Detailed Description
In order for those skilled in the art to better understand the technical solutions of the present disclosure, embodiments of the present disclosure will be described in further detail below with reference to the accompanying drawings.
It is to be understood that the specific embodiments and figures described herein are merely illustrative of the present disclosure, and are not limiting of the present disclosure.
It is to be understood that the various embodiments of the disclosure and features of the embodiments may be combined with one another without conflict.
It is to be understood that for convenience of description, only portions relevant to the present disclosure are shown in the drawings of the present disclosure, and portions irrelevant to the present disclosure are not shown in the drawings.
It is to be understood that each module and unit referred to in the embodiments of the present disclosure may correspond to only one physical structure, may be composed of a plurality of physical structures, or may be integrated into one physical structure.
It will be appreciated that, without conflict, the functions and steps noted in the flowcharts and block diagrams of this disclosure may occur out of the order noted in the figures.
It will be appreciated that in the flow charts and block diagrams of the present disclosure, architecture, functionality, and operation of possible implementations of systems, apparatuses, devices, methods according to various embodiments of the present disclosure are shown. Where each block in the flowchart or block diagrams may represent a module, unit, segment, or code, which comprises executable instructions for implementing the specified functions. Moreover, each block or combination of blocks in the block diagrams and flowchart illustrations can be implemented by hardware-based devices that perform the specified functions, or by combinations of hardware and computer instructions.
It will be appreciated that the modules and units referred to in the embodiments of the disclosure may be implemented in software or hardware, e.g., the modules and units may be located in a processor.
Example 1:
as shown in fig. 1, the present disclosure provides a method for predicting a fallback cell, the method comprising:
S1, acquiring a cell withdrawal pre-judging parameter, wherein the cell withdrawal pre-judging parameter comprises a cell resident user number, a cell complaint number and a cell neighbor configuration;
s2, prejudging and analyzing the service withdrawal cell according to the cell service withdrawal prejudging parameter, wherein the method comprises the following steps:
in response to the decrease in the number of cell-resident users being greater than a first threshold, determining the cell as a preliminary pre-appraisal serving cell,
Obtaining a pre-judging and pre-taking out influence weighted score of a pre-judging and pre-taking out serving cell according to the number of resident users of the cell, the number of complaints of the cell and the configuration of the cell neighbor cells;
And S3, according to the unworked influence weighted score, making an investigation treatment scheme of the preliminary prejudging unworked district.
In this embodiment, the service-withdrawal cell is pre-judged and analyzed by using the cell service-withdrawal pre-judging parameters, including preliminary pre-judging the service-withdrawal cell according to the amplitude reduction of the number of resident users of the cell, analyzing the influence of the service withdrawal of the cell according to the number of resident users of the cell, the number of complaints of the cell and the configuration of the neighboring cell, taking the influence of the service withdrawal of the preliminary pre-judging service-withdrawal cell as a pre-judging analysis result, and timely checking and processing the possible service withdrawal condition of the cell according to the pre-judging analysis result to realize the pre-judgment of the service withdrawal cell. The method can be applied to the out-of-service cell pre-judging device shown in fig. 2, wherein the device comprises a network monitoring module for executing step S1, an intelligent analysis module for executing step S2 and a checking processing module for executing step S3, and the intelligent analysis module comprises a preliminary pre-judging unit and an influence analysis unit.
In particular, the rapid development of 5G (fifth generation mobile communication technology, 5th Generation Mobile Communication Technology) networks, each new service puts higher demands on network quality, network reliability, and failure handling recovery time. In daily network maintenance and network optimization, cell out-of-service has great influence on network quality and user perception. For large cities, 5G networks typically have tens of thousands of cells, which can produce a significant number of 5G out-of-service/zero-service cells per day due to network failure, network regulation, etc.
In the present disclosure, the pre-service-judging cell includes 3 cases of cell failure exit service, cell zero service, and cell service greatly decreasing, and for convenience of description, the service-exiting/zero service cell is abbreviated as service-exiting cell. The complete service withdrawal of the cell is caused by no communication signal in the cell and incapability of carrying out normal signal receiving and transmitting, which is generally caused by transmission faults, carrier frequency faults, antenna feed faults, power failure or high temperature and the like, the zero service of the cell is caused by the fact that the cell has signals but cannot absorb service, the incomplete service withdrawal of the cell is possibly caused by the problems of wrong configuration of cell parameters, abnormal base station/cell software and the like, the great reduction of the cell service is caused by the fact that the performance of the cell equipment is reduced or the antenna feed system is caused by the fact that the service volume is greatly reduced, and the situation needs to timely contact operation and maintenance personnel for maintenance so as to ensure normal communication of users.
