District network performance evaluation method, evaluation device and evaluation system

Abstract

The invention provides a district network performance evaluation method, evaluation device and evaluation system. The method comprises the following steps: dividing a target district into a plurality of sub-districts; performing weighted average on the network data corresponding to the test points of each sub-area to obtain three average signal strengths and three average signal-to-noise ratios of each sub-area, the network data including drive test data, measurement report data and user feedback data; performing weighted averaging on the three average signal intensities of each sub-area to obtain the comprehensive average signal intensity of each sub-area, and performing weighted averaging on the three average signal-to-noise ratios of each sub-area to obtain the comprehensive average signal-to-noise ratio of each sub-area; and under the condition that the comprehensive average signal strength of the network of the operator to be evaluated in the target sub-area is smaller than the preset signal strength or the comprehensive average signal-to-noise ratio is smaller than the preset signal-to-noise ratio, the network performance of the target sub-area is determined to be poor, and the problem that the evaluation result of the network performance is inaccurate in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the field of communication service technology, and in particular to a method for evaluating area network performance, an evaluation device, a computer-readable storage medium, a computer program product, and an evaluation system for area network performance. Background Art

[0002] As one of the indispensable infrastructures in modern society, mobile communications are facing unprecedented challenges. With the rapid growth of mobile data traffic and the increasing demand of users for high-quality network connections, operators not only need to cope with fierce market competition, but also need to continuously improve network performance to meet user expectations. However, current technical means have many shortcomings in evaluating the network performance of different operators, especially the inability to effectively compare the service quality differences of different operators in different regions, making it difficult to accurately implement network optimization measures.

[0003] Although there are some technical solutions for monitoring and analyzing mobile network performance, current technologies still have obvious limitations. For example, the prior art has proposed some basic methods for testing and evaluating the quality of wireless mobile networks, such as fixed-size grid division and testing methods combining DT (Drive Test) and CQT (Call Quality Test), but these methods have obvious limitations. Fixed-size grid division cannot provide sufficient testing accuracy when facing areas with different user densities and geographical characteristics, which can easily lead to too few test points in high-density areas and the creation of test blind spots in low-density areas. In addition, the testing methods are single, mainly relying on the two methods of DT and CQT, which cannot fully reflect the actual performance of the network, especially in terms of multi-source data fusion and comprehensive evaluation.

[0004] Similarly, the prior art also proposes a method for evaluating cell perception performance based on measurement report data, and takes into account factors such as the number of user devices and reference signal receiving power. However, this method also ignores the need for comprehensive analysis of multi-source data and does not adopt dynamic adaptive grid division technology, resulting in poor performance in terms of network performance monitoring accuracy, especially in areas with different population densities. It is difficult to provide detailed network performance evaluation and comparison.

[0005] It can be seen that the existing technology generally fails to effectively integrate multiple data sources (such as road test data DT, measurement report data MR, user feedback data UR), lacks the function of comprehensive score calculation, and this defect may lead to the neglect of certain key indicators or improper weight distribution in the process of network performance evaluation, thus affecting the accuracy and reliability of the evaluation results. In addition, the existing technical solutions usually do not have the ability of dynamic adaptive grid division, that is, they cannot automatically adjust the size of the monitoring unit according to the changes in user density and geographical features. In places with dense populations or complex geographical environments, the traditional static, fixed-size grid division method is prone to cause imbalance in data distribution - there are too few data points in high-density areas, and too many data points in low-density areas, so it cannot accurately reflect the actual network status. In addition, the existing technology also lacks the ability of differentiated labeling and visual display. This lack not only limits the intuitive display of network performance differences, but also hinders the development of effective user interaction mechanisms, thereby affecting the rapid identification and resolution of network problem areas. Summary of the invention

[0006] The main purpose of the present application is to provide a method for evaluating area network performance, an evaluation device, a computer-readable storage medium, a computer program product and an evaluation system for area network performance, so as to at least solve the problem of inaccurate evaluation results of network performance in the prior art.

[0007] In order to achieve the above-mentioned purpose, according to one aspect of the present application, a method for evaluating the performance of an area network is provided, comprising: dividing a target area into a plurality of sub-areas; performing weighted averaging on the network data corresponding to the test points of each of the sub-areas to obtain the average signal strength of the road test, the average signal-to-noise ratio of the road test, the average signal strength of the measurement report, the average signal-to-noise ratio of the measurement report, the average signal strength of the user feedback, and the average signal-to-noise ratio of the user feedback of each of the sub-areas, wherein the network data comprises the road test data, the measurement report data, and the user feedback data, wherein the road test data comprises the signal strength and the signal-to-noise ratio of the test point of the road test, the measurement report data comprises the signal strength and the signal-to-noise ratio of the test point uploaded by the terminal, and the user feedback data comprises the average signal strength and the signal-to-noise ratio of the test point at which the user feedback is located. signal strength and signal-to-noise ratio; weighted average the road test average signal strength, the measurement report average signal strength and the user feedback average signal strength of each sub-area to obtain a comprehensive average signal strength of each sub-area, and weighted average the road test average signal-to-noise ratio, the measurement report average signal-to-noise ratio and the user feedback average signal-to-noise ratio of each sub-area to obtain a comprehensive average signal-to-noise ratio of each sub-area; when the comprehensive average signal strength of the network of the operator to be evaluated in the target sub-area is less than a predetermined signal strength or the comprehensive average signal-to-noise ratio of the network of the operator to be evaluated in the target sub-area is less than a predetermined signal-to-noise ratio, it is determined that the network performance of the target sub-area is poor, and the target sub-area is any one of the sub-areas.

[0008] Optionally, dividing the target area into a plurality of sub-areas comprises: obtaining a map of the target area; dividing the target area into N sub-areas on the map, so that the boundaries of the sub-areas are located on the roads of the map and the areas of the sub-areas are smaller than the predetermined areas, N≥2; performing weighted average on the user number density, data flow density and connection number density of each sub-area to obtain the network usage density of each sub-area, wherein the user number density is the ratio of the total number of users of the sub-area to the area of ​​the sub-area, the data flow density is the ratio of the total data flow of the sub-area within a predetermined time period to the area of ​​the sub-area, and the connection number density is the ratio of the number of connections of the users of the sub-area to the network within the predetermined time period to the area of ​​the sub-area; calculating the average value of the network usage density of each sub-area to obtain the average network usage density of the target area; and using New Grid Size=Base Grid Size×(1+(Network Density-Average Density) / (Average Density)) to calculate the adjusted area of ​​each sub-area, wherein New Grid Size is the adjusted area, Base Grid Size is the area of ​​the sub-area before adjustment, Network Density is the network usage density of the sub-area, and AverageDensity is the average network usage density; the target area is re-divided according to the adjusted area of ​​each sub-area to obtain multiple sub-areas.

[0009] Optionally, dividing the target area into N sub-areas on the map includes: using a quadtree algorithm to divide the target area into 4 sub-areas so that the boundaries of the sub-areas are located on the roads of the map; a division step, when the area of ​​the target sub-area is larger than the predetermined area, using the quadtree algorithm to divide the target sub-area into 4 new sub-areas, the target sub-area being any one of the sub-areas; repeating the division step at least once until the areas of all the sub-areas are smaller than the predetermined area, thereby obtaining N sub-areas.

[0010] Optionally, obtaining network data corresponding to the test points of each sub-area and performing weighted averaging to obtain the average signal strength of the road test, the average signal-to-noise ratio of the road test, the average signal strength of the measurement report, the average signal-to-noise ratio of the measurement report, the average signal strength of the user feedback, and the average signal-to-noise ratio of the user feedback of each sub-area includes: dividing the grid of the target sub-area into multiple sub-grids; according to Calculate the time difference weight of each test point in each sub-grid, Weigh_t jiis the time difference weight of the i-th test point in the j-th subgrid, ji is the time difference between the collection time of the network data of the ith test point in the jth sub-grid and the current time, and ∈ is a constant; the network data corresponding to the test point is weighted averaged according to the time difference weight of each test point in each sub-grid to obtain the road test average signal strength, the road test average signal-to-noise ratio, the measurement report average signal strength, the measurement report average signal-to-noise ratio, the user feedback average signal strength and the user feedback average signal-to-noise ratio of the target sub-area.

[0011] Optionally, performing a weighted average on the drive test average signal strength, the measurement report average signal strength, and the user feedback average signal strength of each sub-area to obtain a comprehensive average signal strength of each sub-area, and performing a weighted average on the drive test average signal-to-noise ratio, the measurement report average signal-to-noise ratio, and the user feedback average signal-to-noise ratio of each sub-area to obtain a comprehensive average signal-to-noise ratio of each sub-area, including: setting a weight W1 of the drive test data, a weight W2 of the measurement report data, and a weight W3 of the user feedback data, so that W1+W2+W3=1; adopting AVG(SS-RSRP)=W1·AVG DT (SS-RSRP)+W2·AVG MR (SS-RSRP)+W3·AVG UR (SS-RSRP) is used to calculate the comprehensive average signal strength of each sub-area, wherein AVG(SS-RSRP) is the comprehensive average signal strength of the sub-area, and AVG DT (SS-RSRP) is the average signal strength of the road test in the sub-slice, AVG MR (SS-RSRP) is the measurement report average signal strength of the sub-slice, AVGUR(SS-RSRP) is the user feedback average signal strength of the sub-slice; AVG(SS-SINR)=W1·AVG DT (SS-SINR)+W2·AVG MR (SS-SINR)+W3·AVG UR (SS-SINR) is calculated to obtain the comprehensive average signal-to-noise ratio of each sub-zone, wherein AVG(SS-SINR) is the comprehensive average signal-to-noise ratio of the sub-zone, and AVG DT (SS-SINR) is the average signal strength of the path test in the sub-slice, AVG MR (SS-SINR) is the average signal-to-noise ratio of the measurement report of the sub-slice, AVG UR(SS-SINR) is the average signal-to-noise ratio of the user feedback in the sub-slice.

[0012] Optionally, when the comprehensive average signal strength of the network of the operator to be evaluated in the target sub-area is less than a predetermined signal strength or the comprehensive average signal-to-noise ratio of the network of the operator to be evaluated in the target sub-area is less than a predetermined signal-to-noise ratio, determining that the network performance of the target sub-area is poor includes: when the network of the operator to be evaluated is jointly built and shared by multiple operators and there is a reference operator, determining the minimum value of the comprehensive average signal strengths of the networks of the multiple operators in the target sub-area as the comprehensive average signal strength of the network of the operator to be evaluated in the target sub-area, and determining the minimum value of the comprehensive average signal strengths of the networks of the multiple operators in the target sub-area as the comprehensive average signal strength of the network of the operator to be evaluated in the target sub-area. The minimum value of the combined average signal-to-noise ratio is determined as the comprehensive average signal-to-noise ratio of the network of the operator to be evaluated in the target sub-area, the comprehensive average signal strength of the network of the reference operator in the target sub-area is determined as the predetermined signal strength, and the comprehensive average signal-to-noise ratio of the network of the reference operator in the target sub-area is determined as the predetermined signal-to-noise ratio; when the comprehensive average signal strength of the network of the operator to be evaluated in the target sub-area is less than the predetermined signal strength or the comprehensive average signal-to-noise ratio of the network of the operator to be evaluated in the target sub-area is less than the predetermined signal-to-noise ratio, it is determined that the network performance of the target sub-area is poor.

