A method for identifying over-covered cells based on MRO

Abstract

The present invention provides an over-coverage cell identification method based on MRO, which belongs to the field of communication technology and includes the steps of: obtaining MRO sampling data of a main service cell and corresponding multiple neighboring cells; obtaining the overlapping coverage of the current main service cell, if the overlapping coverage is greater than a preset overlapping coverage threshold, the neighboring cell corresponding to the current main service cell is an affected neighboring cell; taking the affected neighboring cells that are not the first circle neighboring cells as over-coverage neighboring cells; if the number of over-coverage neighboring cells is greater than the over-coverage neighboring cell threshold, the current main service cell is an over-coverage cell. The present invention can truly reflect the actual network situation of the user terminal through the massive MRO data measured periodically, and performs over-coverage analysis of the cell according to MRO, which greatly improves the accuracy of the analysis; it not only considers the coverage distance of the cell unilaterally, but also combines the overlapping coverage of the main service cell and the neighboring cell, which improves the accuracy of the over-coverage analysis; compared with the traditional road test scanning technology, it saves labor costs.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to an over-coverage cell identification method based on MRO. Background Art

[0002] In recent years, with the rapid economic growth and high-speed urban development, new high-density cells have emerged. In order to prevent the radio signals of mobile communications from being blocked and attenuated during transmission, the method of adding base stations has been adopted to strengthen signal coverage to ensure that users can switch to appropriate adjacent cells in time when moving to avoid communication interruption. However, this method will lead to excessive cell coverage and overlap. Overcoverage will have a great negative impact on user experience, including: (1) Overcoverage is prone to produce island effects and frequency interference, which can easily make it difficult for user equipment to switch between different base stations, and can easily lead to dropped calls and frequent TCH switching due to untimely switching; (2) Overcoverage will absorb additional traffic and easily cause cell channel congestion in the overlapping area, affecting user communication and call efficiency.

[0003] Traditional over-coverage analysis technology requires manual handheld professional equipment to perform road testing or frequency scanning, use the cell to be tested as the main service cell to perform signal sampling, analyze the characteristics of the sampling points, and obtain communication data from professional equipment to determine whether the sampling point is over-covered. This method can only test a limited number of sampling points, and the areas covered by multiple base stations need to be tested separately by manual labor, which is inefficient and difficult to cover large areas, easily leading to a waste of manpower and material resources.

[0004] Therefore, it is difficult for existing over-coverage analysis technologies to determine over-coverage cells efficiently, accurately, and quickly. Summary of the invention

[0005] The present invention provides an over-coverage cell identification method based on MRO, which quickly analyzes the over-coverage cells of the entire network through massive 5G MRO sampling data, thereby saving labor costs and improving analysis efficiency.

[0006] The present invention provides a method for identifying over-covered cells based on MRO, comprising the steps of:

[0007] S1 obtains MRO sampling data of any primary serving cell and corresponding multiple neighboring cells respectively;

[0008] S2 obtains the overlapping coverage of the current primary service cell based on the MRO sampling data. If the overlapping coverage is greater than a preset overlapping coverage threshold, the neighboring cell corresponding to the current primary service cell is an affected neighboring cell, and the number of affected neighboring cells of the primary service cell is output;

[0009] S3 determines whether each affected neighboring cell is a first-circle neighboring cell of the primary serving cell, and whether the affected neighboring cells that are not the first-circle neighboring cells are over-covered neighboring cells, and outputs the number of the over-covered neighboring cells;

[0010] S4: If the number of over-covered neighboring cells of the current primary serving cell is greater than a preset over-covered neighboring cell threshold, the current primary serving cell is an over-covered cell.

[0011] According to an over-coverage cell identification method based on MRO provided by the present invention, the MRO sampling data is parsed, comprising the steps of:

[0012] Obtaining existing network working parameters, including cell name, eNodeBID, base station type, base station location information, CI, base station signal frequency, base station antenna direction angle, base station antenna hanging height, and base station antenna transmission power;

[0013] Get the RSRP of the primary serving cell, the weak coverage sampling points, the neighboring cell relationship of the primary serving cell, the RSRP of the neighboring sampling points, and the RSRP of the overlapping coverage area.

