A network coverage performance evaluation method and device, electronic equipment and storage medium

Abstract

The application discloses a network coverage performance evaluation method and device, electronic equipment and storage medium, the method comprises the following steps: acquiring the measurement data set reported by a mobile terminal, collecting key fields from the measurement data; determining the target base station corresponding to the mobile terminal based on the call record identification data; acquiring the first position information of the target base station; obtaining the second position information of the mobile terminal based on the first position information and combining the azimuth angle conversion; processing the second position information to obtain the moving speed of the mobile terminal; determining the position type of the mobile terminal based on the moving speed; based on the third position information corresponding to the indoor terminal and the terminal receiving level value, obtaining the network coverage performance of different height intervals in the target area. Based on the moving characteristics of indoor users, the application realizes automatic matching and calculation through related data, identifies high-layer coverage scene users, efficiently realizes network coverage performance evaluation, and can be widely applied to the technical field of data processing.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a method, apparatus, electronic device, and storage medium for evaluating network coverage performance. Background Technology

[0002] With the acceleration of urbanization, more and more high-rise buildings are appearing. This architectural trend has brought unprecedented challenges to the indoor coverage of mobile communication networks, becoming a key and difficult issue in mobile network optimization and indoor coverage system construction.

[0003] The Challenges of Indoor Coverage in High-Rise Buildings: Signal Penetration and Attenuation: Building materials such as walls and glass curtain walls in high-rise buildings significantly shield and attenuate wireless signals, resulting in insufficient indoor signal strength and degraded signal quality. This problem is particularly severe when the signal source base station is far away or when obstacles exist in the signal propagation path.

[0004] Existing network performance testing methods have several limitations: To evaluate mobile network coverage performance in high-rise buildings, traditional methods require on-site traversal testing. However, this method faces numerous limitations in high-rise buildings: High testing difficulty: High-rise buildings have complex interior spaces and numerous floors, making it difficult for testers to comprehensively cover all areas, especially in upper floors. High testing cost: On-site traversal testing requires significant investment of manpower, resources, and time, resulting in high costs. Particularly in high-rise buildings, the transportation, installation, and debugging of test equipment add further difficulty and cost. Inaccurate test results: Due to the unique environment of high-rise buildings, on-site traversal testing often fails to accurately reflect the actual signal coverage. For example, factors such as the speed at which testers move between different floors, and the accuracy and stability of the test equipment, can all affect the accuracy of the test results. Summary of the Invention

[0005] This invention proposes a method, apparatus, electronic device, and storage medium for evaluating network coverage performance, aiming to at least partially solve one of the technical problems in related technologies. The embodiments of this invention can efficiently achieve network coverage performance evaluation.

[0006] On one hand, embodiments of the present invention provide a method for evaluating network coverage performance, including:

[0007] Obtain the measurement dataset reported by the mobile terminal and extract key fields from the measurement data;

[0008] The measurement dataset includes measurement data from multiple reporting time points within the statistical period; the measurement data includes measurement reports and minimized drive test data; key fields include call detail record (CDR) identification data, azimuth angle, and terminal received signal level.

[0009] Determine the target base station corresponding to the mobile terminal based on the call detail record (CDR) identifier data; obtain the first location information of the target base station;

[0010] Based on the first location information, the second location information of the mobile terminal is obtained by combining the azimuth angle conversion; the second location information includes the third location information of the mobile terminal at each reporting time point within the statistical period.

[0011] Both the first and third location information include latitude, longitude, and altitude.

[0012] The mobile terminal's moving speed is obtained based on the second location information; the location type of the mobile terminal is determined based on the moving speed; the location type includes indoor terminal and outdoor terminal;

[0013] Based on the third location information corresponding to the indoor terminal and the terminal's received signal level, the network coverage performance of different height ranges in the target area is obtained.

[0014] Optionally, the call detail record (CDR) identification data includes the CDR ID, physical cell identifier, and user CDR; determining the target base station corresponding to the mobile terminal based on the CDR identification data includes the following steps:

[0015] Based on the call detail record (CDR) ID, physical cell identification code, and user call detail record, the mobile terminal and target base station associated with each test data are determined, and then the target base station corresponding to each mobile terminal is determined.

[0016] Optionally, the azimuth angle includes a first direction angle and an elevation angle; the first location information includes the base station's latitude and longitude and its altitude; the third location information includes the terminal's latitude and longitude and its altitude; the measurement data also includes a time advance; based on the first location information, the second location information of the mobile terminal is obtained by combining the azimuth angle conversion, including the following steps:

[0017] Obtain the antenna azimuth and antenna tilt angle of the target base station;

[0018] The second orientation angle of the mobile terminal relative to true north is obtained by converting the first orientation angle and the antenna orientation angle.

[0019] The transmission delay of electromagnetic waves between the mobile terminal and the target base station is determined based on the time advance, and the relative distance between the mobile terminal and the target base station is obtained based on the transmission delay.

[0020] Based on the relative distance, the horizontal and vertical distances between the mobile terminal and the target base station are obtained by combining the elevation angle and the antenna tilt angle.

[0021] The terminal's latitude and longitude are obtained by combining the base station's latitude and longitude with the horizontal distance and the second direction angle.

[0022] The terminal height is obtained by converting the base station height into vertical distance.

[0023] The third location information for the corresponding reporting time point is obtained by organizing the terminal's latitude, longitude, and altitude. The second location information is obtained by organizing the third location information for all reporting time points within the statistical period.

[0024] Optionally, the moving speed of the mobile terminal is obtained based on the second location information, including the following steps:

[0025] The third position information of the start time point in the statistical period is obtained from the second position information as the fourth position information, and the third position information of the end time point is obtained as the fifth position information;

[0026] The mobile terminal's travel distance within the statistical period is determined based on the latitude and longitude in the fourth and fifth location information.

