Base station azimuth correction method, device and system, and storage medium

Abstract

The present disclosure relates to a base station azimuth angle correction method, device and system, and a storage medium. The base station azimuth angle correction method comprises: screening measurement report data satisfying a screening condition, wherein the screening condition is that a reference signal received power is greater than a predetermined reference signal received power; in the measurement report data satisfying the screening condition, screening measurement report data with an accurate time advance value; and determining a predicted azimuth angle according to the measurement report data with the accurate time advance value. The present disclosure can correct the base station azimuth angle based on MR data. The present disclosure can quickly determine whether the base station antenna azimuth angle of a source cell deviates, thereby achieving cost reduction and efficiency improvement.

Description

Technical Field

[0001] This disclosure relates to the field of communication technology, and in particular to a base station azimuth correction method, apparatus and system, and storage medium. Background Technology

[0002] In mobile communication systems, the transmission and reception of wireless signals rely on antennas. Therefore, antennas play a crucial role in mobile communication networks. Among the various parameters configured for base station antennas, the antenna azimuth angle is extremely important. However, in actual mobile communication networks, the antenna azimuth angle can sometimes shift due to natural disasters such as strong winds and earthquakes, leading to a deterioration in mobile communication network quality. Summary of the Invention

[0003] The inventors discovered through research that the relevant technical verification methods are based on road test data, which require vehicles, personnel, and tools, resulting in high testing costs. Furthermore, routine checks of the azimuth angle of the community require frequent on-site data collection through methods such as field testing and station visits, threatening the personal safety of maintenance personnel. Manual verification is inefficient and cannot achieve automated verification.

[0004] In view of at least one of the above technical problems, this disclosure provides a base station azimuth correction method, apparatus and system, and storage medium, which corrects the base station azimuth based on MR (Measurement Report) data.

[0005] According to one aspect of this disclosure, a base station azimuth correction method is provided, comprising:

[0006] Filter out measurement report data that meet the filtering criteria, wherein the filtering criteria is that the reference signal received power is greater than a predetermined reference signal received power;

[0007] From the measurement report data that meets the screening criteria, select the measurement report data with accurate time advance values;

[0008] The predicted azimuth is determined based on the measurement report data of the accurate time advance value.

[0009] In some embodiments of this disclosure, the base station azimuth correction method further includes:

[0010] The predicted azimuth angle and the filed azimuth angle are compared, and the predetermined reference signal receiving power is iteratively corrected.

[0011] According to the corrected predetermined reference signal received power, the steps of filtering out measurement report data that meet the filtering conditions, filtering out measurement report data with accurate time advance values, and calculating the base station azimuth angle based on the measurement report data with accurate time advance values ​​are repeated.

[0012] In some embodiments of this disclosure, the base station azimuth correction method further includes:

[0013] Based on the predicted azimuth angle, identify the cells with problematic base station azimuth angles;

[0014] The cells with problematic base station azimuth angles will be sent to users for verification and rectification.

[0015] In some embodiments of this disclosure, determining the cell with a problematic base station azimuth angle based on the predicted azimuth angle includes:

[0016] For the first cell and the second cell where the error between the predicted azimuth and the registered azimuth is within a predetermined range, if the difference between the predicted azimuth of the first cell and the registered azimuth of the second cell is less than a first predetermined angle, and the difference between the predicted azimuth of the second cell and the registered azimuth of the first cell is less than a second predetermined angle, then it is determined that the base station azimuths of the first cell and the second cell are reversed.

[0017] In some embodiments of this disclosure, determining the cell with a problematic base station azimuth angle based on the predicted azimuth angle includes:

[0018] For a cell where the error between the predicted azimuth and the registered azimuth is within a predetermined range, if the proportion of the number of measurement report data within the third predetermined angle range on both sides of the registered azimuth of the cell to the total number of measurement report data is less than a predetermined proportion, then the azimuth deviation of the cell is determined to be greater than a predetermined threshold.

[0019] In some embodiments of this disclosure, the step of filtering out measurement report data that meet the filtering criteria includes:

[0020] The latitude and longitude, reference signal received power, base station identifier, cell identifier, and time advance data in the measurement report are associated with the base station identifier and base station latitude and longitude.

[0021] From the associated measurement report data, filter out the measurement report data that meets the filtering criteria.

[0022] In some embodiments of this disclosure, the measurement report data used to filter out accurate time advance values ​​includes:

[0023] For each time advance value in a single base station, the collection range of the corresponding location point is determined as a circular area;

[0024] For multiple time advance values ​​in a single base station, the range of multiple concentric ring regions is determined, and the range of the region is the effective time advance value region.

