Cell determination method, apparatus, and storage medium

Abstract

The application provides a cell determination method, device and storage medium, relates to the technical field of communication, and can improve the accuracy of determining the user equipment resident cell. The method comprises the following steps: determining the positions of a target terminal device at multiple moments within a preset time period and target geographical area borders of multiple cells; the target geographical area borders are determined based on first cell border data and second cell border data of the cells; the first cell border data is the geographical area border of a first cell in a map; the second cell border data is the geographical area border of the first cell drawn based on a drawing tool; based on the positions of the target terminal device at the multiple moments and the geographical area borders of the multiple cells, the number of times that the target terminal device appears in each cell within the preset time period is determined; and the cell with a number of times greater than or equal to a preset threshold is determined as the target cell of the target terminal device. The embodiments of the application are used in the process of cell determination.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a cell determination method, apparatus and storage medium. Background Technology

[0002] With the continuous development of communication networks, the permanent cell of user equipment (UE) has become an important and essential piece of information in communication networks, and the demand for this information is increasing. For example, in scenarios such as wireless network optimization and broadband planning and construction, timely, comprehensive, and accurate data based on the UE's permanent cell is needed for the aforementioned analysis. Currently, the UE's permanent cell is mainly determined based on the following method: first, the location of the UE and the cell coverage area are determined, and then the UE's permanent cell is determined based on the UE's location and cell coverage area.

[0003] However, the cell coverage area in the above method is determined based on the base station signal coverage area. However, due to factors such as base station density, geographical distribution, and different signal coverage areas, the cell coverage area determined by the above method is generally a circular area. This makes the cell coverage area inaccurate, which in turn leads to low accuracy in determining the permanent cell of user equipment based on the cell coverage area. Summary of the Invention

[0004] This application provides a cell determination method, apparatus, and storage medium, which can improve the accuracy of determining the cells where user equipment resides.

[0005] To achieve the above objectives, this application adopts the following technical solution:

[0006] In a first aspect, this application provides a cell determination method, which includes: determining the location of a target terminal device at multiple times within a preset time period, and the target geographical region borders of multiple cells; the target geographical region borders are determined based on first cell border data and second cell border data; the first cell border data is the geographical region border of the first cell in a map; the second cell border data is the geographical region border of the first cell drawn using a drawing tool; based on the location of the target terminal device at multiple times and the geographical region borders of multiple cells, determining the number of times the target terminal device appears in each cell within the preset time period; and determining cells with a number greater than or equal to a preset threshold as target cells for the target terminal device.

[0007] In one possible implementation, determining the location of the target terminal device at multiple times within a preset time period includes: acquiring measurement report (MR) data of the target terminal device at multiple times; inputting the MR data at multiple times into a preset model to obtain the location of the target terminal device at the target time; the preset model is trained based on the MR data and locations of the multiple terminal devices.

[0008] In one possible implementation, determining target border data for multiple cells includes: obtaining first cell border data and second cell border data for each of the multiple cells; performing the following operation on the first cell border data and second cell border data for each cell to obtain target border data for each cell: determining the union of the first cell border data and second cell border data of the target cell as the target geographic area border of the target cell; the target cell is any one of the multiple cells.

[0009] In one possible implementation, based on the location of the terminal device at multiple times and the target geographic region borders of multiple cells, the number of times the terminal device appears in each cell within a preset time period is determined. This includes: performing steps 1 to 3 for the location at each time of the multiple times to obtain the number of times the target terminal device appears in each cell within the preset time period; Step 1: Determine the i-th cell from the multiple cells as the sample cell; i is a positive integer; Step 2: Under a first preset condition, determine that the location of the terminal device at the target time is located in the sample cell, and update the number of times the target terminal device appears in the sample cell within the preset time period; wherein, the first preset condition includes at least one of the following: the target geographic region border of the sample cell is abnormal data, and the distance between the location point represented by the location at the target time and the center point of the sample cell is less than the minimum distance; the distance between the location point represented by the location at the target time and the center point of the sample cell is less than the maximum distance, the target geographic region border of the sample cell is normal data, and the sample ray and the sample The case where the number of intersection points of the target geographic region border of the cell is odd; the endpoint of the sample ray is located at the target time, and the direction of the sample ray is a preset direction; Step 3, under the second preset case, the (i+1)th cell is used as the sample cell, and steps 1, 2, and 3 are repeated until it is determined that the location of the terminal device at the target time is in the sample cell, and the number of times the target terminal device appears in the sample cell within the preset time period is updated; wherein, the second preset case includes at least one of the following: the distance between the location point represented by the location at the target time and the center point of the sample cell is greater than or equal to the maximum distance; the target geographic region border of the sample cell is abnormal data, and the distance between the location point represented by the location at the target time and the center point of the sample cell is greater than or equal to the minimum distance; the distance between the location point represented by the location at the target time and the center point of the sample cell is less than the maximum distance, the target geographic region border of the sample cell is normal data, and the number of intersection points of the sample ray and the target geographic region border of the sample cell is even.

[0010] Secondly, this application provides a cell determination device, which includes: a processing unit; the processing unit is configured to determine the location of a target terminal device at multiple times within a preset time period, and the target geographical region borders of multiple cells; the target geographical region borders are determined based on first cell border data and second cell border data; the first cell border data is the geographical region border of a first cell in a map; the second cell border data is the geographical region border of the first cell drawn using a drawing tool; the processing unit is further configured to determine the number of times the target terminal device appears in each cell within the preset time period based on the location of the target terminal device at multiple times and the geographical region borders of multiple cells; the processing unit is further configured to determine cells with a number of occurrences greater than or equal to a preset threshold as target cells for the target terminal device.

[0011] In one possible implementation, the device further includes: a communication unit; the communication unit is used to acquire measurement report (MR) data of the target terminal device at multiple times; the processing unit is further used to input the MR data at multiple times into a preset model to obtain the position of the target terminal device at the target time; the preset model is trained based on the MR data of multiple terminal devices and the positions of multiple terminal devices.

[0012] In one possible implementation, the communication unit is further configured to acquire first cell border data and second cell border data for each of the multiple cells; the processing unit is further configured to perform the following operation on the first cell border data and second cell border data of each cell to obtain target border data for each cell: determine the union of the first cell border data and second cell border data of the target cell as the target geographical area border of the target cell; the target cell is any one of the multiple cells.