[0014] According to an over-covered cell identification method based on MRO provided by the present invention, in step S2, obtaining overlapping coverage of multiple neighboring cells and the current primary serving cell specifically includes:

[0015] S201, based on the MRO sampling data, obtain sampling points of a neighboring area that appear in the MRO sampling data, and obtain a first RSRP value of each sampling point;

[0016] S202: based on the MR data of the neighboring area, obtaining the total number of sampling points in the neighboring area, obtaining the same overlapping sampling points and corresponding numbers as in step S201, and obtaining the second RSRP value of each overlapping sampling point;

[0017] S203, for any overlapping sampling point, obtaining a difference between the first RSRP value and the second RSRP value;

[0018] S204 outputs the number of sampling points whose difference is greater than the preset RSRP difference threshold, and obtains the overlapping coverage as:

[0019] Overlap coverage=the number of sampling points whose difference is greater than the preset RSRP difference threshold / the total number of sampling points×100%.

[0020] According to an over-coverage cell identification method based on MRO provided by the present invention, obtaining the over-coverage impact ratio of the primary serving cell on the neighboring cell specifically includes:

[0021] Over-coverage impact ratio = number of overlapping sampling points / total number of sampling points × 100%.

[0022] According to a method for identifying over-covered cells based on MRO provided by the present invention, for any neighboring cell, if the over-coverage impact ratio of the corresponding main service cell on the neighboring cell is greater than a preset over-coverage impact ratio threshold, the distance between the neighboring cell and the corresponding main service cell is less than a preset distance and the overlapping coverage is greater than a preset overlapping coverage threshold, then the neighboring cell is an affected neighboring cell of the corresponding main service cell.

[0023] According to a method for identifying over-covered cells based on MRO provided by the present invention, it is determined whether each affected neighboring cell is a first-circle neighboring cell of the primary serving cell, specifically comprising the steps of:

[0024] For each affected neighboring cell, obtaining the distance between the affected neighboring cell and the primary serving cell;

[0025] Obtain the direction angles of the main service cell and the affected neighboring cell, and respectively obtain the angles between the bisector of the direction angle and the connecting line between the main service cell and the affected neighboring cell;

[0026] According to the angle from small to large, it is determined whether the main service cell has an influencing neighboring area with a smaller angle and a smaller distance than the current influencing neighboring area. If not, it is determined that the current influencing neighboring area is the first circle neighboring area of ​​the main service cell.

[0027] According to a method for identifying over-covered cells based on MRO provided by the present invention, it is determined whether each affected neighboring cell is a first-circle neighboring cell of the primary serving cell, including the steps of:

[0028] According to the distance size, a plurality of distance lists between the affected neighboring cells and the primary service cell are arranged from large to small; according to the angle size, a plurality of angle lists between the affected neighboring cells and the primary service cell are arranged from large to small;

[0029] According to the distance list and the angle list, it is determined in turn whether the main service cell has an influencing neighboring area with a smaller angle and a smaller distance than the current influencing neighboring area. If not, it is determined that the current influencing neighboring area is the first circle neighboring area of ​​the main service cell.

[0030] On the other hand, the present invention also provides an over-coverage cell identification device based on MRO, comprising a data acquisition module, a data analysis module, an over-coverage neighboring area judgment module and an over-coverage cell identification module, wherein:

[0031] The data acquisition module is used to acquire MRO sampling data of any primary serving cell and corresponding multiple neighboring cells from the corresponding base station;

[0032] The data analysis module is used to analyze the MRO sampling data to obtain the overlapping coverage of the current primary service cell. If the overlapping coverage is greater than a preset overlapping coverage threshold, the neighboring area corresponding to the current primary service cell is an affected neighboring area, and the number of affected neighboring areas of the primary service cell is output;

[0033] The over-covered neighboring area judgment module is used to judge whether each affected neighboring area is a first-circle neighboring area of ​​the primary serving cell, and the affected neighboring area that is not a first-circle neighboring area is an over-covered neighboring area, and output the number of the over-covered neighboring areas;

[0034] The over-covered cell identification module obtains the number of the over-covered neighboring cells. If the number of the over-covered neighboring cells of the current primary serving cell is greater than a preset over-covered neighboring cell threshold, the current primary serving cell is an over-covered cell.

[0035] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of any of the above-mentioned methods for identifying over-covered cells are implemented.

[0036] The present invention also provides a non-transitory computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of any of the above-mentioned methods for identifying over-covered cells are implemented.

[0037] The present invention provides an over-coverage cell identification method based on MRO, which obtains MRO sampling data of a primary service cell and corresponding multiple neighboring cells, and can truly reflect the actual network situation of a user terminal through the massive MRO data measured periodically. The over-coverage analysis of the cell is performed according to MRO, which greatly improves the accuracy of the analysis.