[0027] The mobile terminal's speed is obtained by the ratio of the distance traveled to the duration of the statistical period.

[0028] Optionally, determining the location type of a mobile terminal based on its movement speed includes the following steps:

[0029] If the moving speed is less than a first preset threshold, the mobile terminal is determined to be an indoor terminal; otherwise, the mobile terminal is determined to be an outdoor terminal.

[0030] Optionally, the method further includes the following steps:

[0031] The average received level of all indoor terminals within the statistical period is averaged to obtain the average received level of the terminals.

[0032] If the difference between the received level of an indoor terminal and the average received level of an indoor terminal exceeds a second preset threshold within the statistical period, the location type corresponding to the indoor terminal will be converted to that of an outdoor terminal.

[0033] Optionally, based on the third location information corresponding to the indoor terminal and the terminal's received signal level, the network coverage performance of different height ranges in the target area is obtained, including the following steps:

[0034] Based on the latitude and longitude of the third location information, all indoor terminals within the target area are marked as statistical terminals;

[0035] The statistical data for each terminal is obtained by organizing the received signal levels of all terminals within the statistical period.

[0036] The target height range of each statistical terminal in the target area is determined based on the third location data.

[0037] Based on a preset numerical color mapping table, according to the gradient range of the statistical data corresponding to each statistical terminal, the corresponding target height interval in the target area is marked as the mapped gradient color, thus obtaining the network coverage performance distribution map of the target area.

[0038] On the other hand, embodiments of the present invention provide a network coverage performance evaluation device, comprising:

[0039] The first module is used to acquire the measurement dataset reported by the mobile terminal and collect key fields from the measurement data;

[0040] The measurement dataset includes measurement data from multiple reporting time points within the statistical period; the measurement data includes measurement reports and minimized drive test data; key fields include call detail record (CDR) identification data, azimuth angle, and terminal received signal level.

[0041] The second module is used to determine the target base station corresponding to the mobile terminal based on the call detail record (CDR) identifier data; and to obtain the first location information of the target base station.

[0042] The third module is used to obtain the second location information of the mobile terminal based on the first location information and combined with the azimuth angle conversion; the second location information includes the third location information of the mobile terminal at each reporting time point within the statistical period.

[0043] Both the first and third location information include latitude, longitude, and altitude.

[0044] The fourth module is used to process the second location information to obtain the mobile terminal's moving speed; and to determine the mobile terminal's location type based on the moving speed; the location type includes indoor terminal and outdoor terminal.

[0045] The fifth module is used to obtain the network coverage performance of different height ranges in the target area based on the third location information corresponding to the indoor terminal and the terminal's received signal level.

[0046] Optionally, the device further includes:

[0047] The sixth module is used to average the received levels of all indoor terminals within the statistical period to obtain the average received level of the terminals.

[0048] The seventh module is used to convert the location type of the indoor terminal to an outdoor terminal when the difference between the terminal's received level and the terminal's average received level exceeds a second preset threshold during the statistical period of the indoor terminal.

[0049] On the other hand, embodiments of the present invention provide an electronic device, including: a processor and a memory; the memory is used to store a program; the processor executes the program to implement the above-described network coverage performance evaluation method.

[0050] On the other hand, embodiments of the present invention provide a computer storage medium storing a processor-executable program, which, when executed by a processor, is used to implement the above-described network coverage performance evaluation method.

[0051] This invention acquires measurement datasets reported by mobile terminals and extracts key fields from these datasets. The measurement datasets include measurement data from multiple reporting time points within a statistical period. The measurement data includes measurement reports and minimized drive test data. Key fields include call detail record (CDR) identification data, azimuth angle, and terminal received signal level. Based on the CDR identification data, the target base station corresponding to the mobile terminal is determined. First location information of the target base station is acquired. Based on the first location information, and combined with azimuth angle conversion, second location information of the mobile terminal is obtained. The second location information includes third location information of the mobile terminal at each reporting time point within the statistical period. Both the first and third location information include latitude, longitude, and altitude. The mobile terminal's movement speed is obtained based on the second location information. The location type of the mobile terminal is determined based on the movement speed. Location types include indoor terminals and outdoor terminals. Based on the third location information corresponding to the indoor terminal and the terminal received signal level, the network coverage performance of different height ranges in the target area is obtained. This invention, based on the movement characteristics of indoor users and based on preset rule logic, achieves automated matching and calculation through relevant data to identify users in high-rise coverage scenarios and further evaluates the network indoor coverage performance in different height ranges of high-rise buildings. This invention can efficiently achieve network coverage performance evaluation. Attached Figure Description

[0052] The accompanying drawings are provided to further understand the technical solutions of the present invention and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the technical solutions of the present invention, and do not constitute a limitation on the technical solutions of the present invention.

[0053] Figure 1 This is a schematic diagram of an implementation environment for network coverage performance evaluation provided in an embodiment of the present invention;

[0054] Figure 2 A flowchart illustrating a network coverage performance evaluation method provided in an embodiment of the present invention;

[0055] Figure 3 This is a schematic diagram of the process for organizing and expanding the second position information provided in an embodiment of the present invention;

[0056] Figure 4 This is a schematic diagram illustrating the process of obtaining the moving speed of a mobile terminal according to an embodiment of the present invention.