[0013] In one possible implementation, the processing unit is further configured to perform the following operations: for each location at multiple time points, perform steps 1 to 3 to obtain the number of times the target terminal device appears in each cell within a preset time period; Step 1: Determine the i-th cell as the sample cell from multiple cells; i is a positive integer; Step 2: Under a first preset condition, determine that the location of the terminal device at the target time point is located in the sample cell, and update the number of times the target terminal device appears in the sample cell within the preset time period; wherein, the first preset condition includes at least one of the following: the target geographic region border of the sample cell is abnormal data, and the distance between the location point represented by the location at the target time point and the center point of the sample cell is less than the minimum distance; the distance between the location point represented by the location at the target time point and the center point of the sample cell is less than the maximum distance, the target geographic region border of the sample cell is normal data, and the number of intersections between the sample ray and the target geographic region border of the sample cell is odd. The endpoint of the sample ray is located at the target time, and the direction of the sample ray is a preset direction. Step 3: Under the second preset condition, the (i+1)th cell is used as the sample cell, and steps 1, 2, and 3 are repeated until it is determined that the terminal device is located in the sample cell at the target time, and the number of times the target terminal device appears in the sample cell within the preset time period is updated. The second preset condition includes at least one of the following: the distance between the location point represented by the location at the target time and the center point of the sample cell is greater than or equal to the maximum distance; the boundary of the target geographical area of ​​the sample cell is abnormal data, and the distance between the location point represented by the location at the target time and the center point of the sample cell is greater than or equal to the minimum distance; the distance between the location point represented by the location at the target time and the center point of the sample cell is less than the maximum distance, the boundary of the target geographical area of ​​the sample cell is normal data, and the number of intersections between the sample ray and the boundary of the target geographical area of ​​the sample cell is even.

[0014] Thirdly, this application provides a cell determination apparatus, which includes: a processor and a communication interface; the communication interface and the processor are coupled, and the processor is used to run computer programs or instructions to implement the cell determination method as described in the first aspect and any possible implementation thereof.

[0015] Fourthly, this application provides a computer-readable storage medium storing instructions that, when executed on a terminal, cause the terminal to perform the cell determination method as described in the first aspect and any possible implementation thereof.

[0016] Fifthly, this application provides a computer program product containing instructions that, when run on a cell determination device, cause the cell determination device to perform the cell determination method as described in the first aspect and any possible implementation thereof.

[0017] In a sixth aspect, this application provides a chip including a processor and a communication interface, the communication interface and the processor being coupled together, the processor being used to run computer programs or instructions to implement the cell determination method as described in the first aspect and any possible implementation thereof.

[0018] Specifically, the chip provided in this application also includes a memory for storing computer programs or instructions.

[0019] The above technical solution brings at least the following beneficial effects: The cell determination method provided in this application calculates the location of the target terminal device at multiple times within a preset time period, as well as the geographical boundaries of multiple cells. Based on the location of the target terminal device at multiple times and the geographical boundaries of multiple cells, it determines the number of times the target terminal device appears in each cell within the preset time period, and determines the cell with the highest number of appearances as the target cell of the target terminal device. The target geographical boundary described in this application is determined based on the first cell boundary data (i.e., the geographical boundary of the first cell in the map) and the second cell boundary data (i.e., the geographical boundary of the first cell drawn by a drawing tool). The geographical boundary of the cell determined in this way is closer to the actual geographical situation. Compared with the roughly circular boundary determined based on the base station signal coverage, the geographical boundary of this application is more accurate, thereby improving the accuracy of determining the target cell (i.e., the resident cell) based on the above geographical boundary. Attached Figure Description

[0020] Figure 1 A structural diagram of a communication system provided in an embodiment of this application;

[0021] Figure 2 A flowchart illustrating a cell determination method provided in this application embodiment;

[0022] Figure 3(a) is a schematic diagram of a target geographic region border provided in an embodiment of this application;

[0023] Figure 3(b) is a schematic diagram of another target geographic region boundary provided in an embodiment of this application;

[0024] Figure 4 A schematic diagram illustrating the stages of a cell determination method provided in an embodiment of this application;

[0025] Figure 5A flowchart illustrating another cell determination method provided in this application embodiment;

[0026] Figure 6 A schematic diagram illustrating the stages of another cell determination method provided in an embodiment of this application;

[0027] Figure 7 A flowchart illustrating another cell determination method provided in this application embodiment;

[0028] Figure 8(a) is a schematic diagram of the relative position of a border provided in an embodiment of this application;

[0029] Figure 8(b) is a schematic diagram of another relative position of the border provided in an embodiment of this application;

[0030] Figure 9 A flowchart illustrating another cell determination method provided in this application embodiment;

[0031] Figure 10 A flowchart illustrating another cell determination method provided in this application embodiment;

[0032] Figure 11 A flowchart illustrating another cell determination method provided in this application embodiment;

[0033] Figure 12 A schematic diagram illustrating the relative position of a sample ray and an edge, provided for an embodiment of this application;

[0034] Figure 13 A schematic diagram illustrating the stages of another cell determination method provided in an embodiment of this application;

[0035] Figure 14 This is a schematic diagram of the structure of a cell determination device provided in an embodiment of this application;

[0036] Figure 15 This is a schematic diagram of another cell determination device provided in an embodiment of this application. Detailed Implementation

[0037] The cell determination method, apparatus, and storage medium provided in the embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0038] In this article, the term "and / or" is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone.

[0039] The terms "first" and "second," etc., used in the specification and drawings of this application are used to distinguish different objects or to distinguish different treatments of the same object, rather than to describe a specific order of objects.

[0040] Furthermore, the terms "comprising" and "having," and any variations thereof, used in the description of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the steps or units listed, but may optionally include other steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus.

[0041] It should be noted that in the embodiments of this application, the words "exemplary" or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of the words "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0042] In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0043] like Figure 1 As shown, Figure 1 A schematic diagram of a communication system provided in an embodiment of this application is shown. The communication system includes a computing device 101 and a terminal device 102.

[0044] The computing device 101 is used to determine the location of the target terminal device at multiple times within a preset time period, as well as the target geographical area borders of multiple cells. Based on the location of the target terminal device at multiple times and the geographical area borders of multiple cells, it determines the number of times the target terminal device appears in each cell within the preset time period, and determines the cells with a number greater than or equal to a preset threshold as the target cells of the target terminal device.

[0045] The target geographic region boundary is determined based on the first and second cell boundary data; the first cell boundary data is the geographic region boundary of the first cell in the map; the second cell boundary data is the geographic region boundary of the first cell drawn using a drawing tool.

[0046] Terminal device 102 is used to provide computing device 101 with measurement report (MR) data for determining location.

[0047] Terminal device 102 is a device with wireless communication capabilities that can be deployed on land, including indoors or outdoors, handheld or vehicle-mounted, or on water (such as on ships). It can also be deployed in the air (e.g., on airplanes, balloons, and satellites).

