CN115334528A - Base station network access quality inspection method, system, equipment and storage medium - Google Patents

Base station network access quality inspection method, system, equipment and storage medium Download PDF

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CN115334528A
CN115334528A CN202210820971.5A CN202210820971A CN115334528A CN 115334528 A CN115334528 A CN 115334528A CN 202210820971 A CN202210820971 A CN 202210820971A CN 115334528 A CN115334528 A CN 115334528A
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base station
score
cell
quality inspection
network
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刘通
陈灿
但德东
齐春言
朱海龙
田波
施兆阳
陈大明
袁振宇
王煜辉
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China Telecom Corp Ltd
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China Telecom Corp Ltd
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    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W24/00Supervisory, monitoring or testing arrangements
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W48/00Access restriction; Network selection; Access point selection
    • H04W48/18Selecting a network or a communication service
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W88/00Devices specially adapted for wireless communication networks, e.g. terminals, base stations or access point devices
    • H04W88/08Access point devices

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Abstract

The embodiment of the invention provides a method, a system, equipment and a storage medium for quality inspection of base station access network, relating to a system for quality inspection of base station access network, wherein the method comprises the following steps: acquiring base station data of a base station through a data acquisition module; evaluating the quantization indexes of different dimensions through a quantization evaluation module according to the base station data to obtain the quality inspection score of the base station; the quality inspection score of the base station is determined based on first weight coefficients of the quantization indexes with different dimensions, and the first weight coefficients are adaptively adjusted based on the mismatch conditions of the quantization indexes with different dimensions; and displaying the quality inspection score of the network access base station through a quality inspection result output module to obtain the quality inspection result of the base station. Under the condition of avoiding relying on manual quality inspection of the network access base station, the network access base station is comprehensively evaluated for quality inspection from quantization indexes of different dimensionalities, specific construction problems of the base station can be presented when quality inspection results are displayed based on the first weight coefficient adjusted in a self-adaptive mode, short boards of the constructed base station are exposed, and the targeted management and control of the network access flow of the base station are enhanced.

Description

Base station network access quality inspection method, system, equipment and storage medium
Technical Field
The present invention relates to the field of communications technologies, and in particular, to a method for quality inspection of a base station access network, a system for quality inspection of a base station access network, a corresponding electronic device, and a corresponding computer storage medium.
Background
The access quality inspection of the 5G (5 th Generation Mobile Communication Technology, fifth Generation Mobile Communication Technology) base station is beneficial to avoiding the access quality problem caused by the 5G base station in the construction stage in engineering optimization and daily optimization, and thus the access quality inspection of the base station is usually required in the construction stage of the base station.
In the related technology of the base station network access quality inspection, the network access quality inspection of the 5G base station is finished manually, and the judgment of the base station opening condition is mainly carried out by manually checking the related data of the equipment network management base station; some Information Technology (IT) systems are used for realizing convenient statistics of partial items; some proposed base station acceptance systems mainly focus on base station data collected in a field part. Generally, the related art of the quality inspection of the base station network access lacks systematic and comprehensive quality inspection.
Disclosure of Invention
In view of the above problems, embodiments of the present invention are provided to provide a base station network access quality inspection method, a base station network access quality inspection system, a corresponding electronic device, and a corresponding computer storage medium, which overcome or at least partially solve the above problems.
The embodiment of the invention discloses a base station network access quality inspection method, which relates to a base station network access quality inspection system, wherein the base station network access quality inspection system comprises a data acquisition module, a quantitative evaluation module and a quality inspection result output module, and the method comprises the following steps:
acquiring base station data of a base station through the data acquisition module;
evaluating the quantization indexes with different dimensions according to the base station data through the quantization evaluation module to obtain the quality inspection score of the base station; the quality inspection score of the base station is determined based on first weight coefficients of quantization indexes of different dimensions, and the first weight coefficients are adaptively adjusted based on the mismatch condition of the quantization indexes of the different dimensions;
and displaying the quality inspection score of the network access base station through the quality inspection result output module to obtain the quality inspection result of the base station.
The embodiment of the invention also discloses a system for detecting the network access quality of the base station, which comprises the following components:
the data acquisition module is used for acquiring base station data of a base station;
the quantitative evaluation module is used for evaluating the quantitative indexes with different dimensions according to the base station data to obtain the quality inspection score of the base station; the quality inspection score of the base station is determined based on first weight coefficients of quantization indexes of different dimensions, and the first weight coefficients are adaptively adjusted based on the mismatch condition of the quantization indexes of the different dimensions;
and the quality inspection result output module is used for displaying the quality inspection score of the network access base station to obtain the quality inspection result of the base station.
The embodiment of the invention also discloses an electronic device, which comprises: the base station network access quality inspection method comprises a processor, a memory and a computer program which is stored on the memory and can run on the processor, wherein the computer program realizes the steps of any one of the base station network access quality inspection methods when being executed by the processor.
The embodiment of the invention also discloses a computer readable storage medium, wherein a computer program is stored on the computer readable storage medium, and when the computer program is executed by a processor, the steps of the network access quality inspection method of any base station are realized.
The embodiment of the invention has the following advantages:
in the embodiment of the invention, the base station network access quality inspection system comprises a data acquisition module, a quantitative evaluation module and a quality inspection result output module, the base station data of the base station can be mainly acquired through the data acquisition module, then the quantitative evaluation module evaluates the quantitative indexes with different dimensions based on the acquired base station data to obtain the quality inspection score which can be adaptively adjusted based on the loss condition of the quantitative indexes with different dimensions, so that the quality inspection score of the network access base station can be displayed through the quality inspection result output module to obtain the quality inspection result of the base station. The obtained base station data are automatically subjected to quantitative evaluation and quality inspection result output through the base station network access quality inspection system, under the condition that manual network access quality inspection is avoided, network access quality inspection of the base station is comprehensively evaluated from quantitative indexes of different dimensionalities, and based on weight coefficients capable of being adaptively adjusted, specific construction problems of the base station are presented when quality inspection results are displayed, short boards of the constructed base station are exposed, and the pertinence management and control of a 5G base station network access flow are enhanced.
Drawings
Fig. 1 is a schematic diagram of a framework of a network access quality inspection system of a base station according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating steps of a method for quality inspection of a base station during network access according to an embodiment of the present invention;
fig. 3 is a schematic diagram illustrating a quality inspection result for a base station according to an embodiment of the present invention;
FIG. 4 is a flowchart illustrating steps of another embodiment of a method for quality inspection of a base station during network access;
FIG. 5 is a schematic diagram of a triangulation network according to an embodiment of the present invention;
fig. 6 is a schematic diagram of a TAC influence domain provided by an embodiment of the present invention;
fig. 7 is a schematic diagram of dividing a neighboring cell set of a "visual angle" according to an embodiment of the present invention;
FIG. 8 is a schematic illustration of latitude and longitude coordinate calculations provided by an embodiment of the present invention;
fig. 9 is a schematic diagram of a cell beacon provided by an embodiment of the present invention;
fig. 10 is a schematic view of an application scenario of quality inspection of network access of a base station according to an embodiment of the present invention;
fig. 11 is a block diagram of a base station network access quality inspection system according to an embodiment of the present invention.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention more comprehensible, the present invention is described in detail with reference to the accompanying drawings and the detailed description thereof.
To facilitate an understanding of the application by those skilled in the art, the following may be interpreted to refer to terms or terms used in the following examples of the invention:
and (3) equipment network management: may be referred to as a network management device, is a device required for network management.
A north interface: is an interface defined for a user to access and manage a network, and the user typically uses an associated network manager in an application layer defined and developed by the northbound interface to enable access and management of the network through the use of the associated network manager.
Big data lake: a centralized repository allows all structured and unstructured data to be stored at any scale.
AAU: active Antenna Unit, which is usually used as a transmitter for 5G base station signals.
RRU: a Remote Radio Unit, is a device that converts a baseband optical signal into a Radio frequency signal at a Remote end, amplifies the Radio frequency signal, and transmits the Radio frequency signal.
And (3) CPRI: common Public Radio Interface, a Common Public Radio Interface, is a standardized protocol, which is mainly used to define the Radio frequency equipment control of the wireless infrastructure base station and the digital Interface between the Radio frequency equipments.
PCI: physical Cell Identifier, and terminal in 5G network distinguish wireless signals of different cells.
PRACH: physical Random Access Channel, physical Random Access Channel.
TAC: tracking Area Code, area Code for terminal location management.
Delaunay triangulation network: a dironian triangle is a set of connected but non-overlapping triangles, and the circumcircles of these triangles do not contain any other point of this area.
CQI: channel Quality Indicator, which is used to represent the Quality of the current Channel, generally corresponds to the snr of the Channel.
Base Line: the lowest baseline.
Reference Line: and (6) aligning the marked lines.
In the process of engineering optimization and daily optimization, the problem of subsequent leaving caused by the 5G base station with the network access quality problem in the construction stage may occur, which brings trouble to the subsequent network optimization and maintenance work, especially under the condition that the construction period is tight and the base station is accessed to the network in order to make progress, the problems that the base station cell or equipment is not fully opened, the equipment has faults, the parameter configuration is improper or wrong and the like may occur, and in severe cases, the accessed base station needs to be returned to the engineering debugging link, which brings adverse effects to the network quality and the user perception. Therefore, it is necessary to perform network access quality control on the base station.
One of the core ideas of the embodiment of the invention is that a base station access quality inspection mode for comprehensive quantitative evaluation is realized, and comprehensive quantitative evaluation can be mainly carried out from quantitative indexes with different dimensions, such as equipment online, working state, key parameters, service bearing, key performance and the like, by constructing a multi-dimensional evaluation model, so that the quality of a newly accessed network station can be objectively and accurately mastered; the dynamic self-adaptive adjustment of the corresponding weight coefficient of the quantization index based on each dimension presents the specific construction problem of the base station when the quality inspection result is displayed, exposes the short board of the constructed base station, directly reveals the problem, reduces unnecessary calculated amount, and strengthens the targeted control of the network access process of the 5G base station; and based on an evaluation visual angle facing the influence domain and a neighbor cell auditing algorithm of a visual angle, the newly-accessed base station and the surrounding comparable base stations are subjected to benchmarking through the cooperation of the set base line and the benchmarking line, so that the aim of performing scene self-adaptive auditing on the newly-accessed base station is fulfilled, the effect of performing accurate auditing in the influence domain is realized, the newly-accessed 5G base station is comprehensively, objectively and accurately evaluated to work, and the auditing efficiency of the base station accessing the network is greatly improved.
Referring to fig. 1, which shows a schematic frame diagram of a base station network access quality inspection system according to an embodiment of the present invention, a base station network access quality inspection system 110 includes a data acquisition module 111, a quantization scoring module 112, and a quality evaluation module 113, which can perform comprehensive quantization evaluation on a newly-accessed base station based on the aforementioned modules of the base station network access quality inspection system.
