CN108632832B - Network coverage analysis method and system - Google Patents

Network coverage analysis method and system Download PDF

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CN108632832B
CN108632832B CN201710177553.8A CN201710177553A CN108632832B CN 108632832 B CN108632832 B CN 108632832B CN 201710177553 A CN201710177553 A CN 201710177553A CN 108632832 B CN108632832 B CN 108632832B
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coverage
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CN108632832A (en
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黄剑锋
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Ultrapower Software Co ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/18—Network planning tools
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
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Abstract

The embodiment of the application discloses a network coverage analysis method and a system, which collect a plurality of items of original data from a target communication network, calculate the coverage correlation coefficient between every two cells in the target communication network respectively aiming at each item of original data to form a coverage correlation matrix corresponding to the item of original data, then perform fusion processing on the coverage correlation matrix corresponding to each item of original data to obtain a fusion coverage correlation matrix, and perform coverage analysis on the target communication network according to the fusion coverage correlation matrix. The embodiment of the application can get rid of the dependence on manual operation in the coverage analysis process, and realize automatic data acquisition, automatic data processing, automatic coverage problem analysis and the like, so that the whole coverage problem analysis process is more standardized and has higher efficiency; according to the embodiment of the application, deeper and more complete coverage analysis of the target communication network can be realized, the coverage problem can be more accurately positioned, the solution can be determined, and the optimization effect can be improved.

Description

Network coverage analysis method and system
Technical Field
The present application relates to the field of mobile communications technologies, and in particular, to a network coverage analysis method and system.
Background
In the daily optimization process of mobile communication networks of various systems, analysis and optimization of network coverage problems are one of critical operations, including initial coverage planning of the mobile communication network in a target cell, analysis of actual coverage conditions after delivery, operation and maintenance, problem processing and the like. The reasonable and deep signal coverage is the premise of ensuring that the mobile communication network has high connectivity, high retentivity, high handover switching power and low call drop rate, and is the key for ensuring the user experience.
In the initial planning stage, the existing network coverage analysis technology is mainly based on general data analysis software (such as mapInfo) or a private tool provided by a wireless manufacturer to perform manual planning; in the network operation and maintenance stage, problems (such as over coverage, weak coverage and the like) are found mainly by means of various background indexes (such as level strength, antenna pitch angle, adjacent cell relation and the like), then the problems are manually analyzed and positioned by maintenance personnel, then the antenna angle is adjusted on site by engineering maintenance personnel, and whether the coverage problem is solved is tested and verified by ground testing personnel.
Therefore, in the prior art, too many manual operations are relied on to realize network coverage analysis and optimization, the normalization is poor, the efficiency is low, and the analyzed data volume is limited, so that the analysis and optimization results are likely to be one-sided, and the problem that the one-step solution is difficult to achieve in the actual implementation process is solved.
Disclosure of Invention
The embodiment of the application provides a network coverage analysis method and a network coverage analysis system, and aims to solve the problems that in the prior art, network coverage analysis and optimization are realized by relying on manual operation too much, the normative is poor, the efficiency is low, and the analysis and optimization results are one-sided.
In a first aspect, an embodiment of the present application provides a network coverage analysis method, which includes:
collecting a plurality of items of original data of a target communication network consisting of N cells; the original data is data representing the operation condition of the target communication network;
respectively calculating any two CELLs CELL in the target communication network according to each original dataiAnd CELLjC of the coverage betweeni,jAnd using the coverage correlation coefficient Ci,jForming a coverage correlation matrix for the matrix elements;
performing fusion processing on each coverage correlation matrix to obtain a fusion coverage correlation matrix;
performing coverage analysis on the target communication network according to one or more elements in the fusion coverage correlation matrix;
wherein the coverage correlation coefficient Ci,jRepresenting two CELLs CELLiAnd CELLjThe coverage overlap degree between the N and the N is an integer not less than 1; 1,2, N, j 1, 2.
Optionally, the calculating a coverage correlation coefficient between any two cells in the target communication network according to each item of raw data includes:
for each item of original data, according to the preset factor number in the original dataCalculating two CELLs CELL in the target communication network according to the preset nonlinear mapping relation between the two CELLsiAnd CELLjC of the coverage betweeni,j；
The preset factor data includes: CELLiOverlaid grid set GiCELL, CELLiIn the grid set GiThe kth grid gi,kNumber M of internally collected sampling pointsi(gi,k) CELL, CELLiAt the grid gi,kStrength of received level P ini(gi,k) And CELLjAt the grid gi,kStrength of received level P inj(gi,k)。
Optionally, performing fusion processing on each coverage correlation matrix to obtain a fusion coverage correlation matrix, including:
determining a preset weight corresponding to each coverage correlation matrix;
and performing fusion calculation on each coverage correlation matrix according to the preset weight to obtain a fusion coverage correlation matrix.
Optionally, performing coverage analysis on the target communication network according to one or more elements in the fusion coverage correlation matrix, including:
respectively judging whether each fusion coverage correlation coefficient in the fusion coverage correlation matrix is not less than a preset attention threshold CCO-th；
Determining that the current value is not less than a preset attention threshold CCO-thEach of the fused coverage correlation coefficients
Figure GDA0003129562640000021
Corresponding two CELLs CELLiAnd CELLjInter-station distance dij；
When the station spacing dijGreater than CELLiCorresponding maximum coverage distance
Figure GDA0003129562640000022
Then, the CELL is determinediThere is an over-coverage problem.
Optionally, performing coverage analysis on the target communication network according to one or more elements in the fusion coverage correlation matrix, further includes:
for the same CELL CELLiComparing the current value with the preset attention threshold CCO-thEach of the fused coverage correlation coefficients
Figure GDA0003129562640000023
Corresponding inter-station distance dijDetermining the CELL CELLiCorresponding maximum inter-station distance
Figure GDA0003129562640000024
When the maximum inter-station distance
Figure GDA0003129562640000025
CELL less than serving CELLiCorresponding minimum coverage distance
Figure GDA0003129562640000026
Then, the CELL is determinediThere is a problem of insufficient coverage.