[0057] Figure 5 A schematic diagram illustrating an example of network coverage provided in an embodiment of the present invention;

[0058] Figure 6 A schematic diagram illustrating the overall data flow principle for network coverage performance evaluation provided in an embodiment of the present invention;

[0059] Figure 7 A schematic diagram illustrating the relationship between HAOA and its related parameters provided in an embodiment of the present invention;

[0060] Figure 8 A schematic diagram illustrating the relationship between VAOA and its related parameters provided in an embodiment of the present invention;

[0061] Figure 9 This is a schematic diagram of the structure of a network coverage performance evaluation device provided in an embodiment of the present invention;

[0062] Figure 10 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0063] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0064] It should be noted that although functional modules are divided in the system diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than the module division in the system or the order in the flowchart. The terms "first / S100," "second / S200," etc., in the specification, claims, and the aforementioned figures are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0065] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0066] To facilitate understanding of the technical solution of this invention, the technical features and proper nouns that may appear in the embodiments of this invention will first be explained:

[0067] MR (Measurement Report): This is the raw network data measured by user terminals. The measurement report contains relevant information for both uplink and downlink radio links, such as RSCP (Received Signal Code Power), ISCP (Interference Signal Code Power), BLER (Block Error Rate), and transmit power. This data is transmitted every 480 milliseconds (470 milliseconds on the signaling channel) for network assessment and optimization. MR data is one of the main bases for evaluating the quality of the radio environment. For GSM systems, it is the primary means for the network side to obtain terminal radio information. In-depth analysis based on MR data can effectively facilitate network problem localization, network coverage analysis, neighbor cell optimization, and other network performance assessment and optimization tasks. Measurement report data mainly comes from the physical layer and RLC layer of user equipment (UE) and base station (Node B), as well as measurement reports calculated during radio resource management.

[0068] MDT (Minimization Drive Test): Introduced in 3G UMTS / 4G LTE / 5G NR, this is an automated drive test technology that uses network configurations to collect, report, and preprocess measurement data from ordinary user / commercial terminals. As long as the user terminal has GPS enabled and supports MDT, it can automatically report MDT data containing user location information to the base station. Similar to MR (Measurement Report), MDT includes fields such as RSRP and RSRQ, and contains GPS latitude and longitude information, which can be used for big data analysis.

[0069] It is understood that the network coverage performance evaluation method provided in this embodiment of the invention can be applied to any computer device with data processing and computing capabilities, and this computer device can be various types of terminals or servers. When the computer device in the embodiment is a server, the server is an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms. Optionally, the terminal can be a smartphone, tablet computer, laptop computer, or desktop computer, but it is not limited to these.

[0070] like Figure 1 The diagram shown is a schematic representation of an implementation environment provided by an embodiment of the present invention. (Refer to...) Figure 1 The implementation environment includes at least one terminal 102 and a server 101. The terminal 102 and the server 101 can be connected via a network, either wirelessly or via a wired connection, to complete data transmission and exchange.

[0071] Server 101 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms.

[0072] Additionally, server 101 can also be a node server in a blockchain network. Blockchain is a novel application model of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanisms, and encryption algorithms.

[0073] Terminal 102 can be a smartphone, tablet computer, laptop computer, desktop computer, smart speaker, smartwatch, etc., but is not limited to these. Terminal 102 and server 101 can be directly or indirectly connected via wired or wireless communication, and this embodiment of the invention does not impose any limitations.

[0074] Exemplary based on Figure 1 The implementation environment shown in this embodiment of the invention provides a network coverage performance evaluation method. The following description uses the application of this network coverage performance evaluation method in terminal 102 as an example. It can be understood that this network coverage performance evaluation method can also be applied to server 101.

[0075] Reference Figure 2 , Figure 2 This is a flowchart illustrating a network coverage performance evaluation method applied to a terminal (e.g., a DPU) according to an embodiment of the present invention. The executing entity of this network coverage performance evaluation method can be any of the aforementioned computer devices (including servers or terminals). (Refer to...) Figure 2 The method includes the following steps:

[0076] S100: Obtain the measurement dataset reported by the mobile terminal and collect key fields from the measurement data;

[0077] The measurement dataset includes measurement data from multiple reporting time points within the statistical period; the measurement data includes measurement reports and minimized drive test data; key fields include call detail record (CDR) identification data, azimuth angle, and terminal received signal level.

[0078] For example, in some specific implementations, the MDT / MR data reported by the mobile terminal (taking a 5G terminal as an example) can first be collected and processed to filter valuable fields. Specifically, extracting key fields from the measurement report reported by the mobile terminal may include the following:

[0079] CALLID: A temporary call detail record (CDR) ID assigned by the base station when a terminal performs communication services;

[0080] PCI: Physical Cell Identifier, used to identify the 5G cell occupied by the terminal;

[0081] CDR: User call detail record, which can continuously track a terminal based on CALLID and other index IDs in CDR, and filter and extract MRs involving that terminal;

[0082] TA: Time advance, the transmission time of electromagnetic waves between the antenna and the terminal;

[0083] Azimuth (MR): The horizontal AOA (also known as direction angle / HAOA) and vertical AOA (also known as pitch angle / VAOA) measured by the terminal in MR can be used to calculate the angular relationship between the terminal and the base station, thereby further locating the latitude and longitude information of the terminal;

[0084] RSRP: Terminal Received Level Value, reflecting the 5G network coverage quality measured by the terminal.

[0085] S200: Determine the target base station corresponding to the mobile terminal based on the call detail record (CDR) identifier data; obtain the first location information of the target base station;

[0086] The first location information includes latitude, longitude, and altitude;

[0087] It should be noted that in some embodiments, the call detail record (CDR) identification data includes the CDR ID, physical cell identification code, and user CDR; determining the target base station corresponding to the mobile terminal based on the CDR identification data may include the following steps: determining the mobile terminal and target base station associated with each test data according to the CDR ID, physical cell identification code, and user CDR, and then determining the target base station corresponding to each mobile terminal.

[0088] For example, in some specific implementations, the base station corresponding to each MR / MDT data, and thus the corresponding relationship between the mobile terminal and the base station, can be determined directly based on the data characteristics of CALLID, PCI, and CDR.

[0089] S300. Based on the first location information, the second location information of the mobile terminal is obtained by combining the azimuth angle conversion; the second location information includes the third location information of the mobile terminal at each reporting time point within the statistical period.