[0048] In some examples, terminal equipment 102 is also referred to as user equipment (UE), mobile station (MS), mobile terminal (MT), and terminal, etc., and is a device that provides voice and / or data connectivity to a user. For example, terminal equipment 102 includes handheld devices with wireless connectivity, vehicle-mounted devices, etc. Currently, terminal device 102 can be: mobile phone, tablet computer, laptop computer, handheld computer, mobile internet device (MID), wearable device (such as smartwatch, smart bracelet, pedometer, etc.), vehicle-mounted device (such as car, bicycle, electric vehicle, airplane, ship, train, high-speed rail, etc.), virtual reality (VR) device, augmented reality (AR) device, wireless terminal in industrial control, smart home device (such as refrigerator, television, air conditioner, electricity meter, etc.), smart robot, workshop equipment, wireless terminal in self-driving, wireless terminal in remote medical surgery, wireless terminal in smart grid, wireless terminal in transportation safety, wireless terminal in smart city, or wireless terminal in smart home, flying equipment (such as smart robot, hot air balloon, drone, airplane), etc. In one possible application scenario of this application, the terminal device is a terminal device that frequently operates on the ground, such as an in-vehicle device. In this application, for ease of description, the chip deployed in the above-mentioned device, such as a system-on-a-chip (SOC), a baseband chip, or other chips with communication functions, can also be referred to as terminal device 102.

[0049] Optionally, the terminal device 102 can be an embedded communication device or a user handheld communication device, including mobile phones, tablets, etc.

[0050] As an example, in this embodiment, the terminal device 102 can also be a wearable device. Wearable devices, also known as wearable smart devices, are a general term for devices that utilize wearable technology to intelligently design and develop everyday wearables, such as glasses, gloves, watches, clothing, and shoes. Wearable devices are portable devices that are worn directly on the body or integrated into the user's clothing or accessories. Wearable devices are not merely hardware devices, but also achieve powerful functions through software support, data interaction, and cloud interaction. Broadly speaking, wearable smart devices include those that are feature-rich, large in size, and can achieve complete or partial functions without relying on a smartphone, such as smartwatches or smart glasses, as well as those that focus on a specific type of application function and require the use of other devices such as smartphones, such as various smart bracelets and smart jewelry for vital sign monitoring.

[0051] Optional, Figure 1 This is just an example framework diagram. Figure 1 The number of nodes included is unlimited, and except for Figure 1 In addition to the functional nodes shown, other nodes may also be included, such as access network device 103, etc. This application does not impose any restrictions on this.

[0052] Access network device 103 is a device located on the access network side of the aforementioned communication system 100, and has wireless transceiver capabilities, or a chip or chip system that can be installed on the device. Access network device 103 includes, but is not limited to: access points (APs) in WiFi systems, such as home gateways, routers, servers, switches, bridges, etc.; evolved NodeBs (eNBs), radio network controllers (RNCs), NodeBs (NBs), base station controllers (BSCs), base transceiver stations (BTSs), home base stations (e.g., home evolved NodeBs, or home NodeBs, HNBs), base band units (BBUs), wireless relay nodes, wireless backhaul nodes, transmission and reception points (TRPs or transmission points, TPs), etc.; and can also be 5G base stations, such as new radio (NR) base stations. Access network equipment 103 can be a gNB (gear node) in a radio (NR) system, or a transmission point (TRP or TP), one or a group of antenna panels (including multiple antenna panels) in a base station in a 5G system, or a network node constituting a gNB or transmission point, such as a baseband unit (BBU), or a distributed unit (DU), a roadside unit (RSU) with base station functionality, or 5G access network (NG radioaccess network, NG-RAN) equipment, etc. Access network equipment 103 also includes base stations in different networking modes, such as a master evolved NodeB (MeNB) and a secondary eNB (SeNB, or secondary gNB, SgNB). Access network equipment 103 also includes different types, such as terrestrial base stations, airborne base stations, and satellite base stations, etc.

[0053] Furthermore, the communication system described in the embodiments of this application is for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and does not constitute a limitation on the technical solutions provided in the embodiments of this application. As those skilled in the art will know, with the evolution of network architecture and the emergence of new communication systems, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0054] With the continuous development of communication networks, the permanent cell of user equipment (UE) has become an important and essential piece of information in communication networks, and the demand for this information is increasing. For example, in scenarios such as wireless network optimization and broadband planning and construction, timely, comprehensive, and accurate data based on the UE's permanent cell is needed for the aforementioned analysis. Currently, the UE's permanent cell is mainly determined based on the following method: first, the location of the UE and the cell coverage area are determined, and then the UE's permanent cell is determined based on the UE's location and cell coverage area.

[0055] However, the cell coverage area in the above method is determined based on the base station signal coverage area. However, due to factors such as base station density, geographical distribution, and different signal coverage areas, the cell coverage area determined by the above method is generally a circular area. This makes the cell coverage area inaccurate, which in turn leads to low accuracy in determining the permanent cell of user equipment based on the cell coverage area.

[0056] To address the problems existing in the prior art, this application proposes a cell determination method that can improve the accuracy of determining the cells where user equipment resides. For example... Figure 2 As shown, the method includes:

[0057] S201. The computing device determines the location of the target terminal device at multiple times within a preset time period, as well as the target geographical area boundaries of multiple cells.

[0058] The target geographic region boundary is determined based on the first and second cell boundary data. The first cell boundary data is the geographic region boundary of the first cell on the map. The second cell boundary data is the geographic region boundary of the first cell drawn using a drawing tool.

[0059] For example, the preset time period can be from 0:00 to 6:00 and from 21:00 to 24:00.

[0060] As an optional implementation, the process of the computing device determining the location of the target terminal device at multiple times within a preset time period in S201 can be as follows: the computing device can first obtain the MR data of the target terminal device at each of the multiple times from the network management device side, and input the MR data into the preset model to obtain the location at each of the multiple times.

[0061] As one possible implementation, the process of the computing device determining the target geographic region borders of multiple cells in S201 above can be as follows: the computing device first determines the first border data and the second border data of the target cell, and determines the union of the first border data and the second border data as the target geographic region border of the target cell. Here, the target cell is any one of the multiple cells. The computing device can determine the target geographic region border of each of the multiple cells based on the above method.

[0062] For example, Figure 3(a) shows an example of the target geographic area border for cell #1. Figure 3(b) shows an example of the target geographic area border for cell #2.

[0063] S202, The computing device determines the number of times the target terminal device appears in each cell within a preset time period based on the location of the target terminal device at multiple times and the geographical boundaries of multiple cells.