[0038] By obtaining the overlapping coverage of the current main service cell, it is possible to determine whether the neighboring cell corresponding to the current main service cell is an impacting neighboring cell. This method not only considers the coverage distance of the cell unilaterally, but also combines the overlapping coverage of the main service cell and the neighboring cell, thereby improving the accuracy of over-coverage analysis. Compared with the traditional drive test scanning technology, it saves labor costs.

[0039] In particular, the method of the present invention is particularly suitable for 5G base station over-coverage analysis. Since the signal range of 5G base stations is relatively small, 5G base stations are often more densely distributed in areas with high population density. The method provided by the present invention helps operators find over-coverage 5G signal areas, thereby avoiding island effects, frequency interference and other phenomena, and assists in reducing the cost of operators deploying 5G base stations, which helps promote the popularization of 5G communication technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0041] Figure 1 It is a flow chart of the over-coverage cell identification method based on MRO provided by the present invention;

[0042] Figure 2 It is one of the neighboring cell structure schematic diagrams of the over-coverage cell identification method based on MRO provided by the present invention;

[0043] Figure 3 This is the second schematic diagram of the neighboring cell structure of the over-coverage cell identification method based on MRO provided by the present invention. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0045] The terms "first", "second", "third", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0046] In one embodiment, Figure 1 The present invention provides a method for identifying over-covered cells based on MRO, comprising the steps of:

[0047] S1 obtains MRO sampling data of any primary serving cell and corresponding multiple neighboring cells respectively;

[0048] S2 obtains the overlapping coverage of the current primary service cell based on the MRO sampling data. If the overlapping coverage is greater than a preset overlapping coverage threshold, the neighboring cell corresponding to the current primary service cell is an affected neighboring cell, and the number of affected neighboring cells of the primary service cell is output;

[0049] S3 determines whether each affected neighboring cell is a first-circle neighboring cell of the primary serving cell, and whether the affected neighboring cells that are not the first-circle neighboring cells are over-covered neighboring cells, and outputs the number of the over-covered neighboring cells;

[0050] S4: If the number of over-covered neighboring cells of the current primary serving cell is greater than a preset over-covered neighboring cell threshold, the current primary serving cell is an over-covered cell.

[0051] Further, the MRO sampling data is parsed, including:

[0052] Obtaining existing network working parameters, including cell name, eNodeBID, base station type, base station location information, CI, base station signal frequency, base station antenna direction angle, base station antenna hanging height, and base station antenna transmission power;

[0053] Preferably, the base station type is a 5G base station. Since the signal range of a 5G base station is relatively small, the 5G base stations are often more densely distributed in places with high population density, which means that 5G base stations are more likely to have over-coverage. Over-coverage will cause the quality of the 5G signal and the network speed to decrease. The method provided by the present invention helps operators find 5G signal areas with over-coverage.

[0054] Get the RSRP of the primary serving cell, the weak coverage sampling points, the neighboring cell relationship of the primary serving cell, the RSRP of the neighboring sampling points, and the RSRP of the overlapping coverage area.

[0055] It should be noted that MRO data collection is based on eNodeBs. Depending on the traffic volume, each cell may have tens of thousands or hundreds of thousands of records every day, with a data volume of tens to hundreds of terabytes or even larger.

[0056] In particular, for the over-coverage analysis of 5G base stations, due to the high transmission rate of 5G signals, the amount of 5G MRO data is much larger than the amount of general MRO data. Therefore, the present invention preferentially uses the Spark big data processing platform based on the hadoop file system to sort, process and analyze the massive MRO data, and write the analysis results into the Oracle database; wherein the MRO data is the original data of the measurement report sample data file (MRO, Measurement Report OriGinal), and the MRO formatted data is obtained by parsing the MRO original data;

[0057] Obtain the working parameters of the existing network, i.e., the working parameters of the existing network, including but not limited to: cell name, eNodeBID, base station type, longitude and latitude of the base station and working range, CI, frequency, base station antenna direction angle, antenna height, antenna transmit power, etc.;

[0058] According to the dimensions of districts and counties, cities, community users, RSRP, RSRQ, etc., and the relationship between the primary server cell and neighboring cells, the MRO data is parsed and clustered;

[0059] Specifically, Hadoop's map and ruduce are used to parse, extract, and cluster the massive MRO data to obtain basic data in units of eNodeBs; optionally, Spark data processing technology and Oracle relational database are used to perform statistics on the basic data with a day as the granularity to obtain the following indicators: cell sampling point statistics, primary service cell and neighboring cell relationship statistics, overlapping coverage point statistics, mobile terminal user statistics, RSRP interval indicator statistics, and RSRQ interval indicator statistics; this is only used as an example of the present invention and should not be regarded as a further limitation of the present invention;