Specifically, the data acquisition module 111 is responsible for acquiring relevant data of a newly-accessed base station, and may mainly acquire base station data through a device network manager, where the acquired data may include configuration data, fault alarm data, performance index data, and other relevant base station data. Besides collecting the relevant data of the base station, the system can also be used as a data providing module of a base station network access quality inspection system, specifically, the system can analyze the collected relevant base station data and store the analyzed data into a big data lake, and the data stored in the big data lake can be used as a data source for quantitative scoring by the quantitative scoring module 112.
The quantization scoring module 112 is responsible for constructing a multidimensional evaluation model to perform comprehensive quantitative evaluation based on quantization indexes of different dimensions, and the multidimensional evaluation model is mainly constructed for the quantization indexes of different dimensions, where the quantization indexes of different dimensions may include indexes such as equipment online, working state, key parameters, service bearers, and key performance. The constructed multidimensional evaluation model can endow a dynamic self-adaptive adjustment mechanism with weight coefficients, an influence domain-oriented auditing algorithm is constructed based on a triangular network, and a scene self-adaptive auditing algorithm is used for coordinating a baseline with a marked line, so that auditing can be performed in the range of the relevant base stations influenced by the newly-accessed 5G base station and the newly-accessed 5G base station during network access quality inspection, and the working condition of the newly-accessed 5G base station is evaluated.
The quality evaluation module 113 may be equivalent to a quality inspection result output module, and is responsible for displaying the quality inspection score of the base station obtained by the quantitative scoring module 112 to present the quality inspection result of the base station, and when displaying the quality inspection result, the quality inspection evaluation can be mainly performed from two perspectives, namely, a single perspective and a total perspective.
Referring to fig. 2, a flow chart of steps of an embodiment of a base station network access quality inspection method according to the present invention is shown, and relates to the base station network access quality inspection system shown in fig. 1, where the base station network access quality inspection system includes a data acquisition module, a quantitative evaluation module, and a quality inspection result output module, and specifically may include the following steps:
step 201, acquiring base station data of a base station through a data acquisition module;
in the embodiment of the invention, the data acquisition module mainly can acquire various types of data required for subsequent quantitative evaluation of a newly-accessed base station, the required various types of data are usually related base station data, and the required various types of data mainly comprise configuration data, fault alarm data, performance index data, session statistical data and the like, and are provided for a base station access quality inspection system.
In practical application, when the data acquisition module acquires the relevant base station data, the data acquisition module can usually acquire the relevant base station data through a northbound interface of a network manager of the wireless device, then the acquired relevant base station data can be analyzed according to a data file format, the analyzed data is stored in a big data lake, and the data stored in the big data lake can be used as a data source for quantitative scoring by the quantitative scoring module.
In the acquired relevant base station data, the configuration data may be used to reflect relevant configuration information of the newly-accessed base station, such as base station parameter configuration, device configuration, and the like; the fault alarm data can be used for reflecting relevant fault alarm information of a newly-accessed base station, such as alarm information, alarm types and the like; the performance index data is mainly used for measuring the working performance of a newly-accessed base station, such as flow, user number, key performance and the like; the session statistics data may be used to reflect the working conditions of the base station newly accessing the network during cell working, such as cell connection success rate, cell disconnection rate, cell handover success rate, and the like.
Step 202, evaluating the quantization indexes with different dimensions through a quantization evaluation module according to the base station data to obtain the quality inspection score of the base station;
the base station data acquired by the data acquisition module can provide a data source for quantitative evaluation for the quantitative evaluation module, and at the moment, the quantitative evaluation module can evaluate the base station data from a big data lake to obtain a quality inspection score for a newly-accessed base station.
In the embodiment of the invention, the quantitative evaluation module can evaluate the quantitative indexes with different dimensions according to the base station data in the process of evaluating the base station data. The quantitative indexes with different dimensions can comprise indexes such as equipment online, working states, key parameters, service bearing, key performance and the like, in practical application, a multi-dimensional quantitative evaluation model can be constructed from the aspect of the quantitative indexes with different dimensions, and comprehensive quantitative evaluation based on the quantitative indexes with different dimensions is realized based on the use of the multi-dimensional quantitative evaluation model, so that the quality of a newly-accessed website can be objectively and accurately mastered.
For the evaluation of the quality inspection score of the base station, in practical application, the evaluation is mainly performed by using the constructed multi-dimensional quantitative evaluation module, and the obtained quality inspection score can comprise a total quality inspection score and a score condition for different quantitative indexes. In the calculation process of the score conditions of different quantization indexes, the method specifically includes acquiring the single score of each quantization index, and determining the first weight coefficient of each quantization index according to the base station data, and at this time, the single score of each quantization index and the first weight coefficient of each quantization index can be adopted to obtain the score conditions of each quantization index; then in the process of calculating the total quality inspection score, the scoring conditions of each quantization index can be summed, so as to obtain the total quality inspection score of the base station.
Specifically, in the constructed multidimensional quantitative evaluation model, the quantitative indexes of different dimensions may be set by a percentile system, the evaluation system is mainly as shown in table 1, the single score of each quantitative index is set to 100, and at this time, the score conditions of each quantitative index may be summed according to the weight coefficient to obtain the total quality inspection score of the base station.
Serial number Quantization index Weight of Scoring the situation Single item score
1 Equipment on-line k1 Score1 100
2 Working state k2 Score2 100
3 Key parameter k3 Score3 100
4 Service bearer k4 Score4 100
5 Key Properties k5 Score5 100
TABLE 1
The formula for the total quality check score for a base station may be as shown in formula (1):
quality _ Score = k1 Score1+ k2 Score2+ k3 Score3+ k4 Score4+ k5 Score5 formula (1)
As shown in table 1, k1 is a first weighting coefficient for the on-line index of the device, and Score1 is a Score of the on-line index of the device; k2 is a first weighting coefficient for the operation state index, and Score2 is the Score of the operation state index; k3 is a first weighting coefficient for the parameter index, score3 is the Score of the parameter index; k4 is a first weighting factor for the service bearer indicator, and Score4 is the Score of the service bearer indicator; k5 is the first weighting factor for the performance indicator and Score5 is the Score for the performance indicator.
The constructed multidimensional evaluation model can endow a weight coefficient with a dynamic self-adaptive adjustment mechanism. In the process of evaluating the quantization indexes with different dimensions according to the base station data, the obtained quality inspection score can be mainly determined by means of the first weight coefficient of the quantization indexes with different dimensions, and the first weight coefficient can be adaptively adjusted based on the fraction loss condition of the quantization indexes with different dimensions, namely the quality inspection score can be adaptively adjusted based on the fraction loss condition of the quantization indexes with different dimensions.
It should be noted that the first weight coefficient is used for adjusting the proportion of different quantization indexes in the overall quality, and in an actual situation, the first weight coefficient is in positive correlation with a loss condition, that is, the first weight coefficient inclines toward a short board item, for example, the first weight coefficient corresponding to the quantization index with a larger loss appears to be larger, so that a specific construction problem of the base station is presented when a quality inspection result is displayed, the short board of the constructed base station is exposed, the problem is directly revealed, unnecessary calculation amount is reduced, and the targeted management and control of a 5G base station network access process is enhanced.
Since the first weighting factor can be adaptively adjusted based on the mismatch condition of the quantization indexes of different dimensions, the determination of the first weighting system can be mainly based on the mismatch condition of the quantization indexes. The quality control method mainly can be determined by a quality control result aiming at the network access base station in a preset time period. Specifically, the quality inspection results of the network access base stations in the latest period are periodically analyzed in the quality inspection results of the network access base stations in the preset time period, the default condition of each quantization index is counted, and then the first weight coefficient of each quantization index is determined according to the default condition of each quantization index. In the embodiment of the present invention, the quality inspection result for the network access base station in the preset time period may refer to a quality inspection result of the base station accessing the network in the latest period, for example, the base station accessing the network in the latest period includes base station 1, base station 2, and base station 3, and the quality inspection result obtained at this time is a quality inspection result of base station 1, base station 2, and base station 3 in this period.
In practical application, the losing score condition of each quantization index is determined based on the average losing score of each quantization index, the average losing score of the quantization index in a certain period is actually determined when the losing score condition of the quantization index is determined, and the average losing score can be represented as the losing score average value of each quantization index in the quality inspection result of the network access base station in the latest period. In the initial condition of the quality inspection of the base station access network, the first weight coefficients of all the quantization indexes can be temporarily set to be the same, for example, 20%, after a period of operation, the quality inspection result of the access network base station in the latest period is analyzed, and the average of all the quantization indexes is countedUniform Score, which can be expressed as 100-Score i (where i is used to indicate the type of the quantization index), at this time, the average loser ratio of each quantization index may be determined by using the average loser of each quantization index, and the average loser ratio of each quantization index may be used as the first weight coefficient of the corresponding quantization index, so as to implement adaptive adjustment of the first weight coefficient.
In the specific implementation, the individual scores of all the quantitative indexes in the quality inspection result of the network access base station in the latest period can be obtained, and the average loss score of all the quantitative indexes is calculated. And obtaining the total loss scores of the quantization indexes aiming at different dimensions in the latest period by adopting the average loss score of each quantization index in the latest period, and obtaining the average loss score ratio of each quantization index by adopting the ratio of the average loss score of each quantization index to the total loss score.
In the embodiment of the present invention, when the score condition of each quantization index of the base station in the preset time duration of network access is obtained according to the base station data, specifically, the score condition of each quantization index of the base station in the preset time duration is obtained by performing quantization evaluation on the device on-line index, the operating state index, the parameter index, the service bearing index, and the performance index of the base station according to the base station data, and obtaining the score condition of each quantization index of the device on-line index, the operating state index, the parameter index, the service bearing index, and the performance index.
Specifically, the formula for the average fraction loss ratio may be as shown in formula (2):
Figure BDA0003744409590000071
wherein, 100-Scorei can be used for representing the average fraction loss of each quantization index, wherein i is used for representing the type of the quantization index, for example, the on-line index of the device in table 1 corresponds to 1, the working state index corresponds to 2, and the like;
Figure BDA0003744409590000072
the amount is determined as the average lost point sum, i.e. the ratio of the average lost point to the average lost point sum of a certain quantitative index at that timeAnd (4) converting the average lost-share ratio of the index.
In a preferred embodiment, a weighting Baseline for each quantization index may be further set, and if a weighting coefficient of a certain quantization index is lower than the Baseline, the weighting coefficient may be modified to be Baseline, in this case, the remaining quantization indexes may perform corresponding deduction operations on the weighting coefficients according to a proportion, such as proportional reduction, to ensure that the total weighting of each quantization index is 100% after the weighting coefficients lower than the weighting Baseline are adjusted to the weighting Baseline.