[0064] As an optional implementation, the above-mentioned S202 implementation process can be as follows: the computing device first determines the cell where the target terminal device is located at the target time, and adds 1 to the original number of times the target terminal device appears in each cell, until the computing device has determined the cells where the target terminal device is located at the above multiple times, and then obtains the number of times the target terminal device appears in each of the above multiple cells within the preset time period.

[0065] S203. The computing device determines the cells whose number of determinations is greater than or equal to a preset threshold as the target cells of the target terminal device.

[0066] As an optional implementation, the above-mentioned S203 process can be as follows: the computing device sorts the number of times the target terminal device appears in each of the above cells within a preset time period from largest to smallest, obtains a frequency sequence, and determines the cell with the largest frequency in the above frequency sequence as the target cell of the target terminal device. In this case, the above-mentioned preset threshold is the number of times the target terminal device appears in the target cell within the preset time period.

[0067] One possible implementation is that if the aforementioned preset time period is in monthly increments, the computing device can further break down the above frequency to obtain the frequency of days the target terminal device appears in the current cell (days_ratio) and the frequency of times the target terminal device appears in the current cell (cnt_ratio). Then, the computing device can perform a weighted summation of the above days_ratio and cnt_ratio to obtain the MR location reliability (which can also be called accuracy), and determine the cell with the highest MR location reliability as the target cell for the target terminal device.

[0068] In one alternative implementation, the above MR location reliability can satisfy the following formula 1:

[0069] mr_score =day_ratio*0.6 +cnt_ratio * 0.4 Formula 1

[0070] Here, mr_score is the MR location reliability.

[0071] Optionally, as shown in Table 1 below, the computing device can record information such as MR location reliability in tabular form. Table 1 may include at least one of the following: city name (city_name), broadband cell standard address name (comm_name), number (msisdn), broadband availability (preds), number of buildings covered by the cell (nbr_building), number of covered users (nbr_cover_user), number of ports (nbr_inter), number of online users (nbr_network_user), port occupancy rate (rate_permeate), access method (inter_type), construction method (contract_desc), whether MR positioning is used (if_mr), construction and commissioning time (date_starting), MR location reliability (mr_score), broadband cell standard address identifier (comm_id), city (city), whether it is a weekend (is_weekend), the cell's ranking in user MR positioning (score_row_number), and preset time period (month).

[0072] Table 1

[0073]

[0074] Optional, such as Figure 4 As shown, the cell determination method provided in this application embodiment can be divided into the following three stages: data processing stage, positioning algorithm stage, and deployment stage. In the data processing stage, the computing device can acquire MR data of the target terminal device at multiple times, as well as cell border data of multiple cells (i.e., including first border data and / or second border data). In the positioning algorithm stage, the computing device needs a user cell identification algorithm to determine the cell where the target terminal device is located at different times. Based on a distance rule algorithm, the computing device integrates the cells where the target terminal device is located at different times to obtain the number of times and days the target terminal device appears in each cell. The number of times and days are then weighted and summed to obtain the MR positioning reliability, and the target cell is determined based on the MR positioning reliability. In the deployment stage, the computing device can optimize the deployment of the algorithm and / or data described in the positioning algorithm.

[0075] The above technical solution brings at least the following beneficial effects: The cell determination method provided in this application calculates the location of the target terminal device at multiple times within a preset time period, as well as the geographical boundaries of multiple cells. Based on the location of the target terminal device at multiple times and the geographical boundaries of multiple cells, it determines the number of times the target terminal device appears in each cell within the preset time period, and determines the cell with the highest number of appearances as the target cell of the target terminal device. The target geographical boundary described in this application is determined based on the first cell boundary data (i.e., the geographical boundary of the first cell in the map) and the second cell boundary data (i.e., the geographical boundary of the first cell drawn by a drawing tool). The geographical boundary of the cell determined in this way is closer to the actual geographical situation. Compared with the roughly circular boundary determined based on the base station signal coverage, the geographical boundary of this application is more accurate, thereby improving the accuracy of determining the target cell (i.e., the resident cell) based on the above geographical boundary.

[0076] In an optional embodiment, as shown in S201, the computing device determines the location of the target terminal device at multiple times within a preset time period. Figure 2 Based on the illustrated method embodiments, this embodiment provides a possible implementation, such as... Figure 5 As shown, Figure 5 The flowchart of another cell determination method provided in this application shows that the process of a computing device determining the location of a target terminal device at multiple times within a preset time period may include the following steps S501 to S502.

[0077] S501, The computing device acquires MR data of the target terminal device at multiple times.

[0078] As one possible implementation, the above-described S501 process can be as follows: Since the target terminal device periodically reports MR data to the network management device, the network management device periodically receives and stores the MR data from the target terminal device. Next, the computing device can send a request message to the network management device, which requests MR data from the target terminal device at multiple times. After receiving the request message, the network management device sends the MR data from the target terminal device at multiple times to the computing device, and the computing device receives the MR data from the network management device at multiple times.

[0079] S502. The computing device inputs the MR data into the preset model to obtain the position of the target terminal device at the target time.

[0080] The preset model is trained based on MR data from multiple terminal devices and the locations of multiple terminal devices.

[0081] Optionally, the above locations can be represented by latitude and longitude. The computing device can preprocess the above latitude and longitude data, that is, take five decimal places of latitude and longitude (latitude and longitude are not empty and not zero), thus aggregating the 6-digit latitude and longitude into 5-digit latitude and longitude.

[0082] In one alternative implementation, such as Figure 6 As shown, the process by which the computing device determines the above-mentioned preset model can be achieved through the following steps 1 to 5.

[0083] Step 1: The computing device collects Minimization Drive Test (MDT) data from multiple terminal devices.

[0084] The MDT data may include metric data and the location of the terminal device.

[0085] Optionally, some of the above indicator data are the same as some of the data in the MR data.

[0086] Step 2: The computing device preprocesses the MDT data from the aforementioned multiple terminal devices.

[0087] For example, the above preprocessing may include at least one of the following: exploratory analysis processing, data cleaning processing, data transformation processing, and standardization management processing.

[0088] Optionally, the above is merely an exemplary description of preprocessing, and the preprocessing may also include other processes, which are not limited in this application.

[0089] Step 3: The computing device divides the MDT data from multiple terminal devices into a training set and a test set, and trains the initial model using the XGBoost regression model based on the training set to obtain the trained initial model.

[0090] Step 4: The computing device tests the trained initial model based on the above test set and obtains the test results.

[0091] The test results are used to characterize the accuracy of the initial model after training.