In view of this, the present embodiment provides a 5G network pre-judging and service cell analysis and investigation device, that is, a service cell pre-judging device, as shown in fig. 3, where "network monitoring module", "data management module", "intelligent analysis module" and "investigation processing module" are set by computer programming. Wherein:
The network monitoring module monitors and counts the index of the resident user number of the cell of the 5G cell from a 5G core network as an evaluation index of the service withdrawal/zero service cell, counts the service volume, neighbor cell configuration and the like of the 5G cell from a 5G wireless network manager, and can comprise cell wireless performance monitoring, base station and cell alarm monitoring and the like, counts the physical and chemical micro grid complaint quantity of the cell from a customer complaint platform, and provides the physical and chemical micro grid complaint quantity for an intelligent analysis module to weighted calculate the influence degree of each 5G pre-judging service withdrawal cell so as to carry out priority processing sequencing.
The data management module is used for storing and calling a database of related data, and can comprise storing and calling a whole network cell wireless ledger, a whole network neighbor cell configuration table, an on/expansion record, a station removal/cell closing record, wireless optimization data, a history service withdrawal processing record, an experience database and the like.
The intelligent analysis module realizes the pre-judging and backing-up service identification of the 5G cell, and comprises the analysis calculation and output of the pre-judging and backing-up service cell primary identification, the cell user quantity coefficient, the micro grid user complaint coefficient and the adjacent cell backing-up service coefficient, and finally the pre-judging and backing-up service cell weighted score calculation is performed by combining the coefficients.
And the 'check processing module' is used for carrying out priority processing sequencing, processing effect evaluation, historical fault processing record and experience database maintenance on the 5G pre-judging and backing serving cell.
More specifically, as shown in fig. 4, a reference and comparison cell out-of-service judging method is mainly used for judging whether a cell is a zero service cell by counting cell traffic, and further judging whether corresponding investigation processing is needed to recover services. The main flow comprises the following steps:
Step 1, statistically extracting network traffic data of 5 days (hereinafter referred to as the first 5 days) and yesterday from the previous day of the whole network 5G cell from each network manager.
And 2, comparing the service volumes of each 5G cell of the whole network in yesterday and the first 5 days, and judging that the service is newly added and withdrawn from the cell if the service exists in the first 5 days (each day) of the cell and the service is zero in yesterday.
And step 3, outputting a newly added and withdrawn serving cell list.
And step 4, filtering out the non-processed deserved cells according to the white list cell summary table. The method is characterized in that the method comprises the steps of dismantling, volume reduction and blocking of the observed descensus cell according to a network planning professional plan, namely a white list cell, and follow-up processing is not needed.
And 5, analyzing each out-of-service/zero-service cell. The reasons for the usual out-of-service/zero traffic generation are the following:
1) A cell failure;
2) Cell network management data configuration errors or network management data error deletion;
3) Cell radio optimization parameters/policy configuration errors;
For the problems, carrying out professional follow-up treatment on the related operations, construction and network optimization according to specific conditions.
In addition, the new finding meets the white list condition, and the follow-up out service/zero service cell is not needed, and the new finding is updated in the white list cell list.
And 6, carrying out professional follow-up service/zero service cell processing such as operation and maintenance, construction, network optimization and the like, and feeding back after finishing.
And 7, the network optimization profession follows up the service recovery condition of each service-quitting/zero-service cell, and if the service is recovered, the closed loop is realized.
And 9, continuously incorporating the non-closed-loop service-withdrawal/zero service cell into the long-term service-withdrawal/zero service cell list to follow up (marked as long-term service-withdrawal/zero service cell).
The statistical analysis and investigation method and flow of the 5G fallback/zero traffic cell as shown in fig. 4 have the following disadvantages:
1. the 5G service-exiting/zero-service cell analysis, investigation, processing, feedback and verification links are more, and the processing time is long.
2. Most links are manually processed, and report statistics and analysis require more time resources of network optimization engineers.
3. The database which can be directly called is lacking, the current and historical network data are required to be counted manually, and a report is generated for comparison and analysis.
4. The analysis process depends on the working experience of network optimization engineers, so that the factors needing to be analyzed and checked are more, a great deal of time and effort are needed, and the large-batch analysis and processing are difficult.
5. It is difficult to develop analysis and follow-up investigation with emphasis on rapid development according to real-time changes of the network.
6. After the service withdrawal/zero service cell is closed loop, the database tool recording processing process is lacked and the subsequent index tracking evaluation is carried out, so that an experience database cannot be effectively formed for subsequent network optimization and investigation reference when the service withdrawal/zero service cell repeatedly appears.
