Antenna angle determination method, device, storage medium and electronic device

Abstract

The present disclosure provides a method, device, storage medium and electronic device for determining antenna angle, and relates to the field of communication technology. The method comprises: acquiring the location data of a mobile terminal; performing statistics on the location data of the mobile terminal covered by each beam of the target antenna, respectively, to obtain the center position of the coverage area of ​​each beam; determining the center direction deflection angle of each beam based on the location of the target antenna and the center position of the coverage area of ​​each beam, wherein the center direction deflection angle is the angle between the center direction of the beam and the reference direction; determining the angle of the target antenna according to the center direction deflection angle of each beam and the lobe width of each beam. The present disclosure determines the angle of the target antenna by performing statistical analysis on the location data of the mobile terminal, thereby realizing an automated process, eliminating the need for on-site field measurements by operators, saving manpower and material costs, and ensuring the accuracy of the results.

Description

Background Art

[0002] With the rapid development of mobile Internet, people have higher and higher demands for communication speed and quality. As an important mobile communication engineering parameter, the angle of the antenna in the base station has a great impact on network coverage and communication quality. Therefore, the optimization of mobile networks requires accurate and real antenna angle data. If the antenna angle data is inaccurate, it will have a negative impact on network optimization.

[0003] In the related art, operators usually carry instruments to the site to measure the antenna angle. However, due to the large number of antennas in the current mobile network, on-site measurement requires a lot of manpower and material costs, and is affected by factors such as the operator's level and the on-site environment, and the accuracy of the measurement cannot be guaranteed. Summary of the invention

[0004] The present disclosure provides an antenna angle determination method, an antenna angle determination device, a computer-readable storage medium and an electronic device, thereby at least to a certain extent solving the problem in the related art that measuring antenna angles is costly and accuracy cannot be guaranteed.

[0005] Other features and advantages of the present disclosure will become apparent from the following detailed description, or may be learned in part by the practice of the present disclosure.

[0006] According to the first aspect of the present disclosure, there is provided a method for determining an antenna angle, comprising: acquiring position data of a mobile terminal; performing statistics on the position data of the mobile terminal covered by each beam of the target antenna to obtain the center position of the coverage area of ​​each beam; determining the center direction deflection angle of each beam based on the position of the target antenna and the center position of the coverage area of ​​each beam, the center direction deflection angle being the angle between the center direction of the beam and a reference direction; determining the angle of the target antenna according to the center direction deflection angle of each beam and the lobe width of each beam.

[0007] In one implementation, the acquiring the location data of the mobile terminal includes: acquiring measurement report data of the mobile terminal, wherein the measurement report data includes the location data of the mobile terminal.

[0008] In one embodiment, obtaining measurement report data of a mobile terminal includes: when the obtained measurement report data does not include location data of the mobile terminal, merging the measurement report data with overhead data of the mobile terminal to obtain measurement report data including the location data of the mobile terminal; wherein the overhead data includes the location data of the mobile terminal.

[0009] In one embodiment, merging the measurement report data with the overhead data of the mobile terminal includes: merging the measurement report data with the overhead data based on common fields in the measurement report data and the overhead data.

[0010] In one implementation, the obtaining of measurement report data of the mobile terminal includes: obtaining assisted positioning measurement report data of the mobile terminal.

[0011] In one embodiment, the measurement report data also includes the sector where the mobile terminal is located; the method also includes: organizing the measurement report data in sectors to obtain the location data of the mobile terminal in the target sector, the target sector being the sector corresponding to the target antenna, and the location data of the mobile terminal in the target sector including the location data of the mobile terminal covered by each beam.

[0012] In one embodiment, the method further includes: when the distance between the position of any mobile terminal in the target sector and the position of the target antenna is less than a first threshold, eliminating the position data of any mobile terminal.

[0013] In one embodiment, the measurement report data also includes a time advance of the mobile terminal; the method further includes: obtaining position data of a mobile terminal with a time advance of zero in a target sector in the measurement report data, and obtaining a predicted position of the target antenna based on the obtained position data; using the predicted position of the target antenna as the position of the target antenna; or when the distance between the predicted position of the target antenna and the position of the target antenna in the basic data is greater than a second threshold, using the predicted position of the target antenna as the position of the target antenna, or canceling the angle determination of the target antenna.

[0014] In one implementation, obtaining the predicted position of the target antenna according to the acquired position data includes: calculating the average longitude and the average latitude of the acquired position data to obtain the predicted position of the target antenna.

[0015] In one embodiment, the measurement report data also includes the main sector and adjacent sectors where the mobile terminal is located; the obtaining of the location data of the mobile terminal also includes: extracting from the measurement report data, the measurement report data of the target sector as the main sector and the measurement report data of the target sector as the adjacent sector, the target sector being the sector corresponding to the target antenna.

[0016] In one embodiment, after acquiring the location data of the mobile terminal, the method further includes: dividing the location data into preset longitude and latitude grids, and replacing the location data with data of the longitude and latitude grids.

[0017] In one embodiment, the location data of mobile terminals covered by each beam of the target antenna are counted respectively to obtain the center position of the coverage area of ​​each beam, including: determining the location data associated with each beam of the target antenna respectively; clustering the location data associated with each beam to obtain one or more location clusters under each beam; and determining the center position of the coverage area of ​​each beam according to the maximum location cluster under each beam, the maximum location cluster being the location cluster containing the most location data.

[0018] In one embodiment, determining the center position of the coverage area of ​​each beam according to the maximum position cluster under each beam includes: determining the center position of the maximum position cluster under each beam as the center position of the coverage area of ​​each beam.

[0019] In one embodiment, determining the center direction deflection angle of each beam based on the position of the target antenna and the center position of the coverage area of ​​each beam includes: determining the direction pointing from the position of the target antenna to the center position of the coverage area of ​​each beam as the center direction of each beam; and determining the angle between the center direction of each beam and the reference direction as the center direction deflection angle of each beam.

[0020] In one embodiment, after determining the central direction deflection angle of each beam, the method further includes: when the difference between the maximum value and the minimum value in the central direction deflection angle is less than a third threshold, performing statistics on the position data of the mobile terminal covered by the target antenna to obtain the central position of the target sector, where the target sector is the sector corresponding to the target antenna; determining the angle of the target antenna based on the position of the target antenna and the central position of the target sector; when the difference between the maximum value and the minimum value in the central direction deflection angle is greater than the third threshold, determining the angle of the target antenna based on the central direction deflection angle of each beam and the lobe width of each beam.

[0021] In one embodiment, the statistics of the location data of the mobile terminals covered by the target antenna to obtain the center position of the target sector includes: clustering the location data of the mobile terminals covered by the target antenna and taking the cluster center as the center position of the target sector.

[0022] In one embodiment, determining the angle of the target antenna based on the central direction deflection angle of each beam and the lobe width of each beam includes: determining the target antenna angle prediction value corresponding to each beam based on the central direction deflection angle of each beam and the lobe width of each beam; and determining the angle of the target antenna based on the target antenna angle prediction value.

[0023] In one embodiment, determining the angle of the target antenna according to the target antenna angle prediction value includes: using the weight values ​​of the respective beams to weight the target antenna angle prediction values ​​corresponding to the respective beams to determine the angle of the target antenna.

[0024] In one embodiment, after determining the central direction deflection angles of each of the beams, the method further includes: comparing the order of the beams with the size order of the central direction deflection angles to determine whether the central direction deflection angles are out of order; determining the weight value of the beam corresponding to the out-of-order central direction deflection angle to be 0, and determining the weight value of the beam corresponding to the non-out-of-order central direction deflection angle to be 1.

[0025] In one embodiment, the method determines whether the central direction deflection angles are out of order by comparing the size sequence of the central direction deflection angles with the order of the beams, including: arranging the beams in order from small to large according to the corresponding central direction deflection angles to obtain a beam sequence; starting from the first beam in the beam sequence, determining in turn whether the identifier of each beam is greater than the identifier of the previous beam, if greater, retaining the beam, and if not greater, removing the beam; after traversing each beam in the beam sequence, determining whether the central direction deflection angles corresponding to the removed beams are out of order.

[0026] In one embodiment, the reference direction includes the true north direction.

[0027] In one implementation, the angle of the target antenna includes an azimuth angle of the target antenna.

[0028] In one embodiment, the target antenna comprises a 5G antenna.

[0029] In one embodiment, after determining the angle of the target antenna, the method further includes: determining whether the target antenna has an angle anomaly according to a difference between the determined angle and the angle of the target antenna in the basic data.

