CN107318114B - Method and device for planning adjacent cells - Google Patents
Method and device for planning adjacent cells Download PDFInfo
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Abstract
The invention provides a method and a device for planning adjacent cells, relates to the field of communication, and solves the problems that in the prior art, a manual planning method is single in dimension, insufficient in accuracy, large in manpower and material resource consumption, low in efficiency, and unilateral and passive in adjacent cell planning. The method comprises the following steps: acquiring preset multi-dimensional data information of each cell in a preset area range; constructing a multi-dimensional interference matrix between each cell and a corresponding history adjacent interval according to the multi-dimensional data information; and planning a corresponding adjacent cell for each cell according to the multi-dimensional interference matrix and preset rule parameters. The scheme of the invention carries out optimization analysis of the adjacent cell planning based on the multidimensional data, achieves the purposes of comprehensive range and clear key, realizes mutual verification and supplement among data, and improves the accuracy of planning; and the accurate automatic analysis of the adjacent region planning optimization is realized, the manpower and material resources are saved, and the working efficiency is improved.
Description
Technical Field
The present invention relates to the field of communications, and in particular, to a method and an apparatus for planning neighboring cells.
Background
With the planning, establishment and operation of an LTE (Long Term Evolution) network, the network scale is continuously developed, and the network structure is increasingly complex. Especially, 2G, 3G and 4G networks exist simultaneously, complement each other in service, and are dependent on each other, so that the whole communication network is mature continuously. Meanwhile, the optimization of related parameters of interoperation such as neighboring cell configuration between multiple systems is also increasingly complex.
However, currently, planning personnel mainly rely on subjective experience and perform planning optimization and cross-system complex network configuration on adjacent cells based on manual operation adjustment, and no good method is provided for overcoming the problems.
As described above, currently, there is no feasible method for solving the problem of neighbor cell planning, and according to the commonly performed manual planning method, the following disadvantages mainly exist:
1. single dimension and insufficient accuracy: because the network scale is large, the data is numerous and complex, planning is mainly carried out by depending on engineering parameters, the accuracy cannot be ensured, and the adjacent cell configuration in the engineering period cannot meet the requirement of improving the network quality along with the coverage change caused by various subsequent factors.
2. Manpower and material resources are consumed greatly, and the efficiency is low: due to the complexity of network configuration among the cross-system modes, the workload is huge at present, and because the planning optimization of the neighboring cells depends on manual operation and adjustment, huge labor cost is caused, and the efficiency is low.
3. One-sided and passive neighbor optimization: the current adjacent cell optimization is a problem-driven passive type, only solves the problems of points (complaints) and lines (drive tests), and cannot find the rationality problem of the adjacent cells of the whole network.
Disclosure of Invention
The invention aims to provide a method and a device for planning adjacent cells, and solves the problems that the conventional manual planning method is single in dimension, insufficient in accuracy, large in manpower and material resource consumption, low in efficiency, and one-sided and passive in adjacent cell planning.
To solve the above technical problem, an embodiment of the present invention provides a method for planning a neighboring cell, including:
acquiring preset multi-dimensional data information of each cell in a preset area range;
constructing a multi-dimensional interference matrix between each cell and a corresponding history adjacent interval according to the multi-dimensional data information;
and planning a corresponding adjacent cell for each cell according to the multi-dimensional interference matrix and preset rule parameters.
The step of obtaining preset multidimensional data information of each cell in a predetermined area range comprises:
acquiring basic data, measurement report MR data, frequency sweep data and telephone traffic data of each cell in a predetermined area range, wherein the basic data comprises working parameter configuration data, switching data and historical neighbor relation data.
Wherein, the step of constructing the multidimensional interference matrix between each cell and the corresponding history adjacent interval according to the multidimensional data information comprises the following steps:
adopting grids with preset sizes to divide the preset area, and carrying out convergence processing on multi-dimensional data information belonging to different network systems in each grid;
according to the gathered multidimensional data information, constructing an MR interference matrix, a frequency sweeping interference matrix and an engineering parameter configuration interference matrix of each cell and a corresponding history adjacent interval under different network systems;
and performing weighted fusion on the MR interference matrix, the sweep frequency interference matrix and the engineering parameter configuration interference matrix to obtain a first fusion interference matrix.
The step of constructing an MR interference matrix, a sweep frequency interference matrix and an engineering parameter configuration interference matrix of each cell and a corresponding history adjacent interval under different network systems according to the aggregated multidimensional data information comprises the following steps:
acquiring MR level parameters of MR level types corresponding to different network systems of each cell and corresponding historical adjacent cells in the MR data subjected to the convergence processing, and acquiring first correlation between each cell and corresponding historical adjacent cells according to the MR level parameters;
constructing an MR interference matrix between each cell and the corresponding history adjacent interval according to the first correlation;
acquiring sweep frequency level parameters of sweep frequency level types corresponding to different network systems of each cell and corresponding historical adjacent cells from the collected sweep frequency data, and acquiring second relativity between each cell and corresponding historical adjacent cells according to the sweep frequency level parameters;
according to the second correlation, constructing a frequency sweep interference matrix of each cell and the corresponding historical adjacent interval;
acquiring an ideal coverage range of each cell and a corresponding historical neighboring cell under configuration structures of different network systems according to the work parameter configuration data subjected to the aggregation processing, and acquiring a third correlation between each cell and the corresponding historical neighboring cell according to the ideal coverage range;
and constructing the power parameter configuration interference matrix between each cell and the corresponding history adjacent interval according to the third correlation.