Optionally, the raw data includes at least one of the following data output by a data interface of a network operator:
measuring report MR data, switching data, drive test data, sweep frequency data, neighbor data, alarm data acquisition and telephone traffic data;
the raw data further includes: and simulating the target communication network according to a preset wireless propagation model to obtain simulation data.
Optionally, the method further includes, before calculating the coverage correlation coefficient, performing at least one of the following preprocessing operations on the raw data: data validity verification, data cleaning and data aggregation and arrangement.
Optionally, the method further includes: and formatting the original data subjected to the preprocessing operation, and removing illegal data in the original data.
Optionally, the method further includes:
after the fusion coverage correlation matrix is obtained, the original data are collected again, and when the difference degree between the collected original data and the collected original data at the previous time exceeds a preset degree, the fusion coverage correlation matrix is updated according to the collected original data;
and/or, after a data updating instruction is received, the original data are collected again, and the fusion coverage correlation matrix is updated according to the collected original data.
In a second aspect, an embodiment of the present application further provides a network coverage analysis system, which includes: the system comprises a data acquisition system and a background analysis system;
the data acquisition system is used for acquiring a plurality of items of original data of a target communication network consisting of N cells; the original data is data representing the operation condition of the target communication network;
the background analysis system at least comprises:
a multidimensional data analysis unit for calculating any two CELLs CELL in the target communication network according to each original dataiAnd CELLjC of the coverage betweeni,jAnd using the coverage correlation coefficient Ci,jForming a coverage correlation matrix for the matrix elements;
the fusion matrix construction unit is used for performing fusion processing on each coverage correlation matrix to obtain a fusion coverage correlation matrix;
a coverage analysis unit, configured to perform coverage analysis on the target communication network according to one or more elements in the converged coverage correlation matrix;
wherein the coverage correlation coefficient Ci,jRepresenting two CELLs CELLiAnd CELLjThe coverage overlap degree between the N and the N is an integer not less than 1; 1,2, N, j 1, 2.
Optionally, the multidimensional data analysis unit includes at least one of:
the measurement report matrix module is used for calculating the coverage correlation coefficient according to the collected measurement report data and forming a measurement report coverage correlation matrix;
the drive test matrix module is used for calculating the coverage correlation coefficient according to the collected road measurement data and forming a drive test coverage correlation matrix;
the sweep frequency matrix module is used for calculating the coverage correlation coefficient according to the collected sweep frequency measurement data and forming a sweep frequency coverage correlation matrix;
and the simulation matrix module is used for simulating the target communication network to obtain simulation data, calculating the coverage correlation coefficient according to the simulation data and forming a simulation coverage correlation matrix.
Optionally, the fusion matrix constructing unit is configured to:
and determining a preset weight corresponding to each coverage correlation matrix, and performing fusion calculation on each coverage correlation matrix according to the preset weight to obtain a fusion coverage correlation matrix.
Optionally, the coverage analysis unit includes:
the coverage problem analysis unit is used for analyzing and positioning the coverage problem of the target communication network according to one or more elements in the fusion coverage correlation matrix;
an overlay planning unit configured to generate an initial overlay planning scheme for the target communication network according to one or more elements in the converged overlay correlation matrix;
and the coverage optimization unit is used for generating a coverage optimization scheme for the target communication network according to one or more elements in the fusion coverage correlation matrix.
Optionally, the background analysis system further includes:
the fusion matrix updating unit is used for acquiring the original data again after the fusion coverage correlation matrix is obtained, and updating the fusion coverage correlation matrix according to the acquired original data when the difference degree between the acquired original data and the acquired original data at the previous time exceeds a preset degree;
and/or, after a data updating instruction is received, the original data are collected again, and the fusion coverage correlation matrix is updated according to the collected original data.
According to the technical scheme, the method comprises the steps of firstly collecting multiple items of original data from a target communication network, then calculating coverage correlation coefficients between every two cells in the target communication network according to the original data to form coverage correlation matrixes corresponding to the original data, then carrying out fusion processing on the coverage correlation matrixes corresponding to the original data to obtain a fusion coverage correlation matrix, and carrying out coverage analysis on the target communication network according to the fusion coverage correlation matrix. Compared with the prior art, the method and the device can get rid of dependence on manual operation in the coverage analysis process, realize automatic data acquisition, automatic data processing, automatic coverage problem analysis and the like, and enable the whole coverage problem analysis process to be more standardized and have higher efficiency; meanwhile, the embodiment collects a plurality of items of original data from the target communication network, and obtains the fusion coverage correlation matrix through matrix-based fusion calculation, and deeper and more complete coverage analysis of the target communication network can be realized according to the fusion coverage correlation matrix, so that the defect that the adjacent cells are difficult to be considered when manual analysis and positioning problems are solved in the prior art is overcome, the coverage problem existing in the target communication network can be more accurately positioned, the solution is determined, and the optimization effect of the mobile communication network can be further improved.
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In order to more clearly explain the technical solution of the present application, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious to those skilled in the art that other drawings can be obtained according to the drawings without any creative effort.
Fig. 1 is an overall architecture diagram of a network coverage analysis system provided in an embodiment of the present application;
fig. 2 is a flowchart of a network coverage analysis method according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of a network coverage analysis system according to an embodiment of the present application;
fig. 4 is another schematic structural diagram of a network coverage analysis system according to an embodiment of the present application.
Detailed Description
The network coverage analysis method and system provided by the embodiment of the application are explained below with reference to the accompanying drawings.
Fig. 1 is a schematic diagram of the overall architecture and application environment of the network coverage analysis system provided in this embodiment. Referring to fig. 1, the network coverage analysis system mainly includes: a data acquisition system 100 and a background analysis system 200; the data acquisition system 100 is connected to a data interface of a mobile communication network operator, and is configured to acquire various data generated during operations, maintenance, and the like of the mobile communication network, and the background analysis system 200 is configured to perform coverage analysis based on multidimensional data acquired by the data acquisition system.