Exemplarily, assuming that initial values of weight coefficients of quantization indexes are 20%, after quality inspection results of an access base station in a latest period are analyzed, it is found that the problems of incomplete line access and key parameter conflict of equipment are more prominent, at this time, the weights of the quantization indexes can be optimized to 35%, 15%, 25%, 10%, and 15% after adaptive adjustment, and then the average fraction loss of the line access indexes and the parameter performance of the equipment is larger, and the average fraction loss ratio as the weight coefficient is also relatively larger, thereby highlighting the problem of short boards.
And 203, displaying the quality inspection score of the network access base station through a quality inspection result output module to obtain a quality inspection result of the base station.
The quality inspection result output module is responsible for displaying the quality inspection score of the base station obtained by the quantitative scoring module so as to present the quality inspection result of the base station, and when the quality inspection result is displayed, the quality inspection evaluation can be mainly performed from a single visual angle and a total visual angle so as to comprehensively, objectively and accurately evaluate the work of the newly-accessed 5G base station.
The obtained quality inspection scores of the base station comprise total quality inspection scores and scoring conditions aiming at different quantization indexes, and at the moment, the total quality inspection scores of the base station and the scoring conditions aiming at different quantization indexes in the base station can be displayed, so that the quality inspection results of the base station at the total angle and the quality inspection results at the single angle are respectively obtained. The quality inspection result in the overall angle can be mainly used for evaluating the overall quality audit result of the base station when the base station accesses the network, and the quality inspection result in the single angle can be mainly used for presenting the specific construction problem of the base station, mainly presenting the short board.
In the embodiment of the invention, the quality of the newly-accessed 5G base station is inspected if the newly-accessed base station is qualified after accessing the network by carrying out quantitative scoring according to quantitative indexes such as online, working state, key parameters, service bearing, key performance and the like of the equipment mainly through the constructed multidimensional evaluation model aiming at the access quality inspection.
In practical application, a single-inspection qualified score line aiming at each quantization index and a total-inspection qualified score line aiming at the total quality inspection score can be set, the quality inspection is qualified when the single inspection and the total inspection are both qualified, otherwise, the quality inspection is unqualified, and the unqualified reason is presented to a user. For example, as shown in fig. 3, when performing quality inspection result display, the relevant result and the short board item may be visually displayed from a radar map or the like, for example, the radar map may be divided into different score lines, score conditions of each quantization index may be drawn based on pentagonal capability distribution conditions, and a total quality inspection score may be displayed in a pentagon drawn for the quantization index; meanwhile, a quantization scoring table can be provided to directly reveal the network access problem of the base station, and the embodiment of the invention is not limited.
The base station network access quality inspection system comprises a data acquisition module, a quantitative evaluation module and a quality inspection result output module, wherein base station data of a base station can be acquired mainly through the data acquisition module, then the quantitative evaluation module evaluates quantitative indexes of different dimensions based on the acquired base station data to obtain quality inspection scores which can be adaptively adjusted based on the mismatch condition of the quantitative indexes of different dimensions, so that the quality inspection scores of the network access base station are displayed through the quality inspection result output module to obtain the quality inspection result of the base station. The obtained base station data are automatically subjected to quantitative evaluation and quality inspection result output through the base station network access quality inspection system, under the condition that manual network access quality inspection is avoided, network access quality inspection of the base station is comprehensively evaluated from quantitative indexes of different dimensionalities, and based on weight coefficients capable of being adaptively adjusted, specific construction problems of the base station are presented when quality inspection results are displayed, and short boards of the constructed base station are exposed, so that the pertinence management and control of a 5G base station network access flow are enhanced.
Referring to fig. 4, a flowchart of steps of another embodiment of a method for quality inspection of a base station access network according to the present invention is shown, and relates to a system for quality inspection of a base station access network shown in fig. 1, where the system for quality inspection of a base station access network shown in fig. 1 includes a data acquisition module, a quantitative evaluation module, and a quality inspection result output module, and the embodiment of the present invention focuses on describing a process in which the quantitative evaluation module performs quantitative evaluation on an equipment on-line index, a working state index, a parameter index, a service bearer index, and a performance index of a base station within a preset time period according to base station data to obtain scores for the equipment on-line index, the working state index, the parameter index, the service bearer index, and the performance index, and specifically may include the following steps:
step 401, obtaining a score condition of the base station for the equipment on-line index according to a comparison condition of cell information and equipment information of the base station with site planning information respectively;
the base station data acquired by the data acquisition module can provide a data source for quantitative evaluation for the quantitative evaluation module, and at the moment, the quantitative evaluation module can evaluate the base station data from a big data lake to obtain a quality inspection score for a newly-accessed base station.
In the embodiment of the invention, the quantitative evaluation module can evaluate the quantitative indexes with different dimensions according to the base station data in the process of evaluating the base station data. The quantitative indexes with different dimensions can comprise indexes such as equipment online, working states, key parameters, service bearing, key performance and the like, in practical application, a multi-dimensional quantitative evaluation model can be constructed from the aspect of the quantitative indexes with different dimensions, and comprehensive quantitative evaluation based on the quantitative indexes with different dimensions is realized based on the use of the multi-dimensional quantitative evaluation model, so that the quality of a newly-accessed website can be objectively and accurately mastered.
When the device on-line index is quantitatively evaluated according to the base station data, the acquired base station data may be configuration data of a base station, and the acquired configuration data includes cell information, device information and site planning information, where the site planning information is used to provide cells planned by the base station and the number of devices planned and configured by each cell and allowed to access to the network.
In practical application, the cell information and the site planning information can be compared to obtain a first matching result, the equipment information and the site planning information can be compared to obtain a second matching result, then the online score condition corresponding to the first matching result is obtained, the online score condition corresponding to the second matching result is obtained, the online score condition corresponding to the first matching result and the score condition corresponding to the second matching result are summed, and the score condition of the base station for the equipment online index is obtained.
The equipment on-line index mainly evaluates whether the equipment is on-line completely, so as to audit the on-line condition of only part of the equipment, for example, a base station plans 3 cells, each cell corresponds to 1 AAU equipment, and whether 3 cells and 3 AAUs are on-line needs to be audited. Then, the first matching result obtained by comparing the cell information with the site planning information may be expressed as the on-line rate of the cell, and the second matching result obtained by comparing the device information with the site planning information may be expressed as the on-line rate of the device.
In specific implementation, for the online score condition corresponding to the first matching result, the online score condition corresponding to the first matching result can be obtained by obtaining the single score of the online index of the device and the first weight of the cell information, and then based on the online number of the cell, by using the single score and the first weight of the online index of the device. And for the online score condition corresponding to the second matching result, acquiring a single score of the online index of the equipment and a second weight of the equipment information, and then obtaining the online score condition corresponding to the second matching result by adopting the single score and the second weight of the online index of the equipment based on the online quantity of the equipment. As shown in table 2, the configuration information may be collected by the device network manager, the cell information and the AAU/RRU device information are obtained, and compared with the site planning information, if matching, a score is obtained, and if not matching, no score is obtained.
Serial number Item Weight of Score of Single item score
1 1 st cell 1/2i K1_C1_Score 100
2 2 nd cell 1/2i K1_C2_Score 100
…… …… …… ……
I Ith cell 1/2i K1_C(i)_Score 100
i+1 1 st apparatus 1/2i K1_Q1_Score 100
i+2 2 nd apparatus 1/2i K1_Q2_Score 100
…… …… …… ……
2i Ith apparatus 1/2i K1_Q(i)_Score 100
Table 2 specifically, the formula for the score condition of the on-device line index may be as shown in formula (3):
Figure BDA0003744409590000091
wherein the first weight
Figure BDA0003744409590000092
Related to the number of lines in the cell, k 1 _C x Refers to the scoring case as to whether the online cell matches the site planning information, and
Figure BDA0003744409590000093
can be used for representing the online score condition corresponding to the first matching result; second weight
Figure BDA0003744409590000094
Related to the number of lines on the device, k 1 _Q x Refers to the score condition for whether the online device matches the site planning information, and
Figure BDA0003744409590000101
can be used to represent the online score condition corresponding to the second matching result.
Exemplarily, it is assumed that a certain newly-accessed base station plans 3 cells, and each cell corresponds to 1 AAU device, that is, there are 3 devices in total, at this time, if cell information acquired by a device network manager is 3 cells, and the acquired device information is 2 AAUs, then a first weight for the cell information is 1/6, a second weight for the device information is 1/6, an online score condition corresponding to the first matching result is 50 scores, an online score condition corresponding to the second matching result is 33.3 scores, that is, a score condition for an online index of the device is 83.3 scores.
Step 402, obtaining the scoring condition of the base station aiming at the working state index according to the alarm type of the alarm information of the base station;
when the working state index is quantitatively evaluated according to the base station data, the acquired base station data can be fault alarm data of the base station, the acquired fault alarm data comprises alarm information of each cell, so that the alarm type of the alarm information of each cell can be mainly determined in the process of quantitatively evaluating the working state index, the working score condition of each cell is determined according to the alarm type, and then the working score conditions of each cell are summed to obtain the score condition of the base station for the working state index.
In practical application, the working score condition of each cell under the condition of corresponding fault alarm can be determined according to the alarm type, and a third weight aiming at the alarm information is obtained; then, based on the number of cells, the working score condition of each cell under the corresponding fault alarm and the third weight are adopted to obtain the working score condition for each cell, and the scoring rule for the working state index thereof may be as shown in table 3:
serial number Item Weight of Score of Single item score
1 1 st cell 1/i K2_C1_Score 100
2 2 nd cell 1/i K2_C2_Score 100
3 …… …… …… ……
i Ith cell 1/i K2_C(i)_Score 100
TABLE 3
The working state index is mainly used for evaluating whether the equipment can normally provide service, checking the conditions of cell out-of-service and other fault alarms influencing performance, such as the condition that 1 cell of the base station out-of-service and the other 1 cell of the base station have CPRI optical power insufficiency alarms.
In a specific implementation, if the alarm type is a cell out-of-service alarm type, the working score condition for the cell is counted as zero; and/or if the alarm type is other alarm types except the community quit alarm type, acquiring the single score of the working state index and the alarm number of fault alarms of other alarm types, deducting the preset score of the single score of the working state index according to the alarm number, and taking the deducted score as the working score condition of the community.
Specifically, the formula for the score condition of the operation state index may be as shown in formula (4) and formula (5):
Figure BDA0003744409590000102
Figure BDA0003744409590000111
wherein the third weight
Figure BDA0003744409590000112
Dependent on the number of cells, k2_ C x And the Score is used for representing the scoring condition of each alarm information after being deducted based on the alarm type.
Exemplarily, assuming that a certain newly-accessed base station plans 3 cells, the third weight for the alarm information is 1/3, and when there are other active alarms affecting the performance, each is deducted by 10 points, i.e. x =10. At this time, if alarm information acquired through the equipment network manager includes that 1 cell leaves service and 1 cell has an alarm of insufficient CPRI optical power, the score for the working state is 63.3.
Step 403, obtaining a score condition for the parameter index according to the configuration parameters of the base station;
when the parameter index is quantitatively evaluated according to the base station data, the acquired base station data may be configuration data for a base station, and the acquired configuration data includes configuration parameters for the base station, such as a cell identification parameter PCI, an access channel parameter PRACH, a tracking area parameter TAC, and a neighboring area parameter.
