CN116249125A

CN116249125A - Cell determination method, device and storage medium

Info

Publication number: CN116249125A
Application number: CN202211683298.1A
Authority: CN
Inventors: 葛阳; 赵雪寒; 杨明; 吴国防; 邵燕; 蒋涛
Original assignee: China United Network Communications Group Co Ltd
Current assignee: China United Network Communications Group Co Ltd
Priority date: 2022-12-27
Filing date: 2022-12-27
Publication date: 2023-06-09

Abstract

The application provides a cell determining method, a cell determining device and a storage medium, relates to the technical field of communication, and can improve the accuracy of a determined resident cell of user equipment. The method comprises the following steps: determining the positions of target terminal equipment at a plurality of moments in a preset time period and target geographic area frames of a plurality of cells; the target geographic area frame is determined based on first cell frame data and second cell frame data of the cell; the first cell frame data is a geographical area frame of the first cell in the map; the second cell frame data is a geographical area frame of the first cell, which is drawn based on a drawing tool; determining the number of times of the target terminal equipment in each cell in a preset time period based on the positions of the target terminal equipment at a plurality of moments and the geographical area frames of a plurality of cells; and determining the cells with times larger than or equal to a preset threshold value as target cells of target terminal equipment. The embodiment of the application is used in the process of cell determination.

Description

Cell determination method, device and storage medium

Technical Field

The present disclosure relates to the field of communications technologies, and in particular, to a method and apparatus for determining a cell, and a storage medium.

Background

With the continuous development of communication networks, the resident cell of the user equipment is an important and necessary information in the communication network, and the demand scene of the information is more and more, for example, in the scenes of wireless network optimization, broadband planning construction and the like, a timely, comprehensive and accurate data basis is required to be provided for the analysis based on the resident cell of the user equipment. The resident cell of the user equipment is currently determined mainly based on the following method: the location and cell coverage of the user equipment are first determined, and the resident cell of the user equipment is determined based on the location and cell coverage of the user equipment.

However, the cell coverage in the above method is determined based on the signal coverage of the base station, but is limited by factors such as density, geographical location distribution, and different sizes of the signal coverage of the base station, so the cell coverage determined based on the above method is generally a circular area, which makes the cell coverage inaccurate, and further results in lower accuracy of the resident cell of the ue determined based on the above cell coverage.

Disclosure of Invention

The application provides a cell determining method, a cell determining device and a storage medium, which can improve the accuracy of a determined resident cell of user equipment.

In order to achieve the above purpose, the present application adopts the following technical scheme:

in a first aspect, the present application provides a cell determining method, the method including: determining the positions of target terminal equipment at a plurality of moments in a preset time period and target geographic area frames of a plurality of cells; the target geographic area frame is determined based on first cell frame data and second cell frame data of the cell; the first cell frame data is a geographical area frame of the first cell in the map; the second cell frame data is a geographical area frame of the first cell, which is drawn based on a drawing tool; determining the number of times of the target terminal equipment in each cell in a preset time period based on the positions of the target terminal equipment at a plurality of moments and the geographical area frames of a plurality of cells; and determining the cells with times larger than or equal to a preset threshold value as target cells of target terminal equipment.

In one possible implementation manner, determining the positions of the target terminal device at a plurality of moments within a preset time period includes: acquiring measurement report MR data of target terminal equipment at a plurality of moments; inputting the MR data at a plurality of moments into a preset model to obtain the position of the target terminal equipment at the target moment; the preset model is trained based on MR data of the plurality of terminal devices and positions of the plurality of terminal devices.

In one possible implementation, determining target border data for a plurality of cells includes: acquiring first cell frame data and second cell frame data of each cell in a plurality of cells; the following operations are performed on the first cell border data and the second cell border data of each cell to obtain target border data of each cell: determining the union of the first frame data and the second frame data of the target cell as a target geographic area frame of the target cell; the target cell is any one of a plurality of cells.

In one possible implementation manner, determining the number of times the terminal device appears in each cell in a preset period of time based on the positions of the terminal device at a plurality of moments and the target geographical area borders of a plurality of cells includes: the following steps 1 to 3 are executed for each of the positions at a plurality of moments to obtain the number of times that the target terminal device appears in each cell in a preset time period; step 1, determining an ith cell as a sample cell from a plurality of cells; i is a positive integer; step 2, under a first preset condition, determining that the position of the terminal equipment at the target time is located in a sample cell, and updating the number of times of the target terminal equipment in the sample cell in a preset time period; wherein the first preset condition includes at least one of: the method comprises the steps that a target geographic area frame of a sample cell is abnormal data, the distance between a position point represented by a position at a target time and a central point of the sample cell is smaller than the minimum distance, the distance between the position point represented by the position at the target time and the central point of the sample cell is smaller than the maximum distance, the target geographic area frame of the sample cell is normal data, and the number of intersection points of a sample ray and the target geographic area frame of the sample cell is odd; the position point of the end point of the sample ray under the target time, and the direction of the sample ray is a preset direction; step 3, under a second preset condition, taking the (i+1) th cell as a sample cell, repeating the step 1, the step 2 and the step 3 until the position of the terminal equipment at the target time is determined to be positioned in the sample cell, and updating the frequency of the target terminal equipment in the sample cell in a preset time period; wherein the second preset condition includes at least one of: the method comprises the steps that when the distance between a position point represented by the position at the target moment and the center point of a sample cell is larger than or equal to the maximum distance, the border of the target geographic area of the sample cell is abnormal data, when the distance between the position point represented by the position at the target moment and the center point of the sample cell is larger than or equal to the minimum distance, the distance between the position point represented by the position at the target moment and the center point of the sample cell is smaller than the maximum distance, the border of the target geographic area of the sample cell is normal data, and the number of intersection points of sample rays and the border of the target geographic area of the sample cell is even.

In a second aspect, the present application provides a cell determining apparatus, the apparatus comprising: a processing unit; the processing unit is used for determining the positions of the target terminal equipment at a plurality of moments in a preset time period and the target geographic area frames of a plurality of cells; the target geographic area frame is determined based on first cell frame data and second cell frame data of the cell; the first cell frame data is a geographical area frame of the first cell in the map; the second cell frame data is a geographical area frame of the first cell, which is drawn based on a drawing tool; the processing unit is further used for determining the number of times of the target terminal equipment in each cell in a preset time period based on the positions of the target terminal equipment at a plurality of moments and the geographical area frames of a plurality of cells; the processing unit is further used for determining the cell with the frequency greater than or equal to a preset threshold value as a target cell of the target terminal equipment.