[0013] Optionally, the method also includes: determining the test points in the target area whose signal strength is greater than a signal strength threshold and whose signal-to-noise ratio is greater than a signal-to-noise ratio threshold as network coverage available test points; calculating the ratio of the number of network coverage available test points to the total number of the test points in the target area to obtain the network coverage availability rate; and when the network coverage availability rate is less than a predetermined network coverage availability rate, determining the network coverage availability rate difference of the target area.

[0014] Optionally, the method also includes: setting weights of the comprehensive average signal strength and the comprehensive average signal-to-noise ratio; performing weighted averaging of the comprehensive average signal strength and the comprehensive average signal-to-noise ratio of each sub-area according to the weights of the comprehensive average signal strength and the comprehensive average signal-to-noise ratio to obtain a comprehensive score of each sub-area; determining the reciprocal of the distance between the center of each sub-area and the center of the target area as the weight of each sub-area; performing weighted averaging of the comprehensive scores of each sub-area according to the weights of each sub-area to obtain an area comprehensive score of the target area; when there are multiple operators in the target area, calculating the mean and standard deviation of the area comprehensive score according to the area comprehensive scores of each operator in the target area; calculating the standardized difference corresponding to the area comprehensive score of each operator according to the mean and standard deviation of the area comprehensive score; and determining the comprehensive performance difference of the operator whose standardized difference is less than 0.

[0015] Optionally, the method also includes: obtaining a map of the target area; obtaining the comprehensive average signal strength and the comprehensive average signal-to-noise ratio of each of the sub-areas; using a first color to mark the sub-areas in the map whose comprehensive average signal strength is greater than the predetermined signal strength, using a second color to mark the sub-areas in the map whose comprehensive average signal strength is equal to the predetermined signal strength, and using a third color to mark the sub-areas in the map whose comprehensive average signal strength is equal to the predetermined signal strength, to obtain a signal strength display map of the target area; using a fourth color to mark the sub-areas in the map whose comprehensive average signal-to-noise ratio is greater than the predetermined signal-to-noise ratio, using a fifth color to mark the sub-areas in the map whose comprehensive average signal-to-noise ratio is equal to the predetermined signal-to-noise ratio, and using a sixth color to mark the sub-areas in the map whose comprehensive average signal-to-noise ratio is equal to the predetermined signal-to-noise ratio, to obtain a signal-to-noise ratio display map of the target area.

[0016] Optionally, the method also includes: obtaining a map of the target area; obtaining the standardized difference corresponding to the comprehensive score of the area of ​​each operator; marking the operators whose standardized difference is greater than 0 with positive altitude, marking the operators whose standardized difference is equal to 0 with zero altitude, and marking the operators whose standardized difference is less than 0 with negative altitude, to obtain a network coverage comprehensive performance display map of each operator in the target area.

[0017] According to another aspect of the present application, a device for evaluating the performance of a network area is provided, comprising: a division unit, configured to divide a target area into a plurality of sub-areas; and a first calculation unit, configured to perform weighted averaging on network data corresponding to test points in each of the sub-areas to obtain a road test average signal strength, a road test average signal-to-noise ratio, a measurement report average signal strength, a measurement report average signal-to-noise ratio, a user feedback average signal strength, and a user feedback average signal-to-noise ratio of each of the sub-areas, wherein the network data comprises road test data, measurement report data, and user feedback data, wherein the road test data comprises signal strength and signal-to-noise ratio of the test point of the road test, the measurement report data comprises signal strength and signal-to-noise ratio of the test point uploaded by a terminal, and the user feedback data comprises the test point of the user feedback. a second calculating unit, configured to perform a weighted average of the road test average signal strength, the measurement report average signal strength and the user feedback average signal strength of each of the sub-areas to obtain a comprehensive average signal strength of each of the sub-areas, and perform a weighted average of the road test signal-to-noise ratio, the measurement report signal-to-noise ratio and the user feedback signal-to-noise ratio of each of the sub-areas to obtain a comprehensive average signal-to-noise ratio of each of the sub-areas; a first determining unit, configured to determine that the network performance of the target sub-area is poor when the comprehensive average signal strength of the network of the operator to be evaluated in the target sub-area is less than a predetermined signal strength or the comprehensive average signal-to-noise ratio of the network of the operator to be evaluated in the target sub-area is less than a predetermined signal-to-noise ratio, and the target sub-area is any one of the sub-areas.

[0018] According to another aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute any one of the methods described.

[0019] According to another aspect of the present application, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, any one of the methods described above is implemented.

[0020] According to another aspect of the present application, a system for evaluating area network performance is provided, comprising: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include methods for executing any one of the described methods.

[0021] By applying the technical solution of the present application, in the above-mentioned area network performance evaluation method, the target area is divided into multiple sub-areas, and network data corresponding to the test points of each sub-area is obtained, including the drive test data, measurement report data and user feedback data respectively obtained through three channels, and the signal strength of the drive test data of each test point is weighted averaged to obtain the average drive test signal strength of the sub-area, the signal strength of the measurement report data of each test point is weighted averaged to obtain the average measurement report signal strength of the sub-area, and the signal strength of the user feedback data of each test point is weighted averaged to obtain the average user feedback signal strength of the sub-area. Similarly, the average drive test signal-to-noise ratio, the average measurement report signal-to-noise ratio and the average user feedback signal-to-noise ratio of the sub-area are obtained, and the average drive test signal strength, the average measurement report signal strength and the average user feedback signal-to-noise ratio of each sub-area are weighted averaged to obtain the comprehensive The average signal strength is calculated to reflect the signal strength of the entire target area. The average signal-to-noise ratio of the road test, the average signal-to-noise ratio of the measurement report and the average signal-to-noise ratio of the user feedback of each sub-area is weighted averaged to obtain the comprehensive average signal-to-noise ratio of each sub-area to reflect the signal quality of the entire target area. The comprehensive average signal strength of the network of the operator to be evaluated in the target sub-area is less than the predetermined signal strength, indicating that the signal strength of the target sub-area is weak. The comprehensive average signal-to-noise ratio of the network of the operator to be evaluated in the target sub-area is less than the predetermined signal-to-noise ratio, indicating that the signal quality of the target sub-area is poor, that is, the coverage network performance of the operator to be evaluated in the target sub-area is poor and needs to be improved. The method comprehensively evaluates the road test data, the measurement report data and the user feedback data, overcomes the defect that the bias of the single channel data leads to inaccurate evaluation results, and solves the problem of inaccurate evaluation results of network performance in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 A hardware structure block diagram of a mobile terminal for executing a method for evaluating area network performance provided in an embodiment of the present application is shown;

[0023] Figure 2 A schematic diagram of a flow chart of a method for evaluating area network performance provided according to an embodiment of the present application is shown;

[0024] Figure 3 A schematic diagram of a flow chart of another area network performance evaluation method provided according to an embodiment of the present application is shown;

[0025] Figure 4 A structural block diagram of a device for evaluating area network performance provided according to an embodiment of the present application is shown.

[0026] The above drawings include the following reference numerals:

[0027] 102, processor; 104, memory; 106, transmission device; 108, input and output devices. DETAILED DESCRIPTION

[0028] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0029] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0030] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings 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 interchanged where appropriate, so that the embodiments of the present application described here. In addition, the terms "including" and "having" and any of their variations 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.

[0031] For the convenience of description, some nouns or terms involved in the embodiments of the present application are explained below:

[0032] SS-RSRP: Synchronization signal reference signal received power, defined as the linear average of the power contribution (in W) of the SSS resource elements. The SS-RSRP measurement time resources are limited to the SS / PBCH block configuration time (SMTC) window. In simple terms, this parameter represents the signal strength of the wireless base station in the coverage area. The larger the value, the stronger the coverage signal.

[0033] SS-SINR: SS signal-to-noise ratio and interference ratio, defined as the linear average of the power contribution (in W) of the SSS resource elements carried divided by the linear average of the noise and interference power contribution (in W) of the SSS resource elements carried in the same frequency bandwidth. Simply put, this parameter indicates the signal quality of the wireless base station in the coverage area. The larger the value, the better the coverage signal quality.

[0034] DT: Drive Test (DT) refers to driving a vehicle specially equipped with test instruments on a predetermined road to collect and record network performance data along the way, including but not limited to key indicators such as SS-RSRP (synchronization signal reference signal received power) and SS-SINR (SS signal-to-noise ratio and interference ratio), to evaluate the quality and performance of the mobile communication network, support network optimization, troubleshooting and service quality improvement.

[0035] MR: Measurement Report. MR is one of the main bases for evaluating the quality of the wireless environment. In a mobile communication system, a measurement report (MR) is a data report sent by a mobile terminal (such as a smartphone) to a network base station to evaluate the quality of the wireless communication environment. MR contains a series of key indicators, such as the synchronization signal reference signal received power (SS-RSRP), SS signal-to-noise ratio and interference ratio (SS-SINR), etc. These indicators reflect the signal strength and quality of the terminal's location. MR data is an important basis for network operators to optimize the network, troubleshoot, and improve service quality.

[0036] UR: User Report. Different from the above MR which is reported regularly or obtained deliberately during a certain period of time, UR is initiated by users and can provide timely and efficient feedback on network problems. It mainly reports SS-RSRP and SS-SINR.

[0037] As introduced in the background technology, the evaluation results of network performance in the prior art are inaccurate. To solve this technical problem, the embodiments of the present application provide a method for evaluating area network performance, an evaluation device, a computer-readable storage medium, a computer program product and an evaluation system for area network performance.

[0038] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0039] The method embodiments provided in the embodiments of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Taking running on a mobile terminal as an example, Figure 1 FIG. 1 is a hardware structure block diagram of a mobile terminal of a method for evaluating area network performance according to an embodiment of the present invention. Figure 1 As shown, the mobile terminal may include one or more ( Figure 1Only one is shown in the figure) a processor 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data, wherein the mobile terminal may also include a transmission device 106 and an input / output device 108 for communication functions. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the mobile terminal. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations are shown.

[0040] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the method for evaluating the performance of the area network in the embodiment of the present invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, the above method is implemented. The memory 104 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 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the mobile terminal via a network. Examples of the above-mentioned networks include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof. The transmission device 106 is used to receive or send data via a network. The above-mentioned specific examples of the network may include a wireless network provided by a communication provider of the mobile terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0041] In this embodiment, a method for evaluating the performance of an area network running on a mobile terminal, a computer terminal or a similar computing device 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.