[0025] In some embodiments of this disclosure, determining the predicted azimuth angle based on measurement report data of accurate time advance includes:

[0026] The predicted azimuth is determined based on the longitude and latitude of the two auxiliary global positioning systems and the accurate time advance value.

[0027] According to another aspect of this disclosure, a base station azimuth correction device is provided, comprising:

[0028] The first filtering module is used to filter out measurement report data that meet the filtering criteria, wherein the filtering criteria is that the reference signal received power is greater than a predetermined reference signal received power.

[0029] The second filtering module is used to filter out measurement report data with accurate time advance values ​​from the measurement report data that meet the filtering conditions.

[0030] The azimuth correction module is used to determine the predicted azimuth based on the measurement report data of the accurate time advance value.

[0031] In some embodiments of this disclosure, the base station azimuth correction device is used to perform operations to implement the base station azimuth correction method as described in any of the above embodiments.

[0032] According to another aspect of this disclosure, a base station azimuth correction device is provided, comprising:

[0033] Memory, used to store instructions;

[0034] A processor is configured to execute the instructions, causing the base station azimuth correction device to perform operations implementing the base station azimuth correction method as described in any of the above embodiments.

[0035] According to another aspect of this disclosure, a base station azimuth correction system is provided, including a base station azimuth correction device as described in any of the above embodiments.

[0036] According to another aspect of this disclosure, a non-transitory computer-readable storage medium is provided, wherein the non-transitory computer-readable storage medium stores computer instructions that, when executed by a processor, implement the base station azimuth correction method as described in any of the above embodiments.

[0037] This disclosure can correct the azimuth angle of a base station based on MR data. This disclosure can quickly determine whether the azimuth angle of the base station antenna in the source cell has deviated, thereby achieving cost reduction and efficiency improvement. Attached Figure Description

[0038] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1 This is a schematic diagram of some embodiments of the base station azimuth correction method disclosed herein.

[0040] Figure 2 This is a schematic diagram of some other embodiments of the base station azimuth correction method disclosed herein.

[0041] Figure 3 This is a diagram showing the range of TA values ​​for base station errors in some embodiments of this disclosure.

[0042] Figure 4 This is a schematic diagram illustrating the range of TA values ​​with the base station as a reference point in some embodiments of this disclosure.

[0043] Figure 5 This describes the actual distribution range of TA points in the map in some embodiments of this disclosure.

[0044] Figure 6 This is a schematic diagram of some embodiments of the base station azimuth correction device disclosed herein.

[0045] Figure 7 This is a schematic diagram of the structure of some embodiments of the base station azimuth correction device disclosed herein. Detailed Implementation

[0046] The technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, and not all embodiments. The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit this disclosure or its application or use. All other embodiments obtained by those skilled in the art based on the embodiments of this disclosure without creative effort are within the scope of protection of this disclosure.

[0047] Unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of this disclosure.

[0048] At the same time, it should be understood that, for ease of description, the dimensions of the various parts shown in the accompanying drawings are not drawn according to actual scale.

[0049] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and equipment should be considered part of the specification.

[0050] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.

[0051] It should be noted that similar labels and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be discussed further in subsequent figures.

[0052] The inventors noted that the verification methods of related technologies cannot promptly confirm the effectiveness and accuracy of changes made to the azimuth angle, thus failing to achieve closed-loop management. For example, in one province, out of 340,000 residential communities, there were 4,312 (1.27%) cases of reversed or abnormal azimuth angles.

[0053] The inventors discovered through research that the related technologies have the following problems:

[0054] 1) Reduce the workload of daily maintenance personnel in collecting high-risk maintenance data, solve the problem of non-automated verification and high optimization costs.

[0055] 2) To solve the problem of not being able to promptly confirm the effectiveness and accuracy of changes after azimuth angle changes, thus achieving closed-loop management.

[0056] 3) It requires manual analysis by combining multiple different systems, resulting in one-sided, inaccurate, and inefficient problem analysis.

[0057] In view of at least one of the above-mentioned technical problems, this disclosure provides a base station azimuth correction method, apparatus, system, and storage medium, which can realize intelligent azimuth verification and reduce the number of high-risk manual data collections. The present disclosure will be described below through specific embodiments.

[0058] Figure 1 This is a schematic diagram of some embodiments of the base station azimuth correction method of this disclosure. Preferably, this embodiment can be executed by the base station azimuth correction device or the base station azimuth correction system of this disclosure. The method may include at least one step in steps 11-13, wherein:

[0059] Step 11: Filter out measurement report data that meet the filtering criteria, wherein the filtering criteria is that the (ReferenceSignal Receiving Power) is greater than the predetermined reference signal receiving power.

