Method and system for evaluating 5G network coverage of residential area

Abstract

The invention discloses a residential area 5G network coverage evaluation method and system, and the method comprises the steps: obtaining a core network call ticket, a wireless network call ticket, an APP perception call ticket and user information in a target area, and forming a basic data set; performing correlation analysis on the data in the basic data set, and splicing the associated data to form an updated data set; performing data cleaning on the updated data set, and screening representative data from the updated data set; and according to the screened data, carrying out data analysis to obtain a building-level or user-level network evaluation index of the target area. According to the invention, a set of residential area 5G network quality monitoring and evaluation system is established, a mobile network ticket is fully utilized in combination with an algorithm scheme, the 5G network use perception of a user is reflected more quickly, accurately and truly, the test cost is reduced, deep coverage blind spots of a residential area are quickly counted, analyzed and positioned, and blind compensation optimization of a mobile network is assisted.

Description

Technical Field

[0001] The present invention belongs to the field of information technology, and particularly relates to a method and system for evaluating the 5G network coverage in residential areas. Background Art

[0002] As one of the most important places in people's daily lives, the 5G network coverage quality in residential areas is directly related to users' perception of the network experience.

[0003] However, there are many deficiencies in the existing methods for evaluating the 5G network coverage in residential areas. On the one hand, traditional testing methods mainly rely on manual testing building by building. This method requires a large amount of manpower and material resources, and the testing cost is extremely high. For example, testers need to carry professional equipment to measure signal strength and other operations in each residential building. Only the labor cost accounts for a large part. Moreover, due to the limited number of testers, the testing efficiency is low, and it is impossible to conduct a comprehensive coverage test on all areas in the residential area.

[0004] On the other hand, manual testing also has the limitation that it cannot penetrate into users' homes. Due to the complex internal structure of residential areas and the large differences in users' indoor environments, users' network perception often depends more on the network performance in the indoor scenario. However, manual testing usually can only conduct dot testing in the corridors, and this method cannot truly reflect the network usage situation of users in the rooms, resulting in a low accuracy of the evaluation of the indoor coverage status and making it difficult to accurately discover the network coverage blind spots indoors.

[0005] In addition, the data obtained by the existing manual testing methods is relatively limited, and it cannot comprehensively and accurately reflect users' true perception. It is difficult to quickly count and locate the deep coverage blind spots in residential communities, which to a certain extent affects the blind spot filling and optimization work of the mobile network, and is also not conducive to timely discovering and solving network coverage problems and improving users' network experience. Summary of the Invention

[0006] The present invention aims to solve at least one of the technical problems existing in the related technologies to some extent.

[0007] One object of the present invention is to provide a method for evaluating the 5G network coverage in residential areas, which is used to establish a monitoring and evaluation system for the 5G network quality in residential areas, make full use of mobile network call records in combination with algorithm solutions, more quickly, accurately and truly reflect users' perception of 5G network usage, reduce testing costs, quickly count, analyze and locate the deep coverage blind spots in residential communities, and assist in the blind spot filling and optimization of the mobile network.

[0008] Another object of the present invention is to provide a system for evaluating the 5G network coverage in residential areas.

[0009] To achieve the above object, on the one hand, the present invention provides a method for evaluating 5G network coverage in residential areas, including: Obtain core network call records, radio network call records, APP perception call records, and user information within the target area to form a basic data set; Perform correlation analysis on the data in the basic data set, and splice the associated data to form an updated data set; Clean the data in the updated data set, and screen out representative data from the updated data set; According to the screened data, perform data analysis to obtain network evaluation indicators at the building level or user level of the target area.

[0010] A further preferred technical solution of the present invention is that the obtaining of core network call records, radio network call records, APP perception call records, and user information within the target area to form a basic data set specifically includes: Extract the core network call records within the target area, denoted as ; extract the radio network call records within the target area, denoted as ; extract the APP perception call records within the target area, denoted as ; obtain the user information within the target area, denoted as ; represent the basic data set as .

[0011] Preferably, the user information within the target area includes user installation and maintenance work orders , user installation addresses , and user mobile addresses , and the user information within the target area is represented as .