[0042] Figure 2 FIG. 1 is a flow chart of a method for evaluating the performance of a network area according to an embodiment of the present application. Figure 2 As shown, the method comprises the following steps:

[0043] Step S201, dividing the target area into multiple sub-areas;

[0044] Step S202, performing weighted averaging on the network data corresponding to the test points of each of the above sub-areas to obtain the average signal strength of the drive test, the average signal-to-noise ratio of the drive test, the average signal strength of the measurement report, the average signal-to-noise ratio of the measurement report, the average signal strength of the user feedback, and the average signal-to-noise ratio of the user feedback of each of the above sub-areas, wherein the above network data includes the drive test data, the measurement report data, and the user feedback data, the above drive test data includes the signal strength and the signal-to-noise ratio of the above test points of the drive test, the above measurement report data includes the signal strength and the signal-to-noise ratio of the above test points uploaded by the terminal, and the above user feedback data includes the signal strength and the signal-to-noise ratio of the above test points fed back by the user;

[0045] Step S203, performing weighted averaging on the drive test average signal strength, the measurement report average signal strength and the user feedback average signal strength of each of the sub-areas to obtain a comprehensive average signal strength of each of the sub-areas, and performing weighted averaging on the drive test average signal-to-noise ratio, the measurement report average signal-to-noise ratio and the user feedback average signal-to-noise ratio of each of the sub-areas to obtain a comprehensive average signal-to-noise ratio of each of the sub-areas;

[0046] Step S204: When the above-mentioned comprehensive average signal strength of the network of the operator to be evaluated in the target sub-area is less than the predetermined signal strength or the above-mentioned comprehensive average signal-to-noise ratio of the network of the operator to be evaluated in the target sub-area is less than the predetermined signal-to-noise ratio, it is determined that the network performance of the above-mentioned target sub-area is poor, and the above-mentioned target sub-area is any one of the above-mentioned sub-areas.

[0047] In the above-mentioned area network performance evaluation method, the target area is divided into multiple sub-areas, and the network data corresponding to the test points in each sub-area is obtained, including the road test data, measurement report data and user feedback data obtained through three channels respectively, and the signal strength of the road test data of each test point is weighted averaged to obtain the road test average signal strength of the sub-area, the signal strength of the measurement report data of each test point is weighted averaged to obtain the measurement report average signal strength of the sub-area, and the signal strength of the user feedback data of each test point is weighted averaged to obtain the user feedback average signal strength of the sub-area. Similarly, the road test average signal-to-noise ratio, measurement report average signal-to-noise ratio and user feedback average signal-to-noise ratio of the sub-area are obtained, and the above-mentioned road test average signal strength, measurement report average signal strength and user feedback average signal strength of each sub-area are weighted averaged to obtain the comprehensive average signal strength of each sub-area. Strength is used to reflect the signal strength of the entire target area. The average signal-to-noise ratio of the road test, the average signal-to-noise ratio of the measurement report and the average signal-to-noise ratio of the user feedback of each sub-area is weighted averaged to obtain the comprehensive average signal-to-noise ratio of each sub-area to reflect the signal quality of the entire target area. The comprehensive average signal strength of the network of the operator to be evaluated in the target sub-area is less than the predetermined signal strength, indicating that the signal strength of the target sub-area is weak. The comprehensive average signal-to-noise ratio of the network of the operator to be evaluated in the target sub-area is less than the predetermined signal-to-noise ratio, indicating that the signal quality of the target sub-area is poor, that is, the coverage network performance of the operator to be evaluated in the target sub-area is poor and needs to be improved. The method comprehensively evaluates the road test data, measurement report data and user feedback data, overcomes the defect that the bias of a single channel data leads to inaccurate evaluation results, and solves the problem of inaccurate evaluation results of network performance in the prior art.

[0048] It should be noted that the Drive Test (DT) data collection: the SS-RSRP and SS-SINR of each operator in each grid are collected through drive testing, namely DT (SS-RSRP) and DT (SS-SINR); the drive test method adopted can be to use a test terminal with a built-in SIM card of the corresponding operator and connected to a professional test tool (such as Dingli Pilot Pioneer), to perform point tests at fixed time intervals, and the above-mentioned network parameters of the corresponding operator can be output through professional tools. As an example, three mobile phones with built-in SIM cards of different operators are used as test terminals. According to GPS positioning, the three mobile phones are moved to multiple random positions in the grid to be tested, and data is collected every one second. The data collected by each mobile phone is output through professional tools. Measurement Report (MR) data collection: The SS-RSRP and SS-SINR of each operator in each grid are collected through Measurement Report (MR), namely MR (SS-RSRP) and MR (SS-SINR); the method adopted is that the user equipment (such as smart phones) regularly sends measurement reports containing key indicators such as SS-RSRP and SS-SINR to the network base station during normal use. These reports are collected and processed by the network background system to form a data set with time and geographic location information; as an example, the user equipment moves in a specified area and spontaneously reports measurement reports at different locations. The background system classifies these reports into the corresponding grid according to the GPS positioning information. Each report contains the location of the user equipment at a certain moment, SS-RSRP and SS-SINR and other information, and the various network parameters in each report are output after processing by professional tools. Data collection based on user feedback (UR): The SS-RSRP and SS-SINR of each operator in each grid are collected through active user feedback, namely UR (SS-RSRP) and UR (SS-SINR); the method adopted is that when user devices (such as smartphones) encounter network problems, they actively submit reports containing key indicators such as SS-RSRP and SS-SINR through dedicated applications or channels. These reports contain the user's location at a certain moment, timestamp and description of the problem encountered; as an example, users can mark the location where they think the network performance is poor in the interactive map tool and provide basic information (such as time, device type, description of the problem encountered, etc.). These reports are collected and processed by the background system to form a data set with time and geographic location information, which is used to evaluate network performance and identify problem areas.

[0049] In order to implement the area division taking into account user density and geographical characteristics, in an optional implementation, the above step S201 includes:

[0050] Step S2011, obtaining a map of the target area;

[0051] Step S2012, dividing the target area into N sub-areas on the map, such that the boundaries of the sub-areas are located on the roads on the map and the areas of the sub-areas are smaller than a predetermined area, N≥2;

[0052] Step S2013, performing weighted average on the user number density, data flow density and connection number density of each of the above sub-areas respectively, to obtain the network usage density of each of the above sub-areas, wherein the user number density is the ratio of the total number of users in the above sub-area to the area of ​​the above sub-area, the data flow density is the ratio of the total data flow of the above sub-area within a predetermined time period to the area of ​​the above sub-area, and the connection number density is the ratio of the number of connections of the above users in the above sub-area to the network within the predetermined time period to the area of ​​the above sub-area;

[0053] Step S2014, calculating the average value of the network usage density of each of the sub-areas to obtain the average network usage density of the target area;

[0054] Step S2015, New Grid Size = Base Grid Size × (1 + (Network Density - Average Density) / (Average Density)) is used to calculate the adjusted area of ​​each of the above sub-areas, wherein New Grid Size is the adjusted area, Base Grid Size is the area of ​​the above sub-area before adjustment, Network Density is the above network usage density of the above sub-area, and Average Density is the above average network usage density;

[0055] Step S2016: re-divide the target area according to the adjusted areas of the sub-areas to obtain a plurality of sub-areas.

[0056] In the above implementation, the target area division can be based on the static grid division of fixed size of longitude and latitude, and the grid division is performed on several designated areas. Specifically, the geographical area can be grid-divided according to the longitude and latitude. For example, the geographical area is divided according to the longitude and latitude to obtain a 20m*20m rectangular grid network, and one grid corresponds to one sub-area. Of course, the dynamic grid division based on user density and geographical features can also be performed to divide the above target area into N sub-areas, and consider drawing grids along streets or traffic routes to better capture the network performance differences in the city, and the area of ​​the above sub-area is less than the predetermined area to meet the fine-grained requirements, NetworkDensity=w uUserDwnsity+w t Traffic Density+w c ConnectionDensity; NetworkDensit is the network usage density, UserDensity is the user number density, TrafficDensity is the data traffic density, ConnectionDensity is the connection number density, and w u 、w t and w c are the weights for the number of users, data traffic and number of connections respectively, and these weights can be set according to actual conditions; according to the network usage density, the grid size of each sub-area is adjusted; in simple terms, the high-density area is divided into a larger grid, and the low-density area is divided into a smaller grid, so that the proportion of grids with weak signals and poor user perception can be increased, ensuring that the network performance data is more accurate and has analytical significance. The specific calculation formula is as follows: New Grid Size = Base GridSize × (1 + (Network Density-Average Density) / (Average Density)) The adjusted area of ​​each of the above sub-areas is calculated, where New Grid Size is the adjusted area, Base Grid Size is the area before adjustment of the above sub-area, Network Density is the above network usage density of the above sub-area, and Average Density is the above average network usage density. By adopting a division method based on user density and geographical features, the size and shape of the grid can be dynamically adjusted according to network usage and the geographical characteristics of the area, so as to better reflect the network performance differences.

[0057] In order to meet the fine-grained requirement of the area division, in an optional implementation manner, the above step S2012 includes:

[0058] Step S20121, using a quadtree algorithm to divide the target area into the four sub-areas, so that the boundaries of the sub-areas are located on the roads on the map;

[0059] Step S20122, a division step, in which, when the area of ​​the target sub-region is larger than the predetermined area, the target sub-region is divided into four new sub-regions using the quadtree algorithm, and the target sub-region is any one of the sub-regions;

[0060] Step S20123, repeat the above division step at least once until the areas of all the above sub-regions are smaller than the above predetermined area, and N above sub-regions are obtained.

[0061] In the above implementation, a quadtree algorithm is used to divide the specified area into smaller sub-areas, and these sub-areas are used as the starting points for grid division; the construction of the quadtree can be completed by a recursive method, starting from the root node, and recursively executing the following steps to construct the quadtree: A. Check whether the current node needs to be divided; B. If division is required, divide the current node into four child nodes, each child node represents four sub-areas of the current node area, and calculate the boundary coordinates of the child nodes; C. Recursively perform the same division process on each child node until the required granularity is reached or the stopping condition is met, one child node corresponds to one sub-area, the granularity can be that the area of ​​all the above sub-areas is less than the above predetermined area, and the stopping condition can be that the number of repetitions reaches the maximum number, thereby obtaining the N above sub-areas that meet the requirements.

[0062] In order to accurately evaluate network performance, in an optional implementation, the above step S202 includes:

[0063] Step S2021, dividing the grid of the target sub-region into a plurality of sub-grids;

[0064] Step S2022, according to Calculate the time difference weight of each of the above test points in each of the above sub-grids, Weigh_t ji is the time difference weight of the i-th test point in the j-th subgrid, Timedifference ji is the time difference between the acquisition time of the network data of the i-th test point in the j-th sub-grid and the current time, ∈ is a constant;

[0065] Step S2023, weighted averaging the network data corresponding to the test points according to the time difference weights of the test points in the sub-grids, to obtain the road test average signal strength, the road test average signal-to-noise ratio, the measurement report average signal strength, the measurement report average signal-to-noise ratio, the user feedback average signal strength, and the user feedback average signal-to-noise ratio of the target sub-area.