[0092] Step 5: Calculate whether the initial model trained above meets the preset requirements based on the test results.

[0093] Optionally, the above preset requirement can be that the test result is greater than or equal to the model threshold (e.g., 95%).

[0094] If the initial model after training meets the preset requirements, the computing device will execute step 6.

[0095] Step 6: The computing device determines that the initial model after the above training is the preset model.

[0096] If the initial model trained above does not meet the preset requirements, the computing device will execute step 7.

[0097] Step 7: The computing device adjusts the parameters of the initial model after training, and uses the adjusted initial model as the initial model in step 3 above. Steps 3 to 7 above are repeated until the test results meet the preset requirements.

[0098] The above technical solution brings at least the following beneficial effects: The cell determination method provided in this application allows the computing device to acquire the measurement report (MR) data of the target terminal device at multiple times, and input the MR data at multiple times into a preset model (i.e., trained based on the MR data and the positions of multiple terminal devices) to obtain the position of the target terminal device at the target time. In this way, the position determined based on the preset model has higher accuracy, providing a data basis for the subsequent computing device to determine the number of times the target terminal device appears in each cell within a preset time period based on the above position.

[0099] In an optional embodiment, as shown in S201, the computing device determines the target geographic region bounding boxes of multiple cells. Figure 5 Based on the illustrated method embodiments, this embodiment provides a possible implementation, such as... Figure 7 As shown, Figure 7 The flowchart of another cell determination method provided in this application shows that the process of a computing device determining the target geographic area boundary of multiple cells may include the following steps S701 to S702.

[0100] S701, The computing device acquires the first cell border data and the second cell border data of each of the multiple cells.

[0101] As an optional implementation, the above-mentioned S701 process can be as follows: The computing device first acquires information about multiple first cell border data and multiple second cell border data. Then, based on the information of the first cell border data of the target cell (i.e., any one of the multiple cells), it performs fuzzy matching with the information of the multiple second cell border data to determine the second cell border data corresponding to the first cell border data of the target cell. The above information may include at least one of the following: broadband standard address and identifier. Each cell border data pair includes one first cell border data and one second cell border data. The computing device determines the first cell border data and the second cell border data for each of the multiple cells based on the above method.

[0102] Optionally, if the first cell border data or the second cell border data is abnormal (e.g., overlapping coverage abnormality), the computing device can process the abnormal first cell border data and second cell border data using ArcGIS tools.

[0103] S702. The computing device performs the following operation on the first cell border data and the second cell border data of each cell to obtain the target border data of each cell: determine the union of the first cell border data and the second cell border data of the target cell as the target geographic area border of the target cell.

[0104] The target community is any one of multiple communities.

[0105] As one possible implementation, the above-mentioned S702 implementation process can be as follows: the computing device can merge the first border data and the second cell border data using ArcGIS tools to obtain the union of the first border data and the second cell border data, and determine the union as the target geographical area border of the target cell.

[0106] Optionally, as shown in Figure 8(a), if there is an overlap between the first border data and the second cell border data, the computing device can use the first border data as a reference, and use the spatial linking deduplication tool in ArcGIS to delete the part of the second border data that overlaps with the first border data. Then, the merge tool can merge the first border data and the deduplicated second border data to obtain the union of the first border data and the second cell border data (for example, the union #1 in Figure 8(a)). The union is then determined as the target geographic area border of the target cell.

[0107] Alternatively, as shown in Figure 8(b), if there is no overlap between the first border data and the second cell border data, the computing device can directly determine the first border data and the second cell border data as the target geographic area border of the target cell (e.g., the union #2 in Figure 8(b)).

[0108] The above technical solution brings at least the following beneficial effects: The cell determination method provided in this application involves a computing device acquiring first cell border data and second cell border data for each of multiple cells. The following operation is performed on the first and second cell border data of each cell to obtain the target border data for each cell: the union of the first and second cell border data of the target cell (i.e., any one of the multiple cells) is determined as the target geographical region border of the target cell. Based on the above, the target geographical region border of this application is determined based on the first cell border data (i.e., the geographical region border of the first cell in the map) and the second cell border data (i.e., the geographical region border of the first cell drawn using a drawing tool). This method determines the geographical region border of the cell more closely resembles the actual geographical situation. Compared to the approximate circular border determined based on the base station signal coverage area, the geographical region border of this application is more accurate, providing a more accurate data foundation for the subsequent computing device to determine the target cell (i.e., the resident cell) based on the aforementioned geographical region border.

[0109] In an optional embodiment, as shown in S202, the computing device determines the number of times the target terminal device appears in each cell within a preset time period based on the location of the target terminal device at multiple times and the geographical boundaries of multiple cells. Figure 2 Based on the illustrated method embodiments, this embodiment provides a possible implementation, such as... Figure 9 As shown, Figure 9 The flowchart of another cell determination method provided in this application shows that the computing device performs the following steps S901 to S903 on the location of the target terminal device at each time point among multiple time points to obtain the number of times the target terminal device appears in each cell within the preset time period.

[0110] S901, The computing device determines the i-th cell as the sample cell from multiple cells.

[0111] Where i is a positive integer.

[0112] Optionally, the number of the aforementioned multiple cells can be determined by the computing device according to the actual situation, and this application does not impose any restrictions on this.

[0113] S902. Under the first preset condition, the computing device determines the sample cell to which the location of the terminal device belongs at the target time, and updates the number of times the target terminal device appears in the sample cell within the preset time period.

[0114] The first preset condition includes at least one of the following: the geographical boundary of the sample cell is abnormal data, and the distance between the location point represented by the location at the target time and the center point of the sample cell is less than the minimum distance; or the distance between the location point represented by the location at the target time and the center point of the sample cell is less than the maximum distance, the geographical boundary of the sample cell is normal data, and the number of intersections between the sample ray and the geographical boundary of the sample cell is odd. The endpoint of the sample ray is at the location point at the target time, and the direction of the sample ray is a preset direction.

[0115] S903. Under the second preset condition, the computing device takes the (i+1)th cell as the sample cell and repeats S901 to S903 until it determines the sample cell to which the terminal device belongs at the target time, and updates the number of times the target terminal device appears in the sample cell within the preset time period.

[0116] The second preset situation includes at least one of the following: the distance between the location point represented by the location at the target time and the center point of the sample cell is greater than or equal to the maximum distance; the geographical boundary of the sample cell is abnormal data and the distance between the location point represented by the location at the target time and the center point of the sample cell is greater than or equal to the minimum distance; the distance between the location point represented by the location at the target time and the center point of the sample cell is less than the maximum distance, the geographical boundary of the sample cell is normal data, and the number of intersections between the sample ray and the geographical boundary of the sample cell is even.

