Tracking area division method and apparatus, non-transitory storage medium, and electronic device

Abstract

The application discloses a tracking area division method and device, a nonvolatile storage medium and an electronic device. The method comprises: obtaining service data of a target area in a preset time period, wherein the service data comprises paging service volume and tracking area update service volume of each tracking area in the preset time period; iteratively updating tracking area ranges of each tracking area in the target area according to the service data until a comprehensive coefficient of the target area converges, wherein the comprehensive coefficient of the target area is determined by the tracking area ranges of each tracking area and the service data of the tracking area in the preset time period; and dividing each tracking area in the target area according to the tracking ranges of each tracking area corresponding to the time when the comprehensive coefficient converges. The application solves the technical problem that the division result does not conform to actual business conditions and the overall business burden in the area is heavy due to the fact that the influence of service data is not considered when tracking areas are divided in the related art.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of wireless communication, in particular to a tracking area division method and device, a nonvolatile storage medium and an electronic device. BACKGROUND

[0002] In the related art, when a tracking area is divided, a geographic information system is usually used in combination with the existing base station site scale to divide the tracking area. The problem with this division method is that the influence of service data on the tracking area division process is not fully considered, resulting in tracking areas that do not conform to actual service conditions, causing heavy overall service burden in the region.

[0003] To address the above problems, no effective solutions have been proposed so far. SUMMARY

[0004] Embodiments of the present application provide a tracking area division method, device, nonvolatile storage medium and electronic device to at least solve the technical problem of heavy overall service burden in the region caused by the fact that the influence of service data is not considered when the tracking area is divided in the related art, resulting in a division result that does not conform to actual service conditions.

[0005] According to an aspect of an embodiment of the present application, a tracking area division method is provided, comprising: obtaining service data of a target region in a preset time period, wherein the service data includes paging service volume and tracking area update service volume of each tracking area in the preset time period; iteratively updating tracking area ranges of each tracking area in the target region according to the service data until a comprehensive coefficient of the target region converges, wherein the tracking area range includes a coverage area of the tracking area, and the comprehensive coefficient of the target region is determined by the tracking area ranges of each tracking area and the service data of the tracking area in the preset time period; and dividing each tracking area in the target region according to the tracking ranges of each tracking area corresponding to the convergence of the comprehensive coefficient.

[0006] Optionally, the service data of the tracking area in the preset time period includes a paging service volume peak and a tracking area update service volume peak of the tracking area in the preset time period; iteratively updating the tracking area ranges of each tracking area in the target region according to the service data includes: determining a preset tracking area range of each tracking area; determining the paging service volume peak and the tracking area update service volume peak of each tracking area according to the preset tracking area range; determining a sub-comprehensive coefficient of each tracking area according to the paging service volume peak and the tracking area update service volume peak of each tracking area, and determining the comprehensive coefficient of the target region as the sum of the sub-comprehensive coefficients of each tracking area, wherein the size of the comprehensive coefficient is used to indicate the preset for dividing each tracking area; and iteratively updating the preset tracking area range of each tracking area in the case where the comprehensive coefficient does not converge until the comprehensive coefficient converges.

[0007] Optionally, determining the sub-comprehensive coefficient for each tracking area based on the peak paging traffic volume and the peak update traffic volume of each tracking area includes: determining the user perception index for each tracking area based on the preset tracking area range; determining the user perception coefficient based on the user perception index, wherein the user perception coefficient is negative when the user perception index indicates a reduction in the preset tracking area range, and positive when the user perception index indicates an expansion of the preset tracking area range; and updating the sub-comprehensive coefficient based on the user perception coefficient, wherein the updated sub-comprehensive coefficient is equal to the sum of the original sub-comprehensive coefficient and the user perception coefficient.

[0008] Optionally, user perception metrics include at least one of the following: user complaints, key quality indicators.

[0009] Optionally, before iteratively updating the tracking area range of each tracking area in the target area based on business data, the tracking area division method further includes: determining the business growth area in the target area; determining the first geographical center point of the business growth area and using the first geographical center point as the anchor point of the newly established tracking area; determining the geographical center point of each existing tracking area, and iteratively updating the coverage of each tracking area based on the geographical center point and the anchor point using a clustering algorithm until the difference between the historical load data of any two tracking areas is within a preset threshold range, wherein the historical load data includes at least one of the following: historical business load, historical network signaling overhead.