[0090] The third location information includes latitude, longitude, and altitude;

[0091] It should be noted that the azimuth angle includes the first direction angle and the elevation angle; the first location information includes the base station's latitude and longitude and the base station's altitude; the third location information includes the terminal's latitude and longitude and the terminal's altitude; the measurement data also includes time advance; in some embodiments, such as Figure 3 As shown, obtaining the second location information of the mobile terminal based on the first location information and by combining it with azimuth angle conversion can include the following steps:

[0092] S301. Obtain the antenna azimuth angle and antenna tilt angle of the target base station;

[0093] S302. The second direction angle of the mobile terminal relative to true north is obtained by converting the first direction angle and the antenna direction angle.

[0094] For example, in some specific implementations, the orientation angle HAOA is defined as follows: when looking directly at the AAU sector, the normal direction of the longitudinal section is 0°, and HAOA is the angle between the line connecting the terminal and the base station and the normal. Starting from the downward projection of the AAU plane normal in the horizontal direction, each unit is 0.5 degrees, with the counter-clockwise direction being positive.

[0095] By combining the antenna azimuth angle η (the angle between the antenna normal and 0° true north) and HAOA, the azimuth angle α of the terminal UE relative to true north can be calculated, and then used for subsequent calculations of the mobile terminal's latitude and longitude on the Earth's surface. The formula is as follows:

[0096] α=IF (η>=HAOA / 2, eta-HAOA / 2, eta-HAOA / 2+360);

[0097] Specifically, the azimuth angle α between the user's (i.e., mobile terminal's) location and the base station is calculated using the horizontal AOA (or simply HAOA, i.e., the first direction angle) and the antenna direction angle (η). If η >= HAOA / 2, α = η - HAOA / 2; otherwise, α = η - HAOA / 2 + 360.

[0098] S303. Determine the transmission delay of electromagnetic waves between the mobile terminal and the target base station based on the time advance, and obtain the relative distance between the mobile terminal and the target base station based on the transmission delay.

[0099] For example, in some specific implementations, the time advance, the transmission delay of electromagnetic waves between the terminal and the antenna feeder, can be used to calculate the distance TA*39 from the terminal to the antenna, in meters. The straight-line distance d between the terminal and the base station can be calculated using the vertical AOA (or simply VAOA), the antenna tilt angle (downtilt, which is the mechanical tilt angle plus the electrical tilt angle), and the TA (time advance, the transmission delay of electromagnetic waves between the terminal and the antenna feeder, which can be used to calculate the distance TA*39 from the terminal to the antenna, in meters) in the MR data reported by the terminal.

[0100] d=TA*39*SIN((VAOA+90-DownTilt)*PI / 180);

[0101] Where SIN is the sine function and PI represents π.

[0102] S304. Based on the relative distance, the horizontal and vertical distances between the mobile terminal and the target base station are obtained by combining the elevation angle and the antenna tilt angle.

[0103] For example, in some specific implementations, the straight-line distance d (i.e., horizontal distance) between the terminal and the base station can be calculated using the vertical AOA (or simply VAOA), the antenna tilt angle (downTilt, which is the mechanical tilt angle plus the electrical tilt angle), and the TA (time advance, the propagation delay of electromagnetic waves between the terminal and the antenna feeder, which can be calculated as the distance from the terminal to the antenna TA*39, in meters) in the MR data reported by the terminal.

[0104] d=TA*39*SIN((VAOA+90-DownTilt)*PI / 180);

[0105] Where SIN is the sine function and PI represents π;

[0106] The vertical distance h from the terminal to the antenna (i.e., the vertical distance):

[0107] h=TA*39*COS((VAOA+90-DownTilt)*PI / 180);

[0108] Where COS is the cosine function.

[0109] S305. The terminal's latitude and longitude are obtained by combining the base station's latitude and longitude with the horizontal distance and the second direction angle.

[0110] For example, in some specific implementations, the base station's latitude and longitude (long1, lati1), the calculated azimuth angle α, and the straight-line distance d between the user and the base station are known. Substituting these into the formula, the latitude and longitude of the 5G terminal can be obtained:

[0111] 5G_long=long1+d*sinα / [ARC*cos(lat1)*2π / 360];

[0112] 5G_lat=lat1+d*cosα / (ARC*2π / 360);

[0113] The ARC uses the Earth's average radius = 6371.012 * 1000 (meters).

[0114] S306. Based on the base station height and combined with the vertical distance conversion, the terminal height is obtained;

[0115] For example, in some specific embodiments, the vertical height of the terminal relative to the ground is:

[0116] Height=H-TA*39*COS((VAOA+90-DownTilt)*PI / 180);

[0117] S307. Based on the terminal's latitude, longitude, and altitude, the third location information of the corresponding reporting time point is obtained. The second location information is obtained by organizing the third location information of all reporting time points within the statistical period.

[0118] S400: The mobile terminal's moving speed is obtained by processing the second location information; the location type of the mobile terminal is determined based on the moving speed;

[0119] The location types include indoor terminals and outdoor terminals;

[0120] It should be noted that in some embodiments, such as Figure 4 As shown, the mobile terminal's moving speed is obtained by processing the second location information, which may include the following steps: S401, obtaining the third location information at the start time of the statistical period as the fourth location information and the third location information at the end time of the statistical period as the fifth location information; S402, determining the mobile terminal's moving distance within the statistical period based on the latitude and longitude in the fourth location information and the latitude and longitude in the fifth location information; S403, obtaining the mobile terminal's moving speed based on the ratio of the moving distance to the duration of the statistical period.

[0121] The duration of the statistical period can be adaptively determined based on the duration of the call detail records (CDRs) as determined by the relevant information in the measurement data. In this case, the statistical period is not a fixed value.

[0122] It should be noted that, in some embodiments, determining the location type of a mobile terminal based on its movement speed may include the following steps: if the movement speed is less than a first preset threshold, the mobile terminal is determined to be an indoor terminal; otherwise, the mobile terminal is determined to be an outdoor terminal.

