CN106376007B  Method and system for positioning coverage performance of base station  Google Patents
Method and system for positioning coverage performance of base station Download PDFInfo
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 CN106376007B CN106376007B CN201510428969.3A CN201510428969A CN106376007B CN 106376007 B CN106376007 B CN 106376007B CN 201510428969 A CN201510428969 A CN 201510428969A CN 106376007 B CN106376007 B CN 106376007B
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 H—ELECTRICITY
 H04—ELECTRIC COMMUNICATION TECHNIQUE
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 H04W16/18—Network planning tools

 H—ELECTRICITY
 H04—ELECTRIC COMMUNICATION TECHNIQUE
 H04W—WIRELESS COMMUNICATION NETWORKS
 H04W24/00—Supervisory, monitoring or testing arrangements
 H04W24/06—Testing, supervising or monitoring using simulated traffic
Abstract
The invention discloses a method for positioning coverage performance of a base station, which comprises the following steps: establishing a cell simulation environment according to the basic data, the threedimensional map and the ray tracking model; correcting the ray tracking model, obtaining a cell simulation environment corresponding to the corrected ray tracking model, and checking the height of a cell antenna according to the threedimensional map; using the cell antenna measured Reference Signal Received Power (RSRP) frequency sweep data after the cell antenna height is checked, rasterizing and calculating cell simulation RSRP data according to the cell simulation environment, and checking the cell simulation RSRP data and the RSRP frequency sweep data; and judging whether the cell is a suspected problem cell or not according to the check result of the simulated RSRP data and the RSRP frequency sweep data of the cell. The invention also discloses a system for positioning the coverage performance of the base station.
Description
Technical Field
The invention relates to a base station construction technology in the field of mobile communication, in particular to a method and a system for positioning coverage performance of a base station.
Background
Due to the complexity of the wireless network environment, great difficulty is brought to the quality control work of the coverage performance of the base station in the Long Term Evolution (LTE) technology. Therefore, how to quickly and effectively collect wireless network quality indexes, find problems existing in the construction of the LTE network and solve the problems is a key point and a difficult point of quality control work in the construction process of the LTE network.
In the LTE network construction process, whether the acceptance link can be opened or operated is determined by the construction quality of the network. At present, the method for controlling the construction quality of the network is as follows: a single station verification report. The singlestation verification comprises four parts of preparation before testing, verification testing, problem analysis processing and singlestation verification report output. If the test procedure or result shows significant problems, then the problems need to be recorded in a single station verification problem record sheet and problem analysis is given. Specifically, the hardware installation problem is solved by an engineering installation team, and the functional problem is solved by an Evolved node b (eNodeB) engineer. After the problem is solved, carrying out verification test again until no obvious problem is found in the test process and result analysis; and then, outputting a single station verification report according to the test result.
However, the single station authentication described in the prior art has the following technical problems:
1. the provincial company of the communication operator cannot check the filling accuracy of the measured data.
Since the singlestation authentication report is provided and filled out by the carrier division, the accuracy and authenticity of the provided data cannot be checked by the provincial company. Provincial companies can not verify the site, and can only verify the difference between the planning data and the provided measured data, and the coverage effect of the test is judged whether to be reasonable or not by people, and is not really compared with the planning effect. Therefore, the provincial company cannot verify the accuracy of the basic data. Therefore, the command control of the provincial company cannot really achieve 'beginning at end', technically cannot directly plan, cannot verify the benchmarking of the measured data, and cannot really verify and determine the difference between the measured data and the planned data.
2. The spot check mode of provincial companies of communication operators has defects.
The percentage of the spot check of the provincial company of the communication operator on the single station verification report is only 10%, although the provincial company of the communication operator can check the quality of the network construction to be controlled by checking a certain percentage of the single station verification reports. However, in view of workload, provincial companies can only perform spot checks, and thus cannot control the whole world to some extent. Therefore, the problem of local control is that the randomness is too high.
3. At present, communication operators and provinces generally adopt a manual mode to check and accept and audit and analyze each base station, the audit efficiency is low, and the audit coverage is small.
In summary, the conventional quality control generally refers to controlling the construction quality of the LTE network by means of singlestation verification performed by the branch companies of the communication operators and companysaving spot inspection performed by the communication operators, so that the difference between planning and actual effects cannot be accurately compared, and the workload is large. Therefore, the singlestation verification period of the base station is long, the efficiency is low, and the coverage performance of the base station cannot be quickly and efficiently positioned.