[0012] Preferably, performing correlation analysis on the data in the basic data set, and splicing the associated data to form an updated data set; specifically includes: According to the user number , associate the core network call record and the installation address of the user, and splice to obtain: ; According to MMES1APID and TMSI, associate the corresponding radio network call record and core network call record of the user, and splice to obtain: ; Among them, is the unique identifier assigned by the S1AP protocol on the MME side of the core network's mobility management entity for the user, is the temporary mobile user identifier; Finally, an updated data set containing user addresses, wireless network information, and core network information is obtained, denoted as: 。

[0013] Preferably, data cleaning is performed on the updated data set, and representative data is screened out from the updated data set, specifically including: Define the time as and the user occupancy rate as . The rules for screening the updated data set are as follows: (1) Combine the user installation addresses to screen out the call detail records during the period with high user activity and small network fluctuations, expressed as: ; ; (2) For residential areas with existing manual test data, screen the user call detail records of the manually tested sectors ; (3) For residential areas without manual test data, mark the call detail record sectors as candidate sectors, clean the candidate sectors with a user occupancy rate less than 10%, mark the other candidate sectors as valid call detail record sectors, and screen the user call detail records under the valid call detail record sectors, expressed as: ; (4) Obtain the APP perception call detail records of the screened users in the same time period, denoted as .

[0014] Preferably, based on the screened data, data analysis is performed to obtain network evaluation indicators at the building level or user level in the target area, specifically: Through the screened call detail records , , and , calculate and output indicators such as average RSRP, overlapping coverage rate , RRC reconstruction ratio , ERAB abnormal disconnection call detail record ratio , handover failure rate, and release failure rate at the granularity of the building level or a single user in the target area; Among them, define the RSRP of the first neighbor cell as , the RSRP of the second neighbor cell as , the RSRP of the third neighbor cell as , and the RSRP of the target area cell as . If RSRP > -110 dBm, and ≤ 6 dB, and ≤ 6 dB, and ≤ 6 dB, then the cell is an overlapping coverage cell, and the call detail records therein are non-compliant call detail records, denoted as . The calculation formula for the overlapping coverage rate is: ; Define the RRC connection success rate as , if in the call record < 99.5%, then it is a non-compliant call record, denoted as , the calculation formula for the RRC reconstruction ratio is: ; If the abnormal disconnection rate of ERAB in the call record ≥ 0.1%, then it is a non-compliant call record, denoted as , the calculation formula for the proportion of abnormal disconnection call records of ERAB is: .

[0015] On the other hand, the present invention provides a 5G network coverage evaluation system for residential areas, including: A data acquisition module, configured to acquire core network call records, radio network call records, APP perception call records, and user information within a target area, and form a basic data set; A data splicing module, configured to perform correlation analysis on the data in the basic data set, and splice the associated data to form an updated data set; A data cleaning module, configured to clean the data in the updated data set, and screen out representative data from the updated data set; A coverage evaluation module, configured to perform data analysis based on the screened data to obtain network evaluation indicators at the building level or user level of the target area.

[0016] On the other hand, the present invention provides a non-transitory computer-readable storage medium, on which computer instructions are stored, and the computer instructions cause the computer to execute the above-mentioned 5G network coverage evaluation method for residential areas.

[0017] On another aspect, the present invention provides an electronic device, including: a processor, a communication interface, a memory, and a communication bus. Among them, the processor, the communication interface, and the memory complete mutual communication through the communication bus, and the processor calls the logical instructions in the memory to execute the above-mentioned 5G network coverage evaluation method for residential areas.

[0018] On yet another aspect, the present invention provides a computer program product, the computer program product includes a computer program, the computer program is stored on a non-transitory computer-readable storage medium, and when the computer program is executed by a processor, the computer executes the above-mentioned 5G network coverage evaluation method for residential areas.

[0019] Beneficial effects: The 5G network coverage evaluation method and system for residential areas of the present invention are different from the traditional method of manual testing building by building. By using the massive call detail record data of residential areas for 5G network coverage evaluation, the testing cost is greatly saved.