In one possible implementation, the apparatus further includes: a communication unit; a communication unit, configured to obtain measurement report MR data of a target terminal device at a plurality of moments; the processing unit is also used for inputting the MR data at a plurality of moments into a preset model to obtain the position of the target terminal equipment at the target moment; the preset model is trained based on MR data of the plurality of terminal devices and positions of the plurality of terminal devices.

In a possible implementation manner, the communication unit is further configured to obtain first cell border data and second cell border data of each cell in the plurality of cells; the processing unit is further configured to perform the following operations on the first cell border data and the second cell border data of each cell, so as to obtain target border data of each cell: determining the union of the first frame data and the second frame data of the target cell as a target geographic area frame of the target cell; the target cell is any one of a plurality of cells.

In a possible implementation manner, the processing unit is further configured to perform the following operations: the following steps 1 to 3 are executed for each of the positions at a plurality of moments to obtain the number of times that the target terminal device appears in each cell in a preset time period; step 1, determining an ith cell as a sample cell from a plurality of cells; i is a positive integer; step 2, under a first preset condition, determining that the position of the terminal equipment at the target time is located in a sample cell, and updating the number of times of the target terminal equipment in the sample cell in a preset time period; wherein the first preset condition includes at least one of: the method comprises the steps that a target geographic area frame of a sample cell is abnormal data, the distance between a position point represented by a position at a target time and a central point of the sample cell is smaller than the minimum distance, the distance between the position point represented by the position at the target time and the central point of the sample cell is smaller than the maximum distance, the target geographic area frame of the sample cell is normal data, and the number of intersection points of a sample ray and the target geographic area frame of the sample cell is odd; the position point of the end point of the sample ray under the target time, and the direction of the sample ray is a preset direction; step 3, under a second preset condition, taking the (i+1) th cell as a sample cell, repeating the step 1, the step 2 and the step 3 until the position of the terminal equipment at the target time is determined to be positioned in the sample cell, and updating the frequency of the target terminal equipment in the sample cell in a preset time period; wherein the second preset condition includes at least one of: the method comprises the steps that when the distance between a position point represented by the position at the target moment and the center point of a sample cell is larger than or equal to the maximum distance, the border of the target geographic area of the sample cell is abnormal data, when the distance between the position point represented by the position at the target moment and the center point of the sample cell is larger than or equal to the minimum distance, the distance between the position point represented by the position at the target moment and the center point of the sample cell is smaller than the maximum distance, the border of the target geographic area of the sample cell is normal data, and the number of intersection points of sample rays and the border of the target geographic area of the sample cell is even.

In a third aspect, the present application provides a cell determining apparatus, including: a processor and a communication interface; the communication interface is coupled to a processor for running a computer program or instructions to implement the cell determination method as described in any one of the possible implementations of the first aspect and the first aspect.

In a fourth aspect, the present application provides a computer readable storage medium having instructions stored therein which, when run on a terminal, cause the terminal to perform a cell determination method as described in any one of the possible implementations of the first aspect and the first aspect.

In a fifth aspect, the present application provides a computer program product comprising instructions which, when run on a cell determination apparatus, cause the cell determination apparatus to perform the cell determination method as described in any one of the possible implementations of the first aspect and the first aspect.

In a sixth aspect, the present application provides a chip comprising a processor and a communication interface, the communication interface and the processor being coupled, the processor being for running a computer program or instructions to implement a cell determination method as described in any one of the possible implementations of the first aspect and the first aspect.

In particular, the chip provided in the present application further includes a memory for storing a computer program or instructions.

The technical scheme at least brings the following beneficial effects: according to the cell determination method, the computing device determines the positions of the target terminal device at a plurality of moments in a preset time period and geographic area frames of a plurality of cells, determines the number of times of the target terminal device in each cell in the preset time period based on the positions of the target terminal device at the plurality of moments and the geographic area frames of the plurality of cells, and determines the cell with the highest number of times as the target cell of the target terminal device. The target geographic area frame recorded in the application is determined based on the first cell frame data (namely the geographic area frame of the first cell in the map) and the second cell frame data (namely the geographic area frame of the first cell drawn based on the drawing tool), the geographic area frame of the determined cell is closer to the actual geographic condition, and compared with the approximately circular frame determined based on the base station signal coverage range, the geographic area frame of the application can be more accurate, and the accuracy of determining the target cell (namely the resident cell) based on the geographic area frame is further improved.

Drawings

Fig. 1 is a block diagram of a communication system according to an embodiment of the present application;

fig. 2 is a flowchart of a method for determining a cell according to an embodiment of the present application;

FIG. 3 (a) is a schematic diagram of a target geographic area border according to an embodiment of the present disclosure;

FIG. 3 (b) is a schematic diagram of another target geographic area border provided in an embodiment of the present application;

fig. 4 is a schematic stage diagram of a cell determining method according to an embodiment of the present application;

fig. 5 is a flowchart of another method for determining a cell according to an embodiment of the present application;

fig. 6 is a schematic stage diagram of another method for determining a cell according to an embodiment of the present application;

fig. 7 is a flowchart of another method for determining a cell according to an embodiment of the present application;

FIG. 8 (a) is a schematic diagram illustrating a relative position of a frame according to an embodiment of the present disclosure;

FIG. 8 (b) is a schematic diagram illustrating another relative position of a frame according to an embodiment of the present disclosure;

fig. 9 is a flowchart of another method for determining a cell according to an embodiment of the present application;

fig. 10 is a flowchart of another method for determining a cell according to an embodiment of the present application;

fig. 11 is a flowchart of another method for determining a cell according to an embodiment of the present application;

FIG. 12 is a schematic diagram of a relative position of a sample ray and a side according to an embodiment of the present disclosure;

fig. 13 is a schematic stage diagram of another method for determining a cell according to an embodiment of the present application;

fig. 14 is a schematic structural diagram of a cell determining apparatus according to an embodiment of the present application;

fig. 15 is a schematic structural diagram of another cell determining apparatus according to an embodiment of the present application.

Detailed Description

The following describes in detail a cell determining method, a cell determining device and a storage medium provided in an embodiment of the present application with reference to the accompanying drawings.

The term "and/or" is herein merely an association relationship describing an associated object, meaning that there may be three relationships, e.g., a and/or B, may represent: a exists alone, A and B exist together, and B exists alone.

The terms "first" and "second" and the like in the description and in the drawings are used for distinguishing between different objects or for distinguishing between different processes of the same object and not for describing a particular sequential order of objects.

Furthermore, references to the terms "comprising" and "having" and any variations thereof in the description of the present application are intended to cover a non-exclusive inclusion. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those listed but may optionally include other steps or elements not listed or inherent to such process, method, article, or apparatus.