[0123] For example, in some specific implementations, the location of a terminal with excessively fast movement speed can be determined based on the starting and ending latitude and longitude distance and speed of the terminal within a statistical time period.

[0124] The formula for calculating the distance between points a and b (i.e., the two location points corresponding to the fourth and fifth location information) using their latitude and longitude is as follows:

[0125] Dis=arc cos((sinlat.a×sinLAT.b)+(coslat.a×coslat.b×cos(|(long.a-long.b)|))×6371004;

[0126] Terminal movement speed is calculated based on distance and call detail record (CDR) duration. Terminals with a movement speed less than a first preset threshold (e.g., 1.5 m / s) are identified as indoor terminals. The movement speed formula is as follows:

[0127] V = Dis / T;

[0128] Where T is the moving duration corresponding to the statistical period.

[0129] In some embodiments, the method may further include the following steps:

[0130] The average received level of all indoor terminals within the statistical period is averaged to obtain the average received level of the terminals.

[0131] If the difference between the received level of an indoor terminal and the average received level of an indoor terminal exceeds a second preset threshold within the statistical period, the location type corresponding to the indoor terminal will be converted to that of an outdoor terminal.

[0132] For example, in some specific embodiments, the RSRP values ​​reported by the terminal within the statistical period can be analyzed using a rasterization method based on latitude and longitude information. Terminals whose average received RSRP differs from the average received RSRP of all MRs within the raster are positioned as indoor terminals if the difference falls within a second preset threshold (e.g., 20%). For example, a terminal that simultaneously meets both conditions shown in Table 1 is positioned as an indoor terminal (otherwise, it is still determined to be an outdoor terminal):

[0133] Table 1

[0134]

[0135]

[0136] S500 obtains the network coverage performance of different height ranges in the target area based on the third location information corresponding to the indoor terminal and the terminal received level value.

[0137] It should be noted that in some embodiments, step S500 may include the following steps: based on the latitude and longitude of the third location information, all indoor terminals in the target area are marked as statistical terminals; statistical data of each statistical terminal is obtained by organizing the received levels of all terminals within the statistical period; the target height range of each statistical terminal in the target area is determined based on the third location data; based on a preset numerical color mapping table, the corresponding target height range in the target area is marked as the mapped gradient color according to the gradient range of the statistical data corresponding to each statistical terminal, thereby obtaining a network coverage performance distribution map of the target area.

[0138] For example, in some specific embodiments, the target altitude region is a three-dimensional location range determined based on latitude, longitude, and altitude; for example, it is assumed that the target region covers an area of ​​1000m. 2 A 99m high-rise building (3m high per floor, 33 floors in total) can have each floor divided into 100 three-dimensional location ranges. For example, first, the specific floor level is determined based on height, then latitude and longitude are used to determine which specific three-dimensional location range falls within that floor. The corresponding area of ​​the physical model is then filled with corresponding numerical mapping colors. The statistical data can be time-series data of all terminal received signal levels within the statistical period, or it can be the average value of terminal received signal levels within the statistical period. For example, Figure 5 The image shows an example of how the coverage of a high-rise building at different heights is presented in a three-dimensional manner based on information such as RSRP, latitude and longitude, and altitude from an indoor scene terminal.

[0139] To explain in detail the principle of the technical solution of the present invention, the overall process of the present invention will be described below with reference to some specific embodiments. It is easy to understand that the following is an explanation of the technical principle of the present invention and should not be regarded as a limitation of the present invention.

[0140] First, it should be noted that for coverage scenarios using macro base stations and spotlight antennas, raw MR data reported by mobile network terminals cannot accurately pinpoint the coverage scene, while MDT data is limited by satellite signal quality and cannot be used for effective indoor scene coverage performance evaluation. Therefore, this invention combines the correlation between MR, MDT, and user signaling to develop a method for identifying user distribution in high-rise community coverage scenarios and evaluating the indoor coverage performance of high-rise buildings. Figure 6 As shown, the technical solution of this invention involves the following:

[0141] 1) Collect and process the MDT / MR data reported by 5G terminals, and filter out valuable fields.

[0142] 2) Determine the base station corresponding to each MR / MDT data;

[0143] 3) Calculate the latitude, longitude, and altitude of the 5G terminal by combining the geographical location and altitude parameters of the base station;

[0144] 4) Determine the terminal's moving speed by combining the MR / MDT reporting time with the latitude and longitude information mentioned above;

[0145] 5) Determine whether the terminal is in an indoor or outdoor environment by combining the terminal's moving speed and the changes in the terminal's received signal level;

[0146] 6) Organize the RSRP and height data of indoor 5G terminals to evaluate the coverage performance of different height areas of high-rise buildings.

[0147] Specifically, the detailed data logic of the technical solution of the present invention can be implemented as follows:

[0148] (a) Extracting key fields from the measurement reports submitted by 5G terminals:

[0149] CALLID: A temporary call detail record (CDR) ID assigned by the base station when a terminal performs communication services;

[0150] PCI: Physical Cell Identifier, used to identify the 5G cell occupied by the terminal;

[0151] CDR: User call detail record, which can continuously track a terminal based on CALLID and other index IDs in CDR, and filter and extract MRs involving that terminal;

[0152] TA: Time advance, the transmission time of electromagnetic waves between the antenna and the terminal;

[0153] Azimuth (MR): The horizontal AOA (also known as direction angle / HAOA) and vertical AOA (also known as pitch angle / VAOA) measured by the terminal in MR can be used to calculate the angular relationship between the terminal and the base station, thereby further locating the latitude and longitude information of the terminal;

[0154] RSRP: Terminal Received Level Value, reflecting the 5G network coverage quality measured by the terminal.