[0066] In the above implementation, when there are three operators, first, for each data source (DT, MR, UR), the average value AVG is calculated, including: AVG DT (SS-RSRP of operator No. 1), AVG DT (SS-RSRP of operator No. 2), AVG DT (SS-RSRP of operator No. 3), AVG DT (SS-SINR of operator No. 1), AVG DT (SS-SINR of operator No. 2), AVGDT (SS-SINR of operator No. 3); AVG MR(SS-RSRP of operator No. 1), AVG MR (SS-RSRP of operator No. 2), AVG MR (SS-RSRP of operator No. 3), AVG MR (SS-SINR of operator No. 1), AVG MR (SS-SINR of operator No. 2), AVG MR (SS-SINR of operator No. 3);AVG UR (SS-RSRP of operator No. 1), AVG UR (SS-RSRP of operator No. 2), AVG UR (SS-RSRP of operator No. 3), AVG UR (SS-SINR of operator No. 1), AVG UR (SS-SINR of operator No. 2), AVG UR (SS-SINR of operator No. 3). The average value can be calculated by ordinary average or weighted average. For example, when weighted average is used, AVG DT (No. 1 operator SS-RSRP), the following method can be used: the grid of the current sub-area is further divided into several sub-grids (for example, a rectangular grid of 5m*5m), and for the drive test data falling into the same sub-grid, the collection time of different data is considered, so that the data collected closer to the current time has a higher weight. Taking AVG (No. 1 operator SS-RSRP) as an example, the calculation formula is as follows: AVG (No. 1 operator DT, MR, UR) data are all calculated using the same formula, where SS-RSRP ji is the SS-RSRP value of operator 1 collected at the ith test point in the jth subgrid, n is the number of test points in the jth subgrid, m is the number of subgrids in the current grid, and Weigh_t ji is the time difference weight of the ith test point in the jth subgrid, which can be set according to the acquisition time. As an example: Among them, Weigh_t ji is the time difference weight of the i-th test point in the j-th sub-grid. ji is the time difference between the acquisition time of the network data of the ith test point in the jth subgrid and the current time. ∈ is a constant to avoid division by zero. It is usually a very small positive number, such as 1×10 -6 .

[0067] In order to comprehensively consider the influence of the drive test data, the measurement report data and the user feedback data, in an optional implementation manner, the above step S203 includes:

[0068] Step S2031, setting the weight W1 of the drive test data, the weight W2 of the measurement report data and the weight W3 of the user feedback data so that W1+W2+W3=1;

[0069] Step S2032: adopt AVG(SS-RSRP)=W1·AVG DT (SS-RSRP)+W2·AVG MR (SS-RSRP)+W3·AVG UR (SS-RSRP) is calculated to obtain the above-mentioned comprehensive average signal strength of each of the above-mentioned sub-areas, wherein AVG(SS-RSRP) is the above-mentioned comprehensive average signal strength of the above-mentioned sub-areas, and AVG DT (SS-RSRP) is the average signal strength of the above-mentioned road test in the above-mentioned sub-area, AVG MR (SS-RSRP) is the average signal strength of the measurement report of the above sub-slice, AVG UR (SS-RSRP) is the average signal strength fed back by the user in the sub-area;

[0070] Step S2033, the above-mentioned comprehensive average signal-to-noise ratio of each of the above-mentioned sub-areas is calculated by using AVG(SS-SINR)=W1·AVGDT(SS-SINR)+W2·AVGMR(SS-SINR)+W3·AVGUR(SS-SINR), wherein AVG(SS-SINR) is the above-mentioned comprehensive average signal-to-noise ratio of the above-mentioned sub-area, and AVG DT (SS-SINR) is the average signal strength of the above-mentioned road test in the above-mentioned sub-area, AVG MR (SS-SINR) is the average signal-to-noise ratio of the measurement report of the above sub-slice, AVG UR (SS-SINR) is the average signal-to-noise ratio of the user feedback in the sub-area.

[0071] In the above implementation, after calculating the average value of the single performance indicator of each data source, the comprehensive average value can be further calculated. The specific calculation formula is as follows: AVG (SS-RSRP) = W1 * AVG DT (SS-RSRP)+W2*AVG MR (SS-RSRP)+W3*AVG UR (SS-RSRP), AVG (SS-SINR) = W1*AVG DT (SS-SINR)+W2*AVG MR(SS-SINR)+W3*AVGUR(SS-SINR), where W1, W2, and W3 are used for the weights of DT, MR, and UR data in SS-RSRP and SS-SINR, respectively. In order to reasonably balance the contribution of different data sources (DT, MR, and UR) in calculating the comprehensive score, the weights W1, W2, and W3 should be set based on factors such as the reliability, importance, timeliness, and coverage of the data source. Specifically, DT data is considered the most reliable data source due to its characteristics of being collected in a controlled environment, so it is given a higher weight W1; MR data is also given a higher weight W2 due to its wide coverage and long-term stability; UR data is given a certain weight W3 due to its real-time and direct user feedback, although its reliability is slightly lower. Based on this, the initial weights W1=0.4, W2=0.4, and W3=0.2 are set, and the weights can be adjusted according to different scenarios such as dense urban villages, high-end office buildings, and open roads. This ensures that the comprehensive score fully considers the reliability and extensiveness of DT and MR data, as well as the real-time nature of UR data, thereby providing a comprehensive and accurate network performance evaluation result.

[0072] In order to find out the sub-area with poor network performance, in an optional implementation manner, the above step S204 includes:

[0073] Step S2041, in the case where the network of the operator to be evaluated is jointly built and shared by multiple operators and there is a reference operator, the minimum value of the above-mentioned comprehensive average signal strengths of the networks of the multiple operators in the above-mentioned target sub-area is determined as the above-mentioned comprehensive average signal strength of the network of the operator to be evaluated in the above-mentioned target sub-area, the minimum value of the above-mentioned comprehensive average signal-to-noise ratios of the networks of the multiple operators in the above-mentioned target sub-area is determined as the above-mentioned comprehensive average signal-to-noise ratio of the network of the operator to be evaluated in the above-mentioned target sub-area, the above-mentioned comprehensive average signal strength of the network of the reference operator in the above-mentioned target sub-area is determined as the above-mentioned predetermined signal strength, and the above-mentioned comprehensive average signal-to-noise ratio of the network of the reference operator in the above-mentioned target sub-area is determined as the above-mentioned predetermined signal-to-noise ratio;

[0074] Step S2042: When the comprehensive average signal strength of the network of the operator to be evaluated in the target sub-area is less than the predetermined signal strength or the comprehensive average signal-to-noise ratio of the network of the operator to be evaluated in the target sub-area is less than the predetermined signal-to-noise ratio, it is determined that the network performance of the target sub-area is poor.

[0075] In the above implementation, since Operator No. 1 and Operator No. 2 implement 5G co-construction and sharing nationwide, the network performance quality received by the mobile terminals of both parties is basically the same. For the convenience of analysis, Operator No. 1 and Operator No. 2 are selected to compare with Operator No. 3, that is, SS-RSRP difference = MIN(AVG(Operator No. 1 SS-RSRP), AVG(Operator No. 2 SS-RSRP))-AVG(Operator No. 3 SS-RSRP), SS-SINR difference = MIN(AVG(Operator No. 1 SS-SINR), AVG(Operator No. 2 SS-SINR))-AVG(Operator No. 3 SS-SINR). The area where the SS-RSRP difference or SS-SINR difference is a negative number is the sub-area where Operator No. 1 and Operator No. 2 need to focus on improving the network quality.

[0076] In order to find out the area with poor network coverage availability, in an optional implementation manner, the method further includes:

[0077] Step S301, determining the test points in the target area whose signal strength is greater than a signal strength threshold and whose signal-to-noise ratio is greater than a signal-to-noise ratio threshold as network coverage available test points;

[0078] Step S302, calculating the ratio of the number of the network coverage available test points to the total number of the test points in the target area to obtain the network coverage availability rate;

[0079] Step S303: when the network coverage availability is less than a predetermined network coverage availability, determine the network coverage availability difference of the target area.

[0080] In the above implementation, the network coverage availability C of the main operator and the target operator in each area is calculated; the calculation method of the network coverage availability C is: using the test point that satisfies the conditions of SS-RSRP>-105dBm and SS-SINR>-3dBm as the numerator, all the test points as the denominator, and dividing the numerator and the denominator to obtain the network coverage availability C; if the above network coverage availability C is less than the predetermined network coverage availability, then the network coverage availability difference of the target area, of course, the network coverage availability difference between the main operator and the target operator can also be calculated: the worse side of operator No. 1 and operator No. 2 is selected and subtracted from operator No. 2, that is, network coverage availability difference = MIN (operator No. 1 C, operator No. 2 C) - operator No. 3 C. The area where the network coverage availability difference is a negative number is the area where operator No. 1 and operator No. 2 need to focus on improving network coverage.

[0081] In order to analyze the comprehensive score of the area, in an optional implementation, the method further includes:

[0082] Step S401, setting weights of the above-mentioned comprehensive average signal strength and the above-mentioned comprehensive average signal-to-noise ratio;

[0083] Step S402, performing weighted averaging on the comprehensive average signal strength and the comprehensive average signal-to-noise ratio of each of the sub-areas according to the weights of the comprehensive average signal strength and the comprehensive average signal-to-noise ratio, to obtain a comprehensive score for each of the sub-areas;

[0084] Step S403, determining the reciprocal of the distance between the center of each of the sub-areas and the center of the target area as the weight of each of the sub-areas;

[0085] Step S404, performing weighted averaging on the comprehensive scores of the sub-areas according to the weights of the sub-areas to obtain a comprehensive score of the target area;

[0086] Step S405, when there are multiple operators in the target area, calculate the mean and standard deviation of the area comprehensive score according to the area comprehensive scores of the operators in the target area;

[0087] Step S406, calculating the standardized difference corresponding to the comprehensive scores of the above-mentioned areas of each of the above-mentioned operators according to the mean and standard deviation of the comprehensive scores of the above-mentioned areas;

[0088] Step S407: determining the comprehensive performance difference of the above-mentioned operators whose standardized difference value is less than 0.