This embodiment addresses the shortcomings of the method shown in fig. 4, focusing on solving the following problems:
1. The method adopts the index of the maximum number of resident users of the cell (hereinafter referred to as the resident users of the cell) to replace the index of the traffic of the cell as the evaluation index of the service-withdrawal/zero-traffic cell, realizes the function of pre-judging the service-withdrawal cell through a computer program tool, and improves the processing timeliness (hereinafter referred to as the analysis processing of the pre-judging service-withdrawal cell).
2. And setting a network monitoring module, establishing connection with a platform/server related to a core network and a wireless network, directly acquiring statistical data, and performing summarization and screening treatment to obtain a 5G pre-judging and backing-off serving cell list.
3. And a database module is arranged to realize the real-time and historical data database storage of the wireless network and the core network for the rapid calling analysis of the subsequent analysis process.
4. And an intelligent analysis module is arranged to replace most of manual statistics, analysis, background investigation and effect evaluation works in the pre-judgment and investigation process of the serving cell.
5. The weighting algorithm of the pre-judging and backing-off serving cell weighting score is adopted, the wireless network practical experience is combined with a computer intelligent algorithm, the weighting score of the influence degree of each pre-judging and backing-off serving cell is calculated, the pre-judging and backing-off serving cell weighting score is ordered, the accurate investigation of the pre-judging and backing-off serving cell is guided, the investigation efficiency is greatly improved, and a large amount of labor and material cost is saved.
6. The data of the checking processing condition of the pre-judging and backing-off serving cell, the cell history/current/subsequent network index, user perception index and the like are recorded through a database to form an experience database for reference of subsequent network optimization and pre-judging and backing-off serving cell analysis processing.
In an embodiment, in step S1, the obtaining the cell outage prediction parameter specifically includes:
acquiring the number of cell resident users of yesterday and the previous N days before yesterday from a core network;
acquiring the physical and chemical micro grid complaint quantity of a community from a customer complaint platform;
and acquiring the cell antenna configuration, the neighbor cell of the cell and the service withdrawal information of the neighbor cell from the wireless network management equipment.
In this embodiment, the cell outage prediction parameter is one of important technical improvement points of the present disclosure. The network monitoring module establishes connection with related servers and platforms such as a core network, a wireless network, a customer complaint information platform and the like, and periodically acquires indexes such as the number of resident users of the cell and the like, thereby realizing the functions of network monitoring and data acquisition, namely acquiring 5G out-of-service cell pre-judging parameters.
The data management module is used for realizing the database management of network indexes and related data required by the device shown in fig. 3, so that other program modules (including a network monitoring module) can be called and analyzed immediately.
The data management module realizes the automatic storage and calling of network index statistics and related data, and comprises the following steps:
The statistics of the acquired data of the network monitoring module mainly comprises the number of resident users of a 5G cell, main wireless indexes of the cell, physical and chemical micro grid dotting quantity data of a user complaint place and the like, wherein the main wireless indexes of the cell refer to wireless common indexes such as cell traffic, wireless call completing rate, wireless switching success rate, wireless disconnection rate and the like, and are used for network optimization engineers to evaluate and reference the wireless quality of the cell;
The method is used for 5G pre-judging and backing out relevant data needed by cell analysis and subsequent optimization, such as 5G whole network cell wireless standing accounts, 5G whole network neighbor cell configuration tables, new station opening records, cell carrier frequency capacity expansion/reduction data records and the like.
Table 1 below is an example of statistics of the number of resident users of a cell obtained using the method as above:
table 1 example of statistics of number of resident users in a cell
In an embodiment, obtaining, from a wireless network management device, cell antenna configuration, a neighbor cell of a cell, and a service exit information of the neighbor cell, specifically includes:
acquiring the hanging height, the downward inclination angle and the vertical pattern beam width of the antenna of the cell from wireless network management equipment;
calculating the maximum coverage distance Dmax (m) =antenna hanging height×tan (90 degrees-antenna downtilt angle+antenna vertical pattern beam width ≡2) of the cell, wherein the maximum value of Dmax (m) is 1000m;
Acquiring longitude and latitude of each base station from wireless network management equipment, and acquiring neighbor base stations positioned within a distance of 1.2Dmax (m) of the cell according to longitude and latitude calculation;
And acquiring neighbor cells of the neighbor base stations towards the base station of the cell and the service withdrawal information of the neighbor cells from the wireless network management equipment.
In this embodiment, the "neighbor cell withdrawal coefficient" of the 5G pre-judgment withdrawal serving cell needs to be determined by analyzing which neighbor cells the cell has, and the method for determining the neighbor cells is shown in fig. 5, and the cell coverage distance Dmax (m) =antenna hanging height×tan (90-antenna downtilt+antenna vertical pattern beam width/2), where 90, antenna downtilt, antenna vertical pattern beam width in the formula are all "angles" according to the hanging height, downtilt, antenna vertical pattern beam width (3 dB) of the base station cell antenna.