[0060] In some embodiments of this disclosure, step 11 may include: statistically analyzing MR data for a predetermined number of days, classifying base stations, and for a cell corresponding to a base station, extracting MR data points with high RSRP, good signal, and a proportion greater than x% (e.g., the first 80%) of the total number of MR data, finding the lower limit value of RSRP for these MR data, and using the lower limit value to filter out MR data.

[0061] In some embodiments of this disclosure, the predetermined number of days can be 15 days.

[0062] In some embodiments of this disclosure, the measurement reports (MR) periodically reported by the 4G user terminals of the mobile network include GPS latitude and longitude and network coverage quality data, thereby laying the foundation for automatic base station azimuth correction by automatically collecting massive amounts of coverage data.

[0063] Step 12: Among the measurement report data that meet the screening criteria, select the measurement report data with accurate TA (Timing Advance) values.

[0064] Step 13: Determine the predicted azimuth angle based on the measurement report data of the accurate time advance value.

[0065] In some embodiments of this disclosure, step 13 may include: dividing the base station into 360 small sectors of 1 degree each, calculating the proportion of MR data in each sector, sorting them in descending order, and removing the top 5 angles with the largest proportions; calculating the MR data of each of the 360 ​​small sectors (horizontal beamwidth / 2) degrees to the left and right of each other, and sorting them in descending order to obtain the angle corresponding to the highest ratio, which is the optimal azimuth angle.

[0066] In some embodiments of this disclosure, step 13 may include: establishing a prediction model for the base station azimuth angle based on multi-dimensional measurement report (MR) data reported by user terminals, such as base station coverage area, base station physical identifier, base station latitude and longitude, user latitude and longitude, RSRP, TA, and cell physical identifier, according to scenarios such as urban and rural areas; and calculating the base station azimuth angle (i.e., the predicted angle) based on the prediction model for the base station azimuth angle.

[0067] The above embodiments of this disclosure propose a method for correcting base station azimuth angles based on MR data. Addressing the problem of untimely detection of base station azimuth angle deviations in related technologies, the above embodiments of this disclosure establish a big data analysis algorithm model to periodically check all cells in the network, improving the accuracy of basic data. Therefore, the above embodiments of this disclosure can quickly determine whether the azimuth angle of the base station antenna in the source cell has deviated, enabling enterprises to reduce costs and increase efficiency.

[0068] Figure 2This is a schematic diagram of some other embodiments of the base station azimuth correction method of this disclosure. Preferably, this embodiment can be executed by the base station azimuth correction device or the base station azimuth correction system of this disclosure. The method may include at least one step from steps 21 to 24, wherein:

[0069] Step 21: Filter out MR data that meets the RSRP value.

[0070] In some embodiments of this disclosure, step 21 may include at least one of steps 211 and 212, wherein:

[0071] Step 211: Associate the latitude and longitude, RSRP, base station identifier (base station id), cell identifier (cell id), TA data in MR with the base station identifier (base station id) and base station latitude and longitude data. The association condition is that the base station ids of the two are equal.

[0072] In some embodiments of this disclosure, MR data from 250 communities in a certain province for 15 days can be selected for pilot testing.

[0073] Step 212: Classify the associated MR data according to the coverage of the base station, take the MR data of one type of base station, and set the RSRP value to -85dBm (assuming that the RSRP lower limit corresponding to 90% is -85dBm). Filter the MR data of all cells, and the filtering condition is RSRP>-85dBm to obtain the MR data that meets the filtering condition.

[0074] Step 22: Filter out MR data with accurate TA values.

[0075] In some embodiments of this disclosure, step 22 may include: for each time advance value in a single base station, determining the collection range of the corresponding location point as a circular region; for multiple time advance values ​​in a single base station, determining the range of multiple concentric circular regions, wherein the range of regions is the effective time advance value region.

[0076] In some embodiments of this disclosure, step 22 may include: taking the MR data filtered in step 21 and further filtering the data in a circular region with a radius of [80m, 800m] centered on the base station; then, for the data with TA=2, filtering to obtain the accurate data corresponding to TA=2 in a circular region with a radius of [78.12*2-40, 78.12*2] (unit meters); for the data with TA=3, filtering to obtain the accurate data corresponding to TA=3 in a circular region with a radius of [78.12*3-40, 78.12*3] (unit meters); and so on, to obtain the accurate data corresponding to TA=4, 5, ..., 10.

[0077] Figure 3 This is a diagram showing the range of TA values ​​for base station errors in some embodiments of this disclosure. Figure 4 This is a schematic diagram illustrating the range of TA values ​​with the base station as a reference point in some embodiments of this disclosure. Figure 5 This describes the actual distribution range of TA points in the map in some embodiments of this disclosure.