[0089] In the above implementation, the composite score of each grid is calculated based on SS-RSRP and SS-SINR: CompositeScore i =α1×AVG(SS-RSRP) i +α2×AVG(SS-SINR) i , where CompositeScore i is the comprehensive score of the i-th grid, AVG(SS-RSRP) i 、AVG(SS-SINR) i are the mean values ​​of SS-RSRP and SS-SINR of the Ith grid (see above for details), α1, α2, are the weights of SS-RSRP and SS-SINR, which can be set according to actual conditions; the comprehensive score of the area is calculated based on the comprehensive score of each grid: Among them, Area Comprehensive Score is the comprehensive score of the area, Composite Score i is the comprehensive score of the i-th grid in the area, n is the number of grids in the area, Weight_l iRepresents the geographic location weight of the i-th grid, which can be set according to the geographic location and regional importance. As an example: Among them, Weight_l i is the geographical location weight of the i-th grid, Distance i is the distance from the center of the ith grid to the center of the patch, which can be calculated using longitude and latitude coordinates. i is the regional importance of the ith grid, which can be set by the user to indicate the importance of a specific region to the overall area; calculate the difference in standardized area comprehensive scores between the subject operator and the target operator. As an example: calculate the mean of the area comprehensive scores of all operators: Where N is the total number of operators, Area Composite Score i is the comprehensive score of the area of ​​the ith operator; calculate the standard deviation of the comprehensive scores of the areas of all operators: Calculate the standardized difference of the k-th operator's comprehensive district score: Among them, Standardized Difference k is the standardized difference of the kth operator’s area composite score, Area Composite Score k is the comprehensive score of the k-th operator in the area, is the mean calculated as above, and SD is the standard deviation calculated as above. By calculating the difference in the above standardized area comprehensive scores, the comprehensive performance of the main operator and the target operator in the specified area can be intuitively compared. If the difference is a positive value, it means that the comprehensive performance of the main operator in the area is higher than that of the target operator. If it is a negative value, it means that the comprehensive performance of the main operator needs to be improved.

[0090] In order to achieve intuitive presentation of network performance differences, in an optional implementation manner, the method further includes:

[0091] Step S501, obtaining a map of the target area;

[0092] Step S502, obtaining the above-mentioned comprehensive average signal strength and the above-mentioned comprehensive average signal-to-noise ratio of each of the above-mentioned sub-areas;

[0093] Step S503, using a first color to mark the sub-area in the map where the comprehensive average signal strength is greater than the predetermined signal strength, using a second color to mark the sub-area in the map where the comprehensive average signal strength is equal to the predetermined signal strength, and using a third color to mark the sub-area in the map where the comprehensive average signal strength is equal to the predetermined signal strength, to obtain a signal strength display map of the target area;

[0094] Step S504: Use a fourth color to mark the sub-area in the map where the comprehensive average signal-to-noise ratio is greater than the predetermined signal-to-noise ratio, use a fifth color to mark the sub-area in the map where the comprehensive average signal-to-noise ratio is equal to the predetermined signal-to-noise ratio, and use a sixth color to mark the sub-area in the map where the comprehensive average signal-to-noise ratio is equal to the predetermined signal-to-noise ratio, to obtain a signal-to-noise ratio display map of the target area.

[0095] In the above implementation, the individual differential mark of each grid is determined according to the individual performance difference; specifically, different color marks are used to visualize the size of the difference, for example, when the difference is positive, a green mark is used, indicating that the performance of operator 1 and operator 2 is better; when the difference is zero, a yellow mark is used, indicating that the performance of operator 1 and operator 2 is the same as that of operator 3; when the difference is negative, an orange or red mark is used, indicating that the performance of operator 1 and operator 2 is poor; the color selection rules can be adjusted according to actual conditions, such as using a more detailed grading method and a more optimized difference evaluation method. Based on the above individual differential marks and the initial map, a single differential display map is generated; specifically, the color mark is added to the corresponding grid of the initial map, and the strength of the individual network performance of each grid is presented through a map with different color marks.

[0096] In order to achieve intuitive presentation of network performance differences, in an optional implementation manner, the method further includes:

[0097] Step S601, obtaining a map of the target area;

[0098] Step S602, obtaining the standardized difference corresponding to the comprehensive score of the area of ​​each of the operators;

[0099] Step S603, using positive altitude to mark the above-mentioned operators whose standardized difference is greater than 0, using zero altitude to mark the above-mentioned operators whose standardized difference is equal to 0, and using negative altitude to mark the above-mentioned operators whose standardized difference is less than 0, to obtain a network coverage comprehensive performance display map of each of the above-mentioned operators in the above-mentioned target area.

[0100] In the above implementation, the comprehensive differentiation mark of each area is determined based on the above comprehensive performance difference; specifically, different altitude marks are used to visualize the difference size. For example, when the difference is positive, 10m altitude is used, indicating that the performance of operator 1 and operator 2 is better; when the difference is zero, zero point altitude is used, indicating that the performance of operator 1 and operator 2 is the same as that of operator 3; when the difference is negative, -10m altitude is used, indicating that the performance of operator 1 and operator 2 is poor; the altitude selection rules can be adjusted according to actual conditions, such as using a more detailed grading method and a more optimized difference evaluation method. Based on the above comprehensive differentiation mark and the initial map, a comprehensive differentiation display map is generated; specifically, the altitude mark is added to the corresponding area of ​​the initial map, and the comprehensive network performance of each area is presented through a map with different altitude marks.

[0101] It should be noted that, through the interactive map tool, interactive functions are provided on the single-item differentiated display map and the comprehensive differentiated display map, and users can hover over a specific area to obtain detailed information, or click to display the performance data of a specific grid. In addition, users are allowed to mark the location where they think the network performance is poor on the interactive map, and provide basic information (such as time, device type, description of the problem encountered, etc.). By applying color marking and altitude marking to the initial map, the single-item differentiated display map and the comprehensive differentiated display map are generated, which can not only intuitively present the network performance differences of each grid and area, but also provide rich user interactive functions through the interactive map tool. Users can hover over a specific area to obtain detailed information, click to display the performance data of a specific grid, and can mark the location where they think the network performance is poor on the map, and provide basic information (such as time, device type, description of the problem encountered, etc.). The advantage of this design is that it not only enhances the readability and information transmission efficiency of the map, but also improves the user's participation and feedback speed, thereby providing an effective means for network operators to quickly identify problem areas and take targeted optimization measures.

[0102] In order to enable those skilled in the art to more clearly understand the technical solution of the present application, the implementation process of the method for evaluating the performance of a network area of ​​the present application will be described in detail below in conjunction with specific embodiments.

[0103] This embodiment relates to a specific method for evaluating the performance of a network in a specific area. Figure 3 As shown, the following steps are included:

[0104] Step 1: Fixed-size static grid division based on longitude and latitude and dynamic grid division based on user density and geographic features;

[0105] Step 2: Obtain network data of the main operator and at least one target operator in grids of several designated areas through drive testing, measurement reports and user feedback;

[0106] Step 3: Based on the above network data, determine the individual performance difference between the main operator and the target operator in each grid and the comprehensive performance difference in each area;

[0107] Step 4: Determine the individual differential mark of each grid and the comprehensive differential mark of each area according to the individual performance difference and the comprehensive performance difference;

[0108] Step 5: Generate a single-item differentiation display map and a comprehensive differentiation display map based on the single-item differentiation mark, the comprehensive differentiation mark and the initial map.

[0109] As shown in Table 1, the network coverage availability of China Telecom, China Unicom and China Mobile in different areas are calculated. Among them, the coverage availability of China Telecom, China Unicom and China Mobile in Futian area are 98.80%, 98.86% and 98.22% respectively. Therefore, the difference in the coverage availability of the three networks can be calculated = MIN (C Telecom, C Unicom) - C Mobile = 98.80% - 98.22% = 0.58pp.

[0110] Table 1

[0111]

[0112] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0113] The embodiment of the present application also provides an evaluation device for the performance of a district network. It should be noted that the evaluation device for the performance of a district network in the embodiment of the present application can be used to execute the evaluation method for the performance of a district network provided in the embodiment of the present application. The device is used to implement the above-mentioned embodiments and preferred implementation modes, and those that have been described will not be repeated. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0114] The following is an introduction to the area network performance evaluation device provided in an embodiment of the present application.

[0115] Figure 4 is a structural block diagram of a device for evaluating the performance of a network area according to an embodiment of the present application. Figure 4 As shown, the device comprises:

[0116] A division unit 10, configured to divide the target area into a plurality of sub-areas;

[0117] A first calculation unit 20 is configured to perform weighted averaging on the network data corresponding to the test points of each of the above sub-areas to obtain the average signal strength of the drive test, the average signal-to-noise ratio of the drive test, the average signal strength of the measurement report, the average signal-to-noise ratio of the measurement report, the average signal strength of the user feedback, and the average signal-to-noise ratio of the user feedback of each of the above sub-areas, wherein the above network data includes the drive test data, the measurement report data, and the user feedback data, the above drive test data includes the signal strength and the signal-to-noise ratio of the above test points of the drive test, the above measurement report data includes the signal strength and the signal-to-noise ratio of the above test points uploaded by the terminal, and the above user feedback data includes the signal strength and the signal-to-noise ratio of the above test points fed back by the user;

[0118] The second calculation unit 30 is configured to perform a weighted average of the drive test average signal strength, the measurement report average signal strength and the user feedback average signal strength of each of the above sub-areas to obtain a comprehensive average signal strength of each of the above sub-areas, and perform a weighted average of the drive test signal-to-noise ratio, the measurement report signal-to-noise ratio and the user feedback signal-to-noise ratio of each of the above sub-areas to obtain a comprehensive average signal-to-noise ratio of each of the above sub-areas;

[0119] The first determination unit 40 is used to determine that the network performance of the target sub-area is poor when the above-mentioned comprehensive average signal strength of the network of the operator to be evaluated in the target sub-area is less than the predetermined signal strength or the above-mentioned comprehensive average signal-to-noise ratio of the network of the operator to be evaluated in the target sub-area is less than the predetermined signal-to-noise ratio. The above-mentioned target sub-area is any one of the above-mentioned sub-areas.

[0120] In the above-mentioned area network performance evaluation device, the target area is divided into multiple sub-areas, and the network data corresponding to the test points of each sub-area is obtained, including the drive test data, measurement report data and user feedback data respectively obtained through three channels, and the signal strength of the drive test data of each test point is weighted averaged to obtain the average drive test signal strength of the sub-area, the signal strength of the measurement report data of each test point is weighted averaged to obtain the average measurement report signal strength of the sub-area, and the signal strength of the user feedback data of each test point is weighted averaged to obtain the average user feedback signal strength of the sub-area. Similarly, the average drive test signal-to-noise ratio, the average measurement report signal-to-noise ratio and the average user feedback signal-to-noise ratio of the sub-area are obtained, and the above-mentioned average drive test signal strength, the average measurement report signal strength and the average user feedback signal strength of each sub-area are weighted averaged to obtain the comprehensive average signal strength of each sub-area. Strength is used to reflect the signal strength of the entire target area. The average signal-to-noise ratio of the road test, the average signal-to-noise ratio of the measurement report and the average signal-to-noise ratio of the user feedback of each sub-area is weighted averaged to obtain the comprehensive average signal-to-noise ratio of each sub-area to reflect the signal quality of the entire target area. The comprehensive average signal strength of the network of the operator to be evaluated in the target sub-area is less than the predetermined signal strength, indicating that the signal strength of the target sub-area is weak. The comprehensive average signal-to-noise ratio of the network of the operator to be evaluated in the target sub-area is less than the predetermined signal-to-noise ratio, indicating that the signal quality of the target sub-area is poor, that is, the coverage network performance of the operator to be evaluated in the target sub-area is poor and needs to be improved. The method comprehensively evaluates the road test data, measurement report data and user feedback data, overcomes the defect that the bias of a single channel data leads to inaccurate evaluation results, and solves the problem of inaccurate evaluation results of network performance in the prior art.