When Dmax (m) >1000 meters, dmax (m) is valued at 1000 meters, so that the distance between 4G sites in Guangzhou urban areas and suburbs is basically within 1000 meters, and the overlapping coverage area between adjacent areas is usually small beyond 1000 meters. For special scenes, dmax (m) can be appropriately adjusted according to specific situations.
According to the distribution condition of Guangzhou 5G network cells, within the distance of 1.2Dmax (m) of the service-withdrawal cell, the first layer neighbor cells around the service-withdrawal cell are generally covered, namely neighbor cells with a certain overlapping coverage area and the closest relationship. For convenience of description, neighbor cells within a distance of 1.2Dmax (m) of the fallback cell are simply referred to as "neighbor cells".
As shown in fig. 6, a simple schematic diagram is shown, where the S1 cell of the base station a has a pre-fallback serving cell, and the neighbor cells within a distance of 1.2Dmax (m) around the base station a-S1 cell are "neighbor cells" (the gray-filled neighbor cells within the dashed line range in fig. 6). It is explained that fig. 6 is only a simple definition diagram, and the configuration of the neighbor cells of the actual network is much more complex.
In one embodiment, in step S2, in response to the decrease in the number of cell-resident users being greater than a first threshold, determining the cell as a preliminary pre-determined serving cell specifically includes:
calculating an average number of cell resident users in the previous N days before yesterday;
calculating the change proportion of the yesterday cell resident user number to the average number;
And determining the cell as a preliminary pre-judgment serving cell in response to the absolute value of the change proportion being greater than a first threshold.
In this embodiment, as shown in fig. 3, the pre-judgment analysis device for the 5G pre-judgment serving cell realizes analysis and output of the 5G pre-judgment serving cell through the intelligent analysis module, and is suitable for pre-judgment, analysis calculation and output of the 5G pre-judgment serving cell.
For example, a 5G pre-judgment exit service cell judgment standard is set, wherein the number of cell resident users in the previous 5 days is more than 10, and the reduction of the number of cell resident users in yesterday is more than or equal to 80%.
The method has the advantages that the amplitude reduction of the cell resident user number and the cell resident user number yesterday in the first 5 days can be adjusted according to actual needs, and 10 is a reference number of the cell resident user number and can be expressed by M.
The intelligent analysis module invokes various indexes of the whole network cell of the local 5G network from a database (data management module) shown in fig. 3, and outputs a 5G pre-judgment and withdrawal service cell list.
One example of an output 5G pre-appraisal serving cell is as follows:
and (3) calling the daily maximum resident user number statistical data of the cells from 24 days to 29 days of 7 months from the database, screening according to the 5G pre-judgment serving cell judgment standard, filtering according to the white list cell, and obtaining a preliminary list of the 5G pre-judgment serving cell needing follow-up processing as shown in the following table 2.
Table 2 preliminary 5G pre-appraisal of serving cell list example
In one embodiment, in step S2, the obtaining the pre-determined service impact weighted score of the service exit cell according to the number of resident users, the number of complaints and the configuration of neighboring cells specifically includes:
Acquiring a cell user number coefficient according to the cell resident user number;
acquiring a community user complaint coefficient according to the community complaint quantity;
Obtaining a cell neighbor cell service withdrawal coefficient according to cell neighbor cell configuration;
and obtaining the unworked influence weighted score of the preliminary prejudging unworked cell according to the cell user number coefficient, the cell user complaint coefficient and the cell neighbor unworked coefficient.
In this embodiment, three aspects of the number of resident users in a cell, the number of complaints in the cell and the configuration of neighboring cells are integrated, and the size of the influence possibly caused by the withdrawal of the cell is considered, so that the method is used as a scientific basis for judging the emergency degree of the withdrawal and check processing of the cell, and numerical conversion operation is performed on all the three aspects, so that the judgment by a computer program is facilitated.
In one embodiment, wherein:
the cell user number coefficient Tyh＝1+(TNyh÷M),TNyh is the average number of cell resident users in the first N days before a certain preliminary pre-judging and degrading serving cell yesterday, and M is a reference number of cell resident users;
The cell user complaint coefficient Kts＝1+(KNts÷N),KNts is the sum of the number of cell complaints of the previous N days before yesterday of a certain preliminary pre-judging and backing-off serving cell;
The neighbor cell service withdrawal coefficient Kn＝1+Ntf,Ntf is the number of service withdrawal cells in the neighbor cells of a certain preliminary pre-judgment service withdrawal cell;
the unwatched impact weighted score Sw＝Tyh×Kts×Kn.