Disclosure of Invention
In view of this, embodiments of the present invention are expected to provide a method and a system for positioning coverage performance of a base station, which can not only improve the working efficiency of the LTE network construction quality, but also make the network coverage more comprehensive; the construction quality of the LTE network can be effectively controlled, and the coverage performance problem can be remotely and intensively discovered.
In order to achieve the above purpose, the technical solution of the embodiment of the present invention is realized as follows:
the embodiment of the invention provides a method for positioning the coverage performance of a base station, which comprises the following steps:
establishing a cell simulation environment according to the basic data, the threedimensional map and the ray tracking model;
correcting the ray tracking model, obtaining a cell simulation environment corresponding to the corrected ray tracking model, and checking the height of a cell antenna according to the threedimensional map; using the RSRP frequency sweep data of the actually measured reference signal receiving power of the cell antenna after the height of the cell antenna is checked, rasterizing and calculating cell simulation RSRP data according to the cell simulation environment, and checking the cell simulation RSRP data and the RSRP frequency sweep data;
and judging whether the cell is a suspected problem cell or not according to the check result of the cell simulation RSRP data and the RSRP frequency sweeping data.
In the foregoing solution, the correcting the ray tracing model includes:
selecting a sceneoriented scene corresponding to the cell in the current network environment, and correcting a direct incidence coefficient, a reflection coefficient and a diffraction coefficient in an RSRP formula according to the measured sceneoriented data;
the direct incidence coefficient is obtained by summing the absolute value of the difference between the RSRP measured value of each road measuring point and the RSRP direct incidence predicted value of each road measuring point, dividing the sum by 10, and multiplying the sum by the reciprocal of the common logarithm summation of the ray propagation distance of each road measuring point;
calculating the reflection coefficient according to the first model prediction error sum of the scene, wherein the first model prediction error sum is the sum of the squares of the difference between the RSRP measured value of each road measuring point and the RSRP direct and reflection predicted values of each road measuring point;
and calculating the diffraction coefficient according to the second model prediction error sum facing the scene, wherein the second model prediction error sum is the sum of the RSRP measured value of each road measuring point and the square of the difference between the RSRP direct incidence and the diffraction predicted value of each road measuring point.
In the above scheme, the rasterizing the cell simulation RSRP data according to the cell simulation environment, and checking the cell simulation RSRP data and RSRP sweep data includes:
rasterizing the cell simulation environment according to a preset precision, and calculating the cell simulation RSRP data of each grid by using the RSRP formula;
performing field test on each grid of the cell to obtain a group of RSRP frequency sweep data of each grid;
calculating an average error of simulated RSRP data for each grid of said cell and an average of said set of RSRP sweep data for said each grid;
calculating a standard deviation of said each set of grid RSRP sweep data for said cell.
In the foregoing solution, the determining, according to a result of checking the simulated RSRP data and the RSRP swept frequency data of the cell, whether the cell is a suspected problem cell includes:
and when the average value of the average errors between the cell simulation RSRP data and the RSRP frequency sweep data of all grids in the cell simulation environment and the average value of the standard variances of the RSRP frequency sweep data of all grids in the cell simulation environment respectively reach a first judgment threshold value and a second judgment threshold value, determining that the cell is the suspected problem cell.
In the above scheme, the method further comprises:
and checking the suspected problem cell.
The embodiment of the invention also provides a base station coverage performance positioning system, which comprises:
the simulation environment establishing module is used for establishing a cell simulation environment according to the basic data, the threedimensional map and the ray tracking model;
the ray model correction module is used for correcting the ray tracking model and obtaining a cell simulation environment corresponding to the corrected ray tracking model;
the antenna height checking module is used for checking the height of the cell antenna according to the threedimensional map;
the verification data module is used for using the actually measured RSRP frequency sweep data of the cell antenna after the height verification of the cell antenna, calculating cell simulation RSRP data according to the rasterization of the cell simulation environment, and verifying the cell simulation RSRP data and the RSRP frequency sweep data;
and the problem cell output module is used for judging whether the cell is a suspected problem cell according to the check result of the simulated RSRP data and the RSRP frequency sweep data of the cell.