[0060] Further, in step S2, specific indicators that need to be paid attention to in the cell over-coverage analysis include but are not limited to: the number of over-covered neighboring cells, the overlapping area, the number of points of the neighboring cells in the overlapping area, the distance between the main service cell and the overlapping coverage area, the distance between the neighboring cell and the overlapping coverage area, and the distance between the main service cell and the neighboring cell;

[0061] Specifically, judging whether it is an over-covered cell mainly includes two aspects: (1) judging whether the neighboring cell is an affected neighboring cell; (2) judging whether the neighboring cell is a first-circle neighboring cell. The first-circle neighboring cells generally do not consider signal switching with the corresponding primary serving cell, so it is necessary to exclude the first-circle neighboring cells in the affected neighboring cells, that is:

[0062] Number of over-covered neighboring cells = total number of affected neighboring cells - number of neighboring cells in the first circle;

[0063] Specifically, obtaining overlapping coverage of multiple neighboring cells and the current primary serving cell includes the following steps:

[0064] S201, based on the MRO sampling data, obtain sampling points of a neighboring area that appear in the MRO sampling data, and obtain a first RSRP value of each sampling point;

[0065] S202: based on the MR data of the neighboring area, obtaining the total number of sampling points in the neighboring area, obtaining the same overlapping sampling points and corresponding numbers as in step S201, and obtaining the second RSRP value of each overlapping sampling point;

[0066] S203, for any overlapping sampling point, obtaining a difference between the first RSRP value and the second RSRP value;

[0067] S204 outputs the number of sampling points whose difference is greater than the preset RSRP difference threshold, and obtains the overlapping coverage as:

[0068] Overlap coverage = number of sampling points whose difference is greater than the preset RSRP difference threshold / total number of sampling points × 100%;

[0069] Specifically, it is also necessary to obtain the over-coverage impact ratio of the primary service cell on the neighboring cells:

[0070] Over-coverage impact ratio = number of overlapping sampling points / total number of sampling points × 100%;

[0071] Specifically, for any neighboring cell, if the over-coverage impact ratio of the corresponding main service cell on the neighboring cell is greater than the preset over-coverage impact ratio threshold, the distance between the neighboring cell and the corresponding main service cell is less than the preset distance, and the overlapping coverage is greater than the preset overlapping coverage threshold, then the neighboring cell is an affected neighboring cell of the corresponding main service cell.

[0072] Preferably, the base station type is a 5G base station. Since the signal range of a 5G base station is relatively small, 5G base stations tend to be more densely distributed in places with high population density, which means that 5G base stations are more likely to have over-coverage. Therefore, the present invention takes the over-coverage impact ratio threshold as 3%, and takes the overlapping coverage threshold as 30%; when the overlapping coverage of the neighboring area is greater than 30%, and the over-coverage impact ratio is greater than 3%, and the distance between the neighboring area and the corresponding main service cell is less than 2km, the neighboring area is judged to be an affected neighboring area of ​​the corresponding main service cell; it should be noted that the threshold value here is only an example of an embodiment of the present invention and should not be regarded as a further limitation of the present invention. In fact, it can be adaptively adjusted according to the location of the base station, population density, number of mobile communication devices, number of calls, and type of base station antenna, rather than a unique value. For example, for a service area with only 4G base stations or a mixed setting of 4G base stations and 5G base stations, the values ​​of the over-coverage impact ratio threshold and the overlapping coverage threshold will be different;

[0073] Specifically, Figure 2 As shown, the examples are as follows:

[0074] For example, the measurement result of the primary service cell includes neighboring cells 1, 2, 3, 4, 5, ..., and the number of cells affected by over-coverage of the primary service cell is calculated: the preset RSRP difference threshold is taken as -6dB;

[0075] Neighboring cell 1: It appears twice in the MRO measurement report of the primary service cell. That is, in the MRO data of the primary service cell, the RSRP of the overlapping sampling points with neighboring cell 1 are -102.67dB and -103.25dB respectively. The total number of sampling points of neighboring cell 1 is 6, and the RSRP of the overlapping points with the primary service cell are: -98.36dB and -99.14dB respectively.

[0076] The difference in power strength of the two RSRP received signal codes obtained by the two overlapping sampling points is greater than -6dB, and the number of sampling points whose difference is greater than the preset RSRP difference threshold is 2. The calculated overlapping coverage is: 2 / 6*100%>30%; the over-coverage impact of the primary service cell on the neighboring cell 1 is: 2 / 6*100%>3%, so the neighboring cell 1 is the affected neighboring cell of the primary service cell A;

[0077] Neighboring cell 2: It appears twice in the measurement report of the primary serving cell. That is, in the MRO data of the primary serving cell, the RSRP of the overlapping sampling points with neighboring cell 2 are -97.45dB and -97.28dB respectively. The total number of sampling points of neighboring cell 2 is 7, and the RSRP of the overlapping sampling points are: -90.36dB and -92.14dB respectively.

