Indoor signal coverage analysis method and device

Abstract

The present application provides an indoor signal coverage analysis method and device. The method includes: obtaining multiple target network change characteristics that match a preset network change characteristic model from the network change characteristics of each resident user terminal located in the target building during a first preset time period; obtaining the floor level of each target user terminal corresponding to each target network change characteristic based on the duration of each target network change characteristic and the elevator lifting and lowering rate of the target building; and determining the indoor signal coverage result of the building level corresponding to each target user terminal based on the measurement report MR data of each target user terminal located in the target building during a second preset time period. The indoor signal coverage analysis method provided in the embodiment of the present application can perform indoor mobile signal coverage analysis on high-rise buildings in a more comprehensive and effective manner.

Description

Technical Field

[0001] The present application relates to the field of wireless communication operation and maintenance technology, and specifically to a method and device for analyzing indoor signal coverage. Background Art

[0002] To ensure mobile signal coverage in high-rise residential areas, such as office buildings and high-rise residential buildings, indoor distributed systems are typically prioritized. However, evaluating and analyzing indoor mobile signal coverage quality has always been a challenge in mobile network optimization. Given the large number and widespread distribution of high-rise buildings, evaluating indoor mobile signal coverage quality in high-rise buildings is a particularly prominent pain point in network optimization.

[0003] To evaluate and analyze indoor mobile signal coverage quality, related technologies often use positioning algorithms to associate MR (Measurement Report) or MDT (Minimization Drive Test) information to implement building-based coverage analysis, or manually conduct CQT field tests and convert field test logs into coverage quality statistics and GIS results.

[0004] However, indoor mobile signal coverage analysis based on positioning algorithms and associating MR or MDT information requires associating precise positioning data sources like OTT, MDT, mobile halls, and home broadband with corresponding building-level data. However, the number of hierarchical fingerprints based on home broadband and SDK is too limited to comprehensively analyze indoor mobile signal coverage at all building levels in high-rise buildings. Manual CQT field testing for indoor mobile signal coverage analysis can only be performed in public areas such as hallways, making it impossible to comprehensively and effectively analyze indoor mobile signal coverage in high-rise buildings.

[0005] Therefore, how to conduct a more comprehensive and effective analysis of indoor mobile signal coverage in high-rise buildings is an urgent problem that needs to be solved in the current mobile network coverage optimization work. Summary of the Invention

[0006] The embodiments of the present application provide a method and apparatus for analyzing indoor signal coverage, which can more comprehensively and effectively analyze indoor mobile signal coverage in high-rise buildings.

[0007] In a first aspect, an embodiment of the present application provides an indoor signal coverage analysis method, comprising:

[0008] Acquire a plurality of target network change characteristics that match a preset network change characteristic model from the network change characteristics of each resident user terminal located in the target building during the first preset period;

[0009] Obtaining the floor level of each target user terminal corresponding to each target network change feature according to the duration of each target network change feature and the elevator ascent and descent rate of the target building;

[0010] According to the measurement report MR data of each target user terminal located in the target building during the second preset time period, the indoor signal coverage result of the building level corresponding to each target user terminal is determined.

[0011] In one embodiment, before obtaining the building level of each target user corresponding to each target network change feature based on the duration of each target network change feature and the elevator ascent and descent rate of the target building, the method further includes:

[0012] Extracting a maximum duration and a minimum duration from the durations of the target network change features;

[0013] The elevator lifting speed is determined according to the maximum duration, the minimum duration, and the measured height of the target building.

[0014] In one embodiment, obtaining the floor level of each target user terminal corresponding to each target network change feature according to the duration of each target network change feature and the elevator ascent and descent rate of the target building includes:

[0015] Determining the floor fingerprint of each target user terminal based on the duration of each target network change feature and the elevator ascent and descent rate of the target building;

[0016] Adjusting the floor fingerprint of each target user terminal according to the Internet access data of at least one target user terminal and the elevator lifting and lowering speed to obtain an accurate floor fingerprint of each target user terminal;

[0017] Obtain the building level of each target user terminal based on the precise floor fingerprint of the target user terminal;

[0018] The Internet access data includes at least one of home broadband data and software development kit (SDK) fingerprint data.