[0030] According to a second aspect of the present disclosure, there is provided an antenna angle determination device, comprising: a position data acquisition module, configured to acquire position data of a mobile terminal; a center position determination module, configured to respectively perform statistics on the position data of the mobile terminal covered by each beam of the target antenna to obtain the center position of the coverage area of ​​each beam; a deflection angle determination module, configured to determine the center direction deflection angle of each beam based on the position of the target antenna and the center position of the coverage area of ​​each beam, wherein the center direction deflection angle is the angle between the center direction of the beam and a reference direction; and an antenna angle determination module, configured to determine the angle of the target antenna according to the center direction deflection angle of each beam and the lobe width of each beam.

[0031] According to a third aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the antenna angle determination method of the first aspect and possible implementation methods thereof are implemented.

[0032] According to a fourth aspect of the present disclosure, an electronic device is provided, comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute the antenna angle determination method of the above-mentioned first aspect and its possible implementation method by executing the executable instructions.

[0033] The technical solution disclosed in this disclosure has the following beneficial effects:

[0034] On the one hand, this solution determines the angle of the target antenna by statistically analyzing the location data of the mobile terminal, realizing an automated solution implementation process, eliminating the need for on-site field measurements by operators, saving manpower and material costs, and is not affected by factors such as the operator's level and on-site environment, thus ensuring the accuracy of the results. On the other hand, the implementation process of this solution is convenient, does not require a long period, and can even achieve real-time monitoring of the antenna angle. The angle of the target antenna is calculated based on the coverage area and center direction of the target antenna beam in actual communication, which can reflect the actual changes in the antenna, making it easy to promptly discover anomalies such as angle deviation and take timely measures to reduce the impact on communication quality.

[0035] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and are used together with the specification to explain the principles of the present disclosure. Obviously, the drawings described below are only some embodiments of the present disclosure, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0037] Figure 1 A flow chart of a method for determining an antenna angle in this exemplary embodiment is shown;

[0038] Figure 2 A schematic diagram showing the merging of MR data and OTT data in this exemplary embodiment;

[0039] Figure 3 A schematic diagram showing the combination of AGPS MR data and OTT MR data in this exemplary embodiment;

[0040] Figure 4 A schematic diagram showing the division of the earth's surface into large regions in this exemplary embodiment;

[0041] Figure 5 A schematic diagram showing sectors and sampling points in this exemplary embodiment is shown;

[0042] Figure 6 A schematic diagram showing the combination of data of a main sector and data of an adjacent sector in this exemplary embodiment;

[0043] Fig. 7A A schematic diagram showing position data obtained before splitting adjacent sectors in this exemplary embodiment is shown;

[0044] Figure 7B A schematic diagram showing position data obtained after splitting adjacent sectors in this exemplary embodiment;

[0045] Figure 8 A schematic diagram showing the arrangement of MR data in this exemplary embodiment;

[0046] Fig. 9 A schematic diagram showing an error-sensitive region in this exemplary embodiment;

[0047] Fig. 10A and Fig. 10B A schematic diagram showing the principle of beamforming in this exemplary embodiment is shown;

[0048] Fig.11 A schematic diagram showing the beam distribution of the antenna in this exemplary embodiment is shown;

[0049] Fig.12A flow chart of a method for determining the center position of the coverage area of ​​each beam in this exemplary embodiment is shown;

[0050] Fig.13 A schematic diagram showing the center position of the coverage area of ​​the beam in this exemplary embodiment;

[0051] Fig.14 A structural diagram of an antenna angle determination device in this exemplary embodiment is shown;

[0052] Fig.15 A structural diagram of an electronic device in this exemplary embodiment is shown. DETAILED DESCRIPTION

[0053] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, exemplary embodiments can be implemented in a variety of forms and should not be construed as being limited to the examples set forth herein; on the contrary, these embodiments are provided so that the present disclosure will be more comprehensive and complete, and the concepts of the exemplary embodiments are fully conveyed to those skilled in the art. The described features, structures, or characteristics may be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure may be practiced while omitting one or more of the specific details, or other methods, components, devices, steps, etc. may be adopted. In other cases, known technical solutions are not shown or described in detail to avoid obscuring various aspects of the present disclosure.

[0054] In addition, the accompanying drawings are only schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor devices and / or microcontroller devices.

[0055] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the steps. For example, some steps may be decomposed, while some steps may be combined or partially combined, so the actual execution order may change according to the actual situation.

[0056] In the related art, considering the labor cost of on-site measurement of antenna angles, each measurement is followed by the next measurement at a certain interval. The interval will not be too short, such as several days to a month. If the antenna is affected by external factors and the angle deviates, it will be difficult to detect before the next measurement, which will affect the communication quality.

[0057] In view of one or more of the above problems, an exemplary embodiment of the present disclosure provides an antenna angle determination method. Figure 1 An exemplary process of the antenna angle determination method is shown, including:

[0058] Step S110, obtaining location data of the mobile terminal;

[0059] Step S120, collecting statistics on the position data of the mobile terminals covered by each beam of the target antenna to obtain the center position of the coverage area of ​​each beam;

[0060] Step S130, determining the center direction deflection angle of each beam based on the position of the target antenna and the center position of the coverage area of ​​each beam, where the center direction deflection angle is the angle between the center direction of the beam and the reference direction;

[0061] Step S140, determining the angle of the target antenna according to the central direction deflection angle of each beam and the lobe width of each beam.

[0062] The target antenna may be any one or more antennas to be detected. The angle of the target antenna may be the angle between the center direction of the target antenna and a predetermined reference direction. For example, if the reference direction is due north, the angle of the target antenna is the azimuth.

[0063] Based on the above method, on the one hand, the angle of the target antenna is determined by statistically analyzing the location data of the mobile terminal, realizing an automated solution implementation process, without the need for on-site field measurements by operators, saving manpower and material costs, and not being affected by factors such as the operator's level and on-site environment, thus ensuring the accuracy of the results. On the other hand, the solution implementation process is convenient, without the need for long intervals, and even enables real-time monitoring of the antenna angle. The angle of the target antenna is calculated based on the target antenna beam coverage area and center direction in actual communication, which can reflect the actual changes in the antenna, thereby facilitating timely detection of abnormalities such as angle deviation, and taking timely measures to reduce the impact on communication quality.

[0064] Below Figure 1 Provide detailed instructions for each step.

[0065] In step S110, the location data of the mobile terminal is obtained.

[0066] The location data of the mobile terminal indicates the location of the mobile terminal during communication, for example, the longitude and latitude.

[0067] The location data of the mobile terminal may be obtained from the communication data. In one embodiment, step S110 may include:

[0068] Obtain MR data (Measurement Report) of the mobile terminal. MR is information periodically reported by the mobile terminal and is used to evaluate network conditions. The MR data may include location data of the mobile terminal.

[0069] The following shows part of the measurement report:

[0070] <fileHeader fileFormatVersion=“xx1”reportTime=“xx2”startTime=“xx3”endTime=“xx4”>

[0071] <gNBid=“xx5”userLabel=“userLabel”>

[0072] <measurement>

[0073] <smr>MR.NrScRSRP……MR.Longitude MR.Latitude

[0074]

[0075] <object......TimeStamp="xx6”id="xx7”>

[0076] <v> ……106.084177 30.492218 / v>

[0077] <v> ……106.085177 30.491218 / v>

[0078] <v>...106.086177 30.490218 / v>

[0079] The measurement report contains two fields, MR.Longitude and MR.Latitude, which represent longitude and latitude respectively. 106.084177, 106.085177, etc. are longitude values, and 30.492218, 30.491218, etc. are latitude values.

[0080] In one embodiment, in order to facilitate subsequent data reading, the measurement report can be converted into a data table or the like, for example, each field and its value can be extracted from the measurement report to form a two-dimensional table, called an MR data table. The MR data described herein can be the MR data converted from the original measurement report, for example, can be an MR data table.

[0081] The position data in the MR data usually comes from the positioning system. When the mobile terminal reports the MR data, the positioning system is in normal working condition. Therefore, the mobile terminal can add the position data output by the positioning system to the MR data and report them together. This type of MR data containing position data can be called auxiliary positioning MR data, for example, it can be AGPS (Assisted Global Positioning System) MR data, or MR data based on other positioning systems (such as Beidou Satellite Navigation System).

[0082] However, the mobile terminal may not include location data when reporting MR data, for example, the positioning system is turned off, disabled, or an abnormal positioning signal occurs. In general, MR data other than auxiliary positioning MR data does not include location data. In one embodiment, the OTT data (Over The Top) of the mobile terminal can also be obtained. The OTT data may include the location data of the mobile terminal. For example, the longitude and latitude data can be obtained by performing data parsing through DPI (Deep Packet Inspection). When the acquired MR data does not include the location data of the mobile terminal (that is, the MR data is not auxiliary positioning MR data), the MR data can be merged with the OTT data. After the merger, it is equivalent to filling the location data in the OTT data into the MR data to obtain MR data containing location data.