[0078] In some embodiments of this disclosure, such as Figure 3 and Figure 4 As shown, the acquisition range of a single location point corresponding to a single TA value in a single base station is a circular area. The circular area is a concentric circle, and the center of the circle is determined by the latitude and longitude of the base station. The radius of the outer circle is approximately TA value * 78.12. The width of the circular area in the radial direction is equal to the suspension height of the base station antenna. By filtering the MR data within the circle, the accurate range of the TA data is obtained. For multiple TA values ​​of a single base station, the range of multiple concentric circular areas can be obtained. This range is the effective TA area, and the MR data within this range is the MR data of the effective TA area for calculating the azimuth angle.

[0079] In some embodiments of this disclosure, the area where the effective RSRP area and the effective TA area intersect is the final effective area range for calculating the azimuth angle. The MR data with more than 30 MR data within this range is the data used by the base station azimuth angle prediction model.

[0080] Step 23, azimuth calculation.

[0081] In some embodiments of this disclosure, step 23 may include: determining the predicted azimuth angle based on measurement report data of accurate time advance value.

[0082] In some embodiments of this disclosure, step 23 may include: determining the predicted azimuth angle based on the longitude and latitude of two AGPS (Assisted Global Positioning System) systems and the accurate time advance value.

[0083] The distance and azimuth between the base station and the MR data location point are calculated using formula (1-3) based on the data selected above. The calculation formula is as follows:

[0084] Formula (1) is the formula for the distance between two AGPS latitude and longitude coordinates:

[0085]

[0086] In formula (1), A2 and B2 are the longitude and latitude of the first point in the AGPS; C2 and D2 are the longitude and latitude of the second point in the AGPS.

[0087] Formula (2) is the conversion formula between TA and actual distance:

[0088] meter = TA × 78.12 (2)

[0089] Formula (3) is the formula for calculating azimuth:

[0090] angle={{arctan2[sin(A2×π / 180-C2×π / 180)×cos(B2×π / 180),cos(D2×π / 180)×sin(B2×π / 180)-sin(D2×π / 180)×cos(B2×π / 180)×cos(A2×π / 180-C2×π / 180)]×180 / π}+360.0}% 360.0 (3)

[0091] In formula (3), A2 and B2 are the longitude and latitude of the first point's AGPS; C2 and D2 are the longitude and latitude of the user's AGPS.

[0092] In some embodiments of this disclosure, such as Figure 3 and Figure 4 As shown, step 23 may include: taking the base station as the center, dividing the circular area with a radius in the range of [80m, 800m] into 360 small fan-shaped areas of 1 degree each, calculating the proportion of MR data in each fan-shaped area, sorting them in descending order, and removing the top 5 angles with the largest proportions; calculating the MR numbers of the small fan-shaped areas with 33 (horizontal beamwidth / 2) degrees to the left and right of each of the 360 ​​angles and their proportions to the total MR numbers, sorting them in descending order, and obtaining the angle corresponding to the highest proportion, which is the optimal azimuth angle.

[0093] Step 24: Calculate the RSRP value by comparing the azimuth angle with the registered azimuth angle.

[0094] In some embodiments of this disclosure, step 24 may include: taking the base station filing azimuth angles of 30 accurately verified cells as training data, comparing them with the calculated azimuth angles of the corresponding cells obtained in step 23 to lose error, obtaining the proportion corresponding to the lower limit of RSRP through gradient descent iteration, and then back-calculating the k value in the screening condition RSRP>k, and then repeating steps 21, 22, and 23 with the RSRP value.

[0095] In some embodiments of this disclosure, the base station azimuth correction method may further include: establishing a predictive model for the base station azimuth based on multi-dimensional MR data such as base station coverage, base station physical identifier, base station latitude and longitude, user latitude and longitude, RSRP, TA, and cell physical identifier, according to scenarios such as urban areas and rural areas; the predictive model automatically generates initial parameters (RSRP values) for filtering MR data, and iteratively updates and optimizes the initial parameter values ​​based on the effect of solving the model to obtain RSRP values ​​corresponding to different types of base stations, locate the area range where MR data with reference signal received power greater than the RSRP value is located, and this area range is the effective RSRP area, and the MR data filtered based on the RSRP value within this range is the MR data of the effective RSRP area for calculating the azimuth.

[0096] In some embodiments of this disclosure, the base station azimuth correction method may further include: step 25, obtaining cells with problematic base station azimuth angles and verifying rectification.

[0097] In some embodiments of this disclosure, step 25 may include: determining the cell with a problematic base station azimuth angle based on the predicted azimuth angle; and sending the cell with the problematic base station azimuth angle to the user for verification and rectification.