[0078] For overlapping sampling point 1, the difference between -97.45dB and -90.36dB is less than -6dB; for overlapping sampling points, the difference between -97.28dB and -92.14dB is greater than -6dB; then the number of sampling points whose difference is greater than the preset RSRP difference threshold is 1, and the calculated overlapping coverage is: 1 / 7*100%<30%, and the result of the over-coverage impact of the primary service cell on the neighboring cell 2 is: 2 / 7*100%>3%, which does not meet the overlapping coverage condition, and it is determined that the neighboring cell 2 is not the affected neighboring cell of the primary service cell A;

[0079] Neighboring cell 3: appears once in the measurement report of the primary service cell, that is, in the MRO data of the primary service cell, the RSRP of the overlapping sampling point with neighboring cell 3 is -95.67dB, the total number of sampling points of neighboring cell 3 is: 34, the RSRP of the overlapping point is: -90.42dB, the RSRP received signal code power strength difference obtained by the overlapping sampling point is greater than -6dB, then the number of sampling points whose difference is greater than the preset RSRP difference threshold is 1, and the calculated overlapping coverage is: 1 / 34*100%<30%, the result of the over-coverage impact of the primary service cell on neighboring cell 1 is: 1 / 34*100%<3%, and neighboring cell 3 is not an affected neighboring cell of the primary service cell A;

[0080] Calculate in sequence the number of neighboring cells affected by the primary service cell;

[0081] The above calculation is only a further explanation of the embodiment of the present invention and should not be regarded as a limitation of the embodiment of the present invention, wherein the value of the preset RSRP difference threshold is an adjustable parameter, which can be further adjusted according to actual conditions such as whether it is a 5G base station, base station signal strength, antenna direction angle, antenna type, etc.;

[0082] Further, determining whether each influencing neighboring cell is a first-circle neighboring cell of the primary serving cell includes:

[0083] For each affected neighboring cell, obtaining the distance between the affected neighboring cell and the primary serving cell;

[0084] Obtain the direction angles of the main service cell and the affected neighboring cell, and respectively obtain the angles between the bisector of the direction angle and the connecting line between the main service cell and the affected neighboring cell;

[0085] According to the angle from small to large, it is determined whether the main service cell has an influencing neighboring area with a smaller angle and a smaller distance than the current influencing neighboring area. If not, it is determined that the current influencing neighboring area is the first circle neighboring area of ​​the main service cell.

[0086] Preferably, determining whether each influencing neighboring cell is a first-circle neighboring cell of the primary serving cell is performed in the following manner, including:

[0087] According to the distance size, multiple distance lists between the affected neighboring cells and the primary service cell are arranged from large to small; according to the angle size, multiple angle lists between the affected neighboring cells and the primary service cell are arranged from small to large, that is, the smaller the angle is and the closer it is to 0, the greater the corresponding weight is, and the weight list is further arranged in descending order;

[0088] According to the distance list and the angle list, it is determined in turn whether the main service cell has an influencing neighboring area with a smaller angle and a smaller distance than the current influencing neighboring area. If not, it is determined that the current influencing neighboring area is the first circle neighboring area of ​​the main service cell.

[0089] In a specific embodiment, Figure 3 As shown, the longitude and latitude of the primary service cell are recorded as p1(X1, Y1), the longitude and latitude of the neighboring cell are recorded as p2(X2, Y2), and the straight line connecting the two points is: (Y1-Y) / (Y2-Y1)=(X1-X) / (X2-X1);

[0090] Take any point on the line and record it as p3(X3,Y3);

[0091] Get the direction angle of the cell, draw a sector-shaped cell according to the direction angle of the cell, and take the midpoint of the sector arc, recorded as p4(X4,Y4);

[0092] According to the cosine theorem formula:

[0093] cosθ=(p1p3*p1p3+p1p4*p1p4–p3p4*p3p4) / 2*p1p3*p1p4;

[0094] The angle θ1 between the line connecting p1p4 and the line connecting the main service cell and the neighboring cell is calculated, and the angle between other neighboring cells and the line connecting the main service cell and the corresponding neighboring cells is further calculated;