[0083] Figure 2 It is a schematic diagram of the merger of MR data 210 and OTT data 220. It can be seen that there are common fields in MR data 210 and OTT data 220, such as date, time, gNBid (base station identifier), cellid (cell / sector identifier), AMF UE NGAP id (UE identifier in AMF, AMF is access and mobility management function, UE is user equipment, i.e. mobile terminal), AMF Region id (AMF region identifier), AMF Set id (AMF set identifier), etc. MR data 210 contains fields that OTT data 220 does not have, such as beamid (beam identifier), Ncellid (neighboring sector identifier), etc.; OTT data 220 also contains fields that MR data 210 does not have, mainly location data, i.e. Longitude and Latitude.

[0084] In one embodiment, the MR data 210 and the OTT data 220 may be merged based on the common fields in the MR data 210 and the OTT data 220. Specifically, if it is determined based on the value of the common field that the MR data 210 and the OTT data 220 are from the same mobile terminal, and the time of data reporting is the same or relatively close (for example, the time difference between the MR data 210 and the OTT data 220 is less than a preset time difference, which may be set based on experience, for example, 5 seconds, 1 second, etc.), then the MR data 210 and the OTT data 220 may be merged. Figure 2 For example, you can set the following conditions:

[0085] Table1_gNBid=Table2_gNBid;

[0086] Table1_cellid=Table2_cellid;

[0087] Table1_AMF UE NGAPid=Table2_AMF UE NGAP id;

[0088] Table1_time - Table2_time < 1s;

[0089] Among them, Table 1 represents MR data 210, and Table 2 represents OTT data 220. Then execute the left join instruction (an instruction in the database language, indicating the association operation with the left table as the main table), take the MR data 210 as the main table, and perform left association, thereby filling the position data in the OTT data 220 into the MR data 210, such as Figure 2 As shown in , the merged data includes all the original fields of the MR data 210 , as well as the Longitude and Latitude fields. The merged data can be called OTTMR data 230 .

[0090] In the above manner, two types of MR data are obtained, namely, auxiliary positioning MR data and OTT MR data. In one embodiment, the two types of MR data can be further combined, for example, the formats of the auxiliary positioning MR data and the OTT MR data are unified, or the two parts of data are merged into a data table, etc., thereby unifying all MR data containing position data for subsequent processing.

[0091] The auxiliary positioning MR data is taken as AGPS MR data as an example. Figure 3 This is a schematic diagram of merging the AGPS MR data 240 and the OTT MR data 230 . The AGPS MR data 240 and the OTT MR data 230 are merged by executing the Union all instruction (an instruction in the database language, indicating taking the union of two data sets). The obtained data is called AGPS&OTT MR data 250 .

[0092] The above describes how to obtain the position data. In order to facilitate the use and processing of the position data in the subsequent steps, the position data can usually be optimized. The present disclosure does not limit the specific optimization method, which is described below through specific implementation methods.

[0093] Optimization method 1: rasterization of location data

[0094] Location data is generally longitude and latitude. In practical applications, longitude and latitude data need to be retained for 10 -4 Even higher precision is required to ensure the accuracy of the location. This will introduce a large amount of floating-point data, increase the complexity of data processing, and make it inconvenient for geographic display.

[0095] In one implementation, a latitude and longitude grid may be preset, and each grid represents a certain range. Figure 4 For example, the surface of the earth is divided into many grids with 6 longitudes and 3 latitudes as units, and each grid is a large area, which is identified by earth_id. Each large area is further divided into small longitude and latitude grids with a preset unit length (such as 20 meters, 50 meters, etc., depending on the accuracy requirements, and the unit lengths of longitude and latitude can be different), which are approximately square, but the present disclosure does not limit the shape of the longitude and latitude grids. x_offset and y_offset are the coordinates of each longitude and latitude grid in the large area. In this way, each longitude and latitude grid on the earth can be determined through the three fields of earth_id, x_offset, and y_offset. For example, the earth_ID of a certain region is 12, and the x_offset and y_offset of the longitude and latitude grid located at the center of the region are both 0, which can be represented by (12, 0, 0); the x_offset of the longitude and latitude grid adjacent to the east of (12, 0, 0) is 1, and the y_offset is 0, which is represented as (12, 1, 0); the x_offset of the longitude and latitude grid adjacent to the south of (12, 1, 0) is 1, and the y_offset is -1, which is represented as (12, 1, -1). After obtaining the location data, the location data is divided into the corresponding longitude and latitude grids, and the original location data is replaced by the data of the longitude and latitude grids. This simplifies the location data, eliminates the need to use a large amount of floating-point data, and is conducive to improving data processing efficiency. In addition, the gridded location data is easy to realize geographic display.

[0096] In one implementation, after acquiring the MR data, determine to which latitude and longitude grid each location data belongs, add the three fields of earth_id, x_offset, and y_offset of the latitude and longitude grid to the MR data, and when the location data is subsequently used, earth_id+x_offset+y_offset can be used to replace Longitude and Latitude data.

[0097] Optimization method 2: data organization

[0098] MR data is generally call-order-level data, that is, a mobile terminal reports information once, forming an MR data record. Due to the large number of mobile terminals reporting information at short intervals, there is a large amount of duplicate information in the MR data. For example, a mobile terminal stays at a certain location for one hour, during which it continuously reports information, and the location data, base station, sector and other information are basically the same. Therefore, the MR data can be sorted.

[0099] MR data usually contains the sector where the mobile terminal is located, and this information can be used to organize data. It should be noted that in this article, sectors and cells are the same concept. In MR data, the cell or sector where the mobile terminal is located is usually cell, and in other data or occasions it can also be other fields such as section, which is not limited in this disclosure. Sector refers to the geographical area covered by the antenna. Reference Figure 5 As shown, it is assumed that there are 7 base stations in a certain area, each base station includes 3 antennas (one antenna usually refers to an antenna array), the coverage of the base station is divided into 3 sectors, each antenna covers a corresponding sector, and the mobile terminals in the sector communicate through the corresponding antennas. For example, the three antennas of base station 1 correspond to sectors 11, 12, and 13. In this exemplary embodiment, the sector corresponding to the target antenna is called the target sector.

[0100] In one implementation, the MR data can be sorted in sectors, for example, the MR data can be divided according to the sector identifier (such as cellid) in the MR data, and the MR data with the same sector identifier can be formed into a set. The sector identifier should be globally unique. For example, gNBid+cellid can be used as the sector identifier in some MR data. Duplicate data and useless fields (such as AMF-related fields) in the set can also be deleted. This achieves data deduplication and greatly reduces the amount of data.

[0101] It should be noted that all MR data can be sorted by sector, so that it is easy to search by sector when using MR data. It is also possible to sort the MR data of one or more specific sectors according to actual needs. For example, the identifier of the target sector is found from the acquired MR data to sort out the MR data of the target sector, including the position data required to determine the angle of the target antenna. Thus, the call order-level data is sorted into regional-level data with sectors as indexes (such as sector identifiers as primary keys), which is conducive to further improving processing efficiency.

[0102] MR data may also include the primary sector (or serving sector) and adjacent sectors where the mobile terminal is located. Table 1 shows some fields in the MR data table, where cellid is the primary sector identifier, beamid is the beam identifier, Nccount is the number of adjacent sectors, Ncellid is the adjacent sector identifier, and Ncbeamid is the beam identifier in the adjacent sector.

[0103] Table 1

[0104]

[0105] Continue to refer Figure 5 , showing 6 sampling points. Table 1 shows the MR data reported when the mobile terminal is located at these 6 points. Each row of data represents a reported MR data record. Each row from 1 to 6 is respectively related to Figure 5 It corresponds to the 6 points from top to bottom in . It can be seen that the adjacent sectors in some MR data records are null values, such as the first row, indicating that the mobile terminal did not receive the antenna signal of the adjacent sector when reporting MR data at this position. The adjacent sectors in some MR data records are not null values, such as the second row, indicating that the terminal received the antenna signal of the adjacent sector when reporting MR data at this position. Taking sampling point 2 as an example, its cellid is 32 and beamid is 6, which means that when reporting MR data, communication is carried out through beam 6 in sector 32, and signals from two adjacent sectors are received at the same time, namely the signal of beam 7 in sector 11 and the signal of beam 1 in sector 13. It can be understood that the position of sampling point 2 belongs to the coverage range of beam 6 in sector 32, and also belongs to the coverage range of beam 7 in sector 11 and the coverage range of beam 1 in sector 13.