Specifically, the formula for the score condition of the parameter index may be as shown in formula (6):
score3= p1 PCI _ Score + p2 PRACH _ Score + p3 TAC _ Score + p4 NB _ Score formula (6)
Wherein, p1, p2, p3, p4 are second weighting coefficients of each parameter.
In order to more efficiently find the short board problem, the dynamic adaptive adjustment mechanism is also adopted for the weight of 4 parameters for auditing the key parameters, and the weight is inclined to the short board item. That is, the second weight coefficient may be used to adjust the proportion of different configuration parameters in the scoring condition of the overall parameter index, and in actual conditions, the second weight coefficient is in positive correlation with the score losing condition, for example, the second weight coefficient corresponding to the configuration parameter with a larger score losing condition is larger, so as to directly reveal the problem and reduce unnecessary calculation amount.
The determination of the second weight coefficient can be determined by a quality inspection result for the network access base station within a preset time period. Specifically, the quality inspection results of the network access base stations in the preset time period for the network access base stations are analyzed, the misclassification conditions of the configuration parameters are counted, and then the second weight coefficients of the configuration parameters are determined according to the misclassification conditions of the configuration parameters. In the embodiment of the present invention, the quality inspection result for the network access base station in the preset time period may refer to a quality inspection result of the base station accessing the network in the latest period, for example, the base station accessing the network in the latest period includes base station 1, base station 2, and base station 3, and the quality inspection result obtained at this time is a quality inspection result of base station 1, base station 2, and base station 3 in this period.
And the loss-score condition of each configuration parameter is determined based on the average loss-score of each configuration parameter, so that when the loss-score condition of each configuration parameter is obtained, the average loss-score of each configuration parameter can be determined according to the average loss-score of each configuration parameter in the quality inspection result of the network access base station in the latest period, the average loss-score occupation ratio of each configuration parameter is determined by adopting the average loss-score of each configuration parameter, and the average loss-score occupation ratio of each configuration parameter is used as the second weight coefficient of the corresponding configuration parameter.
In the specific implementation, the individual scores of the configuration parameters can be obtained, and the average losing score of the configuration parameters in the latest period is calculated according to the score condition of the configuration parameters in the quality inspection result of the network access base station in the latest period by adopting the individual scores of the configuration parameters and the score condition of the configuration parameters in the quality inspection result of the network access base station in the latest period; and finally, obtaining the total loss scores aiming at different configuration parameters in the latest period by adopting the average loss scores of the configuration parameters in the latest period, obtaining the average loss score ratio of the configuration parameters by adopting the ratio of the average loss scores of the configuration parameters to the total loss scores, and taking the average loss score ratio as a second weight coefficient. The average fraction loss of the configuration parameters such as the cell identification parameter PCI, the access channel parameter PRACH, the tracking area parameter TAC, the neighbor cell parameter and the like of the network-accessed 5G base station in the latest period can be calculated, and the average fraction loss ratio of each parameter is taken as a weight coefficient. Specifically, the formula for the average fraction loss ratio may be as shown in formula (7):
Figure BDA0003744409590000121
wherein, 100-p i The _ Score may be used to indicate an average lossiness of each quantization index, where i is used to indicate a kind of configuration parameter, for example, a cell identification parameter corresponds to 1, an access channel parameter corresponds to 2, and the like;
Figure BDA0003744409590000122
the average lost score sum is used for representing each configuration parameter; wherein x is used to indicate the type of each configuration parameter, for example, the cell identification parameter corresponds to 1, the access channel parameter corresponds to 2, and the like, and at this time, the average lost-shared ratio of a certain configuration parameter is determined by using the ratio of the average lost-shared to the sum of the average lost-shared of the configuration parameter.
In a preferred embodiment, a weighting Baseline for each configuration parameter may be further set, and if a weighting coefficient of a certain configuration parameter is lower than the Baseline, the configuration parameter may be modified to be Baseline, in this case, the weighting coefficients of the remaining configuration parameters may be correspondingly subtracted according to a proportion, for example, proportionally reduced, so as to ensure that after the weighting coefficients lower than the weighting Baseline are adjusted to the weighting Baseline, the total weighting of each configuration parameter is 100%.
Illustratively, the initial values of the weight of the parameters are all 25%, the problem of missing allocation of the neighboring cells is found to be more prominent through analysis of quality inspection results of the access network base station in the latest period, and the weight of each configuration parameter can be optimized to be 20%, 20% and 40% through adaptive adjustment.
In the embodiment of the invention, the influence domain-oriented key parameter auditing algorithm can be provided, so that the auditing is accurate in a reasonable and necessary range, the auditing accuracy is improved, and the unnecessary calculation amount is reduced. The influence domain refers to a certain range of neighboring base stations around the newly accessed base station, and is mainly a base station which may be influenced or influenced by the newly accessed base station. When the score condition of each configuration parameter is determined, the cell identification parameter PCI, the access channel parameter PRACH, the tracking area parameter TAC and the neighboring area parameter of the base station within a preset time period may be quantitatively evaluated mainly according to the configuration parameters, so as to obtain the score condition for the cell identification parameter, the access channel parameter, the tracking area parameter and the neighboring area parameter respectively.
Specifically, (1) when determining the score condition for the cell identification parameter, a triangulation network may be constructed centering on the newly-accessed base station, and the constructed triangulation network is used to determine the influence domain for the cell identification parameter. At this time, the cell identifier multiplexing condition of the neighboring base station in the influence domain may be obtained, and the cell identifier multiplexing condition is determined based on the first cell identifier multiplexing layer number (i.e., the PCI multiplexing layer number) and the second cell identifier multiplexing layer number (i.e., the PCI mod30 multiplexing layer number).
When the PCI audit is performed, the influence domain of the PCI needs to be determined, a Delaunay triangular network can be constructed by taking the base station as a point, the newly-accessed 5G base station is taken as a center, other vertexes of the adjacent triangles of the newly-accessed base station are the first-layer adjacent base stations, other vertexes of the adjacent triangles of the first-layer adjacent base stations are the second-layer adjacent base stations, and by analogy, n layers of adjacent base stations of the newly-accessed 5G base station can be accurately obtained and used as the influence domain of the key parameter audit. In general, n may take 3 or 4.
When the triangulation network is constructed, firstly, base station data can be preprocessed, which is mainly represented by taking a station address as a unit, merging stations with near addresses within a certain range to reduce the complexity of the triangulation network, for example, station addresses within a distance of 50 meters are merged into 1 station address, and the station addresses participate in the triangulation network generation as 1 point, and the point carries information of all the stations involved in the merging; then, the triangulation network is constructed, as shown in fig. 5, which shows that the site is used as a point, the construction is performed according to the Delaunay triangulation rule, a growth method can be adopted, that is, a newly-accessed 5G base station is used as an initial point, a nearest existing network station is searched, a connecting line between the two points is used as an initial edge, a third point which accords with the Delaunay rule is searched on one side of the initial edge to construct a first triangle, and then, the three edges of the first triangle are used as initial edges in sequence, and the third points are searched outwards respectively to be sequentially expanded. In the triangular network shown in fig. 5, ". Major" can be used to indicate a newly accessed 5G base station, followed by a layer 1 neighboring base station, a layer 2 neighboring base station, and a layer 3 neighboring base station.
When performing quantitative evaluation according to the PCI multiplexing condition of the adjacent base station in the affected area, the quantitative evaluation of the cell identifier parameters of the base station in the preset time period may be mainly performed by using the number of multiplexing layers of the first cell identifier (that is, the number of multiplexing layers of the PCI) and the number of multiplexing layers of the second cell identifier (that is, the number of multiplexing layers of the PCI imod 30), which may be specifically shown in table 4:
Figure BDA0003744409590000131
TABLE 4
The ranges of PCI _ Reuse _ Layer _ C (x) and PCI mod30_ Reuse _ Layer _ C (x) shown in table 4 are 1 to n +1. If the same PCI multiplex exists in the level 1 neighbor site, PCI _ Reuse _ Layer _ C (i) =1, if the same PCI multiplex exists in the level 2 neighbor site, PCI _ Reuse _ Layer _ C (i) =2, and so on; if the PCIs are not multiplexed in the n-tier neighbor stations, PCI _ Reuse _ Layer _ C (i) = n +1.
In a specific implementation, the score condition corresponding to the number of multiplexing layers of the first cell identifier may be obtained, the score condition corresponding to the number of multiplexing layers of the second cell identifier may be obtained, and then the score condition corresponding to the number of multiplexing layers of the first cell identifier and the score condition corresponding to the number of multiplexing layers of the second cell identifier may be summed to obtain the score condition of the base station for the cell identifier parameter.
Specifically, for the score condition corresponding to the number of multiplexing layers of the first cell identifier, the individual score for the cell identifier parameter, the preset score dereferencing range threshold, the multiplexing score for the number of multiplexing layers of the first cell identifier, and the fourth weight for the number of multiplexing layers of the first cell identifier may be obtained, and then, based on the number of cells, the score condition corresponding to the number of multiplexing layers of the first cell identifier is obtained by using the individual score of the cell identifier parameter, the preset score dereferencing range threshold, the multiplexing score for the number of multiplexing layers of the first cell identifier, and the fourth weight. And for the score condition corresponding to the number of the second cell identifier multiplexing layers, the single score for the cell identifier parameter, the preset score value range threshold, the multiplexing score for the number of the second cell identifier multiplexing layers, and the fifth weight for the number of the second cell identifier multiplexing layers can be obtained, and then based on the number of the cells, the single score, the preset score value range threshold, the multiplexing score for the number of the second cell identifier multiplexing layers, and the fifth weight are adopted to obtain the score condition corresponding to the number of the second cell identifier multiplexing layers.
The formula for the scoring case of the cell identification parameter can be as shown in formula (8):
Figure BDA0003744409590000141
wherein the fourth weight
Figure BDA0003744409590000142
The multiplexing score of the multiplexing layer number of the first cell identifier is positively correlated with the multiplexing layer number of the first cell identifier, mainly linearly increased and can be based on the cell number of the newly accessed network base station
Figure BDA0003744409590000143
Represents; fifth weight
Figure BDA0003744409590000144
The multiplexing score of the second cell identification multiplexing layer number is positively correlated with the second cell identification multiplexing layer number, mainly linearly increased, and can be based on the cell number of the newly accessed base station
Figure BDA0003744409590000145
And (4) showing.