In the foregoing solution, the ray model correction module includes:
a sceneoriented selecting unit, configured to select a scene oriented corresponding to the cell in a current network environment;
the direct incidence coefficient correction unit is used for correcting a direct incidence coefficient in an RSRP formula according to the sceneoriented measured data;
a reflection coefficient correction unit, configured to correct a reflection coefficient in the RSRP formula according to the actually measured data oriented to the scene;
and the diffraction coefficient correction unit is used for correcting the diffraction coefficient in the RSRP formula according to the actually measured data facing the scene.
In the above solution, the data checking module includes:
a simulation RSRP data unit, configured to rasterize the cell simulation environment according to a predetermined accuracy, and calculate the cell simulation RSRP data of each grid using the RSRP formula;
an RSRP sweep data unit, configured to perform a field test on each grid of the cell to obtain a set of RSRP sweep data of each grid;
an average error unit for calculating an average error of the cell simulation RSRP data of each grid and an average of the set of RSRP sweep data of each grid;
a standard deviation unit to calculate a standard deviation of the set of RSRP frequency sweep data for each grid.
In the above scheme, the determining, by the problem cell output module, whether the cell is a suspected problem cell according to a check result of the simulated RSRP data and the simulated RSRP swept frequency data of the cell includes:
and when the average value of the average errors between the cell simulation RSRP data and the RSRP frequency sweep data of all grids in the cell simulation environment and the average value of the standard variances of the RSRP frequency sweep data of all grids in the cell simulation environment respectively reach a first judgment threshold value and a second judgment threshold value, determining that the cell is the suspected problem cell.
According to the method and the system for positioning the coverage performance of the base station, provided by the embodiment of the invention, a cell simulation environment is established by the positioning system for the coverage performance of the base station according to basic data, a threedimensional map and a ray tracking model; correcting the ray tracking model, obtaining a cell simulation environment corresponding to the corrected ray tracking model, and checking the height of a cell antenna according to the threedimensional map; using the Reference Signal Received Power (RSRP) sweep data actually measured by the cell antenna after the height check of the cell antenna, rasterizing and calculating cell simulation RSRP data according to the cell simulation environment, checking the cell simulation RSRP data and the RSRP sweep data, and judging whether the cell is a suspected problem cell according to the check result of the cell simulation RSRP data and the RSRP sweep data. Therefore, the LTE planning stage and the construction stage are effectively linked, so that the working efficiency of controlling the LTE construction quality is improved, and the network coverage is more comprehensive; moreover, the problem of network coverage performance can be remotely and intensively discovered, and the requirement of 'beginning and end' of LTE network construction is ensured; meanwhile, the accuracy of basic data is solved, and a good foundation is laid for higherlevel optimization.
In addition, the method and the system for positioning the coverage performance of the base station provided by the embodiment of the invention have low investment cost and effectively avoid user loss; moreover, the working process is simple and efficient, basic data and frequency sweep data can be analyzed, managed and controlled in a centralized mode, and utilized in a centralized mode, and the fact that the LTE network is really 'opened, namely operated' is achieved.
Drawings
Fig. 1 is a schematic flow chart illustrating an implementation of a method for positioning coverage performance of a base station according to embodiment 1 of the present invention;
fig. 2 is a schematic structural diagram of a grid provided in embodiment 1 of the present invention;
fig. 3 is a comparison diagram of a cell simulation environment and a cell actual measurement environment provided in embodiment 1 of the present invention;
fig. 4 is a schematic structural diagram of a base station coverage performance positioning system according to embodiment 2 of the present invention.
Detailed Description
In the embodiment of the invention, a cell simulation environment is established by a base station coverage performance positioning system according to basic data, a threedimensional map and a ray tracking model; correcting the ray tracking model, obtaining a cell simulation environment corresponding to the corrected ray tracking model, and checking the height of a cell antenna according to the threedimensional map; and using the RSRP frequency sweep data of the actually measured reference signal received power of the cell antenna after the height check of the cell antenna, calculating the simulated RSRP data of the cell according to the rasterization of the cell simulation environment, checking the simulated RSRP data of the cell and the RSRP frequency sweep data, and judging whether the cell is a suspected problem cell according to the check result of the simulated RSRP data of the cell and the RSRP frequency sweep data of the cell.
The invention is further described in detail below with reference to the drawings and the specific embodiments.