[0106] It can be seen that the actual coverage of each sector is not limited to the area set by the project, and the information of adjacent sectors in the MR data also reflects the coverage of the sector to a certain extent, and the coverage of each sector can be expanded. In one embodiment, when the above MR data is sorted, each sector can be sorted into a set as a main sector and the MR data as a target sector. For example, the MR data of the target sector as the main sector and the MR data of the target sector as the adjacent sector can be extracted from the MR data.

[0107] Considering that the main sector and the adjacent sector are different fields, and an MR data record may contain multiple adjacent sectors, it is difficult to search and organize directly. In one embodiment, the data corresponding to the adjacent sectors in the MR data can be split out. For example, the second row of Table 1 includes two adjacent sectors. The two adjacent sectors are respectively used as the main sectors to split out two data records, as shown in the first and second rows of Table 2; similarly, three data records corresponding to adjacent sectors can be split out from the third row of Table 1, as shown in rows 3 to 5 of Table 2. After the split, the original table can be merged with the split table. Reference Figure 6 As shown, the position data of the main sector and the position data of the adjacent sectors can be merged through the union all instruction to obtain all the position data of each sector as the main sector and the adjacent sectors. Furthermore, by searching the main sector identifier (cellid), all the position data of a sector can be obtained, which is convenient for sorting.

[0108] Table 2

[0109] Cellid beamid Nccount Ncellid Ncbeamid Longitude Latitude 11 7 1

[32] [6] 106.0794 30.4959 13 1 1

[32] [6] 106.0794 30.4959 13 2 1

[41] [2] 106.0796 30.4936 32 3 1

[41] [2] 106.0796 30.4936 42 8 1

[41] [2] 106.0796 30.4836

[0110] Fig. 7A It shows that only the target sector is extracted as the location data of the main sector, and the location data is represented by a longitude and latitude grid, where blocks of different grayscales represent the longitude and latitude grids of different target sectors. It can be seen that the location data of each sector is less and the coverage area is also smaller. Figure 7B It shows that the target sector is extracted as the position data of the main sector and the adjacent sectors, the position data of each sector increases, and the coverage is also expanded, thereby improving the utilization rate of MR data and facilitating further improving the accuracy in the subsequent calculation of the target antenna angle.

[0111] Figure 8 The schematic diagram of organizing the single-level MR data is shown. Through the above splitting and merging of the data corresponding to the main sector and the adjacent sector, the complete position data of each sector as the main sector and the adjacent sector is obtained. In this way, there is no need to retain the information of the adjacent sector in the MR data, and the fields related to the adjacent sector (such as Nccount, Ncellid, Ncbeamid) can be deleted. Figure 8 The single-level MR data does not contain these fields. Then, through the group by instruction, the data is sorted by sectors and longitude and latitude grids, and useless fields are further deleted to obtain the MR data of multiple longitude and latitude grids under each sector for subsequent use.

[0112] Optimization method three: Eliminate invalid data

[0113] The acquired position data may not be beneficial to the calculation. There may be noise data or data with low reliability, which will introduce large errors to the results. These position data are collectively referred to as non-valid data and can be eliminated.

[0114] In one implementation, noise data in the position data can be removed. For example, statistics are taken on the position data in the target sector, such as calculating the average value of the position data to obtain the center position of the target sector, and then a reasonable range of the target sector is defined with the center position as the center of the circle according to a preset reasonable radius, and the position data outside the range is noise data. Alternatively, the position data in the target sector is clustered to find the noise data with a more serious deviation and remove it.

[0115] In one implementation, when the distance between the position of any mobile terminal in the target sector and the position of the target antenna is less than a first threshold, the position data of the mobile terminal may be discarded.

[0116] refer to Fig. 9 As shown, point O represents the position of the target antenna; T1 is the first threshold; with O as the center and T1 as the radius, a circular area is determined, which is called the error-sensitive area. When the mobile terminal is located in the error-sensitive area, the error of its position data will have a greater impact on the angle estimation of the target antenna; when the mobile terminal is outside the error-sensitive area, the impact is smaller. For example, the mobile terminal is actually located at point P1. In the error-sensitive area, due to the measurement error of the positioning system, the position reported by the mobile terminal is P1', which in turn causes an error of angle 1 in the angle estimation of the target antenna; when the mobile terminal is located at point P2, outside the error-sensitive area, the reported position is P2', which causes an error of angle 2 in the angle estimation of the target antenna; although the distance from P1 to P1' is similar to the distance from P2 to P2', that is, the error of the position data is similar, but angle 2 is much smaller than angle 1, indicating that the angle determination of the target antenna is more sensitive to the error of the position data within the error-sensitive area.

[0117] Since the error in position data is difficult to completely eliminate, in order to reduce its impact on the implementation of this solution, the position data in the error-sensitive area can be treated as non-valid data and eliminated. This will help further improve the accuracy of subsequent determination of the target antenna angle.

[0118] It should be noted that the first threshold is a distance standard for determining the error sensitive area, which can be determined based on experience and actual conditions. Generally, the smaller the target sector, the smaller the first threshold. For example, for a 5G communication scenario, the first threshold may be 80 meters.

[0119] In the above calculation, the position of the target antenna needs to be used. In addition, the position of the target antenna also needs to be used in step S130. The following describes how to obtain this parameter.

[0120] In one implementation, the location of the target antenna can be obtained from basic data. Basic data is data that records various engineering parameters and information of the mobile network; the location of the target antenna in the basic data is usually the location where the target antenna is initially installed, or the location updated during operation and maintenance, etc. Alternatively, the location of the target sector can be used as the location of the target antenna, and the two are usually the same in the basic data.

[0121] In one embodiment, the position of the target antenna can be estimated based on the MR data. The MR data usually contains the TA (Time Advance) of the mobile terminal, which refers to the amount of time required to send data in advance in order to transmit the uplink data of the mobile terminal to the base station at the desired time, which is used to offset the radio frequency transmission delay caused by the distance from the mobile terminal to the antenna. It can be seen that TA actually reflects the distance between the mobile terminal and the antenna. When TA=0, it means that the distance between the mobile terminal and the antenna is very close, and the radio frequency transmission delay is approximately 0. Based on this, the position data of the mobile terminal with TA of 0 in the target sector can be obtained from the MR data, and the predicted position of the target antenna can be obtained based on the obtained position data. TA of 0 indicates that the distance between the mobile terminal and the target antenna is very close. The position data of the mobile terminal is used as the observed value of the position of the target antenna. By statistically analyzing a large amount of such position data, the predicted position of the target antenna can be obtained. For example, the average longitude and average latitude of the obtained position data are statistically analyzed as the predicted position of the target antenna; or the obtained position data are clustered to eliminate the position data with more serious deviations, and the cluster center is used as the predicted position of the target antenna. Further, the predicted position of the target antenna may be used as the position of the target antenna to be used in the above calculation of the error sensitive area and in the subsequent step S130.

[0122] In one implementation, if the predicted position of the target antenna and the position of the target antenna in the basic data are obtained, the two positions can also be compared. Under normal circumstances, the predicted position of the target antenna and the position of the target antenna in the basic data should be the same or similar. When the distance between the two positions is greater than the second threshold, it means that the deviation between the two positions is large, and it can be determined that at least one of the positions is inaccurate.

[0123] The second threshold is a distance standard for measuring whether the position deviation is too large, and can be set according to experience or actual conditions. For example, the larger the target sector, the worse the accuracy of the mobile terminal's position data may be, and the larger the second threshold. Exemplarily, the second threshold may be 50 meters.

[0124] When it is determined that at least one of the above two positions is inaccurate, the following two measures may be further taken:

[0125] Measure 1: If the number of position data (i.e., the position data of the mobile terminal in the target sector with TA 0) used to calculate the predicted position is large (e.g., 10,000 or 100,000, and the specific standard can be determined based on experience and actual conditions) is large, the predicted position is considered to have high credibility and is used as the position of the target antenna;

[0126] Measure 2: If the reliability of the predicted position is not high, the position of the target antenna cannot be accurately obtained, and the accuracy of the relevant calculations cannot be guaranteed. Therefore, the angle determination of the target antenna can be cancelled, the basic data can be checked, or more position data can be collected.

[0127] The above introduces three optimization methods for location data. The above optimization methods can be used in any combination according to actual needs, and the order of different optimization methods can be set arbitrarily, which is not limited in the present disclosure.

[0128] Continue to refer Figure 1 In step S120, the position data of the mobile terminals covered by each beam of the target antenna are counted to obtain the center position of the coverage area of ​​each beam.