[0019] In one embodiment, it further includes:

[0020] Clustering is performed on network change characteristics of each resident user terminal located in the target building during a first preset time period to obtain a preset network change characteristic model.

[0021] In one embodiment, it further includes:

[0022] Obtaining network fluctuation data of the resident user terminal located in the target building during a plurality of the first preset time periods;

[0023] The network fluctuation data of a plurality of the first preset time periods are aggregated to determine the network change characteristics of the resident user terminal in the first preset time period.

[0024] In one embodiment, it further includes:

[0025] During a target period, sequentially collecting the mobility robustness optimization (MRO) data of the resident user terminals located in the target building according to a preset sampling period;

[0026] When N consecutive MRO data meeting the preset conditions are collected, a first preset time period is determined according to the collection time of the MRO data meeting the preset conditions;

[0027] Among them, N≥1.

[0028] In one embodiment, it further includes:

[0029] Slicing the signaling data of each user terminal located in the target building according to a preset period to determine the duration that each user terminal is located in the target building;

[0030] From the user terminals, user terminals whose duration of being in the target building is greater than a preset duration are obtained as resident user terminals.

[0031] In a second aspect, an embodiment of the present application provides an indoor signal coverage analysis device, comprising:

[0032] a network feature determination module, configured to obtain a plurality of target network change features that match a preset network change feature model from network change features of resident user terminals located in a target building during a first preset period;

[0033] A building level determination module, configured to obtain the floor level of each target user terminal corresponding to each target network change feature based on the duration of each target network change feature and the elevator ascent and descent rate of the target building;

[0034] The signal coverage analysis module is used to determine the indoor signal coverage result of the building level corresponding to each target user terminal based on the measurement report MR data of each target user terminal located in the target building during the second preset time period.

[0035] In a third aspect, an embodiment of the present application provides an electronic device, comprising a processor and a memory storing a computer program, wherein when the processor executes the program, the steps of the indoor signal coverage analysis method described in the first aspect are implemented.

[0036] In a fourth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the indoor signal coverage analysis method described in the first aspect.

[0037] The indoor signal coverage analysis method and device provided in the embodiments of the present application screens multiple target network change characteristics that match a preset network change characteristic model from the network change characteristics of each resident user terminal located in a target building during a first preset time period. Based on the duration of each target network change characteristic and the elevator ascent and descent rate of the target building, the device determines the building level of each target user terminal corresponding to each target network change characteristic, thereby aggregating the MR data of target user terminals at the same building level. This allows for more efficient indoor mobile signal coverage analysis on each floor of a high-rise building, thereby improving the accuracy of indoor mobile signal coverage analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions in the present application or the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0039] Figure 1 This is one of the flow charts of the indoor signal coverage analysis method provided in an embodiment of the present application;

[0040] Figure 2 Schematic diagram of the mapping relationship between the duration of the target network change feature and the floor fingerprint provided in an embodiment of the present application;

[0041] Figure 3 This is one of the structural diagrams of the indoor signal coverage analysis device provided in an embodiment of the present application;

[0042] Figure 4 is a structural diagram of an electronic device provided in an embodiment of the present application; DETAILED DESCRIPTION

[0043] To make the objectives, technical solutions, and advantages of this application more clear, the technical solutions in this application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of this application.

[0044] The embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0045] See also Figure 1 , is one of the flow charts of the indoor signal coverage analysis method provided by an embodiment of the present invention, which is applied in a server to perform indoor mobile signal coverage analysis on a target building. Figure 1 As shown, this embodiment provides an indoor signal coverage analysis method including:

[0046] Step 101 : Acquire a plurality of target network change characteristics that match a preset network change characteristic model from network change characteristics of resident user terminals located in a target building during a first preset period of time.

[0047] Step 102 : Acquire the floor level of each target user terminal corresponding to each target network change feature according to the duration of each target network change feature and the elevator ascent and descent rate of the target building.

