CN101621808B - Method and device for confirming cell coverage area - Google Patents
Method and device for confirming cell coverage area Download PDFInfo
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Abstract
The invention discloses a method and a device for confirming a cell coverage area. The method comprises the following steps: step A, collecting and choosing initial data needed for confirming a coverage area of a source cell from an operation and maintenance center system; step B, acquiring category messages of each sample cell after classifying each sample cell according to the collected and chosen initial data needed for confirming the coverage area of the source cell; and acquiring the coverage area of the source cell according to the category messages of each sample cell. The invention can accurately confirm the coverage area of the source cell in time, and can judge the deviation of the coverage area of the source cell through a plurality of coverage areas of the source cell, which are obtained by comparing the initial data which are in different time quantum and are collected and chosen from the OMC system, thereby helping an operator timely and effectively discover the deviation of the coverage area of the source cell and better performing network maintenance and optimization.
Description
Technical Field
The present invention relates to a cell coverage technology in mobile communication, and in particular, to a method and an apparatus for determining a cell coverage area.
Background
In the last two decades, terrestrial wireless mobile communications have been rapidly developed. The communication between the mobile phone user and the base station is information communication in an electromagnetic wave propagation mode. In a mobile communication network, which usually includes a huge number of cells, each cell has its own coverage, one of the important factors affecting the mobile communication quality is that the cell coverage is problematic, such as handover coverage, critical coverage, under-coverage, etc., and therefore, how to determine the coverage of each cell in a mobile communication network including a large number of cells is crucial for network optimization.
In the prior art, there are generally two ways to determine the cell coverage:
1) and (4) a drive test mode.
The method comprises the steps that a measurer walks along a certain measuring path in a cell needing to be measured and a cell where a sampling point is located in a walking mode, a driving mode and the like, and field intensity values of the cell on the measuring path are measured point by a field intensity tester in the traveling process to obtain field intensity distribution of the cell. Due to the limitation of the ground, the terrain, the cost and other factors, the field intensity data of each point in the required measurement area cannot be obtained by the drive test method, and only partial discrete values in the field intensity distribution of the cell can be obtained.
2) The prediction mode.
The field strength distribution of the area under investigation can be predicted by a corresponding algorithm (e.g. a field strength prediction algorithm) using the field strength distribution of the known area. In the prediction mode, not only the propagation model in the algorithm is required to be in accordance with the actual situation of the current network, but also a lot of very detailed geographic data are needed in the prediction process. For example, the geographic data may include data of terrain, landform, building location, and the like, and may further include parameters such as specific terrain trend information, building height information, and the like, and may further include parameters such as material information of each obstacle; moreover, since the actual geographic environment changes every moment, the geographic data also changes at any moment, so that it is generally difficult to obtain a prediction result that is very consistent with the actual result by using the prediction method. Therefore, the above prediction method needs to analyze, fit and count a large amount of measured data, and has the advantages of large required data amount, large calculation amount, matched geographic data requirement and small effective time period.
Therefore, in the existing method for determining the cell coverage, a large amount of manpower and material resources are required to be consumed for measurement, a large amount of mathematical statistics calculation is required, and the cell level coverage cannot be accurately determined in real time.
Disclosure of Invention
In view of the above, the main objective of the present invention is to provide a method and an apparatus for determining a cell coverage in a mobile communication network, which can accurately determine the cell coverage in real time, and help an operator to timely and effectively find a cell coverage error, thereby performing better network maintenance and optimization work.
In order to achieve the purpose, the technical scheme of the invention is realized as follows:
a method of determining cell coverage, the method comprising:
step A, collecting and selecting original data required by determining a source cell coverage area from an operation and maintenance center OMC system; the source cell is a cell needing to determine a coverage area;
b, classifying each sampling point cell according to the collected and selected original data required for determining the coverage area of the source cell to obtain classification information of each sampling point cell; obtaining the coverage area of the source cell according to the classification information of each sampling point cell; and the sampling point cell is a cell where sampling points except the source cell are located.
The raw data required for determining the coverage area of the source cell comprises: the average downlink level of the source cell; the classification information of each sampling point cell is the classification information of the source cell average downlink level interval of each sampling point cell; the step B comprises the following steps:
step B1, counting the occurrence frequency of each source cell average downlink level value in the collected and selected original data required for determining the source cell coverage area, and calculating the occurrence probability of each source cell average downlink level value in all source cell average level values;
step B2, taking the average downlink level value of the source cell as a horizontal axis and the probability as a vertical axis, smoothly connecting the probability of the average downlink level value of each source cell in the average level values of all the source cells by using a moving average algorithm to obtain a probability curve, and performing interval division on the average downlink level value of the source cells by using the trough of the probability curve as a segmentation point;
step B3, dividing each sampling point cell into different source cell average downlink level intervals according to the source cell average downlink level corresponding to each sampling point cell collected and selected, thereby obtaining source cell average downlink level interval classification information of each sampling point cell;
and step B4, obtaining the coverage area of the source cell according to the source cell average downlink level interval classification information of each sampling point cell.
The raw data required for determining the coverage area of the source cell comprises: the number of sampling points of a weak interference interval of each sampling point cell by a source cell, the number of sampling points of a critical interference interval of each sampling point cell by the source cell and the number of sampling points of a strong interference interval of each sampling point cell by the source cell; the classification information of each sampling point cell is the classification information of the number of sampling points of each sampling point cell;
the step B comprises the following steps:
step B11, respectively carrying out mean value calculation on the number of sampling points of the collected and selected source cell to three interference intervals of each sampling point cell to obtain the average number of the sampling points of the corresponding interference intervals;
step B12, classifying each sampling point cell according to the magnitude relation between the number of sampling points in three interference intervals of each sampling point cell by the source cell and the average number of sampling points in the corresponding interference interval, and obtaining the number classification information of the sampling points of each sampling point cell;
and step B13, obtaining the coverage area of the source cell according to the sampling point number classification information of each sampling point cell.
In step B12, the classifying the sampling point cells to obtain the sampling point number classification information of the sampling point cells includes:
comparing the number of the sampling points in the three interference intervals of the source cell to each sampling point cell with the average number of the sampling points in the corresponding interference interval obtained in the step B11, and obtaining the classification information of the number of the sampling points of each sampling point cell according to the comparison condition;
the condition that the number of sampling points in the interference interval of the sampling point cell is larger than or equal to the average number of the sampling points in the corresponding interference interval is marked as large, the condition that the number of the sampling points in the interference interval of the sampling point cell is smaller than the average number of the sampling points in the corresponding interference interval is marked as small, and each sampling point cell is divided into 8 types according to the mark combination of three interference intervals of each sampling point cell.
The 8 types of sampling point cells comprise:
class 1: the weak interference area is marked as large, the critical interference area is marked as large, and the strong interference area is marked as large;
class 2: the weak interference area is marked as large, the critical interference area is marked as large, and the strong interference area is marked as small;
class 3: the weak interference area is marked as large, the critical interference area is marked as small, and the strong interference area is marked as large;
class 4: the weak interference area is marked as large, the critical interference area is marked as small, and the strong interference area is marked as small;
class 5: the weak interference area is marked as small, the critical interference area is marked as large, and the strong interference area is marked as large;
class 6: the weak interference area is marked as small, the critical interference area is marked as large, and the strong interference area is marked as small;
class 7: the weak interference area is marked as small, the critical interference area is marked as small, and the strong interference area is marked as large;
class 8: the weak interference zone is marked as small, the critical interference zone is marked as small, and the strong interference zone is marked as small.
The raw data required for determining the coverage area of the source cell comprises: the method comprises the following steps that the average downlink level of a source cell, the number of sampling points of a weak interference interval of the source cell to each sampling point cell, the number of sampling points of a critical interference interval of the source cell to each sampling point cell and the number of sampling points of a strong interference interval of the source cell to each sampling point cell are determined; the classification information of each sampling point cell comprises the source cell average downlink level interval classification information of each sampling point cell and the sampling point number classification information of each sampling point cell;
the step B comprises the following steps:
step B111, counting the occurrence frequency of the average downlink level value of each source cell in the collected and selected original data required for determining the coverage area of the source cell, and calculating the occurrence probability of the average downlink level value of each source cell in the average level values of all the source cells;
step B112, taking the average downlink level value of the source cell as a horizontal axis, taking the probability as a vertical axis, smoothly connecting the probabilities of the average downlink level value of each source cell in the average level values of all the source cells by using a moving average algorithm to obtain a probability curve, and performing interval division on the average downlink level value of the source cell by using a trough of the probability curve as a segmentation point;
step B113, dividing each sampling point cell into different source cell average downlink level intervals according to the source cell average downlink level corresponding to each sampling point cell which is collected and selected, thereby obtaining source cell average downlink level interval classification information of each sampling point cell;
step B114, respectively carrying out average value calculation on the number of sampling points of the collected and selected source cell in three interference intervals of each sampling point cell to obtain the average number of the sampling points in the corresponding interference intervals;
step B115, classifying each sampling point cell according to the magnitude relation between the number of sampling points in three interference intervals of each sampling point cell and the average number of sampling points in the corresponding interference interval by the source cell to obtain the number classification information of the sampling points of each sampling point cell;
step B116: and obtaining the coverage area of the source cell according to the source cell average downlink level interval classification information of each sampling point cell and the sampling point number classification information of each sampling point cell.
The step B of obtaining the coverage area of the source cell according to the classification information of each sampling point cell includes:
adding the classification information of each sampling point cell into a system for displaying a cell distribution diagram to obtain a coverage area diagram of a source cell
The system for displaying the cell distribution diagram is a Geographic Information System (GIS).
The method further comprises:
and B, acquiring and selecting original data of different time periods from the OMC system according to the method in the step A and the step B, obtaining the coverage areas of a plurality of source cells according to the original data, and comparing the obtained coverage areas of the plurality of source cells to judge the coverage error of the source cell.