Example 1
Fig. 1 is a schematic flow chart of an implementation of a method for positioning coverage performance of a base station according to embodiment 1 of the present invention, where as shown in fig. 1, the method includes:
step 110: and establishing a cell simulation environment according to the basic data, the threedimensional map and the ray tracking model.
Here, the basic data is the engineering parameter data of the planning base station, including the cell name, the base station name, the longitude and latitude and other data.
Specifically, the threedimensional map is composed of basic map layers such as a cell, a cell building, a cell base station, an antenna, a network element and an important traffic main road; the community map layer comprises community terrain height information, and the community building map layer comprises threedimensional attribute information such as community building height, shape characteristics and the like. The threedimensional map provides an accurate geographic information system for the cell simulation environment. Therefore, accurate geographic information which has influence on radio wave propagation, such as building coordinate information, provided by the threedimensional map ensures the accuracy of ray tracing. Therefore, the geographic information included in the threedimensional map is an important basis for carrying out ray tracing model correction, coverage and interference analysis.
The ray tracking model is a threedimensional ray tracking model and can be used for tracking all possible ray paths from a base station antenna transmitting point to a cell receiving point in the cell radio wave propagation process and calculating the RSRP of rays.
It should be noted that, for different cell simulation environments, only the same ray tracing model is used, and the ray coefficient factor is corrected by the method in step 120 described below. The reason is that: some cell simulation environments may be suitable for urban environments, while other cell simulation environments may be suitable only for rural areas. Therefore, the frequency bands and the antenna height ranges of different cell simulation environments are different, so that different cell simulation environments correspond to different ray tracking models theoretically. However, setting different ray tracing models for different cell simulation environments often results in a heavy workload. In view of this, a ray tracing model is adopted, and simulation and correction are performed by checking the propagation coefficient of the ray tracing model according to different environments.
In addition, the ray tracing model only comprises three cases of direct incidence, reflection and diffraction. In an actual network environment, there are four propagation modes of wireless signals: direct, reflected, scattered, and diffracted. These propagation situations arise under different propagation environments. In view of the complexity of the scattering events, they are not considered in practical engineering practice.
Step 120: and correcting the ray tracking model to obtain a cell simulation environment corresponding to the corrected ray tracking model, and checking the height of the cell antenna according to the threedimensional map.
Since the same ray tracing model is used for different cell simulation environments, as described in step 110 above, the ray tracing model needs to be corrected to obtain a ray tracing model suitable for each cell simulation environment. In particular, the accuracy of coverage and interference prediction in a cell simulation environment can be improved only by correcting ray coefficients of RSRP in the ray tracking model. Here, the ray tracing model is corrected, specifically, each ray parameter in RSRP is corrected; and then, the simulated RSRP data can be obtained by using the RSRP formula after the parameters are corrected, so that the simulated RSRP data is compared with the RSRP frequency sweep data. And correcting the ray tracking model and obtaining a cell simulation environment corresponding to the corrected ray tracking model.
Specifically, the method comprises the following steps. In this step, the correcting the ray tracing model includes:
a. selecting a scene corresponding to the cell in the current network environment, and selecting a scene according to the sceneCorrecting a direct incidence coefficient, a reflection coefficient and a diffraction coefficient in an RSRP formula by the measured data; the direct incidence coefficient is obtained by summing the absolute value of the difference between the RSRP measured value of each road measuring point and the RSRP direct incidence predicted value of each road measuring point, dividing the sum by 10, and multiplying the sum by the reciprocal of the sum of the common logarithms of the ray propagation distances of each road measuring point, wherein the specific formula is as follows:wherein, delta_{1}For the coefficient of incidence, i for each road measurement point, P_{r} ^{T}(i) For the actual value of RSRP of each road measuring point, P_{r} ^{M}(i) For each road station RSRP direct prediction, d_{i}And N is a positive integer greater than 0 and is the ray propagation distance of each path measuring point.
b. Calculating the reflection coefficient according to the first model prediction error sum facing the scene, wherein the first model prediction error sum is the sum of the squares of the difference between the RSRP measured value of each road measuring point and the RSRP direct and reflection predicted values of each road measuring point, and the specific formula is as follows:wherein, Pr^{M}(i,δ_{1}，δ_{2}) For each road station RSRP direct and reflection prediction, delta_{2}Is the reflection coefficient;
calculating the diffraction coefficient according to the second model prediction error sum of the scene, wherein the second model prediction error sum is the sum of the RSRP measured value of each road measuring point and the square of the difference between the RSRP direct injection and the diffraction predicted value of each road measuring point, and the specific formula is as follows:wherein, P_{r} ^{M}(i,δ_{1}，δ_{3}) RSRP direct and diffraction predictions, δ, for each road survey point_{3}Is the diffraction coefficient.