[0155] (II) Calculating the geographical location of the terminal based on 5G-MR data:

[0156] By using the geographical location information of base stations, 5G base stations with a probability of overlapping coverage with 4G base stations can be screened. Using the key fields of 5G-MR, namely azimuth angle (HAOA) and pitch angle (VAOA), combined with parameters such as base station antenna height and antenna physical tilt angle, the geographical location of the reported 5G-MR terminal can be calculated.

[0157] like Figure 7As shown, the azimuth angle HAOA: when looking directly at the AAU sector, with the normal direction of the longitudinal section as 0°, HAOA is the angle between the line connecting the terminal and the base station and the normal to the AAU plane. Starting from the downward projection of the AAU plane normal onto the horizontal direction, each unit is 0.5 degrees, with the counterclockwise direction being positive.

[0158] By combining the antenna azimuth angle η and HAOA, the azimuth angle α of the terminal UE relative to true north can be calculated, which can then be used to calculate the latitude and longitude of the mobile terminal on the Earth's surface. The formula is as follows:

[0159] α=IF (η>=HAOA / 2, eta-HAOA / 2, eta-HAOA / 2+360);

[0160] like Figure 8 As shown, the pitch angle VAOA: when looking directly at the AAU sector, the normal direction of the cross section is 0°. The pitch angle is the angle between the line connecting the terminal and the antenna feeder and the normal of the cross section. Its actual range is [-90°, 90°], which can be determined based on the angle of the normal.

[0161] Based on the known data such as the base station's latitude and longitude (long1, lat1) and base station altitude H, the latitude and longitude (long2, lat2) during the terminal's PCI ambiguity handover can be derived and calculated by combining the above HAOA and VAOA.

[0162] The specific implementation process of the above logic is as follows:

[0163] (1) Calculate the azimuth angle α between the user (i.e., mobile terminal) and the base station using the horizontal AOA (abbreviated as HAOA, i.e. first direction angle) and the antenna direction angle (η); if η>=HAOA / 2, α=η-HAOA / 2; otherwise, α=η-HAOA / 2+360.

[0164] (2) Calculate the straight-line distance d between the terminal and the base station using the vertical AOA (or simply VAOA), the antenna tilt angle (downTilt, which is the mechanical tilt angle plus the electrical tilt angle), and the TA (time advance, the propagation delay of electromagnetic waves between the terminal and the antenna feeder, which can be calculated as the distance from the terminal to the antenna TA*39, in meters).

[0165] d=TA*39*SIN((VAOA+90-DownTilt)*PI / 180);

[0166] (3) Given the base station's latitude and longitude (long1, lati1), the direction angle α calculated in the first step, and the straight-line distance d between the user and the base station calculated in the second step, the latitude and longitude of the 5G terminal can be obtained by substituting them into the formula:

[0167] 5G_long=long1+d*sinα / [ARC*cos(lat1)*2π / 360];

[0168] 5G_lat=lat1+d*cosα / (ARC*2π / 360);

[0169] The ARC uses the Earth's average radius = 6371.012 * 1000 (meters).

[0170] (4) Based on the height H of the base station antenna feeder and the vertical distance h from the terminal to the antenna, h = TA * 39 * COS((VAOA + 90 - DownTilt) * PI / 180), the vertical height of the terminal relative to the ground is:

[0171] Height=H-TA*39*COS((VAOA+90-DownTilt)*PI / 180);

[0172] (III) Calculate the terminal's moving speed:

[0173] Based on the starting and ending latitude and longitude distance and speed of the terminal within the statistical time period, the formula for calculating the distance between outdoor fast-moving terminals a and b using latitude and longitude is as follows:

[0174] Dis=arc cos((sinlat.a×sinLAT.b)+(coslat.a×coslat.b×cos(|(long.a-long.b)|))×6371004;

[0175] Based on distance and call detail records, the terminal's moving speed V = Dis / T is calculated. Terminals with a moving speed of less than 1.5 m / s are identified as indoor terminals.

[0176] (iv) Compare changes in terminal voltage levels:

[0177] Based on latitude and longitude information, the RSRP values ​​reported by the terminal within the statistical period are analyzed in a grid. Terminals whose average received RSRP differs from the average received RSRP of all MRs in the grid within a range of 20% are identified as indoor scene terminals.

[0178] (V) Example of Indoor Terminal Coverage Assessment:

[0179] A terminal that simultaneously meets both of the conditions described in Table 1 above is classified as an indoor terminal.

[0180] like Figure 5 As shown, based on information such as RSRP, latitude and longitude, and altitude from indoor scene terminals, the coverage of different height ranges of high-rise buildings can be presented in a three-dimensional way.

[0181] In summary, the purpose of this invention is to develop a method for identifying users in high-rise coverage scenarios and further evaluating the indoor coverage performance of 5G networks in various height ranges of high-rise buildings, based on measurement data such as MDT, MR, and CDR reported by 4G and 5G users, and by matching and calculating relevant data based on the mobility characteristics of indoor users. Compared with the prior art, this invention has at least the following beneficial effects:

[0182] This invention utilizes raw data such as MDT, MR, and CDR reported by 4G and 5G terminals, and employs big data analytics to analyze and determine whether overlapping coverage exists in 4G and 5G networks within a specific area, guiding the formulation of strategies to improve 5G dwell time. Compared to current dwell time analysis methods based on single-site analysis and field testing, this invention identifies overlapping coverage areas across the entire network based on mobile terminal behavior, resulting in more accurate positioning and higher efficiency.

[0183] On the other hand, such as Figure 9 As shown, this embodiment of the invention provides a network coverage performance evaluation device 900, comprising:

[0184] The first module 901 is used to acquire the measurement dataset reported by the mobile terminal and collect key fields from the measurement data;

[0185] The measurement dataset includes measurement data from multiple reporting time points within the statistical period; the measurement data includes measurement reports and minimized drive test data; key fields include call detail record (CDR) identification data, azimuth angle, and terminal received signal level.