For example, if n =3 is taken, and a 1 st cell of a new network access base station uses the same PCI in a 1 st-Layer neighbor base station, PCI _ Reuse _ Layer _ C (1) =1; if the 2 nd cell and the 3 rd cell do not use the same PCI in the adjacent three-tier base station, PCI _ Reuse _ Layer _ C (2) =4 and PCI _ Reuse _ Layer _ C (3) =4; in the 1 st cell, if there are PCIMODs 30 in the adjacent base stations in the 1 st Layer, the PCIMODs 30_ Reuse _ Layer _ C (1) =1; if the 2 nd cell and the 3 rd cell have no PCIMOD30 in the adjacent three-tier base station, the PCIMOD30Reuse _ Layer _ C (2) =4 and the PCIMOD30Reuse _ Layer _ C (3) =4. Then the PCI audit score is 66.7.
(2) When the score condition of the access channel parameters is determined, a triangulation network can be constructed by taking a base station which is accessed to the network as a center, the constructed triangulation network is used for determining an influence domain aiming at the access channel parameters, and at the moment, the multiplexing condition of the access channels of adjacent base stations in the influence domain can be obtained; and determining the multiplexing condition of the access channel based on the number of the multiplexing layers of the access channel, and then performing quantitative evaluation on the access channel parameters of the base station within a preset time length by adopting the number of the multiplexing layers of the access channel to obtain the scoring condition of the base station for the access channel parameters. In practical applications, quantitative scoring may be performed according to the PRACH multiplexing condition in neighboring base stations within the influence domain, as shown in table 5:
Figure BDA0003744409590000151
TABLE 5
In practical application, the individual score for the access channel parameter, the preset score value range threshold, the multiplexing score for the number of access channel multiplexing layers, and the sixth weight for the number of access channel multiplexing layers may be obtained, and then the score condition for the access channel parameter is obtained by using the individual score for the access channel parameter, the preset score value range threshold, the multiplexing score for the number of access channel multiplexing layers, and the sixth weight based on the number of cells.
Specifically, the formula for the score case of the access channel parameter can be as shown in formula (9):
Figure BDA0003744409590000152
wherein the sixth weight
Figure BDA0003744409590000153
The number of cells of the newly accessed base station is correlated, and the multiplexing score of the access channel multiplexing layer number is positively correlated with the access channel multiplexing layer number, mainly linearly increased, and can be based on
Figure BDA0003744409590000154
And (4) showing. The PRACH _ Reuse _ Layer _ C (x) value rule shown in table 5 is the same as PCI.
(3) When the score condition of the tracking area parameters is determined, the tracking area parameters of the base station accessing the network and the tracking area parameter set of the adjacent base station in the influence domain can be obtained.
In practical applications, the determination of the TAC influence domain may be determined based on the first-layer neighboring base station in the constructed Delaunay triangulation network. Namely, the TAC mainly audits whether the flower arrangement phenomenon exists, namely, the newly-accessed 5G base station TAC is one of the TACs of the base stations of the adjacent layer. As shown in fig. 6, the first layer of neighboring base stations in the triangulation network may be divided into TAC1, TAC2, and TAC3, that is, a neighboring layer of base station TAC set NB _ TAC = { TAC1, TAC2, \8230; \8230 }, and the newly networked 5G base station TAC is NewSite _ TAC and should be a subset of NB _ TAC.
The formula for the score condition of the tracking area parameters can be shown as formula (10):
Figure BDA0003744409590000161
if the tracking area parameters of the accessed base station do not belong to the tracking area parameter set of the adjacent base station in the influence domain, the score condition aiming at the tracking area parameters is calculated to be zero; and/or if the tracking area parameters of the accessed base stations belong to the tracking area parameter set of the adjacent base stations in the influence domain, determining the single score aiming at the tracking area parameters as the score condition aiming at the tracking area parameters.
(4) When the score condition of the parameters of the adjacent cells is determined, the first-layer adjacent base station is mainly checked, and the method can be expanded to the 2 nd and above adjacent base stations according to the requirement. The adjacent cells mainly check the missing distribution of the adjacent cells, including 5G-5G and 5G-4G adjacent cells, and carry out quantitative scoring according to the condition of the missing distribution of the adjacent cells in the influence domain. The azimuth angle of a newly-accessed 5G base station cell is taken as a center, and a peripheral 360-degree range is divided into three regions of green, blue and red according to a visual angle of 'seeing and seen', wherein the cells adjacent to the base station, all cells of a first layer adjacent base station in the green region, the cells in the same direction and opposite directions of the first layer adjacent base station in the blue region, and the cells in the same direction of the first layer adjacent base station in the red region are required to be set as adjacent cells.
In practical application, the base station accessing the network can be taken as a center to acquire the azimuth information of the base station accessing the network and the adjacent base stations, then a necessary adjacent cell set is determined based on the mutual difference between the azimuth information of each base station accessing the network and the adjacent base stations, and finally the necessary adjacent cell set and the configured adjacent cell set are adopted to carry out quantitative evaluation on the adjacent cell parameters of the base station within the preset time length.
The azimuth information comprises a cell azimuth of a base station accessing the network, a cell azimuth of an adjacent base station in an influence domain, an azimuth of the adjacent base station relative to a main cell and an azimuth of the main cell relative to the adjacent base station.
Referring to fig. 7, a schematic diagram of dividing a neighbor set of a "visual angle" provided by an embodiment of the present invention is shown. Wherein, the judging mode of the green area can be that | alpha-gamma | is less than or equal to 60 degrees or | alpha-gamma | is more than or equal to 300 degrees; the judgment condition of the blue zone can be that the alpha-gamma is more than or equal to 120 degrees at an angle of 60 degrees or more than or equal to 300 degrees at an angle of 240 degrees or more than or equal to alpha-gamma; the judgment condition of the equidirectional cell can be that | alpha-beta | is less than or equal to 60 degrees or | alpha-beta | is more than or equal to 300 degrees; judging conditions of the opposite cells: 60 degrees < | alpha-beta | <300 degrees, and (| beta-theta | < 60 or | beta-theta | > 300 degrees); the judgment condition of the red area can be that the angle is 120 degrees < | gamma-alpha | is less than 240 degrees; the judgment condition of the equidirectional cell can be that | beta-alpha | is less than or equal to 60 degrees or | beta-alpha | is more than or equal to 300 degrees.
Wherein alpha is the azimuth angle of the newly-built 5G base station cell, beta is the azimuth angle of the adjacent base station cell, gamma is the azimuth angle of the adjacent base station relative to the main cell, and theta is the azimuth angle of the main cell relative to the adjacent base station, and the values are all 0-360 degrees. As shown in fig. 8, γ and θ can be calculated by longitude and latitude coordinates, which can be expressed as
Tanγ=(n-y)/(m-x)
Gamma = arctan [ (n-y)/(m-x) ], value range [ -pi/2, pi/2 ]
Wherein, the quadrant can be judged through m-x, n-y plus-minus, and then the accurate angle of gamma is judged: the first quadrant, [ +, + ], the true angle [0, π/2]; the second quadrant, [ -, + ], the true angle [ pi/2, pi ]; third quadrant, [ -, - ] true angle [ pi, 3 pi/2 ]; quadrant four, true angle [3 π/2,2 π ]. It should be noted that, the principle of auditing the 5G-4G neighboring cells is the same as that of the above 5G-5G, and only the neighboring base stations need to be replaced with 4G base stations, and the Delaunay triangulation network is reconstructed to obtain the neighboring base stations.
At this time, the obtained neighbor cells are Necessary neighbor cell sets (Necessary _ 5to5. Cnb, necessary _ 5to4. Cnb), and the neighbor cells obtained from the device network manager are configured neighbor cell sets (Necessary _ 5to5. Cnb, necessary _ 5to4. Cnb). And the number of the adjacent cells in the intersection of the necessary adjacent cell set and the configured adjacent cell set accounts for the proportion of the number of the adjacent cells in the necessary adjacent cell set, namely the adjacent cell configuration effective factor. Specifically, as shown in table 7:
Figure BDA0003744409590000171
TABLE 7
When the necessary neighbor cell set and the configured neighbor cell set are adopted to quantitatively evaluate the neighbor cell parameters of the base station within the preset time, the formula for the scoring condition of the neighbor cell parameters can be as shown in formula (11):
Figure BDA0003744409590000172
in practical application, the single score of the parameters of the neighbor cells, the proportion of the number of the neighbor cells in the intersection of the necessary neighbor cell set and the configured neighbor cell set to the number of the neighbor cells in the necessary neighbor cell set can be obtained, and the proportion is used as a neighbor cell configuration effective factor for neighbor cell auditing and a seventh weight; wherein the seventh weight is related to the number of cells. Then, the score condition for the neighbor cell parameters can be obtained by adopting the single score of the neighbor cell parameters, the proportion of the number of neighbor cells in the intersection of the necessary neighbor cell set and the configured neighbor cell set to the number of neighbor cells in the necessary neighbor cell set, and the seventh weight.
Illustratively, for a new network access base station, the necessary neighbor cell set of the 1 st cell includes 50 5G-5G neighbor cells and 30 5G-4G neighbor cells, but there are 45 and 28 of the actually configured neighbor cells belonging to the necessary neighbor cell set; the necessary neighbor cell set of the 2 nd cell comprises 60 5G-5G neighbor cells and 40 5G-4G neighbor cells, but the actually configured neighbor cells belong to the necessary neighbor cell set and respectively comprise 52 cells and 35 cells; the necessary neighbor cell set of the 3 rd cell has 30 5G-5G neighbor cells and 18 5G-4G neighbor cells, but if the actually configured neighbor cells belong to the necessary neighbor cell set and have 30 and 18 cells respectively, the neighbor cell audit score is 92.9.
Step 404, obtaining the score condition of the base station for the service bearing index according to the cell flow and the number of cell connection users of the base station;
when the service carrying index is quantitatively evaluated according to the base station data, the acquired base station data can be performance index data aiming at the base station, the acquired performance index data comprises the cell flow and the number of cell connection users of the base station, and therefore, in the process of quantitatively evaluating the service carrying index, the method can be mainly represented as acquiring adjacent base stations of the base station which is accessed to the network, and acquiring the cell flow and the number of cell connection users of cells with different grades in the adjacent base stations; and determining the average value of the cell flow of the adjacent base stations aiming at the cells with different grades and the average value of the number of the cell connection users aiming at the cells with different grades to be used as a pair marking line aiming at the service bearing index.
In practical application, in view of the influence of the location on the base stations in different areas such as urban areas, counties and cities, rural areas and the like, objective differences exist in the aspects of flow, the number of connected users and the like, a unified standard is not suitable for being adopted, but a lowest base line (BaseLine) can be set. The service bearer is also evaluated facing the influence domain, and compared with the peripheral stations, the adjacent base stations in the first layer of the Delaunay triangulation network can be taken as the influence domain.
Considering the influence of the coverage area, the 3 cells of the same base station often have unbalanced traffic, so three opposite lines (ReferenceLine) for high, medium and low traffic are set for the cells with high, medium and low traffic respectively. For example, as shown in fig. 9, an average value of cells with the highest flow rate and the highest number of connected users of each base station in the first-layer adjacent base stations may be taken as a high-traffic cell pair line (referential line _ H); taking the average value of cells with central flow and central number of connected users of each base station in the first layer of adjacent base stations as a middle-service-volume cell pair marking line (ReferenceLine _ M); and taking the average value of the cells with the lowest flow and the lowest number of connected users of each base station in the first layer of adjacent base stations as a low-traffic cell pair line (ReferenceLine _ L).