[0048] Step 103 : determining the indoor signal coverage result of the building level corresponding to each target user terminal according to the measurement report MR data of each target user terminal located in the target building during the second preset time period.

[0049] By selecting multiple target network change characteristics that match a preset network change characteristic model from the network change characteristics of each resident user terminal in the target building during a first preset time period, and determining the building level of each target user terminal corresponding to each target network change characteristic based on the duration of each target network change characteristic and the elevator ascent and descent rate of the target building, the MR data of target user terminals at the same building level are aggregated. This allows for more efficient indoor mobile signal coverage analysis on each floor of a high-rise building, thereby improving the accuracy of indoor mobile signal coverage analysis.

[0050] In step 101, the target building is a high-rise building for indoor signal coverage analysis, specifically an office building or a residential building. Given the uncertainty of foot traffic in office buildings, statistical analysis is difficult to perform effectively, so the target building is preferably a residential building. Furthermore, to make the resulting network change characteristics more universal and thus improve the accuracy of subsequent indoor mobile signal coverage analysis, network change characteristics of resident user terminals located in the target building during a first preset time period are obtained.

[0051] In one embodiment, a resident user terminal may be a user terminal that has spent more than a preset duration in the target building on multiple days. For example, a user terminal may spend more than three hours in the target building on three days out of a week. Whether a user terminal is resident in the target building can be determined based on precise positioning technologies such as OTT and MDT (Minimized Drive Test).

[0052] To more accurately identify user terminals located in the target building, in one embodiment, the signaling data from user terminal 4, the 5G network control plane interface S1_MME, and N1N2 is aggregated and sliced ​​at an hourly granularity to calculate the dwell time of each user terminal in the network element cell where the target building is located. Since the trigger period for updating the existing network configuration timer is 54 minutes when the user terminal is not interacting with any services, using an hourly time slicing period ensures that the network element cell where the user terminal resides can be identified while the user terminal is using services or accessing broadband services. After determining the residence time of each user terminal in the network element cell where the target building is located, the MR data generated by each user terminal with a residence time exceeding the preset value during the night residence period, such as 21:00-24:00 in the network element cell, are clustered and counted. After clustering and counting with a step size of 5dB, the records with MR data records accounting for more than 20% of the total sampling of all user terminals in the network element cell during the night residence period are retained. The MR data retained for one week are then aggregated to select the three MR data models with the highest sampling numbers as the stable network measurement report models.

[0053] After obtaining the stable network measurement report model, multiple user terminals whose MR data matches the stable network measurement report model are screened out from each user terminal based on the stable network measurement report model. Based on precise positioning technologies such as OTT and MDT (minimized drive test), multiple user terminals located in the target building are screened out from the multiple user terminals that match the stable network measurement report model.

[0054] In order to more accurately determine the duration that a user terminal located in a target building has resided in the target building, thereby improving the accuracy of determining a resident user terminal from a plurality of user terminals located in the target building, in one embodiment, the method further includes: slicing signaling data of each user terminal located in the target building according to a preset period to determine the duration that each user terminal has been located in the target building;

[0055] From each user terminal, each user terminal that has been in the target building for a period longer than a preset period is obtained as each resident user terminal. The preset period may be one hour.

[0056] In one embodiment, the preset duration is the required length of time that a user terminal must remain in the target building during a specific time period. For example, the user terminal must remain in the target building for three hours during any of the following time periods: 9:00-11:00, 13:00-17:00, 0:00-6:00, or 21:00-24:00. If a user terminal remains in the target building for three hours during any of these time periods on three days of the week, the user terminal is determined to be a resident user terminal.

[0057] By slicing the signaling data of each user terminal located in the target building according to a preset period, the length of time each user terminal is located in the target building can be determined more accurately, thereby screening out resident user terminals based on the length of time each user terminal is located in the target building.

[0058] In step 101, the first preset period of time may be a preset period of time before the network status of the resident user terminal is detected to match the steady-state network fingerprint library of the resident user terminal, such as three minutes before the network status of the resident user terminal matches the steady-state network fingerprint library of the resident user terminal. The steady-state network fingerprint library may be obtained by clustering a large amount of MR data of the resident user terminal when it is located in the target building.