It should be noted that, in the embodiments of the present application, words such as "exemplary" or "such as" are used to mean serving as an example, instance, or illustration. Any embodiment or design described herein as "exemplary" or "for example" should not be construed as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "such as" is intended to present related concepts in a concrete fashion.

In the description of the present application, unless otherwise indicated, the meaning of "a plurality" means two or more.

As shown in fig. 1, fig. 1 shows a schematic structural diagram of a communication system according to an embodiment of the present application. The communication system includes: a computing device 101 and a terminal device 102.

The computing device 101 is configured to determine a location of the target terminal device at a plurality of times within a preset time period, and a target geographical area border of the plurality of cells, determine a 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 the plurality of times and the geographical area border of the plurality of cells, and determine a cell with a number of times greater than or equal to a preset threshold as a target cell of the target terminal device.

The target geographic area frame is determined based on first cell frame data and second cell frame data of the cells; the first cell frame data is a geographical area frame of the first cell in the map; the second cell frame data is a geographical area frame of the first cell, which is drawn based on a drawing tool;

a terminal device 102 for providing measurement report (Measurement Report, MR) data for determining a position to the computing device 101.

The terminal device 102 is a device with a wireless communication function, and may be deployed on land, including indoor or outdoor, hand-held or vehicle-mounted, or on water (e.g., a ship, etc.). But may also be deployed in the air (e.g., on aircraft, balloon, satellite, etc.).

In some examples, the terminal device 102, also referred to as a User Equipment (UE), a Mobile Station (MS), a Mobile Terminal (MT), a terminal, etc., is a device that provides voice and/or data connectivity to a user. For example, the terminal device 102 includes a handheld device, an in-vehicle device, and the like having a wireless connection function. Currently, the terminal device 102 may be: a mobile phone, a tablet, a laptop, a palmtop, a mobile internet device (mobile internet device, MID), a wearable device (e.g., a smartwatch, a smartband, a pedometer, etc.), a vehicle-mounted device (e.g., an automobile, a bicycle, an electric car, an airplane, a ship, a train, a high-speed rail, etc.), a Virtual Reality (VR) device, an augmented reality (augmented reality, AR) device, a wireless terminal in an industrial control (industrial control), a smart home device (e.g., a refrigerator, a television, an air conditioner, an electric meter, etc.), a smart robot, a workshop device, a wireless terminal in a drone (self driving), a wireless terminal in a teleoperation (remote medical surgery), a wireless terminal in a smart grid (smart grid), a wireless terminal in a transportation security (transportation safety), a wireless terminal in a smart city (smart city), or a wireless terminal in a smart home (smart home), a flying device (e.g., a smart robot, a hot balloon, an airplane, etc. In one possible application scenario, the terminal device is a terminal device that is often operated on the ground, for example a vehicle-mounted device. In this application, for convenience of description, chips disposed in the above devices, such as a System-On-a-Chip (SOC), a baseband Chip, etc., or other chips having a communication function may also be referred to as a terminal device 102.

Alternatively, the terminal device 102 may be an embedded communication device, or may be a handheld communication device of a user, including a mobile phone, a tablet computer, etc.

As an example, in the embodiment of the present application, the terminal device 102 may also be a wearable device. The wearable device can also be called as a wearable intelligent device, and is a generic name for intelligently designing daily wear by applying wearable technology and developing wearable devices, such as glasses, gloves, watches, clothes, shoes and the like. The wearable device is a portable device that is worn directly on the body or integrated into the clothing or accessories of the user. The wearable device is not only a hardware device, but also can realize a powerful function through software support, data interaction and cloud interaction. The generalized wearable intelligent device includes full functionality, large size, and may not rely on the smart phone to implement complete or partial functionality, such as: smart watches or smart glasses, etc., and focus on only certain types of application functions, and need to be used in combination with other devices, such as smart phones, for example, various smart bracelets, smart jewelry, etc. for physical sign monitoring.

Alternatively, fig. 1 is only an exemplary frame diagram, and the number of nodes included in fig. 1 is not limited, and other nodes may be included in addition to the functional nodes shown in fig. 1, for example: access network device 103, etc., to which the present application is not limited in any way.

The access network device 103 is a device located at the access network side of the communication system 100 and having a wireless transceiver function or a chip system that can be disposed in the device. Access network devices 103 include, but are not limited to: an Access Point (AP) in a WiFi system, such as a home gateway, a router, a server, a switch, a bridge, etc., an evolved NodeB (eNB), a radio network controller (radio network controller, RNC), a NodeB (NB), a base station controller (base station controller, BSC), a base transceiver station (base transceiver station, BTS), a home base station (e.g., home evolved NodeB, or home NodeB, HNB), a Base Band Unit (BBU), a radio relay node, a radio backhaul node, a transmission point (transmission and reception point, TRP, transmission point, TP), etc., may also be a 5G base station, such as a gNB in a new air interface (new radio, NR) system, or a transmission point (TRP, TP), an antenna panel or a group of base stations in a 5G system (including multiple antenna panels), or may also be a network node constituting a gNB or a transmission point, such as a Base Band Unit (BBU), or a distributed unit (distributed unit), a base station having a roadside unit (RSU), an access network (RSU), a base station-side unit (RSU), or a service node (RSU), etc. The access network device 103 further includes base stations in different networking modes, such as a master enhanced NodeB (MeNB), a secondary eNB (SeNB), or a secondary gNB (SgNB). The access network equipment 103 also includes different types, such as ground base stations, air base stations, satellite base stations, and the like.

In addition, the communication system described in the embodiments of the present application is for more clearly describing the technical solution of the embodiments of the present application, and does not constitute a limitation on the technical solution provided in the embodiments of the present application, and as a person of ordinary skill in the art can know, with evolution of the network architecture and appearance of a new communication system, the technical solution provided in the embodiments of the present application is equally applicable to similar technical problems.

In order to solve the problems in the prior art, the embodiment of the application provides a cell determining method, which can improve the accuracy of the determined resident cell of the user equipment. As shown in fig. 2, the method includes:

and S201, the computing equipment determines the positions of the target terminal equipment at a plurality of moments in a preset time period and the target geographic area frames of a plurality of cells.

The target geographic area border is determined based on the first cell border data and the second cell border data of the cell. The first cell border data is a geographical area border of the first cell in the map. The second cell border data is a geographical area border of the first cell drawn based on the drawing tool.

For example, the preset time period may be 0:00 to 6: 00. 21:00 to 24:00.

as an optional implementation manner, the implementation process of determining, by the computing device in S201, the position of the target terminal device at a plurality of moments within the preset time period may be: the computing device may first acquire MR data of the target terminal device at each of the plurality of moments from the network management device side, and input the MR data into a preset model to obtain a position of the target terminal device at each moment.