First, in order to ensure the accuracy of the correction, a sceneoriented context corresponding to the cell needs to be selected in the current network environment. In view of the fact that the accuracy of the ray tracking model mainly depends on the influence of obstacles such as buildings on the propagation of base station signals, the influence of the propagation environment on the direct transmission, the reflection and the diffraction of the base station signals under different facing scenes is different, and meanwhile, each cell has different interference conditions such as cofrequency interference, adjacent frequency interference, intermodulation interference and internetwork interference, it is necessary to select a facing scene corresponding to the terrain and topography of the cell, the buildings and the interference conditions, so as to realize the correction of the ray coefficient of RSRP in the ray tracking model.
Secondly, correcting a direct incidence coefficient, a reflection coefficient and a diffraction coefficient in an RSRP formula according to the selected measured data facing the scene to ensure that the RSRP formula corresponds to the RSRP in the cell simulation environment, wherein the RSRP formula corrects a propagation model by using the measured data.
Here, the RSRP is a sum of carrier wavelength divided by a product of 4 and pi, emission power divided by a distance between grid coordinate points in each cell, 2 plus a power of direct incidence coefficient, a direct product of reflection coefficient and reflection coefficient square, and a direct product of direct incidence coefficient and diffraction coefficient square, and is specifically represented byWherein, (i, j) is point coordinate, λ is carrier wavelength, wP_{i}For transmit power, dis () is the distance, cellid is the cell number, G (i, j) is the rasterized coordinate point, R_{u}Is a reflection coefficient, T_{v}The coefficient is direct incidence coefficient, and m and n are positive integers more than 0.
First, the direct coefficient δ needs to be adjusted_{1}And (6) carrying out correction. Specifically, a section of open area or path is selected in the facing scene, and the test terminal only receives the direct signal from the base station in the section of area and does not receive the reflected or diffracted signal. Within this segment of the area or path, the simplified received RSRP equation is:
the calculation unit of the RSRP is decibel millivoltAnd dbm. According to the simplified RSRP formula,according to the simplified RSRP formula,due to the fact thatThus, the coefficient of incidence is
Then, for the reflection coefficient δ_{2}And (6) carrying out correction. To correct the reflection coefficient delta_{2}And selecting a section of area or path in the facing scene, wherein the test terminal only receives the direct signal and the reflected signal from the base station in the section of area. Within this segment of area or path, the simplified RSRP formula is:
δ_{1}is the corrected direct coefficient. Based on the simplified RSRP formula, the sum of the prediction errors of the first model is obtained to beThe reflection coefficient delta can be obtained according to the sum of the prediction errors of the first model_{2}。
For the diffraction coefficient delta_{3}Method for correcting and correcting said reflection coefficient delta_{2}The method of performing the correction is consistent. To correct the diffraction coefficient delta_{3}And selecting a section of area or path in the facing scene, wherein the test terminal only receives the direct signal and the diffraction signal from the base station in the section of area. Within this segment of area or path, the simplified RSRP formula is:
δ_{1}is the corrected direct coefficient. Based on the simplified RSRP formula, the sum of the prediction errors of the second model is obtained to beThe diffraction coefficient delta can be obtained according to the sum of the predicted errors of the second model_{3}。
At this point, the correction of the ray tracing model is completed.
And then, checking the height of the cell antenna according to the threedimensional map. Specifically, through the building height information in the threedimensional map, a base station with a base station antenna height shorter than that of a cell building is quickly found, and checking is performed by combining with site base station information.
Step 130: and using the actually measured RSRP frequency sweep data of the cell antenna after the height of the cell antenna is checked, calculating cell simulation RSRP data according to the rasterization of the cell simulation environment, and checking the cell simulation RSRP data and the RSRP frequency sweep data.
Specifically, the method comprises the following steps:
a: rasterizing the cell simulation environment according to a predetermined accuracy, and calculating the cell simulation RSRP data of each grid using the RSRP formula.