[0059] For example, MR data of resident user terminals in the target building can be obtained during the night residence period, such as 0:00-6:00 or 21:00-24:00. The MR data obtained during the night residence period every day can be clustered to obtain a steady-state network fingerprint library of the resident user terminals.

[0060] In step 101, the network change feature includes at least one of a intra-cell signal strength fluctuation feature and a network disconnection / inter-system fallback feature. The intra-cell signal strength fluctuation feature is the attenuation of the normal signal strength of the cell, and the normal signal strength can be obtained from a steady-state network fingerprint library.

[0061] In step 101, a preset network variation characteristic model includes at least one of a signal strength fluctuation characteristic interval and a network disconnection / inter-system fallback characteristic. The signal strength fluctuation characteristic interval can be determined by processing a large number of network variation characteristics corresponding to a large number of user terminals located in elevators of a target building during a first preset time period. For example, the interval can be 20-30 dB or 10-20 dB.

[0062] For example, if the network variation characteristic is a signal strength fluctuation characteristic, for example, a resident user terminal located in a building falls within the signal strength fluctuation characteristic range of a preset network variation characteristic model during the first period of time (e.g., the network variation characteristic is 25dB and the signal strength fluctuation characteristic range is 20-30dB), then the network variation characteristic is determined to be the target network variation characteristic. At this point, the target user terminal corresponding to the target network variation characteristic can be determined to be located in an elevator.

[0063] In one embodiment, obtaining the preset network change characteristic model includes:

[0064] Clustering is performed on network change characteristics of each resident user terminal located in the target building during a first preset time period to obtain a preset network change characteristic model.

[0065] Exemplarily, statistics are collected on resident user terminals and trigger frequency penetration rates of different network change characteristics, and network change characteristics of resident user terminals with a trigger frequency penetration rate greater than 30% are screened and aggregated to form a preset network change characteristic model.

[0066] By obtaining multiple target network change characteristics that match the preset network change characteristic model from the network change characteristics of each resident user terminal located in the target building during the first preset time period, unrepresentative network change characteristics caused by special reasons, such as user terminal damage or orientation problems, are screened out, making the data used in subsequent indoor signal coverage analysis more accurate.

[0067] In step 102, since the signal strength usually fluctuates significantly only when the user terminal is in the elevator, the corresponding network change characteristics appear. At the same time, after screening by the preset network change characteristic model, the screened target network change characteristics can be made more consistent with the network characteristics when the user terminal is in the elevator of the target building. Therefore, the duration of the target network change characteristics can be used as the duration of the target user terminal in the elevator corresponding to the target network change characteristics. At this time, the floor fingerprint of each target user terminal can be determined based on the duration and the elevator lifting speed of the target building. Among them, the corresponding relationship between the duration t and the floor fingerprint can be as follows: Figure 2 shown.

[0068] In one embodiment, the elevator acceleration rate can be determined by averaging the acceleration rates set for a large number of elevators, such as 0.5-1.5 seconds per floor. For example, when the elevator acceleration rate is 1 second per floor and the duration of the target network change feature is 10 seconds, the floor fingerprint of each target user terminal is determined to be 10 floors.

[0069] In order to determine a more accurate elevator lifting rate, thereby improving the accuracy of the floor fingerprint of the target user terminal, in one embodiment, the method further includes:

[0070] Extracting a maximum duration and a minimum duration from the durations of the target network change features;

[0071] The elevator lifting speed is determined according to the maximum duration, the minimum duration, and the measured height of the target building.

[0072] In one embodiment, the variance of the duration of each target network change feature is first obtained. Durations with large variance dispersion or outside a reasonable range are then eliminated based on the variance. The maximum and minimum durations are then extracted from the remaining durations. The elevator rate is then calculated by dividing the target building's measured height by (maximum duration - minimum duration). For example, if the target building is 34 stories high, the maximum duration is 45 seconds, and the minimum duration is 10 seconds, the elevator rate is: 34 / (45 - 10) = 1 floor / s.