As a possible implementation manner, the implementation process of determining, by the computing device, the target geographic area borders of the plurality of cells in S201 may be: the computing equipment firstly determines first frame data and second frame data of a target cell, and determines the union of the first frame data and the second frame data as a target geographic area frame of the target cell. Wherein the target cell is any one of the plurality of cells. The computing device may determine a target geographic area border for each of the plurality of cells based on the method.

By way of example, fig. 3 (a) shows an example of a target geographic area border for cell # 1. Fig. 3 (b) shows an example of the target geographical area border of cell # 2.

S202, the computing device determines the number of times that the target terminal device appears in each cell in a preset time period based on the positions of the target terminal device at a plurality of moments and the geographical area borders of a plurality of cells.

As an alternative implementation manner, the implementation process of S202 may be: the computing equipment firstly determines the cell in which the position under the target time is located, and adds 1 on the basis of the number of times that the original target terminal equipment appears in each cell until the computing equipment finishes determining the cell in which the position under the multiple times is located, and then the number of times that the target terminal equipment appears in each cell in the multiple cells in a preset time period is obtained.

S203, the computing device determines that the cell with the frequency greater than or equal to the preset threshold value is the target cell of the target terminal device.

As an alternative implementation manner, the implementation process of S203 may be: the computing equipment sorts the times of the occurrence of the target terminal equipment in the cells from large to small in a preset time period to obtain a time sequence, and determines the largest cell in the time sequence as the target cell of the target terminal equipment. In this case, the preset threshold is the number of times the target terminal device appears in the target cell within a preset period of time.

In one possible implementation manner, if the preset time period is in granularity of month, the computing device may further split the number of times to obtain a frequency of days (days_ratio) of the occurrence of the target terminal device in the current cell and a frequency of times (cnt_ratio) of the occurrence of the target terminal device in the current cell. Then, the computing device may perform weighted summation on the above-mentioned data_ratio and cnt_ratio to obtain an MR positioning confidence (which may also be referred to as accuracy), and determine the cell with the greatest MR positioning confidence as the target cell of the target terminal device.

In an alternative implementation, the MR positioning confidence may satisfy the following equation 1:

mr_score=day_ratio 0.6+cnt_ratio 0.4 equation 1

Wherein mr_score is MR positioning confidence.

Alternatively, as shown in table 1 below, the computing device may record information such as MR positioning confidence in the form of a table. Table 1 below may include at least one of the following: city name (city_name), broadband cell standard address name (comm_name), number (msisdn), handling broadband possibility (pres), number of cell coverage building (nbr_building), number of coverage users (nbr_cover_user), number of ports (nbr_inter), number of network users (nbr_network_user), port occupancy (rate_permeate), access mode (inter_type), construction mode (construct_desc), whether MR positioning (if_mr), build-in-service time (date_status), MR positioning confidence (mr_score), broadband cell standard address identification (comm_id), city (city), whether weekend (is_weekend), ranking of the cell at the MR positioning of the user (ore_row_number), preset time period (mol).

TABLE 1

Alternatively, as shown in fig. 4, the method for determining a cell provided in the embodiment of the present application may be divided into the following three stages: a data processing stage, a positioning algorithm stage, and a deployment stage. In the data processing stage, the computing device may acquire MR data of the target terminal device at a plurality of times, and cell border data (i.e., including the first border data and/or the second border data) of a plurality of cells. In the positioning algorithm stage, a computing device needs a user cell identification algorithm to determine cells in which the target terminal device is located at different moments, integrates the cells in which the target terminal device is located at different moments based on a distance rule algorithm to obtain the number of times and the number of days of the occurrence of the target terminal device in each cell, performs weighted summation on the number of times and the number of days to obtain MR positioning confidence, and determines the target cell based on the MR positioning confidence. In the deployment node, the computing device may perform deployment optimization on the algorithms and/or data described in the positioning algorithms described above.

In an alternative embodiment, as shown in S201, the computing device determines the location of the target terminal device at a plurality of moments in a preset time period, and on the basis of the embodiment of the method shown in fig. 2, this embodiment provides a possible implementation, as shown in fig. 5, fig. 5 is a flowchart of another cell determining method provided in the present application, and the process of determining, by the computing device, the location of the target terminal device at a plurality of moments in the preset time period may include the following steps S501 to S502.

S501, the computing device acquires MR data of the target terminal device at a plurality of moments.

As a possible implementation manner, the implementation process of S501 may be: since the target terminal device periodically reports the MR data to the network management device, the network management device periodically receives the MR data from the target terminal device and stores the MR data. The computing device may then send a request message to the network management device requesting MR data of the target terminal device at a plurality of times. After the network management equipment receives the request message, the network management equipment sends MR data of the target terminal equipment at a plurality of moments to the computing equipment, and correspondingly, the computing equipment receives the MR data of the target terminal equipment from the network management equipment at the plurality of moments.

S502, the computing device inputs the MR data into a preset model to obtain the position of the target terminal device at the target time.

The preset model is obtained through training according to MR data of a plurality of terminal devices and positions of the plurality of terminal devices.

Alternatively, the above-mentioned positions may be represented by warp and weft. The computing device may perform data preprocessing on the longitude and latitude, that is, take five bits after the longitude and latitude decimal point (the longitude and latitude is not null and is not zero), so that 6 bits of longitude and latitude are aggregated into 5 bits of longitude and latitude.

In an alternative implementation, as shown in fig. 6, the process of determining the preset model by the computing device may be implemented in the following steps 1 to 5.

Step 1, a computing device collects minimization of drive tests (Minimization Drive Test, MDT) data of a plurality of terminal devices.

The MDT data may include index data and a location of the terminal device.

Optionally, the index data is the same as part of the MR data.

And 2, preprocessing MDT data of the plurality of terminal devices by the computing device.

Illustratively, the preprocessing may include at least one of: exploratory analysis processing, data cleansing processing, data conversion processing, and specification management processing.

Alternatively, the foregoing is merely exemplary of the pretreatment, and the pretreatment may further include other treatments, which are not limited in any way in the present application.

And 3, dividing MDT data of a plurality of terminal devices into a training set and a testing set by the computing device, and carrying out xgboost regression model training on the initial model based on the training set to obtain a trained initial model.

And 4, testing the trained initial model by the computing equipment based on the test set to obtain a test result.

The test result is used for representing the accuracy of the initial model after training.

And 5, evaluating whether the trained initial model meets the preset requirement or not by the computing equipment model based on the test result.