[0117] As an optional implementation method, such as Figure 10 As shown, the implementation process of S902 to S903 can be as follows: the computing device determines the target geographical area border of the above multiple cells as a cell border configuration file, and performs initialization processing on the above cell border configuration file.

[0118] Next, the computing device can determine the location at the target time from the locations at the above multiple times, and determine information such as the city where the target terminal device is located, the maximum distance, and the minimum distance.

[0119] Next, the computing device can perform the following operations on the sample cell to determine whether the target location is located in the sample cell: first, determine that the distance between the location point represented by the target location and the center point of the sample cell is less than the maximum distance; if the distance between the location point represented by the target location and the center point of the sample cell is the maximum distance, then the computing device determines whether the target geographic region border of the sample cell is abnormal (e.g., whether it is empty).

[0120] If the target geographic area border of the above sample cell is abnormal, then if the distance between the location point represented by the target location of the computing device and the center point of the above sample cell is less than the minimum distance, it is determined that the terminal device's location at the target time is within the sample cell, and the number of times the target terminal device appears in the sample cell within the preset time period is updated; if the distance between the location point represented by the target location and the center point of the above sample cell is greater than or equal to the minimum distance, it is determined that the terminal device's location at the target time is not within the sample cell, and the (i+1)th cell is taken as the sample cell, and the above judgment process is repeated until the sample cell to which the terminal device's location at the target time belongs is determined, and the number of times the target terminal device appears in the sample cell within the preset time period is updated.

[0121] If the target geographical area border of the above sample cell is normal, the computing device determines whether the terminal device's location at the target time belongs to the sample cell based on the ray casting method.

[0122] Optional, such as Figure 11 As shown, the process by which the computing device determines whether the location of the terminal device at the target time belongs to the sample cell based on the above-mentioned ray method can be as follows: the computing device determines the data of multiple edges from the target geographical area border of the target cell, and draws a ray (i.e., the sample ray) with the location of the target terminal device at the target time as the endpoint and the horizontal direction to the right as the preset direction.

[0123] Next, the computing device first determines whether the sample ray intersects with the target edge (i.e., any one of the multiple edges). After each of the multiple edges has been judged based on the above method, the number of intersection points between the sample ray and the multiple edges is counted.

[0124] Finally, the computing device determines whether the number of intersections between the sample ray and the multiple edges is odd. If the number of intersections is odd, the computing device determines the sample cell to which the terminal device's location belongs at the target time. If the number of intersections is not odd (i.e., the number of intersections is even), the computing device determines that the terminal device's location at the target time does not belong to a sample cell, and uses the (i+1)th cell as the sample cell, repeating the above judgment process until the sample cell to which the terminal device's location belongs at the target time is determined.

[0125] Optional, such as Figure 12 As shown, under the conditions of parallelism, overlap, line segment length of 0, and the sample ray intersecting only the lower breakpoint of the edge, the computing device can determine that the sample ray does not intersect the target edge.

[0126] Optionally, the number of times the target terminal device appears in each cell within the aforementioned preset time period can be listed in a table for more intuitive information retrieval. The aforementioned preset time period can be divided into two cases: Case 1, the preset time period is in daily granularity; Case 2, the preset time period is in monthly granularity. The table's format will differ depending on the granularity of the preset time period. The following explains the tables for each of these two cases.

[0127] Case 1: The above-mentioned preset time period is in days.

[0128] In scenario 1, the table above can be represented as shown in Table 2 below. Table 2 may include: mobile phone number (msisdn), city name (city_name), user longitude (longitude), user latitude (latitude), standard address of the broadband cell (comm_id), number of times the target terminal device appears in each cell (cnt_day), whether it is a weekend (is_weekend), and preset time period (day).

[0129] Table 2

[0130]

[0131] Case 2: The above-mentioned preset time period is in monthly increments.

[0132] In scenario 2, the above table can be presented as shown in Table 3 below. Table 3 may include: mobile phone number (msisdn), broadband cell standard address identifier (comm_id), number of times the target terminal device appears in each cell (cnt_each), sum of the number of times the target terminal device appears in each cell (sum_cnt), frequency of the number of times the target terminal device appears in each cell (cnt_ratio), number of days the target terminal device appears in each cell (days_each), sum of the number of days the target terminal device appears in each cell (days), frequency of the number of days the target terminal device appears in each cell (days_ratio), whether it is a weekend (is_weekend), and time (day).

[0133] Table 3

[0134]

[0135]

[0136] As shown in Table 3 above, the frequency of the target terminal device appearing in each cell is the ratio of the number of times the target terminal device appears in each cell to the sum of the number of times the target terminal device appears in each cell. The frequency of the target terminal device appearing on each cell by day is the ratio of the number of days the target terminal device appears in each cell to the sum of the number of days the target terminal device appears in each cell.

[0137] Optionally, the presentation of the above table can be further refined as the scenario changes, such as weekday scenarios, weekend scenarios, and scenarios for certain specific time periods. The computing device can flexibly configure the above table according to actual needs and business scenarios.

[0138] Alternatively, the table above may also include information on community broadband resources, such as broadband resource port occupancy rate, broadband construction time, number of broadband users, and number of buildings. This information on community broadband resources can provide operators with more comprehensive and accurate data for wireless optimization and broadband planning and construction.

[0139] The above technical solution brings at least the following beneficial effects: The cell determination method provided in this application involves a computing device performing the following steps 1 to 3 for each location at multiple time points to obtain the cell to which the location belongs at each time point: The computing device can determine the i-th cell from multiple cells as a sample cell. In a first preset case, the sample cell to which the terminal device's location belongs at the target time point is determined. In a second preset case, the (i+1)-th cell is used as the sample cell, and the above process is repeated until the sample cell to which the terminal device's location belongs at the target time point is determined. Then, the computing device can count the number of times the target terminal device appears in each cell within a preset time period based on the cell to which the location belongs at each time point. This provides a data basis for the subsequent computing device to determine the target cell based on the aforementioned count.

[0140] Optional, such as Figure 13 As shown, the cell determination method provided in this application embodiment can be divided into the following three stages: input data stage, algorithm stage, output data node, and algorithm verification stage. In the input data node, the computing device can determine the location, city, cell border data (i.e., first cell border data and / or second cell border data), maximum distance, and minimum distance of the target terminal device at multiple times. In the algorithm stage, the computing device can determine the number of times the target terminal device appears in each cell within a preset time period based on the user cell identification algorithm, big data rule model modeling, and user-resident cell positioning algorithm. In the output data stage, the computing device can determine the target cell based on the number of times the target terminal device appears in each cell within the preset time period. In the algorithm verification stage, the computing device can evaluate and optimize the big data rule model.