Here, as shown in fig. 2, the cell simulation environment may be rasterized according to a predetermined precision of 5 meters by 5 meters, and center point RSRP data of each grid may be calculated using the RSRP formula after correcting the direct incidence coefficient, the reflection coefficient, and the diffraction coefficient, to obtain a set of cell simulation RSRP data Wherein the content of the first and second substances,representing each gridThe cell simulation RSRP data, g1 represents a first grid, gn represents an nth grid, and n is a positive integer.
The advantages of the rasterization are: average fast fading; reducing the impact caused by the building structure; the influence caused by the test route selection is reduced.
b: and performing field test on each grid of the cell to obtain a group of RSRP frequency sweep data of each grid.
Here, a field test is performed on the first grid g1 to obtain a set of the RSRP frequency sweep data R1_{g1}，R2_{g1}，……Rk_{g1}Wherein, R1_{g1}Representing the first RSRP frequency sweep data, Rk, obtained from the first ingrid test_{g1}And k is a positive integer and represents the kth RSRP frequency sweep data obtained by the first ingrid test.
And performing field test on the nth grid gn by analogy to obtain a group of RSRP frequency sweep data R1_{gn}，R2_{gn}，……Rk_{gn}Wherein, R1_{gn}Represents the first RSRP frequency sweep data, Rk, obtained from the nth grid test_{gn}And k represents the kth RSRP frequency sweep data obtained by the nth grid test, wherein k is a positive integer.
c: calculating an average error of the cell simulation RSRP data for the each grid and an average of the set of RSRP frequency sweep data for the each grid.
In c, an average of the set of RSRP sweep data for each grid is first calculated. Specifically, the average value of the set of RSRP sweep data for each grid is: a set of RSRP sweep data is summed and divided by the number of RSRP sweep data in the set, and the average is given by:
here, m is a positive integer.
The average error of the cell simulation RSRP data for each grid and the average of the set of RSRP sweep data for each grid is: each of saidSubtracting the average value of the set of RSRP frequency sweep data of each grid from the cell simulation RSRP data of the grid, wherein the average error epsilon is calculated by the formula:
d: calculating a standard deviation of the set of RSRP frequency sweep data for the each grid.
Specifically, the standard deviation of the set of RSRP sweep data for each grid is: a sum of squares of differences between each RSRP sweep data of the set of RSRP sweep data for each grid and an average of the set of RSRP sweep data for the each grid, and a value divided by a number of the set of RSRP sweep data for the each grid, a standard deviation σ of the set of RSRP sweep data for the each grid^{2}The formula of (1) is:
subsequently, as shown in fig. 3, the geography presents a comparative graph of the cell simulation environment and the cell measured environment.
Step 140: and judging whether the cell is a suspected problem cell or not according to the check result of the cell simulation RSRP data and the RSRP frequency sweeping data.
Specifically, the method comprises the following steps:
and when the average value of the average errors between the cell simulation RSRP data and the RSRP frequency sweep data of all grids in the cell simulation environment and the average value of the standard variances of the RSRP frequency sweep data of all grids in the cell simulation environment respectively reach a first judgment threshold value and a second judgment threshold value, determining that the cell is the suspected problem cell.
For example, when the number of cell sweep grids for which the RSRP sweep data can be checked is greater than 50, when the first decision threshold value is greater than 5dbm and the second decision threshold value is greater than 8 dbm; or when the first decision threshold value is less than10 dbm and the second decision threshold value is less than10 dbm, confirming that the cell is the suspected problem cell. The first decision threshold value and the second decision threshold value are empirical values and can be obtained based on factors such as actual landform environment and building condition.
After completing step 140, the method further comprises:
and checking the suspected problem cell. And the suspected reason and the treatment suggestion of the problem cell can be positioned through the background check, the auxiliary judgment condition and the geographically presented comparison graph of the cell simulation environment and the cell actual measurement environment.
At this point, the process of base station coverage performance location is completed.