An apparatus for determining cell coverage, the apparatus comprising: the system comprises a data acquisition unit, a sampling point cell classification unit and a sampling point cell classification information processing unit, wherein the data acquisition unit and the sampling point cell classification information processing unit are respectively connected to the sampling point cell classification unit; wherein,
the data acquisition unit is used for acquiring and selecting original data required by determining the coverage area of a source cell from an operation and maintenance center OMC system and sending the original data to the sampling point cell classification unit; the source cell is a cell needing to determine a coverage area;
the sampling point cell classification unit is used for classifying each sampling point cell according to the original data sent by the data acquisition unit to obtain the classification information of each sampling point cell and sending the obtained classification information of each sampling point cell to the sampling point cell classification information processing unit; the sampling point cell is a cell where sampling points other than the source cell are located;
and the sampling point cell classification information processing unit is used for obtaining the coverage range of the source cell according to the classification information of each sampling point cell sent by the sampling point cell classification unit.
The sampling point cell classification unit comprises a level occurrence probability calculation module, a source cell average downlink level interval division module and a sampling point cell classification according to level, wherein the level occurrence probability calculation module and the sampling point cell classification according to level are respectively connected with the source cell average downlink level interval division module; wherein,
the level occurrence probability calculation module is used for receiving original data which are sent by the data acquisition unit and are required for determining the coverage area of the source cell, and the original data which are required for determining the coverage area of the source cell comprise: the source cell average downlink level is used for counting the occurrence frequency of each source cell average downlink level value in the original data, calculating the occurrence probability of each source cell average downlink level value in all source cell average level values, and sending the calculated occurrence probability of each source cell average downlink level value in all source cell average level values to a source cell average downlink level interval division module;
the source cell average downlink level interval dividing module is used for smoothly connecting the probability of each source cell average downlink level value in all source cell average level values sent by the level occurrence probability calculation module by using a moving average algorithm and taking the source cell average downlink level value as a horizontal axis and the probability as a vertical axis to obtain a probability curve, performing interval division on the source cell average downlink level values by using a trough of the probability curve as a segmentation point, and sending the source cell average downlink level interval dividing result to the sampling point cell classifying module according to the level;
the sampling point cell classification module is used for classifying each sampling point cell into different source cell average downlink level intervals according to the interval division result of the source cell sent by the source cell average downlink level interval division module and the source cell average downlink level corresponding to each sampling point cell which is collected and selected, so as to obtain classification information of each sampling point cell, wherein the classification information of each sampling point cell is the source cell average downlink level interval classification information of each sampling point cell, and the obtained source cell average downlink level interval classification information of each sampling point cell is sent to the sampling point cell classification information processing unit.
The sampling point cell classification unit comprises a sampling point number average value calculation module and a sampling point cell classification module according to the number of sampling points, and the sampling point number average value calculation module is connected with the sampling point cell classification module according to the number of the sampling points; wherein,
the sampling point number average calculation module is used for receiving original data sent by a data acquisition unit and required for determining the coverage area of a source cell, and the original data required for determining the coverage area of the source cell comprises: the method comprises the steps that the number of sampling points of a weak interference interval of a source cell to each sampling point cell, the number of sampling points of a critical interference interval of the source cell to each sampling point cell and the number of sampling points of a strong interference interval of the source cell to each sampling point cell are respectively subjected to mean value calculation on the number of the sampling points of three interference intervals of the source cell to each sampling point cell, so that the average number of the sampling points of the corresponding interference intervals is obtained, and the obtained average number of the sampling points of the three interference intervals of the source cell to each sampling point cell is sent to a sampling point cell classification module according to the number of the sampling points;
the sampling point cell classification module according to the number of sampling points is used for classifying each sampling point cell according to the size relation between the number of sampling points in three interference intervals of each sampling point cell by a source cell and the average number of sampling points of a corresponding interference interval sent by the sampling point number average value calculation module to obtain classification information of each sampling point cell, wherein the classification information of each sampling point cell is the sampling point number classification information of each sampling point cell, and the obtained sampling point number classification information of each sampling point cell is sent to the sampling point cell classification information processing unit.
The sampling point cell classification unit comprises a level occurrence probability calculation module, a source cell average downlink level interval division module, a sampling point cell classification module according to level, a sampling point number average value calculation module and a sampling point cell classification module according to the number of sampling points, wherein the level occurrence probability calculation module and the sampling point cell classification module according to level are respectively connected with the source cell average downlink level interval division module, and the sampling point number average value calculation module is connected with the sampling point cell classification module according to the number of sampling points; wherein,
the level occurrence probability calculation module is used for receiving original data which are sent by the data acquisition unit and are required for determining the coverage area of the source cell, and the original data which are required for determining the coverage area of the source cell comprise: the source cell average downlink level is used for counting the occurrence frequency of each source cell average downlink level value in the original data, calculating the occurrence probability of each source cell average downlink level value in all source cell average level values, and sending the calculated occurrence probability of each source cell average downlink level value in all source cell average level values to a source cell average downlink level interval division module;
the source cell average downlink level interval dividing module is used for smoothly connecting the probability of each source cell average downlink level value in all source cell average level values sent by the level occurrence probability calculation module by using a moving average algorithm and taking the source cell average downlink level value as a horizontal axis and the probability as a vertical axis to obtain a probability curve, performing interval division on the source cell average downlink level values by using a trough of the probability curve as a segmentation point, and sending the source cell average downlink level interval dividing result to the sampling point cell classifying module according to the level;
the sampling point cell classification according to level module is used for classifying each sampling point cell into different source cell average downlink level intervals according to the source cell average downlink level interval classification result sent by the source cell average downlink level interval classification module and the source cell average downlink level corresponding to each sampling point cell collected and selected, so as to obtain classification information of each sampling point cell, wherein the classification information of each sampling point cell is the source cell average downlink level interval classification information of each sampling point cell, and the obtained source cell average downlink level interval classification information of the sampling point cell is sent to the sampling point cell classification information processing unit;
the sampling point number average calculation module is used for receiving original data sent by a data acquisition unit and required for determining the coverage area of a source cell, and the original data required for determining the coverage area of the source cell comprises: the method comprises the steps that the number of sampling points of a weak interference interval of a source cell to each sampling point cell, the number of sampling points of a critical interference interval of the source cell to each sampling point cell and the number of sampling points of a strong interference interval of the source cell to each sampling point cell are respectively subjected to mean value calculation on the number of the sampling points of three interference intervals of the source cell to each sampling point cell, so that the average number of the sampling points of the corresponding interference intervals is obtained, and the obtained average number of the sampling points of the three interference intervals of the source cell to each sampling point cell is sent to a sampling point cell classification module according to the number of the sampling points;
the sampling point cell classification module according to the number of sampling points is used for classifying each sampling point cell according to the size relation between the number of sampling points in three interference intervals of each sampling point cell by a source cell and the average number of sampling points of a corresponding interference interval sent by the sampling point number average value calculation module to obtain classification information of each sampling point cell, wherein the classification information of each sampling point cell is the sampling point number classification information of each sampling point cell, and the obtained sampling point number classification information of each sampling point cell is sent to the sampling point cell classification information processing unit.
And the sampling point cell classification information processing unit is a Geographic Information System (GIS) platform for displaying a cell distribution diagram.
According to the technical scheme, the method and the device can accurately determine the coverage range of the source cell in real time by utilizing the average downlink level of the source cell, the number of sampling points of the source cell in three interference intervals to the sampling point cell or the combination of the average downlink level of the source cell and the number of the sampling points, and can judge the coverage range deviation of the source cell by comparing a plurality of source cell coverage ranges obtained according to the original data collected and selected from the OMC system in different time periods, thereby being beneficial to an operator to timely and effectively find the coverage range error of the source cell, and better performing network maintenance and optimization work.
Drawings
Fig. 1 is a flow chart of a method for determining cell coverage in the present invention;
fig. 2 is a flowchart of classifying sample cells according to the average downlink level of a source cell in each sample cell in embodiment 1 of the method of the present invention;
FIG. 3 is a probability curve obtained by the moving average algorithm in embodiment 1 of the method of the present invention;
fig. 4 is a source cell coverage map obtained in embodiment 1 of the method of the present invention;
fig. 5 is a flowchart of a method for classifying sample cells according to the number of sample points in three interference intervals of a source cell to each sample cell in embodiment 2 of the method of the present invention;
fig. 6 is a source cell coverage map obtained in embodiment 2 of the method of the present invention;
fig. 7 is a flowchart of a method for classifying sample cells according to an average downlink level of a source cell and the number of sample points in three interference intervals of the source cell to each sample cell and obtaining a coverage area of the source cell in embodiment 3 of the method of the present invention;
fig. 8 is a coverage area map of a source cell obtained in embodiment 3 of the method of the present invention;
fig. 9 is a schematic structural diagram of the apparatus for determining a cell coverage area according to the present invention;
fig. 10 is a schematic structural diagram of an apparatus for determining a cell coverage area according to a first embodiment of the present invention;
fig. 11 is a schematic structural diagram of an apparatus for determining a cell coverage area according to a second embodiment of the present invention;
fig. 12 is a schematic structural diagram of an apparatus for determining a cell coverage area according to a third embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings and examples.
The main idea of the invention is as follows: the method comprises the steps of collecting and selecting original data required for determining the coverage area of a source cell from an Operation and Maintenance Center (OMC) system, classifying each sampling point cell according to the collected original data, processing classification information of each sampling point cell to obtain the coverage area of the source cell, and judging the coverage error of the source cell by comparing the coverage areas of the source cells obtained in different time periods.
