Mobile network scene operation and maintenance management method and device

By analyzing multi-source data sets of mobile network scenarios, identifying and evaluating cell grids, dividing related cell sets, and calculating health under the service indicator dimension, the accuracy of mobile network scenario assessment and differentiated resource allocation issues are solved, thereby improving network operation quality and user experience.

CN119789131BActive Publication Date: 2025-10-21CHINA TELECOM CORP LTD
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Patent Information

Application Number
CN202411983201.8
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2024-12-30
Publication Date
2025-10-21
Estimated Expiration
2044-12-30

AI Technical Summary

Technical Problem

Existing technologies are unable to accurately evaluate the traffic volume and network quality of mobile network scenarios, resulting in low accuracy and high cost in scene quality improvement. In addition, the evaluation method cannot differentiate resource allocation by scenario category.

Method used

By acquiring multi-source data sets in the target area, including scene layer data, basic engineering parameter data, and operation and maintenance data, the cell grids within the mobile network scene are identified and evaluated. Combined with MR recording information, the associated cell sets are divided, and the scene operation and maintenance health under multiple business indicator dimensions is calculated, and differentiated management is performed.

Benefits of technology

The accuracy and efficiency of mobile network scenario operation evaluation have been improved, and differentiated resource allocation can be carried out according to scenario categories, thereby improving network operation quality and user experience.

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Abstract

The application discloses a mobile network scene operation and maintenance management method and device. The method comprises the following steps: obtaining a target data set of a target area in a preset time period, wherein the target data set at least comprises a scene layer data set, a basic parameter data set of each cell in the target area, and an operation and maintenance data set; determining at least one cell in each mobile network scene according to the target data set; for each mobile network scene, determining a scene operation and maintenance health degree of the mobile network scene in multiple business index dimensions according to the operation and maintenance data set of each cell in the mobile network scene, wherein the business index dimensions comprise at least one of the following: a coverage dimension, a perception dimension, a quality dimension, and an efficiency dimension; and performing a management operation on each mobile network scene according to the scene operation and maintenance health degree. The application solves the technical problem that related technologies can only qualitatively evaluate the mobile network scene, and cannot comprehensively and quantitatively evaluate the operation of the mobile network scene.
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Description

Technical Field

[0001] The present application relates to the field of wireless communication technology, and more specifically, to a method and device for managing mobile network scenario operation and maintenance. Background Art

[0002] To build a high-quality mobile network with excellent signal quality, superior user experience, and robust capabilities, scenario assessment is paramount. Currently, scenario assessment primarily uses wireless network elements (associated cells) surrounding the scenario, aggregating metrics at the eNodeB / gNodeB base station and cell levels. However, because wireless base stations / cells have a coverage radius of 300m-2000m and typically cover other surrounding buildings, directly aggregating metrics using network element metrics will include services outside the scenario, resulting in overstated traffic volume and an inability to accurately represent the target scenario's traffic volume and network quality. This discrepancy is particularly pronounced in smaller scenarios, such as government centers and business hotels, impacting the accuracy, efficiency, and cost of scenario quality improvement.

[0003] Furthermore, traditional mobile network evaluation methods rely primarily on network optimization engineers evaluating a scenario based on single dimensions such as coverage, speed, and traffic. The evaluation results are then compared against fixed thresholds to determine if the scenario is qualified. Consequently, traditional mobile network evaluation methods are unable to comprehensively and quantitatively assess the operational performance of mobile network scenarios, and the evaluation criteria cannot be differentiated by scenario type or resource allocation.

[0004] To address the above-mentioned problems, no effective solutions have been proposed so far. Summary of the Invention

[0005] The embodiments of the present application provide a method and device for mobile network scenario operation and maintenance management, so as to at least solve the technical problem that the relevant technology can only perform qualitative evaluation of mobile network scenarios, but cannot comprehensively and quantitatively evaluate the operation status of mobile network scenarios.

[0006] According to one aspect of an embodiment of the present application, a mobile network scenario operation and maintenance management method is provided, including: obtaining a target data set of a target area within a preset time period, wherein the target data set includes at least: a scene layer data set for reflecting different mobile network scenario information of the target area, a basic engineering parameter data set for reflecting the physical location information of each cell in the target area, and an operation and maintenance data set for reflecting MR recording information of each cell in the target area; determining at least one cell in each mobile network scenario based on the target data set; for each mobile network scenario, determining the scenario operation and maintenance health of the mobile network scenario under multiple business indicator dimensions based on the operation and maintenance data sets of each cell in the mobile network scenario, wherein the business indicator dimensions include at least one of the following: coverage dimension, perception dimension, quality dimension, and efficiency dimension; and performing management operations on each mobile network scenario based on the scenario operation and maintenance health.

[0007] Optionally, at least one cell in each mobile network scenario is determined based on the target data set, including: for each cell in the target area, rasterizing the cell to obtain multiple cell grids, and determining the grid longitude and latitude coordinates of each cell grid based on the basic engineering parameter data of the cell; determining the area of ​​each cell grid in the service area of ​​different mobile network scenarios based on the scene layer data set and the basic engineering parameter data set of the cell; determining the first number of MR recording information of each cell grid in each mobile network scenario based on the operation and maintenance data set of the cell and the grid longitude and latitude coordinates of each cell grid in the cell; for each cell grid in the cell, when the area of ​​the cell grid in the service area of ​​the target mobile network scenario is not less than a preset area threshold, and the first number of MR recording information of the cell grid in the target mobile network scenario is not less than a preset second threshold, it is determined that the cell corresponding to the cell grid is in the service area of ​​the mobile network scenario.

[0008] Optionally, the operation and maintenance data set includes at least: multiple MR record information based on the assisted global satellite positioning system reported by multiple mobile terminals in the cell within a preset time period, and the MR record information includes at least one of the following: a TA value, an RSRP value, wherein the first number of MR record information of each cell grid in each mobile network scenario is determined based on the operation and maintenance data set of the cell and the grid longitude and latitude coordinates of each cell grid in the cell, including: determining the longitude and latitude coordinates of the mobile terminal that reports each MR record information in the cell in each mobile network scenario based on the operation and maintenance data set of the cell; determining the MR record information of each cell grid in each mobile network scenario based on the matching result of the longitude and latitude coordinates of the mobile terminal with the grid longitude and latitude coordinates of each cell grid, counting the MR record information of each cell grid in each mobile network scenario, and obtaining the first number of MR record information of the cell grid in each mobile network scenario.

[0009] Optionally, the basic engineering parameter data set includes at least: the longitude and latitude coordinates of the cell, and the scene layer data set includes at least: the coverage areas of different mobile network scenarios. Before determining the scene operation and maintenance health of the mobile network scenario under multiple business indicator dimensions based on the operation and maintenance data set of each cell in the mobile network scenario, the method also includes: for each mobile network scenario, judging whether the longitude and latitude coordinates of any cell in the mobile network scenario are completely within the service area of ​​the mobile network scenario based on the scene layer data set and the basic engineering parameter data set of the cell; if so, determining that the cell belongs to the first associated cell set of the mobile network scenario; if not, determining the MR record information in each cell grid of the cell in the mobile network scenario based on the scene layer data set and the operation and maintenance data set of the cell The method further comprises the steps of: determining a second number of MR recorded information in each cell grid of the cell within the mobile network scenario and determining whether a first ratio of the second number to the first number of MR recorded information in each cell grid of the cell is not lower than a preset third threshold; if so, determining that the cell belongs to a second associated cell set of the mobile network scenario; if not, determining whether a second ratio of the sum of the second number of MR recorded information in each cell grid of the cell within the mobile network scenario to the sum of the first number of MR recorded information in each cell grid of the cell is greater than a preset fourth threshold and whether the first ratio is not lower than a preset fifth threshold, wherein the fifth threshold is less than the third threshold; if so, determining that the cell belongs to a third associated cell set of the mobile network scenario; wherein the association level of the first associated cell set is higher than that of the second associated cell set, and the association level of the second associated cell set is higher than that of the third associated cell set.

[0010] Optionally, the scene operation and maintenance health of the mobile network scene under multiple business indicator dimensions is determined based on the operation and maintenance data set of each cell in the mobile network scene, including: determining the business indicator quantity of the mobile network scene under multiple business indicator dimensions based on the operation and maintenance data set of each cell in the mobile network scene and the association level of the associated cell set of the mobile network scene to which each cell belongs, wherein the business indicator quantity includes at least one of the following: MR coverage rate and weakly associated cell grid proportion corresponding to the coverage dimension, access success rate, drop rate, switching success rate, and business excellence rate corresponding to the quality dimension, business data volume corresponding to the efficiency dimension, and transmission rate and complaint rate corresponding to the perception dimension; determining the business indicator quantity of the mobile network scene under multiple business indicator dimensions based on the relationship between the business indicator quantity of the mobile network scene under multiple business indicator dimensions and the indicator threshold value corresponding to each business indicator dimension. Scores of mobile network scenarios under multiple business indicator dimensions, wherein the scores under multiple business indicator dimensions include at least one of the following: a first score under the coverage sub-dimension corresponding to the MR coverage rate, a second score under the weak correlation sub-dimension corresponding to the weak correlation cell grid ratio, a third score under the access sub-dimension corresponding to the access success rate, a fourth score under the retention sub-dimension corresponding to the drop rate, a fifth score under the mobility sub-dimension corresponding to the switching success rate, a sixth score under the service quality sub-dimension corresponding to the service excellence rate, a seventh score under the efficiency dimension corresponding to the service data volume, an eighth score under the rate sub-dimension corresponding to the transmission rate, and a ninth score under the complaint sub-dimension corresponding to the complaint rate; the scenario operation and maintenance health of the mobile network scenario under multiple business indicator dimensions is determined based on the scores of the mobile network scenario under each business indicator dimension.