[0129] Fig. 10A and Fig. 10B The principle of antenna beamforming is shown. Fig. 10A For the case of two feed sources, each feed source emits a wave, the solid line represents the wave crest, and the dotted line represents the wave trough. According to the interference phenomenon of waves, after two waves of the same frequency are superimposed, the vibration of some areas is strengthened, and the vibration of some areas is weakened. Generally, the vibration of the area where the wave crests are superimposed and the wave troughs are superimposed is the most significant, that is, Fig. 10A In fact, the vibration enhancement area is petal-shaped. After the two waves are superimposed, multiple petal-shaped vibration enhancement areas can be formed, among which the area with the strongest intensity is called the main lobe, and the rest are called side lobes. Fig. 10A The arrows in the figure show the center directions of the main lobe and the side lobes respectively. Fig. 10B The figure shows the change of the main lobe shape as the number of feed sources increases. It can be seen that as the number of feed sources increases, the main lobe becomes narrower and narrower. Most of the current antennas are MIMO (Multiple-In Multiple-Out) antenna arrays, which have multiple feed sources, so narrower beams can be modulated to accurately cover the corresponding area. The beam coverage area or lobe described in this exemplary embodiment mainly refers to the main lobe of the beam.

[0130] Fig.11 The beams emitted by the antenna of the 5G base station, including Beam1 to Beam8, are shown, all with specific directions. Of course, the number of beams per antenna is not limited to 8, and beamforming can be configured according to the shape, structure and actual needs of the antenna to obtain any number of beams. When the mobile terminal is located at different positions within the sector, the corresponding beams are also different. Fig.11 It shows that the mobile terminal is located in the Beam4 direction of the antenna, that is, it is within the coverage area of ​​Beam4.

[0131] Above Figure 6 The corresponding relationship between the antenna and the sector is shown. Each sector can be further divided into multiple areas, which are the coverage areas corresponding to each beam of the antenna. In step S120, the position data in the coverage area of ​​each beam of the target antenna can be divided out, and the position data can be counted in units of beams to obtain the center position of the coverage area of ​​each beam.

[0132] In one embodiment, reference Fig.12 As shown, step S120 may include:

[0133] Step S1210, respectively determining position data associated with each beam of the target antenna;

[0134] Step S1220, clustering the position data associated with each beam to obtain one or more position clusters under each beam;

[0135] Step S1230, determining the center position of the coverage area of ​​each beam according to the maximum position cluster under each beam, the maximum position cluster being the position cluster containing the most position data.

[0136] MR data contains beam identifiers, such as Figure 8 The sorted data in contains the beamid field. Therefore, the location data can be searched according to the beam identifier, for example, the latitude and longitude grid data or longitude and latitude data with beamid 1 can be searched to obtain the location data associated with Beam1, that is, the location data covered by Beam-1. Then, the location data associated with Beam1 can be clustered, and one or more location clusters can be obtained after clustering, which are the location clusters under Beam1. The location cluster refers to a set of location data clustered into one category. Next, the number of location data in each location cluster under Beam1 is counted, and the location cluster with the largest number of location data is selected, that is, the maximum location cluster, and the center position of the coverage area of ​​Beam1 is determined according to the maximum location cluster. It should be noted that when the data of the latitude and longitude grid is used as the location data, the latitude and longitude grid data covered by each beam can be clustered to obtain multiple location clusters, and the location cluster with the largest number of grids under each beam is selected as the maximum location cluster, and then the center position of the coverage area of ​​each beam is determined according to the maximum location cluster.

[0137] The present disclosure does not limit the specific clustering algorithm used in step S1220. The following is an example of the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm. D is the set of location data associated with Beam1, x j Represents any position data in D, and the clustering process is as follows:

[0138] For x j ∈D, and replace D with x j The position data whose distance is not greater than ∈ forms a subset of D, called x j ∈ neighborhood, denoted as N∈(x j );

[0139] Count the number of location data in the neighborhood of ∈, if it is not less than MinPts, that is, if |N∈(x j )|≥MinPts, then determine x j It is the core point;

[0140] If another position data x in D i Located at x j ∈-neighborhood, and x j is a core point, then x i By x j Density direct access;

[0141] If x i and x j There is a sequence of position data (p1, p2, ..., p T ) satisfies p1=x i , p T =x j , and p k+1 By p k The density reaches (k is any positive integer between 1 and T), then x j By x i Density is reachable, density reachability satisfies transitivity;

[0142] If there is a core point x in D L , so that x i and x j All by x L The density can reach, then x i and x j Density is connected; density is connected with symmetry;

[0143] Starting from a core point, it continues to expand to the density-reachable area until a maximized area containing the core point and the boundary point is obtained. If any two points in the area are connected by density, the maximized area is a position cluster.

[0144] In one embodiment, the center position of the maximum position cluster under each beam can be determined as the center position of the coverage area of ​​each beam. The center position of the maximum position cluster can be the geometric center of the position cluster, or the center of gravity of the position cluster (i.e., the average value of all position data in the maximum position cluster), etc., which is not limited in the present disclosure.

[0145] right Fig.11 The latitude and longitude grid data of mobile terminals covered by Beam1 to Beam8 are clustered separately. The clustering results can be referred to Fig.13 As shown. The longitude and latitude grid data associated with Beam1 are clustered to obtain one or more location clusters. When there are multiple location clusters, the location cluster with the largest number of longitude and latitude grids is taken, that is, the largest location cluster. The average longitude and latitude of the longitude and latitude grids are calculated to obtain the center position of the coverage area of ​​Beam1, which is recorded as pos_1. Similarly, the center positions of the coverage areas of Beam2 to Beam8 can be obtained, which are recorded as pos_2 to pos_8 respectively.

[0146] Continue to refer Figure 1 In step S130, based on the position of the target antenna and the center position of the coverage area of ​​each beam, the center direction deflection angle of each beam is determined, and the center direction deflection angle is the angle between the center direction of the beam and the reference direction.

[0147] The reference direction can be any predetermined direction. Fig.13 As shown, the reference direction may be the north (N) direction.

[0148] In one implementation, the direction from the position of the target antenna to the center position of the coverage area of ​​each beam may be determined as the center direction of each beam. Fig.13 As shown, the position O of the target antenna is connected with the center position pos_1 of the coverage area of ​​Beam1 to obtain the center direction of Beam1, which is recorded as direction A. Similarly, the center directions of Beam2 to Beam8 can be obtained, which are recorded as directions B to H, respectively. Then, the angle between the center direction of each beam and the reference direction is determined as the center direction deflection angle of each beam. For example Fig.14 Taking the north direction (N) as the reference direction, the central direction deflection angle of Beam1 is ∠NOA, and the angle value is recorded as ∠1. Similarly, the central direction deflection angles of Beam2 to Beam8 are ∠NOB to ∠NOH, respectively, and the angle values ​​are recorded as ∠2 to ∠8.

[0149] In one implementation, after step S130, the following steps may also be performed:

[0150] When the difference between the maximum value and the minimum value of each center direction deflection angle is less than a third threshold, the position data of the mobile terminal covered by the target antenna is counted to obtain the center position of the target sector;

[0151] The angle of the target antenna is determined based on the position of the target antenna and the center position of the target sector, and step S140 does not need to be performed again;

[0152] When the difference between the maximum value and the minimum value of each center direction deflection angle is greater than the third threshold, step S140 is executed.

[0153] Among them, the difference between the maximum and minimum values ​​of the deflection angles in each center direction reflects the coverage angle of the target antenna to a certain extent. If the value is too small, it means that the beamforming effect of the target antenna is not ideal and effective beam differentiation cannot be performed. In this way, it is difficult to clearly divide the coverage area of ​​each beam. If the position data associated with each beam is counted separately, the result may not be accurate.

[0154] The third threshold is an angle standard for measuring whether the beamforming effect of the target antenna is ideal, and can be set according to experience and actual needs. Exemplarily, the third threshold can be 30 degrees. When the difference between the maximum value and the minimum value is less than the third threshold, the position data associated with each beam may not be counted separately, but the position data of the mobile terminal covered by the target antenna may be counted, that is, the position data associated with all beams may be counted together. For example, the position data in the target sector may be clustered, and the cluster center may be used as the center position of the target sector. If multiple position clusters are obtained after clustering, the largest position cluster is selected, and its center position is used as the center position of the target sector. Then, the position of the target antenna is connected to the center position of the target sector to determine the direction of the target antenna, and the angle of this direction relative to the reference direction is the angle of the target antenna.

[0155] refer to Fig.13 As shown, the position data in the target sector is obtained, clustering is performed, and the center position pos_9 of the target sector is obtained; the position O of the target antenna is connected with pos_9, and the direction of the target antenna is determined, which is recorded as direction I; the angle ∠NOI between the reference direction N and the direction I is calculated, and the angle value is recorded as ∠9, where ∠9 is the angle of the target antenna.

[0156] When the difference between the maximum value and the minimum value of the above-mentioned central direction deflection angle is greater than the third threshold, step S140 can be executed.