The method for positioning the coverage performance of the base station provided by the embodiment effectively links an LTE planning stage and a construction stage, so that the working efficiency of controlling the LTE construction quality is improved, and the network coverage is more comprehensive; moreover, the network coverage problem can be remotely and intensively discovered, and the requirement of 'beginning to end' of LTE network construction is ensured; meanwhile, the accuracy of basic data is solved, and a good foundation is laid for higherlevel optimization; the working efficiency of the LTE network construction quality can be improved, the network coverage is more comprehensive, the LTE network construction quality can be effectively controlled, and the problem of coverage performance can be remotely and intensively discovered.
Example 2
Fig. 4 is a schematic structural diagram of a base station coverage performance positioning system provided in embodiment 2 of the present invention, and as shown in fig. 4, the system includes:
and the simulation environment establishing module 210 is used for establishing a cell simulation environment according to the basic data, the threedimensional map and the ray tracking model.
And the ray model correction module 220 is configured to correct the ray tracking model and obtain a cell simulation environment corresponding to the corrected ray tracking model.
The ray model correction module 220 includes:
a sceneoriented selecting unit 221, configured to select a scene oriented corresponding to the cell in an existing network environment;
a direct incidence coefficient correction unit 222, configured to correct a direct incidence coefficient in an RSRP formula according to the sceneoriented measured data;
a reflection coefficient correction unit 223, configured to correct a reflection coefficient in the RSRP formula according to the actually measured data facing the scene;
a diffraction coefficient correction unit 224, configured to correct a diffraction coefficient in the RSRP formula according to the measured data facing the scene.
And an antenna height checking module 230, configured to check the height of the cell antenna according to the threedimensional map.
A data checking module 240, configured to use the cell antenna actual measurement RSRP frequency sweep data after the cell antenna height check, calculate cell simulation RSRP data according to the cell simulation environment rasterization, and check the cell simulation RSRP data and the RSRP frequency sweep data.
The collation data module 240 includes:
a simulated RSRP data unit 241, configured to rasterize the cell simulation environment according to a predetermined accuracy, and calculate the cell simulation RSRP data of each grid using the RSRP formula;
an RSRP sweep data unit 242, configured to perform a field test on each grid of the cell to obtain a set of RSRP sweep data of each grid;
an average error unit 243 for calculating an average error of the cell simulation RSRP data of said each grid and an average value of the set of RSRP sweep data of said each grid;
a standard deviation unit 244 for calculating a standard deviation of the set of RSRP sweep data for the each grid.
A problem cell output module 250, configured to determine whether the cell is a suspected problem cell according to a check result of the simulated RSRP data and the RSRP swept frequency data of the cell.
Specifically, the determining, by the problem cell output module 250, whether the cell is a suspected problem cell according to the check result of the simulated RSRP data and the simulated RSRP swept frequency data of the cell includes:
and when the average value of the average errors between the cell simulation RSRP data and the RSRP frequency sweep data of all grids in the cell simulation environment and the average value of the standard variances of the RSRP frequency sweep data of all grids in the cell simulation environment respectively reach a first judgment threshold value and a second judgment threshold value, determining that the cell is the suspected problem cell.
In practical applications, the simulation environment establishing module 210, the radiation model correcting module 220, the antenna height checking module 230, the verification data module 240, and the problem cell output module 250 may be implemented by a Central Processing Unit (CPU), a Digital Signal Processor (DSP), a microprocessor Unit (MPU), or a Programmable logic Array (FPGA) in any computer device.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention.
Claims (9)
1. A method for positioning coverage performance of a base station, the method comprising:
establishing a cell simulation environment according to the basic data, the threedimensional map and the ray tracking model;
selecting a scene facing to the terrain and landform, buildings and interference conditions of the cell in the current network environment, correcting the ray tracking model based on the scene facing to the scene, obtaining a cell simulation environment corresponding to the corrected ray tracking model, and checking the height of the cell antenna according to the threedimensional map; using the RSRP frequency sweep data of the actually measured reference signal receiving power of the cell antenna after the height of the cell antenna is checked, rasterizing and calculating cell simulation RSRP data according to the cell simulation environment, and checking the cell simulation RSRP data and the RSRP frequency sweep data;
and judging whether the cell is a suspected problem cell or not according to the check result of the cell simulation RSRP data and the RSRP frequency sweeping data.