[0098] In some embodiments of this disclosure, the step of determining a cell with a problematic base station azimuth angle based on the predicted azimuth angle may include: establishing a prediction model for the base station azimuth angle based on multi-dimensional MR data such as base station coverage area, base station physical identifier, base station latitude and longitude, user latitude and longitude, RSRP, TA, and cell physical identifier, according to scenarios such as urban areas and rural areas; calculating the base station azimuth angle (i.e., the predicted angle) based on the prediction model and comparing the error with the registered base station azimuth angle (i.e., the registered angle) to determine the cell with the problematic base station azimuth angle.

[0099] In some embodiments of this disclosure, the step of comparing the error between the base station azimuth angle (i.e., the predicted angle) calculated according to the prediction model and the registered base station azimuth angle (i.e., the registered angle) to determine the cell with a problematic base station azimuth angle may include: for a first cell and a second cell where the error between the predicted azimuth angle and the registered azimuth angle is within a predetermined range, if the difference between the predicted azimuth angle of the first cell and the registered azimuth angle of the second cell is less than a first predetermined angle, and the difference between the predicted azimuth angle of the second cell and the registered azimuth angle of the first cell is less than a second predetermined angle, then it is determined that the base station azimuth angles of the first cell and the second cell are reversed.

[0100] In some embodiments of this disclosure, the predetermined range is greater than 130 degrees and less than 176 degrees; the first predetermined angle is 10 degrees; and the second predetermined angle is 65 degrees.

[0101] In some embodiments of this disclosure, the step of comparing the error between the base station azimuth angle (i.e., the predicted angle) calculated according to the prediction model and the registered base station azimuth angle (i.e., the registered angle) to determine the cell with a problematic base station azimuth angle may include: for a cell where the error between the predicted azimuth angle and the registered azimuth angle is within a predetermined range, if the proportion of the number of measurement report data within the third predetermined angle range on both sides of the registered azimuth angle of the cell to the total number of measurement report data is less than a predetermined proportion value, then it is determined that the deviation of the azimuth angle of the cell is greater than a predetermined threshold.

[0102] In some embodiments of this disclosure, the third predetermined angle range can be 33 degrees (beamwidth / 2).

[0103] In some embodiments of this disclosure, the predetermined ratio value can be 20%.

[0104] In some embodiments of this disclosure, MR data from 250 cells in a certain province were collected over 15 days for a pilot project. The azimuth angles of 212 cells were calculated, and the results are shown in Table 1.

[0105] Table 1

[0106] Error range (degrees) 0-5 6-10 11-15 16-20 20-30 31-65 65-130 130 and above percentage 9％ 7.08％ 8.02％ 5.66％ 16.50％ 30.66％ 14.62％ 8.00％ Number of residential communities 20 15 17 12 35 65 31 17 Total number of residential communities 20 35 52 64 99 164 195 212 Cumulative percentage 9％ 16.51％ 24.53％ 30.19％ 46.70％ 77.36％ 92％ 100％

[0107] In some embodiments of this disclosure, the rule for determining the azimuth angle of the problematic base station is as follows: First, take two cells (cell a and cell b) whose predicted angle and the registered angle have an error greater than 130 degrees and less than 176 degrees. When the difference between the predicted angle of cell a and the registered angle of cell b is less than 10 degrees and the difference between the predicted angle of cell b and the registered angle of cell a is less than 65 degrees, it is determined that the azimuth angles of the base stations of the two cells are reversed.

[0108] Second, for cells whose predicted angle and registered angle error is greater than 130 degrees but less than 176 degrees, and whose MR data for calculating the registered azimuth angle of the cell is 33 degrees to the left and right (beamwidth / 2) respectively, the proportion of such data to the total number of data is less than 20%, it is considered that the azimuth angle of the cell has a large deviation.

[0109] Ultimately, nine problematic cells were selected based on the above rules and handed over to the branch office for verification and rectification. The rectification status is shown in Table 2, which is a table of verification status of problematic cells with base station azimuth angle. It can be seen that the selected problematic cells do indeed have problems, indicating that the method of correcting the base station azimuth angle is feasible.

[0110] Table 2

[0111]

[0112] In view of the technical problems of current base station azimuth angle correction, such as the need to consume a lot of manpower and material resources, the large workload and low efficiency, and the one-sided and inaccurate analysis of the problem, the above-mentioned embodiments of this disclosure propose a method for automatic correction of base station azimuth angle based on big data.

[0113] like Figure 2 As shown, the above embodiments of this disclosure perform systematic data analysis on the closed-loop process of "RSRP initial parameter determination" - "azimuth calculation program operation" - "feedback azimuth data training and optimization of RSRP parameters". Compared with the open-loop parameter determination method of related technologies that is detached from big data analysis, the output parameters are more reliable.

[0114] The embodiments disclosed above do not rely on the carrier-to-interference ratio, thus eliminating the dependence on neighboring base stations. They can determine more base station azimuth deviations than related technologies, solving the pain points of related technologies.