[0157] Continue to refer Figure 1 In step S140, the angle of the target antenna is determined according to the central direction deflection angle of each beam and the lobe width of each beam.

[0158] Depend on Fig. 10A , Fig. 10B and Fig.11 It can be seen that the lobe of the beam has a certain shape, and the angle at which the lobe opens from the position where the signal is emitted by the antenna is the lobe width. Fig.13 As shown, the beam width of Beam1 is the fan angle ∠w1 in the dotted area, and the beam widths of Beam2 to Beam8 can also be obtained, which are ∠w2 to ∠w8 respectively.

[0159] The basic data usually includes the base station network management configuration data, which includes the relevant parameters of the antenna beam. As shown in Table 3, the relevant parameters of the beam may include the beam identifier, azimuth, inclination, horizontal beam width, vertical beam width, beam validity, etc. The meaning of each parameter is shown in the table. Among them, the horizontal beam width is the beam width. Therefore, the beam width can be directly obtained from the basic data.

[0160] It should be noted that the azimuth angle in Table 3 has the same meaning as the above-mentioned center direction deflection angle. The difference is that the azimuth angle is the deflection angle relative to the true north direction, while the above-mentioned center direction deflection angle can be the deflection angle relative to any reference direction. Table 3 records the parameter values ​​set by the project, which are theoretical values, while the above-mentioned center direction deflection angle is calculated through the location data of the mobile terminal, which is an actual value. There is usually a difference between the two.

[0161] Table 3

[0162]

[0163] In one embodiment, the lobe width of each beam can also be calculated based on the location data of the mobile terminal. Exemplarily, the coverage area of ​​each beam can be determined based on the location data associated with each beam, and then the coverage area boundary of each beam can be determined. For example, the coverage area boundary of Beam1 is determined, including two boundaries that intersect at the position of the target antenna, and the angle between the two boundaries is the lobe width of Beam1. It should be noted that when determining the coverage area based on the location data, the location data associated with each beam can be clustered, and the radius used for clustering can be larger than the radius used for clustering in step S1220, so as to cluster the location data associated with each beam into a location cluster as much as possible, and the area determined by the location cluster is the coverage area of ​​the beam.

[0164] In one implementation, step S140 may include:

[0165] Determine the target antenna angle prediction value corresponding to each beam according to the central direction deflection angle of each beam and the lobe width of each beam;

[0166] The angle of the target antenna is determined according to the predicted value of the target antenna angle.

[0167] The target antenna angle prediction value is the deflection angle of the target antenna obtained by deflecting according to the lobe width of each beam on the basis of the deflection angle of the central direction of each beam.

[0168] by Fig.13 Take an example to illustrate, and record the target antenna angle prediction values ​​corresponding to Beam1 to Beam8 as Z1 to Z8 respectively. ∠1 represents the deflection angle of the center direction A of Beam1 relative to the true north direction. In order to predict the deflection angle of the center direction of the target antenna relative to the true north direction, ∠1 can be rotated clockwise. After rotating 1 / 2 ∠w1, it reaches the coverage area boundary of Beam1 and Beam2, and then rotates ∠w2 to reach the coverage area boundary of Beam2 and Beam3, and then rotates ∠w3 to reach the coverage area boundary of Beam3 and Beam4, and then rotates ∠w4 to reach the coverage area boundary of Beam4 and Beam5. It is predicted that this direction is the center direction of the target antenna, and its deflection angle relative to the true north direction is:

[0169] Z1=∠1+1 / 2*∠w1+∠w2+∠w3+∠w4

[0170] Thus, the target antenna angle prediction value corresponding to Beam1 is obtained. It can be seen that the target antenna angle prediction value is the prediction of the deflection angle of the target antenna in the center direction. Similarly, the target antenna angle prediction values ​​of Beam2 to Beam8 can be obtained as follows:

[0171] Z2=∠2+1 / 2*∠w2+∠w3+∠w4

[0172] Z3=∠3+1 / 2*∠w3+∠w4

[0173] Z4=∠4+1 / 2*∠w4

[0174] Z5=∠5-1 / 2*∠w5

[0175] Z6=∠6-∠w5-1 / 2*∠w6

[0176] Z7=∠7-∠w5-∠w6-1 / 2*∠w7

[0177] Z8=∠8-∠w5-∠w6-∠w7-1 / 2*∠w8

[0178] Each of the above target antenna angle prediction values ​​can be used as the angle of the target antenna.

[0179] In order to further improve the accuracy of the calculation results, the above-mentioned target antenna angle prediction values ​​can be combined to obtain the final angle result. For example, all target antenna angle prediction values ​​are counted and the average value, median value, and modulus of the statistics are taken as the angle of the target antenna.

[0180] In one implementation, the weight values ​​of the respective beams may be used to weight the target antenna angle prediction values ​​corresponding to the respective beams to determine the angle of the target antenna.

[0181] Let a1 to a8 represent the weight values ​​of Beam1 to Beam8 respectively, then the angle (Z0) of the target antenna can be obtained as:

[0182] Z0=(a1*Z1+a2*Z2+a3*Z3+a4*Z4+a5*Z5+a6*Z6+a7*Z7+a8*Z8) / (a1+a2+a3+a4+a5+a6+a7+a8)

[0183] The weight value is used to indicate the proportion of each target antenna angle prediction value in the final result. The weight value can be set based on experience and actual conditions.

[0184] In one embodiment, the number of position data used to determine the center position of the coverage area of ​​each beam in step S130 may be counted, for example, the number of position data in the maximum position cluster under each beam. Generally, the number of position data can be considered that the more accurate the center position of the coverage area of ​​the beam is, the higher the credibility of the target antenna angle prediction value calculated thereby is, and a higher weight may be set. Exemplarily, the number of position data corresponding to each beam is counted, and the number is normalized to obtain the weight value of each beam.

[0185] In another implementation, the weight value of each beam may also be determined in the following manner:

[0186] By comparing the magnitude sequence of the deflection angles in each central direction with the sequence of each beam, it is determined whether the deflection angles in each central direction are out of order;

[0187] The weight value of the beam corresponding to the deflection angle in the center direction where disorder occurs is determined to be 0, and the weight value of the beam corresponding to the deflection angle in the center direction where disorder does not occur is determined to be 1.

[0188] The order of each beam can be obtained from the basic data. For example, according to the base station network management configuration data in Table 3 above, the order of the 8 beams is Beam1 to Beam8, and the corresponding 8 center direction deflection angles should be strictly increasing. Fig.13 In the equation, the values ​​of ∠1 to ∠8 satisfy the increasing order, which means that ∠1 to ∠8 are not out of order, and the weight values ​​of Beam1 to Beam8 are all 1. The angle of the target antenna is calculated as follows:

[0189] Z0=(Z1+Z2+Z3+Z4+Z5+Z6+Z7+Z8) / 8

[0190] Assume that the values ​​of ∠1 to ∠8 are arranged in the order of ∠1<∠3<∠2<∠4<∠7<∠6<∠5<∠8 from small to large. According to the order of beams 1 to 8, it can be determined that ∠3, ∠2, ∠7, and ∠5 are out of order, and the corresponding weight values ​​of Beam3, Beam2, Beam7, and Beam5 are 0. The order of ∠1, ∠4, ∠6, and ∠8 is correct, and the corresponding weight values ​​of Beam1, Beam4, Beam5, and Beam8 are 1.

[0191] When the position data error is small, the order of the center direction deflection angles of each beam should be consistent with the order of the beams themselves. The existence of disorder indicates that the credibility of the center direction deflection angle is low. Setting its weight value to 0 can reduce its impact on the calculation results.

[0192] The reliability of the un-randomized center direction deflection angle is higher. In one embodiment, when the number of un-randomized center direction deflection angles reaches the fourth threshold, it is determined that the center direction deflection angle is reliable as a whole, and the angle of the target antenna is calculated by the un-randomized center direction deflection angle. The fourth threshold is a quantitative threshold for measuring whether the center direction deflection angle is reliable as a whole. Exemplarily, when the number of beams of the target antenna is 8, the fourth threshold may be 3 or 4. When the number of un-randomized center direction deflection angles is less than the fourth threshold, it means that the center direction deflection angle is not reliable as a whole, or the beamforming effect is not good, and the angle of the target antenna can be determined by other means, such as determining the angle of the target antenna based on the position of the target antenna and the center position of the target sector, or canceling the determination of the target antenna angle.

[0193] It should be noted that different methods may be used to determine whether the order is disordered, and the results obtained may also be different.

[0194] In the above example, the order of the beams is compared with the order of the center direction deflection angles one by one, and if they are inconsistent, it is determined that the center direction deflection angles are out of order.