[0073] In one embodiment, the height of the target building can be determined by the maximum duration and the preset lifting rate of the elevator. Specifically, the actual height of the target building, such as 34 floors, can be obtained through GIS (Geographic Information System or Geo-Information system, Geographic Information System). Then, based on the maximum duration and the preset lifting rate of the elevator, such as 0.5-1.5s / floor, the maximum height that can be reached under the maximum duration is determined. If the maximum height is greater than or equal to the actual height of the target building, the actual height of the target building is used as the measured height of the target building; if the maximum height is less than the actual height of the target building, the maximum height is used as the measured height of the target building.

[0074] In one embodiment, after determining the floor fingerprint of each target user terminal corresponding to each target network change characteristic, each floor fingerprint is classified according to a preset level mapping table that records the relationship between floor fingerprints and building levels, thereby determining the building level corresponding to each target user terminal. For example, if the floor fingerprint of the target user terminal is between 1 and 10 floors, the floor corresponding to the target user terminal can be the ground floor, and the corresponding building level is 1; if the floor fingerprint of the target user terminal is between 10 and 20 floors, the floor corresponding to the target user terminal can be the middle floor, and the corresponding building level is 2; if the floor fingerprint of the target user terminal is above the 20th floor, the floor corresponding to the target user terminal can be the high floor, and the corresponding building level is 3.

[0075] In order to make the calculated building level corresponding to each target user terminal more accurate, thereby improving the accuracy of indoor signal coverage analysis for each building level, in one embodiment,

[0076] The acquiring, based on the duration of each target network change characteristic and the elevator ascent and descent rate of the target building, the floor level of each target user terminal corresponding to each target network change characteristic includes:

[0077] Determining the floor fingerprint of each target user terminal based on the duration of each target network change feature and the elevator ascent and descent rate of the target building;

[0078] Adjusting the floor fingerprint of each target user terminal based on the internet access data of at least one target user terminal and the elevator lift rate to obtain a precise floor fingerprint of each target user terminal; wherein the internet access data includes at least one of home broadband data or software development kit (SDK) fingerprint data;

[0079] According to the precise floor fingerprint of the target user terminal, the building level corresponding to each target user terminal is determined.

[0080] In one embodiment, since home broadband data or software development kit (SDK) fingerprint data both record the user's specific floor information, each target user terminal is detected to determine whether corresponding home broadband data or SDK fingerprint data exists. If so, the corresponding specific floor information is obtained, and the floor fingerprint of each target user terminal is adjusted based on the specific floor information of the target user terminal for which home broadband data or SDK fingerprint data exists, thereby establishing a precise floor fingerprint for each target user terminal. For example, if the home broadband data corresponding to target user terminal 1 determines that target user terminal 1 is on the 18th floor, the user's floor fingerprint is adjusted based on the specific floor determined from the home broadband data of target user terminal 1 and the elevator lift rate, thereby obtaining a precise floor fingerprint for each target user terminal, and then determining the building level corresponding to each target user terminal based on the precise floor fingerprint of each target user terminal.

[0081] In step 103, to ensure that the final signal coverage result more comprehensively reflects the signal coverage of the target building, the second preset time period can be the time period when the user corresponding to the target user terminal is stably living in the target building. This can be determined through big data analysis of work-residence trends. Preferably, it can be 0:00-6:00 and / or 21:00-24:00.

[0082] In one embodiment, the MR data of each target user terminal within the second preset time period is aggregated, and coverage quality indicators are aggregated based on the building level to which each target user terminal belongs, thereby obtaining an indoor coverage analysis and evaluation result of a high-rise building.

[0083] In one embodiment, the MRORSRP (Reference Signal Receiving Power) value of the target network change characteristic corresponding to the target user terminal can also be summarized and counted. For example, the user who is disconnected from the network / has fallen back to a different system is counted once every 5 seconds during the duration, and the RSRP is set to -141, so as to obtain the coverage quality analysis and evaluation results of the building elevator and basement public special areas.