[0011] Optionally, the score of the mobile network scenario in multiple business indicator dimensions is determined based on the size relationship between the business indicator quantities of the mobile network scenario in multiple business indicator dimensions and the indicator thresholds corresponding to each business indicator dimension, including: judging the size relationship between the MR coverage rate and the preset coverage rate threshold; when the MR coverage rate is not less than the coverage rate threshold, determining the first score of the mobile network scenario in the coverage rate sub-dimension as full score; when the MR coverage rate is less than the coverage rate threshold, determining the difference between the coverage rate threshold and the MR coverage rate of the mobile network scenario, and determining the score obtained by multiplying the ratio of the difference to the preset adjustment coefficient by the full score, and taking the maximum value between the difference between the full score and the score and zero as the first score of the mobile network scenario in the coverage rate sub-dimension.

[0012] Optionally, based on the size relationship between the business indicator amount of the mobile network scenario under multiple business indicator dimensions and the indicator threshold corresponding to each business indicator dimension, the score of the mobile network scenario under multiple business indicator dimensions is determined, including: determining the MR coverage rate of the cell grid of each cell in the mobile network scenario, and taking the cell grid with an MR coverage rate less than the coverage rate threshold as a weakly associated cell grid; counting the number of all weakly associated cell grids in the mobile network scenario and the number of all cell grids in the mobile network scenario, and determining the proportion of weakly associated cell grids in the mobile network scenario; judging the proportion of weakly associated cell grids and the predicted The relationship between the first full score threshold value and the preset first zero score threshold value; when the proportion of weakly associated cell grids is not higher than the first full score threshold value, the second score of the mobile network scenario in the weak association sub-dimension is determined to be full score; when the proportion of weakly associated cell grids is higher than the first full score threshold value, the ratio of the difference between the proportion of weakly associated cell grids in the mobile network scenario and the first full score threshold value and the difference between the first zero score threshold value and the first full score threshold value is determined, and the maximum value between the difference between the full score and the product of the ratio and the full score and zero score is taken as the second score of the mobile network scenario in the weak association sub-dimension.

[0013] Optionally, the score of the mobile network scenario in multiple business indicator dimensions is determined based on the size relationship between the business indicator amount of the mobile network scenario in multiple business indicator dimensions and the indicator threshold value corresponding to each business indicator dimension, including: for each business indicator amount corresponding to the quality dimension, judging the size relationship between the business indicator amount and a preset second full score threshold value and a preset second zero score threshold value, wherein the business indicator amount is any one of the access success rate, the drop rate, the handover success rate, and the business excellence rate; when the business indicator amount is not less than the second full score threshold value, determining that the score of the mobile network scenario in the quality dimension is full score; when the business indicator amount is less than the second zero score threshold value, determining that the mobile network scenario The score under the quality dimension is zero; when the service indicator quantity is less than the second full score threshold value and not less than the second zero score threshold value, determine the ratio between the difference between the second full score threshold value and the service indicator quantity of the mobile network scenario and the difference between the second full score threshold value and the second zero score threshold value, and take the maximum value between the difference between the full score minus the product of the ratio and the full score and zero as the score of the mobile network scenario under the quality dimension; wherein, the score of the mobile network scenario under the quality dimension includes: the third score of the access sub-dimension corresponding to the access success rate, the fourth score of the retention sub-dimension corresponding to the drop rate, the fifth score of the mobility sub-dimension corresponding to the switching success rate, and the sixth score of the service quality sub-dimension corresponding to the service excellence rate.

[0014] Optionally, the score of the mobile network scenario in multiple business indicator dimensions is determined based on the size relationship between the business indicator amount of the mobile network scenario in multiple business indicator dimensions and the indicator threshold value corresponding to each business indicator dimension, including: determining the weight coefficient of each cell in the mobile network scenario based on the first ratio of each cell grid in each cell in the mobile network scenario and the association level of the associated cell set of the mobile network scenario to which each cell belongs; taking the weighted sum of the weight coefficient of each cell and the preset efficiency threshold as the scene efficiency threshold of the mobile network scenario; taking the product of the ratio of the business data volume of the mobile network scenario and the scene efficiency threshold and the full score, and the minimum value between the full scores as the seventh score of the mobile network scenario in the efficiency dimension.

[0015] Optionally, the score of the mobile network scenario in multiple business indicator dimensions is determined based on the size relationship between the business indicator amount of the mobile network scenario in multiple business indicator dimensions and the indicator threshold value corresponding to each business indicator dimension, including: judging the size relationship between the transmission rate of the mobile network scenario in different frequency bands and bandwidths and the preset third full score threshold value and the third zero score threshold value; when the transmission rate of the mobile network scenario in a single frequency band and bandwidth is not lower than the third full score threshold value, determining that the score of the rate sub-dimension of the mobile network scenario in a single frequency band and bandwidth is full score; when the transmission rate of the mobile network scenario in a single frequency band and bandwidth is lower than the third zero score threshold value , determine that the score of the rate sub-dimension of the mobile network scenario in a single frequency band and bandwidth is zero; when the transmission rate of the mobile network scenario in the frequency band and bandwidth is lower than the third full score threshold but not lower than the third zero score threshold, determine the ratio between the difference between the third full score threshold and the transmission rate of the mobile network scenario and the difference between the third full score threshold and the third zero score threshold, and take the maximum value between the difference between the full score and the product of the ratio and the full score and zero as the score of the rate sub-dimension of the mobile network scenario in a single frequency band and bandwidth; take the average of the scores of the rate sub-dimension of the mobile network scenario in each frequency band and bandwidth as the eighth score of the mobile network scenario in the rate sub-dimension.

[0016] Optionally, the score of the mobile network scenario in multiple business indicator dimensions is determined based on the size relationship between the business indicator quantity of the mobile network scenario in multiple business indicator dimensions and the indicator threshold value corresponding to each business indicator dimension, including: judging the size relationship between the complaint rate of the mobile network scenario and the preset fourth full score threshold value and the fourth zero score threshold value; when the complaint rate of the mobile network scenario is not lower than the fourth full score threshold value, determining the ninth score of the mobile network scenario in the complaint sub-dimension as full score; when the complaint rate of the mobile network scenario is lower than the fourth full score threshold value, determining the ratio between the difference between the complaint rate of the mobile network scenario and the fourth full score threshold value and the difference between the fourth zero score threshold value and the fourth full score threshold value, and taking the maximum value between the difference between the full score minus the product of the ratio and the full score and zero score as the ninth score of the mobile network scenario in the complaint sub-dimension.

[0017] Optionally, management operations are performed on each mobile network scenario based on the scenario operation and maintenance health, including: determining abnormal mobile network scenarios whose scenario operation and maintenance health of each mobile network scenario is lower than a preset health threshold; optimizing and managing the abnormal mobile network scenarios according to a preset optimization strategy, wherein the optimization strategy includes at least one of the following: network expansion, resource scheduling, and parameter optimization.

[0018] According to another aspect of an embodiment of the present application, a mobile network scenario operation and maintenance management device is also provided, including: an acquisition module for acquiring a target data set of a target area within a preset time period, wherein the target data set includes at least: a scene layer data set for reflecting different mobile network scenario information of the target area, a basic engineering parameter data set for reflecting the physical location information of each cell in the target area, and an operation and maintenance data set for reflecting the measurement report MR record information of each cell in the target area; a determination module for determining at least one cell in each mobile network scenario based on the target data set; an evaluation module for determining, for each mobile network scenario, the scenario operation and maintenance health of the mobile network scenario under multiple business indicator dimensions based on the operation and maintenance data sets of each cell in the mobile network scenario, wherein the business indicator dimension includes at least one of the following: coverage dimension, perception dimension, quality dimension, and efficiency dimension; a management module for performing management operations on each mobile network scenario based on the scenario operation and maintenance health.

[0019] According to another aspect of an embodiment of the present application, a computer program product is further provided, which includes: a computer program, wherein when the computer program is executed by a processor, the above-mentioned mobile network scenario operation and maintenance management method is implemented.

[0020] According to another aspect of an embodiment of the present application, an electronic device is further provided, which includes: a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to execute the above-mentioned mobile network scenario operation and maintenance management method through the computer program.

[0021] In an embodiment of the present application, by analyzing and processing multi-source data sets collected within a preset time period in a target area, the service cells within each mobile network scenario are identified. Furthermore, by analyzing relevant information about the service cells within a single mobile network scenario, the comprehensive scenario operation and maintenance health of the single mobile network scenario is accurately assessed from multiple business indicator dimensions, thereby achieving the goal of improving the accuracy, efficiency, and differentiation capability of mobile network scenario operation evaluation. Furthermore, by managing and operating the mobile network scenario based on its scenario operation and maintenance health, the network can be efficiently and targetedly managed and optimized to improve network operation quality and user experience. This solves the technical problem that related technologies can only perform qualitative evaluations of mobile network scenarios, but cannot comprehensively and quantitatively evaluate the operational status of mobile network scenarios. It also avoids the problem that, due to the uniformity of evaluation standards, differentiated evaluations cannot be performed based on scenario categories or resource allocations. This solves the technical problem that related technologies can only perform qualitative evaluations of mobile network scenarios, but cannot comprehensively and quantitatively evaluate the operational status of mobile network scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0023] Figure 1 This is a flow chart of an optional mobile network scenario operation and maintenance management method according to an embodiment of the present application;

[0024] Figure 2 1 is a schematic structural diagram of an optional mobile network scenario operation and maintenance management device according to an embodiment of the present application;

[0025] Figure 3 It is a schematic structural diagram of an optional electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this application.

[0027] It should be noted that the terms "first", "second", etc. in the specification, claims, and drawings of the present application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products, or devices.