2. The method of claim 1, wherein the correcting the ray tracing model comprises:
correcting a direct incidence coefficient, a reflection coefficient and a diffraction coefficient in an RSRP formula according to the actually measured data facing the scene;
the direct incidence coefficient is obtained by summing the absolute value of the difference between the RSRP measured value of each road measuring point and the RSRP direct incidence predicted value of each road measuring point, dividing the sum by 10, and multiplying the sum by the reciprocal of the common logarithm summation of the ray propagation distance of each road measuring point;
calculating the reflection coefficient according to the first model prediction error sum of the scene, wherein the first model prediction error sum is the sum of the squares of the difference between the RSRP measured value of each road measuring point and the RSRP direct and reflection predicted values of each road measuring point;
and calculating the diffraction coefficient according to the second model prediction error sum facing the scene, wherein the second model prediction error sum is the sum of the RSRP measured value of each road measuring point and the square of the difference between the RSRP direct incidence and the diffraction predicted value of each road measuring point.
3. The method of claim 2, wherein the calculating cell simulation RSRP data from the cell simulation environment rasterization and collating the cell simulation RSRP data with RSRP sweep data comprises:
rasterizing the cell simulation environment according to a preset precision, and calculating the cell simulation RSRP data of each grid by using the RSRP formula;
performing field test on each grid of the cell to obtain a group of RSRP frequency sweep data of each grid;
calculating an average error of simulated RSRP data for each grid of said cell and an average of said set of RSRP sweep data for said each grid;
calculating a standard deviation of said each set of grid RSRP sweep data for said cell.
4. The method of claim 3, wherein determining whether the cell is a suspected problem cell based on the comparison of the simulated RSRP data and the RSRP frequency sweep data comprises:
and when the average value of the average errors between the cell simulation RSRP data and the RSRP frequency sweep data of all grids in the cell simulation environment and the average value of the standard variances of the RSRP frequency sweep data of all grids in the cell simulation environment respectively reach a first judgment threshold value and a second judgment threshold value, determining that the cell is the suspected problem cell.
5. The method according to any one of claims 1 to 4, further comprising:
and checking the suspected problem cell.
6. A base station coverage performance positioning system, the system comprising:
the simulation environment establishing module is used for establishing a cell simulation environment according to the basic data, the threedimensional map and the ray tracking model;
the ray model correction module is used for selecting a scene facing the situation corresponding to the landform, the building and the interference situation of the cell in the current network environment, correcting the ray tracking model based on the scene facing the situation and obtaining a cell simulation environment corresponding to the corrected ray tracking model;
the antenna height checking module is used for checking the height of the cell antenna according to the threedimensional map;
the verification data module is used for using the actually measured RSRP frequency sweep data of the cell antenna after the height verification of the cell antenna, calculating cell simulation RSRP data according to the rasterization of the cell simulation environment, and verifying the cell simulation RSRP data and the RSRP frequency sweep data;
and the problem cell output module is used for judging whether the cell is a suspected problem cell according to the check result of the simulated RSRP data and the RSRP frequency sweep data of the cell.
7. The system of claim 6, wherein the ray model correction module comprises:
the direct incidence coefficient correction unit is used for correcting a direct incidence coefficient in an RSRP formula according to the sceneoriented measured data;
a reflection coefficient correction unit, configured to correct a reflection coefficient in the RSRP formula according to the actually measured data oriented to the scene;
and the diffraction coefficient correction unit is used for correcting the diffraction coefficient in the RSRP formula according to the actually measured data facing the scene.
8. The system of claim 7, wherein said reconciliation data module comprises:
a simulation RSRP data unit, configured to rasterize the cell simulation environment according to a predetermined accuracy, and calculate the cell simulation RSRP data of each grid using the RSRP formula;
an RSRP sweep data unit, configured to perform a field test on each grid of the cell to obtain a set of RSRP sweep data of each grid;
an average error unit for calculating an average error of the cell simulation RSRP data of each grid and an average of the set of RSRP sweep data of each grid;
a standard deviation unit to calculate a standard deviation of the set of RSRP frequency sweep data for each grid.
9. The system of claim 8, wherein the problem cell output module determining whether the cell is a suspected problem cell based on the comparison of the simulated RSRP data and the RSRP swept data comprises:
and when the average value of the average errors between the cell simulation RSRP data and the RSRP frequency sweep data of all grids in the cell simulation environment and the average value of the standard variances of the RSRP frequency sweep data of all grids in the cell simulation environment respectively reach a first judgment threshold value and a second judgment threshold value, determining that the cell is the suspected problem cell.
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