In addition, the network coverage analysis system provided in this embodiment may further include: a system maintenance management platform 300 and a user control management platform 400; the system maintenance management platform 300 is configured to maintain the data acquisition system 100 and the background analysis system 200 to ensure normal operation thereof, and the user control management platform 400 is mainly configured to display, evaluate and manage a network coverage analysis result, a coverage problem solution, and the like obtained by the background analysis system 200.
Fig. 2 is a flowchart of a network coverage analysis method provided in an embodiment of the present application, where the method includes the following steps:
step S201, collecting multiple items of original data of a target communication network composed of N cells.
The target communication network represents an existing mobile communication network to be analyzed in the embodiment, or a mobile communication network to be established. The original data is data which is generated in the operation process of the target communication network and represents information such as the operation condition of the target communication network; each piece of raw data may include a plurality of attribute data of the target through the network, such as level strength, antenna pitch angle, and the like. The target communication network may be formed of one or more cells, i.e., N is an integer and N ≧ 1.
Corresponding to the coverage analysis system, the step S201 is performed by the data acquisition system 100, and the subsequent steps (including steps S202 to S204 described below) of processing the acquired data may be performed by the background analysis system 200.
Step S202, calculating any two CELLs CELL in the target communication network according to each original dataiAnd CELLjC of the coverage betweeni,jAnd using the coverage correlation coefficient Ci,jFor the matrix elements, an overlay correlation matrix is formed.
Wherein the coverage correlation coefficient Ci,jRepresents any two CELLs CELLiAnd CELLjThe coverage overlap degree between the two is set as Ci,j∈[0,1]1,2, N, j 1, 2. When i ═ j, Ci,j＝Ci,iRepresenting the coverage correlation coefficient of the cell and the cell, and according to the practical physical meaning, the cell and the cell are completely overlapped, so Ci,iThe value should be the maximum value, i.e. Ci,i1. Based on the coverage correlation coefficient Ci，jEach formed coverage correlation matrix is an N-order square matrix.
With 3 CELLs CELL1、CELL2And CELL3Taking the formed mobile communication network (i.e. N is 3) as an example, in step S202, the coverage correlation coefficients between each two of the 3 cells are respectively calculated according to any one of the original Data1 collected in step S201
Figure GDA0003129562640000051
To obtain the coverage correlation matrix C corresponding to the original Data11. According to the actual physical meaning, the following characteristics are found:
Figure GDA0003129562640000052
therefore, only need to calculate:
CELL1as a serving CELL, it is connected to a covering neighbor CELL CELL2Coefficient of coverage correlation between
Figure GDA0003129562640000053
And itCELL with another covering adjacent CELL3Coefficient of coverage correlation between
Figure GDA0003129562640000054
CELL2As a serving CELL, it is connected to a covering neighbor CELL CELL3Coefficient of coverage correlation between
Figure GDA0003129562640000055
And its CELL with another covering neighbor CELL1Coefficient of coverage correlation between
Figure GDA0003129562640000056
CELL3As a serving CELL, it is connected to a covering neighbor CELL CELL2Coefficient of coverage correlation between
Figure GDA0003129562640000061
And its CELL with another covering neighbor CELL2Coefficient of coverage correlation between
Figure GDA0003129562640000062
Based on the above calculation results, the coverage correlation matrix C corresponding to the original Data1 can be obtained1：
Figure GDA0003129562640000063
Based on the above calculation process, a coverage correlation matrix C corresponding to another original Data2 can also be calculated2And a coverage correlation matrix C corresponding to the other original Data33… …; that is, for each item of raw data, a coverage correlation matrix representing the degree of coverage between cells in the mobile communication network can be calculated.
And step S203, performing fusion processing on each coverage correlation matrix to obtain a fusion coverage correlation matrix.
Step S204, performing coverage analysis on the target communication network according to one or more elements in the fusion coverage correlation matrix.
A plurality of N-order coverage correlation matrixes obtained by calculation according to various original data are processed by a preset fusion algorithm (expressed as a function f in the following)s) Are fused into a matrix, i.e. the fused coverage correlation matrix CCO(ii) a Assuming that a total of X coverage correlation matrices are obtained, the fusion algorithm relation can be expressed as: cCO＝fs(C1,C2,...,CX). Through matrix fusion, a fusion coverage correlation matrix C is finally obtainedCONetwork operation and maintenance information contained in each item of original data is integrated, so that the relevant matrix C is covered according to the fusionCOEach matrix element carries out coverage analysis on the corresponding mobile communication network, the analysis degree can be ensured to be deeper, the coverage problem existing in the mobile communication network can be positioned more accurately, the solution can be determined, and the optimization effect on the mobile communication network can be further improved.
It can be seen from the foregoing technical solutions that, in the network coverage analysis method provided in the embodiments of the present application, multiple items of raw data are collected from a target communication network, then, coverage correlation coefficients between every two cells in the target communication network are calculated for each item of raw data, respectively, to form a coverage correlation matrix corresponding to the item of raw data, then, the coverage correlation matrices corresponding to each item of raw data are subjected to fusion processing, so as to obtain a fusion coverage correlation matrix, and coverage analysis is performed on the target communication network according to the fusion coverage correlation matrix. Compared with the prior art, the method and the device can get rid of dependence on manual operation in the coverage analysis process, realize automatic data acquisition, automatic data processing, automatic coverage problem analysis and the like, and enable the whole coverage problem analysis process to be more standardized and have higher efficiency; meanwhile, the embodiment collects a plurality of items of original data from the target communication network, and obtains the fusion coverage correlation matrix through matrix-based fusion calculation, and deeper and more complete coverage analysis of the target communication network can be realized according to the fusion coverage correlation matrix, so that the defect that the adjacent cells are difficult to be considered when manual analysis and positioning problems are solved in the prior art is overcome, the coverage problem existing in the target communication network can be more accurately positioned, the solution is determined, and the optimization effect of the mobile communication network can be further improved.
In one possible embodiment of the present application, the raw data collected in step S201 includes, but is not limited to: at least one of Measurement Report (MR) data, road test data (drive test data for short), road frequency sweep test data (frequency sweep data for short), neighbor data, traffic data, handover data, basic data, alarm data acquisition, and configuration data.