Alternatively, the predetermined requirement may be that the test result is greater than or equal to the model threshold (e.g., 95%).

If the trained initial model meets the preset requirement, the computing equipment executes step 6.

And 6, the computing equipment determines the trained initial model as a preset model.

If the trained initial model does not meet the preset requirement, the computing device executes step 7.

And 7, the computing equipment adjusts parameters of the trained initial model, takes the adjusted initial model as the initial model in the step 3, and repeatedly executes the steps 3 to 7 until a test result meets a preset requirement.

The technical scheme at least brings the following beneficial effects: according to the cell determination method, the computing device acquires measurement report MR data of the target terminal device at a plurality of moments, the MR data at the moments are input into the preset model (namely, the MR data are obtained according to the MR data of the terminal devices and the position training of the terminal devices), the position of the target terminal device at the target moment is obtained, and therefore the position determined based on the preset model has higher accuracy, and a data basis is provided for the subsequent computing device to determine the number of times that the target terminal device appears in each cell in a preset time period based on the position.

In an alternative embodiment, as shown in S201, the computing device determines the target geographical area borders of the plurality of cells, and on the basis of the method embodiment shown in fig. 5, this embodiment provides a possible implementation, as shown in fig. 7, fig. 7 is a flowchart of another cell determining method provided in the present application, where the process of determining the target geographical area borders of the plurality of cells by the computing device may include the following steps S701 to S702.

S701, the computing device obtains first cell border data and second cell border data of each of the plurality of cells.

As an alternative implementation manner, the implementation process of S701 may be: the computing device obtains information of a plurality of first cell frame data and information of a plurality of second cell frame data, and then performs fuzzy matching based on the information of the first cell frame data of a target cell (namely any one of the cells) and the information of the plurality of second cell frame data, so as to determine the second cell frame data corresponding to the first cell frame data of the target cell. The information may include at least one of: broadband standard address, and identification. The cell border data pair comprises a first cell border data and a second cell border data. The computing device determines first cell border data and second cell border data for each of the plurality of cells based on the method.

Optionally, if the first cell border data or the second cell border data has an anomaly (for example, overlapping coverage anomaly), the computing device may process the first cell border data and the second cell border data that have an anomaly through an arcgis tool.

S702, the computing device performs the following operations on the first cell border data and the second cell border data of each cell to obtain target border data of each cell: and determining the union of the first frame data and the second frame data of the target cell as the target geographic area frame of the target cell.

Wherein the target cell is any one of a plurality of cells.

As a possible implementation manner, the implementation process of S702 may be: the computing device may combine the first frame data and the second cell frame data through an arcgis tool to obtain a union of the first frame data and the second cell frame data, and determine the union as a target geographic area frame of the target cell.

Optionally, as shown in fig. 8 (a), when there is an overlap between the first frame data and the second cell border data, the computing device may delete a portion of the second border data overlapping the first frame data through spatial link deduplication in the arcgis tool, and merge the first border data and the deduplicated second border data by the merge tool, to obtain a union of the first border data and the second cell border data (for example, a union #1 in fig. 8 (a)), and determine that the union is a target geographic area border of the target cell.

Alternatively, as shown in fig. 8 (b), in the case where there is no overlap between the first frame data and the second cell border data, the computing device may directly determine the first frame data and the second cell border data as the target geographical area border of the target cell (e.g., union #2 in fig. 8 (b)).

The technical scheme at least brings the following beneficial effects: according to the cell determination method, the computing device acquires the first cell frame data and the second cell frame data of each cell in the plurality of cells, and performs the following operations on the first cell frame data and the second cell frame data of each cell to obtain target frame data of each cell: a union of the first and second cell border data of the target cell (i.e., any one of the plurality of cells) is determined as a target geographic region border of the target cell. Based on the above, the target geographic area frame of the present application is determined based on the first cell frame data of the cell (i.e., the geographic area frame of the first cell in the map) and the second cell frame data (i.e., the geographic area frame of the first cell drawn based on the drawing tool), so that the determined geographic area frame of the cell is closer to the actual geographic situation, and compared with the approximately circular frame determined based on the signal coverage of the base station, the geographic area frame of the present application can be more accurate, and provides a data basis with higher accuracy for the subsequent computing device to determine the target cell (i.e., the resident cell) based on the geographic area frame.

In an alternative embodiment, as shown in S202, the computing device determines, based on the location of the target terminal device at a plurality of moments and the geographical area borders of a plurality of cells, the number of times the target terminal device appears in each cell in a preset time period, and on the basis of the method embodiment shown in fig. 2, this embodiment provides a possible implementation, as shown in fig. 9, fig. 9 is a flowchart of another cell determination method provided in this application, and the computing device performs the following S901 to S903 on the location of the target terminal device at each moment in the locations of the target terminal device at the plurality of moments, so as to obtain the number of times the target terminal device appears in each cell in the preset time period.

S901, the computing device determines an i-th cell from the plurality of cells as a sample cell.

Wherein i is a positive integer.

Alternatively, the number of the plurality of cells may be determined by the computing device according to the actual situation, which is not limited in this application.

S902, under a first preset condition, the computing device determines a sample cell to which the position of the terminal device at the target time belongs, and updates the number of times that the target terminal device appears in the sample cell in a preset time period.

Wherein the first preset condition includes at least one of: the method comprises the steps that the geographical area frame of a sample cell is abnormal data, the distance between a position point represented by a position at a target time and the center point of the sample cell is smaller than the minimum distance, the distance between the position point represented by the position at the target time and the center point of the sample cell is smaller than the maximum distance, the geographical area frame of the sample cell is normal data, and the number of intersection points of sample rays and the geographical area frame of the sample cell is odd. The end point of the sample ray is a position point under the target time, and the direction of the sample ray is a preset direction.

And S903, under the second preset condition, the computing device takes the (i+1) th cell as a sample cell, repeatedly executes S901 to S903 until the sample cell to which the position of the terminal device at the target time belongs is determined, and updates the number of times of the target terminal device in the sample cell in a preset time period.

Wherein the second preset condition includes at least one of: the method comprises the steps that when the distance between a position point represented by the position at the target time and the center point of a sample cell is larger than or equal to the maximum distance, the geographical area frame of the sample cell is abnormal data, when the distance between the position point represented by the position at the target time and the center point of the sample cell is larger than or equal to the minimum distance, the distance between the position point represented by the position at the target time and the center point of the sample cell is smaller than the maximum distance, the geographical area frame of the sample cell is normal data, and the number of intersection points of sample rays and the geographical area frame of the sample cell is even.