Fig. 1 is a flowchart of a method for determining a cell coverage area according to the present invention. As shown in fig. 1, the method of the present invention mainly comprises the following steps:
step A, collecting and selecting original data required by determining the coverage area of a source cell from an OMC system.
In a mobile communication network, such as a Global System for mobile Communications (GSM) network, due to various mobile communication services or network side requirements (e.g., cell reselection), a mobile terminal (e.g., a mobile phone) in each cell uploads some measurement data (e.g., Serving cell ID, Serving cell downlink level, Interfering cell IDs (Interfering cell IDs), Interfering cell downlink levels, etc.) of its current location (i.e., a sampling point) to the network side of the mobile communication network at intervals (e.g., 580 milliseconds). The network side, for example, a Base Station Controller (BSC), can calculate the carrier-to-interference ratio between the serving cell and the multiple interfering cells of each sampling point according to the measurement data uploaded by each sampling point. Wherein, the carrier-to-interference ratio of the serving cell to the interfering cell is: the ratio of the downlink level of the serving cell where the sampling point is located to the downlink level of an interfering cell. An OMC system at a network side calculates a mean value of a plurality of downlink levels of an interference cell uploaded by a plurality of sampling points in the same service cell at intervals (such as 1 hour), so as to obtain an average downlink level of the interference cell relative to the service cell; for example, taking a serving cell a and an interfering cell B of the serving cell a as an example, if there are x sampling points in the serving cell a to upload the downlink levels of the interfering cell B in a certain time period, so as to obtain x downlink levels of the interfering cell B on the network side, the OMC system will average the x downlink levels, so as to obtain an average downlink level of the interfering cell B relative to the serving cell a.
In addition, the OMC system further processes the carrier-to-interference ratio between each service cell and the interference cell calculated according to the BSC. Still take the above-mentioned serving cell a and interfering cell B of the serving cell a as an example to explain the processing, because x sampling points in the serving cell a upload the downlink level of interfering cell B and also upload the downlink level of serving cell a at the same time, the carrier-to-interference ratio of x serving cells a and interfering cell B can be obtained by calculation of BSC; obtaining the reciprocal of the x carrier-to-interference ratios after taking the reciprocal of the x carrier-to-interference ratios; then dividing the x carrier-to-interference ratio reciprocals into three intervals of (-infinity, -12dB ], (-12dB, 0dB) and [0dB, ∞) according to the numerical value, and counting the number of the carrier-to-interference ratio reciprocals in each interval respectively, wherein each carrier-to-interference ratio reciprocal corresponds to one sampling point, so that the number of the carrier-to-interference ratio reciprocals in each interval is equivalent to the number of sampling points in each interval. In the OMC system, the three intervals are represented by Class1, Class2 and Class3, respectively.
In a mobile communication system (such as GSM), a co-channel interference protection ratio of a cell is 9dB, and in practical engineering, 3dB, that is, 12dB is generally added, that is, only when a carrier-to-interference ratio is greater than or equal to 12dB, a downlink level of an interfering cell does not cause co-channel interference in a serving cell, and the serving cell can perform normal mobile communication service. After the carrier-to-interference ratio is inverted, the co-channel interference is not caused when the reciprocal of the carrier-to-interference ratio is smaller than or equal to-12 dB, so that if a certain reciprocal of the carrier-to-interference ratio is divided into a segment Class1 (— infinity, -12 dB), the downlink level of an interference cell corresponding to the reciprocal of the carrier-to-interference ratio does not cause co-channel interference in a service cell corresponding to the reciprocal of the carrier-to-interference ratio, so that the segment Class1 can be called a weak interference segment of the interference cell to the service cell, and if the reciprocal of the carrier-to-interference ratio is larger than or equal to 0dB, that is, the reciprocal of the carrier-to-interference ratio is divided into a segment Class3 ([ 0dB, ∞), the downlink level of the interference cell is not lower than the downlink level of the service cell, so that the segment Class3 can be called a strong interference segment of the interference cell to the service cell; if the reciprocal carrier-to-interference ratio is between-12 dB and 0dB, that is, the reciprocal carrier-to-interference ratio is divided into the interval Class2 (-12dB, 0dB), it indicates that the downlink level of the interfering cell is lower than the downlink level of the serving cell, but the same frequency interference of the serving cell is caused, so the interval Class2 may be referred to as a critical interference interval of the interfering cell to the serving cell.
The above obtained average downlink level of the interfering cell and the number of sampling points in the three interference intervals are stored in the OMC system, for example, in the form of a record together with the corresponding serving cell identifier and interfering cell identifier, so that each record in the OMC includes: a certain serving cell identifier, an identifier of a certain interfering cell of the serving cell, an average downlink level of the interfering cell corresponding to the serving cell (referred to as the average downlink level of the interfering cell, the same below), and the number of sampling points in three interference intervals of the interfering cell to the serving cell.
Meanwhile, the OMC system also stores, for example, in a recorded form, configuration information of each cell in the area covered by the mobile communication system, such as each cell identifier, the longitude and latitude of each cell base station, the antenna azimuth angle, and the like.
In the embodiment of the present invention, for convenience of description, a cell in which a coverage needs to be determined may be referred to as a source cell, and a cell in which a sampling point other than the source cell is located may be referred to as a sampling point cell.
Therefore, in this step, all data of an area to be analyzed within a certain period of time (for example, during busy hours in a day) may be collected from the OMC system, and original data (referred to as original data, the same applies below) required to determine the coverage of the source cell may be selected from the data collected from the OMC system, that is, the average downlink level of the interfering cell (i.e., the source cell) in the multiple records where the interfering cell identifier is the source cell identifier and the number of sampling points of the interfering cell to the three interference intervals of the serving cell (i.e., the sampling point cell) may be selected from the data collected from the OMC system; if there are multiple records with the same serving cell identifier in the selected original data, multiple records with the same serving cell identifier need to be merged, that is, multiple average downlink levels of an interfering cell (i.e., a source cell) in the multiple records with the same serving cell identifier are averaged and the obtained average is used as the average downlink level of the interfering cell (i.e., the source cell), the number of sampling points of the interfering cell in the record with the same serving cell identifier to multiple weak interference intervals of the serving cell is added and the obtained sum is used as the number of sampling points of the interfering cell to the weak interference intervals of the serving cell, the number of sampling points of the interfering cell to the multiple critical interference intervals of the serving cell in the record with the same serving cell identifier is added and the obtained sum is used as the number of sampling points of the critical interference intervals of the interfering cell to the serving cell, adding the number of sampling points of a plurality of strong interference intervals of the interference cell to the service cell in the record with the same service cell identification, taking the obtained sum as the number of sampling points of the strong interference intervals of the interference cell to the service cell, and inquiring configuration information (such as the longitude and latitude and the azimuth of a source cell base station, the longitude and latitude and the azimuth of a plurality of sampling point base stations and the like) of the source cell and the plurality of sampling point cells from the OMC system according to the source cell identification and the plurality of sampling point cell identifications,
in an embodiment of the present invention, the raw data collected and selected from the OMC system and required to determine the coverage area of the source cell may include: the method comprises the following steps of identifying a source cell (for example, the name of the source cell), the average downlink level of the source cell, the longitude and latitude of a source cell base station, the antenna azimuth angle of the source cell base station, the cell identification of each sampling point (for example, the name of each sampling point cell), the longitude and latitude of each sampling point base station, the antenna azimuth angle of each sampling point base station, the number of sampling points of a weak interference interval of the source cell to each sampling point cell, the number of sampling points of a critical interference interval of the source cell to each sampling point cell and the number of sampling points of a strong interference interval of the source cell to each sampling point cell.
The total number of the sampling points in the area to be analyzed is generally large, and the distribution of the sampling points is also relatively in accordance with the actual application environment (for example, the number of the sampling points in the dense personnel area is large, the number of the sampling points in the sparse personnel area is small, and the like).
In order to eliminate decoding errors that may exist in the collected and selected raw data, the collected and selected raw data may be further preprocessed, where the preprocessing may be exception-removing preprocessing, for example, to remove null values or scrambled data in the collected and selected raw data.
And step B, classifying each sampling point cell according to the collected and selected original data required for determining the coverage area of the source cell to obtain the classification information of each sampling point cell, and obtaining the coverage area of the source cell according to the classification information of each sampling point cell.
In this step, the sampling point cells may be classified according to one or more of the collected and selected raw data required for determining the coverage of the source cell, and classification information of each sampling point cell may be obtained, and the coverage of the source cell may be obtained according to the classification information of each sampling point cell.
In the invention, a plurality of classification processing methods can be used for classifying the sampling point cells and obtaining the classification information of each sampling point cell. For example, the sampling point cells can be classified according to the average downlink level of the source cell to obtain classification information of each sampling point cell; or classifying the sampling point cells according to the number of the sampling points in the three interference intervals of the source cell to each sampling point cell to obtain the classification information of each sampling point cell. In order to better describe the technical solution of the present invention, the above various classification processing methods will be described below with reference to specific embodiments.
Example 1: classifying the sampling point cells according to the average downlink level of the source cell to obtain the classification information of each sampling point cell, and obtaining the coverage area of the source cell according to the classification information of each sampling point cell.
In this embodiment, the sampling point cells may be classified according to the acquired and selected average downlink level of the source cell, for example, the average downlink level value of the source cell is divided into several level intervals, and the level interval where each sampling point cell is located is determined according to the average downlink level of the source cell corresponding to each acquired sampling point cell, that is, each sampling point cell is divided into different types of level intervals, so as to obtain classification information of each sampling point cell (which may be referred to as "classification information of the average downlink level interval of the source cell"), and then the coverage area of the source cell may be obtained according to the classification information of the average downlink level interval of the source cell of each sampling point cell.