[0141] It is understood that the above-described cell determination method can be implemented by a cell determination device. To achieve the above functions, the cell determination device includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should readily recognize that, based on the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein, the embodiments disclosed in this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the embodiments disclosed in this application.

[0142] The embodiments disclosed in this application can divide the cell determination device generated by the above method example into functional modules. For example, each function can be divided into its own functional module, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware or as a software functional module. It should be noted that the module division in the embodiments disclosed in this application is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods.

[0143] Figure 14 This is a schematic diagram of a cell determination device provided in an embodiment of the present invention. Figure 14 As shown, the cell determination device 140 can be used to perform... Figure 2 , Figure 5 , Figure 7 , Figure 9 The cell determination method shown. The cell determination device 140 includes: a processing unit 1401.

[0144] Processing unit 1401 is used to determine the location of the target terminal device at multiple times within a preset time period, and the target geographical area borders of multiple cells; the target geographical area borders are determined based on the first cell border data and the second cell border data; the first cell border data is the geographical area border of the first cell in the map; the second cell border data is the geographical area border of the first cell drawn using a drawing tool; processing unit 1401 is also used to determine the number of times the target terminal device appears in each cell within the preset time period based on the location of the target terminal device at multiple times and the geographical area borders of multiple cells; processing unit 1401 is also used to determine the cells with a number greater than or equal to a preset threshold as the target cells of the target terminal device.

[0145] In one possible implementation, the device further includes: a communication unit 1402; the communication unit 1402 is used to acquire measurement report (MR) data of the target terminal device at multiple times; the processing unit 1401 is also used to input the MR data at multiple times into a preset model to obtain the position of the target terminal device at the target time; the preset model is trained based on the MR data of multiple terminal devices and the positions of multiple terminal devices.

[0146] In one possible implementation, the communication unit 1402 is further configured to acquire first cell border data and second cell border data of each of the multiple cells; the processing unit 1401 is further configured to perform the following operation on the first cell border data and second cell border data of each cell to obtain target border data of each cell: determine the union of the first border data and second cell border data of the target cell as the target geographical area border of the target cell; the target cell is any one of the multiple cells.

[0147] In one possible implementation, the processing unit 1401 is further configured to perform the following operations: For each location at a given time from multiple time points, perform steps 1 to 3 to obtain the number of times the target terminal device appears in each cell within a preset time period; Step 1: Determine the i-th cell from the multiple cells as the sample cell; i is a positive integer; Step 2: Under a first preset condition, determine that the location of the terminal device at the target time point is located in the sample cell, and update the number of times the target terminal device appears in the sample cell within the preset time period; wherein, the first preset condition includes at least one of the following: the target geographic region border of the sample cell is abnormal data, and the distance between the location point represented by the location at the target time point and the center point of the sample cell is less than the minimum distance; the distance between the location point represented by the location at the target time point and the center point of the sample cell is less than the maximum distance, the target geographic region border of the sample cell is normal data, and the number of intersections between the sample ray and the target geographic region border of the sample cell is odd. Case 1; The endpoint of the sample ray is located at the target time, and the direction of the sample ray is a preset direction; Step 3, under the second preset case, the (i+1)th cell is used as the sample cell, and steps 1, 2, and 3 are repeated until it is determined that the terminal device is located in the sample cell at the target time, and the number of times the target terminal device appears in the sample cell within the preset time period is updated; wherein, the second preset case includes at least one of the following: the distance between the location point represented by the location at the target time and the center point of the sample cell is greater than or equal to the maximum distance; the target geographical area border of the sample cell is abnormal data, and the distance between the location point represented by the location at the target time and the center point of the sample cell is greater than or equal to the minimum distance; the distance between the location point represented by the location at the target time and the center point of the sample cell is less than the maximum distance, the target geographical area border of the sample cell is normal data, and the number of intersections between the sample ray and the target geographical area border of the sample cell is even.

[0148] In implementing the functions of the integrated modules described above using hardware, this embodiment of the invention provides a possible structural diagram of the cell determination device involved in the above embodiments. For example... Figure 15 As shown, a cell determination device 150, for example, is used to perform... Figure 2 , Figure 5 , Figure 7 , Figure 9 The cell determination method is shown. The cell determination device 150 includes a processor 1501, a memory 1502, and a bus 1503. The processor 1501 and the memory 1502 can be connected via the bus 1503. Optionally, the cell determination device 150 may also include a communication interface 1504.

[0149] Processor 1501 is the control center of the user equipment and can be a single processor or a collective term for multiple processing elements. For example, processor 1501 can be a general-purpose central processing unit (CPU) 1502, or other general-purpose processors. The general-purpose processor can be a microprocessor or any conventional processor. As an example, combined with... Figure 14 The processing unit 1401 in the cell determination device performs the same functions as... Figure 15 The processor 1501 in it has the same function.

[0150] As one embodiment, processor 1501 may include one or more CPUs, such as CPU0 and CPU1.

[0151] The memory 502 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but is not limited thereto.

[0152] In one possible implementation, the memory 1502 can exist independently of the processor 1501. The memory 1502 can be connected to the processor 1501 via a bus 1503 and is used to store instructions or program code. When the processor 1501 calls and executes the instructions or program code stored in the memory 1502, it can implement the map drawing method provided in this embodiment of the invention. In another possible implementation, the memory 1502 can also be integrated with the processor 1501.

[0153] Bus 1503 can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. This bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 15The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0154] The communication interface 1504 is used to connect with other devices via a communication network. This communication network can be Ethernet, a wireless access network, a wireless local area network (WLAN), etc. The communication interface 1504 may include a communication unit 1402 for receiving data. In one design, in the cell determination apparatus 150 provided in this embodiment of the invention, the communication interface may also be integrated into the processor.