As an alternative implementation manner, as shown in fig. 10, the implementation procedure of S902 to S903 may be: and the computing equipment determines the target geographical area border of the cells as a cell border configuration file, and initializes the cell border configuration file.

The computing device may then determine the location at the target time from the locations at the multiple times, and determine information about the city, maximum distance, minimum distance, etc., where the target terminal device is located.

Still further, the computing device may perform the following operations on the sample cell to determine whether the location of the target location is located in the sample cell: first determining that a distance between a location point characterized by the location of the target location and a center point of the sample cell is less than a maximum distance, and if the distance between the location point characterized by the location of the target location and the center point of the sample cell is the maximum distance, the computing device further determines whether a target geographic area border of the sample cell is abnormal (e.g., empty).

If the target geographical area frame of the sample cell is abnormal, under the condition that the distance between the position point represented by the position of the target position and the central point of the sample cell is smaller than the minimum distance, the computing device determines that the position of the terminal device at the target moment is positioned in the sample cell, and updates the frequency of the occurrence of the target terminal device in the sample cell in a preset time period; and under the condition that the distance between the position point represented by the position of the target position and the center point of the sample cell is larger than or equal to the minimum distance, determining that the position of the terminal equipment at the target time is not located in the sample cell, taking the (i+1) th cell as the sample cell, repeatedly executing the judging process until the sample cell to which the position of the terminal equipment at the target time belongs is determined, and updating the frequency of the target terminal equipment in the sample cell in a preset time period.

If the target geographical area frame of the sample cell is normal, the computing device determines whether the position of the terminal device at the target time belongs to the sample cell or not based on a ray method.

Optionally, as shown in fig. 11, the implementation process of determining, by the computing device, whether the location of the terminal device at the target time belongs to the sample cell based on the radiation method may be: the computing device determines data of a plurality of edges from a target geographic area frame of a target cell, and takes the position of a target terminal device under a target time as an endpoint, and takes a right horizontal direction as a preset direction as a ray (namely a sample ray).

Then, the computing device determines whether the sample ray intersects the target edge (i.e., any edge of the plurality of edges) first, until the number of intersection points between the sample ray and the plurality of edges is counted after each edge of the plurality of edges is judged based on the method.

Finally, the computing equipment determines whether the number of the intersection points of the sample rays and the edges is odd, and if the number of the intersection points of the sample rays and the edges is odd, the computing equipment determines a sample cell to which the position of the terminal equipment at the target time belongs; if the number of the intersection points of the sample ray and the plurality of edges is not odd (i.e., the number of the intersection points of the sample ray and the plurality of edges is even), the computing device determines that the position of the terminal device at the target time does not belong to the sample cell, and uses the (i+1) th cell as the sample cell, and repeatedly executes the determining process until the position of the terminal device at the target time is determined to belong to the sample cell.

Alternatively, as shown in FIG. 12, where the parallel, overlapping, line segment length is 0, and the sample ray intersects only the next breakpoint of the edge, the computing device may determine that the sample ray does not intersect the target edge.

Optionally, the number of times that the target terminal device appears in each cell in the preset time period may be listed in a table, so as to be capable of more intuitively acquiring information. The above-mentioned preset period of time may be divided into the following two cases: in case 1, the preset time period takes days as granularity; and 2, taking the month as granularity in the preset time period. In the case where the granularity of the preset time period is different, the expression form of the table is also different. Tables for the above two cases are described below.

In case 1, the preset time period takes days as granularity.

In case 1, the expression of the above table can be shown in the following table 2. The following table 2 may include: a mobile phone number (msisdn), a city name (city_name), a user longitude (longitude), a user latitude (latitude), a home broadband cell standard address (comm_id), a number of times a target terminal device is present in each cell (cnt_day), whether or not a weekend (is_weekend), and a preset time period (day).

TABLE 2

And 2, taking the month as granularity in the preset time period.

In case 2, the expression of the above table can be shown in the following table 3. The following table 3 may include: a mobile phone number (msisdn), a broadband cell standard address identification (comm_id), a number of times the target terminal device appears in each cell (cnt_each), a sum of times the target terminal device appears in each cell (sum_cnt), a frequency of times the target terminal device appears in each cell (cnt_ratio), a number of days the target terminal device appears in each cell (days_each), a sum of days the target terminal device appears in each cell (days), a frequency of days the target terminal device appears in each cell (days_ratio), whether a weekend (is_weekend), and a time (day).

TABLE 3 Table 3

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As can be seen from table 3, the frequency of the occurrence of the target terminal device in each cell is the ratio of the occurrence of the target terminal device in each cell to the sum of the occurrence of the target terminal device in each cell. The frequency of the number of days of the target terminal equipment in each cell is the ratio of the number of days of the target terminal equipment in each cell and the sum of the number of days of the target terminal equipment in each cell.

Optionally, the expression form of the table may be further refined along with the change of the scene, for example, a workday scene, a weekend scene, and a scene of some specific period, and the computing device may flexibly configure the table according to the actual requirement for the business scene.

Optionally, the table may further include information of cell broadband resources, for example, broadband resource port occupancy rate, broadband build time, broadband user number, building number, etc., where the cell broadband resource information may provide more comprehensive and accurate data basis for wireless optimization and broadband planning construction of operators.

The technical scheme at least brings the following beneficial effects: according to the cell determination method provided by the application, the computing equipment executes the following steps 1 to 3 on the position under each time in the positions under a plurality of times so as to obtain the cell to which the position under each time belongs: the computing device may determine that an i-th cell is a sample cell from the multiple cells, determine, under a first preset condition, a sample cell to which a position of the terminal device at the target time belongs, and repeatedly execute the above process with the i+1th cell as the sample cell under a second preset condition until it is determined that the position of the terminal device at the target time belongs to the sample cell. The computing device may then count the number of times the target terminal device appears in each cell within a preset period of time based on the cell to which the location at each time belongs, which may provide a data basis for subsequent computing devices to determine the target cell based on the number of times.

Alternatively, as shown in fig. 13, the cell determining method provided in the embodiment of the present application may be divided into the following three stages: an input data phase, an algorithm phase, an output data node, and an algorithm verification phase. In the input data node, the computing device may determine a location of the target terminal device at a plurality of times, a city, cell border data (i.e., the first cell border data and/or the second cell border data), a maximum distance, and a minimum distance. In the algorithm stage, the computing device may determine the number of times the target terminal device appears in each cell within a preset period of time based on the user cell identification algorithm, the big data rule model modeling, and the user resident cell location algorithm. In the output data phase, the computing device may determine the target cell based on the number of times the target terminal device appears in each cell within the above-described preset period of time. In the algorithm verification phase, the computing device may evaluate the big data rule model and optimize the big data rule model.