Wherein, the step of constructing the multidimensional interference matrix between each cell and the corresponding history adjacent interval according to the multidimensional data information further comprises:
according to the switching data subjected to the convergence processing, a switching interference matrix of each cell and the corresponding history adjacent interval under different network systems is constructed;
and performing weighted fusion on the switching interference matrix and the first fusion interference matrix to obtain a second fusion interference matrix.
Before performing weighted fusion on the MR interference matrix, the sweep frequency interference matrix, and the engineering parameter configuration interference matrix to obtain a first fusion interference matrix, the method further includes:
and respectively carrying out telephone traffic weighting on the MR interference matrix, the frequency sweep interference matrix and the engineering parameter configuration interference matrix according to the telephone traffic data subjected to the convergence processing.
Before the constructing the multidimensional interference matrix between each cell and the corresponding history neighbor interval according to the multidimensional data information, the method further includes:
abandoning the data with incomplete sweep frequency, the data lacking longitude and latitude and the data with the level value lower than a preset threshold;
and acquiring the average value of the level data belonging to the same longitude and latitude in the MR data and the sweep frequency data.
The step of planning a corresponding neighboring cell for each cell according to the multidimensional interference matrix and preset rule parameters includes:
acquiring the actual coverage area of each cell according to the work parameter configuration data;
and planning a corresponding adjacent cell for each cell by adopting a genetic algorithm according to the multi-dimensional interference matrix, the preset rule parameters and the actual coverage range of each cell.
To solve the foregoing technical problem, an embodiment of the present invention further provides an apparatus for planning a neighboring cell, including:
the acquisition module is used for acquiring preset multi-dimensional data information of each cell in a preset area range;
the building module is used for building a multi-dimensional interference matrix between each cell and the corresponding history adjacent interval according to the multi-dimensional data information;
and the planning module is used for planning the corresponding adjacent cell for each cell according to the multi-dimensional interference matrix and the preset rule parameters.
Wherein the acquisition module comprises:
the first acquisition unit is used for acquiring basic data, measurement report MR data, frequency sweep data and telephone traffic data of each cell in a preset area range, wherein the basic data comprises work parameter configuration data, switching data and historical neighbor relation data.
Wherein the building block comprises:
the rasterization unit is used for dividing the preset area by adopting grids with preset sizes and converging the multi-dimensional data information belonging to different network systems in each grid;
the first construction unit is used for constructing an MR interference matrix, a frequency sweeping interference matrix and an engineering parameter configuration interference matrix of each cell and a corresponding history adjacent interval under different network systems according to the multi-dimensional data information subjected to the convergence processing;
and the second fusion unit is used for performing weighted fusion on the MR interference matrix, the frequency sweep interference matrix and the engineering parameter configuration interference matrix to obtain a first fusion interference matrix.
Wherein the building block further comprises:
the second construction unit is used for constructing a switching interference matrix of each cell and the corresponding historical adjacent interval under different network systems according to the switching data subjected to the convergence processing;
and the second fusion unit is used for performing weighted fusion on the switching interference matrix and the first fusion interference matrix to obtain a second fusion interference matrix.
Wherein the planning module comprises:
the second acquisition unit is used for acquiring the actual coverage area of each cell according to the working parameter configuration data;
and the planning unit is used for planning the corresponding adjacent cell for each cell by adopting a genetic algorithm according to the multi-dimensional interference matrix, the preset rule parameters and the actual coverage range of each cell.
The technical scheme of the invention has the following beneficial effects:
the method for planning the adjacent cells comprises the steps of firstly obtaining preset multi-dimensional data information of each cell in a preset area range; then, according to the multidimensional data information, a multidimensional interference matrix of each cell and a corresponding history adjacent interval is constructed; and finally planning a corresponding adjacent cell for each cell according to the multi-dimensional interference matrix and preset rule parameters. The method carries out optimization analysis of the adjacent region planning based on the multidimensional data, achieves the purposes of comprehensive range and clear key, realizes mutual verification and supplement among the data, and improves the accuracy of the planning; the method realizes accurate automatic analysis of adjacent region planning optimization, saves manpower and material resources and improves working efficiency; the problems that the existing manual planning method is single in dimension, insufficient in accuracy, large in manpower and material resource consumption, low in efficiency, and one-sided and passive in neighbor cell planning are solved.
Drawings
FIG. 1 is a flow chart of a method for planning a neighboring cell according to the present invention;
fig. 2 is a schematic structural diagram of the apparatus for planning a neighboring cell according to the present invention.
Detailed Description
In order to make the technical problems, technical solutions and advantages of the present invention more apparent, the following detailed description is given with reference to the accompanying drawings and specific embodiments.
As shown in fig. 1, the method for planning a neighboring cell according to the embodiment of the present invention includes:
102, constructing a multi-dimensional interference matrix of each cell and a corresponding history adjacent interval according to the multi-dimensional data information;
and 103, planning a corresponding adjacent cell for each cell according to the multi-dimensional interference matrix and preset rule parameters.
The method for planning the adjacent cells performs optimization analysis on the planning of the adjacent cells based on the multidimensional data, achieves the purposes of comprehensive range and clear key points, realizes mutual verification and supplement among the data, and improves the accuracy of planning; accurate automatic analysis of neighbor planning optimization is realized, manpower and material resources are saved, and working efficiency is improved; the problems that the existing manual planning method is single in dimension, insufficient in accuracy, large in manpower and material resource consumption, low in efficiency, and one-sided and passive in neighbor cell planning are solved.