In a mobile communication system, for example, in a GSM network, the average downlink level value of an interfering cell (i.e., a source cell) generally ranges from-47 dBm to-110 dBm; in this embodiment, there may be a plurality of methods for classifying the average downlink level of the source cell in the collected and selected raw data, that is, dividing the level interval, and dividing the average downlink level value range of the source cell into a plurality of level intervals with equal length or different lengths as required. For the sake of simplicity, in the following embodiments, a specific method for dividing the source cell average downlink level interval is taken as an example, and the embodiments will be described in detail.
Referring to fig. 2, fig. 2 is a flowchart of a method for classifying sample cells according to an average downlink level of a source cell and obtaining a coverage area of the source cell in embodiment 1 of the method of the present invention, which mainly includes the following steps:
and step B1, counting the occurrence times of the average downlink level value of each source cell in the collected and selected original data required for determining the coverage area of the source cell, and calculating the occurrence probability of the average downlink level value of each source cell in the average level values of all the source cells.
The acquired and selected original data comprises a plurality of source cell average downlink level values, so that the frequency of occurrence of a certain source cell average downlink level value in the acquired original data is counted, namely the source cell average downlink level value corresponding to which sampling point cells are equal to the source cell average downlink level value is counted, and similarly, the probability of occurrence of the certain source cell average downlink level value in all the source cell average level values is calculated, namely the ratio of the number of the sampling point cells corresponding to the source cell average downlink level value to the number of all the sampling point cells is calculated.
According to the method, the occurrence frequency of the average downlink level value of each source cell is determined one by one, and the probability of the average downlink level value of each source cell appearing in the average level values of all source cells is calculated.
And step B2, taking the average downlink level value of the source cell as a horizontal axis and the probability as a vertical axis, smoothly connecting the probabilities of the average downlink level value of each source cell in the average level values of all the source cells by using a moving average algorithm to obtain a probability curve, and performing interval division on the average downlink level value of the source cell by using the trough of the probability curve as a segmentation point.
Fig. 3 is a probability curve obtained by the moving average algorithm in embodiment 1 of the method of the present invention, and as shown in fig. 3, the probability curve may be divided into a plurality of intervals by using the trough of the probability curve as a segmentation point. For example, the average downlink level interval (may be simply referred to as level interval) of 5 source cells such as A, B, C, D, E may be divided, where level interval a is [ -47dBm, -54dBm ], level interval B is [ -54dBm, -70dBm), level interval C is [ -70dBm, -82dBm ], level interval D is (-82dBm, -98dBm ], and level interval E is (-98dBm, -110 dBm.
The wave trough of the probability curve is taken as a segmentation point, so that the probability curve of each source cell average downlink level interval is approximately in normal distribution, namely in each source cell average downlink level interval, the probability of each source cell average downlink level value approximately obeys normal distribution, and the actual situation of obtaining the source cell average downlink level in each sampling point cell is also met.
The segment points of the level interval may also be selected from peaks or other values of the probability curve, or the number of segment points and partition intervals may be selected at will, which is not described herein again.
And step B3, dividing each sampling point cell into different source cell average downlink level intervals according to the source cell average downlink level corresponding to each sampling point cell collected and selected, thereby obtaining the source cell average downlink level interval classification information of each sampling point cell.
In this step, each sampling point cell may be divided into the corresponding source cell average downlink level interval determined in step B1 according to the source cell average downlink level corresponding to each sampling point cell collected and selected, so as to obtain the source cell average downlink level interval classification information of each sampling point cell, that is, the level interval where the source cell average downlink level corresponding to each sampling point cell is located. For example, if the value of the source cell average downlink level corresponding to a certain sampling point cell is-50 dBm, the source cell average downlink level is located in a level interval a, so that the classification information of the sampling point cell is a; if the value of the source cell average downlink level corresponding to a certain sampling point cell is-100 dBm, the source cell average downlink level is located in a level interval E, so that the classification information of the sampling point cell is E; and so on, the classification information of all sampling point cells can be obtained.
And step B4, obtaining the coverage area of the source cell according to the source cell average downlink level interval classification information of each sampling point cell.
An engineer may use various means to obtain the coverage area of the source cell according to the classification information of the average downlink level interval of the source cell of the sampling point cell obtained in step B3, for example, a specific computer program is used to process the classification information of the average downlink level interval of the source cell of each sampling point to obtain the coverage area of the source cell or a specific computer program is used to add the classification information of the average downlink level interval of the source cell of each sampling point cell to the cell layout to obtain the coverage area map of the source cell. The present embodiment will be described in detail below by taking an example in which classification information of the source cell average downlink level interval of each sampling point cell is added to a cell distribution map to obtain a coverage area map of the source cell.
In this embodiment, the cell distribution map may be displayed in a Geographic Information System (GIS) or other system capable of displaying cell distribution information, using configuration information of cells, such as the longitude and latitude of the source cell base station, the azimuth of the source cell base station antenna, the longitude and latitude of each sampling point base station, the azimuth of each sampling point base station antenna, and the like, collected from the OMC system, and how to display the cell distribution map on the system is the prior art and is not described herein again. Adding the classification information of the source cell average downlink level interval of each sampling point cell into the cell distribution diagram to obtain a source cell coverage area diagram,
referring to fig. 4, fig. 4 is a source cell coverage map obtained in embodiment 1 of the method of the present invention. Taking fig. 4 as an example, it can be known from the classification information of each sampling point cell that the other two sampling point cells sharing the base station 1 with the source cell are in the source cell average downlink level interval a; the only sampling point cell of the base station 2 is positioned in the average downlink level interval A of the source cell; one sampling point cell of the base station 3 is positioned in a source cell average downlink level interval B, and the other two sampling point cells are positioned in a source cell average downlink level interval C; one sampling point cell of the base station 4 is positioned in the source cell average downlink level interval D, and the other two sampling point cells are positioned in the source cell average downlink level interval E; one sampling point cell of the base station 5 is positioned in the source cell average downlink level interval D, and the other two sampling point cells are positioned in the source cell average downlink level interval E; one sampling point cell of the base station 6 is positioned in the source cell average downlink level interval D, and the other two sampling point cells are positioned in the source cell average downlink level interval E; the only sampling point cell of the base station 7 is positioned in the average downlink level interval C of the source cell; the only sampling point cell of the base station 8 is in the source cell average downlink level interval a.
As can be seen from fig. 4, the downlink levels of the source cell received by the only one sampling point cell of the base station 7 and the only one sampling point cell of the base station 8, which are far away from the base station 1 of the source cell, are abnormal, and the reason for the abnormality may be that configuration parameters of the relevant base station, such as an azimuth angle or longitude and latitude of an antenna, are deviated, or that an actual environmental factor such as weather, such as strong wind, causes a change in an antenna height, an azimuth angle or a pitch angle, and thus, an engineer may check settings of the relevant base station and the relevant cell according to the condition displayed in the coverage area diagram of the source cell.
In addition, the original data of different time periods can be collected and selected from the OMC system according to the method, the coverage areas of a plurality of source cells are obtained according to the original data, and the obtained coverage areas of the plurality of source cells are compared to judge the coverage error of the source cell. If the average downlink level interval of the source cell where a certain sampling point cell is located is found to be changed through comparison, engineering technicians can check the setting of the source cell or the changed sampling point cell, and operators can find out the coverage error of the source cell timely and effectively, so that network maintenance and optimization work can be better carried out.
Example 2: classifying the sampling point cells according to the number of the sampling points in three interference intervals of each sampling point cell by the source cell to obtain the classification information of each sampling point cell, and obtaining the coverage area of the source cell according to the classification information of each sampling point cell.
In this embodiment, the average value of the number of sampling points of the source cell in the collected and selected raw data to the three interference intervals of each sampling point cell may be calculated to obtain the average number of sampling points of the corresponding interference interval, and each sampling point cell is classified according to the size relationship between the number of sampling points of the source cell to the three interference intervals of each sampling point cell and the average number of sampling points of the corresponding interference interval to obtain the classification information (which may be referred to as sampling point number classification information) of each sampling point cell; and then classifying the information according to the number of the sampling points of each sampling point cell to obtain the coverage area of the source cell.
Referring to fig. 5, fig. 5 is a flowchart of a method for classifying sample point cells according to the number of sample points in three interference intervals of each sample point cell by a source cell and obtaining a coverage area of the source cell in embodiment 2 of the method of the present invention, where the method specifically includes the following steps:
and step B11, respectively carrying out average value calculation on the number of the sampling points of the collected and selected source cell to the three interference intervals of each sampling point cell to obtain the average number of the sampling points of the corresponding interference intervals.
In this step, the average value calculation may be performed by using a plurality of common average value calculation methods, for example, the number of all sampling points in an interference interval (for example, a weak interference interval) of all sampling point cells may be accumulated by the acquired source cell, and then divided by the number of the sampling point cells, so as to obtain the average number of the sampling points in the interference interval.
The average number of sampling points per interference interval may be determined one by one according to the method described above. The average number of sampling points in the Class1 interval (i.e., the weak interference interval) is represented by Avg1, the average number of sampling points in the Class2 interval (i.e., the critical interference interval) is represented by Avg2, and the average number of sampling points in the Class3 interval (i.e., the strong interference interval) is represented by Avg 3.
And step B12, classifying each sampling point cell according to the size relation between the number of the sampling points in the three interference intervals of each sampling point cell by the source cell and the average number of the sampling points in the corresponding interference intervals, and obtaining the number classification information of the sampling points of each sampling point cell.