It will be appreciated that the above-described cell determination method may be implemented by a cell determination device. The cell determining device comprises a hardware structure and/or a software module corresponding to each function for realizing the functions. Those of skill in the art will readily appreciate that the various illustrative modules and algorithm steps described in connection with the embodiments disclosed herein may be implemented as hardware or combinations of hardware and computer software. Whether a function is implemented as hardware or computer software driven hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the disclosed embodiments.

The embodiment of the disclosure may divide the functional modules according to the cell determining apparatus generated by the above method example, for example, each functional module may be divided corresponding to each function, or two or more functions may be integrated into one processing module. The integrated modules may be implemented in hardware or in software functional modules. It should be noted that, in the embodiment disclosed in the present application, the division of the modules is merely a logic function division, and other division manners may be implemented in actual practice.

Fig. 14 is a schematic structural diagram of a cell determining apparatus according to an embodiment of the present invention. As shown in fig. 14, the cell determining device 140 may be configured to perform the cell determining methods shown in fig. 2, 5, 7, and 9. The cell determination device 140 includes: a processing unit 1401.

A processing unit 1401, configured to determine positions of a target terminal device at a plurality of moments in a preset time period, and target geographical area borders of a plurality of cells; the target geographic area frame is determined based on first cell frame data and second cell frame data of the cell; the first cell frame data is a geographical area frame of the first cell in the map; the second cell frame data is a geographical area frame of the first cell, which is drawn based on a drawing tool; the processing unit 1401 is further configured to determine, based on the positions of the target terminal device at a plurality of moments and the geographical area borders of a plurality of cells, the number of times that the target terminal device appears in each cell in a preset time period; the processing unit 1401 is further configured to determine a cell with a number of times greater than or equal to a preset threshold as a target cell of the target terminal device.

In one possible implementation, the apparatus further includes: a communication unit 1402; a communication unit 1402, configured to obtain measurement report MR data of a target terminal device at a plurality of times; the processing unit 1401 is further configured to input MR data at a plurality of moments into a preset model, so as to obtain a position of the target terminal device at the target moment; the preset model is trained based on MR data of the plurality of terminal devices and positions of the plurality of terminal devices.

In a possible implementation manner, the communication unit 1402 is further configured to obtain first cell border data and second cell border data of each of the plurality of cells; the processing unit 1401 is further configured to perform the following operations on the first cell border data and the second cell border data of each cell, so as to obtain target border data of each cell: determining the union of the first frame data and the second frame data of the target cell as a target geographic area frame of the target cell; the target cell is any one of a plurality of cells.

In a possible implementation manner, the processing unit 1401 is further configured to perform the following operations: the following steps 1 to 3 are executed for each of the positions at a plurality of moments to obtain the number of times that the target terminal device appears in each cell in a preset time period; step 1, determining an ith cell as a sample cell from a plurality of cells; i is a positive integer; step 2, under a first preset condition, determining that the position of the terminal equipment at the target time is located in a sample cell, and updating the number of times of the target terminal equipment in the sample cell in a preset time period; wherein the first preset condition includes at least one of: the method comprises the steps that a target geographic area frame of a sample cell is abnormal data, the distance between a position point represented by a position at a target time and a central point of the sample cell is smaller than the minimum distance, the distance between the position point represented by the position at the target time and the central point of the sample cell is smaller than the maximum distance, the target geographic area frame of the sample cell is normal data, and the number of intersection points of a sample ray and the target geographic area frame of the sample cell is odd; the position point of the end point of the sample ray under the target time, and the direction of the sample ray is a preset direction; step 3, under a second preset condition, taking the (i+1) th cell as a sample cell, repeating the step 1, the step 2 and the step 3 until the position of the terminal equipment at the target time is determined to be positioned in the sample cell, and updating the frequency of the target terminal equipment in the sample cell in a preset time period; wherein the second preset condition includes at least one of: the method comprises the steps that when the distance between a position point represented by the position at the target moment and the center point of a sample cell is larger than or equal to the maximum distance, the border of the target geographic area of the sample cell is abnormal data, when the distance between the position point represented by the position at the target moment and the center point of the sample cell is larger than or equal to the minimum distance, the distance between the position point represented by the position at the target moment and the center point of the sample cell is smaller than the maximum distance, the border of the target geographic area of the sample cell is normal data, and the number of intersection points of sample rays and the border of the target geographic area of the sample cell is even.

In case of implementing the functions of the above integrated modules in the form of hardware, an embodiment of the present invention provides a possible structural schematic diagram of the cell determining apparatus referred to in the above embodiment. As shown in fig. 15, a cell determining apparatus 150 is used, for example, to perform the cell determining methods shown in fig. 2, 5, 7, and 9. The cell determination device 150 includes a processor 1501, a memory 1502, and a bus 1503. The processor 1501 and the memory 1502 may be connected by a bus 1503. Optionally, the cell determination device 150 may further include a communication interface 1504.

The processor 1501 is a control center of the user equipment, and may be one processor or a collective term of a plurality of processing elements. For example, the processor 1501 may be a general-purpose central processing unit 1502 (central processing unit, CPU), or may be other general-purpose processors. Wherein the general purpose processor may be a microprocessor or any conventional processor or the like. As an example, in connection with fig. 14, the processing unit 1401 in the cell determination device realizes the same function as the processor 1501 in fig. 15.

The processor 1501 may include one or more CPUs, for example, CPU0 and CPU 1, as an embodiment.

The memory 502 may be, but is not limited to, a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (random access memory, RAM) or other type of dynamic storage device that can store information and instructions, or an electrically erasable programmable read-only memory (electrically erasable programmable read-only memory, EEPROM), magnetic disk storage or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.

As a possible implementation, the memory 1502 may exist separately from the processor 1501, and the memory 1502 may be connected to the processor 1501 through the bus 1503 for storing instructions or program code. The processor 1501, when calling and executing instructions or program code stored in the memory 1502, can implement the map plotting method provided by the embodiment of the present invention. In another possible implementation, the memory 1502 may also be integrated with the processor 1501.

Bus 1503 may be an industry standard architecture (Industry Standard Architecture, ISA) bus, a peripheral component interconnect (Peripheral Component Interconnect, PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, among others. The bus may be classified as an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in fig. 15, but not only one bus or one type of bus.

A communication interface 1504 for connecting with other devices via a communication network. The communication network may be an ethernet, a radio access network, a wireless local area network (wireless local area networks, WLAN), etc. The communication interface 1504 may include a communication unit 1402 for receiving data. In one design, the communication interface may also be integrated into the processor in the cell determination device 150 provided in an embodiment of the present invention.