[0186] The second module 902 is used to determine the target base station corresponding to the mobile terminal based on the call detail record (CDR) identifier data; and to obtain the first location information of the target base station.

[0187] The third module 903 is used to obtain the second location information of the mobile terminal based on the first location information and combined with the azimuth angle conversion; the second location information includes the third location information of the mobile terminal at each reporting time point within the statistical period.

[0188] Both the first and third location information include latitude, longitude, and altitude.

[0189] The fourth module 904 is used to process the second location information to obtain the mobile terminal's moving speed; and to determine the location type of the mobile terminal based on the moving speed; the location type includes indoor terminal and outdoor terminal.

[0190] The fifth module 905 is used to obtain the network coverage performance of different height ranges in the target area based on the third location information corresponding to the indoor terminal and the terminal received level value.

[0191] In some embodiments, the apparatus may further include:

[0192] The sixth module is used to average the received levels of all indoor terminals within the statistical period to obtain the average received level of the terminals.

[0193] The seventh module is used to convert the location type of the indoor terminal to an outdoor terminal when the difference between the terminal's received level and the terminal's average received level exceeds a second preset threshold during the statistical period of the indoor terminal.

[0194] The content of the method embodiments of the present invention is applicable to the device embodiments. The specific functions implemented by the device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above methods.

[0195] On the other hand, embodiments of the present invention also provide an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the aforementioned sensitive information method. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.

[0196] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0197] like Figure 10 As shown, Figure 10 This illustration shows a specific example of the hardware structure of an electronic device 1000 according to one embodiment. The electronic device 1000 includes:

[0198] The processor 1001 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present invention.

[0199] The memory 1002 can be implemented as a read-only memory (ROM), static storage device, dynamic storage device, or random access memory (RAM). The memory 1002 can store the operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 1002 and is called and executed by the processor 1001 to execute the network node population optimization method of the embodiments of this invention.

[0200] Input / output interface 1003 is used to implement information input and output;

[0201] The communication interface 1004 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0202] Bus 1005 transmits information between various components of the device (e.g., processor 1001, memory 1002, input / output interface 1003, and communication interface 1004);

[0203] The processor 1001, memory 1002, input / output interface 1003 and communication interface 1004 are connected to each other within the device via bus 1005.

[0204] The electronic device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0205] The content of the method embodiments of the present invention is applicable to the embodiments of the present electronic device. The specific functions implemented by the embodiments of the present electronic device are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above methods.

[0206] Another aspect of this invention provides a computer-readable storage medium storing a program that is executed by a processor to implement the aforementioned method.

[0207] It should be noted that the computer-readable medium shown in the embodiments of the present invention can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD to ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In the present invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In the present invention, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, wherein computer-readable program code is carried. Such transmitted data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to wireless, wired, etc., or any suitable combination thereof.

[0208] The content of the method embodiments of the present invention is applicable to the computer-readable storage medium embodiments. The specific functions implemented by the computer-readable storage medium embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above methods.

[0209] This invention also discloses a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device can read the computer instructions from the computer-readable storage medium and execute the computer instructions, causing the computer device to perform the aforementioned method.

[0210] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0211] It should be noted that although several modules for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to embodiments of the present invention, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0212] Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, portable hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, touch terminal, or network device, etc.) to execute the method according to the embodiments of the present invention.

[0213] In some alternative embodiments, the functions / operations mentioned in the block diagrams may not occur in the order shown in the operation diagrams. For example, depending on the functions / operations involved, two consecutively shown blocks may actually be executed substantially simultaneously, or the blocks may sometimes be executed in reverse order. Furthermore, the embodiments presented and described in the flowcharts of this invention are provided by way of example to provide a more comprehensive understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented herein. Alternative embodiments are contemplated in which the order of various operations is changed and sub-operations described as part of a larger operation are executed independently.

[0214] Furthermore, although the invention has been described in the context of functional modules, it should be understood that, unless otherwise stated, one or more of the functions and / or features may be integrated into a single physical device and / or software module, or one or more functions and / or features may be implemented in a separate physical device or software module. It is also understood that a detailed discussion of the actual implementation of each module is unnecessary for understanding the invention. Rather, given the properties, functions, and internal relationships of the various functional modules in the apparatus disclosed herein, the actual implementation of the module will be understood within the scope of conventional skill of an engineer. Therefore, those skilled in the art can implement the invention as set forth in the claims using ordinary techniques without excessive experimentation. It is also understood that the specific concepts disclosed are merely illustrative and not intended to limit the scope of the invention, which is determined by the full scope of the appended claims and their equivalents.

[0215] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0216] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution means, apparatus, or device (such as a computer-based device, a processor-including device, or other means that can fetch and execute instructions from, or in conjunction with, an instruction execution means, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution means, apparatus, or device.

[0217] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which programs can be printed, because programs can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0218] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution device. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0219] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0220] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

[0221] The above is a detailed description of the preferred embodiments of the present invention. However, the present invention is not limited to the embodiments. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention. All such equivalent modifications or substitutions are included within the scope defined by the claims of the present invention.