[0028] In order to better understand the embodiments of the present application, some nouns or terms that appear in the description of the embodiments of the present application are first translated and explained as follows:

[0029] MR (Measurement Report): This refers to information sent every 480ms on the traffic channel (470ms on the signaling channel). This data can be used for network evaluation and optimization. MR is typically performed by the Mobile Station (MS) and the Base Transceiver Station (BTS). The MS performs and reports the GSM cell's downlink power level, quality, and TA, while the BTS performs and reports the uplink MS's reception power level and quality. MR processing is typically performed in the base station controller (when BTS preprocessing methods are used, MR processing can be moved down to the BTS). It provides basic filtering, interpolation, and other functions, providing the basic input for subsequent handover decision algorithms and forming the foundation for handover decision algorithms and power control algorithms.

[0030] Time Advanced (TA): The maximum time advance (TA) is the difference between the actual arrival time of a mobile station's signal at the base station and the arrival time assumed to be zero distance from the base station. The base station continuously monitors the arrival time of mobile station signals and sends TA commands on the downlink SACCH (Slow Associated Control Channel) based on changes in arrival time.

[0031] RSRP (Reference Signal Received Power): A key parameter that represents wireless signal strength in LTE (Long Term Evolution) networks and one of the physical layer measurement requirements. It is the average of the received signal power on all resource elements carrying the reference signal within a symbol.

[0032] Example 1

[0033] According to an embodiment of the present application, a mobile network scenario operation and maintenance management method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0034] Figure 1 This is a flow chart of a mobile network scenario operation and maintenance management method provided according to an embodiment of the present application, such as Figure 1 As shown, the method includes steps S102-S108, wherein:

[0035] Step S102: obtaining a target data set of a target area within a preset time period.

[0036] In the technical solution provided in step S102 above, the target dataset is a multi-source dataset collected and integrated, including but not limited to a scene layer dataset, a basic engineering parameter dataset, and an operation and maintenance dataset.

[0037] A scene layer dataset refers to a collection of information describing different mobile network scenarios in the target area (i.e., scenarios applied by 4G or 5G networks, such as schools, subways, high-efficiency networks, and urban villages). The dataset includes relevant label information such as scene type, scene name, scene range outline set (such as WKT format data), scene code, center longitude and latitude, etc.

[0038] The basic engineering parameter data set records the physical location and technical parameters of each service cell in the target area, covering information such as city, district, county, base station number, cell number, cell name, longitude, latitude, network type, construction operator, frequency band, bandwidth, and coverage type.

[0039] The operation and maintenance data set is a collection of network operation status data of each service cell in the target area within a preset time period, including coverage data (such as 4 / 5GMR grid, total number of MRs, number of MRs at each threshold, such as the number of MRs greater than -105dBm), wireless network performance data (such as number of access times, number of dropped calls, switching success rate, etc.), efficiency data (service traffic, call volume), perception data (such as 5G user traffic, uplink and downlink rates, and user complaints at 4G sites), and other information.

[0040] These data sets together constitute the above-mentioned target data set to provide basic data support for the evaluation of subsequent scenario traffic and network quality.

[0041] Step S104: determining at least one cell in each mobile network scenario according to the target data set.

[0042] In the technical solution provided in the above step S104, by analyzing the scene layer dataset, the basic engineering parameter dataset and the operation and maintenance dataset of each cell in the target dataset, it is determined which mobile network scene coverage service cell each cell in the target area belongs to.

[0043] Step S106 : For each mobile network scenario, the scenario operation and maintenance health of the mobile network scenario in multiple service indicator dimensions is determined based on the operation and maintenance data set of each cell in the mobile network scenario.

[0044] In the technical solution provided in step S106 above, all cells within a specific mobile network scenario are analyzed to determine scores for the mobile network scenario across different service indicator dimensions, where the service indicator dimensions include at least one of the following: coverage, perception, quality, and efficiency. The operational health of the mobile network scenario is then determined based on the scores across these service indicator dimensions.

[0045] Step S108: Perform management operations on each mobile network scenario based on the scenario operation and maintenance health.

[0046] In the technical solution provided in the above step S108, each mobile network scenario is sorted based on the operation and maintenance health of the above scenario to determine the mobile network scenario with lower health, and the mobile network scenario with lower health is optimized to improve the network operation quality and user experience, while optimizing resource allocation and improving operational efficiency.

[0047] Based on the technical solution provided by the above steps S102-S108, it can be seen that in the embodiment of the present application, by analyzing and processing the multi-source data set collected in the target area within a preset time period to identify the service cells in each mobile network scenario, and by analyzing the relevant information of the service cells in a single mobile network scenario, the comprehensive scenario operation and maintenance health of the single mobile network scenario is accurately evaluated from multiple business indicator dimensions, thereby achieving the purpose of improving the accuracy, efficiency and differentiation capability of the mobile network scenario operation evaluation; in addition, the mobile network scenario is managed and operated according to the scenario operation and maintenance health of the mobile network scenario, which can efficiently and specifically manage and optimize the network to improve the network operation quality and user experience. This solves the technical problem that the relevant technology can only perform qualitative evaluation of mobile network scenarios, but cannot comprehensively and quantitatively evaluate the operation status of mobile network scenarios. At the same time, it can also avoid the problem that the evaluation standard is unified, resulting in the inability to perform differentiated evaluation according to scenario category and resource allocation.

[0048] The following describes the various steps of the mobile network scenario operation and maintenance management method in conjunction with the specific implementation process.

[0049] As an optional implementation, in the technical solution provided in step S104 above, each cell in the target area is traversed, and the following analysis is performed on each cell to determine the ownership of the cell, including:

[0050] Step S1041, rasterize the cell to obtain multiple cell grids, and determine the grid longitude and latitude coordinates of each cell grid based on the basic engineering parameter data of the cell; determine the area of ​​each cell grid in the service area of ​​different mobile network scenarios based on the scene layer dataset and the basic engineering parameter dataset of the cell; determine the first number of MR recording information of each cell grid in each mobile network scenario based on the operation and maintenance dataset of the cell and the grid longitude and latitude coordinates of each cell grid in the cell.

[0051] The above step S1041 can be understood as: first, the cell coverage area is divided into a series of uniformly sized cell grids (such as a grid of 20m*20m in size) according to the basic engineering parameter data of each cell, and the longitude and latitude coordinates of each cell grid are determined to facilitate subsequent geographic information matching and data analysis; then, the scene contour information in the scene layer dataset is used to determine whether the cell grid is located in the service area of ​​different mobile network scenarios. If so, the area of ​​the region where the cell grid overlaps with the scene contour is calculated; at the same time, the first number of MR recording information of each cell grid in each mobile network scenario is determined based on the cell's operation and maintenance dataset and the grid longitude and latitude coordinates of each cell grid in the cell.

[0052] Specifically, the operation and maintenance data set of each cell includes at least: multiple MR record information based on the Assisted Global Positioning System (AGPS) reported by multiple mobile terminals in the cell within a preset time period, and the MR record information includes at least one of the following: TA value and RSRP value. Therefore, in the embodiment of the present application, the first number of MR record information of each cell grid in each mobile network scenario can be determined according to the following method, including:

[0053] Step 1: Based on the cell's operation and maintenance dataset, the latitude and longitude coordinates of the mobile terminal reporting each MR record in each mobile network scenario are determined. Specifically, based on the TA and RSRP values ​​in multiple MR records within a preset time period, combined with the cell's azimuth, frequency band, and other information, the latitude and longitude coordinates of the mobile terminal reporting each MR record are predicted, and the predicted results are backfilled into the corresponding MR record.

[0054] Step 2: Based on the matching results of the longitude and latitude coordinates of the mobile terminal with the longitude and latitude coordinates of each cell grid, the MR record information of each cell grid in each mobile network scenario is determined, and the MR record information of each cell grid in each mobile network scenario is counted to obtain the first number of MR record information of the cell grid in each mobile network scenario. In other words, the longitude and latitude coordinates of the mobile terminal are matched with the longitude and latitude coordinates of each cell grid to determine the MR record information belonging to each cell grid, and the MR record information belonging to the same cell grid is counted to obtain the first number of MR record information of the cell grid in each mobile network scenario (i.e., the total number of MR records in a single cell grid).

[0055] Step S1042: For each cell grid within the cell, if the area of ​​the cell grid within the service area of ​​the target mobile network scenario is not less than a preset area threshold, and the first number of MR recording information of the cell grid in the target mobile network scenario is not less than a preset second threshold, it is determined that the cell corresponding to the cell grid is in the service area of ​​the mobile network scenario.

[0056] The above-mentioned step S1042 can be understood as: based on whether the area of ​​the cell grid within the service area of ​​the specific mobile network scenario is not less than a preset area threshold (for example, 50%), and whether the first number of MR record information of the cell grid in the target mobile network scenario (that is, the total number of records) is not less than a preset second threshold (such as 3 records), the cell grid covered by the specific mobile network scenario is screened out, and the cell corresponding to the cell grid is used as the cell within each mobile network scenario.

[0057] Furthermore, after determining the mobile network scenario to which each cell belongs, in order to more accurately evaluate the operational health of each mobile network scenario, the cells under the coverage service of each mobile network scenario can be divided into associated levels to identify which cells have a significant impact on the operational status within the mobile network scenario and which cells have a smaller impact, thereby avoiding giving higher weights to cells with light coverage, resulting in less accurate evaluation results of the scenario's operational health.

[0058] As an optional implementation, the association levels of cells in a mobile network scenario may be divided according to the following rules, including:

[0059] For each mobile network scenario, the scenario layer dataset and the cell's basic engineering parameter dataset are used to determine whether the longitude and latitude coordinates of any cell within the mobile network scenario are completely within the mobile network scenario's service area. In other words, the longitude and latitude coordinates of any cell within the mobile network scenario are determined to be within the mobile network scenario's scene outline set.