[0155] It should be pointed out that, Figure 15 The structure shown does not constitute a limitation on the cell determination device 150. Except... Figure 15 In addition to the components shown, the cell determination device 150 may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0156] Through the above description of the embodiments, those skilled in the art will clearly understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0157] The computer-readable storage medium may 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 (a non-exhaustive list) of computer-readable storage media include: electrical connections having one or more wires; portable computer disks; hard disks; random access memory (RAM); read-only memory (ROM); erasable programmable read-only memory (EPROM); registers; hard disks; optical fibers; portable compact disc read-only memory (CD-ROM); optical storage devices; magnetic storage devices; or any suitable combination thereof; or any other form of computer-readable storage medium known in the art. An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium may also be a component of the processor. The processor and the storage medium may reside in an application-specific integrated circuit (ASIC). In the embodiments of this application, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0158] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for determining a cell, characterized in that, include: Obtain the first cell border data and the second cell border data for each cell in multiple cells; the first cell border data is the geographical area border of the cell in the map; the second cell border data is the geographical area border of the cell drawn based on a drawing tool. The following operation is performed on the first cell border data and the second cell border data of each cell to obtain the target border data of each cell: the union of the first cell border data and the second cell border data of the target cell is determined as the target geographic region border of the target cell; the target cell is any one of the multiple cells; Determine the location of the target terminal device at multiple times within a preset time period; Based on the location of the target terminal device at multiple times and the target geographical area borders of multiple cells, determine the number of times the target terminal device appears in each cell within the preset time period; Cells whose frequency is greater than or equal to a preset threshold are identified as target cells for the target terminal device.

2. The method according to claim 1, characterized in that, Determining the location of the target terminal device at multiple times within a preset time period includes: Obtain the measurement report (MR) data of the target terminal device at the multiple time points; The MR data at the multiple time points are input into a preset model to obtain the position of the target terminal device at the target time point; the preset model is trained based on the MR data of the multiple terminal devices and the positions of the multiple terminal devices.

3. The method according to claim 1 or 2, characterized in that, The step of determining the number of times the terminal device appears in each cell within the preset time period based on the location of the terminal device at multiple times and the target geographical area borders of multiple cells includes: For each location at any of the multiple time points, perform steps 1 to 3 as follows to obtain the number of times the target terminal device appears in each cell within the preset time period; Step 1: Determine the i-th cell from the multiple cells as the sample cell; i is a positive integer; Step 2: Under the first preset condition, determine that the location of the terminal device at the target time is in the sample cell, and update the number of times the target terminal device appears in the sample cell within the preset time period; The first preset situation includes at least one of the following: the target geographic region border of the sample cell is abnormal data, and the distance between the location point represented by the location at the target time and the center point of the sample cell is less than the minimum distance; the distance between the location point represented by the location at the target time and the center point of the sample cell is less than the maximum distance; the target geographic region border of the sample cell is normal data, and the number of intersections between the sample ray and the target geographic region border of the sample cell is odd; the endpoint of the sample ray is the location point at the target time, and the direction of the sample ray is a preset direction. Step 3: Under the second preset condition, the (i+1)th cell is used as the sample cell, and Step 1, Step 2 and Step 3 are repeated until it is determined that the terminal device is located in the sample cell at the target time, and the number of times the target terminal device appears in the sample cell within the preset time period is updated. The second preset situation includes at least one of the following: the distance between the location point represented by the location at the target time and the center point of the sample cell is greater than or equal to the maximum distance; the target geographical region border of the sample cell is abnormal data and the distance between the location point represented by the location at the target time and the center point of the sample cell is greater than or equal to the minimum distance; the distance between the location point represented by the location at the target time and the center point of the sample cell is less than the maximum distance, the target geographical region border of the sample cell is normal data, and the number of intersections between the sample ray and the target geographical region border of the sample cell is even.

4. A cell determination device, characterized in that, include: Processing unit and communication unit; The communication unit is used to acquire first cell border data and second cell border data for each of the multiple cells. The processing unit is configured to perform the following operation on the first cell border data and the second cell border data of each cell to obtain the target border data of each cell: determine the union of the first cell border data and the second cell border data of the target cell as the target geographical area border of the target cell; the target cell is any one of the plurality of cells; The processing unit is used to determine the location of the target terminal device at multiple times within a preset time period, and the target geographical area borders of multiple cells; the target geographical area borders are determined based on the first cell border data and the second cell border data of the cells; the first cell border data is the geographical area border of the first cell in the map; the second cell border data is the geographical area border of the first cell drawn using a drawing tool. The processing unit is further configured to determine the number of times the target terminal device appears in each cell within the preset time period based on the location of the target terminal device at multiple times and the target geographical area borders of multiple cells; The processing unit is further configured to determine the cells whose number of occurrences is greater than or equal to a preset threshold as the target cells of the target terminal device.

5. The apparatus according to claim 4, characterized in that, The communication unit is used to acquire the measurement report (MR) data of the target terminal device at the multiple times. The processing unit is further configured to input the MR data at the multiple time points into a preset model to obtain the position of the target terminal device at the target time point; the preset model is trained based on the MR data of the multiple terminal devices and the positions of the multiple terminal devices.

6. The apparatus according to claim 4 or 5, characterized in that, The processing unit is also configured to perform the following operations: For each location at any of the multiple time points, perform steps 1 to 3 as follows to obtain the number of times the target terminal device appears in each cell within the preset time period; Step 1: Determine the i-th cell from the multiple cells as the sample cell; i is a positive integer; Step 2: Under the first preset condition, determine that the location of the terminal device at the target time is in the sample cell, and update the number of times the target terminal device appears in the sample cell within the preset time period; The first preset situation includes at least one of the following: the target geographic region border of the sample cell is abnormal data, and the distance between the location point represented by the location at the target time and the center point of the sample cell is less than the minimum distance; the distance between the location point represented by the location at the target time and the center point of the sample cell is less than the maximum distance; the target geographic region border of the sample cell is normal data, and the number of intersections between the sample ray and the target geographic region border of the sample cell is odd; the endpoint of the sample ray is the location point at the target time, and the direction of the sample ray is a preset direction. Step 3: Under the second preset condition, the (i+1)th cell is used as the sample cell, and Step 1, Step 2 and Step 3 are repeated until it is determined that the terminal device is located in the sample cell at the target time, and the number of times the target terminal device appears in the sample cell within the preset time period is updated. The second preset situation includes at least one of the following: the distance between the location point represented by the location at the target time and the center point of the sample cell is greater than or equal to the maximum distance; the target geographical region border of the sample cell is abnormal data and the distance between the location point represented by the location at the target time and the center point of the sample cell is greater than or equal to the minimum distance; the distance between the location point represented by the location at the target time and the center point of the sample cell is less than the maximum distance, the target geographical region border of the sample cell is normal data, and the number of intersections between the sample ray and the target geographical region border of the sample cell is even.

7. A cell determination device, characterized in that, include: A processor and a communication interface; the communication interface is coupled to the processor, the processor being used to run computer programs or instructions to implement the cell determination method as described in any one of claims 1-3.

8. A computer-readable storage medium storing instructions, characterized in that, When the computer executes the instruction, the computer performs the cell determination method as described in any one of claims 1-3.

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