In this step, the number of sampling points in three interference intervals (strong interference area, critical interference area, and weak interference area) of each sampling point cell from the collected source cell may be compared with the average number of sampling points in the corresponding interference interval, and according to the comparison result, the classification information of the number of sampling points in each sampling point cell is obtained. The situation that the number of sampling points in the interference interval of the sampling point cell is larger than or equal to the average number of the sampling points in the corresponding interference interval can be marked as large, and the situation that the number of the sampling points in the interference interval of the sampling point cell is smaller than the average number of the sampling points in the corresponding interference interval can be marked as small. The sampling point cells are divided into 8 classes according to the mark combination of the three interference intervals of the sampling point cells, as shown in table 1,
| classification information | Weak interference area | Critical interference region | Strong interference zone | Interference level |
| Class1 | Big (a) | Big (a) | Big (a) | High interference |
| Class2 | Big (a) | Big (a) | Small | Critical interference |
| Class3 | Big (a) | Small | Big (a) | |
| Class | ||||
| 4 | Big (a) | Small | Small | Weak interference |
| Class 5 | Small | Big (a) | Big (a) | |
| Class | ||||
| 6 | Small | Big (a) | Small | Critical interference |
| Class 7 | Small | Small | Big (a) | High interference |
| Class 8 | Small | Small | Small | Weak interference |
TABLE 1
As can be seen from table 1, if the number of sampling points in three interference intervals of a certain sampling point cell is greater than the average number of sampling points in the corresponding interference interval, the classification information of the sampling point cell is 1, that is, the sampling point cell belongs to the category 1 listed in table 1; if the number of sampling points in the weak interference area and the critical interference area of a certain sampling point cell is respectively greater than the average number of sampling points in the weak interference area and the critical interference area, but the number of sampling points in the strong interference area of the sampling point cell is less than the average number of sampling points in the strong interference area, the classification information of the sampling point cell is 2, namely the sampling point cell belongs to the 2 nd class condition listed in the table 1; and so on, the classification information of all sampling point cells can be obtained.
Wherein, the condition that the strong interference area mark in table 1 is large indicates that the number of sampling points of the strong interference area of the type of sampling point cell by the source cell is larger than the average number of sampling points of the strong interference area, that is, the source cell causes strong interference to the type of sampling point cell, that is, the type 1, 3, 5, and 7 sampling point cells; the condition that the mark of the critical interference zone is large indicates that the number of sampling points of the source cell to the critical interference zone of the type of sampling point cell is larger than the average number of the sampling points of the critical interference zone, namely the source cell causes critical interference to the type of sampling point cell, namely the type 2 and 6 sampling point cells; and the other classes represent that the source cell causes weak interference to the class of sampling point cells, and normal communication of the class of sampling point cells is not influenced, namely the class 4 and 8 sampling point cells.
And step B13, obtaining the coverage range of the source cell according to the sampling point number classification information of each sampling point cell.
The engineer may use various means to obtain the coverage of the source cell according to the classification information of the number of sampling points of each sampling point cell obtained in step B12, such as processing the classification information of the number of sampling points of each sampling point cell with a specific computer program to obtain the coverage of the source cell or adding the classification information of the number of sampling points of each sampling point cell to the cell layout to obtain the coverage map of the source cell. The present embodiment will be described in detail below by taking an example in which the coverage area map of the source cell is obtained by adding the classification information of the number of sampling points of each sampling point cell to the cell distribution map.
In this embodiment, the cell distribution map may be displayed in a Geographic Information System (GIS) or other system capable of displaying cell distribution information, using configuration information of cells, such as the longitude and latitude of the source cell base station, the azimuth of the source cell base station antenna, the longitude and latitude of each sampling point base station, the azimuth of each sampling point base station antenna, and the like, collected from the OMC system, and how to display the cell distribution map on the system is the prior art and is not described herein again. And adding the sampling point number classification information of each sampling point cell into the cell distribution diagram to obtain a source cell coverage area diagram.
Referring to fig. 6, fig. 6 is a source cell coverage map obtained in embodiment 2 of the method of the present invention. Taking fig. 6 as an example, in fig. 6, a type of sampling point cell in which the source cell causes strong interference to the type of sampling point cell is denoted by a double asterisk ". another type of sampling point cell in which the source cell causes critical interference to the type of sampling point cell is denoted by a single asterisk". the type of sampling point cell in which the source cell causes weak interference to the type of sampling point cell does not need to be particularly labeled. As shown in fig. 6, according to the classification information of each sampling point cell, it can be known that two other sampling point cells sharing the base station 1 with the source cell belong to the type 2 sampling point cell, and the source cell causes critical interference to the type 2 sampling point cell; the only sampling point cell of the base station 2 belongs to the type 1 sampling point cell, and a source cell causes strong interference to the type of sampling point cell; one sampling point cell of the base station 3 belongs to the type 3 sampling point cell, a source cell causes strong interference to the type of sampling point cell, the other sampling point cell belongs to the type 6 sampling point cell, the source cell causes critical interference to the type of sampling point cell, the third sampling point cell belongs to the type 4 sampling point cell, and the source cell causes weak interference to the type of sampling point cell; one sampling point cell of the base station 4 belongs to the type 3 sampling point cell, a source cell causes strong interference to the type of sampling point cell, the other two sampling point cells both belong to the type 4 sampling point cell, and the source cell causes weak interference to the type of sampling point cell; two sampling point cells of the base station 5 belong to a category 6 sampling point cell, a source cell causes critical interference to the category 6 sampling point cell, the other sampling point cell belongs to a category 4 sampling point cell, and the source cell causes weak interference to the category 4 sampling point cell; one sampling point cell of the base station 6 belongs to a type 3 sampling point cell, a source cell causes strong interference to the type of sampling point cell, the other sampling point cell belongs to a type 6 sampling point cell, the source cell causes critical interference to the type of sampling point cell, the third sampling point cell belongs to a type 4 sampling point cell, and the source cell causes weak interference to the type of sampling point cell; the only sampling point cell of the base station 7 belongs to the type 1 sampling point cell, and the source cell causes strong interference to the type 1 sampling point cell; the only sampling point cell of the base station 8 belongs to the type 2 sampling point cell, and the source cell causes critical interference to the type 2 sampling point cell.
As can be seen from fig. 6, the sampling point cells causing strong interference in the source cell are concentrated in the sampling point cells of the base stations 2, 3, 4, 6 and 7, wherein a unique sampling point cell of the base station 7, which is far away from the base station 1 of the source cell, belongs to the class1 sampling point cell, which indicates that the source cell causes strong interference to the class of sampling point cells, and needs to pay attention to the relevant point, see table 1, it can be found that the number of sampling points in three interference intervals of the source cell to the sampling point cell is greater than the average number of sampling points in the corresponding interference interval, which indicates that the configuration of the sampling point cell is abnormal, and the reason for the abnormality may be the configuration parameters of the relevant base station, such as deviation of the azimuth angle or longitude and latitude angle of the antenna, or the actual environmental factors such as weather, such as strong wind, and the change of the antenna height, azimuth angle or pitch angle, thus, an engineer can check the settings of the relevant base stations and cells based on the conditions displayed in the cell layout map.
In addition, the original data of different time periods can be collected and selected from the OMC system according to the method, the coverage areas of a plurality of source cells are obtained according to the original data, and the obtained coverage areas of the plurality of source cells are compared to judge the coverage error of the source cell. If the category of a certain sampling point cell is found to be changed through comparison, engineering technicians can check the setting of the source cell or the changed sampling point cell, and operators can find out the coverage error of the source cell timely and effectively, so that network maintenance and optimization work can be better carried out.
Example 3: classifying the sampling point cells according to the average downlink level of the source cell and the number of the sampling points in three interference intervals of the source cell to each sampling point cell to obtain the classification information of each sampling point cell, and obtaining the coverage area of the source cell according to the classification information of each sampling point cell.
In this embodiment, the sampling point cells may be classified according to the collected and selected average downlink level of the source cell, for example, the average downlink level value of the source cell is divided into several level intervals, and the level interval where each sampling point cell is located is determined according to the average downlink level of the source cell corresponding to each collected sampling point cell, that is, each sampling point cell is divided into different types of level intervals, so as to obtain classification information (which may be referred to as classification information of the average downlink level interval of the source cell) of each sampling point cell; moreover, the average value of the number of sampling points of the source cell in the collected and selected original data to the three interference intervals of each sampling point cell can be respectively calculated to obtain the average number of the sampling points of the corresponding interference intervals, and each sampling point cell is classified according to the size relationship between the number of the sampling points of the source cell to the three interference intervals of each sampling point cell and the average number of the sampling points of the corresponding interference intervals to obtain the classification information (which can be called as sampling point number classification information) of each sampling point cell; and then obtaining the coverage area of the source cell according to the source cell average downlink level interval classification information of each sampling point cell and the sampling point number classification information of each sampling point cell.
Referring to fig. 7, fig. 7 is a flowchart of a method for classifying sample point cells according to an average downlink level of a source cell and the number of sample points in three interference intervals of each sample point cell by the source cell and obtaining a coverage area of the source cell in embodiment 3 of the method of the present invention, where the method specifically includes the following steps:
in this embodiment, steps B111 to B113 are the same as steps B1 to B3 in embodiment 1, and steps B114 to B115 are the same as steps B11 to B12 in embodiment 2, and specific steps may refer to steps B1 to B3 in embodiment 1 and steps B11 to B12 in embodiment 2, which are not described herein again.
Because steps B111-B113 and steps B114-B115 process different data, the step B111-B113 may be used to obtain the source cell average downlink level interval classification information of each sampling point cell first, and then the step B114-B115 may be used to obtain the sampling point number classification information of each sampling point cell, or the step B114-B115 may be used to obtain the sampling point number classification information of each sampling point cell first, and then the step B111-B113 may be used to obtain the source cell average downlink level interval classification information of each sampling point cell, or the step B111-B113 and the step B114-B115 may be used to obtain the source cell average downlink level interval classification information of each sampling point cell and the sampling point number classification information of each sampling point cell simultaneously.
Step B116: and obtaining the coverage area of the source cell according to the source cell average downlink level interval classification information of each sampling point cell and the sampling point number classification information of each sampling point cell.