[0095] If the angle is closer to 0, it means that the signal overlap between the two cells is more serious. The smaller the angle is, the greater the corresponding weight is, that is, the greater the weight of judging whether it is the first circle neighboring cell;

[0096] Repeat the above steps to calculate the angle between each neighboring cell and the primary serving cell, and sort them in descending order of weight;

[0097] Calculate the distances between the affected neighboring cells 1, 2, 3, ... and the primary service cell respectively, distance 1, distance 2, distance 3 ..., and sort them in descending order;

[0098] Under the condition that the weight remains unchanged, according to the weight list arranged in descending order, it is judged in turn whether there is a neighboring area with a smaller distance value and a smaller weight within the radius of the main service cell and the neighboring area i. If not, the neighboring area i is recorded as the first circle neighboring area of ​​the main service cell; otherwise, it is a non-first circle neighboring area;

[0099] Specifically, for example, there are three neighboring areas, a, b, and c. They are arranged in descending order of distance, and in descending order of weight, they are neighboring area a, neighboring area b, and neighboring area c. Neighboring areas a to c are judged in order of weight sorting. For neighboring area a, the distance and weight corresponding to neighboring area a are the largest, and there are neighboring areas b and c with smaller distance values ​​and smaller weights. Therefore, neighboring area a is not a first-circle neighboring area; for neighboring area b, there is neighboring area c with a smaller distance value and a smaller weight, so neighboring area b is not a first-circle neighboring area; for neighboring area c, there is no neighboring area with a smaller distance value and a smaller weight, so neighboring area c is a first-circle neighboring area.

[0100] Based on the total number of affected neighboring areas and the number of first-circle neighboring areas calculated by the above method, the formula is applied:

[0101] Number of over-covered neighboring cells = total number of affected neighboring cells - number of neighboring cells in the first circle;

[0102] The number of over-covered neighboring areas is calculated, and step S4 is further performed:

[0103] If the number of over-covered neighboring cells of the current primary service cell is greater than the preset over-covered neighboring cell threshold, it means that the current primary service cell has too many over-covered neighboring cells, and there are areas with severe signal interference with a large number of neighboring cells, which will have a bad impact on the user experience of local users. Therefore, the current primary service cell is judged to be an over-covered cell;

[0104] The method of the present invention can quickly and accurately analyze and confirm the main service cell with over-coverage problem from the massive data through the MRO data stored in the base station, so as to facilitate the technical personnel to make targeted adjustments to the areas with interference and jamming problems, which is helpful for communication service operators to improve service quality and can be used as an effective auxiliary means for base station layout, base station adjustment and signal calibration;

[0105] It should be noted that the over-coverage neighboring cell threshold can be adaptively set according to local specific conditions such as resident population, number of cells, average distance between cells, base station layout location, etc., and the present invention does not limit this.

[0106] In particular, the method of the present invention is particularly suitable for 5G base station over-coverage analysis. Since the signal range of 5G base stations is small, 5G base stations are often more densely distributed in places with high population density. The method provided by the present invention helps operators find 5G signal areas with over-coverage, thereby avoiding the island effect, frequency interference and other phenomena, and auxiliaryly reducing the cost of operators deploying 5G base stations, which is helpful to promote the popularization of 5G communication technology; on the one hand, it saves planning and construction costs, and on the other hand, it can quickly implement 5G network construction;

[0107] In addition, since the coverage area of ​​5G base stations is smaller than that of 4G base stations, the range of the main service cell of 5G base stations is also smaller. Within the same area, more and denser 5G base stations need to be deployed, and the penetration of 5G signals is weaker than that of 4G signals. There will also be signal interference with the existing deployed 4G base stations. Therefore, it is not advisable to manually test the signal quality of each sampling point one by one on site. The method of this application can efficiently detect areas with over-coverage, which can greatly reduce the operator's signal detection labor costs;

[0108] On the other hand, the present invention further provides an over-coverage cell identification device based on MRO. The over-coverage cell identification device described below and the over-coverage cell identification method described above can refer to each other, and specifically includes a data acquisition module, a data analysis module, an over-coverage neighboring area judgment module and an over-coverage cell identification module, wherein:

[0109] The data acquisition module is used to acquire MRO sampling data of any primary service cell and corresponding multiple neighboring cells from the corresponding base station;

[0110] The data analysis module is used to analyze the MRO sampling data to obtain the overlapping coverage of the current primary service cell. If the overlapping coverage is greater than a preset overlapping coverage threshold, the neighboring area corresponding to the current primary service cell is an affected neighboring area, and the number of affected neighboring areas of the primary service cell is output;

[0111] The over-covered neighboring area judgment module is used to judge whether each affected neighboring area is a first-circle neighboring area of ​​the primary service cell, and the affected neighboring area that is not a first-circle neighboring area is an over-covered neighboring area, and output the number of the over-covered neighboring areas;

[0112] The over-covered cell identification module obtains the number of the over-covered neighboring cells. If the number of the over-covered neighboring cells of the current primary serving cell is greater than a preset over-covered neighboring cell threshold, the current primary serving cell is an over-covered cell.