[0121] In order to implement the area division taking into account user density and geographical characteristics, in an optional implementation, the above-mentioned division unit includes:

[0122] An acquisition module is used to acquire a map of the target area;

[0123] A first division module is used to divide the target area into N sub-areas on the map, so that the boundaries of the sub-areas are located on the roads on the map and the areas of the sub-areas are smaller than a predetermined area, N≥2;

[0124] A first calculation module is used to perform weighted average of the user number density, data flow density and connection number density of each of the above sub-areas to obtain the network usage density of each of the above sub-areas, wherein the user number density is the ratio of the total number of users in the above sub-area to the area of ​​the above sub-area, the data flow density is the ratio of the total data flow of the above sub-area within a predetermined time period to the area of ​​the above sub-area, and the connection number density is the ratio of the number of connections of the above users in the above sub-area to the network within the predetermined time period to the area of ​​the above sub-area;

[0125] A second calculation module is used to calculate the average value of the network usage density of each of the sub-areas to obtain the average network usage density of the target area;

[0126] A third calculation module is used to calculate the adjusted area of ​​each of the sub-areas by New Grid Size=Base Grid Size×(1+(NetworkDensity-Average Density) / (Average Density)), wherein New Grid Size is the adjusted area, Base Grid Size is the area of ​​the sub-area before adjustment, NetworkDensity is the network usage density of the sub-area, and Average Density is the average network usage density;

[0127] The second division module is used to re-divide the target area according to the adjusted areas of each of the sub-areas to obtain a plurality of sub-areas.

[0128] In order to meet the fine-grained requirement of the area division, in an optional implementation manner, the first division module includes:

[0129] The first division submodule is used to divide the target area into the four sub-areas by using a quadtree algorithm, so that the boundaries of the sub-areas are located on the roads in the map;

[0130] A second division submodule is used to perform the division step, and when the area of ​​the target subregion is larger than the predetermined area, the target subregion is divided into four new subregions by using the quadtree algorithm, and the target subregion is any one of the subregions;

[0131] The repeating submodule is used to repeat the above division step at least once until the areas of all the above sub-regions are smaller than the above predetermined area, thereby obtaining N above sub-regions.

[0132] In order to accurately evaluate network performance, in an optional implementation manner, the first calculation unit includes:

[0133] A third division module is used to divide the grid of the target sub-region into a plurality of sub-grids;

[0134] The fourth calculation module is used to calculate Calculate the time difference weight of each of the above test points in each of the above sub-grids, Weigh_t ji is the time difference weight of the i-th test point in the j-th sub-grid. jiis the time difference between the acquisition time of the network data of the i-th test point in the j-th sub-grid and the current time, ∈ is a constant;

[0135] The fifth calculation module is used to perform weighted averaging on the network data corresponding to the test points according to the time difference weights of the test points in the sub-grids to obtain the road test average signal strength, the road test average signal-to-noise ratio, the measurement report average signal strength, the measurement report average signal-to-noise ratio, the user feedback average signal strength and the user feedback average signal-to-noise ratio of the target sub-area.

[0136] In order to comprehensively consider the influence of the drive test data, the measurement report data and the user feedback data, in an optional implementation manner, the second calculation unit includes:

[0137] A setting module, used to set the weight W1 of the drive test data, the weight W2 of the measurement report data and the weight W3 of the user feedback data, so that W1+W2+W3=1;

[0138] The sixth calculation module is used to adopt AVG(SS-RSRP)=W1·AVG DT (SS-RSRP)+W2·AVG MR (SS-RSRP)+W3·AVG UR (SS-RSRP) is calculated to obtain the above-mentioned comprehensive average signal strength of each of the above-mentioned sub-areas, wherein AVG(SS-RSRP) is the above-mentioned comprehensive average signal strength of the above-mentioned sub-areas, and AVG DT (SS-RSRP) is the average signal strength of the above-mentioned road test in the above-mentioned sub-area, AVG MR (SS-RSRP) is the average signal strength of the measurement report of the above sub-slice, AVG UR (SS-RSRP) is the average signal strength fed back by the user in the sub-area;

[0139] The seventh calculation module is used to calculate the above-mentioned comprehensive average signal-to-noise ratio of each of the above-mentioned sub-areas by using AVG(SS-SINR)=W1·AVGDT(SS-SINR)+W2·AVGMR(SS-SINR)+W3·AVGUR(SS-SINR), wherein AVG(SS-SINR) is the above-mentioned comprehensive average signal-to-noise ratio of the above-mentioned sub-areas, and AVG DT (SS-SINR) is the average signal strength of the above-mentioned road test in the above-mentioned sub-area, AVG MR (SS-SINR) is the average signal-to-noise ratio of the measurement report of the above sub-slice, AVG UR (SS-SINR) is the average signal-to-noise ratio of the user feedback in the sub-area.

[0140] In order to find out the sub-area with poor network performance, in an optional implementation manner, the first determining unit includes:

[0141] A first determination module is used for, when the network of the operator to be evaluated is jointly built and shared by multiple operators and there is a reference operator, determining the minimum value of the above-mentioned comprehensive average signal strengths of the networks of the multiple operators in the above-mentioned target sub-area as the above-mentioned comprehensive average signal strength of the network of the operator to be evaluated in the above-mentioned target sub-area, determining the minimum value of the above-mentioned comprehensive average signal-to-noise ratios of the networks of the multiple operators in the above-mentioned target sub-area as the above-mentioned comprehensive average signal-to-noise ratio of the network of the operator to be evaluated in the above-mentioned target sub-area, determining the above-mentioned comprehensive average signal strength of the network of the reference operator in the above-mentioned target sub-area as the above-mentioned predetermined signal strength, and determining the above-mentioned comprehensive average signal-to-noise ratio of the network of the reference operator in the above-mentioned target sub-area as the above-mentioned predetermined signal-to-noise ratio;

[0142] The second determination module is used to determine that the network performance of the above-mentioned target sub-area is poor when the above-mentioned comprehensive average signal strength of the network of the above-mentioned operator to be evaluated in the above-mentioned target sub-area is less than the above-mentioned predetermined signal strength or the above-mentioned comprehensive average signal-to-noise ratio of the network of the above-mentioned operator to be evaluated in the above-mentioned target sub-area is less than the above-mentioned predetermined signal-to-noise ratio.

[0143] In order to find out the area with poor network coverage availability, in an optional implementation manner, the above-mentioned device further includes:

[0144] A second determining unit is used to determine the test point in the target area whose signal strength is greater than a signal strength threshold and whose signal-to-noise ratio is greater than a signal-to-noise ratio threshold as a network coverage available test point;

[0145] A third calculation unit is used to calculate the ratio of the number of the network coverage available test points to the total number of the test points in the target area to obtain a network coverage availability rate;

[0146] The third determining unit is used to determine the network coverage availability difference of the target area when the network coverage availability is less than the predetermined network coverage availability.

[0147] In order to analyze the comprehensive score of the area, in an optional implementation, the above-mentioned device further includes:

[0148] A setting unit, used to set the weight of the above-mentioned comprehensive average signal strength and the above-mentioned comprehensive average signal-to-noise ratio;

[0149] a fourth calculation unit, configured to perform weighted averaging of the comprehensive average signal strength and the comprehensive average signal-to-noise ratio of each of the sub-areas according to the weights of the comprehensive average signal strength and the comprehensive average signal-to-noise ratio, so as to obtain a comprehensive score of each of the sub-areas;

[0150] a fourth determining unit, configured to determine the reciprocal of the distance between the center of each of the sub-areas and the center of the target area as the weight of each of the sub-areas;

[0151] A fifth calculation unit is used to perform weighted averaging on the comprehensive scores of the sub-areas according to the weights of the sub-areas to obtain a comprehensive score of the target area;

[0152] A sixth calculation unit, configured to calculate a mean and a standard deviation of the area comprehensive score according to the area comprehensive scores of the operators in the target area when there are multiple operators in the target area;

[0153] A seventh calculation unit, configured to calculate a standardized difference corresponding to the area comprehensive score of each of the operators according to the mean and standard deviation of the area comprehensive score;

[0154] The fifth determining unit is used to determine the comprehensive performance difference of the operator whose standardized difference value is less than 0.

[0155] In order to realize intuitive presentation of network performance differences, in an optional implementation manner, the above-mentioned device further includes:

[0156] A first acquisition unit is used to acquire a map of the target area;

[0157] A second acquisition unit, used for acquiring the above-mentioned comprehensive average signal strength and the above-mentioned comprehensive average signal-to-noise ratio of each of the above-mentioned sub-areas;

[0158] A first marking unit is used to mark the sub-area in the map where the comprehensive average signal strength is greater than the predetermined signal strength with a first color, mark the sub-area in the map where the comprehensive average signal strength is equal to the predetermined signal strength with a second color, and mark the sub-area in the map where the comprehensive average signal strength is equal to the predetermined signal strength with a third color, so as to obtain a signal strength display map of the target area;

[0159] The second marking unit is used to mark the sub-area in the map where the comprehensive average signal-to-noise ratio is greater than the predetermined signal-to-noise ratio with a fourth color, mark the sub-area in the map where the comprehensive average signal-to-noise ratio is equal to the predetermined signal-to-noise ratio with a fifth color, and mark the sub-area in the map where the comprehensive average signal-to-noise ratio is equal to the predetermined signal-to-noise ratio with a sixth color, so as to obtain a signal-to-noise ratio display map of the target area.

[0160] In order to realize intuitive presentation of network performance differences, in an optional implementation manner, the above-mentioned device further includes:

[0161] A third acquisition unit is used to acquire a map of the target area;

[0162] A fourth obtaining unit is used to obtain the standardized difference corresponding to the area comprehensive score of each of the operators;

[0163] The third marking unit is used to mark the above-mentioned operators whose standardized difference is greater than 0 with positive altitude, mark the above-mentioned operators whose standardized difference is equal to 0 with zero altitude, and mark the above-mentioned operators whose standardized difference is less than 0 with negative altitude, so as to obtain a network coverage comprehensive performance display map of each of the above-mentioned operators in the above-mentioned target area.