[0020] Due to the large building density and many high-rise buildings in residential areas, the wireless signal propagation environment is complex. The traditional user positioning method can only predict based on coverage sectors, propagation models, etc., with limited accuracy. The present invention realizes precise positioning by extracting the mobile phone numbers of users under the installed addresses and combining attributes such as coverage sectors, time, and user movement.

[0021] Traditional optimization of residential areas mainly relies on manual testing, generally conducting dot tests in corridors and unable to conduct traversal tests indoors. Therefore, the accuracy of the evaluated indoor coverage is relatively low and cannot truly reflect the network performance of users in the rooms. The present invention extracts the indoor call detail records of residential area users to truly reflect the usage situation and network status of users.

[0022] The present invention uses database operations to realize the functions of downloading, importing, and analyzing automatic call detail records and core network call detail records, periodically generating reports, continuously monitoring the perception of residential area users, real-time discovering blind spots in residential areas and periodically evaluating. At the same time, it can analyze the reasons for problems through the reasons for event failures carried by call detail records to assist in optimization. Description of the Drawings

[0023] Figure 1 is the overall flowchart of the 5G network coverage evaluation method for residential areas of the present invention; Figure 2 is the flowchart of the data splicing method in Embodiment 1 of the present invention; Figure 3 is the flowchart of the data cleaning method in Embodiment 1 of the present invention; Figure 4 is the flowchart of the data analysis method in Embodiment 1 of the present invention. Detailed Embodiments

[0024] To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below in conjunction with the drawings in the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention, and they should not be construed as limitations on the present invention. Based on the embodiments in the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of the present invention. In the description of the present invention, it should be understood that the terms used are only for the purpose of description and cannot be construed as indicating or implying relative importance.

[0025] Before elaborating on the present invention, some technical terms and abbreviations involved in the present invention are described and defined.

[0026] IMSI (International Mobile Subscriber Identity): International Mobile Subscriber Identity, a globally unique identifier used to identify users in a mobile network.

[0027] TMSI (Temporary Mobile Subscriber Identity): A temporary mobile subscriber identifier used to temporarily replace the IMSI for transmission in the network to protect the user's identity information from being leaked.

[0028] MMES1APID (Mobility Management Entity S1): Mobility Management Entity MME S1 Application Protocol Identifier.

[0029] RSRP (Reference Signal Receiving Power): Reference Signal Receiving Power, a key parameter representing the wireless signal strength in a wireless network and one of the physical layer measurement requirements, which is the average of the signal powers received on all RE (resource elements) carrying reference signals within a certain symbol.

[0030] LTE (Long Term Evolution): A wireless data communication technology standard, which is the long-term evolution of the UMTS (Universal Mobile Telecommunications System) technology standard developed by the 3GPP (The 3rd Generation Partnership Project). ERAB (Evolved Radio Access Bearer): Evolved Radio Access Bearer. An E-RAB refers to the bearer in the user plane, used to transmit voice, data, and multimedia services between the UE (User Equipment) and the CN (Core Network).

[0031] RRC (Radio Resource Control): Radio Resource Control, referring to the management, control, and scheduling of radio resources through certain strategies and means.

[0032] The following combines Figures 1-4 to describe the residential area 5G network coverage evaluation method and evaluation system provided by the present invention.

[0033] Example 1: This example provides a method for evaluating the 5G network coverage in a residential area. As Figure 1 shown, it includes: Obtain the core network call records, radio network call records, APP perception call records, and user information within the target area to form a basic data set; Perform correlation analysis on the data in the basic data set, and splice the associated data to form an updated data set; Clean the data in the updated data set, and screen out representative data from the updated data set; According to the screened data, perform data analysis to obtain network evaluation indicators at the building level or user level of the target area.

[0034] The following is a detailed description of each step.

[0035] S1. Data acquisition: Extract the core network call records , radio network call records , APP perception call records , user installation and maintenance work orders , user installation addresses , user mobile addresses As the basic data set, define the user information as , then the basic data set can be expressed as: .