[0115] The embodiments described above utilize geometric knowledge to obtain an accurate MR data acquisition range (e.g., Figure 3 , Figure 4 , Figure 5 Compared to the single-sector region value taking of the prior art, the above embodiments of this disclosure can realize multi-sector region value taking of one TA value and one sector region, which efficiently extracts the features of big data, thereby reducing the loss of cluster computing power and enabling enterprises to reduce costs and increase efficiency.

[0116] Figure 6 These are schematic diagrams illustrating some embodiments of the base station azimuth correction device disclosed herein. For example... Figure 6 As shown, the base station azimuth correction device disclosed herein may include a first screening module 61, a second screening module 62, and an azimuth correction module 63, wherein:

[0117] The first filtering module 61 is used to filter out measurement report data that meet the filtering conditions, wherein the filtering condition is that the reference signal received power is greater than a predetermined reference signal received power.

[0118] In some embodiments of this disclosure, the first filtering module 61 can be used to associate the latitude and longitude, reference signal received power, base station identifier, cell identifier, and time advance data in the measurement report data with the base station identifier and base station latitude and longitude; and to filter out the measurement report data that meets the filtering conditions from the associated measurement report data.

[0119] The second filtering module 62 is used to filter out measurement report data with accurate time advance values ​​from the measurement report data that meet the filtering conditions.

[0120] In some embodiments of this disclosure, the second filtering module 62 can be used to determine the collection range of the corresponding location point as a circular region for each time advance value in a single base station; and to determine the range of multiple concentric circular regions for multiple time advance values ​​in a single base station, wherein the range of regions is the effective time advance value region.

[0121] The azimuth correction module 63 is used to determine the predicted azimuth based on the measurement report data of the accurate time advance value.

[0122] In some embodiments of this disclosure, the azimuth correction module 63 can be used to determine the predicted azimuth based on the longitude and latitude of two auxiliary global positioning systems and the accurate time advance value.

[0123] In some embodiments of this disclosure, such as Figure 6 As shown, the base station azimuth correction device disclosed herein may further include 2364, wherein:

[0124] The comparison and correction module 64 is used to compare the predicted azimuth angle and the filed azimuth angle, and iteratively correct the predetermined reference signal receiving power. According to the corrected predetermined reference signal receiving power, the first screening module 61, the second screening module 62 and the azimuth angle correction module 63 are then instructed to repeatedly perform the operations of screening out measurement report data that meet the screening conditions, screening out measurement report data with accurate time advance values ​​and calculating the base station azimuth angle based on the measurement report data with accurate time advance values.

[0125] In some embodiments of this disclosure, such as Figure 6 As shown, the base station azimuth correction device of this disclosure may further include a problem cell determination module 65, wherein:

[0126] The problematic cell identification module 65 is used to identify cells with problematic base station azimuth angles based on the predicted azimuth angle; and to send the cells with problematic base station azimuth angles to the user for verification and rectification.

[0127] In some embodiments of this disclosure, the problem cell determination module 65 can be used to determine the base station azimuth angles of the first cell and the second cell whose error between the predicted azimuth angle and the registered azimuth angle is within a predetermined range. If the difference between the predicted azimuth angle of the first cell and the registered azimuth angle of the second cell is less than a first predetermined angle, and the difference between the predicted azimuth angle of the second cell and the registered azimuth angle of the first cell is less than a second predetermined angle, then the base station azimuth angles of the first cell and the second cell are reversed.

[0128] In some embodiments of this disclosure, the problematic cell determination module 65 can be used to determine that the azimuth deviation of a cell is greater than a predetermined threshold if the proportion of the number of measurement report data within the third predetermined angle range on both sides of the cell's registered azimuth angle to the total number of measurement report data is less than a predetermined proportion.

[0129] In some embodiments of this disclosure, the base station azimuth correction device is used to perform any of the embodiments described above (e.g., Figures 1-5 The operation of the base station azimuth correction method described in any embodiment.

[0130] The present disclosure provides a device for correcting base station azimuth angles based on MR data. Addressing the issue of untimely detection of base station azimuth angle deviations in related technologies, the present disclosure improves the accuracy of basic data by establishing a big data analysis algorithm model to periodically check all cells in the network. Therefore, the present disclosure can quickly determine whether the azimuth angle of the base station antenna in the source cell has deviated, enabling enterprises to reduce costs and increase efficiency.

[0131] Figure 7 This is a schematic diagram of the structure of some embodiments of the base station azimuth correction device disclosed herein. For example... Figure 7 As shown, the base station azimuth correction device includes a memory 71 and a processor 72.