[0060] If so, determining that the cell belongs to the first associated cell set of the mobile network scenario;

[0061] If not, determining a second number of MR record information in each cell grid of the cell in the mobile network scene based on the scene layer dataset and the cell operation and maintenance dataset, and determining whether a first ratio of the second number to the first total number of MR record information in each cell grid of the cell is not less than a preset third threshold (e.g., 20-30%).

[0062] If so, determining that the cell belongs to the second associated cell set of the mobile network scenario;

[0063] If not, continue to determine whether a second ratio of the sum of the second number of MR record information in each cell grid of the cell in the mobile network scenario to the sum of the first number of MR record information in each cell grid of the cell is greater than a preset fourth threshold (e.g., 30%) and whether the first ratio is not less than a preset fifth threshold (e.g., 10%), wherein the fifth threshold is less than the third threshold;

[0064] If so, it is determined that the cell belongs to the third associated cell set of the mobile network scenario.

[0065] By repeatedly executing the above classification process, different associated cell sets for each mobile network scenario can be obtained, wherein the association level of the above first associated cell set is higher than that of the above second associated cell set, and the association level of the above second associated cell set is higher than that of the above third associated cell set.

[0066] In addition to the classification implementation schemes listed above, based on the basic concept of the present invention, those skilled in the art can also implement the association classification of each cell under the mobile network scenario coverage service through other technical solutions. For example, those skilled in the art may make changes to the above implementation schemes, which should also be within the scope of protection of the present invention.

[0067] Furthermore, after knowing the correlation level of each cell within each mobile network scenario through the above steps, the scenario operation and maintenance health of the mobile network scenario under multiple service indicator dimensions can be comprehensively determined based on the operation and maintenance data set of each cell and the cell correlation level, including:

[0068] Step S1061 , determining the service indicator quantities of the mobile network scenario under multiple service indicator dimensions based on the operation and maintenance data set of each cell in the mobile network scenario and the association level of the associated cell set of the mobile network scenario to which each cell belongs.

[0069] In the technical solution provided in step S1061 above, the service indicator quantities for the mobile network scenario under multiple service indicator dimensions are specifically weighted and summed by combining the coverage data, wireless network performance data, and perception data in the operation and maintenance data set of each cell with the corresponding weight coefficient of the cell, thereby obtaining the service indicator quantities for the mobile network scenario under multiple service indicator dimensions. The weight coefficient corresponding to the cell is determined by combining the association level of the associated cell set of the mobile network scenario to which each cell belongs and the second ratio of the sum of the second number of MR recording information in each cell grid of the cell within the mobile network scenario to the sum of the first number of MR recording information in each cell grid of the cell within the mobile network scenario. For example, if the association level of the associated cell set of the mobile network scenario to which the area belongs is higher and the second ratio of the cell grids of the cell within the mobile network scenario is larger, the weight coefficient of the cell is also higher; conversely, if the association level of the associated cell set of the mobile network scenario to which the area belongs is lower and the second ratio of the cell grids of the cell within the mobile network scenario is smaller, the weight coefficient of the cell is also lower.

[0070] In addition, the above-mentioned business indicators include at least one of the following: MR coverage rate and weakly associated cell grid ratio corresponding to the coverage dimension, access success rate, drop rate, switching success rate, and business excellence rate corresponding to the quality dimension, business data volume corresponding to the efficiency dimension, and transmission rate and complaint rate corresponding to the perception dimension.

[0071] Specifically, a mobile network scenario A includes n cells, and the weight coefficients corresponding to each cell are W1, W2, ..., W n , then the calculation methods for business indicator quantities under different business indicator dimensions can be divided into:

[0072] (1) Calculation method of scenario data (such as business data volume).

[0073] Assume that the uplink and downlink service data volume of each of the n cells in the mobile network scenario A within the preset time period is {F1, F2, ..., F n}, then the total amount of service data in the mobile network scenario A during the preset time period can be recorded as: Among them, W i represents the i-th cell, F i Indicates the uplink and downlink service data volume of the i-th cell within the preset time period.

[0074] (2) Calculation method of scene rate (ie, transmission rate).

[0075] Based on the cell frequency band and bandwidth, each cell in the mobile network scenario is divided into multiple cell sets. The downlink traffic (excluding tail packets), uplink traffic (excluding tail packets), downlink transmission time (excluding tail packets), and uplink transmission time (excluding tail packets) of the corresponding cell in each cell set are taken, and then the uplink and downlink rates of each frequency band in the mobile network scenario are calculated by weighted average by frequency band.

[0076] For example, mobile network scenario A includes two types of cells: Band 1 20M and Band 78 100M. To calculate the downlink rate of Band 1 20M, you can first filter out the corresponding cell set {C1, C2, ..., C k}, and obtain the corresponding cell downlink traffic (excluding the tail packet) {DF1, DF2, ..., DF k} and downlink transmission time (excluding tail packet) {DT1,T,…,DT k}, then the downlink rate of Band 1 in mobile network scenario A is The calculation methods for uplink and downlink rates in other frequency bands are similar and will not be explained here one by one.

[0077] (3) Calculation methods for scenario indicators (such as access success rate, call drop rate, handover success rate, and service quality rate).

[0078] Get the denominator of the indicator {X1, X2, ..., X n}, indicator numerator {Y1,Y2,…Y n},but

[0079] For example, when calculating the 5G call drop rate of mobile network scenario A, the number of 5G radio resource control RRC connection successes {ConS1, ConS2, ..., ConS n} and the number of 5G RRC connection drops {ConD1,ConD2,…,ConD n}, and calculate the mobile network scenario A by the following formula

[0080] (4) Scene coverage calculation method.

[0081] First, the total number of MRs and the number of MR effective coverage items of all cell grids corresponding to each cell in a specific scenario are determined based on the scene layer dataset and the operation and maintenance dataset of each cell. The number of MR effective coverage items refers to the total number of MR records that meet the effective coverage conditions in the cell grid. It is generally believed that an RSRP greater than or equal to -110dBm under a 4G or 5G network is considered effective coverage). Then, for each cell grid in a specific scenario, the total number of MRs of each cell in the cell grid and the number of MR effective coverage items of each cell in the cell grid are summed up respectively to obtain the total number of MRs and the number of MR effective coverage items of the cell grid. The ratio of the number of MR effective coverage items to the total number of MR items of the cell grid is used as the MR coverage rate of the cell grid. Finally, the MR coverage rates of each cell grid in a specific scenario are summed up to obtain the MR coverage rate of the specific scenario.

[0082] (5) Calculation method of scenario complaint rate.

[0083] First, the total number of user complaints in the scene contour area is screened out by performing correlation calculation with the latitude and longitude of the center point of the annual cumulative user complaints (complaint work order / grid). TOT Then, the MR records in each cell in a specific scenario are counted and deduplicated according to the user identifier (such as user number MSI, SDN) to obtain the number of users in each cell within a unit time (the unit can be day, week, etc.), so as to obtain the total number of users USER in the specific scenario. TOT =sum(U1,U2,…,U n ); Finally, based on the total number of users USER in a specific scenario TOT and the total number of user complaints in this scenario COMPLAINT TOT The ratio of , determines the complaint rate of a specific scenario is

[0084] Step S1062 : determining scores of the mobile network scenario in the multiple business indicator dimensions based on the relationship between the business indicator amounts of the mobile network scenario in the multiple business indicator dimensions and the indicator thresholds corresponding to the respective business indicator dimensions.

[0085] Among them, the above-mentioned coverage dimension includes the coverage rate sub-dimension and the weak correlation sub-dimension; the perception dimension includes the access sub-dimension, the retention sub-dimension, the mobility sub-dimension, and the service quality sub-dimension; the quality dimension includes the rate sub-dimension and the complaint sub-dimension. Therefore, the scores under the above-mentioned multiple service indicator dimensions include at least one of the following: a first score under the coverage rate sub-dimension corresponding to the MR coverage rate, a second score under the weak correlation sub-dimension corresponding to the weak correlation cell grid ratio, a third score under the access sub-dimension corresponding to the access success rate, a fourth score under the retention sub-dimension corresponding to the drop rate, a fifth score under the mobility sub-dimension corresponding to the switching success rate, a sixth score under the service quality sub-dimension corresponding to the service excellence rate, a seventh score under the efficiency dimension corresponding to the service data volume, an eighth score under the rate sub-dimension corresponding to the (uplink and downlink) transmission rate, and a ninth score under the complaint sub-dimension corresponding to the complaint rate.

[0086] Specifically, the process of determining the first score of the mobile network scenario in the coverage sub-dimension includes:

[0087] First, determine the relationship between the MR coverage and the preset coverage threshold, where the coverage threshold is calculated by counting the MR coverage of each scene in the entire network. Then, according to the 90% compliance rate of each scene, the initial coverage rate compliance threshold of each type of scene is calculated separately; finally, K-means clustering analysis is performed to divide the clusters into K clusters, which are used as the coverage rate compliance threshold of each type of scene. Generally speaking, the various scenarios of the existing network can be analyzed and divided into three categories. The first category has a coverage threshold of 97.5%, which includes scenarios such as transportation hubs, tertiary hospitals, subways, government centers, universities, and high-traffic business districts; the second category has a coverage threshold of 93%, which includes scenarios such as scenic spots and high-density residential areas; the third category has a coverage threshold of 95%, which includes scenarios such as urban villages and highways.

[0088] If the MR coverage is not less than the coverage threshold, the first score of the mobile network scenario under the coverage sub-dimension is determined to be 100. In the case of , the first score of the mobile network scenario under the coverage sub-dimension is The score is 100 points.