Then, the service bearing score of each cell in the base station accessing the network for the cell flow and the service bearing score for the number of cell connection users can be obtained, and the service bearing score of the base station accessing the network for the flow and the service bearing score for the number of cell connection users are summed to obtain the score condition of the base station for the service bearing index in the preset time. Specifically, as shown in table 8:
Figure BDA0003744409590000181
table 8 specifically, the scoring condition for the traffic bearer indicator can be as shown in formula (12) and formula (13):
Figure BDA0003744409590000191
Figure BDA0003744409590000192
the service bearing score aiming at the flow is determined based on the cell flow of each cell in the network-accessed base station, a base line and a marking line aiming at the flow, a single score aiming at the service bearing index and an eighth weight, the service bearing score aiming at the cell connection user number is determined based on the cell user connection number of each cell in the network-accessed base station, the base line and the marking line aiming at the cell connection user number, the single score aiming at the service bearing index and the eighth weight, and the obtained eighth weight is related to the cell number.
Illustratively, for a new network access base station, the adjacent base stations in the first layer of the Delaunay triangulation network are taken as the influence domain, and the traffic and the number of connected user pair marked lines of the high, medium and low traffic cells of the adjacent base stations in the first layer are calculated. The traffic line of a high-traffic cell is assumed to be 10 GB/cell/hour, and the number of connected users is 87/cell/hour; the marking line of the medium telephone traffic cell is 5 GB/cell/hour in flow, and the number of connected users is 45/cell/hour; the pair marked lines of the low telephone traffic cell are 2 GB/cell/hour, and the number of the connected users is 15/cell/hour; and the base line is set as the base line according to the minimum requirement, as long as the flow and the user exist, the flow can be 0.1 GB/cell/hour, and the number of connected users is 1/cell/hour.
Then, when the network manager counts a newly-accessed network base station, the flow of the 1 st cell is 12 GB/h, the average number of connected users is 95/h, and the method is suitable for the alignment mark of the high-traffic cell; the flow of the 2 nd cell is 3 GB/h, the average number of connected users is 25/h, and the traffic is marked in application; the flow of the 3 rd cell is 0 GB/h, the average number of connected users is 0/h, and when the method is suitable for the alignment lines of the low-traffic cell, the service bearing audit score is 52.3 points.
Step 405, determining to obtain the scoring condition of the base station for the performance index according to the cell connection success rate, the cell drop rate, the cell switching success rate and the cell channel quality good rate of the base station.
When the performance index is quantitatively evaluated according to the base station data, the acquired base station data can be session statistical data of the base station, and the acquired session statistical data comprises cell connection success rate, cell drop rate, cell switching success rate and cell channel quality goodness rate.
In practical application, key performance is mainly used for evaluating whether each performance index of a newly-accessed base station is normal, the evaluation method is the same as the service bearing, a base line is set and a marking line is quantitatively evaluated in the same way for an influence domain, and the difference is that in the selection of specific indexes, the height of a telephone traffic can not be distinguished on the marking line, and only one marking line pair is arranged. Usually, key performance indexes such as connection success rate, disconnection rate, switching success rate and 5GCQI excellent rate are selected for quantitative evaluation. Setting a lowest base line (BaseLine), wherein the influence domain is the adjacent base stations of the first layer of the Delaunay triangulation network, and taking the average value of the key performance indexes of the adjacent base stations of the first layer as a pair marking line (referenceLine).
And then, acquiring performance scores of each cell in the base station accessing the network respectively aiming at the cell connection success rate, the cell drop rate, the cell switching success rate and the cell channel quality goodness rate, and summing the performance scores of the base station accessing the network aiming at the cell connection success rate, the cell drop rate, the cell switching success rate and the cell channel quality goodness rate to obtain the score condition of the base station aiming at the performance index within preset time. Specifically, as shown in table 9:
Figure BDA0003744409590000201
table 9 specifically, the formula for the score case of the performance index may be as shown in formula (14) and formula (15):
Figure BDA0003744409590000202
Figure BDA0003744409590000203
the performance score aiming at the cell connection success rate is determined based on the cell connection success rate of each cell in the base station accessing the network, a base line and a marking line aiming at the cell connection success rate, a single score aiming at the performance index and a ninth weight; the performance score aiming at the cell drop rate is determined based on the cell drop rate of each cell in the base station accessed to the network, a base line and a pair marking line aiming at the cell drop rate, a single score aiming at the performance index and a ninth weight; the performance score aiming at the cell switching success rate is determined based on the cell switching success rate of each cell in the base station accessing the network, a base line and a marking line aiming at the cell switching success rate, a single score aiming at the performance index and a ninth weight; the performance score for the cell channel quality goodness rate is determined based on the cell channel quality goodness rate of each cell in the networked base station, a baseline and a diagonal line for the cell channel quality goodness rate, a single score for the performance index, and a ninth weight, and the ninth weight is related to the number of cells.
Referring to fig. 10, a schematic view of an application scenario of the network access quality inspection of the base station provided in the embodiment of the present invention is shown, where the application scenario may be a scenario of performing comprehensive quality inspection evaluation on a base station newly accessing a network. In this scenario, assuming that the cells planned by the newly-accessed base station include cell 1, cell 2, and cell 3, the access quality inspection performed may be represented as an evaluation of the situation when the newly-accessed base station performs a service on the planned cells. When the network access quality inspection is carried out on the newly-accessed base station, the network access quality inspection system of the base station is related to, and the network access quality inspection system of the base station comprises a data acquisition module, a quantitative grading module and a quality evaluation module, namely, the newly-accessed base station can be comprehensively and quantitatively evaluated based on the modules of the network access quality inspection system of the base station.
Specifically, the data acquisition module is responsible for acquiring relevant data of a newly-accessed base station, the data acquisition module can mainly acquire the base station data through equipment network management, and the acquired data can include configuration data, fault alarm data, performance index data and other relevant base station data. Besides collecting the relevant data of the base station, the base station access quality inspection system can also be used as a data providing module of the base station access quality inspection system, specifically, the collected relevant base station data can be analyzed, the analyzed data is stored in a big data lake, and the data stored in the big data lake can be used as a data source for quantitative scoring by a quantitative scoring module.
The quantitative scoring module is responsible for constructing a multi-dimensional evaluation model so as to perform comprehensive quantitative evaluation based on the quantitative indexes of different dimensions, and the multi-dimensional evaluation model is mainly constructed aiming at the quantitative indexes of different dimensions, wherein the quantitative indexes of different dimensions can comprise indexes such as equipment online, working states, key parameters, service bearing, key performances and the like. The constructed multidimensional evaluation model can endow a dynamic self-adaptive adjustment mechanism to a weight coefficient, an influence domain-oriented auditing algorithm is constructed based on a triangular network, and a scene self-adaptive auditing algorithm for coordinating a base line and a marking line is adopted, so that auditing can be carried out in the range of the relevant base stations influenced by the newly-accessed 5G base station and the newly-accessed 5G base station during network access quality inspection, and the working condition of the newly-accessed 5G base station is evaluated. It should be noted that, for the process in which the quantitative evaluation module performs quantitative evaluation on the device on-line index, the operating state index, the parameter index, the service bearing index, and the performance index of the base station within the preset time period according to the base station data to obtain the scores of the device on-line index, the operating state index, the parameter index, the service bearing index, and the performance index, and the process in which the total quality inspection score of the base station is obtained based on the scores of the various quantitative indexes, details may refer to the description of the method embodiment, and are not described herein again.
The quantity evaluation module can be equivalent to a quality inspection result output module and is responsible for displaying the quality inspection score of the base station obtained by the quantitative grading module so as to display the quality inspection result of the base station, and when the quality inspection result is displayed, the quality inspection evaluation module can mainly perform quality inspection evaluation from single and overall visual angles so as to comprehensively, objectively and accurately evaluate the newly-accessed 5G base station. In practical application, a single-inspection qualified score line aiming at each quantization index and a total-inspection qualified score line aiming at the total quality inspection score can be set, the quality inspection is qualified when the single inspection and the total inspection are both qualified, otherwise, the quality inspection is unqualified, and the unqualified reason is presented to a user. For example, as shown in fig. 3, when performing quality inspection result display, the relevant result and the short board item may be visually displayed from a radar map or the like, for example, the radar map may be divided into different score lines, score conditions of each quantization index may be drawn based on pentagonal capability distribution conditions, and a total quality inspection score may be displayed in a pentagon drawn for the quantization index; meanwhile, a quantization scale table shown in table 10 can be provided to directly reveal the network access problem of the base station.
Figure BDA0003744409590000221
Watch 10
In the embodiment of the invention, a multidimensional weight self-adaptive quantitative evaluation model is provided through innovation, a quantitative scoring model is constructed from 5 aspects of equipment online, working state, key parameters, service bearing, key performance and the like, sub-item weight coefficients are dynamically and self-adaptively adjusted according to the failure classification condition, and the weight is inclined to a short board project, so that the problem of the short board can be more efficiently found; an influence domain-oriented accurate auditing algorithm is innovatively provided, an influence domain is constructed based on a Delaunay triangulation network, accurate auditing is carried out in the range of the relevant base stations influenced by the newly-accessed 5G base station and influenced by the newly-accessed base station, and the method is more objective, scientific and efficient; an adjacent region auditing algorithm based on a visual angle is innovatively provided, the adjacency relation of a newly-accessed base station is calculated based on a relative angle, 360 degrees are divided into three regions of green, blue and red according to 'seeing and seen', and the partition is applied to strategy to realize accurate identification and auditing of the adjacent region; a baseline + pair marking scene self-adaptive auditing algorithm is innovatively provided, the position difference is adapted, the influence domain-oriented scene self-adaptive pair marking is combined with the baseline based on expert experience, and the key performance auditing of 'one station and one threshold' is realized.
IT should be noted that the base station network access method provided by the embodiment of the present invention has universality, and can implement efficient deployment and application based on a network management data source and an IT technology. The method can be widely applied to mobile communication wireless network construction, particularly current 5G construction, provides comprehensive quality inspection for a new network access base station, avoids network access with diseases, provides strong guarantee for network quality and customer perception, has wide applicability to various communication operators, and has applicability to subsequent evolution networks as long as a cellular network structure is continuously used; the base station network access method provided by the embodiment of the invention can efficiently manage and control 5G construction opening quality, comprehensively, objectively and accurately evaluate the working condition of the newly accessed 5G base station, more efficiently find short board problems, access gateways well, ensure the quality of a wireless network and customer perception, and can be extended to be used for daily monitoring of the 5G wireless network and master the working state and quality of the 5G base station anytime and anywhere.