Preferably, the step of step 101 may include:
step 1011, acquiring basic data, measurement report MR data, frequency sweep data and traffic data of each cell in the predetermined area range, wherein the basic data includes engineering parameter configuration data, handover data and historical neighboring relation data.
At the moment, a multi-dimensional interference matrix is constructed based on MR data, sweep frequency data, engineering parameter configuration data, switching data and the like, and neighbor planning optimization analysis is realized based on the multi-dimensional interference matrix, so that the purposes of comprehensive range and clear key point are achieved, mutual verification and supplement among data are realized, and the planning accuracy is improved.
The basic data may also include cell identification, cell type, longitude and latitude, frequency point, code, etc. The basic data is the most basic part for realizing the interference analysis of the adjacent regions, and the accuracy and the effectiveness of the basic data directly influence the analysis result.
Specifically, MR data of a cell in a busy day, morning and evening, and sweep data in an MR period can be acquired.
The switching data reflects the switching relation among the cells, and when the interference relation among the cells is analyzed based on switching, the switching data of busy hours in a continuous week of the cells can be collected; when the inter-cell interference relationship is analyzed based on other modes, the switching data of busy hours in 2-3 days of the cell can be collected. The Cell identification (CelId) and the Neighbor Cell identification (Neighbor Cell Id) of the switching data correspond to the same type of fields in the basic data.
The format of the collected switching data may be as shown in table 1 below:
TABLE 1
The historical neighboring cell relation data reflects the neighboring cell relation among the cells, and the neighboring cell relation is used as the current network configuration data, is the main content required by analyzing the interference among the cells, and can be generally obtained according to the cell related information in the basic data. The Cell Id and Neighbor Cell Id of the historical Neighbor relation data also correspond to the same type of fields in the basic data.
The format of the collected historical neighboring relationship data based on GSM (Global System for Mobile Communication) can be shown in table 2 below:
TABLE 2
After the MR data, frequency sweep data, working parameter configuration data, switching data and other data of the cells are obtained, the inter-cell interference matrix can be constructed by comprehensively considering weight factors. Longitude and latitude, azimuth angle, inclination angle, station height and cell transmitting power can be considered based on the working parameter configuration data; considering the number of handover attempts and the number of successes based on the handover data; considering the level and time delay of a frequency sweep neighbor cell based on frequency sweep data; considering MR measurement levels based on MR data; traffic volume and traffic flow are considered based on the traffic volume data.
In order to adapt to different analysis scenes, a frequency sweep interference matrix, an MR interference matrix, an engineering parameter configuration interference matrix and the like need to be generated respectively. The following describes the steps for obtaining different interference matrices.
Preferably, the step of step 102 may include:
step 1021, adopting grids with preset sizes to divide the preset area, and converging the multi-dimensional data information belonging to different network systems in each grid.
In the method, the multi-dimensional data information of different network systems can be gathered through rasterization so as to comprehensively analyze data of different network systems, and the accuracy and the efficiency of data analysis are ensured. The different network systems may include 3 network systems, such as GSM, TD-SCDMA (Time Division-Synchronous Code Division Multiple Access) and LTE.
Taking the sweep frequency data as an example, because the sweep frequency data are respectively output by G/T/L, different devices may output results in different forms, and only single-network data exists at the same sampling point in the same longitude and latitude, and rasterization data convergence is required.
The size of the grid can be adjusted according to the actual situation, for example, the grid size can be initially set to 20m by 20 m. The level data attributed to G/T/L in the grid can be averaged by the following equation:
grid average level ═ Σ sampling point level/number of sampling points.
And 1022, constructing an MR interference matrix, a frequency sweep interference matrix and an engineering parameter configuration interference matrix of each cell and the corresponding history adjacent interval under different network systems according to the aggregated multidimensional data information.
The multi-dimensional deep fusion analysis based on the interference relationship between the multi-dimensional interference matrix and the cells is realized by constructing the MR interference matrix, the frequency sweep interference matrix and the engineering parameter configuration interference matrix between each cell and the historical neighbor cells under different network systems, so that the corresponding neighbor cells can be accurately planned for each cell.
And 1023, performing weighted fusion on the MR interference matrix, the sweep frequency interference matrix and the engineering parameter configuration interference matrix to obtain a first fusion interference matrix.
The fusion interference matrix is obtained based on the multi-dimensional interference matrix, so that comprehensive analysis and use of the adjacent region planning are facilitated, and the accuracy and the efficiency of planning are improved.
At the moment, accurate and automatic analysis of neighbor cell planning optimization is realized by constructing the multi-dimensional interference matrixes and the corresponding fusion interference matrixes under different network systems, and the accuracy and the high efficiency of neighbor cell planning are ensured.
Further, the step of step 1022 may include:
step 10221, acquiring, in the MR data subjected to aggregation processing, MR level parameters of MR level types corresponding to different network systems of each cell and corresponding historical neighboring cells, and acquiring a first correlation between each cell and corresponding historical neighboring cells according to the MR level parameters;
step 10222, constructing an MR interference matrix between each cell and a corresponding history neighbor according to the first correlation;
step 10223, obtaining sweep frequency level parameters of sweep frequency level types corresponding to different network systems of each cell and corresponding historical neighboring cells from the sweep frequency data subjected to convergence processing, and obtaining a second correlation between each cell and corresponding historical neighboring cells according to the sweep frequency level parameters;
step 10224, according to the second correlation, constructing a frequency sweep interference matrix between each cell and the corresponding history neighbor interval;
step 10225, obtaining an ideal coverage range of each cell and the corresponding historical neighboring cell under configuration structures of different network systems according to the aggregated working parameter configuration data, and obtaining a third correlation between each cell and the corresponding historical neighboring cell according to the ideal coverage range;
step 10226, according to the third correlation, constructing an interference matrix of the power parameter configuration between each cell and the corresponding history neighbor interval.