[0195] In another implementation, whether the center direction deflection angle is out of order may also be determined in the following manner:

[0196] Arrange the beams in order from small to large according to the corresponding central direction deflection angles to obtain a beam sequence;

[0197] Starting from the first beam in the beam sequence, determine in turn whether the identifier of each beam is greater than the identifier of the previous beam. If so, keep the beam; if not, remove the beam.

[0198] After traversing each beam in the beam sequence, it is determined that the central direction deflection angles corresponding to the removed beams are out of order.

[0199] For example, assuming that the order of the eight central direction deflection angles from small to large is: ∠1<∠3<∠2<∠4<∠7<∠6<∠5<∠8, thus a beam sequence S=(Beam1, Beam3, Beam2, Beam4, Beam7, Beam6, Beam5, Beam8) can be formed. Starting from Beam1, the identifier of each beam is compared with the previous beam in turn (in fact, the first beam does not need to be judged). If the identifier of Beam3 is greater than the identifier of Beam1, Beam3 is retained; if the identifier of Beam2 is less than the identifier of Beam3, Beam2 is removed; and so on, the beams finally removed include Beam2, Beam6, and Beam5, that is, the corresponding ∠2, ∠6, and ∠5 are in disorder, and the deflection angles of other central directions are not in disorder.

[0200] In addition to 0 / 1, other weight values ​​may be set for the beams corresponding to the deflection angles of the center direction of the disordered and non-disordered beams, such as 0.3 / 0.7, etc., which is not limited in the present disclosure.

[0201] In the above manner, the target antenna angle prediction values ​​corresponding to each beam are weighted to determine the angle of the target antenna.

[0202] In one embodiment, it can be determined whether the target antenna has an angle abnormality based on the difference between the determined angle and the angle of the target antenna in the basic data. Among them, the angle of the target antenna in the basic data can be the angle of the target antenna measured on site most recently, or the angle of the target antenna after the most recent update. It can be determined whether the difference between the angle obtained in step S140 and the angle of the target antenna in the basic data (usually the absolute value of the difference between the two angles) is greater than the fifth threshold. The fifth threshold is an error threshold for determining whether the angle deviation is too large. Exemplarily, the fifth threshold can be 30 degrees. When the difference between the above two angles is greater than the fifth threshold, it means that the angle of the target antenna may have changed significantly, and it is marked as an angle abnormality, and further measures need to be taken, such as on-site problem investigation, angle restoration, etc. In this way, the antenna angle can be monitored to detect angle abnormalities in a timely manner and reduce the impact on communication quality.

[0203] It should be noted that this solution can be applied to various antennas in mobile communications, such as antennas of different communication standards.

[0204] In one implementation, the present solution can also be particularly applied to 5G antennas. Since beamforming is an important feature of 5G signals, there is a strong correlation between the spatial distribution of beams, the coverage areas of different beams, and the actual orientation of sectors. The present solution can be used to determine the angle of the 5G antenna with high accuracy.

[0205] The exemplary embodiment of the present disclosure also provides an antenna angle determination device. Fig.14 As shown, the antenna angle determination device 1400 may include:

[0206] The location data acquisition module 1410 is configured to acquire location data of the mobile terminal;

[0207] The center position determination module 1420 is configured to collect statistics on the position data of the mobile terminal covered by each beam of the target antenna, and obtain the center position of the coverage area of ​​each beam;

[0208] The deflection angle determination module 1430 is configured to determine the center direction deflection angle of each beam based on the position of the target antenna and the center position of the coverage area of ​​each beam, wherein the center direction deflection angle is the angle between the center direction of the beam and a reference direction;

[0209] The antenna angle determination module 1440 is configured to determine the angle of the target antenna according to the central direction deflection angle of each beam and the lobe width of each beam.

[0210] In one implementation, the location data acquisition module 1410 is configured to:

[0211] The measurement report data of the mobile terminal is obtained, where the measurement report data includes the location data of the mobile terminal.

[0212] In one implementation, the location data acquisition module 1410 is configured to:

[0213] When the acquired measurement report data does not include the location data of the mobile terminal, the measurement report data is merged with the overhead data of the mobile terminal to obtain the measurement report data including the location data of the mobile terminal; wherein the overhead data includes the location data of the mobile terminal.

[0214] In one implementation, the location data acquisition module 1410 is configured to:

[0215] The measurement report data and the overhead data are merged based on common fields in the measurement report data and the overhead data.

[0216] In one implementation, the location data acquisition module 1410 is configured to:

[0217] Obtain the auxiliary positioning measurement report data of the mobile terminal.

[0218] In one implementation, the measurement report data also includes the sector where the mobile terminal is located.

[0219] The location data acquisition module 1410 is configured to:

[0220] The measurement report data is sorted in sectors to obtain the location data of the mobile terminal in the target sector. The target sector is the sector corresponding to the target antenna. The location data of the mobile terminal in the target sector includes the location data of the mobile terminal covered by each beam.

[0221] In one implementation, the location data acquisition module 1410 is configured to:

[0222] When the distance between the position of any mobile terminal in the target sector and the position of the target antenna is less than a first threshold, the position data of any mobile terminal is discarded.

[0223] In one implementation, the measurement report data also includes the timing advance of the mobile terminal.

[0224] The location data acquisition module 1410 is configured to:

[0225] Obtaining position data of a mobile terminal in a target sector with a time advance of zero from the measurement report data, and obtaining a predicted position of a target antenna according to the obtained position data;

[0226] The predicted position of the target antenna is used as the position of the target antenna; or when the distance between the predicted position of the target antenna and the position of the target antenna in the basic data is greater than a second threshold, the predicted position of the target antenna is used as the position of the target antenna, or the angle determination of the target antenna is canceled.

[0227] In one implementation, the location data acquisition module 1410 is configured to:

[0228] The average longitude and average latitude of the acquired position data are calculated to obtain the predicted position of the target antenna.

[0229] In one implementation, the measurement report data also includes the primary sector and the adjacent sector where the mobile terminal is located.

[0230] The location data acquisition module 1410 is configured to:

[0231] From the measurement report data, the measurement report data of the target sector as the main sector and the measurement report data of the target sector as the adjacent sector are extracted, and the target sector is the sector corresponding to the target antenna.

[0232] In one implementation, the location data acquisition module 1410 is configured to:

[0233] After the location data of the mobile terminal is acquired, the location data is divided into preset longitude and latitude grids, and the location data is replaced by the data of the longitude and latitude grids.

[0234] In one implementation, the center location determination module 1420 is configured to:

[0235] respectively determining position data associated with each beam of the target antenna;

[0236] Clustering the position data associated with each beam to obtain one or more position clusters under each beam;

[0237] The center position of the coverage area of ​​each beam is determined according to the maximum position cluster under each beam, and the maximum position cluster is the position cluster containing the most position data.

[0238] In one implementation, the center location determination module 1420 is configured to:

[0239] The center position of the maximum position cluster under each beam is determined as the center position of the coverage area of ​​each beam.

[0240] In one implementation, the deflection angle determination module 1430 is configured to:

[0241] Determine a direction from the position of the target antenna to the center position of the coverage area of ​​each beam as the center direction of each beam;

[0242] The angle between the center direction of each beam and the reference direction is determined as the center direction deflection angle of each beam.

[0243] In one implementation, the antenna angle determination module 1440 is configured to:

[0244] When the difference between the maximum value and the minimum value in the above-mentioned central direction deflection angle is less than a third threshold, the position data of the mobile terminal covered by the target antenna is counted to obtain the center position of the target sector, where the target sector is the sector corresponding to the target antenna;

[0245] determining an angle of the target antenna based on the position of the target antenna and the center position of the target sector;

[0246] When the difference between the maximum value and the minimum value in the central direction deflection angle is greater than the third threshold, the angle of the target antenna is determined according to the central direction deflection angle of each beam and the lobe width of each beam.

[0247] In one implementation, the antenna angle determination module 1440 is configured to:

[0248] The location data of the mobile terminals covered by the target antenna are clustered, and the cluster center is used as the center position of the target sector.

[0249] In one implementation, the antenna angle determination module 1440 is configured to:

[0250] Determine the target antenna angle prediction value corresponding to each beam according to the central direction deflection angle of each beam and the lobe width of each beam;

[0251] The angle of the target antenna is determined according to the above target antenna angle prediction value.

[0252] In one implementation, the antenna angle determination module 1440 is configured to:

[0253] The target antenna angle prediction values ​​corresponding to each beam are weighted by using the weight values ​​of each beam to determine the angle of the target antenna.