[0164] The above-mentioned area network performance evaluation device includes a processor and a memory, and the above-mentioned division unit, the first calculation unit, the second calculation unit and the first determination unit are all stored in the memory as program units, and the processor executes the above-mentioned program units stored in the memory to realize the corresponding functions. The above-mentioned modules are all located in the same processor; or, the above-mentioned modules are located in different processors in any combination.

[0165] The processor includes a kernel, which retrieves the corresponding program unit from the memory. One or more kernels can be set, and the problem of inaccurate evaluation results of network performance in the prior art can be solved by adjusting kernel parameters.

[0166] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0167] An embodiment of the present invention provides a computer-readable storage medium, which includes a stored program, wherein when the program is running, the device where the computer-readable storage medium is located is controlled to execute the method for evaluating the performance of the area network.

[0168] Specifically, the evaluation methods of the area network performance include:

[0169] Step S201, dividing the target area into a plurality of sub-areas; Step S202, performing weighted averaging on the network data corresponding to the test points of each of the above sub-areas to obtain the average signal strength of the drive test, the average signal-to-noise ratio of the drive test, the average signal strength of the measurement report, the average signal-to-noise ratio of the measurement report, the average signal strength of the user feedback, and the average signal-to-noise ratio of the user feedback of each of the above sub-areas, wherein the above network data includes the drive test data, the measurement report data, and the user feedback data, wherein the above drive test data includes the signal strength and the signal-to-noise ratio of the above test points of the drive test, the above measurement report data includes the signal strength and the signal-to-noise ratio of the above test points uploaded by the terminal, and the above user feedback data includes the signal strength and the signal-to-noise ratio of the above test points fed back by the user; Step S203, performing weighted averaging on the network data corresponding to the test points of each of the above sub-areas to obtain the average signal strength of the drive test, the average signal-to-noise ratio of the drive test, the average signal strength of the measurement report, the average signal-to-noise ratio of the measurement report, the average signal strength of the user feedback, and the average signal-to-noise ratio of the user feedback of the above test points; The above-mentioned road test average signal strength, the above-mentioned measurement report average signal strength and the above-mentioned user feedback average signal strength of the sub-area are weighted averaged to obtain the comprehensive average signal strength of each of the above-mentioned sub-areas, and the above-mentioned road test average signal-to-noise ratio, the above-mentioned measurement report average signal-to-noise ratio and the above-mentioned user feedback average signal-to-noise ratio of each of the above-mentioned sub-areas are weighted averaged to obtain the comprehensive average signal-to-noise ratio of each of the above-mentioned sub-areas; step S204, when the above-mentioned comprehensive average signal strength of the network of the operator to be evaluated in the target sub-area is less than the predetermined signal strength or the above-mentioned comprehensive average signal-to-noise ratio of the network of the operator to be evaluated in the target sub-area is less than the predetermined signal-to-noise ratio, it is determined that the network performance of the above-mentioned target sub-area is poor, and the above-mentioned target sub-area is any one of the above-mentioned sub-areas.

[0170] An embodiment of the present invention provides a processor, and the processor is used to run a program, wherein the program executes the method for evaluating the performance of the area network when running.

[0171] Specifically, the evaluation methods of the area network performance include:

[0172] Step S201, dividing the target area into a plurality of sub-areas; Step S202, performing weighted averaging on the network data corresponding to the test points of each of the above sub-areas to obtain the average signal strength of the drive test, the average signal-to-noise ratio of the drive test, the average signal strength of the measurement report, the average signal-to-noise ratio of the measurement report, the average signal strength of the user feedback, and the average signal-to-noise ratio of the user feedback of each of the above sub-areas, wherein the above network data includes the drive test data, the measurement report data, and the user feedback data, wherein the above drive test data includes the signal strength and the signal-to-noise ratio of the above test points of the drive test, the above measurement report data includes the signal strength and the signal-to-noise ratio of the above test points uploaded by the terminal, and the above user feedback data includes the signal strength and the signal-to-noise ratio of the above test points fed back by the user; Step S203, performing weighted averaging on the network data corresponding to the test points of each of the above sub-areas to obtain the average signal strength of the drive test, the average signal-to-noise ratio of the drive test, the average signal strength of the measurement report, the average signal-to-noise ratio of the measurement report, the average signal strength of the user feedback, and the average signal-to-noise ratio of the user feedback of the above test points; The above-mentioned road test average signal strength, the above-mentioned measurement report average signal strength and the above-mentioned user feedback average signal strength of the sub-area are weighted averaged to obtain the comprehensive average signal strength of each of the above-mentioned sub-areas, and the above-mentioned road test average signal-to-noise ratio, the above-mentioned measurement report average signal-to-noise ratio and the above-mentioned user feedback average signal-to-noise ratio of each of the above-mentioned sub-areas are weighted averaged to obtain the comprehensive average signal-to-noise ratio of each of the above-mentioned sub-areas; step S204, when the above-mentioned comprehensive average signal strength of the network of the operator to be evaluated in the target sub-area is less than the predetermined signal strength or the above-mentioned comprehensive average signal-to-noise ratio of the network of the operator to be evaluated in the target sub-area is less than the predetermined signal-to-noise ratio, it is determined that the network performance of the above-mentioned target sub-area is poor, and the above-mentioned target sub-area is any one of the above-mentioned sub-areas.

[0173] An embodiment of the present invention provides a system for evaluating the performance of a network in an area, including a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, at least the following steps are implemented:

[0174] Step S201, dividing the target area into a plurality of sub-areas; Step S202, performing weighted averaging on the network data corresponding to the test points of each of the above sub-areas to obtain the average signal strength of the drive test, the average signal-to-noise ratio of the drive test, the average signal strength of the measurement report, the average signal-to-noise ratio of the measurement report, the average signal strength of the user feedback, and the average signal-to-noise ratio of the user feedback of each of the above sub-areas, wherein the above network data includes the drive test data, the measurement report data, and the user feedback data, wherein the above drive test data includes the signal strength and the signal-to-noise ratio of the above test points of the drive test, the above measurement report data includes the signal strength and the signal-to-noise ratio of the above test points uploaded by the terminal, and the above user feedback data includes the signal strength and the signal-to-noise ratio of the above test points fed back by the user; Step S203, performing weighted averaging on the network data corresponding to the test points of each of the above sub-areas to obtain the average signal strength of the drive test, the average signal-to-noise ratio of the drive test, the average signal strength of the measurement report, the average signal-to-noise ratio of the measurement report, the average signal strength of the user feedback, and the average signal-to-noise ratio of the user feedback of the above test points; The above-mentioned road test average signal strength, the above-mentioned measurement report average signal strength and the above-mentioned user feedback average signal strength of the sub-area are weighted averaged to obtain the comprehensive average signal strength of each of the above-mentioned sub-areas, and the above-mentioned road test average signal-to-noise ratio, the above-mentioned measurement report average signal-to-noise ratio and the above-mentioned user feedback average signal-to-noise ratio of each of the above-mentioned sub-areas are weighted averaged to obtain the comprehensive average signal-to-noise ratio of each of the above-mentioned sub-areas; step S204, when the above-mentioned comprehensive average signal strength of the network of the operator to be evaluated in the target sub-area is less than the predetermined signal strength or the above-mentioned comprehensive average signal-to-noise ratio of the network of the operator to be evaluated in the target sub-area is less than the predetermined signal-to-noise ratio, it is determined that the network performance of the above-mentioned target sub-area is poor, and the above-mentioned target sub-area is any one of the above-mentioned sub-areas.

[0175] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing a program for initializing at least the following method steps:

[0176] Step S201, dividing the target area into a plurality of sub-areas; Step S202, performing weighted averaging on the network data corresponding to the test points of each of the above sub-areas to obtain the average signal strength of the drive test, the average signal-to-noise ratio of the drive test, the average signal strength of the measurement report, the average signal-to-noise ratio of the measurement report, the average signal strength of the user feedback, and the average signal-to-noise ratio of the user feedback of each of the above sub-areas, wherein the above network data includes the drive test data, the measurement report data, and the user feedback data, wherein the above drive test data includes the signal strength and the signal-to-noise ratio of the above test points of the drive test, the above measurement report data includes the signal strength and the signal-to-noise ratio of the above test points uploaded by the terminal, and the above user feedback data includes the signal strength and the signal-to-noise ratio of the above test points fed back by the user; Step S203, performing weighted averaging on the network data corresponding to the test points of each of the above sub-areas to obtain the average signal strength of the drive test, the average signal-to-noise ratio of the drive test, the average signal strength of the measurement report, the average signal-to-noise ratio of the measurement report, the average signal strength of the user feedback, and the average signal-to-noise ratio of the user feedback of the above test points; The above-mentioned road test average signal strength, the above-mentioned measurement report average signal strength and the above-mentioned user feedback average signal strength of the sub-area are weighted averaged to obtain the comprehensive average signal strength of each of the above-mentioned sub-areas, and the above-mentioned road test average signal-to-noise ratio, the above-mentioned measurement report average signal-to-noise ratio and the above-mentioned user feedback average signal-to-noise ratio of each of the above-mentioned sub-areas are weighted averaged to obtain the comprehensive average signal-to-noise ratio of each of the above-mentioned sub-areas; step S204, when the above-mentioned comprehensive average signal strength of the network of the operator to be evaluated in the target sub-area is less than the predetermined signal strength or the above-mentioned comprehensive average signal-to-noise ratio of the network of the operator to be evaluated in the target sub-area is less than the predetermined signal-to-noise ratio, it is determined that the network performance of the above-mentioned target sub-area is poor, and the above-mentioned target sub-area is any one of the above-mentioned sub-areas.

[0177] Obviously, those skilled in the art should understand that the above modules or steps of the present invention can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order than here, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0178] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0179] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0180] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0181] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0182] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0183] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0184] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0185] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0186] The above description is only the preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for evaluating area network performance, characterized in that: include: Divide the target area into multiple sub-areas; Perform weighted averaging on the network data corresponding to the test points of each sub-area to obtain the average signal strength of the drive test, the average signal-to-noise ratio of the drive test, the average signal strength of the measurement report, the average signal-to-noise ratio of the measurement report, the average signal strength of the user feedback, and the average signal-to-noise ratio of the user feedback of each sub-area, wherein the network data includes the drive test data, the measurement report data, and the user feedback data, the drive test data includes the signal strength and the signal-to-noise ratio of the test point of the drive test, the measurement report data includes the signal strength and the signal-to-noise ratio of the test point uploaded by the terminal, and the user feedback data includes the signal strength and the signal-to-noise ratio of the test point fed back by the user; Performing a weighted average on the drive test average signal strength, the measurement report average signal strength, and the user feedback average signal strength of each sub-area to obtain a comprehensive average signal strength of each sub-area, and performing a weighted average on the drive test average signal-to-noise ratio, the measurement report average signal-to-noise ratio, and the user feedback average signal-to-noise ratio of each sub-area to obtain a comprehensive average signal-to-noise ratio of each sub-area; When the comprehensive average signal strength of the network of the operator to be evaluated in the target sub-area is less than the predetermined signal strength or the comprehensive average signal-to-noise ratio of the network of the operator to be evaluated in the target sub-area is less than the predetermined signal-to-noise ratio, it is determined that the network performance of the target sub-area is poor, and the target sub-area is any one of the sub-areas.