At the moment, through the correlation analysis of the cell and the corresponding historical adjacent interval, the correlation interference matrix of the cell and the corresponding historical adjacent interval can be accurately constructed, and then accurate adjacent area planning is realized according to the interference matrix.
The following illustrates specific implementation steps for acquiring the first correlation in different network systems.
GSM network standard-MR interference matrix:
the step of the step 10221 may include: acquiring the number MR of sample points which appear in a measurement report of a main cell s in a history neighbor cell i of the main cell s and have a difference of Rxlev received signal code power intensity with the main cell s larger than a first threshold value asi(a) And obtaining a total number of sample points MR of the MR measurement of the primary cell sall；
Obtaining a first correlation GMR between a main cell s and a history adjacent cell i by the following formularsi：
GMRrsi＝MRsi(a)/MRall*100％；
Wherein MR can be obtained by the following formulasi(a)：
Wherein (MR)j.GSMNciRxlev-MRjGSMScRxlev) > a represents the attribute of the sampling point that the strength difference between the Rxlev received signal code power of the adjacent cell i of the jth sampling point and the Rxlev received signal code power of the main cell s is greater than a first threshold value a. m is the number of the historical neighbor cells of the main cell s, m is an integer greater than or equal to 1, and j is greater than or equal to 1 and less than or equal to m. The first threshold value a is an adjustable parameter, such as-12 dB.
The correlation between the main cell s and each historical adjacent cell can also be calculated once through the mode.
To is directed atMR data of GSM, the MRsi(a)And MRallOr not from the sampling point, the neighbor cell interference level measurement statistical result output from the existing equipment is only needed.
TD network system-MR interference matrix:
similar to the above MR interference matrix obtaining manner of the GSM network system, the step 10221 may include: acquiring the number MR of sample points which appear in a measurement report of a main cell s in a history adjacent cell i of the main cell s and have the power intensity difference with the P-CCPCH receiving signal code of the main cell s larger than a second threshold value bsi(b)And obtaining a total number of sample points MR of the MR measurement of the primary cell sall；
Obtaining a first correlation TMR between a main cell s and a historical neighbor cell i through the following formularsi：
TMRrsi＝MRsi(b)/MRall*100％；
Wherein MR can be obtained by the following formulasi(b)：
Wherein (MR)j.TDNciPccpchRscp-MRjTDScPcpchRscp) > b represents the attribute of the sampling point that the intensity difference between the P-CCPCH received signal code power of the j-th sampling point adjacent cell i and the P-CCPCH received signal code power of the main cell s is greater than a second threshold value b. The second threshold b is an adjustable parameter, which may be-6 dB, for example.
LTE network standard-MR interference matrix:
similar to the above MR interference matrix obtaining manner of GSM and TD network systems, the step 10221 may include: acquiring the number MR of sample points which appear in a measurement report of the main cell s in a history neighbor cell i of the main cell s and have the RSRP receiving signal code power intensity difference with the main cell s larger than a third threshold value csi(c)And obtaining a total number of sample points MR of the MR measurement of the primary cell sall；
Obtaining a first correlation LMR between a main cell s and a historical neighbor cell i through the following formularsi：
LMRrsi＝MRsi(c)/MRall*100％；
Wherein MR can be obtained by the following formulasi(c)：
Wherein (MR)j.LTENciRSRP-MRjLTESCRSRP) > c represents the attribute of the sampling point that the intensity difference between the RSRP receiving signal code power of the adjacent region i of the jth sampling point and the RSRP receiving signal code power of the main cell s is larger than a third threshold value c. The third threshold value c is an adjustable parameter, such as-6 dB.
The manner of obtaining the second correlation may refer to the manner of the first correlation, and will not be further described here.
The following illustrates specific implementation steps for obtaining the third correlation in different network systems.
GSM network type-engineering parameter configuration interference matrix:
the step of step 10225 may include: acquiring the coverage overlapping area CF of a main cell s and a history adjacent cell isiI.e. the intersection of the ideal coverage of the main cell s and the ideal coverage of the history neighboring cell i; and obtains the ideal coverage area CF of the primary cell ssall；
Obtaining a third correlation GCF between the main cell s and the historical neighbor cell i by the following formularsi：
GCFrsi＝CFsi/CFsall*100％；
The radius of the ideal coverage area refers to a preset multiple, such as 1.6 times, of the average distance value of the nearest 3 base stations within the cell coverage direction angle range. Ideal coverage area CFsallThe radius of accessible ideal coverage draws the circle, intercepts the area that the district covered the angle and occupies, promptly:
radius circle of ideal coverage area cell coverage direction angle/360;
the cell coverage direction angle is 120 degrees by default, and 360 degrees is taken in all directions.
The same manner as the GSM network system described above may be adopted when obtaining the third correlation in TD, TD-GSM, LTE-GSM, and LTE-TD network systems, and details are not repeated here.