In this embodiment, the nine data items can be obtained from the multidimensional data interface of the target communication network by the data acquisition system 100 in the coverage analysis system shown in fig. 1.
In other possible embodiments of the present application, the raw data collected in step S201 may further include simulation data; the simulation data is simulation data generated by combining a specific wireless propagation model according to cell base station engineering parameters in a target communication network, so that simulation signal coverage data of each cell is generated. Based on the simulation data, the potential problem of the target communication network can be found in time, and the early warning of the coverage problem of the target communication network is realized, so that the target communication network is optimized in advance.
In a preferred embodiment of the present application, the measurement report data may be used as basic total coverage related data to ensure overall coverage, and then the measurement report data is fused with an interference matrix (i.e., a coverage related matrix) generated based on other raw data according to different requirements.
In another preferred embodiment of the present application, the simulation data can be used as basic total coverage related data to ensure overall coverage, and then the simulation data is fused with the interference matrix generated based on other raw data according to different requirements.
In another preferred embodiment of the present application, measurement report data and simulation data can be used as basic total coverage related data to ensure overall coverage, and simulation data can fill in data gaps; and on the basis, the interference matrix generated based on other original data is fused according to different requirements.
In this embodiment of the application, the step S202 of calculating the coverage correlation coefficient C between any two cells in the target communication websitei,jSpecifically, one or more data related to the cell coverage degree may be selected from each item of raw data, respectively, as preset factor data, and then the coverage correlation coefficient C may be calculated according to the nonlinear mapping relationship between the preset factor datai,j。
In a possible embodiment of the present application, the preset factor data may include: the number of covering grids of each of the two cells, the intensity of the received level in each grid, the number of sampling points and the like. In this embodiment, each cell in the target communication network is divided into a plurality of grids (e.g., square geographic grids of 25m × 25 m) with the same size in a grid form, and relevant data processing and calculation are performed with the grids as units, so as to implement deep and accurate analysis of the coverage condition of each cell.
For example, suppose CELLiServing CELL, and coverage neighbor CELLjC of the coverage betweeni,jFirst, the preset factor data to be determined specifically include: CELL of service CELLiAll grids g coveredi,k(wherein, Gi＝{gi,1,gi,2,...,gi,TT is CELLiTotal number of covered grids) set GiCELL, serving CELLiIn the grid set GiThe kth grid gi,kThe number M of sampling points acquired within (k ═ 1, 2.. times, T)i(gi,k) CELL, serving CELLiAt the grid gi,kStrength of received level P ini(gi,k) And covering the neighboring CELL CELLjAt the grid gi,kStrength of received level P inj(gi,k) (ii) a Then, calculating the CELL CELL according to the nonlinear mapping relation f of the preset factor dataiAnd its coverage neighbor CELLjThe coverage correlation coefficient between the two is represented by the following formula:
Ci,j＝f[Pi(gi,k),Pj(gi,k),Mi(gi,k),gi,k∈Gi]。
in the embodiment of the application, the preset factor data corresponding to different original data can be the same or different and is related to the data type contained in the original data; for the same group of preset factor data, different nonlinear mapping relations can be adopted to calculate the coverage relation coefficient between two cells, so as to obtain different coverage correlation matrixes, and the coverage correlation matrixes can be subjected to fusion processing through the step S203, so that the comprehensive, deep and comprehensive analysis of the target communication network is achieved.
In a possible embodiment of the present application, the step S203 of merging multiple coverage correlation matrices into one matrix may specifically adopt the following method:
s2031, determining a preset weight corresponding to each coverage correlation matrix;
s2032, fusion calculation is carried out on each coverage correlation matrix according to the preset weight to obtain a fusion coverage correlation matrix CCO。
The matrix fusion calculation process of this embodiment is described in detail below by taking the four original data items of measurement report data, drive test data, sweep frequency data, and simulation data, as examples.
Based on the measurement report data, in step S202, a corresponding measurement report coverage correlation matrix C can be obtainedMRIn step S2031, the preset weight corresponding thereto may be determined as βMR；
Based on the drive test data, a corresponding drive test coverage correlation matrix C can be obtained in step S202DTIn step S2031, it may be determined that the corresponding preset weight is βDT；
Based on the frequency sweep data, a corresponding frequency sweep coverage correlation matrix C can be obtained in step S202SCIn step S2031, it may be determined that the corresponding preset weight is βSC；
Based on the simulation data, a corresponding simulation coverage correlation matrix C can be obtained in step S202SIIn step S2031, it may be determined that the corresponding preset weight is βSI；
In step S2032, a final fusion coverage correlation matrix C is obtained by weighted summation of the coverage correlation matricesCOAs shown in the following formula: cCO＝βCOC。
In the above formula, betaCOA weight vector, i.e. beta, formed for each preset weightCO＝[βMR,βDT,βSC,βSI](ii) a C is a matrix vector composed of the respective coverage correlation matrices, i.e., C ═ CMR,CDT,CSC,CSI](ii) a For a target communication network formed by N cells, the four coverage correlation matrixes in the formula are all N-order square matrixes, so that the fusion coverage correlation matrix C obtained by the fusion calculationCOAlso an N-th order square matrix, and in view of this, the above formula can be further expanded as follows:
Figure GDA0003129562640000091
wherein the fusion covers the correlation matrix CCOAny one of the elements of
Figure GDA0003129562640000092
Can be expressed as:
Figure GDA0003129562640000093
wherein, i is 1,2, and N, j is 1, 2.
The above embodiment only takes four items of original data as an example, and describes the process and specific calculation formula of the fusion calculation of the coverage correlation matrix in the present application; in other embodiments of the present application, any number of coverage correlation matrices may be fused according to the above principle, and details are not described herein.