An engineer can obtain the coverage area of the source cell according to the source cell average downlink level interval classification information of each sampling point cell and the sampling point number classification information of each sampling point cell obtained in this embodiment by using various means, such as processing the source cell average downlink level interval classification information of each sampling point cell and the sampling point number classification information of each sampling point cell by using a specific computer program to obtain the coverage area of the source cell or adding the source cell average downlink level interval classification information of each sampling point cell and the sampling point number classification information of each sampling point cell to a cell layout to obtain a coverage area map of the source cell. The following describes the present embodiment in detail by taking an example in which the classification information of the average downlink level interval of the source cell of each sampling point cell and the classification information of the number of sampling points of each sampling point cell are added to the cell distribution map to obtain the coverage map of the source cell.
In this embodiment, the cell distribution map may be displayed in a Geographic Information System (GIS) or other system capable of displaying cell distribution information, using configuration information of cells, such as the longitude and latitude of the source cell base station, the azimuth of the source cell base station antenna, the longitude and latitude of each sampling point base station, the azimuth of each sampling point base station antenna, and the like, collected from the OMC system, and how to display the cell distribution map on the system is the prior art and is not described herein again. And adding the classification information of the average downlink level interval of the source cell of each sampling point cell and the classification information of the number of sampling points of each sampling point cell into the cell distribution diagram to obtain a coverage area diagram of the source cell.
Referring to fig. 8, fig. 8 is a coverage area map of a source cell obtained in embodiment 3 of the method of the present invention.
Taking fig. 8 as an example, according to the classification information of each sampling point cell, it can be known that two other sampling point cells sharing the base station 1 with the source cell are in the source cell average downlink level interval a and belong to the above-mentioned type 2 sampling point cell, and the source cell causes critical interference to the type of sampling point cell; the only sampling point cell of the base station 2 is positioned in the average downlink level interval A of the source cell and belongs to the type 1 sampling point cell, and the source cell causes strong interference to the type of sampling point cell; one sampling point cell of the base station 3 is positioned in a source cell average downlink level interval B and belongs to the type 3 sampling point cell, the source cell causes strong interference to the type sampling point cell, the other two sampling point cells are positioned in a source cell average downlink level interval C, one sampling point cell belongs to the type 6 sampling point cell, the source cell causes critical interference to the type sampling point cell, the other sampling point cell belongs to the type 4 sampling point cell, and the source cell causes weak interference to the type sampling point cell; one sampling point cell of the base station 4 is positioned in the source cell average downlink level interval D and belongs to the type 3 sampling point cell, the source cell causes strong interference to the type of sampling point cell, the other two sampling point cells are positioned in the source cell average downlink level interval E and both belong to the type 4 sampling point cell, and the source cell causes weak interference to the type of sampling point cell; one sampling point cell of the base station 5 is positioned in a source cell average downlink level interval D and belongs to a 6 th type sampling point cell, the source cell causes critical interference to the type of sampling point cell, the other two sampling point cells are positioned in a source cell average downlink level interval E, one sampling point cell belongs to the 6 th type sampling point cell, the source cell causes critical interference to the type of sampling point cell, the other sampling point cell belongs to the 4 th type sampling point cell, and the source cell causes weak interference to the type of sampling point cell; one sampling point cell of the base station 6 is positioned in a source cell average downlink level interval D and belongs to a 3 rd class sampling point cell, the source cell causes strong interference to the sampling point cell, the other two sampling point cells are positioned in a source cell average downlink level interval E, one sampling point cell belongs to the 6 th class sampling point cell, the source cell causes critical interference to the sampling point cell, the other sampling point cell belongs to the 4 th class sampling point cell, and the source cell causes weak interference to the sampling point cell; the only sampling point cell of the base station 7 is positioned in the average downlink level interval C of the source cell and belongs to the type 1 sampling point cell, and the source cell causes strong interference to the type of sampling point cell; the only sampling point cell of the base station 8 is located in the average downlink level interval a of the source cell and belongs to the type 2 sampling point cell, and the source cell causes critical interference to the type of sampling point cell.
As can be seen from fig. 8, both the unique sampling point cell of the base station 7 and the unique sampling point cell of the base station 8, which are far away from the base station 1 of the source cell, receive the higher average downlink level of the source cell and belong to the sampling point cells causing strong interference and critical interference, respectively, which needs to be paid attention by the terminal, which indicates that the configuration of the two sampling point cells is abnormal. The reason for the above abnormality may be that a configuration parameter of the relevant base station, for example, an azimuth angle or longitude and latitude of the antenna, is deviated, or an actual environmental factor such as weather, for example, strong wind, changes an antenna height, an azimuth angle or a pitch angle, and the like, so that an engineer can check settings of the relevant base station and the cell according to a condition displayed in the cell distribution diagram.
In addition, the original data of different time periods can be collected and selected from the OMC system according to the method, the coverage areas of a plurality of source cells are obtained according to the original data, and the obtained coverage areas of the plurality of source cells are compared to judge the coverage error of the source cell. If the average downlink level of the source cell where a certain sampling point cell is located or the category of the sampling point cell is found to be changed through comparison, engineering technicians can check the setting of the source cell or the changed sampling point cell, and operators can find out the coverage error of the source cell timely and effectively, so that network maintenance and optimization work can be better carried out.
The present invention further provides a device for determining a cell coverage, as shown in fig. 9, fig. 9 is a schematic structural diagram of the device for determining a cell coverage in the present invention. The device for determining the cell coverage area comprises the following steps: the device comprises a data acquisition unit, a sampling point cell classification unit and a sampling point cell classification information processing unit, wherein the data acquisition unit and the sampling point cell classification information processing unit are respectively connected to the sampling point cell classification unit.
The data acquisition unit is used for acquiring and selecting original data required by determining the coverage area of a source cell from an OMC system and sending the original data to the sampling point cell classification unit;
the sampling point cell classification unit is used for classifying each sampling point cell according to the original data sent by the data acquisition unit to obtain classification information of each sampling point cell and sending the obtained classification information of each sampling point cell to the sampling point cell classification information processing unit;
and the sampling point cell classification information processing unit is used for obtaining the coverage range of the source cell according to the classification information of each sampling point cell sent by the sampling point cell classification unit.
As shown in fig. 10, fig. 10 is a schematic structural diagram of a device for determining a cell coverage area according to a first embodiment of the present invention. In the first embodiment of the apparatus for determining a cell coverage area of the present invention, the sampling point cell classification unit includes a level occurrence probability calculation module, a source cell average downlink level interval division module, and a sampling point cell per level classification module, and the level occurrence probability calculation module and the sampling point cell per level classification module are respectively connected to the source cell average downlink level interval division module;
the level occurrence probability calculation module is configured to receive raw data sent by the data acquisition unit and required for determining a coverage area of a source cell, where the raw data required for determining the coverage area of the source cell includes: the source cell average downlink level is used for counting the occurrence frequency of each source cell average downlink level value in the original data, calculating the occurrence probability of each source cell average downlink level value in all source cell average level values, and sending the calculated occurrence probability of each source cell average downlink level value in all source cell average level values to a source cell average downlink level interval division module;
the source cell average downlink level interval dividing module is used for smoothly connecting the probability of each source cell average downlink level value in all source cell average level values sent by the level occurrence probability calculation module by using a moving average algorithm and taking the source cell average downlink level value as a horizontal axis and the probability as a vertical axis to obtain a probability curve, performing interval division on the source cell average downlink level values by using a trough of the probability curve as a segmentation point, and sending the source cell average downlink level interval dividing result to the sampling point cell classifying module according to the level;
the sampling point cell classification module is used for classifying each sampling point cell into different source cell average downlink level intervals according to the interval division result of the source cell sent by the source cell average downlink level interval division module and the source cell average downlink level corresponding to each sampling point cell which is collected and selected, so as to obtain classification information of each sampling point cell, wherein the classification information of each sampling point cell is the source cell average downlink level interval classification information of each sampling point cell, and the obtained source cell average downlink level interval classification information of each sampling point cell is sent to the sampling point cell classification information processing unit.
As shown in fig. 11, fig. 11 is a schematic structural diagram of an apparatus for determining a cell coverage area according to a second embodiment of the present invention. In a second embodiment of the apparatus for determining a cell coverage area of the present invention, the sampling point cell classifying unit includes a sampling point number average calculating module and a sampling point cell classifying module according to the number of sampling points, the sampling point number average calculating module is connected to the sampling point cell classifying module according to the number of sampling points;
the sampling point number average value calculating module is used for receiving original data sent by the data acquisition unit and required for determining the coverage area of the source cell, and the original data required for determining the coverage area of the source cell comprises: the method comprises the steps that the number of sampling points of a weak interference interval of a source cell to each sampling point cell, the number of sampling points of a critical interference interval of the source cell to each sampling point cell and the number of sampling points of a strong interference interval of the source cell to each sampling point cell are respectively subjected to mean value calculation on the number of the sampling points of three interference intervals of the source cell to each sampling point cell, so that the average number of the sampling points of the corresponding interference intervals is obtained, and the obtained average number of the sampling points of the three interference intervals of the source cell to each sampling point cell is sent to a sampling point cell classification module according to the number of the sampling points;
the sampling point cell classification module according to the number of sampling points is used for classifying each sampling point cell according to the size relation between the number of sampling points in three interference intervals of each sampling point cell by a source cell and the average number of sampling points of a corresponding interference interval sent by the sampling point number average value calculation module to obtain classification information of each sampling point cell, wherein the classification information of each sampling point cell is the sampling point number classification information of each sampling point cell, and the obtained sampling point number classification information of each sampling point cell is sent to the sampling point cell classification information processing unit.