In performing correlation analysis such as cell redundancy, it is also necessary to refer to an interference relationship of inter-cell handover, and therefore, preferably, the step of step 102 may further include:
step 1024, constructing a switching interference matrix between each cell and a corresponding history adjacent interval under different network systems according to the switching data subjected to the convergence processing;
and 1025, performing weighted fusion on the switching interference matrix and the first fusion interference matrix to obtain a second fusion interference matrix.
At the moment, the switching interference matrix is obtained, so that the data reference types are enriched, different service requirements are met, mutual verification and supplement among data are realized, and the planning accuracy is improved.
Similar to the MR interference matrix, the sweep frequency interference matrix, and the engineering parameter configuration interference matrix, when the handover interference matrix is obtained, the fourth correlation between each cell and the corresponding history neighbor interval may be obtained according to the handover data, and then the handover interference matrix is constructed according to the fourth correlation.
The following illustrates specific implementation steps for obtaining the fourth correlation in different network systems.
GSM network type-switching interference matrix:
obtaining T1Switching times between a history adjacent cell i of a main cell s and the main cell s within hour
The method comprises the steps of switching times from a neighboring cell i to a main cell s and switching times from the main cell s to the neighboring cell i; and obtain T1Total number of handovers of primary cell s within hour
The total cut-in times and the total cut-out times are included;
obtaining a main cell s and a neighbor cell by the following formulaFourth correlation GHO of region irsi：
The same manner as the GSM handover may be adopted when the fourth correlation is obtained by LTE intra-network handover and LTE-TD inter-network handover, which is not described herein again.
Preferably, before the step 1023, the method may further include:
and step 1026, traffic weighting is respectively performed on the MR interference matrix, the frequency sweep interference matrix and the engineering parameter configuration interference matrix according to the traffic data subjected to aggregation processing.
At the moment, the matrix is weighted by telephone traffic, so that mutual authentication and supplement among data are further realized, the data architecture is enriched, and the accuracy and the efficiency of adjacent region planning are improved.
Preferably, before the step 102, the method may further include:
and 104, discarding the data with incomplete frequency sweep, the data lacking latitude and longitude and the data with the level value lower than a preset threshold value.
The useless data with incomplete sweep frequency, lack of latitude and longitude and level values lower than the preset threshold value are abandoned, so that the further processing of the useless data is avoided, the data load is reduced, the operation efficiency is improved, the interference of the useless data on the analysis is avoided, and the accuracy of the analysis is ensured.
For the sweep frequency data, the sensitivity of the sweep frequency instrument is high, signals with the level lower than-120 dBm can be received, but the data can not be analyzed by the mobile phone terminal, and the data cannot play a role in analysis, so the sweep frequency data can be directly discarded. Based on this, the preset threshold may be set to-120 dBm.
And 105, acquiring an average value of the level data belonging to the same longitude and latitude in the MR data and the sweep frequency data.
Here, by obtaining the average value of the level data, the accuracy and effectiveness of the subsequent level data-based analysis are improved.
When the frequency sweep data is processed, a cell corresponding to the frequency sweep data can be determined according to the frequency point and the cell ID in the frequency sweep data, so that the frequency sweep data can be analyzed and processed based on the cell.
Preferably, the step of step 103 may include:
step 1031, acquiring the actual coverage area of each cell according to the work parameter configuration data;
and 1032, planning a corresponding adjacent cell for each cell by adopting a genetic algorithm according to the multi-dimensional interference matrix, the preset rule parameters and the actual coverage range of each cell.
Here, the genetic algorithm is based on an inter-cell interference relationship model, and can integrate multiple algorithms such as a user-specified neighbor cell relationship, a co-sited cell, a forward indoor distribution, a forward interference relationship, a backward interference relationship, a forward first round neighbor cell and a backward first round neighbor cell, and the like, so as to realize the compatibility of neighbor cell planning and optimization.
At the moment, the neighbor cell is planned for the cell in an analysis mode of a genetic algorithm, so that the compatibility of neighbor cell planning and optimization is realized, and the accuracy of planning and optimization is improved. The method of the embodiment of the invention supports the user to set the rule parameters autonomously. And aiming at the finally generated multi-dimensional interference matrix, the optimal neighbor cell configuration suggestion is given by combining with a user-defined setting rule, so that the distributed neighbor cells can be applied to the existing network, and the optimization efficiency is improved.
Specifically, the method according to the embodiment of the present invention may obtain the preset rule parameters according to a preset GIS (Geographic information system) layer setting interface, an interference matrix parameter setting interface, an inter-cell overlapping coverage parameter setting interface, a neighboring cell planning parameter setting interface, and the like.
Preferably, the specific implementation flow of step 1031 is as follows:
firstly, receiving or measuring level-95 dBm is taken as a cell coverage edge;
then taking the straight-line distance from the coverage edge to the longitude and latitude of the cell as the coverage radius of the cell;
determining the azimuth angle and the lobe width of the covered sector from the clockwise starting point to the end point of the measured edge sampling point;
and finally, according to the longitude and latitude, the station height, the inclination angle, the azimuth angle and the transmitting power of the cell in the working parameters, sleeving a propagation model to calculate the actual coverage range of the cell.
Further, after step 103, the method according to the embodiment of the present invention may further include: and displaying the adjacent cell plan of the corresponding cell to a user according to the received adjacent cell plan output instruction of the at least one cell.
At this time, the user may select multiple or all cells to view the neighbor cell plan. Specifically, the cell selected by the user may be determined according to a group of cell names input by the user, all cells within an area selected through the GIS, or filtering the cells according to a BSC (Base station controller), a Base station, a planning zone, a division company, and the like.