[0010] Optionally, the tracking area division method further includes: determining an initial tracking area list corresponding to the target terminal device; determining the distance between the geographical center point of the tracking area where the target terminal device is located and the geographical center points of each initial tracking area in the initial tracking area list; for each initial tracking area, determining the location update parameters corresponding to the initial tracking area based on the paging service peak and tracking area update service peak of the initial tracking area within a preset time period, as well as the distance; and adjusting the initial tracking area list of the target terminal device according to the location update parameters if the initial tracking area list where the target terminal device is located changes.

[0011] Optionally, adjusting the initial tracking area list of the target terminal device based on the location update parameters includes: determining a preset threshold based on the traffic volume of the target area, wherein the preset threshold and the traffic volume are positively correlated; and removing the initial tracking area with the largest corresponding location update parameter from the initial tracking area list if the sum of the location update parameters corresponding to each initial tracking area in the initial tracking area list is greater than the preset threshold.

[0012] According to another aspect of the embodiments of this application, a tracking area division device is also provided, comprising: a first processing module, configured to acquire service data of a target area within a preset time period, wherein the service data includes paging service volume and tracking area update service volume of each tracking area within the preset time period; a second processing module, configured to iteratively update the tracking area range of each tracking area in the target area based on the service data until the comprehensive coefficient of the target area converges, wherein the tracking area range includes the coverage area of ​​the tracking area, and the comprehensive coefficient of the target area is determined by the tracking area range of each tracking area and the service data of the tracking area within the preset time period; and a third processing module, configured to divide each tracking area in the target area based on the tracking range of each tracking area corresponding to the convergence of the comprehensive coefficient.

[0013] According to another aspect of the embodiments of this application, a non-volatile storage medium is also provided, wherein a program is stored in the non-volatile storage medium, and the program controls the device where the non-volatile storage medium is located to execute a tracking area partitioning method when it runs.

[0014] According to another aspect of the embodiments of this application, an electronic device is also provided, including: a memory and a processor, the processor being configured to run a program stored in the memory, wherein the program executes a trace area partitioning method during runtime.

[0015] According to another aspect of the embodiments of this application, a computer program product is also provided, including a computer program that implements a tracking region partitioning method when executed by a processor.

[0016] In this embodiment, the method involves acquiring business data of the target area within a preset time period. This business data includes paging traffic and tracking area update traffic for each tracking area within the preset time period. The tracking area range of each tracking area in the target area is iteratively updated based on the business data until the comprehensive coefficient of the target area converges. The tracking area range includes the coverage area of ​​the tracking area. The comprehensive coefficient of the target area is determined by the tracking area range of each tracking area and the business data of the tracking area within the preset time period. Based on the tracking range of each tracking area corresponding to the convergence of the comprehensive coefficient, the target area is divided into tracking areas. By guiding the iterative update of the tracking area range of each tracking area based on business data, the method achieves the goal of matching the final planned tracking area coverage with actual business needs. This achieves the technical effect of balancing and reducing the overall business burden of the region, thereby solving the technical problem in related technologies where the division of tracking areas does not consider the impact of business data, resulting in a division result that does not conform to the actual business situation and leads to a heavy overall business burden in the region. Attached Figure Description

[0017] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments of this application and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0018] Figure 1 This is a schematic diagram of the structure of a server according to an embodiment of this application;

[0019] Figure 2 This is a flowchart illustrating a tracking area division method according to an embodiment of this application;

[0020] Figure 3 This is a flowchart illustrating a tracking area division process according to an embodiment of this application;

[0021] Figure 4 This is a comparative schematic diagram of the tracking area before and after division according to an embodiment of this application;

[0022] Figure 5 This is a schematic diagram of an initial tracking area list provided according to an embodiment of this application;

[0023] Figure 6 This is a schematic diagram of an initial tracking area list after location update according to an embodiment of this application;

[0024] Figure 7 This is a schematic diagram of a tracking area planning device provided according to an embodiment of this application. Detailed Implementation

[0025] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0026] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0027] To better understand the embodiments of this application, the technical terms involved in the embodiments of this application are explained below:

[0028] Tracking Area (TA): In the field of wireless communication, a tracking area is an area consisting of multiple base station cells used to manage the location information of mobile terminals in a wireless communication network. When a mobile terminal moves within the same tracking area, it does not need to report its location change to the network, which reduces the signaling burden on the network.