As shown in fig. 12, fig. 12 is a schematic structural diagram of a third embodiment of the apparatus for determining a cell coverage area in the present invention. In a third embodiment of the apparatus for determining a cell coverage area of the present invention, the sampling point cell classifying unit includes a level occurrence probability calculating module, a source cell average downlink level interval dividing module, a sampling point cell level classifying module, a sampling point number average calculating module, and a sampling point cell sampling point number classifying module, wherein the level occurrence probability calculating module and the sampling point cell level classifying module are respectively connected to the source cell average downlink level interval dividing module, and the sampling point number average calculating module is connected to the sampling point cell sampling point number classifying module;
the level occurrence probability calculation module is configured to receive raw data sent by the data acquisition unit and required for determining a coverage area of a source cell, where the raw data required for determining the coverage area of the source cell includes: the source cell average downlink level is used for counting the occurrence frequency of each source cell average downlink level value in the original data, calculating the occurrence probability of each source cell average downlink level value in all source cell average level values, and sending the calculated occurrence probability of each source cell average downlink level value in all source cell average level values to a source cell average downlink level interval division module;
the source cell average downlink level interval dividing module is used for smoothly connecting the probability of each source cell average downlink level value in all source cell average level values sent by the level occurrence probability calculation module by using a moving average algorithm and taking the source cell average downlink level value as a horizontal axis and the probability as a vertical axis to obtain a probability curve, performing interval division on the source cell average downlink level values by using a trough of the probability curve as a segmentation point, and sending the source cell average downlink level interval dividing result to the sampling point cell classifying module according to the level;
the sampling point cell classification according to level module is used for classifying each sampling point cell into different source cell average downlink level intervals according to the source cell average downlink level interval classification result sent by the source cell average downlink level interval classification module and the source cell average downlink level corresponding to each sampling point cell collected and selected, so as to obtain the classification information of each sampling point cell, wherein the classification information of each sampling point cell is the source cell average downlink level interval classification information of each sampling point cell, and the obtained source cell average downlink level interval classification information of the sampling point cell is sent to the sampling point cell classification information processing unit;
the sampling point number average calculation module is used for receiving original data sent by a data acquisition unit and required for determining the coverage area of a source cell, and the original data required for determining the coverage area of the source cell comprises: the method comprises the steps that the number of sampling points of a weak interference interval of a source cell to each sampling point cell, the number of sampling points of a critical interference interval of the source cell to each sampling point cell and the number of sampling points of a strong interference interval of the source cell to each sampling point cell are respectively subjected to mean value calculation on the number of the sampling points of three interference intervals of the source cell to each sampling point cell, so that the average number of the sampling points of the corresponding interference intervals is obtained, and the obtained average number of the sampling points of the three interference intervals of the source cell to each sampling point cell is sent to a sampling point cell classification module according to the number of the sampling points;
the sampling point cell classification module according to the number of sampling points is used for classifying each sampling point cell according to the size relation between the number of sampling points in three interference intervals of each sampling point cell by a source cell and the average number of sampling points of a corresponding interference interval sent by the sampling point number average value calculation module to obtain classification information of each sampling point cell, wherein the classification information of each sampling point cell is the sampling point number classification information of each sampling point cell, and the obtained sampling point number classification information of each sampling point cell is sent to the sampling point cell classification information processing unit.
In addition, because the level occurrence probability calculation module, the source cell average downlink level interval division module, the sampling point cell classification according to level module, the sampling point number average calculation module and the sampling point cell classification according to sampling point number module respectively process different data, the execution sequence of the two modules can be set arbitrarily, can be executed simultaneously or can be executed successively.
The method determines the coverage area of the source cell based on the measured data of the mobile terminal, does not need special tools to carry out special measurement, comprehensively considers various factors which possibly influence the coverage area of the determined source cell, such as the number of sampling points, the average downlink level of the source cell, the distance between the source cell and the sampling point cell and the like, ensures that the obtained coverage area of the source cell is more consistent with the practical application environment, can judge the coverage area deviation of the source cell by comparing a plurality of source cell coverage areas obtained according to the original data collected and selected from an OMC system in different time periods, is beneficial to an operator to timely and effectively discover the coverage area error of the source cell, and further better carries out network maintenance and optimization work.
The above description is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention.
Claims (14)
1. A method for determining cell coverage, the method comprising:
step A, collecting and selecting original data required by determining a source cell coverage area from an operation and maintenance center OMC system; the source cell is a cell needing to determine a coverage area;
b, classifying each sampling point cell according to the collected and selected original data required for determining the coverage area of the source cell to obtain classification information of each sampling point cell; obtaining the coverage area of the source cell according to the classification information of each sampling point cell; and the sampling point cell is a cell where sampling points except the source cell are located.
2. The method of claim 1, wherein the raw data required for determining the source cell coverage comprises: the average downlink level of the source cell; the classification information of each sampling point cell is the classification information of the source cell average downlink level interval of each sampling point cell; the step B comprises the following steps:
step B1, counting the occurrence frequency of each source cell average downlink level value in the collected and selected original data required for determining the source cell coverage area, and calculating the occurrence probability of each source cell average downlink level value in all source cell average level values;
step B2, taking the average downlink level value of the source cell as a horizontal axis and the probability as a vertical axis, smoothly connecting the probability of the average downlink level value of each source cell in the average level values of all the source cells by using a moving average algorithm to obtain a probability curve, and performing interval division on the average downlink level value of the source cells by using the trough of the probability curve as a segmentation point;
step B3, dividing each sampling point cell into different source cell average downlink level intervals according to the source cell average downlink level corresponding to each sampling point cell collected and selected, thereby obtaining source cell average downlink level interval classification information of each sampling point cell;
and step B4, obtaining the coverage area of the source cell according to the source cell average downlink level interval classification information of each sampling point cell.
3. The method of claim 1, wherein the raw data required for determining the source cell coverage comprises: the number of sampling points of a weak interference interval of each sampling point cell by a source cell, the number of sampling points of a critical interference interval of each sampling point cell by the source cell and the number of sampling points of a strong interference interval of each sampling point cell by the source cell; the classification information of each sampling point cell is the classification information of the number of sampling points of each sampling point cell;
the step B comprises the following steps:
step B11, respectively carrying out mean value calculation on the number of sampling points of the collected and selected source cell to three interference intervals of each sampling point cell to obtain the average number of the sampling points of the corresponding interference intervals;
step B12, classifying each sampling point cell according to the magnitude relation between the number of sampling points in three interference intervals of each sampling point cell by the source cell and the average number of sampling points in the corresponding interference interval, and obtaining the number classification information of the sampling points of each sampling point cell;
and step B13, obtaining the coverage area of the source cell according to the sampling point number classification information of each sampling point cell.
4. The method according to claim 3, wherein the classifying the sample cells in step B12 to obtain the sample number classification information of each sample cell comprises:
comparing the number of the sampling points in the three interference intervals of the source cell to each sampling point cell with the average number of the sampling points in the corresponding interference interval obtained in the step B11, and obtaining the classification information of the number of the sampling points of each sampling point cell according to the comparison condition;
the condition that the number of sampling points in the interference interval of the sampling point cell is larger than or equal to the average number of the sampling points in the corresponding interference interval is marked as large, the condition that the number of the sampling points in the interference interval of the sampling point cell is smaller than the average number of the sampling points in the corresponding interference interval is marked as small, and each sampling point cell is divided into 8 types according to the mark combination of three interference intervals of each sampling point cell.
5. The method of claim 4, wherein the class 8 sample point cells comprise:
class 1: the weak interference area is marked as large, the critical interference area is marked as large, and the strong interference area is marked as large;
class 2: the weak interference area is marked as large, the critical interference area is marked as large, and the strong interference area is marked as small;
class 3: the weak interference area is marked as large, the critical interference area is marked as small, and the strong interference area is marked as large;
class 4: the weak interference area is marked as large, the critical interference area is marked as small, and the strong interference area is marked as small;
class 5: the weak interference area is marked as small, the critical interference area is marked as large, and the strong interference area is marked as large;
class 6: the weak interference area is marked as small, the critical interference area is marked as large, and the strong interference area is marked as small;
class 7: the weak interference area is marked as small, the critical interference area is marked as small, and the strong interference area is marked as large;
class 8: the weak interference zone is marked as small, the critical interference zone is marked as small, and the strong interference zone is marked as small.
6. The method of claim 1, wherein the raw data required for determining the source cell coverage comprises: the method comprises the following steps that the average downlink level of a source cell, the number of sampling points of a weak interference interval of the source cell to each sampling point cell, the number of sampling points of a critical interference interval of the source cell to each sampling point cell and the number of sampling points of a strong interference interval of the source cell to each sampling point cell are determined; the classification information of each sampling point cell comprises the source cell average downlink level interval classification information of each sampling point cell and the sampling point number classification information of each sampling point cell;
the step B comprises the following steps:
step B111, counting the occurrence frequency of the average downlink level value of each source cell in the collected and selected original data required for determining the coverage area of the source cell, and calculating the occurrence probability of the average downlink level value of each source cell in the average level values of all the source cells;
step B112, taking the average downlink level value of the source cell as a horizontal axis, taking the probability as a vertical axis, smoothly connecting the probabilities of the average downlink level value of each source cell in the average level values of all the source cells by using a moving average algorithm to obtain a probability curve, and performing interval division on the average downlink level value of the source cell by using a trough of the probability curve as a segmentation point;
step B113, dividing each sampling point cell into different source cell average downlink level intervals according to the source cell average downlink level corresponding to each sampling point cell which is collected and selected, thereby obtaining source cell average downlink level interval classification information of each sampling point cell;
step B114, respectively carrying out average value calculation on the number of sampling points of the collected and selected source cell in three interference intervals of each sampling point cell to obtain the average number of the sampling points in the corresponding interference intervals;
step B115, classifying each sampling point cell according to the magnitude relation between the number of sampling points in three interference intervals of each sampling point cell and the average number of sampling points in the corresponding interference interval by the source cell to obtain the number classification information of the sampling points of each sampling point cell;
step B116: and obtaining the coverage area of the source cell according to the source cell average downlink level interval classification information of each sampling point cell and the sampling point number classification information of each sampling point cell.