[0084] In order to make the obtained network change characteristics of the resident user terminal in the first preset time period more accurate, in one embodiment, the method further includes:

[0085] Obtaining network fluctuation data of the resident user terminal located in the target building during a plurality of the first preset time periods;

[0086] The network fluctuation data of a plurality of the first preset time periods are aggregated to determine the network change characteristics of the resident user terminal in the first preset time period.

[0087] In one embodiment, network fluctuation data is used to represent changes in network signaling during a first preset period of time for a resident user terminal located within a target building. After obtaining multiple network fluctuation data sets for the resident user, a KNN (K-Nearest Neighbor) algorithm is used to aggregate the network fluctuation data sets for the first preset period of time. This algorithm eliminates network fluctuation data from different serving cells and data with large variances in RSRP and network fluctuation duration to obtain network variation characteristics. This ensures the regularity of the network variation characteristics for the resident user terminal and improves the accuracy of subsequent indoor signal coverage analysis.

[0088] In order to accurately determine the first preset time period, in one embodiment, the method further includes:

[0089] During a target period, sequentially collecting the mobility robustness optimization (MRO) data of the resident user terminals located in the target building according to a preset sampling period;

[0090] When N consecutive MRO data that meet the preset conditions are collected, a first preset time period is determined based on the collection time of the MRO data that meet the preset conditions, where N≥1.

[0091] In one embodiment, the target time period is the peak time period for each resident user terminal to return home, such as 5:00 PM to 10:00 PM. The preset sampling period can be determined based on the MRO sampling period configured in the existing network. For example, if the MRO sampling period configured in the existing network is 5 seconds, the preset sampling period is 5 seconds.

[0092] In one embodiment, when N MRO data are collected continuously and match the steady-state network fingerprint library of the resident user terminal, it is judged that the collected MRO data meets the preset conditions. At this time, the collection time of the first collected MRO data that matches the steady-state network fingerprint library of the resident user terminal is defined as the user's return home time point, and three minutes before the user's return home time point is the first preset time period.

[0093] The indoor signal coverage analysis device provided in an embodiment of the present application is described below. The indoor signal coverage analysis device described below and the indoor signal coverage analysis method described above can be referenced to each other.

[0094] In one embodiment, if Figure 3 As shown, an indoor signal coverage analysis device is provided, comprising:

[0095] The network characteristic determination module 210 is configured to obtain a plurality of target network change characteristics that match a preset network change characteristic model from the network change characteristics of each resident user terminal located in the target building during the first preset period;

[0096] The building level determination module 220 is configured to obtain the floor level of each target user terminal corresponding to each target network change feature based on the duration of each target network change feature and the elevator ascent and descent rate of the target building;

[0097] The signal coverage analysis module 230 is configured to determine the indoor signal coverage result at the building level corresponding to each target user terminal based on the measurement report MR data of each target user terminal located in the target building during the second preset time period.

[0098] In one embodiment, the building level determination module 220 is further configured to: extract a maximum duration and a minimum duration from the durations of the target network change characteristics;

[0099] The elevator lifting speed is determined according to the maximum duration, the minimum duration, and the measured height of the target building.

[0100] In one embodiment, the building level determination module 220 is specifically configured to: adjust the floor fingerprint of each target user terminal based on the internet access data of at least one target user terminal and the elevator lift rate, to obtain a precise floor fingerprint of each target user terminal; wherein the internet access data includes at least one of home broadband data or software development kit (SDK) fingerprint data;

[0101] According to the precise floor fingerprint of the target user terminal, the building level corresponding to each target user terminal is determined.

[0102] In one embodiment, the network feature determination module 210 is further configured to cluster the network change features of the resident user terminals located in the target building during the first preset period of time to obtain a preset network change feature model.

[0103] In one embodiment, the network feature determination module 210 is further configured to: obtain network fluctuation data of the resident user terminal located in the target building during a plurality of the first preset time periods;

[0104] The network fluctuation data of a plurality of the first preset time periods are aggregated to determine the network change characteristics of the resident user terminal in the first preset time period.