[0036] S2. Data splicing: As Figure 2 shown, according to the user number , associate the core network call record and the installation address of the user, and splice them to get: ; According to MMES1APID and TMSI, associate the corresponding radio network call record and core network call record of the user, and splice them to get: ; Among them, is the unique identifier assigned by the S1AP protocol on the MME side of the core network's mobility management entity for the user, is the temporary mobile subscriber identity; Finally, obtain an updated data set containing user addresses, wireless network information, and core network information, expressed as: .

[0037] S3. Data cleaning: As Figure 3As shown in the figure, the updated dataset is cleaned by combining time and manual test data. The defined time is , and the user occupancy rate is . The rules for screening the updated dataset are as follows: (1) Combine the user installation address to screen out the call detail records of users from 22:00 to 23:00, which is expressed as: ; Combining user research and analysis, the probability of users being indoors in residential areas from 22 to 23 is relatively high. And from data analysis, the average RSRP standard deviation of residential area users from 22 to 23 is <= 1dBm, with relatively small fluctuations and low mobility.

[0038] (2) For residential areas with existing manual test data, screen the call detail records of users in the manually tested sectors .

[0039] (3) For residential areas without manual test data, mark the call detail record sectors as candidate sectors, clean the candidate sectors with a user occupancy rate less than 10%, mark other candidate sectors as valid call detail record sectors, and screen the call detail records of users under the valid call detail record sectors, which is expressed as: .

[0040] (4) Obtain the APP perception call detail records of the screened users in the same time period, denoted as .

[0041] S4. Data analysis: As Figure 4 shown, through the screened call detail records , , and , calculate and output the average RSRP, overlapping coverage rate , RRC reconstruction ratio , ERAB abnormal disconnection call detail record ratio , handover failure rate, and release failure rate indicators at the granularity of building level or individual users in the target area.

[0042] Among them, define the RSRP of the first neighbor cell as , the RSRP of the second neighbor cell as , the RSRP of the third neighbor cell as , and the RSRP of the target area cell as . If the RSRP > -110dBm, and <= 6dB, and <= 6dB, and <= 6dB, then this cell is an overlapping coverage cell, and the call detail records in it are non-compliant call detail records, denoted as , overlapping coverage rate The calculation formula is: ; Define the RRC connection success rate as , if in the call record < 99.5%, then it is a non-compliant call record, denoted as , the RRC reconstruction ratio calculation formula is: ; If the abnormal disconnection rate of ERAB in the call record ≥0.1%, then it is a non-compliant call record, denoted as , the calculation formula for the proportion of abnormal disconnection call records of ERAB is: .

[0043] In this embodiment, the above analysis method is used to obtain, taking 8 cells in a certain target area as an example, the average RSRP, overlapping coverage rate , RRC reconstruction ratio , the proportion of abnormal disconnection call records of ERAB , handover failure rate and release failure rate indicators, as shown in Table 1.

[0044] Table 1 Building-level network analysis statistical table

[0045] In order to verify the effectiveness of the method in this embodiment, on-site tests and verifications are carried out through the following cases.

[0046] The number of buildings in Community A is 230, and the number of households is 2,678. The community is mainly covered by five macro station sectors: macro station 1_50, macro station 2_49, macro station 3_50, macro station 4_49, and macro station 5_51.

[0047] There are 25 buildings with user call records in Community A. One of them is selected for on-site testing. The test results show that the coverage rate is 5.21%, and the average RSRP is -119.63 dBm.

[0048] Through the method of this example, the call record data is analyzed. The analysis results show that the coverage rate is 5.01%, and the average RSRP is -120.5 dBm.

[0049] The results show that the on-site manual test is basically consistent with the analysis results of the present invention. The overall deep coverage of this community is weak, and radio frequency optimization and new cell coverage are required to enhance the deep coverage of this community.

[0050] Embodiment 2: A 5G network coverage evaluation system for residential areas, including: A data acquisition module, configured to acquire core network call records, radio network call records, APP perception call records, and user information within a target area, and form a basic data set; A data splicing module, configured to perform correlation analysis on the data in the basic data set, and splice the associated data to form an updated data set; A data cleaning module, configured to clean the data in the updated data set, and screen out representative data from the updated data set; A coverage evaluation module, configured to perform data analysis based on the screened data to obtain network evaluation indicators at the building level or user level of the target area.