[0089] When the MR coverage rate is less than the coverage rate threshold, the difference between the coverage rate threshold and the MR coverage rate of the mobile network scenario is determined, and the score obtained by multiplying the ratio of the difference to the preset adjustment coefficient by the full score is determined. The maximum value between the difference between the full score and the score and zero is used as the first score of the mobile network scenario in the coverage rate sub-dimension. That is, if the mobile network scenario In the case of , the expression of the first score is:

[0090] Specifically, the process of determining the second score of the mobile network scenario in the weak correlation sub-dimension includes:

[0091] First, determine the MR coverage of the cell grid of each cell in the mobile network scenario, and take the cell grid with MR coverage less than the coverage threshold as a weakly associated cell grid, where the coverage threshold is the coverage threshold of the above scenario.

[0092] Next, the number of all weakly associated cell grids in the mobile network scenario and the number of all cell grids in the mobile network scenario are counted, and the proportion of weakly associated cell grids in the mobile network scenario is determined. That is, the ratio of the number of all weakly associated cell grids in the mobile network scenario to the number of all cell grids in the mobile network scenario is used as the proportion of weakly associated cell grids in the mobile network scenario.

[0093] Then, the relationship between the proportion of weakly associated cell grids and the preset first full score threshold and the preset first zero score threshold is determined, wherein the above-mentioned first full score threshold is the proportion of weakly associated cell grids in all scenarios of the existing network, recorded as TRESH1 100 , and the first zero-point threshold is the value of the bottom 5% of the weakly associated cell grid proportion in all scenarios of the existing network, denoted as TRESH10.

[0094] When the proportion of weakly associated cell grids is not higher than the first full score threshold, the second score of the mobile network scenario under the weakly associated sub-dimension is determined to be full score, that is, the second score Assign a value of 100.

[0095] When the proportion of weakly associated cell grids is higher than the first full score threshold, the ratio of the difference between the proportion of weakly associated cell grids in the mobile network scenario and the first full score threshold and the difference between the first zero score threshold and the first full score threshold is determined, and the maximum value between the difference between the full score minus the product of the ratio and the full score and zero is used as the second score of the mobile network scenario in the weak association sub-dimension, where the expression of the second score is:

[0096] Specifically, the third score under the access sub-dimension corresponding to the mobile network scenario access success rate, the fourth score under the hold sub-dimension corresponding to the call drop rate, the fifth score under the mobility sub-dimension corresponding to the handover success rate, and the sixth score under the service quality sub-dimension corresponding to the service excellence rate are determined in a similar manner. The following will be collectively referred to as the score of the quality dimension to describe the determination process of the above-mentioned third score, fourth score, fifth score, and sixth score, including:

[0097] First, for each service indicator corresponding to the quality dimension, determine the relationship between the service indicator and the preset second full score threshold and the preset second zero score threshold. The service indicator is any one of the access success rate, drop rate, handover success rate, and service quality rate. The second full score threshold is the average value of the scenario indicator data of all scenarios in the existing network, which is recorded as TRESH2. 100 , and the second zero-point threshold is set based on historical experience and is recorded as TRESH20.

[0098] For example, for the access success rate indicator, the corresponding second full score threshold value can be 99.5%, and the second zero score threshold value can be 98.5%; for the drop rate indicator, the corresponding second full score threshold value can be 0.1%, and the second zero score threshold value can be 0.2%; for the switching success rate indicator, the corresponding second full score threshold value can be 99%, and the second zero score threshold value can be 98%; for the service quality rate indicator, the corresponding second full score threshold value can be 0.1%, and the second zero score threshold value can be 0.2%.

[0099] When the service indicator amount is not less than the second full score threshold, the score of the mobile network scenario in the quality dimension is determined to be full score, that is, the score SCORE of the mobile network scenario in the quality dimension is assigned a value of 100.

[0100] When the service indicator value is less than the second zero-score threshold, the score of the mobile network scenario in the quality dimension is determined to be zero, that is, the score SCORE of the mobile network scenario in the quality dimension is assigned to 0.

[0101] When the service indicator quantity is less than the second full score threshold and not less than the second zero score threshold, the ratio between the difference between the second full score threshold and the service indicator quantity of the mobile network scenario and the difference between the second full score threshold and the second zero score threshold is determined, and the maximum value between the difference between the full score minus the product of the ratio and the full score and zero score is used as the score of the mobile network scenario in the quality dimension, that is, the score of the mobile network scenario in the quality dimension SCORE=100-(TRESH2 100 –SENCE KPI ) / (TRESH2 100 -TRESH20)*100.

[0102] It should be noted that for the access sub-dimension, the access success rate generally includes: wireless connection success rate and voice establishment success rate. Therefore, when determining the third score of the mobile network scenario under the access sub-dimension, the average of the scores corresponding to the wireless connection success rate of the mobile network scenario and the scores corresponding to the voice establishment success rate of the mobile network scenario can be taken, that is:

[0103] Score corresponding to wireless connection success rate Specifically: If Then the score is 100; otherwise,

[0104] The score corresponding to the success rate of voice establishment Specifically: If Then the score is 100; otherwise,

[0105] Therefore, the third score of the mobile network scenario in the access sub-dimension is

[0106] For the retention sub-dimension, the drop rate generally includes: E-RAB (Evolved Radio Access Bearer) drop rate and voice drop rate. Therefore, when determining the fourth score of the mobile network scenario under the retention sub-dimension, the average of the scores corresponding to the E-RAB drop rate of the mobile network scenario and the scores corresponding to the voice drop rate of the mobile network scenario can be taken, that is:

[0107] The score corresponding to the E-RAB drop rate Specifically: If Then the score is 100; otherwise,

[0108] Score corresponding to the voice drop rate Specifically: If Then the score is 100; otherwise,

[0109] Therefore, the fourth score of the mobile network scenario under the maintenance sub-dimension is

[0110] For the mobility sub-dimension, both 4G and 5G networks involve handover success rate, while 5G networks also include the handover success rate from VoNR (Voice over New Radio) to VOLTE (Voice over Long-Term Evolution, LTE voice). Therefore, the fifth score under the mobility sub-dimension of the 5G network corresponding to the mobile network scenario is the average of the scores corresponding to the handover success rate and the scores corresponding to the handover success rate from VoNR to VOLTE, that is:

[0111] Score corresponding to the switching success rate within the system Specifically: If Then the score is 100; otherwise,

[0112] The score corresponding to the success rate of VoNR switching to VOLTE switching Specific: if Then the score is 100; otherwise,

[0113] Therefore, the fifth score of the mobility sub-dimension of the 4G network corresponding to the mobile network scenario is The fifth score of the mobility sub-dimension of the 5G network corresponding to the mobile network scenario is

[0114] For the service quality sub-dimension, the service quality rate includes: CQI (Channel Quality Indicator) quality rate and voice packet loss rate. Therefore, when determining the sixth score of the mobile network scenario under the service quality sub-dimension, the average of the score corresponding to the CQI quality rate of the mobile network scenario and the score corresponding to the voice packet loss rate of the mobile network scenario can be taken, that is:

[0115] The score corresponding to the CQI excellent rate Specifically: If Then the score is 100; otherwise,

[0116] Score corresponding to the voice packet loss rate Specifically: If 0.1%, then the score is 100; otherwise,

[0117] Therefore, the mobile network scenario is rated sixth in the service quality sub-dimension.

[0118] Specifically, the process for determining the seventh score of the performance dimension in the mobile network scenario includes:

[0119] First, the weight coefficient of each cell in the mobile network scenario is determined based on the first ratio of each cell grid in each cell in the mobile network scenario and the association level of the associated cell set of the mobile network scenario to which each cell belongs. That is, the weight coefficient of each cell is determined comprehensively based on the association level of the associated cell set of the mobile network scenario to which the cell belongs and the MR proportion of each cell grid in the cell.

[0120] Then, the weighted sum of each cell's weight coefficient and the preset efficiency threshold is used as the scenario efficiency threshold of the mobile network scenario. Among them, the preset efficiency threshold corresponding to each cell is the value of the average traffic of other cells with the same frequency band and bandwidth in the entire network within the preset time period based on the frequency band and bandwidth of the cell, and the efficiency threshold can be recorded as CELL TREsH Therefore, the scene performance threshold of the mobile network scene can be expressed as:

[0121] Finally, the product of the ratio of the mobile network scenario's service data volume to the scenario's efficiency threshold, the full score, and the minimum value between the full scores are taken as the seventh score of the mobile network scenario in the efficiency dimension. Therefore, the seventh score can be expressed as: EFFICIENCY sCORE =min(100,FLow / TRESH*100).

[0122] Specifically, the process of determining the eighth score of the (uplink and downlink) rate sub-dimension of the mobile network scenario includes:

[0123] Determine the relationship between the transmission rate of the mobile network scenario in different frequency bands and bandwidths and the preset third full score threshold (also known as the perception standard threshold) and the third zero score threshold (also known as the perception 0 score threshold). The third full score threshold is the value of the top 80% of the cell rates in the entire network, recorded as TRESH3 100 The third zero-score threshold is the top 90% of all cell speeds in the entire network, TRESH30. Furthermore, based on live network statistics, the perceived threshold for 3.5G 100M is 40Mbps, and the perceived zero-score threshold is 10Mbps; the perceived threshold for 2.1G / 1.8G 20M is 10Mbps, and the perceived zero-score threshold is 2Mbps; and the perceived threshold for 800M 10M is 5Mbps, and the perceived zero-score threshold is 1Mbps.

[0124] When the transmission rate of the mobile network scenario in a single frequency band and bandwidth is not lower than the third full score threshold, the score of the rate sub-dimension of the mobile network scenario in a single frequency band and bandwidth is determined to be full marks.