[0105] In one embodiment, the network feature determination module 210 is further configured to: sequentially collect, within a target period, according to a preset sampling period, each mobility robustness optimization MRO data of the resident user terminal located in the target building;

[0106] When N consecutive MRO data meeting the preset conditions are collected, a first preset time period is determined according to the collection time of the MRO data meeting the preset conditions;

[0107] Among them, N≥1.

[0108] In one embodiment, the network feature determination module 210 is further configured to:

[0109] Slicing the signaling data of each user terminal located in the target building according to a preset period to determine the duration that each user terminal is located in the target building;

[0110] From the user terminals, user terminals whose duration of being in the target building is greater than a preset duration are obtained as resident user terminals.

[0111] The user terminal involved in the embodiments of the present application may refer to a device that provides voice and / or data connectivity to the user terminal, a handheld device with wireless connection capabilities, or other processing devices connected to a wireless modem, such as a mobile phone, a wearable device, etc. The name of the user terminal may vary in different systems. For example, in a 5G system, the user terminal may be referred to as a user equipment (UE).

[0112] Figure 4 An example of a physical structure diagram of an electronic device is shown below. Figure 4 As shown, the electronic device may include: a processor 810, a communication interface 820, a memory 830, and a communication bus 840, wherein the processor 810, the communication interface 820, and the memory 830 communicate with each other via the communication bus 840. The processor 810 may call a computer program in the memory 830 to execute the steps of the indoor signal coverage analysis method, for example, including:

[0113] Acquire a plurality of target network change characteristics that match a preset network change characteristic model from network change characteristics of each resident user terminal located in the target building during a first preset period of time;

[0114] Obtaining, based on the duration of each target network change characteristic and the elevator ascent and descent rate of the target building, a floor fingerprint of each target user terminal corresponding to each target network change characteristic, and determining, based on the floor fingerprint of each target user terminal, a building level corresponding to each target user terminal;

[0115] According to the measurement report MR data of each target user terminal located in the target building during the second preset time period, the indoor signal coverage result of the building level corresponding to each target user terminal is determined.

[0116] In addition, the logic instructions in the above-mentioned memory 830 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0117] On the other hand, embodiments of the present application further provide a computer program product, comprising a computer program. The computer program may be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can perform the steps of the indoor signal coverage analysis method provided in each of the above embodiments, for example, including:

[0118] Obtaining, based on the duration of each target network change feature and the elevator ascent and descent rate of the target building, a floor fingerprint of each target user terminal corresponding to each target network change feature;

[0119] Determine the floor level corresponding to each target user terminal based on the floor fingerprint;

[0120] According to the measurement report MR data of each target user terminal located in the target building during the second preset time period, the indoor signal coverage result of the building level corresponding to each target user terminal is determined.

[0121] On the other hand, an embodiment of the present application further provides a processor-readable storage medium, wherein the processor-readable storage medium stores a computer program, wherein the computer program is configured to cause a processor to execute the steps of the methods provided in the above embodiments, for example, including:

[0122] Acquire a plurality of target network change characteristics that match a preset network change characteristic model from the network change characteristics of each resident user terminal located in the target building during the first preset period;

[0123] Obtaining, based on the duration of each target network change feature and the elevator ascent and descent rate of the target building, a floor fingerprint of each target user terminal corresponding to each target network change feature;

[0124] Determine the floor level corresponding to each target user terminal based on the floor fingerprint;

[0125] According to the measurement report MR data of each target user terminal located in the target building during the second preset time period, the indoor signal coverage result of the building level corresponding to each target user terminal is determined.

[0126] The processor-readable storage medium can be any available medium or data storage device that can be accessed by the processor, including but not limited to magnetic storage (such as floppy disks, hard disks, magnetic tapes, magneto-optical disks (MO)), optical storage (such as CDs, DVDs, BDs, HVDs, etc.), and semiconductor storage (such as ROMs, EPROMs, EEPROMs, non-volatile memories (NANDFLASH), solid-state drives (SSDs)), etc.

[0127] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0128] 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, or of course, by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the existing technology 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, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling 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 certain parts of the embodiments.