[0051] In this embodiment, the data acquisition module and the data splicing module realize the automatic download and splicing of radio network, core network, and installation address data.

[0052] Radio network call record data: Download the radio side call records from the northbound interface and automatically import them into the database.

[0053] Core network call record data: Download the core network call record data and automatically import it into the database. The time uses the globally unified standard time.

[0054] Installation address data: Extract all mobile phone numbers under the name of a user with the installation address in a certain residential community, and the user address registered at the time of opening the mobile phone number.

[0055] In this embodiment, the data cleaning module automatically cleans the spliced call record data according to information such as time and address, including: (1) Time screening: Select data for two hours from 22:00 to 23:00 at night.

[0056] (2) Geographic screening: Match the installation address community with the cell coverage sector, and further clean the call records for the coverage sector of the residential community.

[0057] (3) Continuity screening: Users with call records in the coverage sector of the residential area for three consecutive days.

[0058] In this embodiment, the coverage evaluation module realizes the automatic output of cell indicators and problem reports.

[0059] Extract various network evaluation analysis indicators such as average RSRP, overlapping coverage rate, ERAB abnormal disconnection call record ratio, RRC reconstruction ratio, handover failure rate, and release failure rate at the granularity of the cell or building, which is more automated and comprehensive, and reflects the real perception of users.

[0060] Embodiment 3: This embodiment provides a non-transitory computer-readable storage medium, on which computer instructions are stored, and the computer instructions cause the computer to execute the method for evaluating the 5G network coverage of a residential area, and the method includes the following steps: Obtain core network call records, radio network call records, APP perception call records, and user information within the target area to form a basic data set; Perform correlation analysis on the data in the basic data set, and splice the associated data to form an updated data set; Perform data cleaning on the updated data set, and screen out representative data from the updated data set; Based on the screened data, perform data analysis to obtain network evaluation indicators at the building level or user level of the target area.

[0061] Embodiment 4: This embodiment provides an electronic device, which may include: a processor, a communications interface, a memory, and a communication bus. Among them, the processor, the communications interface, and the memory complete mutual communication through the communication bus. The processor can call the logical instructions in the memory to execute the method for evaluating the 5G network coverage in a residential area, and this method includes the following steps: Obtain core network call records, radio network call records, APP perception call records, and user information within the target area to form a basic data set; Perform correlation analysis on the data in the basic data set, and splice the associated data to form an updated data set; Perform data cleaning on the updated data set, and screen out representative data from the updated data set; Based on the screened data, perform data analysis to obtain network evaluation indicators at the building level or user level of the target area.

[0062] In addition, when the logical instructions in the above-mentioned memory are implemented in the form of software function units and sold or used as an independent product, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this 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 for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. And the aforementioned storage medium includes: USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical disks, etc., which can store program codes.

[0063] Embodiment 5: This embodiment provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the method for evaluating the 5G network coverage in a residential area, and the method includes the following steps: Obtain core network call records, radio network call records, APP perception call records, and user information within the target area to form a basic data set; Perform correlation analysis on the data in the basic data set, and splice the associated data to form an updated data set; Perform data cleaning on the updated data set, and screen out representative data from the updated data set; Based on the screened data, perform data analysis to obtain network evaluation indicators at the building level or user level in the target area.

[0064] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative efforts.

[0065] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0066] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for evaluating 5G network coverage in residential areas, characterized in that: include: Obtain core network call records, wireless network call records, APP-aware call records, and user information in the target area to form a basic data set; Performing correlation analysis on the data in the basic data set, and splicing the related data to form an updated data set; Performing data cleaning on the updated data set, and screening out representative data from the updated data set; Based on the filtered data, data analysis is performed to obtain building-level or user-level network evaluation indicators in the target area.