[0125] When the transmission rate of the mobile network scenario in a single frequency band and bandwidth is lower than the third zero-score threshold, the score of the rate sub-dimension of the mobile network scenario in a single frequency band and bandwidth is determined to be zero.

[0126] When the transmission rate of the mobile network scenario in the frequency band and bandwidth is lower than the third full score threshold but not lower than the third zero score threshold, determine the ratio between the difference between the third full score threshold and the transmission rate of the mobile network scenario and the difference between the third full score threshold and the third zero score threshold, and take the maximum value between the difference between the full score and the product of the ratio and the full score and zero score as the score of the rate sub-dimension of the mobile network scenario in a single frequency band and bandwidth.

[0127] For example, the score corresponding to the uplink perceived rate of a single frequency band and bandwidth in a mobile network scenario Specifically: If UL VELOCITY ≥TRESH3 100 , then the score is 100; otherwise,

[0128] Scores corresponding to the downlink perceived rate in a single frequency band and bandwidth in mobile network scenarios Specifically: If DL VELOCITY ≥TRESH3 100 , then the score is 100; otherwise,

[0129] Finally, the average of the scores of the rate sub-dimension of the mobile network scenario in each frequency band and bandwidth is used as the eighth score of the mobile network scenario in the rate sub-dimension. Therefore, the eighth score may include: the eighth score corresponding to the uplink perceived rate The eighth score DL corresponding to the downlink perceived rate VELOCITYSCORE =∑ Band,Bandwidth DL VELOCITYSCORE / n.

[0130] Specifically, the process for determining the ninth score of the mobile network scenario in the complaint sub-dimension includes:

[0131] Determine the relationship between the complaint rate of the mobile network scenario and the preset fourth full score threshold and fourth zero score threshold, where the fourth full score threshold is the average of the complaint rates of all scenarios in the current network, recorded as TRESH4 100 The fourth zero-point threshold is a multiple of the average complaint rate of all scenarios in the current network, such as TRESH40 = 5*TRESH4 100 .

[0132] If the complaint rate of the mobile network scenario is not lower than the fourth full score threshold, the ninth score of the mobile network scenario in the complaint sub-dimension is determined to be full score. RATE ≥TRESH4 100 , the ninth score is 100.

[0133] If the complaint rate of the mobile network scenario is lower than the fourth full score threshold, determine the ratio of the difference between the complaint rate of the mobile network scenario and the fourth full score threshold to the difference between the fourth zero score threshold and the fourth full score threshold, and use the maximum value between the difference between the full score minus the product of the ratio and the full score and zero as the ninth score of the mobile network scenario in the complaint sub-dimension. That is, COMPLAINT. RATE <TRESH4 100 , then the ninth score COMPLANE SCORE =max[0,100–(COMPLAIN RATE –TRESH4 100 ) / (TRESH40–TRESH4 100 )*100].

[0134] Step S1063 , determining the scene operation and maintenance health of the mobile network scene in multiple business indicator dimensions based on the scores of the mobile network scene in each business indicator dimension.

[0135] Specifically, the CRITIC weighting method is used to determine the weight of each service indicator dimension layer by layer. For example, the weight coefficient of the coverage sub-dimension can be 20%, and the weight coefficient of the weak correlation sub-dimension can be 10%; the weight coefficients of the access sub-dimension can be 6%, the weight coefficients of the retention sub-dimension can be 6%, the weight coefficients of the mobility sub-dimension can be 6%, and the weight coefficients of the service quality sub-dimension can be 12%; the weight coefficients of the uplink rate sub-dimension can be 3%, the weight coefficients of the downlink rate sub-dimension can be 12%, and the weight coefficients of the complaints sub-dimension can be 10%; and the weight coefficient of the efficiency dimension can be 15%. The scores of the mobile network scenarios under each service indicator dimension are then weighted and summed with the indicator weights of each service indicator dimension to obtain the scenario operation and maintenance health of the mobile network scenario under multiple service indicator dimensions.

[0136] Among them, the above-mentioned CRITIC weighting method is an objective weighting method based on data volatility, and its idea lies in the volatility (comparison strength) index and the conflict (correlation) index. The comparison strength can be identified by the standard deviation. If the data standard deviation is larger, the volatility is greater, and the weight will be higher; while the conflict is identified by the correlation coefficient. If the correlation coefficient value between the indicators is larger, the conflict is smaller, and the corresponding weight is lower. The above-mentioned method for determining the indicator weight is only described as an example, and this application does not impose any specific restrictions on this determination method.

[0137] After determining the operational health of a single mobile network scenario through steps S1061-S1063, the relationship between the operational health of the scenario and a preset health threshold can be determined. If the operational health of the scenario exceeds the preset health threshold, the network health of the mobile network scenario meets the standard. Furthermore, if both the 4G network and the 5G network corresponding to the mobile network scenario meet the standard, the mobile network scenario meets the comprehensive 4 / 5G network standard.

[0138] If the scenario operation and maintenance health is lower than the preset health threshold, the abnormal mobile network scenarios whose scenario operation and maintenance health is lower than the preset health threshold can be determined first; then, the abnormal mobile network scenarios are optimized and managed according to the preset optimization strategy, wherein the optimization strategy includes at least one of the following: network expansion, resource scheduling, and parameter optimization.

[0139] Specifically, when optimizing abnormal mobile network scenarios, the management priority of each abnormal mobile network scenario can be determined based on the level of scenario operation and maintenance health of each abnormal mobile network scenario. Generally, the lower the scenario operation and maintenance health, the higher the corresponding management priority, and it is preferred to optimize and manage it. At the same time, different optimization measures can be formulated for abnormal mobile network scenarios with different management priorities, where the optimization measures include but are not limited to: network optimization, resource scheduling, troubleshooting, etc. In addition, after implementing the optimization management operation, the network quality and user perception of each optimized scenario are continuously monitored, and the scenario operation and maintenance health is re-evaluated regularly to ensure the network optimization effect and timely adjust the management strategy.

[0140] Through the above-mentioned mobile network scenario operation and maintenance management method, four major business indicator dimensions of coverage, quality, efficiency and perception and their subordinate sub-dimensions are proposed to build a multi-dimensional and differentiated comprehensive health assessment system for mobile network scenario operations. At the same time, the traditional qualitative evaluation is converted into a quantitative evaluation, thereby greatly expanding the breadth and depth of the evaluation, so that the scenario operation health is adapted to the improvement of network quality perception and market development needs, and greatly improving the accuracy of mobile network scenario evaluation. In addition, in the above-mentioned scheme, based on the MR proportion of the cell grid within the scenario-associated cell and the association level of the associated cell set of the mobile network scenario to which each cell belongs, the cell weight of each cell is comprehensively determined, and combined with the business indicator volume of each cell, the accuracy of the scenario business calculation is greatly improved, avoiding the problem of excessive business volume caused by counting the full amount of business of the associated cell into the scenario. In addition, during the entire evaluation process, scenario-specific coverage evaluations are proposed based on the differentiated business requirements of different classification scenarios, and differentiated resource allocation efficiency and perception rate evaluations are proposed based on different frequency bands and bandwidths. This allows for differentiated scenario operation evaluations based on scenario categories and resource allocations, and improves the accuracy of scenario resource efficiency and operational efficiency, thereby significantly reducing the probability of scenario operation guarantees such as over-allocation, low efficiency, and poor targeting (difficulty in adapting to scenario business characteristics).

[0141] Example 2

[0142] According to an embodiment of the present application, a mobile network scenario operation and maintenance management device is also provided for implementing the mobile network scenario operation and maintenance management method in Example 1, such as Figure 2 As shown, the mobile network scenario operation and maintenance management device includes at least: an acquisition module 22, a determination module 24, an evaluation module 26 and a management module 28, wherein:

[0143] An acquisition module 22 is configured to acquire a target dataset of a target area within a preset time period, wherein the target dataset includes at least: a scene layer dataset reflecting different mobile network scene information of the target area, a basic engineering parameter dataset reflecting the physical location information of each cell in the target area, and an operation and maintenance dataset reflecting measurement report (MR) record information of each cell in the target area;

[0144] A determination module 24, configured to determine at least one cell within each mobile network scenario based on the target data set;

[0145] An evaluation module 26 is configured to determine, for each mobile network scenario, the operational health of the mobile network scenario in multiple service indicator dimensions based on the operational data set of each cell within the mobile network scenario, wherein the service indicator dimensions include at least one of the following: coverage dimension, perception dimension, quality dimension, and efficiency dimension;

[0146] The management module 28 is used to manage each mobile network scenario according to the scenario operation and maintenance health.

[0147] It should be noted that each module in the mobile network scenario operation and maintenance management device in the embodiment of the present application corresponds one-to-one to each implementation step of the mobile network scenario operation and maintenance management method in Example 1. Since a detailed description has been given in Example 1, some details not reflected in this embodiment can be referred to Example 1 and will not be elaborated here.

[0148] Example 3

[0149] According to an embodiment of the present application, a computer program product is also provided, which includes a computer program, wherein when the computer program is executed by a processor, it implements the mobile network scenario operation and maintenance management method in Example 1.

[0150] According to an embodiment of the present application, a non-volatile storage medium is also provided, which includes a stored computer program, wherein the device where the non-volatile storage medium is located executes the mobile network scenario operation and maintenance management method in Example 1 by running the computer program.

[0151] According to an embodiment of the present application, a processor is further provided, which is used to run a computer program, wherein the mobile network scenario operation and maintenance management method in Example 1 is executed when the computer program is running.

[0152] According to an embodiment of the present application, an electronic device is also provided, which includes: a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to execute the mobile network scenario operation and maintenance management method in Example 1 through the computer program.