In this embodiment, an example of the operation of calculating the cell outage influence weighted score is as follows:
1. analyzing and calculating the 'cell user quantity coefficient', 'micro grid user complaint coefficient' of the 5G pre-judging and backing-off serving cell:
In order to refine the local 5G network optimization work of Guangzhou and the processing of 5G pre-judging and backing out the serving cell, a geochemical micro-grid management mode is adopted, the Guangzhou area is divided into 30000 micro-grid areas by about 460 x 460 meters, and analysis is carried out by combining micro-grid user complaint dotting conditions. According to the longitude and latitude of the user complaint location, the user complaint can be dotted to the corresponding micro grid. The more the micro grid dotting complaint quantity is, the more the possible network quality problems in the micro grid are, the larger the influence on the user use perception is, and the wireless network fault investigation or network optimization of the relevant coverage cells of the micro grid is required to be carried out preferentially.
For example, as shown in FIG. 7, guangzhou-H-leaching teaches North relocation-8455845-2-1-ONR, and the micro grid is "Guangzhou sea ball area_6906" according to the longitude and latitude of the cell. Matching the micro-grids of each 5G pre-judging and backing-off serving cell, and counting the complaint dotting quantity in the latest 5-day micro-grid as shown in the following table 3:
Table 3 example of statistics of the number of cell physicochemical micro grid dotting complaints
According to the information of Table 3, the influence degree of the pre-judging and withdrawing service of the cell is analyzed according to the number of resident users of 5 balances in front of the cell and the total number of dotting complaints of users 5 days in front of the micro grid where the cell is located.
The larger the number of resident users in the cell, the larger the influence of the occurrence of the withdrawal of the cell on the network user is, so that the 'cell user number coefficient' Tyh is adopted for the subsequent calculation of the 'pre-judging withdrawal cell' weighting score.
Tyh defines the cell user number factor Tyh＝1+(T5yh/10).
Where T5yh is the average value of the number of residents 5 days before a cell, typically the number of residents in a cell may span a lot, and thus is divided by 10 to adjust in order to avoid excessive coefficient fluctuation.
Tyh calculation example:
Based on the statistical index of 7 months 24 to 7 months 28 days 5 days, the average number of resident users before 5 days of Guangzhou-H-leaching north moving-8455845-2-1-ONR district is 76, Tyh＝1+(T5yh/10) =1+ (76/10) =8.6;
the average number of resident users 5 days before Guangzhou-H-Haizhu Bu Linji-8456119-3-1-ONR cell was 134, Tyh＝1+(T5yh +.10) =1+ (134+.10) =14.4.
There may be 1 or more cells within a micro-grid, or there may be no cells within the micro-grid, with network coverage by cells located outside the micro-grid.
The more micro grid point complaints the cells are located, the worse the network quality (insufficient coverage or insufficient capacity) of the cells is reflected in general, and the larger the influence of the cell withdrawal on network users is, so that the micro grid user complaint coefficient Kts is increased for the subsequent calculation of the weighted score of the influence of the pre-judging withdrawal serving cell on the network.
Kts define a micro grid user complaint coefficient Kts＝1+(K5ts/5).
Wherein K5ts is the total number of micro grid dotting complaints of the cell in the day of 5, divided by 5 to obtain the number of micro grid dotting complaints of the cell in the day of 5.
Kts calculation example:
According to the statistical index of 24 days of 7 months to 28 days of 7 months and 5 days of 5 days before 5 days of micro grid dotting complaints of Guangzhou-H-leaching teaching north moving-8455845-2-1-ONR district,
Kts＝1+(K5ts÷5)=1+(5÷5)=2;
Micro grid dotting complaints 4 were 5 days before Guangzhou-H-sea pearl Bu Linji-8456119-3-1-ONR cell, Kts＝1+(K5ts/5) =1+ (4/5) =1.8.
2. Analyzing and determining the 'neighbor cell withdrawal coefficient' of the 5G pre-withdrawal service cell:
if there is a neighbor cell that is in the base station where the neighbor cell is located or within 1.2Dmax (m) of the periphery, the neighbor cell is taken out, which causes the larger network quality degradation of the cell, in this case, the "neighbor cell take out coefficient" Kn is increased for the subsequent calculation of the "pre-judgment take out cell" weighting score.
Kn defines the neighbor cell out-of-service coefficient Kn＝1+Ntf.
The description is that 1 in the above formula represents the present prejudgment and withdrawal service cell, and the number is 1. Ntf in the above formula is defined as the total number of the neighbor cells of the present pre-determined fallback serving cell.
Kn calculation example:
radio engineering parameters for Guangzhou-H-leaching North relocation-8455845-2-1-ONR cells are shown in Table 4 below:
table 4 engineering parameter examples of cells
Dmax (m) =antenna hanging height×tan (90-antenna downtilt+antenna vertical pattern beamwidth +.2) =21×tan (90-10+14+.2) =400.7 (meters)
1.2Dmax (m) =1.2x400.7= 480.8 (meters), then the neighboring cells within 480.7 meters of the surrounding distance of Guangzhou-H-leaching north-removing-8455845-2-1-ONR cell are "neighboring cells", and the geographical distribution is shown in fig. 8.