[0132] Memory 71 is used to store instructions, and processor 72 is coupled to memory 71. Processor 72 is configured to execute instructions stored in memory as described in any of the above embodiments (e.g., Figure 1 or Figure 4 The base station azimuth correction method described in the embodiment)

[0133] like Figure 7 As shown, the base station azimuth correction device also includes a communication interface 73 for information exchange with other devices. Simultaneously, the base station azimuth correction device also includes a bus 74, through which the processor 72, communication interface 73, and memory 71 communicate with each other.

[0134] The memory 71 may include high-speed RAM, and may also include non-volatile memory, such as at least one disk drive. The memory 71 may also be a memory array. The memory 71 may also be divided into blocks, and the blocks may be combined into virtual volumes according to certain rules.

[0135] Furthermore, processor 72 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present disclosure.

[0136] The embodiments disclosed above systematically analyze the closed-loop process of "RSRP initial parameter determination" - "azimuth calculation program operation" - "feedback azimuth data training and optimization of RSRP parameters". Compared with the open-loop parameter determination methods of related technologies that are detached from big data analysis, the output parameters are more reliable.

[0137] The embodiments disclosed above do not rely on the carrier-to-interference ratio, thus eliminating the dependence on neighboring base stations. They can determine more base station azimuth deviations than related technologies, solving the pain points of related technologies.

[0138] The embodiments described above utilize geometric knowledge to obtain an accurate MR data acquisition range (e.g., Figure 3 , Figure 4 , Figure 5 Compared to the single-sector region value taking of the prior art, the above embodiments of this disclosure can realize multi-sector region value taking of one TA value and one sector region, which efficiently extracts the features of big data, thereby reducing the loss of cluster computing power and enabling enterprises to reduce costs and increase efficiency.

[0139] According to another aspect of this disclosure, a base station azimuth correction system is provided, comprising any of the embodiments described above (e.g., Figure 6 or Figure 7 The base station azimuth correction device described in the embodiment)

[0140] According to another aspect of this disclosure, a non-transitory computer-readable storage medium is provided, wherein the non-transitory computer-readable storage medium stores computer instructions that, when executed by a processor, implement any of the embodiments described above (e.g., Figures 1-5 The base station azimuth correction method described in any embodiment.

[0141] Those skilled in the art will understand that embodiments of this disclosure can be provided as methods, apparatus, or computer program products. Therefore, this disclosure can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this disclosure can take the form of a computer program product embodied on one or more computer-usable non-transitory storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0142] This disclosure is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0143] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0144] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0145] The base station azimuth correction device described above can be implemented as including a general-purpose processor, programmable logic controller (PLC), digital signal processor (DSP), application-specific integrated circuit (ASIC), field-programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware component or any suitable combination thereof for performing the functions described in this application.

[0146] This concludes the detailed description of the present disclosure. To avoid obscuring the concept of the disclosure, some details known in the art have not been described. Those skilled in the art will fully understand how to implement the technical solutions disclosed herein based on the above description.

[0147] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware, or by a program instructing the relevant hardware to implement them. The program can be stored in a non-transitory computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0148] The description in this disclosure is provided for illustrative and descriptive purposes only and is not intended to be exhaustive or to limit the disclosure to its forms. Many modifications and variations will be apparent to those skilled in the art. The embodiments were chosen and described in order to better illustrate the principles and practical application of this disclosure and to enable those skilled in the art to understand this disclosure and to design various embodiments with various modifications suitable for a particular purpose.

Claims

1. A base station azimuth correction method, characterized by, include: Filter out measurement report data that meet the filtering criteria, wherein the filtering criteria is that the reference signal received power is greater than a predetermined reference signal received power; From the measurement report data that meets the screening criteria, select the measurement report data with accurate time advance values; The predicted azimuth is determined based on the measurement report data of the accurate time advance value; Based on the predicted azimuth angle, the cells with problematic base station azimuth angles are identified. The determination of the cells with problematic base station azimuth angles based on the predicted azimuth angle includes: for a first cell and a second cell where the error between the predicted azimuth angle and the registered azimuth angle is within a predetermined range, if the difference between the predicted azimuth angle of the first cell and the registered azimuth angle of the second cell is less than a first predetermined angle, and the difference between the predicted azimuth angle of the second cell and the registered azimuth angle of the first cell is less than a second predetermined angle, then it is determined that the base station azimuth angles of the first cell and the second cell are reversed. The cells with problematic base station azimuth angles will be sent to users for verification and rectification.

2. The base station azimuth correction method according to claim 1, characterized in that, Also includes: The predicted azimuth angle and the filed azimuth angle are compared, and the predetermined reference signal receiving power is iteratively corrected. According to the corrected predetermined reference signal received power, the steps of filtering out measurement report data that meet the filtering conditions, filtering out measurement report data with accurate time advance values, and calculating the base station azimuth angle based on the measurement report data with accurate time advance values ​​are repeated.