[0153] Optionally, the computer program executes the following steps when it is running: obtaining a target data set of the target area within a preset time period, wherein the target data set includes at least: a scene layer data set for reflecting different mobile network scene information of the target area, a basic engineering parameter data set for reflecting the physical location information of each cell in the target area, and an operation and maintenance data set for reflecting the measurement report MR record information of each cell in the target area; determining at least one cell in each mobile network scene based on the target data set; for each mobile network scene, determining the scene operation and maintenance health of the mobile network scene under multiple business indicator dimensions based on the operation and maintenance data sets of each cell in the mobile network scene, wherein the business indicator dimensions include at least one of the following: coverage dimension, perception dimension, quality dimension, and efficiency dimension; and performing management operations on each mobile network scene based on the scene operation and maintenance health.

[0154] As an optional implementation, the electronic device may be in the form of a mobile terminal, a computer terminal or a similar computing device. Figure 3The figure shows a hardware structure block diagram of an electronic device for implementing a mobile network scene operation and maintenance management method. Figure 3 As shown, the electronic device 30 may include one or more (illustrated as 302a, 302b, ..., 302n in the figure) processors 302 (the processor 302 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 304 for storing data, and a transmission device 306 for communication functions. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the BUS bus), a network interface, a power supply and / or a camera. It will be understood by those skilled in the art that Figure 3 The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 3 More or fewer components than shown, or with Figure 3 Different configurations shown.

[0155] It should be noted that the one or more processors 302 and / or other data processing circuits described above may generally be referred to herein as "data processing circuitry". The data processing circuitry may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. In addition, the data processing circuitry may be a single independent processing module, or may be incorporated in whole or in part into any of the other components of the electronic device 30. As described in the embodiments of the present application, the data processing circuitry serves as a processor control (e.g., selection of a variable resistor terminal path connected to an interface).

[0156] The memory 304 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the mobile network scenario operation and maintenance management method in the embodiment of the present application. The processor 302 executes various functional applications and data processing by running the software programs and modules stored in the memory 304, that is, implementing the vulnerability detection method of the above-mentioned application. The memory 304 may include a high-speed random access memory and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 304 may further include a memory remotely located relative to the processor 302, and these remote memories may be connected to the electronic device 30 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0157] The transmission device 306 is used to receive or send data via a network. Specific examples of the aforementioned network may include a wireless network provided by the communications provider of the electronic device 30. In one embodiment, the transmission device 306 includes a network interface controller (NIC), which can be connected to other network devices via a base station to enable communication with the Internet. In one embodiment, the transmission device 306 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0158] The display may be, for example, a touch screen liquid crystal display (LCD) that enables a user to interact with a user interface of the electronic device 30 .

[0159] The serial numbers of the above embodiments are for description only and do not represent the advantages or disadvantages of the embodiments.

[0160] In the above embodiments of the present application, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0161] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only exemplary. For example, the division of units can be a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0162] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple units. Some or all of the units may be selected to achieve the purpose of the present embodiment according to actual needs.

[0163] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0164] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk.

[0165] The above is only a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A mobile network scenario operation and maintenance management method, characterized in that: include: Obtain a target dataset of a target area within a preset time period, wherein the target dataset includes at least: a scene layer dataset for reflecting different mobile network scene information of the target area, a basic engineering parameter dataset for reflecting physical location information of each cell in the target area, and an operation and maintenance dataset for reflecting measurement report (MR) record information of each cell in the target area; determining at least one cell within each mobile network scenario based on the target data set; For each of the mobile network scenarios, determining the scenario operation and maintenance health of the mobile network scenario under multiple service indicator dimensions based on the operation and maintenance data set of each cell in the mobile network scenario, wherein the service indicator dimensions include at least one of the following: coverage dimension, perception dimension, quality dimension, and efficiency dimension; Perform management operations on each of the mobile network scenarios according to the scenario operation and maintenance health; Among them, the scene operation and maintenance health of the mobile network scene under multiple business indicator dimensions is determined based on the operation and maintenance data set of each cell in the mobile network scene, including: determining the business indicator quantity of the mobile network scene under multiple business indicator dimensions based on the operation and maintenance data set of each cell in the mobile network scene and the association level of the associated cell set of the mobile network scene to which each cell belongs, wherein the business indicator quantity includes at least one of the following: MR coverage rate and weakly associated cell grid proportion corresponding to the coverage dimension, access success rate, drop rate, switching success rate, and business excellence rate corresponding to the quality dimension, business data volume corresponding to the efficiency dimension, and transmission rate and complaint rate corresponding to the perception dimension; based on the difference between the business indicator quantity under multiple business indicator dimensions of the mobile network scene and the indicator threshold value corresponding to each business indicator dimension. Small relationship, determine the scores of the mobile network scenario under multiple business indicator dimensions, wherein the scores under the multiple business indicator dimensions include at least one of the following: a first score under the coverage sub-dimension corresponding to the MR coverage rate, a second score under the weak correlation sub-dimension corresponding to the weak correlation cell grid proportion, a third score under the access sub-dimension corresponding to the access success rate, a fourth score under the hold sub-dimension corresponding to the drop rate, a fifth score under the mobility sub-dimension corresponding to the switching success rate, a sixth score under the service quality sub-dimension corresponding to the service excellence rate, a seventh score under the efficiency dimension corresponding to the service data volume, an eighth score under the rate sub-dimension corresponding to the transmission rate, and a ninth score under the complaint sub-dimension corresponding to the complaint rate; determine the scenario operation and maintenance health of the mobile network scenario under multiple business indicator dimensions according to the scores of the mobile network scenario under each of the business indicator dimensions; Among them, based on the size relationship between the business indicator amount of the mobile network scenario in multiple business indicator dimensions and the indicator threshold corresponding to each business indicator dimension, the score of the mobile network scenario in multiple business indicator dimensions is determined, including: judging the size relationship between the MR coverage rate and the preset coverage rate threshold; when the MR coverage rate is not less than the coverage rate threshold, determining that the first score of the mobile network scenario in the coverage rate sub-dimension is full score; when the MR coverage rate is less than the coverage rate threshold, determining the difference between the coverage rate threshold and the MR coverage rate of the mobile network scenario, and determining the score obtained by multiplying the ratio of the difference to the preset adjustment coefficient by the full score, and taking the maximum value between the difference between the full score and the score and zero as the first score of the mobile network scenario in the coverage rate sub-dimension.

2. The method according to claim 1, characterized in that Determining at least one cell in each mobile network scenario according to the target data set includes: For each cell in the target area, rasterizing the cell to obtain a plurality of cell grids, and determining the grid longitude and latitude coordinates of each of the cell grids based on the basic engineering parameter data of the cell; determining the area of ​​each cell grid in the cell within the service area of ​​different mobile network scenarios based on the scene layer dataset and the basic engineering parameter dataset of the cell; and determining the first number of MR recording information of each cell grid in each mobile network scenario based on the operation and maintenance dataset of the cell and the grid longitude and latitude coordinates of each cell grid in the cell; For each cell grid within the cell, if the area of ​​the cell grid within the service area of ​​the target mobile network scenario is not less than a preset area threshold, and the first number of MR recording information of the cell grid in the target mobile network scenario is not less than a preset second threshold, it is determined that the cell corresponding to the cell grid is in the service area of ​​the mobile network scenario.

3. The method according to claim 2, characterized in that The operation and maintenance data set includes at least: multiple MR record information based on the assisted global satellite positioning system reported by multiple mobile terminals in the cell within a preset time period, and the MR record information includes at least one of the following: a time advance TA value and a reference signal received power RSRP value. Determining a first number of MR record information of each cell grid in each mobile network scenario based on the operation and maintenance data set of the cell and the grid longitude and latitude coordinates of each cell grid in the cell includes: Determining, based on the operation and maintenance data set of the cell, the longitude and latitude coordinates of the mobile terminal that reports each MR recording information in each mobile network scenario of the cell; Based on the matching results of the latitude and longitude coordinates of the mobile terminal and the grid longitude and longitude coordinates of each cell grid, the MR recording information of each cell grid in each mobile network scenario is determined, and the MR recording information of each cell grid in each mobile network scenario is counted to obtain the first number of MR recording information of the cell grid in each mobile network scenario.

4. The method according to claim 2, characterized in that The basic engineering parameter data set includes at least the latitude and longitude coordinates of a cell, and the scene layer data set includes at least the coverage areas of different mobile network scenarios. Before determining the scene operation and maintenance health of the mobile network scenario under multiple business indicator dimensions based on the operation and maintenance data set of each cell in the mobile network scenario, the method further includes: For each of the mobile network scenarios, determining whether the longitude and latitude coordinates of any cell in the mobile network scenario are completely within the service area of ​​the mobile network scenario based on the scenario layer dataset and the basic engineering parameter dataset of the cell; If so, determining that the cell belongs to the first associated cell set of the mobile network scenario; If not, determining a second number of MR record information in each cell grid of the cell in the mobile network scene based on the scene layer dataset and the operation and maintenance dataset of the cell, and determining whether a first ratio of the second number to the first number of MR record information in each cell grid of the cell is not less than a preset third threshold; If so, determining that the cell belongs to the second associated cell set of the mobile network scenario; If not, determining whether a second ratio of the sum of the second number of MR recorded information in each cell grid of the cell in the mobile network scenario to the sum of the first number of MR recorded information in each cell grid of the cell is greater than a preset fourth threshold and whether the first ratio is not lower than a preset fifth threshold, wherein the fifth threshold is less than the third threshold; If so, determining that the cell belongs to a third associated cell set of the mobile network scenario; The association level of the first associated cell set is higher than that of the second associated cell set, and the association level of the second associated cell set is higher than that of the third associated cell set.