1.2 Times Dmax (m) is a general scene of a dense urban area, a circle of base station distance situation fixed value near a reference cell can be flexibly adjusted, and the base station distance situation fixed value can be adjusted to be a numerical value of 1.5 times, 2 times and the like under the condition of larger base station distance. The neighbor cell referred to by the wireless network optimization profession generally refers to a neighbor cell of the nearest circle or a neighbor cell with a relatively close distance and more wireless switching.
From the database "Whole network neighbor relation table", it is queried that the Guangzhou-H-leaching North transfer-8455845-2-1-ONR "cells have 37 neighbor cells in total, and the details are shown in the following Table 5:
table 5 pre-appraisal of neighbor cell examples around a serving cell
The base station account of the whole network cell of the database has longitude and latitude data of each cell, and the longitude and latitude data of each cell can be used for calculating the earth surface distance from the source cell of the pre-judging backing service cell to each adjacent cell. The calculation formula is as follows:
In the above formula, latitude is defined as latitude and longitude is longitude. a= latitude1-latitude2, b= longitude1-longitude2, 6378.137 (KM) is the earth radius and S is in meters. The longitude and latitude in the formula are converted into radian and substituted into the formula for calculation.
As shown in table 5, 22 neighbor cells among the neighbor cells of the non-serving cell guangzhou-H-leaching north relocation-8455845-2-1-ONR have a distance within 1.2Dmax (m) = 480.8 meters, and the 22 neighbor cells are "neighbor cells" thereof.
Among these 22 "neighbor cells," analysis and statistics show that Guangzhou-H-leaching park-8457482-2-1-ONR, guangzhou-H-leaching park second-8457482-2-3-ONR is currently in a cell out-of-service state.
Kn＝1+Ntf＝Kn=1+2=3
3. 5G pre-judging and backing off the influence degree analysis and weighted score calculation of the serving cell:
Defining a weighted score of the influence degree of the pre-judgment serving cell by adopting a weighted scoring method, evaluating the influence degree of the pre-arranged pre-judgment serving cell on the 5G network user, sequencing the pre-judgment serving cell according to the weighted score of Sw, and determining the processing priority.
Sw＝Tyh×Kts×Kn, wherein Sw is a pre-determined serving cell impact degree weighted score, and Tyh、Kts、Kn is defined in detail above.
Embodiment of calculating "prejudged serving cell impact degree weighted score" for Guangzhou-H-leaching North movement-8455845-2-1-ONR Sw:
Sw＝Tyh×Kts×Kn
=[1+(T5yh÷10)]×[1+(K5ts÷5)]×(1+Ntf)
= [1+ (76/10) ]× [1+ (3/5) ]× (1+2) =8.6x1.6x3=41.28 (minutes)
In one embodiment, S3, a preliminary pre-judgment review processing scheme is formulated according to the review impact weighted score, which specifically includes:
sorting all preliminary prejudgment annealing serving cells in the area according to the magnitude of each annealing influence weighted score;
and pushing the district service withdrawal checking processing task to operation and maintenance personnel according to the arrangement sequence of each preliminary pre-judging service withdrawal district.
In this embodiment, after obtaining the pre-withdrawal serving cells, the pre-withdrawal serving cell list is sequentially output, and the "intelligent analysis module" sequentially analyzes and checks each pre-withdrawal serving cell by adopting the above algorithm, outputs the pre-withdrawal serving cell list, and orders the pre-withdrawal serving cells according to the size of the weighted score S, and the result is shown in table 6.
Table 6 pre-appraisal of example cell list (with investigation priority)
The pre-appraisal service cell is checked according to the table 6, the output list of the pre-appraisal service cell is used for pushing the operation and maintenance professionally to arrange the on-site check processing through a man-machine communication interface of the device shown in the figure 3, and the effect verification and evaluation are carried out on the check solving condition through continuous index statistical analysis through an intelligent analysis module. For example, if the number of cell resident users, main radio indexes, and the like of the pre-determined cells are restored to normal before the pre-determined cells within one week after the exclusion processing, the closed loop is completed. The pre-judging service cell list can be rapidly sequenced according to the importance degree, and service cells with high influence on the network can be preferentially and rapidly processed and sequenced before.
An example is that Guangzhou-H-leaching teaching north is moved-8455845-2-1-ONR to pre-judge and exit a serving cell, after maintenance major on-site replacement of a fault radio frequency unit (RRU, remote Radio Unit), the pre-judge and exit the serving cell to restore normal work, and after observing a week, the number of resident users and wireless indexes of the cell are normal, and closed loop is completed.