To facilitate coverage problem analysis, the control fusion coverage correlation matrix CCOIn (1)Each matrix element
Figure GDA0003129562640000094
In a possible embodiment of the present application, the range of each coverage correlation coefficient in each coverage correlation matrix is Ci,j∈[0,1]In addition, it may further be set that: the value range of the preset weight corresponding to each coverage correlation matrix is [0,1 ]]And the sum of the preset weights corresponding to all the coverage correlation matrixes is 1. Still taking the above four original data as an example, it can be set that: beta is aMR+βDT+βSC+βSI1. The setting of the value range of the preset weight ensures CCOEach matrix element in (1)
Figure GDA0003129562640000095
Namely ensure
Figure GDA0003129562640000096
The range value interval characteristic of (a) facilitates setting a threshold value (or threshold value) based on the limited value interval, and further based on the threshold value or threshold value, fusing each original in the coverage correlation matrix
Figure GDA0003129562640000097
The value size of (a) was used for coverage analysis.
In addition, in this embodiment, different coverage correlation matrices correspond to different types of raw data, so that the coverage problem under the influence of different factors can be highlighted by configuring and adjusting the weight corresponding to each coverage correlation matrix on the premise of ensuring the overall coverage.
For example: can be set as betaCO＝[βMR,βDT,βSC,βSI]＝[0.5,0.2,0.2,0.1](ii) a In this embodiment, the measurement report data and the simulation data are used as basic total coverage related data, which can be collected in each cell of the target communication network, so as to ensure the total coverage; on the basis, the method can highlight the emphasis by adding the special road-specific drive test data and the special road-specific frequency sweep dataAnalytical localization of road coverage problems.
In this embodiment of the present application, in step S204, according to one or more elements in the fusion coverage correlation matrix, a coverage problem existing in the target communication network can be obtained through analysis.
In one possible embodiment, the specific method for determining whether the target communication network has the problems of over coverage and under coverage may be:
s2041, determining fusion coverage correlation matrix CCOThe fusion coverage correlation coefficient in (1)
Figure GDA0003129562640000101
Is preset attention threshold CCO -th；
The value of the preset attention threshold can be adjusted according to the actual scene, and generally, C is more than or equal to 0CO-th≤0.1。
S2042, determining each service CELL CELLiCorresponding maximum coverage distance
Figure GDA0003129562640000102
And minimum coverage distance
Figure GDA0003129562640000103
S2043, respectively judging whether each fusion coverage correlation coefficient in the fusion coverage correlation matrix is not less than a preset attention threshold CCO-th；
Namely: traverse CCOEach element in (1)
Figure GDA0003129562640000104
Determine if there is
Figure GDA0003129562640000105
S2044, for the condition that the current attention is not less than the preset attention threshold CCO-thThe fusion coverage correlation coefficient of
Figure GDA0003129562640000106
Determining the corresponding CELL CELLiAnd covering the adjacent CELL CELLjInter-station distance dij；
For example, after the traversal judgment, it is determined that the following three values are not less than the preset attention threshold CCO-thThe fusion coverage correlation coefficient of (2):
Figure GDA0003129562640000107
and
Figure GDA0003129562640000108
(step S2043); further, it is necessary to determine the CELL CELL separately1And CELL2Inter-station distance d12CELL, CELL2And CELL3Inter-station distance d23And CELL2And CELL4Inter-station distance d24。
S2045, judging the inter-station distance dijWhether greater than CELL CELLiCorresponding maximum coverage distance
Figure GDA0003129562640000109
If yes, then the CELL CELL is judgediThere is an over-coverage problem;
if d is12Greater than CELL CELL1Maximum coverage distance of
Figure GDA0003129562640000111
Namely, it is
Figure GDA0003129562640000112
Then the CELL CELL can be judged1CELL covering its neighboring CELLs2There is an over-coverage problem.
Likewise, if d23Greater than CELL CELL2Maximum coverage distance of
Figure GDA0003129562640000113
Namely, it is
Figure GDA0003129562640000114
Then the CELL CELL can be judged2CELL covering its neighboring CELLs3There is an over-coverage problem; if it is not
Figure GDA0003129562640000115
Then the CELL CELL can be judged2CELL covering its neighboring CELLs4There is also an over-coverage problem.
S2046, CELL for the same CELLiComparing the current value with the preset attention threshold CCO-thEach of the fused coverage correlation coefficients
Figure GDA0003129562640000116
Corresponding inter-station distance dijDetermining the CELL CELLiCorresponding maximum inter-station distance
Figure GDA0003129562640000117
Due to the same CELL2Corresponding two fused overlay correlation coefficients
Figure GDA0003129562640000118
And
Figure GDA0003129562640000119
are not less than a preset attention threshold CCO-thSo that the corresponding two station spacings d are compared23And d24The maximum value of the above-mentioned components is
Figure GDA00031295626400001110
Suppose d23＞d24Then, then
Figure GDA00031295626400001111
S2047, judging the maximum station spacing
Figure GDA00031295626400001112
Whether it is less than CELLiCorresponding minimum coverage distance
Figure GDA00031295626400001113
If yes, then the CELL CELL is judgediThere is a problem of insufficient coverage.
If it is not
Figure GDA00031295626400001114
CELL less than serving CELL2Minimum coverage distance of
Figure GDA00031295626400001115
Namely, it is
Figure GDA00031295626400001116
The serving CELL can be determined2There is a problem of insufficient coverage.
As can be seen from the above steps and specific examples, according to the elements in the fusion coverage correlation matrix, the embodiment of the present application can determine whether the target communication network has the problem of over coverage or insufficient coverage, and can also specifically determine which cell has the problem of over coverage or insufficient coverage for which cell, thereby realizing accurate positioning of the coverage problem; compared with the mode that the problems need to be manually analyzed and positioned by maintenance personnel in the prior art, the method and the device can reduce the dependence on manual operation, avoid the problems of one-sided analysis, poor optimization effect and the like caused by human factors, improve the coverage analysis efficiency of the mobile communication network, and facilitate the one-step in-place coverage problem in the network. In the embodiment of the present application, in addition to the coverage problem analysis, coverage planning, coverage optimization, and the like can be performed on the target communication network according to the fusion coverage correlation matrix.
In a possible embodiment of the present application, the network coverage analysis method may further include:
before calculating the coverage adjacent coefficient between any two cells (step S202), preprocessing each item of collected original data, including data validity verification, data cleaning, data aggregation and arrangement and the like; optionally, the preprocessing operation may be specifically executed by the relevant modules in the data acquisition system 100 shown in fig. 1.