[0113] The present invention also provides an electronic device, which may include: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus. The processor may call the logic instructions in the memory to execute the MRO-based over-coverage cell identification method provided by the above methods, including the steps of:

[0114] S1 obtains MRO sampling data of any primary serving cell and corresponding multiple neighboring cells respectively;

[0115] S2 obtains the overlapping coverage of the current primary service cell based on the MRO sampling data. If the overlapping coverage is greater than a preset overlapping coverage threshold, the neighboring cell corresponding to the current primary service cell is an affected neighboring cell, and the number of affected neighboring cells of the primary service cell is output;

[0116] S3 determines whether each affected neighboring cell is a first-circle neighboring cell of the primary serving cell, and whether the affected neighboring cells that are not the first-circle neighboring cells are over-covered neighboring cells, and outputs the number of the over-covered neighboring cells;

[0117] S4 If the number of over-covered neighboring cells of the current primary serving cell is greater than a preset over-covered neighboring cell threshold, the current primary serving cell is an over-covered cell. In addition, the logic instructions in the memory 830 described above can be implemented in the form of software function units and can be stored in a computer-readable storage medium when sold or used as an independent product.

[0118] Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., various media that can store program codes.

[0119] On the other hand, the present invention further provides a computer program product, the computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, and when the program instructions are executed by a computer, the computer can execute the MRO-based over-coverage cell identification method provided by the above methods, including the steps of:

[0120] S1 obtains MRO sampling data of any primary serving cell and corresponding multiple neighboring cells respectively;

[0121] S2 obtains the overlapping coverage of the current primary service cell based on the MRO sampling data. If the overlapping coverage is greater than a preset overlapping coverage threshold, the neighboring cell corresponding to the current primary service cell is an affected neighboring cell, and the number of affected neighboring cells of the primary service cell is output;

[0122] S3 determines whether each affected neighboring cell is a first-circle neighboring cell of the primary serving cell, and whether the affected neighboring cells that are not the first-circle neighboring cells are over-covered neighboring cells, and outputs the number of the over-covered neighboring cells;

[0123] S4: If the number of over-covered neighboring cells of the current primary serving cell is greater than a preset over-covered neighboring cell threshold, the current primary serving cell is an over-covered cell.

[0124] In another aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the method for identifying over-covered cells based on MRO provided by the above methods is implemented, comprising the steps of:

[0125] S1 obtains MRO sampling data of any primary serving cell and corresponding multiple neighboring cells respectively;

[0126] S2 obtains the overlapping coverage of the current primary service cell based on the MRO sampling data. If the overlapping coverage is greater than a preset overlapping coverage threshold, the neighboring cell corresponding to the current primary service cell is an affected neighboring cell, and the number of affected neighboring cells of the primary service cell is output;

[0127] S3 determines whether each affected neighboring cell is a first-circle neighboring cell of the primary serving cell, and whether the affected neighboring cells that are not the first-circle neighboring cells are over-covered neighboring cells, and outputs the number of the over-covered neighboring cells;

[0128] S4 If the number of over-covered neighboring cells of the current main service cell is greater than the preset over-coverage neighboring cell threshold, the current main service cell is an over-coverage cell. The above-described device embodiments are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Those of ordinary skill in the art may understand and implement it without creative effort.

[0129] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0130] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for identifying over-covered cells based on MRO, characterized in that: include: S1 obtains MRO sampling data of any primary serving cell and corresponding multiple neighboring cells respectively; S2 obtains the overlapping coverage of the current primary service cell based on the MRO sampling data. If the overlapping coverage is greater than a preset overlapping coverage threshold, the neighboring cell corresponding to the current primary service cell is an affected neighboring cell, and the number of affected neighboring cells of the primary service cell is output; S3 determines whether each affected neighboring cell is a first-circle neighboring cell of the primary serving cell, and whether the affected neighboring cells that are not the first-circle neighboring cells are over-covered neighboring cells, and outputs the number of the over-covered neighboring cells; S4: If the number of over-covered neighboring cells of the current primary serving cell is greater than a preset over-covered neighboring cell threshold, the current primary serving cell is an over-covered cell; Determining whether each influencing neighboring cell is a first-circle neighboring cell of the primary serving cell includes: For each affected neighboring cell, obtaining the distance between the affected neighboring cell and the primary serving cell; Obtain the direction angles of the main service cell and the affected neighboring cell, and respectively obtain the angles between the bisector of the direction angle and the connecting line between the main service cell and the affected neighboring cell; According to the angle from small to large, it is determined whether the main service cell has an influencing neighboring area with a smaller angle and a smaller distance than the current influencing neighboring area. If not, it is determined that the current influencing neighboring area is the first circle neighboring area of ​​the main service cell.