[0129] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for analyzing indoor signal coverage, characterized in that: include: Acquire a plurality of target network change characteristics that match a preset network change characteristic model from the network change characteristics of each resident user terminal located in the target building during the first preset period; Obtaining the floor level of each target user terminal corresponding to each target network change feature according to the duration of each target network change feature and the elevator ascent and descent rate of the target building; Determining, based on the measurement report MR data of each target user terminal located in the target building during the second preset time period, an indoor signal coverage result at the building level corresponding to each target user terminal; The acquisition of the preset network change characteristic model includes: Clustering is performed on the network change characteristics of the resident user terminals located in the target building during the first preset time period to obtain the preset network change characteristic model.

2. The indoor signal coverage analysis method according to claim 1, characterized in that: Before obtaining the building level of each target user corresponding to each target network change feature according to the duration of each target network change feature and the elevator ascending / descending rate of the target building, the method further includes: Extracting a maximum duration and a minimum duration from the durations of the target network change characteristics; The elevator lifting speed is determined according to the maximum duration, the minimum duration, and the measured height of the target building.

3. The indoor signal coverage analysis method according to claim 1, characterized in that: The acquiring, based on the duration of each target network change characteristic and the elevator ascent and descent rate of the target building, the floor level of each target user terminal corresponding to each target network change characteristic includes: Determining the floor fingerprint of each target user terminal based on the duration of each target network change feature and the elevator ascent and descent rate of the target building; Adjusting the floor fingerprint of each target user terminal according to the Internet access data of at least one target user terminal and the elevator lifting and lowering speed to obtain an accurate floor fingerprint of each target user terminal; Obtain the building level of each target user terminal based on the precise floor fingerprint of the target user terminal; The Internet access data includes at least one of home broadband data and software development kit (SDK) fingerprint data.

4. The indoor signal coverage analysis method according to claim 1, characterized in that: Also includes: Clustering is performed on network change characteristics of each resident user terminal located in the target building during a first preset time period to obtain a preset network change characteristic model.

5. The indoor signal coverage analysis method according to claim 1, characterized in that: Also includes: Obtaining network fluctuation data of the resident user terminal located in the target building during a plurality of the first preset time periods; The network fluctuation data of a plurality of the first preset time periods are aggregated to determine the network change characteristics of the resident user terminal in the first preset time period.

6. The indoor signal coverage analysis method according to claim 1, 4 or 5, characterized in that: Also includes: During a target period, sequentially collecting the mobility robustness optimization (MRO) data of the resident user terminals located in the target building according to a preset sampling period; When N consecutive MRO data meeting the preset conditions are collected, a first preset time period is determined according to the collection time of the MRO data meeting the preset conditions; Among them, N≥1.

7. The indoor signal coverage analysis method according to claim 1, 4 or 5, characterized in that: Also includes: Slicing the signaling data of each user terminal located in the target building according to a preset period to determine the duration that each user terminal is located in the target building; From the user terminals, user terminals whose duration of being in the target building is greater than a preset duration are obtained as resident user terminals.

8. An indoor signal coverage analysis device, characterized in that: include: a network feature determination module, configured to obtain a plurality of target network change features that match a preset network change feature model from network change features of resident user terminals located in a target building during a first preset period; A building level determination module, configured to obtain the floor level of each target user terminal corresponding to each target network change feature based on the duration of each target network change feature and the elevator ascent and descent rate of the target building; a signal coverage analysis module, configured to determine, based on the measurement report MR data of each target user terminal located in the target building during the second preset time period, an indoor signal coverage result at the building level corresponding to each target user terminal; The acquisition of the preset network change characteristic model includes: Clustering is performed on the network change characteristics of the resident user terminals located in the target building during the first preset time period to obtain the preset network change characteristic model.

9. An electronic device comprising a processor and a memory storing a computer program, characterized in that: When the processor executes the computer program, the steps of the indoor signal coverage analysis method according to any one of claims 1 to 7 are implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the indoor signal coverage analysis method according to any one of claims 1 to 7 are implemented.

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