Optionally, the network coverage analysis method may further include: formatting the preprocessed original data, eliminating illegal data in the original data, and extracting key data in the illegal data; this step may be specifically performed by the relevant modules in the background analysis system 200 shown in fig. 1.
In an actual application scenario, the coverage condition of the target communication network may change in real time, so that in order to find the coverage problem of the target communication network in time, the real-time monitoring and coverage analysis of the target communication network can be realized by acquiring the original data for multiple times and updating the fusion coverage correlation matrix according to the newly acquired original data.
In one possible embodiment of the present application, whether updating is needed or not may be determined according to the degree of difference between the original data; specifically, after the fusion coverage correlation matrix is obtained, the original data is collected again, and when the difference degree between the collected original data and the collected original data of the previous time exceeds a preset degree, the fusion coverage correlation matrix is updated according to the collected original data.
In another possible embodiment of the present application, the updating may also be performed according to an updating instruction sent by the relevant control device; specifically, after a data updating instruction is received, the original data is collected again, and the fusion coverage correlation matrix is updated according to the collected original data.
In a possible embodiment of the present application, a Geographic Information System (Geographic Information System or Geo-Information System, GIS) may also be used to implement a Geographic presentation function of the target communication network, including but not limited to displaying an overall coverage effect map of the target coverage network, coverage problem points, and coverage scheme preview and coverage effect evaluation of the target coverage network.
Based on the network coverage problem analysis method, the embodiment of the application also provides a network coverage problem analysis system. Referring to the system architecture diagram shown in fig. 1 and the system structure diagram shown in fig. 3, the network coverage problem analysis system at least includes: a data acquisition system 100 and a background analysis system 200.
The data acquisition system 100 is configured to acquire multiple items of original data of a target communication network composed of N cells; the raw data is data characterizing the operation condition of the target communication network.
The background analysis system 200 at least comprises:
a multidimensional data analysis unit 210, configured to calculate any two CELLs CELL in the target communication network according to each original data respectivelyiAnd CELLjC of the coverage betweeni,jAnd using the coverage correlation coefficient Ci,jForming a coverage correlation matrix for the matrix elements;
a fusion matrix constructing unit 220, configured to perform fusion processing on each coverage correlation matrix to obtain a fusion coverage correlation matrix;
a coverage analysis unit 230, configured to perform coverage analysis on the target communication network according to one or more elements in the converged coverage correlation matrix.
Wherein the coverage correlation coefficient Ci,jRepresenting two CELLs CELLiAnd CELLjThe coverage overlap degree between the N and the N is an integer not less than 1; 1,2, N, j 1, 2.
Therefore, compared with the prior art, the method and the device can get rid of dependence on manual operation in the coverage analysis process, realize automatic data acquisition, automatic data processing, automatic coverage problem analysis and the like, and enable the whole coverage problem analysis process to be more standardized and have higher efficiency; meanwhile, the embodiment collects a plurality of items of original data from the target communication network, and obtains the fusion coverage correlation matrix through matrix-based fusion calculation, and deeper and more complete coverage analysis of the target communication network can be realized according to the fusion coverage correlation matrix, so that the defect that the adjacent cells are difficult to be considered when manual analysis and positioning problems are solved in the prior art is overcome, the coverage problem existing in the target communication network can be more accurately positioned, the solution is determined, and the optimization effect of the mobile communication network can be further improved.
Fig. 4 is a schematic diagram illustrating a specific structure of a network coverage analysis system according to a possible embodiment of the present application.
Referring to fig. 4, in an embodiment of the present application, the data acquisition system 100 may include: a multidimensional data acquisition unit, a data preprocessing unit 120 and a data return management unit 130.
The multidimensional data acquisition unit may include a plurality of data acquisition modules, which are respectively used for acquiring different types of raw data from a multidimensional data interface of a target communication network, including but not limited to a measurement report data acquisition module 111, a handover data acquisition module 112, a drive test data acquisition module 113, a traffic data acquisition module 114, a neighbor data acquisition module 115, a sweep data acquisition module 116, a basic data acquisition module 117, and the like shown in fig. 4.
The data preprocessing unit 120 is configured to preprocess each item of raw data acquired by the multidimensional data acquisition unit, including but not limited to: the device comprises a data verification module 121 for verifying the validity of the original data, a data cleaning module 122 for cleaning the original data, a data unloading module 123 and a data storage module 124.
The data return management unit 130 is configured to return the raw data preprocessed by the data preprocessing unit 120 to the background analysis system 200.
Still referring to fig. 4, in the embodiment of the present application, the multidimensional data analysis unit 210 in the background analysis unit 200 includes a plurality of coverage correlation matrix building modules, including but not limited to at least one of the following:
a measurement report matrix module 211, configured to calculate the coverage correlation coefficient according to the collected measurement report data, and form a measurement report coverage correlation matrix;
a drive test matrix module 212, configured to calculate the coverage correlation coefficient according to the collected road measurement data, and form a drive test coverage correlation matrix;
the sweep frequency matrix module 213 is configured to calculate the coverage correlation coefficient according to the collected sweep frequency measurement data, and form a sweep frequency coverage correlation matrix;
the simulation matrix module 214 is configured to simulate the target communication network to obtain simulation data, calculate the coverage correlation coefficient according to the simulation data, and form a simulation coverage correlation matrix;
and a switching matrix module 215, a neighbor matrix module 216, a traffic matrix module 217, and the like.
In a practical embodiment of the present application, the fusion matrix constructing unit 220 may be specifically configured to determine a preset weight corresponding to each coverage correlation matrix, and perform fusion calculation on each coverage correlation matrix according to the preset weight to obtain a fusion coverage correlation matrix. For a specific calculation method, reference may be made to the related description in the foregoing method embodiments, and details are not repeated here.