2. The method for identifying over-covered cells based on MRO according to claim 1, characterized in that: The MRO sampling data is analyzed, including: Obtaining existing network working parameters, including cell name, eNodeBID, base station type, base station location information, CI, base station signal frequency, base station antenna direction angle, base station antenna hanging height, and base station antenna transmission power; Get the RSRP of the primary serving cell, the weak coverage sampling points, the neighboring cell relationship of the primary serving cell, the RSRP of the neighboring sampling points, and the RSRP of the overlapping coverage area.

3. The method for identifying over-covered cells based on MRO according to claim 2, characterized in that: In step S2, obtaining overlapping coverage of multiple neighboring cells and the current primary serving cell includes: S201, based on the MRO sampling data, obtain sampling points of a neighboring area that appear in the MRO sampling data, and obtain a first RSRP value of each sampling point; S202: based on the MR data of the neighboring area, obtaining the total number of sampling points in the neighboring area, obtaining the same overlapping sampling points and corresponding numbers as in step S201, and obtaining the second RSRP value of each overlapping sampling point; S203, for any overlapping sampling point, obtaining a difference between the first RSRP value and the second RSRP value; S204 outputs the number of sampling points whose difference is greater than the preset RSRP difference threshold, and obtains the overlapping coverage: Overlap coverage=the number of sampling points whose difference is greater than the preset RSRP difference threshold / the total number of sampling points×100%.

4. The method for identifying over-covered cells based on MRO according to claim 3, characterized in that: Get the proportion of over-coverage impact of the main service cell on the neighboring cells: Over-coverage impact ratio = number of overlapping sampling points / total number of sampling points × 100%.

5. The method for identifying over-covered cells based on MRO according to claim 4, characterized in that: For any neighboring cell, if the over-coverage impact ratio of the corresponding main service cell on the neighboring cell is greater than the preset over-coverage impact ratio threshold, the distance between the neighboring cell and the corresponding main service cell is less than the preset distance and the overlapping coverage is greater than the preset overlapping coverage threshold, then the neighboring cell is an affected neighboring cell of the corresponding main service cell.

6. The method for identifying over-covered cells based on MRO according to claim 1, characterized in that: Determining whether each influencing neighboring cell is a first-circle neighboring cell of the primary serving cell includes: According to the distance size, a plurality of distance lists between the affected neighboring cells and the primary service cell are arranged from large to small; according to the angle size, a plurality of angle lists between the affected neighboring cells and the primary service cell are arranged from large to small; According to the distance list and the angle list, it is determined in turn whether the main service cell has an influencing neighboring area with a smaller angle and a smaller distance than the current influencing neighboring area. If not, it is determined that the current influencing neighboring area is the first circle neighboring area of ​​the main service cell.

7. An MRO-based over-coverage cell identification device, executing the MRO-based over-coverage cell identification method according to claim 1, characterized in that: include: A data acquisition module, used to acquire MRO sampling data of any primary service cell and corresponding multiple neighboring cells from a corresponding base station; A data analysis module is used to analyze the MRO sampling data to obtain the overlapping coverage of the current primary service cell. If the overlapping coverage is greater than a preset overlapping coverage threshold, the neighboring area corresponding to the current primary service cell is an affected neighboring area, and the number of affected neighboring areas of the primary service cell is output; An over-covered neighboring cell judgment module is used to judge whether each affected neighboring cell is a first-circle neighboring cell of the primary service cell, and whether an affected neighboring cell other than the first-circle neighboring cell is an over-covered neighboring cell, and output the number of the over-covered neighboring cells; The over-covered cell identification module obtains the number of the over-covered neighboring cells. If the number of the over-covered neighboring cells of the current primary serving cell is greater than a preset over-covered neighboring cell threshold, the current primary serving cell is an over-covered cell.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the over-coverage cell identification method based on MRO are implemented as described in any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the over-coverage cell identification method based on MRO are implemented as claimed in any one of claims 1 to 6.

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