2. The method according to claim 1, characterized in that Divide the target area into multiple sub-areas, including: Obtaining a map of the target area; Dividing the target area into N sub-areas on the map, such that the boundaries of the sub-areas are located on the roads on the map and the areas of the sub-areas are smaller than a predetermined area, N≥2; Performing weighted average on the user number density, data flow density and connection number density of each sub-area respectively to obtain the network usage density of each sub-area, wherein the user number density is the ratio of the total number of users in the sub-area to the area of ​​the sub-area, the data flow density is the ratio of the total data flow of the sub-area within a predetermined time period to the area of ​​the sub-area, and the connection number density is the ratio of the number of connections of the users in the sub-area connected to the network within the predetermined time period to the area of ​​the sub-area; Calculating the average value of the network usage density of each of the sub-areas to obtain the average network usage density of the target area; use Calculate and obtain the adjusted area of ​​each sub-area, wherein New Grid Size is the adjusted area, Base Grid Size is the area of ​​the sub-area before adjustment, Network Density is the network usage density of the sub-area, and AverageDensity is the average network usage density; The target area is re-divided according to the adjusted areas of each sub-area to obtain a plurality of sub-areas.

3. The method according to claim 2, characterized in that Dividing the target area into N sub-areas on the map includes: Using a quadtree algorithm to divide the target area into four sub-areas, so that the boundaries of the sub-areas are located on the roads of the map; a division step, in the case where the area of ​​the target sub-region is larger than the predetermined area, using the quadtree algorithm to divide the target sub-region into four new sub-regions, the target sub-region being any one of the sub-regions; The dividing step is repeated at least once until the areas of all the sub-regions are smaller than the predetermined area, thereby obtaining N sub-regions.

4. The method according to claim 1, characterized in that: Obtaining network data corresponding to the test points of each sub-area and performing weighted averaging to obtain the average signal strength of the drive test, the average signal-to-noise ratio of the drive test, the average signal strength of the measurement report, the average signal-to-noise ratio of the measurement report, the average signal strength of the user feedback, and the average signal-to-noise ratio of the user feedback of each sub-area, including: Divide the grid of the target sub-region into multiple sub-grids; according to Calculate the time difference weight of each test point in each sub-grid, Weigh_t ji is the time difference weight of the i-th test point in the j-th subgrid, ji is the time difference between the acquisition time of the network data of the ith test point in the jth subgrid and the current time, ∈ is a constant; The network data corresponding to the test points are weighted averaged according to the time difference weights of the test points in each sub-grid to obtain the road test average signal strength, the road test average signal-to-noise ratio, the measurement report average signal strength, the measurement report average signal-to-noise ratio, the user feedback average signal strength and the user feedback average signal-to-noise ratio of the target sub-area.

5. The method according to claim 1, characterized in that The method comprises: performing a weighted average of the drive test average signal strength, the measurement report average signal strength, and the user feedback average signal strength of each sub-area to obtain a comprehensive average signal strength of each sub-area; performing a weighted average of the drive test average signal-to-noise ratio, the measurement report average signal-to-noise ratio, and the user feedback average signal-to-noise ratio of each sub-area to obtain a comprehensive average signal-to-noise ratio of each sub-area, including: Setting a weight W1 of the drive test data, a weight W2 of the measurement report data, and a weight W3 of the user feedback data so that W1+W2+W3=1; Using AVG(SS-RSRP)=W1·AVG DT (SS-RSRP)+W2·AVG MR (SS-RSRP)+W3·AVG UR (SS-RSRP) is used to calculate the comprehensive average signal strength of each sub-area, wherein AVG(SS-RSRP) is the comprehensive average signal strength of the sub-area, and AVG DT (SS-RSRP) is the average signal strength of the road test in the sub-slice, AVG MR (SS-RSRP) is the average signal strength of the measurement report of the sub-slice, AVG UR (SS-RSRP) is the average signal strength of the user feedback in the sub-slice; Using AVG(SS-SINR)=W1·AVG DT (SS-SINR)+W2·AVG MR (SS-SINR)+W3·AVG UR (SS-SINR) is calculated to obtain the comprehensive average signal-to-noise ratio of each sub-zone, wherein AVG(SS-SINR) is the comprehensive average signal-to-noise ratio of the sub-zone, and AVG DT (SS-SINR) is the average signal strength of the path test in the sub-slice, AVG MR (SS-SINR) is the average signal-to-noise ratio of the measurement report of the sub-slice, AVG UR (SS-SINR) is the average signal-to-noise ratio of the user feedback in the sub-slice.

6. The method according to claim 1, characterized in that When the comprehensive average signal strength of the network of the operator to be evaluated in the target sub-area is less than the predetermined signal strength or the comprehensive average signal-to-noise ratio of the network of the operator to be evaluated in the target sub-area is less than the predetermined signal-to-noise ratio, determining that the network performance of the target sub-area is poor includes: In the case where the network of the operator to be evaluated is jointly built and shared by multiple operators and there is a reference operator, the minimum value of the comprehensive average signal strengths of the networks of the multiple operators in the target sub-area is determined as the comprehensive average signal strength of the network of the operator to be evaluated in the target sub-area, the minimum value of the comprehensive average signal-to-noise ratios of the networks of the multiple operators in the target sub-area is determined as the comprehensive average signal-to-noise ratio of the network of the operator to be evaluated in the target sub-area, the comprehensive average signal strength of the network of the reference operator in the target sub-area is determined as the predetermined signal strength, and the comprehensive average signal-to-noise ratio of the network of the reference operator in the target sub-area is determined as the predetermined signal-to-noise ratio; When the comprehensive average signal strength of the network of the operator to be evaluated in the target sub-area is less than the predetermined signal strength or the comprehensive average signal-to-noise ratio of the network of the operator to be evaluated in the target sub-area is less than the predetermined signal-to-noise ratio, it is determined that the network performance of the target sub-area is poor.

7. The method according to any one of claims 1 to 6, characterized in that The method further comprises: Determine the test point in the target area whose signal strength is greater than a signal strength threshold and whose signal-to-noise ratio is greater than a signal-to-noise ratio threshold as a network coverage available test point; Calculate the ratio of the number of available test points for network coverage to the total number of test points in the target area to obtain a network coverage availability rate; When the network coverage availability is less than a predetermined network coverage availability, a network coverage availability difference of the target area is determined.

8. The method according to any one of claims 1 to 6, characterized in that The method further comprises: Setting weights of the comprehensive average signal strength and the comprehensive average signal-to-noise ratio; Performing a weighted average of the comprehensive average signal strength and the comprehensive average signal-to-noise ratio of each of the sub-areas according to the weights of the comprehensive average signal strength and the comprehensive average signal-to-noise ratio to obtain a comprehensive score of each of the sub-areas; Determine the reciprocal of the distance between the center of each sub-region and the center of the target region as the weight of each sub-region; According to the weights of the sub-areas, the comprehensive scores of the sub-areas are weighted averaged to obtain the comprehensive score of the target area; In the case where there are multiple operators in the target area, the mean and standard deviation of the area comprehensive score are calculated according to the area comprehensive scores of the operators in the target area; Calculating the standardized difference corresponding to the area comprehensive score of each operator according to the mean and standard deviation of the area comprehensive score; The comprehensive performance of the operator whose standardized difference value is less than 0 is determined to be poor.

9. The method according to any one of claims 1 to 6, characterized in that The method further comprises: Obtaining a map of the target area; Obtaining the comprehensive average signal strength and the comprehensive average signal-to-noise ratio of each of the sub-areas; The sub-area in the map where the comprehensive average signal strength is greater than the predetermined signal strength is marked with a first color, the sub-area in the map where the comprehensive average signal strength is equal to the predetermined signal strength is marked with a second color, and the sub-area in the map where the comprehensive average signal strength is equal to the predetermined signal strength is marked with a third color, to obtain a signal strength display map of the target area; The sub-area in the map whose comprehensive average signal-to-noise ratio is greater than the predetermined signal-to-noise ratio is marked with a fourth color, the sub-area in the map whose comprehensive average signal-to-noise ratio is equal to the predetermined signal-to-noise ratio is marked with a fifth color, and the sub-area in the map whose comprehensive average signal-to-noise ratio is equal to the predetermined signal-to-noise ratio is marked with a sixth color, to obtain a signal-to-noise ratio display map of the target area.

10. The method according to claim 8, characterized in that The method further comprises: Obtaining a map of the target area; Obtaining the standardized difference corresponding to the comprehensive score of the area of ​​each operator; The operators whose standardized difference is greater than 0 are marked with positive altitude, the operators whose standardized difference is equal to 0 are marked with zero altitude, and the operators whose standardized difference is less than 0 are marked with negative altitude, so as to obtain a network coverage comprehensive performance display map of each operator in the target area.

11. A device for evaluating area network performance, characterized in that: include: A division unit, used for dividing the target area into a plurality of sub-areas; a first calculation unit, configured to perform weighted averaging on the network data corresponding to the test points of each of the sub-areas to obtain a drive test average signal strength, a drive test average signal-to-noise ratio, a measurement report average signal strength, a measurement report average signal-to-noise ratio, a user feedback average signal strength, and a user feedback average signal-to-noise ratio of each of the sub-areas, wherein the network data comprises drive test data, measurement report data, and user feedback data, the drive test data comprises a signal strength and a signal-to-noise ratio of the test points of the drive test, the measurement report data comprises a signal strength and a signal-to-noise ratio of the test points uploaded by a terminal, and the user feedback data comprises a signal strength and a signal-to-noise ratio of the test points fed back by users; A second calculation unit is configured to perform a weighted average of the drive test average signal strength, the measurement report average signal strength and the user feedback average signal strength of each sub-area to obtain a comprehensive average signal strength of each sub-area, and perform a weighted average of the drive test signal-to-noise ratio, the measurement report signal-to-noise ratio and the user feedback signal-to-noise ratio of each sub-area to obtain a comprehensive average signal-to-noise ratio of each sub-area; The first determination unit is used to determine that the network performance of the target sub-area is poor when the comprehensive average signal strength of the network of the operator to be evaluated in the target sub-area is less than a predetermined signal strength or the comprehensive average signal-to-noise ratio of the network of the operator to be evaluated in the target sub-area is less than a predetermined signal-to-noise ratio. The target sub-area is any one of the sub-areas.

12. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the method according to any one of claims 1 to 10.

13. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method according to any one of claims 1 to 10 is implemented.

14. A system for evaluating the performance of a regional network, characterized in that: include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include methods for executing any one of claims 1 to 10.

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