Still referring to fig. 4, in the embodiment of the present application, the coverage analysis unit 230 in the background analysis unit 200 includes:
a coverage problem analysis unit 231, configured to analyze a coverage problem of the target communication network, report a problem point, mark a problem area, or warn an area where a problem may occur according to one or more elements in the converged coverage correlation matrix;
a coverage planning unit 232, configured to generate an initial coverage planning scheme for the target communication network according to one or more elements in the fusion coverage correlation matrix, where the planning scheme specifically includes a cell position and antenna parameter planning suggestion for a coverage hole or a newly-built site;
a coverage optimization unit 233, configured to generate a coverage optimization scheme for the target communication network according to one or more elements in the fusion coverage correlation matrix, and also generate effect analysis before and after implementation of the coverage optimization scheme;
a solution management unit 234, configured to perform centralized management on analysis results obtained by the coverage problem analysis unit 231, the coverage planning unit 232, and the coverage optimization unit 233.
The coverage problem analysis unit 231 may be configured by referring to the coverage problem analysis method described in the foregoing method embodiment, and may accurately analyze and locate problems of over coverage, insufficient coverage, and the like in the target communication network.
Still referring to fig. 4, in the embodiment of the present application, the background analysis system 200 further includes: and a fusion matrix updating unit 240, configured to update the obtained fusion coverage correlation matrix.
In a possible embodiment, the fusion matrix updating unit 240 may re-acquire the original data after obtaining the fusion coverage related matrix, and update the fusion coverage related matrix according to the acquired original data when a difference degree between the acquired original data and the acquired original data at the previous time exceeds a preset degree.
In another possible embodiment, the fusion matrix updating unit 240 may further re-collect the original data after receiving the data updating instruction, and update the fusion coverage correlation matrix according to the re-collected original data.
In an actual application scenario, the coverage condition of the target communication network may change in real time, so that the embodiment updates the fusion coverage related matrix through the fusion matrix updating unit, so as to implement real-time monitoring and coverage analysis on the target communication network, and timely find the coverage problem occurring in the target communication network.
In this embodiment of the application, the background analysis system 200 further includes: a geographic presence service unit 250, configured to implement a geographic presence function of the target communication network by using the GIS; the geographic presentation function includes, but is not limited to, displaying an overall coverage effect graph of the target coverage network, covering problem points, and previewing and evaluating coverage effect of the coverage scheme of the target coverage network.
Still referring to fig. 4, the network coverage analysis system provided in the embodiment of the present application may further include:
the system maintenance management platform 300 is used for maintaining the data acquisition system 100 and the background analysis system 200 and ensuring the normal operation of the data acquisition system and the background analysis system;
and the user control management platform 400 is configured to supervise the data acquisition system 100 and the background analysis system 200, and display, evaluate, manage, and the like network coverage analysis results, coverage problem solutions, and the like obtained by the background analysis system 200. For example, the user control management platform 400 may send a data update instruction to the background analysis system 200, so that the fusion matrix updating unit 240 updates the fusion coverage correlation matrix according to the data update instruction.
In specific implementation, the present invention further provides a computer storage medium, where the computer storage medium may store a program, and the program may include some or all of the steps in each embodiment of the network coverage analysis method provided in the present invention when executed. The storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM) or a Random Access Memory (RAM).
Those skilled in the art will readily appreciate that the techniques of the embodiments of the present invention may be implemented as software plus a required general purpose hardware platform. Based on such understanding, the technical solutions in the embodiments of the present invention may be essentially or partially implemented in the form of a software product, which may be stored in a storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method according to the embodiments or some parts of the embodiments.
The same and similar parts in the various embodiments in this specification may be referred to each other. Especially, for the embodiment of the network coverage system, since it is basically similar to the method embodiment, the description is simple, and the relevant points can be referred to the description in the method embodiment.
The above-described embodiments of the present invention should not be construed as limiting the scope of the present invention.

Claims (9)

1. A network coverage analysis method, comprising:
collecting a plurality of items of original data of a target communication network consisting of N cells; the original data is data representing the operation condition of the target communication network;
respectively calculating any two CELLs CELL in the target communication network according to each original dataiAnd CELLjC of the coverage betweeni,jAnd using the coverage correlation coefficient Ci,jForming a coverage correlation matrix for the matrix elements;
performing fusion processing on each coverage correlation matrix to obtain a fusion coverage correlation matrix;
performing coverage analysis on the target communication network according to one or more elements in the fusion coverage correlation matrix;
wherein the coverage correlation coefficient Ci,jRepresenting two CELLs CELLiAnd CELLjThe coverage overlap degree between the N and the N is an integer not less than 1; 1,2, N, j 1,2, N;
the calculating of the coverage correlation coefficient between any two cells in the target communication network according to each item of original data includes:
for each item of original data, calculating two CELLs CELL in a target communication network according to a preset nonlinear mapping relation between preset factor data in the original dataiAnd CELLjC of the coverage betweeni,j；
The preset factor data includes: CELLiOverlaid grid set GiCELL, CELLiIn the grid set GiThe kth grid gi,kNumber M of internally collected sampling pointsi(gi,k) CELL, CELLiAt the grid gi,kStrength of received level P ini(gi,k) And CELLjAt the grid gi,kStrength of received level P inj(gi,k)。
2. The method of claim 1, wherein performing coverage analysis on the target communication network according to one or more elements in the converged coverage correlation matrix comprises:
determining each of the fusion coverage correlation matrices separatelyWhether the fusion coverage correlation coefficient is not less than a preset attention threshold CCO-th；
Determining that the current value is not less than a preset attention threshold CCO-thEach of the fused coverage correlation coefficients
Figure FDA0003129562630000011
Corresponding two CELLs CELLiAnd CELLjInter-station distance dij；
When the station spacing dijGreater than CELLiCorresponding maximum coverage distance
Figure FDA0003129562630000012
Then, the CELL is determinediThere is an over-coverage problem;
for the same CELL CELLiComparing the current value with the preset attention threshold CCO-thEach of the fused coverage correlation coefficients
Figure FDA0003129562630000013
Corresponding inter-station distance dijDetermining the CELL CELLiCorresponding maximum inter-station distance
Figure FDA0003129562630000014
When the maximum inter-station distance
Figure FDA0003129562630000015
CELL less than serving CELLiCorresponding minimum coverage distance
Figure FDA0003129562630000016
Then, the CELL is determinediThere is a problem of insufficient coverage.