In one embodiment, the method further comprises:
and comparing and recording the number of resident users of the cells before and after the primary pre-judging and backing-off service cell checking treatment and the wireless network performance index.
In this embodiment, the "data management module" is also responsible for building a pre-judgment and back-off service cell analysis and investigation experience database, and the discovery, analysis and investigation processing processes of each pre-judgment and back-off service cell are classified and stored in a form of a standing book, and building a pre-judgment and back-off service cell analysis and investigation experience database, so that experience output reference is provided for subsequent analysis and investigation work.
The embodiment 1 provides an analysis and algorithm of a 5G pre-judging and backing-off serving cell, and provides a pre-judging and analyzing device of the 5G pre-judging and backing-off serving cell, which is suitable for pre-judging, analyzing, calculating and outputting of the 5G pre-judging and backing-off serving cell by arranging a network monitoring module, a database module and an intelligent analyzing module, and realizing a technical method from network monitoring to efficient pre-judging and analyzing and list ordering output of the 5G pre-judging and backing-off serving cell. The method comprises the following main technical innovation points:
1) The index of the maximum resident user number of the cell counted from the 5G core network is used as the evaluation index of the service-withdrawal/zero-service cell, and the function of pre-judging the service-withdrawal cell is realized through a computer program tool.
2) And calculating the weighted score and the ranking of the influence degree of each pre-judgment serving cell by adopting a weighted algorithm of the pre-judgment serving cell weighted score. The neighbor cell application of the pre-judgment and withdrawal serving cell is to calculate one weighted score coefficient of the pre-judgment and withdrawal serving cell by calculating a neighbor cell withdrawal coefficient Kn.
3) Before the 5G generates zero flow, the state of the cell withdrawal is pre-judged through the mutation of the resident user number of the cell, the priority order of the 5G pre-judging withdrawal cell to the influence degree of the user is output according to the intelligent analysis of various monitoring data, the influence degree coefficient to the user is increased to distinguish the importance and the urgency of the problem, the list of the 5G pre-judging withdrawal problem cell and the processing priority order thereof are output, and the 5G withdrawal cell is more efficient in processing.
Example 2:
As shown in fig. 2 and 3, the present disclosure provides a device for predicting a fallback cell, the device including:
The network monitoring module is used for acquiring cell withdrawal pre-judging parameters including cell resident user number, cell complaint number and cell neighbor cell configuration;
the intelligent analysis module is connected with the network monitoring module and is used for prejudging and analyzing the service withdrawal cell according to the cell service withdrawal prejudging parameter, and comprises the following steps:
a preliminary pre-judgment unit for determining the cell as a preliminary pre-judgment fallback serving cell in response to the decrease in the number of cell resident users being greater than a first threshold,
The influence analysis unit is connected with the preliminary pre-judging unit and is used for acquiring the withdrawal influence weighted score of the preliminary pre-judging withdrawal district according to the number of resident users in the district, the number of complaints in the district and the configuration of the neighborhood district;
and the check processing module is connected with the intelligent analysis module and is used for making a check processing scheme of the preliminary pre-judging and withdrawing service cell according to the withdraw service influence weighted score.
In one embodiment, the network monitoring module specifically includes:
a user number monitoring unit, configured to obtain, from a core network, a number of cell resident users yesterday and a previous N days before yesterday;
The complaint quantity monitoring unit is used for acquiring the physical and chemical micro grid complaint quantity of the cell from the customer complaint platform;
the neighbor cell monitoring unit is used for acquiring cell antenna configuration, neighbor cells of the cells and service withdrawal information of the neighbor cells from the wireless network management equipment.
In one embodiment, the neighbor cell monitoring unit specifically includes:
the antenna configuration monitoring unit is used for acquiring the hanging height, the downward inclination angle and the antenna vertical pattern beam width of the antenna of the cell from the wireless network management equipment;
The coverage distance calculation unit is connected with the antenna configuration monitoring unit and is used for calculating the maximum coverage distance Dmax (m) =antenna hanging height multiplied by Tan (90 degrees-antenna downtilt angle+antenna vertical pattern beam width/2), and the maximum value of Dmax (m) is 1000m;
The neighbor calculation unit is connected with the coverage distance calculation unit and is used for acquiring the longitude and latitude of each base station from the wireless network management equipment and acquiring the neighbor base stations positioned in the distance of 1.2Dmax (m) of the cell according to the longitude and latitude calculation;
The neighbor cell configuration monitoring unit is connected with the neighbor calculation unit and is used for acquiring neighbor cells of the neighbor base station towards the base station of the cell and the deserving information of the neighbor cells from the wireless network management equipment.