It should be noted that for simplicity of description, the method embodiments are shown as a series of combinations of acts, but those skilled in the art will recognize that the embodiments are not limited by the order of acts, as some steps may occur in other orders or concurrently in accordance with the embodiments. Further, those of skill in the art will appreciate that the embodiments described in the specification are presently preferred and that no particular act is required to implement the embodiments of the invention.
Referring to fig. 11, a block diagram of a structure of an embodiment of a base station network access quality inspection system according to the present invention is shown, which may specifically include the following modules:
a data obtaining module 1101, configured to obtain base station data of a base station;
a quantization evaluation module 1102, configured to evaluate quantization indexes of different dimensions according to the base station data, so as to obtain a quality inspection score of the base station; the quality inspection score of the base station is determined based on first weight coefficients of quantization indexes of different dimensions, and the first weight coefficients are adaptively adjusted based on the mismatch condition of the quantization indexes of the different dimensions;
and a quality inspection result output module 1103, configured to display the quality inspection score of the network-connected base station, so as to obtain a quality inspection result of the base station.
In one embodiment of the invention, the quality inspection score of the base station comprises a total quality inspection score and a score condition for different quantization indexes; the quantitative evaluation module 1102 may include the following sub-modules:
the first weight coefficient determining submodule is used for acquiring a quality inspection result aiming at the network access base station in a preset time period, determining a first weight coefficient of each quantization index according to the miss-separation condition of each quantization index in the quality inspection result and the miss-separation condition of each quantization index;
the score condition determining submodule is used for acquiring the single scores of the quantization indexes and obtaining the score conditions of the quantization indexes by adopting the single scores of the quantization indexes and the first weight coefficient;
and the total quality inspection score determining submodule is used for summing the score conditions of the quantization indexes to obtain the total quality inspection score of the base station.
In an embodiment of the present invention, the mismatch condition of each quantization index is determined based on an average mismatch of each quantization index, and the first weighting factor determination submodule may include the following units:
the average lost score generating unit is used for generating average lost scores of all quantization indexes in the quality inspection results aiming at the network access base station in a preset time period;
and the first weight coefficient determining unit is used for determining the average lost-divided ratio of each quantization index by adopting the average lost-divided ratio of each quantization index, and taking the average lost-divided ratio of each quantization index as the first weight coefficient of the corresponding quantization index.
In an embodiment of the present invention, the average score loss generating unit may include the following sub-units:
the score condition acquisition subunit is used for acquiring the single score of each quantitative index and according to the score condition of each quantitative index in the quality inspection result of the network access base station in a preset time period;
and the average loss score generation subunit is used for calculating the average loss score of each quantization index by adopting the single score of each quantization index and the score condition of each quantization index in the quality inspection result aimed at in a preset time period.
The scoring condition of each quantitative index in the quality inspection result of the network access base station in the preset time period can be realized by respectively carrying out quantitative evaluation on the equipment on-line index, the working state index, the parameter index, the service bearing index and the performance index of the base station in the preset time period according to the data of the base station to respectively obtain the scoring condition of the equipment on-line index, the working state index, the parameter index, the service bearing index and the performance index. For the detailed calculation process of the score of each quantization index, reference may be made to the description of the method embodiment, which is not repeated herein.
In one embodiment of the invention, the quality inspection score of the base station comprises a total quality inspection score and a score condition for different quantization indexes; the quality inspection result output module 1103 may include the following sub-modules:
the quality inspection result display submodule is used for displaying the total quality inspection score of the base station and the score conditions aiming at different quantization indexes in the base station, and respectively obtaining the quality inspection result of the base station at the total angle and the quality inspection result at the single angle; the quality inspection result at the overall angle is used for evaluating the overall quality audit result when the base station accesses the network, and the quality inspection result at the single angle is used for presenting the specific construction problem of the base station.
The base station network access quality inspection system comprises a data acquisition module, a quantitative evaluation module and a quality inspection result output module, wherein base station data of a base station can be acquired mainly through the data acquisition module, then the quantitative evaluation module evaluates quantitative indexes of different dimensions based on the acquired base station data to obtain quality inspection scores which can be adaptively adjusted based on the mismatch condition of the quantitative indexes of different dimensions, so that the quality inspection scores of the network access base station are displayed through the quality inspection result output module to obtain the quality inspection result of the base station. The acquired base station data are automatically subjected to quantitative evaluation and quality inspection result output through a base station network access quality inspection system, under the condition of avoiding dependence on manual network access quality inspection, network access quality inspection of the base station is comprehensively evaluated from quantitative indexes of different dimensions, and based on a weight coefficient capable of being adaptively adjusted based on a lost-to-classified condition, the specific construction problem of the base station can be presented when the quality inspection result is displayed, and a short board of the constructed base station is exposed, so that the targeted management and control of a 5G base station network access flow is enhanced.
For the device embodiment, since it is basically similar to the method embodiment, the description is simple, and for the relevant points, refer to the partial description of the method embodiment.
An embodiment of the present invention further provides an electronic device, including:
the base station network access quality inspection method comprises a processor, a memory and a computer program which is stored in the memory and can run on the processor, wherein when the computer program is executed by the processor, each process of the base station network access quality inspection method embodiment is realized, the same technical effect can be achieved, and in order to avoid repetition, the description is omitted.
The embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when being executed by a processor, the computer program implements each process of the foregoing base station network access quality inspection method embodiment, and can achieve the same technical effect, and is not described herein again to avoid repetition.
The embodiments in the present specification are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, apparatus, or computer program product. Accordingly, embodiments of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
Embodiments of the present invention are described with reference to flowchart illustrations and/or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing terminal to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing terminal to cause a series of operational steps to be performed on the computer or other programmable terminal to produce a computer implemented process such that the instructions which execute on the computer or other programmable terminal provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications of these embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including the preferred embodiment and all changes and modifications that fall within the true scope of the embodiments of the present invention.
Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "include", "including" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or terminal device including a series of elements includes not only those elements but also other elements not explicitly listed or inherent to such process, method, article, or terminal device. Without further limitation, an element defined by the phrases "comprising one of 8230; \8230;" 8230; "does not exclude the presence of additional like elements in a process, method, article, or terminal device that comprises the element.
The base station network access quality inspection method, the base station network access quality inspection system, the corresponding electronic device and the corresponding computer storage medium provided by the invention are described in detail, specific examples are applied in the text to explain the principle and the implementation mode of the invention, and the description of the above embodiments is only used for helping to understand the method and the core idea of the invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.

Claims (19)

1. A base station network access quality inspection method is characterized by relating to a base station network access quality inspection system, wherein the base station network access quality inspection system comprises a data acquisition module, a quantitative evaluation module and a quality inspection result output module, and the method comprises the following steps:
acquiring base station data of a base station through the data acquisition module;
evaluating the quantization indexes of different dimensions according to the base station data through the quantization evaluation module to obtain the quality inspection score of the base station; the quality inspection score of the base station is determined based on first weight coefficients of quantization indexes of different dimensions, and the first weight coefficients are adaptively adjusted based on the mismatch condition of the quantization indexes of the different dimensions;
and displaying the quality inspection score of the network access base station through the quality inspection result output module to obtain the quality inspection result of the base station.
2. The method of claim 1, wherein the quality test scores of the base stations comprise total quality test scores and score cases for different quantization indexes; the evaluating the quantization indexes of different dimensions according to the base station data to obtain the quality inspection score of the base station comprises the following steps:
obtaining a quality test result aiming at a network access base station in a preset time period, determining a first weight coefficient of each quantization index according to the fraction losing condition of each quantization index in the quality test result and the fraction losing condition of each quantization index;
acquiring the single score of each quantization index, and obtaining the score condition of each quantization index by adopting the single score of each quantization index and the first weight coefficient;
and summing the score conditions of the quantization indexes to obtain the total quality inspection score of the base station.
3. The method according to claim 2, wherein the determining of the fraction lost of each quantization index based on the average fraction lost of each quantization index comprises:
according to the average loss score of each quantitative index in the quality inspection result of the network access base station in the preset time period;
and determining the average lost-divided ratio of each quantization index by adopting the average lost-divided ratio of each quantization index, and taking the average lost-divided ratio of each quantization index as a first weight coefficient of the corresponding quantization index.
4. The method according to claim 3, wherein the average lossless according to each quantization index in the quality inspection result for the network access base station in the preset time period comprises:
acquiring the single score of each quantitative index, and according to the score condition of each quantitative index in the quality inspection result of the network access base station in a preset time period;
and calculating to obtain the average loss score of each quantitative index by adopting the single score of each quantitative index and the score condition of each quantitative index in the quality inspection result aimed at in a preset time period.
5. The method of claim 4, wherein the quantization indices for different dimensions comprise on-device line indices; the base station data comprises configuration data for the base station, wherein the configuration data comprises cell information, equipment information and site planning information;
the obtaining of the score of each quantization index of the base station within the preset network access time according to the base station data includes:
comparing the cell information with the site planning information to obtain a first matching result, and comparing the equipment information with the site planning information to obtain a second matching result;
acquiring an online score condition corresponding to the first matching result and acquiring an online score condition corresponding to the second matching result; determining an online score condition corresponding to the first matching result based on the online quantity of the cells, the single score aiming at the online index of the equipment and a first weight; the online score condition corresponding to the second matching result is determined based on the single score of the online indexes of the equipment and the second weight of the online quantity of the equipment; the first weight is related to the number of the devices on the cell, and the second weight is related to the number of the devices on the cell;
and summing the online score condition corresponding to the first matching result and the score condition corresponding to the second matching result to obtain the score condition of the base station aiming at the online index of the equipment.
6. The method of claim 4, wherein the quantization indices for different dimensions comprise an operating state index; the base station data includes fault alarm data for the base station, the fault alarm data includes alarm information for each cell;
the obtaining of the score condition of each quantization index of the base station within the preset network access duration according to the base station data includes:
acquiring the alarm type of the alarm information of each cell, and determining the working score condition aiming at each cell according to the alarm type; the working score condition is determined based on the number of the cells, the working score condition of each cell under the condition of corresponding fault alarm and a third weight; wherein the third weight is related to the number of cells;
and summing the working score conditions of the cells to obtain the score condition of the base station for the working state index.
7. The method of claim 4, wherein the quantization indices for different dimensions comprise parameter indices; the base station data comprises configuration data for the base station, the configuration data comprising configuration parameters for the base station;
the obtaining of the score condition of each quantization index of the base station within the preset network access duration according to the base station data includes:
determining a second weight coefficient of each configuration parameter according to the failure condition of each configuration parameter in the quality inspection result of the network access base station in a preset time period and according to the failure condition of each configuration parameter;
acquiring the single scores of the configuration parameters of the base station, and obtaining the score condition of each configuration parameter by adopting the single scores of the configuration parameters and the second weight coefficient;
and summing the score conditions of the configuration parameters to obtain the score conditions for the parameter indexes.