3. A base station azimuth correction method, characterized by, include: Filter out measurement report data that meet the filtering criteria, wherein the filtering criteria is that the reference signal received power is greater than a predetermined reference signal received power; From the measurement report data that meets the screening criteria, select the measurement report data with accurate time advance values; The predicted azimuth is determined based on the measurement report data of the accurate time advance value; Based on the predicted azimuth angle, the cells with problematic base station azimuth angles are identified. The identification of cells with problematic base station azimuth angles based on the predicted azimuth angle includes: for cells where the error between the predicted azimuth angle and the registered azimuth angle is within a predetermined range, if the proportion of the number of measurement report data within the third predetermined angle range on both sides of the registered azimuth angle of the cell to the total number of measurement report data is less than a predetermined proportion value, then the deviation of the azimuth angle of the cell is determined to be greater than a predetermined threshold. The cells with problematic base station azimuth angles will be sent to users for verification and rectification.

4. The base station azimuth correction method according to any one of claims 1 to 3, characterized by, The measurement report data that meets the screening criteria includes: The latitude and longitude, reference signal received power, base station identifier, cell identifier, and time advance data in the measurement report are associated with the base station identifier and base station latitude and longitude. From the associated measurement report data, filter out the measurement report data that meets the filtering criteria.

5. The base station azimuth correction method according to any one of claims 1 to 3, characterized by, The measurement report data that filters out accurate time advance values ​​includes: For each time advance value in a single base station, the collection range of the corresponding location point is determined as a circular area; For multiple time advance values ​​in a single base station, the range of multiple concentric ring regions is determined, and the range of the region is the effective time advance value region.

6. The base station azimuth correction method according to any one of claims 1 to 3, characterized by, The determination of the predicted azimuth angle based on the measurement report data of the accurate time advance value includes: The predicted azimuth is determined based on the longitude and latitude of the two auxiliary global positioning systems and the accurate time advance value.

7. A base station azimuth correction apparatus, characterized by comprising: include: The first filtering module is used to filter out measurement report data that meet the filtering criteria, wherein the filtering criteria is that the reference signal received power is greater than a predetermined reference signal received power. The second filtering module is used to filter out measurement report data with accurate time advance values ​​from the measurement report data that meet the filtering conditions. The azimuth correction module is used to determine the predicted azimuth based on the measurement report data of the accurate time advance value; The problematic cell identification module is used to identify cells with problematic base station azimuth angles based on the predicted azimuth angle; and to send the cells with problematic base station azimuth angles to the user for verification and rectification. In the problematic cell determination module, when a cell with a problematic base station azimuth is determined based on the predicted azimuth, the module is used to determine the base station azimuth of the first cell and the second cell, where the error between the predicted azimuth and the registered azimuth is within a predetermined range. If the difference between the predicted azimuth of the first cell and the registered azimuth of the second cell is less than a first predetermined angle, and the difference between the predicted azimuth of the second cell and the registered azimuth of the first cell is less than a second predetermined angle, then the module determines that the base station azimuths of the first cell and the second cell are reversed.

8. A base station azimuth correction apparatus, characterized by comprising: include: The first filtering module is used to filter out measurement report data that meet the filtering criteria, wherein the filtering criteria is that the reference signal received power is greater than a predetermined reference signal received power. The second filtering module is used to filter out measurement report data with accurate time advance values ​​from the measurement report data that meet the filtering conditions. The azimuth correction module is used to determine the predicted azimuth based on the measurement report data of the accurate time advance value; The problematic cell identification module is used to identify cells with problematic base station azimuth angles based on the predicted azimuth angle; and to send the cells with problematic base station azimuth angles to the user for verification and rectification. Among them, the problematic cell determination module, when determining a cell with a problematic base station azimuth angle based on the predicted azimuth angle, is used for cells where the error between the predicted azimuth angle and the registered azimuth angle is within a predetermined range. If the proportion of the number of measurement report data within the third predetermined angle range on both sides of the registered azimuth angle of the cell to the total number of measurement report data is less than a predetermined proportion value, then the azimuth angle deviation of the cell is determined to be greater than a predetermined threshold.

9. A base station azimuth correction apparatus, characterized by comprising: include: Memory, used to store instructions; A processor is configured to execute the instructions, causing the base station azimuth correction device to perform operations implementing the base station azimuth correction method as described in any one of claims 1-6.

10. A base station azimuth correction system, characterized by, It includes the base station azimuth correction device as described in any one of claims 7-9.

11. A non-transitory computer-readable storage medium, characterized in that, The non-transient computer-readable storage medium stores computer instructions that, when executed by a processor, implement the base station azimuth correction method as described in any one of claims 1-6.

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