In one embodiment, the preliminary pre-judging unit specifically includes:
An average calculating unit for calculating an average number of cell resident users in the previous N days before yesterday;
The change calculation unit is connected with the average calculation unit and is used for calculating the change proportion of the yesterday cell resident user number to the average;
And the comparison and determination unit is connected with the change calculation unit and is used for determining the cell as a preliminary pre-judgment serving cell in response to the absolute value of the change proportion being larger than a first threshold value.
In one embodiment, the impact analysis unit specifically includes:
the first coefficient unit is used for acquiring the cell user number coefficient according to the cell resident user number;
The second coefficient unit is used for acquiring the complaint coefficient of the cell user according to the number of the cell complaints;
a third coefficient unit, configured to obtain a cell neighbor service withdrawal coefficient according to the cell neighbor configuration;
the weighted score unit is connected with the first, second and third coefficient units and is used for obtaining the unworked influence weighted score of the preliminary prejudging unworked cell according to the cell user coefficient, the cell user complaint coefficient and the cell neighbor unworked coefficient.
In one embodiment, wherein:
A first coefficient unit for calculating a cell user number coefficient Tyh＝1+(TNyh÷M),TNyh which is an average number of cell resident users N days before a certain preliminary pre-judgment service cell yesterday, and M which is a reference number of cell resident users;
the second coefficient unit calculates a cell user complaint coefficient Kts＝1+(KNts÷N),KNts as the sum of the number of cell complaints of the previous N days before a certain preliminary pre-judgment service cell is yesterday;
A third coefficient unit for calculating that the neighbor cell service withdrawal coefficient Kn＝1+Ntf,Ntf is the number of service withdrawal cells in the neighbor cells of a certain preliminary pre-judgment service withdrawal cell;
and a weighted score unit for calculating a unwatched influence weighted score Sw＝Tyh×Kts×Kn.
In one embodiment, the checking processing module specifically includes:
The ranking unit is used for ranking the preliminary pre-judgment and withdrawal service cells in the area according to the magnitude of the respective withdrawal influence weighted scores;
the pushing unit is connected with the ordering unit and used for pushing the district service withdrawal checking processing task to the operation and maintenance personnel according to the arrangement sequence of each preliminary pre-judging service withdrawal district.
In one embodiment, the apparatus further comprises:
the data management module is connected with the network monitoring module, the intelligent analysis module and the checking processing module and is used for comparing and recording the number of cell resident users and the wireless network performance index before and after the checking processing of each preliminary pre-judging and backing service cell.
Example 3:
Embodiment 3 of the present disclosure provides a computer-readable storage medium having a computer program stored therein, which when executed by a processor, implements the method for pre-determining an out-of-service cell as described in embodiment 1 or implements the apparatus for pre-determining an out-of-service cell as described in embodiment 2.
The computer-readable storage media includes volatile or nonvolatile, removable or non-removable media implemented in any method or technology for storage of information such as computer-readable instructions, data structures, computer program elements, or other data. Computer-readable storage media includes, but is not limited to, RAM (Random Access Memory ), ROM (Read-Only Memory), EEPROM (ELECTRICALLY ERASABLE PROGRAMMABLE READ ONLY MEMORY, charged erasable programmable Read-Only Memory), flash Memory or other Memory technology, CD-ROM (Compact Disc Read-Only Memory), digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer.
In addition, the present disclosure may further provide a computer apparatus including a memory and a processor, where the memory stores a computer program, and when the processor runs the computer program stored in the memory, the processor performs the method for pre-determining a fallback cell as described in embodiment 1. The computer means may be a descensus cell pre-judgment means as described in example 2.
The memory is connected with the processor, the memory can be flash memory or read-only memory or other memories, and the processor can be a central processing unit or a singlechip.
Embodiments 1 to 3 of the present disclosure provide a method for pre-judging a service-withdrawal cell, a device for pre-judging a service-withdrawal cell, and a computer readable storage medium, wherein the pre-judging and analyzing the service-withdrawal cell by using a cell service-withdrawal pre-judging parameter includes preliminarily pre-judging the service-withdrawal cell according to a reduced amplitude of a cell resident user number, analyzing an influence of the service withdrawal of the cell according to the cell resident user number, a cell complaint number and a cell neighbor configuration, taking the service withdrawal influence of the preliminarily pre-judging service-withdrawal cell as a pre-judging analysis result, and timely checking a possible service withdrawal condition of the cell according to the pre-judging analysis result, thereby realizing the pre-judgment of the service-withdrawal cell.
It is to be understood that the above embodiments are merely exemplary embodiments employed to illustrate the principles of the present disclosure, however, the present disclosure is not limited thereto. Various modifications and improvements may be made by those skilled in the art without departing from the spirit and substance of the disclosure, and are also considered to be within the scope of the disclosure.