8. The method according to claim 7, wherein the determining the fraction loss of each configuration parameter based on the average fraction loss of each configuration parameter and the determining the second weighting factor of each configuration parameter according to the fraction loss of each configuration parameter comprises:
according to the average lost score of each configuration parameter in the quality inspection result aiming at the network access base station in the preset time period;
and determining the average loss-score occupation ratio of each configuration parameter by adopting the average loss score of each configuration parameter, and taking the average loss-score occupation ratio of each configuration parameter as a second weight coefficient of the corresponding configuration parameter.
9. The method according to claim 8, wherein the average lossiness according to each configuration parameter in the quality inspection result for the network access base station in the preset time period comprises:
acquiring the single score of each configuration parameter, and according to the score condition of each configuration parameter in the quality inspection result aiming at the network access base station in a preset time period;
and calculating to obtain the average loss score of each configuration parameter by adopting the single score of each configuration parameter and the score condition of each configuration parameter in the quality inspection result of the network access base station in a preset time period.
10. The method of claim 9, wherein the configuration parameters for the base station comprise a cell identification parameter; the obtaining of the score condition of each configuration parameter of the base station within the preset time of network access according to the configuration parameters includes:
constructing a triangular network by taking a base station which is accessed to the network as a center; the constructed triangulation network is used for determining an influence domain aiming at the cell identification parameter;
acquiring the cell identification multiplexing condition of the adjacent base station in the influence domain; the cell identifier multiplexing condition is determined based on the first cell identifier multiplexing layer number and the second cell identifier multiplexing layer number;
obtaining a score condition corresponding to the number of the first cell identifier multiplexing layers and a score condition corresponding to the number of the second cell identifier multiplexing layers; the score condition corresponding to the first cell identifier multiplexing layer number is determined based on the cell number, the single score of the cell identifier parameter, a preset score value range threshold, the multiplexing score aiming at the first cell identifier multiplexing layer number and a fourth weight; the score condition corresponding to the second cell identifier multiplexing layer number is determined based on the cell number, the single score of the cell identifier parameter, a preset score value range threshold, the multiplexing score aiming at the second cell identifier multiplexing layer number and a fifth weight; the fourth weight is related to the number of cells for the base station, the fifth weight is related to the number of cells for the base station, the multiplexing score of the multiplexing layer number of the first cell identifier is positively related to the multiplexing layer number of the first cell identifier, and the multiplexing score of the multiplexing layer number of the second cell identifier is positively related to the multiplexing layer number of the second cell identifier;
and summing the score condition corresponding to the first cell identification multiplexing layer number and the score condition corresponding to the second cell identification multiplexing layer number to obtain the score condition of the base station for the cell identification parameters.
11. The method of claim 9, wherein the configuration parameters for the base station comprise access channel parameters; the obtaining of the score condition of each configuration parameter of the base station within the preset time of network access according to the configuration parameters includes:
constructing a triangular network by taking a base station which is accessed to the network as a center; the constructed triangulation network is used for determining the influence domain aiming at the access channel parameters;
acquiring the multiplexing condition of access channels of adjacent base stations in the influence domain; the multiplexing condition of the access channel is determined based on the multiplexing layer number of the access channel;
acquiring a single score for the access channel parameter, a preset score value range threshold, a multiplexing score for the number of multiplexing layers of the access channel, and a sixth weight for the number of multiplexing layers of the access channel; the sixth weight is related to a number of cells for a base station; wherein, the multiplexing gain of the access channel multiplexing layer number is positively correlated with the access channel multiplexing layer number;
and obtaining the score condition aiming at the access channel parameters by adopting the individual scores of the cell identification parameters, a preset score value range threshold value, the multiplexing scores aiming at the number of the access channel multiplexing layers and the sixth weight based on the number of the cells.
12. The method of claim 9, wherein the configuration parameters for the base station comprise tracking area parameters; the obtaining of the score condition of each configuration parameter of the base station within the preset time of network access according to the configuration parameters includes:
acquiring tracking area parameters of a base station which is accessed to the network and acquiring a tracking area parameter set of an adjacent base station in the influence domain;
if the tracking area parameters of the network-accessed base station do not belong to the tracking area parameter set of the adjacent base station in the influence domain, calculating the score condition aiming at the tracking area parameters as zero;
and/or if the tracking area parameters of the network-accessed base station belong to the tracking area parameter set of the adjacent base station in the influence domain, determining that the single score aiming at the tracking area parameters is the score condition aiming at the tracking area parameters.
13. The method of claim 9, wherein the configuration parameters for the base station comprise neighbor cell parameters; the obtaining of the score condition of each configuration parameter of the base station within the preset time of network access according to the configuration parameters includes:
acquiring azimuth angle information of a base station accessed to the network and an adjacent base station by taking the base station accessed to the network as a center; the azimuth information comprises a cell azimuth of a base station accessing the network, a cell azimuth of an adjacent base station in an influence domain, an azimuth of an adjacent station relative to a main cell and an azimuth of the main cell relative to the adjacent station;
determining a necessary neighbor set based on mutual difference between the azimuth information of each network-accessing base station and the adjacent base station;
acquiring the single score of the neighbor cell parameters, the proportion of the number of neighbor cells in the intersection of the necessary neighbor cell set and the configured neighbor cell set to the number of neighbor cells in the necessary neighbor cell set, and a seventh weight; the seventh weight is related to a number of cells;
and obtaining the score condition aiming at the neighbor cell parameters by adopting the single score of the neighbor cell parameters, the proportion of the number of the neighbor cells in the intersection of the necessary neighbor cell set and the configured neighbor cell set to the number of the neighbor cells in the necessary neighbor cell set and the seventh weight.
14. The method of claim 4, wherein the quantization indexes of different dimensions comprise traffic bearer indexes; the base station data comprises performance index data aiming at the base station, and the performance index data comprises cell flow of the base station and the number of cell connection users;
the obtaining of the score condition of each quantization index of the base station within the preset network access duration according to the base station data includes:
acquiring adjacent base stations of a base station accessing a network, and acquiring cell flow and the number of cell connection users of cells of different grades in the adjacent base stations;
determining the average value of the cell flow of the adjacent base stations aiming at the cells with different grades as a pair marking line, and determining the average value of the number of the cell connection users aiming at the cells with different grades as the pair marking line;
acquiring service bearing scores of each cell in a base station accessing a network aiming at cell flow and service bearing scores aiming at the number of cell connection users; the service bearing score aiming at the flow is determined based on the cell flow of each cell in the base station accessing the network, a base line and a calibration line aiming at the flow, a single score aiming at the service bearing index and an eighth weight, and the service bearing score aiming at the number of cell connecting users is determined based on the number of cell user connections of each cell in the base station accessing the network, the base line and the calibration line aiming at the number of cell connecting users, the single score aiming at the service bearing index and the eighth weight; wherein the eighth weight is related to the number of cells;
and summing the service bearing score of the network-accessed base station for the flow and the service bearing score for the number of cell connection users to obtain the score condition of the base station for the service bearing index.
15. The method of claim 4, wherein the quantization indexes of different dimensions comprise performance indexes; the base station data comprises session statistical data aiming at the base station, wherein the session statistical data comprises a cell connection success rate, a cell disconnection rate, a cell switching success rate and a cell channel quality goodness rate;
the obtaining of the score condition of each quantization index of the base station within the preset network access duration according to the base station data includes:
acquiring a first layer of adjacent base stations of a base station which is accessed to a network, acquiring the cell connection success rate, the cell disconnection rate, the cell switching success rate and the cell channel quality goodness rate of each cell in the adjacent base stations, and determining the average value of the cell connection success rate, the cell disconnection rate, the cell switching success rate and the cell channel quality goodness rate of each cell in the adjacent base stations as a pair mark line;
acquiring performance scores of each cell in a base station accessing a network respectively aiming at cell connection success rate, cell disconnection rate, cell switching success rate and cell channel quality good rate; the performance score for the cell connection success rate is determined based on the cell connection success rate of each cell in the network-accessed base station, a baseline and a pair marking for the cell connection success rate, a single score for the performance index and a ninth weight, the performance score for the cell drop rate is determined based on the cell drop rate of each cell in the network-accessed base station, a baseline and a pair marking for the cell drop rate, a single score for the performance index and a ninth weight, the performance score for the cell handover success rate is determined based on the cell handover success rate of each cell in the network-accessed base station, a baseline and a pair marking for the cell handover success rate, a single score for the performance index and a ninth weight, and the performance score for the cell channel quality goodness rate is determined based on the cell channel quality goodness rate of each cell in the network-accessed base station, a baseline and a pair marking for the cell channel quality goodness rate, a single score and a ninth weight for the performance index; wherein the ninth weight is related to a number of cells;
and summing the performance scores of the network-accessed base station aiming at the cell connection success rate, the cell disconnection rate, the cell switching success rate and the cell channel quality good rate to obtain the score condition of the base station aiming at the performance index.
16. The method of claim 1, wherein the quality test scores of the base stations comprise total quality test scores and score cases for different quantization indexes; the step of displaying the quality inspection score of the base station to obtain the quality inspection result of the base station comprises the following steps:
displaying the total quality inspection score of the base station and the score conditions aiming at different quantization indexes in the base station, and respectively obtaining the quality inspection result of the base station at the total angle and the quality inspection result at the single angle; the quality inspection result at the overall angle is used for evaluating the overall quality audit result of the base station when the base station accesses the network, and the quality inspection result at the single angle is used for presenting the specific construction problem of the base station.
17. A network access quality inspection system for a base station, the system comprising:
the data acquisition module is used for acquiring base station data of a base station;
the quantitative evaluation module is used for evaluating the quantitative indexes with different dimensions according to the base station data to obtain the quality inspection score of the base station; the quality inspection score of the base station is determined based on first weight coefficients of quantization indexes of different dimensions, and the first weight coefficients are adaptively adjusted based on the mismatch condition of the quantization indexes of the different dimensions;
and the quality inspection result output module is used for displaying the quality inspection score of the network access base station to obtain the quality inspection result of the base station.
18. An electronic device, comprising: processor, memory and computer program stored on the memory and capable of running on the processor, the computer program when executed by the processor implementing the steps of the base station network access quality inspection method according to any of claims 1-16.
19. A computer-readable storage medium, wherein a computer program is stored on the computer-readable storage medium, and when executed by a processor, the computer program implements the steps of the network access quality inspection method for the base station according to any one of claims 1 to 16.
CN202210820971.5A 2022-07-13 2022-07-13 Base station network access quality inspection method, system, equipment and storage medium Pending CN115334528A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116634473A (en) * 2023-07-21 2023-08-22 中国铁塔股份有限公司云南省分公司 Method and device for predicting failure of power failure and service withdrawal of wireless station

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116634473A (en) * 2023-07-21 2023-08-22 中国铁塔股份有限公司云南省分公司 Method and device for predicting failure of power failure and service withdrawal of wireless station
CN116634473B (en) * 2023-07-21 2023-10-10 中国铁塔股份有限公司云南省分公司 Method and device for predicting failure of power failure and service withdrawal of wireless station

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