3. The method of any of claims 1 to 2, further comprising:
after the fusion coverage correlation matrix is obtained, the original data are collected again, and when the difference degree between the collected original data and the collected original data at the previous time exceeds a preset degree, the fusion coverage correlation matrix is updated according to the collected original data;
and/or, after a data updating instruction is received, the original data are collected again, and the fusion coverage correlation matrix is updated according to the collected original data.
4. The method according to any of claims 1 to 2, wherein the raw data comprises at least one of the following data output by a data interface of a network operator:
measuring report MR data, switching data, drive test data, sweep frequency data, neighbor data, alarm data acquisition and telephone traffic data;
the raw data further includes: and simulating the target communication network according to a preset wireless propagation model to obtain simulation data.
5. A network coverage analysis system, comprising: the system comprises a data acquisition system and a background analysis system;
the data acquisition system is used for acquiring a plurality of items of original data of a target communication network consisting of N cells; the original data is data representing the operation condition of the target communication network;
the background analysis system at least comprises:
a multidimensional data analysis unit for calculating any two CELLs CELL in the target communication network according to each original dataiAnd CELLjC of the coverage betweeni,jAnd using the coverage correlation coefficient Ci,jForming a coverage correlation matrix for the matrix elements;
the fusion matrix construction unit is used for performing fusion processing on each coverage correlation matrix to obtain a fusion coverage correlation matrix;
a coverage analysis unit, configured to perform coverage analysis on the target communication network according to one or more elements in the converged coverage correlation matrix;
wherein the coverage correlation coefficient Ci,jRepresenting two CELLs CELLiAnd CELLjThe coverage overlap degree between the N and the N is an integer not less than 1; 1,2, N, j 1,2, N;
the calculating of the coverage correlation coefficient between any two cells in the target communication network according to each item of original data includes:
for each item of original data, calculating two CELLs CELL in a target communication network according to a preset nonlinear mapping relation between preset factor data in the original dataiAnd CELLjC of the coverage betweeni,j；
The preset factor data includes: CELLiOverlaid grid set GiCELL, CELLiIn the grid set GiThe kth grid gi,kNumber M of internally collected sampling pointsi(gi,k) CELL, CELLiAt the grid gi,kStrength of received level P ini(gi,k) And CELLjAt the grid gi,kStrength of received level P inj(gi,k)。
6. The system of claim 5, wherein the multidimensional data analysis unit comprises at least one of:
the measurement report matrix module is used for calculating the coverage correlation coefficient according to the collected measurement report data and forming a measurement report coverage correlation matrix;
the drive test matrix module is used for calculating the coverage correlation coefficient according to the collected road measurement data and forming a drive test coverage correlation matrix;
the sweep frequency matrix module is used for calculating the coverage correlation coefficient according to the collected sweep frequency measurement data and forming a sweep frequency coverage correlation matrix;
and the simulation matrix module is used for simulating the target communication network to obtain simulation data, calculating the coverage correlation coefficient according to the simulation data and forming a simulation coverage correlation matrix.
7. The system of claim 5, wherein the fusion matrix construction unit is configured to:
and determining a preset weight corresponding to each coverage correlation matrix, and performing fusion calculation on each coverage correlation matrix according to the preset weight to obtain a fusion coverage correlation matrix.
8. The system of claim 5, wherein the coverage analysis unit comprises:
the coverage problem analysis unit is used for analyzing and positioning the coverage problem of the target communication network according to one or more elements in the fusion coverage correlation matrix;
an overlay planning unit configured to generate an initial overlay planning scheme for the target communication network according to one or more elements in the converged overlay correlation matrix;
and the coverage optimization unit is used for generating a coverage optimization scheme for the target communication network according to one or more elements in the fusion coverage correlation matrix.
9. The system of claim 5, wherein the background analysis system further comprises:
the fusion matrix updating unit is used for acquiring the original data again after the fusion coverage correlation matrix is obtained, and updating the fusion coverage correlation matrix according to the acquired original data when the difference degree between the acquired original data and the acquired original data at the previous time exceeds a preset degree;
and/or, after a data updating instruction is received, the original data are collected again, and the fusion coverage correlation matrix is updated according to the collected original data.
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CN109472075B (en) * 2018-10-30 2022-11-08 成都四方伟业软件股份有限公司 Base station performance analysis method and system
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CN113382436B (en) * 2020-03-09 2022-08-23 中国移动通信集团设计院有限公司 Inter-cell interference detection method and device
CN112203317B (en) * 2020-10-20 2022-04-08 中国联合网络通信集团有限公司 Network coverage analysis method and device

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102480742A (en) * 2010-11-25 2012-05-30 中国移动通信集团广东有限公司 Method and device for detecting overshooting of wireless network
CN102781020A (en) * 2011-05-10 2012-11-14 北京迪特卡得通信设备有限公司 Method and system for positioning area with obvious network structure problem
CN103796227A (en) * 2012-10-31 2014-05-14 中国电信股份有限公司 Method and system for performing wireless signal coverage analysis

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090023477A1 (en) * 2007-07-19 2009-01-22 Telefonaktiebolaget Lm Ericsson (Publ) Method and apparatus for reconfiguring a multi-sector base station
CN103384372B (en) * 2012-05-03 2016-08-10 华为技术有限公司 A kind of optimize network capacity and cover compromise method, Apparatus and system

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102480742A (en) * 2010-11-25 2012-05-30 中国移动通信集团广东有限公司 Method and device for detecting overshooting of wireless network
CN102781020A (en) * 2011-05-10 2012-11-14 北京迪特卡得通信设备有限公司 Method and system for positioning area with obvious network structure problem
CN103796227A (en) * 2012-10-31 2014-05-14 中国电信股份有限公司 Method and system for performing wireless signal coverage analysis

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
Evaluation of forward prediction scheduling in heterogeneous access networks;Farhan H. Mirani; Nadia Boukhatem;《2012 IEEE Wireless Communications and Networking Conference (WCNC)》;20120611;1811-1816 *
TD-LTE网络重叠覆盖分析;武海斌;《CNKI 计算机与网络》;20130926;64-67 *

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