5. The method according to claim 1, wherein Determining scores for the mobile network scenario in the multiple business indicator dimensions based on a relationship between business indicator quantities for the mobile network scenario in the multiple business indicator dimensions and indicator thresholds corresponding to the respective business indicator dimensions includes: Determine the MR coverage of the cell grid of each cell in the mobile network scenario, and define the cell grid with the MR coverage less than the coverage threshold as a weakly associated cell grid; Counting the number of all weakly associated cell grids in the mobile network scenario and the number of all cell grids in the mobile network scenario, and determining the proportion of weakly associated cell grids in the mobile network scenario; Determine the relationship between the proportion of the weakly associated cell grid and a preset first full score threshold and a preset first zero score threshold; When the proportion of the weakly associated cell grid is not higher than the first full score threshold, determining that the second score of the mobile network scenario in the weakly associated sub-dimension is full score; When the proportion of the weakly associated cell grid is higher than the first full score threshold, the ratio between the difference between the proportion of the weakly associated cell grid of the mobile network scenario and the first full score threshold and the difference between the first zero score threshold and the first full score threshold is determined, and the maximum value between the difference between the full score minus the product of the ratio and the full score and zero score is used as the second score of the mobile network scenario under the weak association sub-dimension.

6. The method according to claim 1, characterized in that Determining scores for the mobile network scenario in the multiple business indicator dimensions based on a relationship between business indicator quantities for the mobile network scenario in the multiple business indicator dimensions and indicator thresholds corresponding to the respective business indicator dimensions includes: For each service indicator corresponding to the quality dimension, determining a relationship between the service indicator and a preset second full score threshold and a preset second zero score threshold, wherein the service indicator is any one of an access success rate, a drop rate, a handover success rate, and a service quality rate; If the service indicator value is not less than the second full score threshold, determining that the score of the mobile network scenario in the quality dimension is full score; When the service indicator value is less than the second zero-score threshold, determining that the score of the mobile network scenario in the quality dimension is zero; If the service indicator quantity is less than the second full score threshold and not less than the second zero score threshold, determine a ratio between a difference between the second full score threshold and the service indicator quantity of the mobile network scenario and a difference between the second full score threshold and the second zero score threshold, and use the maximum value between zero and a difference between the full score minus the product of the ratio and the full score as the score of the mobile network scenario under the quality dimension; Among them, the scoring of the mobile network scenario under the quality dimension includes: the third score of the access sub-dimension corresponding to the access success rate, the fourth score of the retention sub-dimension corresponding to the drop rate, the fifth score of the mobility sub-dimension corresponding to the switching success rate, and the sixth score of the service quality sub-dimension corresponding to the service excellence rate.

7. The method according to claim 1, characterized in that Determining scores for the mobile network scenario in the multiple business indicator dimensions based on a relationship between business indicator quantities for the mobile network scenario in the multiple business indicator dimensions and indicator thresholds corresponding to the respective business indicator dimensions includes: Determining a weight coefficient of each cell in the mobile network scenario according to a first ratio of each cell grid in each cell in the mobile network scenario and an association level of an associated cell set of the mobile network scenario to which each cell belongs; Taking the weighted sum of the weight coefficient of each cell and the preset performance threshold as the scenario performance threshold of the mobile network scenario; The product of the ratio of the business data volume of the mobile network scenario to the scenario performance threshold and the full score, and the minimum value of the full scores are used as the seventh score of the mobile network scenario in the performance dimension.

8. The method according to claim 1, characterized in that Determining scores for the mobile network scenario in the multiple business indicator dimensions based on a relationship between business indicator quantities for the mobile network scenario in the multiple business indicator dimensions and indicator thresholds corresponding to the respective business indicator dimensions includes: Determine the relationship between the transmission rate of the mobile network scenario in different frequency bands and bandwidths and a preset third full score threshold and a third zero score threshold; If the transmission rate of the mobile network scenario in the single frequency band and bandwidth is not lower than the third full score threshold, determine that the score of the rate sub-dimension of the mobile network scenario in the single frequency band and bandwidth is full score; When the transmission rate of the mobile network scenario in the single frequency band and bandwidth is lower than the third zero-score threshold, determine that the score of the rate sub-dimension of the mobile network scenario in the single frequency band and bandwidth is zero; If the transmission rate of the mobile network scenario in the frequency band and bandwidth is lower than the third full score threshold but not lower than the third zero score threshold, determine the ratio of the difference between the third full score threshold and the transmission rate of the mobile network scenario to the difference between the third full score threshold and the third zero score threshold, and use the maximum value between the difference between the full score and the product of the ratio and the full score and zero as the score of the rate sub-dimension of the mobile network scenario in the single frequency band and bandwidth; The average value of the scores of the rate sub-dimension of the mobile network scenario in each frequency band and bandwidth is used as the eighth score of the mobile network scenario in the rate sub-dimension.

9. The method according to claim 1, characterized in that Determining scores for the mobile network scenario in the multiple business indicator dimensions based on a relationship between business indicator quantities for the mobile network scenario in the multiple business indicator dimensions and indicator thresholds corresponding to the respective business indicator dimensions includes: Determining a relationship between the complaint rate of the mobile network scenario and a preset fourth full score threshold and a fourth zero score threshold; If the complaint rate of the mobile network scenario is not lower than the fourth full score threshold, determining that the ninth score of the mobile network scenario in the complaint sub-dimension is full score; When the complaint rate of the mobile network scenario is lower than the fourth full score threshold, determine the ratio between the difference between the complaint rate of the mobile network scenario and the fourth full score threshold and the difference between the fourth zero score threshold and the fourth full score threshold, and take the maximum value between the difference between the full score minus the product of the ratio and the full score and zero score as the ninth score of the mobile network scenario in the complaint sub-dimension.

10. The method according to claim 1, characterized in that Performing management operations on each of the mobile network scenarios based on the scenario operation and maintenance health, including: Determining abnormal mobile network scenarios whose scenario operation and maintenance health is lower than a preset health threshold within the scenario operation and maintenance health of each of the mobile network scenarios; The abnormal mobile network scenario is optimized and managed according to a preset optimization strategy, wherein the optimization strategy includes at least one of the following: network capacity expansion, resource scheduling, and parameter optimization.

11. A mobile network scene operation and maintenance management device, characterized in that: include: An acquisition module is configured to acquire a target data set of a target area within a preset time period, wherein the target data set includes at least: a scene layer data set for reflecting different mobile network scene information of the target area, a basic engineering parameter data set for reflecting the physical location information of each cell in the target area, and an operation and maintenance data set for reflecting measurement report (MR) record information of each cell in the target area; a determination module, configured to determine at least one cell within each mobile network scenario based on the target data set; an evaluation module configured to determine, for each mobile network scenario, a scenario operation and maintenance health of the mobile network scenario in multiple service indicator dimensions based on an operation and maintenance data set of each cell within the mobile network scenario, wherein the service indicator dimensions include at least one of the following: coverage dimension, perception dimension, quality dimension, and efficiency dimension; A management module, configured to perform management operations on each of the mobile network scenarios based on the scenario operation and maintenance health; Among them, the scene operation and maintenance health of the mobile network scene under multiple business indicator dimensions is determined based on the operation and maintenance data set of each cell in the mobile network scene, including: determining the business indicator quantity of the mobile network scene under multiple business indicator dimensions based on the operation and maintenance data set of each cell in the mobile network scene and the association level of the associated cell set of the mobile network scene to which each cell belongs, wherein the business indicator quantity includes at least one of the following: MR coverage rate and weakly associated cell grid proportion corresponding to the coverage dimension, access success rate, drop rate, switching success rate, and business excellence rate corresponding to the quality dimension, business data volume corresponding to the efficiency dimension, and transmission rate and complaint rate corresponding to the perception dimension; based on the difference between the business indicator quantity under multiple business indicator dimensions of the mobile network scene and the indicator threshold value corresponding to each business indicator dimension. Small relationship, determine the scores of the mobile network scenario under multiple business indicator dimensions, wherein the scores under the multiple business indicator dimensions include at least one of the following: a first score under the coverage sub-dimension corresponding to the MR coverage rate, a second score under the weak correlation sub-dimension corresponding to the weak correlation cell grid proportion, a third score under the access sub-dimension corresponding to the access success rate, a fourth score under the hold sub-dimension corresponding to the drop rate, a fifth score under the mobility sub-dimension corresponding to the switching success rate, a sixth score under the service quality sub-dimension corresponding to the service excellence rate, a seventh score under the efficiency dimension corresponding to the service data volume, an eighth score under the rate sub-dimension corresponding to the transmission rate, and a ninth score under the complaint sub-dimension corresponding to the complaint rate; determine the scenario operation and maintenance health of the mobile network scenario under multiple business indicator dimensions according to the scores of the mobile network scenario under each of the business indicator dimensions; Among them, based on the size relationship between the business indicator amount of the mobile network scenario in multiple business indicator dimensions and the indicator threshold corresponding to each business indicator dimension, the score of the mobile network scenario in multiple business indicator dimensions is determined, including: judging the size relationship between the MR coverage rate and the preset coverage rate threshold; when the MR coverage rate is not less than the coverage rate threshold, determining that the first score of the mobile network scenario in the coverage rate sub-dimension is full score; when the MR coverage rate is less than the coverage rate threshold, determining the difference between the coverage rate threshold and the MR coverage rate of the mobile network scenario, and determining the score obtained by multiplying the ratio of the difference to the preset adjustment coefficient by the full score, and taking the maximum value between the difference between the full score and the score and zero as the first score of the mobile network scenario in the coverage rate sub-dimension.

12. A computer program product, characterized in that include: A computer program, wherein when the computer program is executed by a processor, it implements the mobile network scenario operation and maintenance management method according to any one of claims 1 to 10.

13. An electronic device, characterized in that: include: A memory and a processor, wherein the memory stores a computer program, and the processor is configured to execute the mobile network scenario operation and maintenance management method according to any one of claims 1 to 10 through the computer program.

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