the target interfered beam direction for each cell based on the average of the interference noise power for each beam for each cell comprises:
for a cell with a target beam, taking the vertical beam direction and the horizontal beam direction of the target beam as target interfered beam directions of the cell;
For a cell without a target beam, taking the antenna normal direction of the cell as the target interfered beam direction of the cell;
the target beam is a beam with the interference noise power average exceeding a third threshold.
6. The method of claim 4, wherein the number of MRs is one or more;
in the case that the number of MRs is plural, determining the interference noise power average value under each beam of each cell according to the measurement report MR of each cell in each target interference cell cluster includes:
determining an interference noise power under said each beam of each cell of each MR record;
according to the weight of each MR, carrying out weighted summation on interference noise power under each wave beam to obtain a first result;
and carrying out average calculation according to the first result and the number of MR, and obtaining a second result serving as the interference noise power average value.
7. The method of claim 4, wherein the determining the suspected interference area in each target interfering cell cluster according to the target interfered beam direction of each cell comprises:
according to the target interfered beam direction of each cell in each target interference type cluster, extending interference rays from the longitude and latitude of the cell to the coverage surface of the antenna;
And determining intersection points of interference rays of all cells in the target interference type cluster, and taking a range formed by the intersection points of the interference rays as a suspected interference area.
8. The method of claim 1, wherein the determining the interference source area according to the suspected interference area in each target interference cell cluster by using a preset clustering ray intersection method includes:
and clustering the range formed by the suspected interference area by adopting the clustering ray intersection point method according to the longitude and latitude information of the suspected interference area, and determining an interference source area.
9. An interference source region locating apparatus, the apparatus comprising:
the first processing module is used for determining at least one type of target interference cell cluster according to the interference degree of the cells;
the second processing module is used for determining a suspected interference area in each target interference cell cluster according to the target interfered beam direction of each cell in each target interference cell cluster;
and the third processing module is used for determining an interference source area according to the suspected interference areas in each target interference cell cluster by using a preset clustering ray intersection method.
10. An interferer region localization device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any one of claims 1 to 8 when said program is executed by said processor.
11. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method according to any one of claims 1 to 8.
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