It should be noted that the structure shown in fig. 15 does not constitute a limitation of the cell determination device 150. The cell determination means 150 may comprise more or less components than shown in fig. 15, or may combine certain components, or a different arrangement of components.

From the foregoing description of the embodiments, it will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of functional modules is illustrated, and in practical application, the above-described functional allocation may be implemented by different functional modules according to needs, i.e. the internal structure of the apparatus is divided into different functional modules to implement all or part of the functions described above. The specific working processes of the above-described systems, devices and units may refer to the corresponding processes in the foregoing method embodiments, which are not described herein.

The computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access Memory (Random Access Memory, RAM), a Read-Only Memory (ROM), an erasable programmable Read-Only Memory (Erasable Programmable Read Only Memory, EPROM), a register, a hard disk, an optical fiber, a portable compact disc Read-Only Memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing, or any other form of computer readable storage medium known in the art. An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an application specific integrated circuit (Application Specific Integrated Circuit, ASIC). In the context of the present application, a computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

The foregoing is merely a specific embodiment of the present application, but the protection scope of the present application is not limited thereto, and any changes or substitutions within the technical scope of the present disclosure should be covered in the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A method for determining a cell, comprising:

determining the positions of target terminal equipment at a plurality of moments in a preset time period and target geographic area frames of a plurality of cells; the target geographic area border is determined based on first cell border data and second cell border data of the cell; the first cell frame data is a geographic area frame of the first cell in a map; the second cell frame data is a geographical area frame of the first cell, which is drawn based on a drawing tool;

determining the number of times of the target terminal equipment in each cell in the preset time period based on the positions of the target terminal equipment at a plurality of moments and the geographical area frames of a plurality of cells;

and determining the cells with the times greater than or equal to a preset threshold value as target cells of the target terminal equipment.

2. The method according to claim 1, wherein determining the location of the target terminal device at a plurality of moments within a preset time period comprises:

acquiring measurement report MR data of the target terminal equipment at the plurality of moments;

inputting the MR data at the multiple moments into a preset model to obtain the positions of the target terminal equipment at the target moments; the preset model is obtained by training according to MR data of a plurality of terminal devices and positions of the plurality of terminal devices.

3. The method of claim 1, wherein determining target border data for a plurality of cells comprises:

acquiring first cell frame data and second cell frame data of each cell in the plurality of cells;

the first cell border data and the second cell border data of each cell are executed as follows, so as to obtain target border data of each cell: determining that the union of the first frame data of the target cell and the second cell frame data is the target geographic area frame of the target cell; the target cell is any one of the plurality of cells.

4. A method according to any one of claims 1-3, wherein said determining the number of times a terminal device is present in each cell during said preset time period based on the location of said terminal device at a plurality of times and the target geographical area borders of a plurality of cells comprises:

the following steps 1 to 3 are executed for the position under each time in the positions under the multiple times, so as to obtain the number of times that the target terminal device appears in each cell in the preset time period;

step 1, determining an ith cell as a sample cell from the cells; i is a positive integer;

step 2, under a first preset condition, determining that the position of the terminal equipment at the target time is located in the sample cell, and updating the frequency of the target terminal equipment in the sample cell in the preset time period;

wherein the first preset condition includes at least one of: the method comprises the steps that a target geographic area frame of a sample cell is abnormal data, the distance between a position point represented by a position at a target time and a central point of the sample cell is smaller than the minimum distance, the distance between a position point represented by the position at the target time and the central point of the sample cell is smaller than the maximum distance, the target geographic area frame of the sample cell is normal data, and the number of intersection points of sample rays and the target geographic area frame of the sample cell is odd; the position point of the end point of the sample ray under the target time, and the direction of the sample ray is a preset direction;

Step 3, in a second preset condition, taking the (i+1) th cell as the sample cell, and repeatedly executing the step 1, the step 2 and the step 3 until the position of the terminal equipment at the target time is determined to be positioned in the sample cell, and updating the frequency of the target terminal equipment in the sample cell in the preset time period;

wherein the second preset condition includes at least one of: the method comprises the steps of determining that a distance between a position point represented by a position at a target time and a central point of a sample cell is larger than or equal to a maximum distance, determining that a target geographic area frame of the sample cell is abnormal data, determining that a distance between the position point represented by the position at the target time and the central point of the sample cell is larger than or equal to a minimum distance, determining that a distance between the position point represented by the position at the target time and the central point of the sample cell is smaller than the maximum distance, determining that the target geographic area frame of the sample cell is normal data, and determining that the number of intersection points of sample rays and the target geographic area frame of the sample cell is even.

5. A cell determining apparatus, comprising: a processing unit;

The processing unit is used for determining the positions of the target terminal equipment at a plurality of moments in a preset time period and the target geographic area frames of a plurality of cells; the target geographic area border is determined based on first cell border data and second cell border data of the cell; the first cell frame data is a geographic area frame of the first cell in a map; the second cell frame data is a geographical area frame of the first cell, which is drawn based on a drawing tool;

the processing unit is further configured to determine the number of times that the target terminal device appears in each cell in the preset time period based on the positions of the target terminal device at a plurality of moments and geographic area borders of a plurality of cells;

the processing unit is further configured to determine that the cell with the number of times greater than or equal to a preset threshold is the target cell of the target terminal device.

6. The apparatus of claim 5, wherein the apparatus further comprises: a communication unit;

the communication unit is used for acquiring measurement report MR data of the target terminal equipment at the plurality of moments;

the processing unit is further configured to input the MR data at the multiple times into a preset model, so as to obtain a position of the target terminal device at the target time; the preset model is obtained by training according to MR data of a plurality of terminal devices and positions of the plurality of terminal devices.

7. The apparatus of claim 5, wherein the device comprises a plurality of sensors,

the communication unit is further configured to obtain first cell border data and the second cell border data of each of the plurality of cells;

the processing unit is further configured to perform the following operations on the first cell border data and the second cell border data of each cell, so as to obtain target border data of each cell: determining that the union of the first frame data of the target cell and the second cell frame data is the target geographic area frame of the target cell; the target cell is any one of the plurality of cells.

8. The apparatus according to any of claims 5-7, wherein the processing unit is further configured to:

9. A cell determining apparatus, comprising: a processor and a communication interface; the communication interface being coupled to the processor for running a computer program or instructions to implement the cell determination method as claimed in any one of claims 1-4.

10. A computer readable storage medium having instructions stored therein, characterized in that when executed by a computer, the computer performs the cell determination method as claimed in any one of the preceding claims 1-4.