Claims

1. A method for evaluating network coverage performance, characterized in that, Includes the following steps: Obtain the measurement dataset reported by the mobile terminal and extract key fields from the measurement data; The measurement dataset includes measurement data from multiple reporting time points within a statistical period; the measurement data includes measurement reports and minimized drive test data; the key fields include call detail record (CDR) identification data, azimuth angle, and terminal received signal level. Based on the call detail record (CDR) identification data, determine the target base station corresponding to the mobile terminal; obtain the first location information of the target base station; Based on the first location information, the second location information of the mobile terminal is obtained by combining the azimuth angle conversion; the second location information includes the third location information of the mobile terminal at each reporting time point within the statistical period. Wherein, both the first location information and the third location information include latitude, longitude and altitude; The mobile terminal's moving speed is obtained by processing the second location information; the location type of the mobile terminal is determined based on the moving speed; the location type includes indoor terminal and outdoor terminal; Based on the third location information corresponding to the indoor terminal and the received level value of the terminal, the network coverage performance of different height ranges in the target area is obtained. The step of obtaining network coverage performance in different height ranges of the target area based on the third location information corresponding to the indoor terminal and the received signal level of the terminal includes the following steps: Based on the latitude and longitude of the third location information, all indoor terminals within the target area are marked as statistical terminals; The statistical data for each terminal is obtained by organizing the received levels of all terminals within the statistical period; The target height range of each statistical terminal in the target area is determined based on the third location information; Based on a preset numerical color mapping table, according to the gradient range of the statistical data corresponding to each statistical terminal, the corresponding target height interval in the target area is marked with the mapped gradient color, thereby obtaining the network coverage performance distribution map of the target area.

2. The network coverage performance evaluation method according to claim 1, characterized in that, The call detail record (CDR) identification data includes a CDR ID, a physical cell identifier, and user CDRs; determining the target base station corresponding to the mobile terminal based on the CDR identification data includes the following steps: Based on the call detail record ID, the physical cell identification code, and the user call detail record, the mobile terminal and the target base station associated with each measurement data are determined, and then the target base station corresponding to each mobile terminal is determined.

3. The network coverage performance evaluation method according to claim 1, characterized in that, The azimuth angle includes a first direction angle and a pitch angle; the first location information includes the base station's latitude and longitude and its altitude; the third location information includes the terminal's latitude and longitude and its altitude; the measurement data also includes a time advance; the process of converting the first location information and the azimuth angle to obtain the second location information of the mobile terminal includes the following steps: Obtain the antenna orientation angle and antenna tilt angle of the target base station; The second orientation angle of the mobile terminal relative to true north is obtained by converting the first orientation angle and the antenna orientation angle. The transmission delay of electromagnetic waves between the mobile terminal and the target base station is determined based on the time advance, and the relative distance between the mobile terminal and the target base station is obtained based on the transmission delay. Based on the relative distance, the horizontal and vertical distances between the mobile terminal and the target base station are obtained by combining the elevation angle and the antenna tilt angle. The terminal's latitude and longitude are obtained by combining the base station's latitude and longitude with the horizontal distance and the second direction angle. The terminal height is obtained by converting the base station height and the vertical distance. The third location information corresponding to the reporting time point is obtained by organizing the terminal's latitude and longitude and the terminal's altitude. The second location information is obtained by organizing the third location information of all the reporting time points within the statistical period.

4. The network coverage performance evaluation method according to claim 1, characterized in that, The process of obtaining the moving speed of the mobile terminal based on the second location information includes the following steps: The third location information at the start time point in the statistical period is obtained from the second location information as the fourth location information, and the third location information at the end time point is obtained as the fifth location information. The mobile terminal's movement distance within the statistical period is determined based on the latitude and longitude in the fourth location information and the latitude and longitude in the fifth location information; The mobile speed of the mobile terminal is obtained based on the ratio of the moving distance to the duration of the statistical period.

5. The network coverage performance evaluation method according to claim 1, characterized in that, Determining the location type of the mobile terminal based on the moving speed includes the following steps: If the moving speed is less than a first preset threshold, the mobile terminal is determined to be the indoor terminal; otherwise, the mobile terminal is determined to be the outdoor terminal.

6. The network coverage performance evaluation method according to claim 1, characterized in that, The method further includes the following steps: The average received level of all the indoor terminals within the statistical period is averaged to obtain the average received level of the terminals. If the difference between the received level of the indoor terminal and the average received level of the terminal is greater than a second preset threshold within the statistical period of the indoor terminal, the location type corresponding to the indoor terminal is converted to that of the outdoor terminal.

7. A network coverage performance evaluation device, characterized in that, include: The first module is used to acquire the measurement dataset reported by the mobile terminal and collect key fields from the measurement data; The measurement dataset includes measurement data from multiple reporting time points within a statistical period; the measurement data includes measurement reports and minimized drive test data; the key fields include call detail record (CDR) identification data, azimuth angle, and terminal received signal level. The second module is used to determine the target base station corresponding to the mobile terminal based on the call detail record (CDR) identifier data; and to obtain the first location information of the target base station. The third module is used to obtain the second location information of the mobile terminal based on the first location information and the azimuth conversion; the second location information includes the third location information of the mobile terminal at each reporting time point within the statistical period. Wherein, both the first location information and the third location information include latitude, longitude and altitude; The fourth module is used to process the second location information to obtain the moving speed of the mobile terminal; and to determine the location type of the mobile terminal based on the moving speed; the location type includes indoor terminal and outdoor terminal; The fifth module is used to obtain the network coverage performance of different height ranges in the target area based on the third location information corresponding to the indoor terminal and the received level value of the terminal. The step of obtaining network coverage performance in different height ranges of the target area based on the third location information corresponding to the indoor terminal and the received signal level of the terminal includes the following steps: Based on the latitude and longitude of the third location information, all indoor terminals within the target area are marked as statistical terminals; The statistical data for each terminal is obtained by organizing the received levels of all terminals within the statistical period; The target height range of each statistical terminal in the target area is determined based on the third location information; Based on a preset numerical color mapping table, according to the gradient range of the statistical data corresponding to each statistical terminal, the corresponding target height interval in the target area is marked with the mapped gradient color, thereby obtaining the network coverage performance distribution map of the target area.

8. An electronic device, characterized in that, Including the processor and memory; The memory is used to store programs; The processor executes the program to implement the method as described in any one of claims 1 to 6.

9. A computer storage medium storing a processor-executable program, characterized in that, The processor-executable program, when executed by the processor, is used to implement the method as described in any one of claims 1 to 6.

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