In addition, when the adjacent cell plan of the corresponding cell is displayed to the user, the adjacent cell plan can be displayed according to the preset display rule. Some preset display rules are illustrated below:
the type of the neighbor cell to be selected can be preset, that is, the planning result includes the neighbor cell configuration conforming to the characteristics of the neighbor cell to be selected. The optional adjacent area can comprise: co-sited cells, close-range covered cells, designated specific cells, etc.
The calculation formula of the priority degree of the adjacent cell selection can be preset.
The upper limit of the number of the adjacent regions can be preset.
The calculation scenario may be preset and stored. The initial calculation scenario may be as follows: outdoor scenes, indoor scenes, key road scenes, and the like.
Furthermore, the adjacent cell relation of the cell can be rendered through the GIS during output, and is obviously distinguished through color, size and connecting lines, and the map can be compatible with search engine presentation, satellite map presentation and the like. When the result is output, the result can be output in a form, and the form information at least comprises: the name and identification of the serving cell (i.e., the primary cell), the name and identification of the neighbor cell, the distance, the priority, the reason for addition (e.g., the candidate-co-sited cell, priority ranking), etc.
In summary, the method for planning the neighboring cells in the embodiment of the invention comprehensively supports three-network multi-dimensional depth fusion analysis, and combines multi-dimensional data to perform scientific modeling, thereby realizing mutual verification and supplement between data and improving the accuracy of planning; comprehensive data analysis based on adjustable grid granularity is realized in the industry through cell rasterization, the relationship between cells is modeled in grid dimension, and a good automatic analysis basis is provided for adjacent cell planning and optimization; and the compatibility of adjacent region planning and optimization is realized through a genetic algorithm analysis mode.
According to the method for planning the adjacent regions, the support data comprise frequency sweep and MR, wherein the frequency sweep supports 2/3/4G frequency sweep data of a mainstream frequency sweep instrument manufacturer, and the MR data supports interface data of 2/3/4G mainstream equipment; the MR and the sweep frequency data are utilized to collect the level relation among all cells of the current position point, and an interference matrix is constructed based on the level relation, so that the method is closer to the actual situation of the existing network compared with the pure engineering parameter simulation prediction; and aiming at the finally generated multi-dimensional interference matrix, and combining with a user-defined neighbor cell setting rule, giving an optimal neighbor cell configuration suggestion, so that the distributed neighbor cells can be applied to the existing network, and the optimization efficiency is improved. The method not only solves the problems of poor normalization and lower accuracy of neighbor cell planning optimization caused by the increasingly huge network scale, but also improves the efficiency of the whole network neighbor cell planning optimization, and truly realizes scientific and accurate analysis of the neighbor cell planning optimization.
As shown in fig. 2, an embodiment of the present invention further provides a device for planning a neighboring cell, including:
the acquisition module is used for acquiring preset multi-dimensional data information of each cell in a preset area range;
the building module is used for building a multi-dimensional interference matrix between each cell and the corresponding history adjacent interval according to the multi-dimensional data information;
and the planning module is used for planning the corresponding adjacent cell for each cell according to the multi-dimensional interference matrix and the preset rule parameters.
The device for planning the adjacent cells performs optimization analysis on the planning of the adjacent cells based on the multidimensional data, achieves the purposes of comprehensive range and clear key points, realizes mutual verification and supplement among the data, and improves the accuracy of planning; accurate automatic analysis of neighbor planning optimization is realized, manpower and material resources are saved, and working efficiency is improved; the problems that the existing manual planning method is single in dimension, insufficient in accuracy, large in manpower and material resource consumption, low in efficiency, and one-sided and passive in neighbor cell planning are solved.
Preferably, the obtaining module may include:
the first acquisition unit is used for acquiring basic data, measurement report MR data, frequency sweep data and telephone traffic data of each cell in a preset area range, wherein the basic data comprises work parameter configuration data, switching data and historical neighbor relation data.
Preferably, the building block may include:
the rasterization unit is used for dividing the preset area by adopting grids with preset sizes and converging the multi-dimensional data information belonging to different network systems in each grid;
the first construction unit is used for constructing an MR interference matrix, a frequency sweeping interference matrix and an engineering parameter configuration interference matrix of each cell and a corresponding history adjacent interval under different network systems according to the multi-dimensional data information subjected to the convergence processing;
and the second fusion unit is used for performing weighted fusion on the MR interference matrix, the frequency sweep interference matrix and the engineering parameter configuration interference matrix to obtain a first fusion interference matrix.
Preferably, the first building unit may include:
the first acquisition subunit is used for acquiring MR level parameters of MR level types corresponding to different network systems of each cell and the corresponding historical neighbor cell in the MR data subjected to the convergence processing, and acquiring a first correlation between each cell and the corresponding historical neighbor cell according to the MR level parameters;
the first constructing subunit is used for constructing an MR interference matrix between each cell and the corresponding history adjacent interval according to the first correlation;
the second acquisition subunit is used for acquiring sweep frequency level parameters of sweep frequency level types corresponding to different network systems of each cell and the corresponding historical neighboring cells in the sweep frequency data subjected to the convergence processing, and acquiring second relativity between each cell and the corresponding historical neighboring cells according to the sweep frequency level parameters;
the second constructing subunit is used for constructing a frequency sweeping interference matrix between each cell and the corresponding history adjacent interval according to the second correlation;
a third obtaining subunit, configured to obtain, according to the aggregated working parameter configuration data, an ideal coverage range of each cell and a corresponding historical neighboring cell in a configuration structure of different network systems, and obtain, according to the ideal coverage range, a third correlation between each cell and the corresponding historical neighboring cell;
and the third constructing subunit is used for constructing the engineering parameter configuration interference matrix between each cell and the corresponding history adjacent interval according to the third correlation.