2. A method for evaluating 5G network coverage in residential areas according to claim 1, characterized in that: The acquisition of core network call records, wireless network call records, APP-aware call records and user information in the target area to form a basic data set specifically includes: Extract the core network call list in the target area, recorded as ; Extract the wireless network call list in the target area, recorded as ; Extract the APP-aware call list in the target area, recorded as ; Get user information in the target area, recorded as ; The basic data set is represented as .

3. A method for evaluating 5G network coverage in residential areas according to claim 2, characterized in that: User information in the target area, including user installation and maintenance work orders 、User installation address , and the user's mobile phone address , the user information in the target area is represented as .

4. A method for evaluating 5G network coverage in residential areas according to claim 3, characterized in that: Perform correlation analysis on the data in the basic data set and splice the related data to form an updated data set; specifically including: According to user number , associate the user's core network call list and installation address, and concatenate them to get: ； According to MMES1APID and TMSI, the wireless network call bill and the core network call bill corresponding to the user are associated and spliced ​​to obtain: ； in, It is the unique identifier assigned to the user by the S1AP protocol on the mobility management entity MME side of the core network. It is a temporary mobile user ID; Finally, we get an updated data set containing user addresses, wireless network information, and core network information, expressed as: 。 5. A method for evaluating 5G network coverage in residential areas according to claim 4, characterized in that: Performing data cleaning on the updated data set and selecting representative data from the updated data set specifically includes: Define the time as , the user share is , the rules for filtering the update data set are: (1) Combine the user's installation address to select users with high user activity and low network fluctuations The call data within the time period is expressed as: ； (2) For residential areas with manual test data, filter the user call records of the manual test sectors. ; (3) For residential areas without artificial test data, the call sheet sectors are marked as candidate sectors, and the candidate sectors with user occupancy rate less than 10% are cleaned. The other candidate sectors are marked as valid call sheet sectors, and the user call sheets under the valid call sheet sectors are screened, which is expressed as: ； (4) Obtain the APP-perceived call records of the selected users in the same time period, recorded as .

6. A method for evaluating 5G network coverage in residential areas according to claim 5, characterized in that: Based on the filtered data, data analysis is performed to obtain the building-level or user-level network evaluation indicators of the target area, specifically: By filtering the call list data , , and , calculate and output the average RSRP and overlap coverage rate at the building level or single user level in the target area , RRC reconstruction ratio , ERAB abnormal call drop ratio , indicators of switching failure rate and release failure rate; The first neighboring area RSRP is defined as , the RSRP of the second neighboring cell is , the RSRP of the third neighboring cell is , the RSRP of the target area cell is , if RSRP>-110dBm, and ≤6dB, and ≤6dB, and ≤6dB, the cell is an overlapping coverage cell, and the call record in it is a substandard call record, recorded as , overlapping coverage The calculation formula is: ； Define the RRC connection success rate as , if the call list <99.5%, it is a substandard call record, recorded as , the RRC reconstruction ratio calculation formula is: ； If the ERAB abnormal drop rate in the call record ≥0.1%, it is a substandard call record, recorded as , the calculation formula for the proportion of abnormal dropped calls in ERAB is: 。 7. A residential area 5G network coverage assessment system, characterized in that: include: The data acquisition module is used to obtain the core network call bills, wireless network call bills, APP-aware call bills and user information in the target area to form a basic data set; A data splicing module is used to perform correlation analysis on the data in the basic data set and splice the related data to form an updated data set; A data cleaning module, used to clean the updated data set and filter out representative data from the updated data set; The coverage assessment module is used to perform data analysis based on the filtered data to obtain building-level or user-level network assessment indicators in the target area.

8. A non-transitory computer-readable storage medium, characterized in that: Computer instructions are stored thereon, which enable the computer to execute the residential area 5G network coverage assessment method described in any one of claims 1-6.

9. An electronic device, characterized in that: include: A processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus, and the processor calls the logic instructions in the memory to execute the residential area 5G network coverage assessment method described in any one of claims 1-6.

10. A computer program product, characterized in that The computer program product includes a computer program, which is stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer executes the residential area 5G network coverage assessment method described in any one of claims 1-6.

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