7. The method according to any one of claims 1 to 6, wherein the step B of obtaining the coverage of the source cell according to the classification information of the cells of the respective sampling points comprises:
and adding the classification information of each sampling point cell into a system for displaying a cell distribution diagram to obtain a coverage area diagram of the source cell.
8. The method of claim 7, wherein the system for displaying a cell layout is a Geographic Information System (GIS).
9. The method of claim 1, further comprising:
and B, acquiring and selecting original data of different time periods from the OMC system according to the method in the step A and the step B, obtaining the coverage areas of a plurality of source cells according to the original data, and comparing the obtained coverage areas of the plurality of source cells to judge the coverage error of the source cell.
10. An apparatus for determining cell coverage, the apparatus comprising: the system comprises a data acquisition unit, a sampling point cell classification unit and a sampling point cell classification information processing unit, wherein the data acquisition unit and the sampling point cell classification information processing unit are respectively connected to the sampling point cell classification unit; wherein,
the data acquisition unit is used for acquiring and selecting original data required by determining the coverage area of a source cell from an operation and maintenance center OMC system and sending the original data to the sampling point cell classification unit; the source cell is a cell needing to determine a coverage area;
the sampling point cell classification unit is used for classifying each sampling point cell according to the original data sent by the data acquisition unit to obtain the classification information of each sampling point cell and sending the obtained classification information of each sampling point cell to the sampling point cell classification information processing unit; the sampling point cell is a cell where sampling points other than the source cell are located;
and the sampling point cell classification information processing unit is used for obtaining the coverage range of the source cell according to the classification information of each sampling point cell sent by the sampling point cell classification unit.
11. The apparatus of claim 10, wherein the sampling point cell classifying unit comprises a level occurrence probability calculating module, a source cell average downlink level interval dividing module and a sampling point cell level classifying module, and the level occurrence probability calculating module and the sampling point cell level classifying module are respectively connected to the source cell average downlink level interval dividing module; wherein,
the level occurrence probability calculation module is used for receiving original data which are sent by the data acquisition unit and are required for determining the coverage area of the source cell, and the original data which are required for determining the coverage area of the source cell comprise: the source cell average downlink level is used for counting the occurrence frequency of each source cell average downlink level value in the original data, calculating the occurrence probability of each source cell average downlink level value in all source cell average level values, and sending the calculated occurrence probability of each source cell average downlink level value in all source cell average level values to a source cell average downlink level interval division module;
the source cell average downlink level interval dividing module is used for smoothly connecting the probability of each source cell average downlink level value in all source cell average level values sent by the level occurrence probability calculation module by using a moving average algorithm and taking the source cell average downlink level value as a horizontal axis and the probability as a vertical axis to obtain a probability curve, performing interval division on the source cell average downlink level values by using a trough of the probability curve as a segmentation point, and sending the source cell average downlink level interval dividing result to the sampling point cell classifying module according to the level;
the sampling point cell classification module is used for classifying each sampling point cell into different source cell average downlink level intervals according to the interval division result of the source cell sent by the source cell average downlink level interval division module and the source cell average downlink level corresponding to each sampling point cell which is collected and selected, so as to obtain classification information of each sampling point cell, wherein the classification information of each sampling point cell is the source cell average downlink level interval classification information of each sampling point cell, and the obtained source cell average downlink level interval classification information of each sampling point cell is sent to the sampling point cell classification information processing unit.
12. The device according to claim 10, wherein the sampling point cell classifying unit comprises a sampling point number average calculating module and a sampling point cell classifying module according to the number of sampling points, and the sampling point number average calculating module is connected with the sampling point cell classifying module according to the number of sampling points; wherein,
the sampling point number average calculation module is used for receiving original data sent by a data acquisition unit and required for determining the coverage area of a source cell, and the original data required for determining the coverage area of the source cell comprises: the method comprises the steps that the number of sampling points of a weak interference interval of a source cell to each sampling point cell, the number of sampling points of a critical interference interval of the source cell to each sampling point cell and the number of sampling points of a strong interference interval of the source cell to each sampling point cell are respectively subjected to mean value calculation on the number of the sampling points of three interference intervals of the source cell to each sampling point cell, so that the average number of the sampling points of the corresponding interference intervals is obtained, and the obtained average number of the sampling points of the three interference intervals of the source cell to each sampling point cell is sent to a sampling point cell classification module according to the number of the sampling points;
the sampling point cell classification module according to the number of sampling points is used for classifying each sampling point cell according to the size relation between the number of sampling points in three interference intervals of each sampling point cell by a source cell and the average number of sampling points of a corresponding interference interval sent by the sampling point number average value calculation module to obtain classification information of each sampling point cell, wherein the classification information of each sampling point cell is the classification information of the number of sampling points of each sampling point cell, and the obtained classification information of the number of sampling points of each sampling point cell is sent to the sampling point cell classification information processing unit.
13. The apparatus of claim 10, wherein the sampling point cell classifying unit comprises a level occurrence probability calculating module, a source cell average downlink level interval dividing module, a sampling point cell level classifying module, a sampling point number average calculating module and a sampling point cell sampling point number classifying module, wherein the level occurrence probability calculating module and the sampling point cell level classifying module are respectively connected with the source cell average downlink level interval dividing module, and the sampling point number average calculating module is connected with the sampling point cell sampling point number classifying module; wherein,
the level occurrence probability calculation module is used for receiving original data which are sent by the data acquisition unit and are required for determining the coverage area of the source cell, and the original data which are required for determining the coverage area of the source cell comprise: the source cell average downlink level is used for counting the occurrence frequency of each source cell average downlink level value in the original data, calculating the occurrence probability of each source cell average downlink level value in all source cell average level values, and sending the calculated occurrence probability of each source cell average downlink level value in all source cell average level values to a source cell average downlink level interval division module;
the source cell average downlink level interval dividing module is used for smoothly connecting the probability of each source cell average downlink level value in all source cell average level values sent by the level occurrence probability calculation module by using a moving average algorithm and taking the source cell average downlink level value as a horizontal axis and the probability as a vertical axis to obtain a probability curve, performing interval division on the source cell average downlink level values by using a trough of the probability curve as a segmentation point, and sending the source cell average downlink level interval dividing result to the sampling point cell classifying module according to the level;
the sampling point cell classification according to level module is used for classifying each sampling point cell into different source cell average downlink level intervals according to the source cell average downlink level interval classification result sent by the source cell average downlink level interval classification module and the source cell average downlink level corresponding to each sampling point cell collected and selected, so as to obtain classification information of each sampling point cell, wherein the classification information of each sampling point cell is the source cell average downlink level interval classification information of each sampling point cell, and the obtained source cell average downlink level interval classification information of the sampling point cell is sent to the sampling point cell classification information processing unit;
the sampling point number average calculation module is used for receiving original data sent by a data acquisition unit and required for determining the coverage area of a source cell, and the original data required for determining the coverage area of the source cell comprises: the method comprises the steps that the number of sampling points of a weak interference interval of a source cell to each sampling point cell, the number of sampling points of a critical interference interval of the source cell to each sampling point cell and the number of sampling points of a strong interference interval of the source cell to each sampling point cell are respectively subjected to mean value calculation on the number of the sampling points of three interference intervals of the source cell to each sampling point cell, so that the average number of the sampling points of the corresponding interference intervals is obtained, and the obtained average number of the sampling points of the three interference intervals of the source cell to each sampling point cell is sent to a sampling point cell classification module according to the number of the sampling points;
the sampling point cell classification module according to the number of sampling points is used for classifying each sampling point cell according to the size relation between the number of sampling points in three interference intervals of each sampling point cell by a source cell and the average number of sampling points of a corresponding interference interval sent by the sampling point number average value calculation module to obtain classification information of each sampling point cell, wherein the classification information of each sampling point cell is the sampling point number classification information of each sampling point cell, and the obtained sampling point number classification information of each sampling point cell is sent to the sampling point cell classification information processing unit.
14. The apparatus according to any one of claims 10-13, wherein the sample point cell classification information processing unit is a Geographic Information System (GIS) platform displaying a cell distribution map.
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| CN102065443B (en) * | 2010-11-29 | 2013-02-06 | 广州杰赛科技股份有限公司 | Method and device for dividing channel region |
| CN102572855A (en) * | 2010-12-15 | 2012-07-11 | 中国移动通信集团设计院有限公司 | Cell coverage simulative dividing method and device |
| CN103096339A (en) * | 2012-11-07 | 2013-05-08 | 无锡成电科大科技发展有限公司 | Method based on mobile phone measured data to confirm cell coverage area |
| CN103595589B (en) * | 2013-11-26 | 2017-04-05 | 中国联合网络通信集团有限公司 | A kind of signal quality measured method and device |
| CN103929775B (en) * | 2014-04-25 | 2017-07-28 | 中国联合网络通信集团有限公司 | A kind of method and apparatus of serving cell coverage direction reasonableness check |
| CN104363614B (en) * | 2014-11-19 | 2017-10-27 | 中国联合网络通信集团有限公司 | A kind of abnormal detection method and device of the coverage direction of cell |
| CN107371170B (en) * | 2016-05-11 | 2019-11-19 | 中国移动通信集团黑龙江有限公司 | A kind of network coverage cavity lookup method and device |
| CN109041079A (en) * | 2017-06-12 | 2018-12-18 | 中国移动通信集团广东有限公司 | A kind of method and device of subzone network inspection |
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| CN101621808A (en) | 2010-01-06 |
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