Preferably, the building module may further include:
the second construction unit is used for constructing a switching interference matrix of each cell and the corresponding historical adjacent interval under different network systems according to the switching data subjected to the convergence processing;
and the second fusion unit is used for performing weighted fusion on the switching interference matrix and the first fusion interference matrix to obtain a second fusion interference matrix.
Preferably, the apparatus may further include:
and the weighting module is used for respectively carrying out telephone traffic weighting on the MR interference matrix, the frequency sweep interference matrix and the engineering parameter configuration interference matrix according to the telephone traffic data subjected to the convergence processing.
Preferably, the apparatus may further include:
the abandoning module is used for abandoning the data with incomplete frequency sweep, the data lacking latitude and longitude and the data with the level value lower than the preset threshold value;
and the second acquisition module is used for acquiring the average value of the level data belonging to the same longitude and latitude in the MR data and the sweep frequency data.
Preferably, the planning module may include:
the second acquisition unit is used for acquiring the actual coverage area of each cell according to the working parameter configuration data;
and the planning unit is used for planning the corresponding adjacent cell for each cell by adopting a genetic algorithm according to the multi-dimensional interference matrix, the preset rule parameters and the actual coverage range of each cell.
The device for planning the adjacent cells comprehensively supports three-network multi-dimensional depth fusion analysis, and carries out scientific modeling by combining multi-dimensional data, thereby realizing mutual verification and supplement among the data and improving the accuracy of planning; comprehensive data analysis based on adjustable grid granularity is realized in the industry through cell rasterization, the relationship between cells is modeled in grid dimension, and a good automatic analysis basis is provided for adjacent cell planning and optimization; and the compatibility of adjacent region planning and optimization is realized through a genetic algorithm analysis mode.
The device for planning the adjacent regions comprises support data including frequency sweep and MR, wherein the frequency sweep supports 2/3/4G frequency sweep data of a mainstream frequency sweep instrument manufacturer, and the MR data supports interface data of 2/3/4G mainstream equipment; the MR and the sweep frequency data are utilized to collect the level relation among all cells of the current position point, and an interference matrix is constructed based on the level relation, so that the method is closer to the actual situation of the existing network compared with the pure engineering parameter simulation prediction; and aiming at the finally generated multi-dimensional interference matrix, and combining with a user-defined neighbor cell setting rule, giving an optimal neighbor cell configuration suggestion, so that the distributed neighbor cells can be applied to the existing network, and the optimization efficiency is improved. The method not only solves the problems of poor normalization and lower accuracy of neighbor cell planning optimization caused by the increasingly huge network scale, but also improves the efficiency of the whole network neighbor cell planning optimization, and truly realizes scientific and accurate analysis of the neighbor cell planning optimization.
It should be noted that the apparatus for planning a neighboring cell is an apparatus corresponding to the method for planning a neighboring cell, where all implementation manners in the method embodiment are applicable to the embodiment of the apparatus, and the same technical effect can be achieved.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (7)
1. A method for planning a neighboring cell, comprising:
acquiring preset multi-dimensional data information of each cell in a preset area range;
constructing a multi-dimensional interference matrix between each cell and a corresponding history adjacent interval according to the multi-dimensional data information;
planning a corresponding adjacent cell for each cell according to the multi-dimensional interference matrix and preset rule parameters;
the step of obtaining the preset multidimensional data information of each cell in the predetermined area range comprises:
acquiring basic data, measurement report MR data, sweep frequency data and telephone traffic data of each cell in a predetermined area range, wherein the basic data comprises work parameter configuration data, switching data and historical neighbor relation data;
the step of constructing the multi-dimensional interference matrix between each cell and the corresponding history adjacent interval according to the multi-dimensional data information comprises the following steps:
adopting grids with preset sizes to divide the preset area, and carrying out convergence processing on multi-dimensional data information belonging to different network systems in each grid;
according to the gathered multidimensional data information, constructing an MR interference matrix, a frequency sweeping interference matrix and an engineering parameter configuration interference matrix of each cell and a corresponding history adjacent interval under different network systems;
performing weighted fusion on the MR interference matrix, the sweep frequency interference matrix and the engineering parameter configuration interference matrix to obtain a first fusion interference matrix;
according to the switching data subjected to the convergence processing, a switching interference matrix of each cell and the corresponding history adjacent interval under different network systems is constructed;
performing weighted fusion on the switching interference matrix and the first fusion interference matrix to obtain a second fusion interference matrix;
wherein, constructing the engineering parameter configuration matrix comprises:
acquiring an ideal coverage range of each cell and a corresponding historical neighboring cell under configuration structures of different network systems according to the work parameter configuration data subjected to the aggregation processing, acquiring a third correlation between each cell and the corresponding historical neighboring cell according to the ideal coverage range, and constructing a work parameter configuration interference matrix between each cell and the corresponding historical neighboring cell according to the third correlation;
the third correlation is obtained by: acquiring the coverage overlapping area CF of a main cell s and a history adjacent cell isiAnd obtaining the ideal coverage area CF of the main cell ssallObtaining a third correlation GCF between the main cell s and the historical neighbor cell i by the following formularsi：
GCFrsi＝CFsiCFsall*100％。
2. The method as claimed in claim 1, wherein the step of constructing the MR interference matrix and the swept interference matrix between each cell and the corresponding history neighbor under different network standards according to the aggregated multidimensional data information comprises:
acquiring MR level parameters of MR level types corresponding to different network systems of each cell and corresponding historical adjacent cells in the MR data subjected to the convergence processing, and acquiring first correlation between each cell and corresponding historical adjacent cells according to the MR level parameters;
constructing an MR interference matrix between each cell and the corresponding history adjacent interval according to the first correlation;
acquiring sweep frequency level parameters of sweep frequency level types corresponding to different network systems of each cell and corresponding historical adjacent cells from the collected sweep frequency data, and acquiring second relativity between each cell and corresponding historical adjacent cells according to the sweep frequency level parameters;
and constructing a frequency sweeping interference matrix of each cell and the corresponding history adjacent interval according to the second correlation.