[0254] In one implementation, the deflection angle determination module 1430 is configured to:

[0255] After determining the central direction deflection angles of each beam, by comparing the magnitude sequence of the central direction deflection angles with the sequence of each beam, it is determined whether the central direction deflection angles are out of order;

[0256] The weight value of the beam corresponding to the deflection angle in the center direction where disorder occurs is determined to be 0, and the weight value of the beam corresponding to the deflection angle in the center direction where disorder does not occur is determined to be 1.

[0257] In one implementation, the deflection angle determination module 1430 is configured to:

[0258] Arrange the beams in order from small to large according to the corresponding central direction deflection angles to obtain a beam sequence;

[0259] Starting from the first beam in the beam sequence, determine in turn whether the identifier of each beam is greater than the identifier of the previous beam. If so, keep the beam; if not, remove the beam.

[0260] After traversing each beam in the beam sequence, it is determined that the central direction deflection angles corresponding to the removed beams are out of order.

[0261] In one embodiment, the reference direction includes the true north direction.

[0262] In one embodiment, the angle of the target antenna includes an azimuth angle of the target antenna.

[0263] In one embodiment, the target antenna comprises a 5G antenna.

[0264] In one implementation, the deflection angle determination module 1430 is configured to:

[0265] After the angle of the target antenna is determined, it is determined whether the target antenna has an angle anomaly based on the difference between the determined angle and the angle of the target antenna in the basic data.

[0266] The specific details of each part of the above device have been described in detail in the implementation method part, so they will not be repeated here.

[0267] The exemplary embodiments of the present disclosure also provide a computer-readable storage medium, which can be implemented in the form of a program product, which includes a program code. When the program product is run on an electronic device, the program code is used to cause the electronic device to perform the steps described in the "Exemplary Method" section of this specification according to various exemplary embodiments of the present disclosure. In one embodiment, the program product can be implemented as a portable compact disk read-only memory (CD-ROM) and includes program code, and can be run on an electronic device, such as a personal computer. However, the program product of the present disclosure is not limited to this. In this document, a readable storage medium can be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, an apparatus, or a device.

[0268] The program product may use any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0269] Computer readable signal media may include data signals propagated in baseband or as part of a carrier wave, in which readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Readable signal media may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0270] The program code embodied on the readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the foregoing.

[0271] Program code for performing the operations of the present disclosure may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., through the Internet using an Internet service provider).

[0272] The exemplary embodiment of the present disclosure also provides an electronic device, which may be a background server of an information platform. Fig.15 The electronic device is described. It should be understood that Fig.15 The electronic device 1500 shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0273] like Fig.15 As shown, the electronic device 1500 is in the form of a general computing device. The components of the electronic device 1500 may include, but are not limited to: at least one processing unit 1510, at least one storage unit 1520, and a bus 1530 connecting different system components (including the storage unit 1520 and the processing unit 1510).

[0274] The storage unit stores program codes, which can be executed by the processing unit 1510, so that the processing unit 1510 performs the steps of various exemplary embodiments of the present invention described in the above "Exemplary Method" section of this specification. For example, the processing unit 1510 can perform the following steps: Figure 1 The method steps shown, etc.

[0275] The storage unit 1520 may include a volatile storage unit, such as a random access storage unit (RAM) 1521 and / or a cache storage unit 1522 , and may further include a read-only storage unit (ROM) 1523 .

[0276] The storage unit 1520 may also include a program / utility 1524 having a set (at least one) of program modules 1525, such program modules 1525 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0277] The bus 1530 may include a data bus, an address bus, and a control bus.

[0278] The electronic device 1500 may also communicate with one or more external devices 1600 (e.g., keyboards, pointing devices, Bluetooth devices, etc.), and such communication may be performed via an input / output (I / O) interface 1540. The electronic device 1500 may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via a network adapter 1550. As shown, the network adapter 1550 communicates with other modules of the electronic device 1500 via a bus 1530. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 1500, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0279] It should be noted that, although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the exemplary embodiments of the present disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided into multiple modules or units to be embodied.

[0280] It will be appreciated by those skilled in the art that various aspects of the present disclosure may be implemented as systems, methods or program products. Therefore, various aspects of the present disclosure may be specifically implemented in the following forms, namely: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or an implementation combining hardware and software aspects, which may be collectively referred to herein as "circuit", "module" or "system". Other embodiments of the present disclosure will be easily conceived by those skilled in the art after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any variations, uses or adaptations of the present disclosure, which follow the general principles of the present disclosure and include common knowledge or customary technical means in the art that are not disclosed in the present disclosure. The specification and implementation are to be regarded as exemplary only, and the true scope and spirit of the present disclosure are indicated by the claims.

[0281] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.< / v> < / v> < / v> < / smr> < / measurement>

Claims

1. A method for determining an antenna angle, characterized in that: include: Obtaining location data of a mobile terminal; Collecting statistics on the position data of the mobile terminal covered by each beam of the target antenna to obtain the center position of the coverage area of ​​each beam; Determine the center direction deflection angle of each beam based on the position of the target antenna and the center position of the coverage area of ​​each beam, wherein the center direction deflection angle is the angle between the center direction of the beam and a reference direction; Determining the angle of the target antenna according to the central direction deflection angle of each beam and the lobe width of each beam; Wherein, determining the angle of the target antenna according to the central direction deflection angle of each beam and the lobe width of each beam includes: Determine a target antenna angle prediction value corresponding to each beam according to a central direction deflection angle of each beam and a lobe width of each beam; The target antenna angle prediction values ​​corresponding to the respective beams are weighted by using the weight values ​​of the respective beams to determine the angle of the target antenna.

2. The method according to claim 1, characterized in that The obtaining of the location data of the mobile terminal comprises: Acquire measurement report data of the mobile terminal, wherein the measurement report data includes location data of the mobile terminal.

3. The method according to claim 2, characterized in that The measurement report data also includes the primary sector and the adjacent sector where the mobile terminal is located; and the acquiring the location data of the mobile terminal further includes: From the measurement report data, the measurement report data of the target sector as the main sector and the measurement report data of the target sector as the adjacent sector are extracted, and the target sector is the sector corresponding to the target antenna.

4. The method according to claim 1, characterized in that: After obtaining the location data of the mobile terminal, the method further includes: The location data is divided into preset longitude and latitude grids, and the location data is replaced by the data of the longitude and latitude grids.

5. The method according to claim 1, characterized in that The respectively counting the position data of the mobile terminal covered by each beam of the target antenna to obtain the center position of the coverage area of ​​each beam includes: respectively determining position data associated with each beam of the target antenna; Clustering the position data associated with each beam to obtain one or more position clusters under each beam; The center position of the coverage area of ​​each beam is determined according to the maximum position cluster under each beam, and the maximum position cluster is the position cluster containing the most position data.

6. The method according to claim 1, characterized in that After determining the central direction deflection angle of each beam, the method further includes: By comparing the size sequence of each center direction deflection angle with the order of each beam, it is determined whether the each center direction deflection angle is out of order, so as to determine whether the each center direction deflection angle is out of order; the weight value of the beam corresponding to the center direction deflection angle that is out of order is determined to be 0, and the weight value of the beam corresponding to the center direction deflection angle that is not out of order is determined to be 1.

7. The method according to claim 6, characterized in that The step of comparing the order of the deflection angles in the central direction with the order of the beams to determine whether the deflection angles in the central direction are out of order includes: Arrange the beams in order from small to large according to the corresponding central direction deflection angles to obtain a beam sequence; Starting from the first beam in the beam sequence, determining in turn whether the identifier of each beam is greater than the identifier of the previous beam, if so, retaining the beam, and if not, removing the beam; After traversing each beam in the beam sequence, it is determined that the central direction deflection angles corresponding to the removed beams are out of order.

8. An antenna angle determination device, characterized in that: include: A location data acquisition module, configured to acquire location data of a mobile terminal; A center position determination module is configured to collect statistics on the position data of the mobile terminal covered by each beam of the target antenna, and obtain the center position of the coverage area of ​​each beam; A deflection angle determination module is configured to determine the center direction deflection angle of each beam based on the position of the target antenna and the center position of the coverage area of ​​each beam, wherein the center direction deflection angle is the angle between the center direction of the beam and a reference direction; An antenna angle determination module is configured to determine the angle of the target antenna according to the central direction deflection angle of each beam and the lobe width of each beam; Among them, the antenna angle determination module is configured to: determine the target antenna angle prediction value corresponding to each beam according to the central direction deflection angle of each beam and the lobe width of each beam; and use the weight value of each beam to weight the target antenna angle prediction value corresponding to each beam to determine the angle of the target antenna.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

10. An electronic device, characterized in that: include: processor; as well as A memory, configured to store executable instructions of the processor; The processor is configured to perform the method of any one of claims 1 to 7 by executing the executable instructions.

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