3. The method of claim 1, wherein before the weighted fusion of the MR interference matrix, the swept frequency interference matrix, and the engineering parameter configuration interference matrix to obtain a first fused interference matrix, the method further comprises:
and respectively carrying out telephone traffic weighting on the MR interference matrix, the frequency sweep interference matrix and the engineering parameter configuration interference matrix according to the telephone traffic data subjected to the convergence processing.
4. The method of claim 1, wherein before the constructing the multi-dimensional interference matrix between each cell and the corresponding historical neighbor according to the multi-dimensional data information, the method further comprises:
abandoning the data with incomplete sweep frequency, the data lacking longitude and latitude and the data with the level value lower than a preset threshold;
and acquiring the average value of the level data belonging to the same longitude and latitude in the MR data and the sweep frequency data.
5. The method of claim 1, wherein the step of planning a corresponding neighbor cell for each cell according to the multidimensional interference matrix and preset rule parameters comprises:
acquiring the actual coverage area of each cell according to the work parameter configuration data;
and planning a corresponding adjacent cell for each cell by adopting a genetic algorithm according to the multi-dimensional interference matrix, the preset rule parameters and the actual coverage range of each cell.
6. An apparatus for neighbor cell planning, comprising:
the acquisition module is used for acquiring preset multi-dimensional data information of each cell in a preset area range;
the building module is used for building a multi-dimensional interference matrix between each cell and the corresponding history adjacent interval according to the multi-dimensional data information;
the planning module is used for planning a corresponding adjacent cell for each cell according to the multi-dimensional interference matrix and preset rule parameters;
the acquisition module includes:
the system comprises a first acquisition unit, a second acquisition unit and a third acquisition unit, wherein the first acquisition unit is used for acquiring basic data, measurement report MR data, sweep frequency data and telephone traffic data of each cell in a preset area range, and the basic data comprises work parameter configuration data, switching data and historical neighbor relation data;
the building module comprises:
the rasterization unit is used for dividing the preset area by adopting grids with preset sizes and converging the multi-dimensional data information belonging to different network systems in each grid;
the first construction unit is used for constructing an MR interference matrix, a frequency sweeping interference matrix and an engineering parameter configuration interference matrix of each cell and a corresponding history adjacent interval under different network systems according to the multi-dimensional data information subjected to the convergence processing;
the second fusion unit is used for performing weighted fusion on the MR interference matrix, the frequency sweep interference matrix and the engineering parameter configuration interference matrix to obtain a first fusion interference matrix;
the building module further comprises:
the second construction unit is used for constructing a switching interference matrix of each cell and the corresponding historical adjacent interval under different network systems according to the switching data subjected to the convergence processing;
the second fusion unit is used for performing weighted fusion on the switching interference matrix and the first fusion interference matrix to obtain a second fusion interference matrix;
wherein, constructing the engineering parameter configuration matrix comprises:
acquiring an ideal coverage range of each cell and a corresponding historical neighboring cell under configuration structures of different network systems according to the work parameter configuration data subjected to the aggregation processing, acquiring a third correlation between each cell and the corresponding historical neighboring cell according to the ideal coverage range, and constructing a work parameter configuration interference matrix between each cell and the corresponding historical neighboring cell according to the third correlation;
the third correlation is obtained by: acquiring the coverage overlapping area CF of a main cell s and a history adjacent cell isiAnd obtaining the ideal coverage area CF of the main cell ssallObtaining a third correlation GCF between the main cell s and the historical neighbor cell i by the following formularsi：
GCFrsi＝CFsi/CFsall*100％。
7. The apparatus of claim 6, wherein the planning module comprises:
the second acquisition unit is used for acquiring the actual coverage area of each cell according to the working parameter configuration data;
and the planning unit is used for planning the corresponding adjacent cell for each cell by adopting a genetic algorithm according to the multi-dimensional interference matrix, the preset rule parameters and the actual coverage range of each cell.
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| CN108156611A (en) * | 2018-03-23 | 2018-06-12 | 上海东洲罗顿通信股份有限公司 | A kind of new PCI planning and the method for coverage optimization |
| CN110809296B (en) * | 2018-08-06 | 2021-09-28 | 中国移动通信集团设计院有限公司 | eSRVCC adjacent cell and 2G measurement frequency point configuration method and device |
| CN112989124B (en) * | 2019-12-02 | 2023-04-07 | 中国移动通信集团浙江有限公司 | Multi-network linkage data collaborative configuration method and device, computing equipment and storage medium |
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