[0029] Tracking Area List (TAL): When a mobile terminal moves within the same tracking area, it does not need to frequently report its location changes to the network, thus reducing the signaling load on the network. The Tracking Area List (TAL) is a list of multiple tracking areas. When a mobile terminal moves within any tracking area of ​​the TAL, no location update is required. A location update is only required when the terminal enters a new tracking area that is not in its registered TAL.

[0030] Paging: Paging is a special function in wireless communication networks used to locate and notify mobile terminals that there is signaling or data to be received. When a mobile terminal is not connected, the core network locates the terminal and establishes a connection by sending paging messages.

[0031] Tracking Area Update (TAU): In the field of wireless communication, location update refers to the process where a mobile device changes its geographical location while moving, requiring the network to update its location information to ensure that the network can accurately locate and page the device.

[0032] Tracking Area (TA) planning is a key method for optimizing mobile network management and resource allocation. TA planning primarily focuses on the coverage area or the number of base stations included in each tracking area. If the coverage area of ​​each tracking area is too large, encompassing a large number of base stations, the probability of paging channel congestion may increase. Conversely, if the coverage area is too small, excessive location area updates may occur, leading to congestion of the system signaling channel.

[0033] In current mobile communication systems, tracking zones are areas designed to manage mobile user location updates. Each tracking zone can contain multiple tracking zone codes to uniquely identify different tracking zones. The tracking zone update cycle determines how frequently mobile devices update location information between tracking zones.

[0034] The commonly used tracking area planning optimization methods in related technologies mainly include the following:

[0035] Using a Geographic Information System (GIS), planning and design are carried out in combination with the existing site size, location, performance indicators and ground features. New sites are incorporated into the nearby planned tracking areas according to the principle of proximity.

[0036] Extract tracking area update data, rasterize TAU counts, locate the central base station in the high traffic grid, divide the base stations within a predetermined distance range according to a predetermined gradient, compare the total traffic volume of the newly added grid in each segment, and select the new TA boundary in the segment with the smallest total traffic volume as the optimal TA boundary.

[0037] Based on the inter-frequency measurement data of MR (Mobile Radio), the TA is assigned, the interference coefficient is calculated, and the TA with the fewest interfering cells is selected as the target TA.

[0038] Based on the measurement report, the tracking area to which the community belongs is determined, and the interaction frequency between the main service community and the surrounding tracking areas is measured by the first quantity ratio. The rationality of the tracking area boundary is judged, and the target community that needs to be replanned is found.

[0039] However, with the development of information and transportation technologies, people's activity range is expanding, and the density of gatherings, competitions, and events is increasing, leading to faster frequency of sudden business disruptions and regional peaks. Existing TA (Traffic Availability) plans, because they do not take into account the impact of communication service data (such as paging traffic and tracking area update traffic), may fail to effectively guarantee the user experience under sudden business disruptions.

[0040] To address the aforementioned issues, this application provides relevant solutions, which are detailed below.

[0041] According to an embodiment of this application, a method embodiment for a tracking area division method is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0042] The methods and embodiments provided in this application can be executed on mobile terminals, computer terminals, or similar computing devices. Figure 1 A hardware block diagram of a computer terminal (or mobile device) for implementing a tracking region partitioning method is shown. Figure 1 As shown, the computer terminal 10 (or mobile device 10) may include one or more processors 102 (shown as 102a, 102b, ..., 102n in the figure) 102 (processor 102 may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.), a memory 104 for storing data, and a transmission device 106 for communication functions. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of a BUS bus), a network interface, a power supply, and / or a camera. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, computer terminal 10 may also include... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0043] It should be noted that the aforementioned one or more processors 102 and / or other data processing circuits are generally referred to herein as "data processing circuits". These data processing circuits may be embodied, in whole or in part, in software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuits may be a single, independent processing module, or may be integrated, in whole or in part, into any other element within the computer terminal 10 (or mobile device). As involved in the embodiments of this application, the data processing circuits serve as a processor control mechanism (e.g., selection of a variable resistor termination path connected to an interface).

[0044] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the tracking area partitioning method in this embodiment. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, thereby implementing the aforementioned tracking area partitioning method. The memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the computer terminal 10 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0045] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the communication provider of the computer terminal 10. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 may be a Radio Frequency (RF) module, used for wireless communication with the Internet.

[0046] The display may be, for example, a touchscreen liquid crystal display (LCD) that allows the user to interact with the user interface of the computer terminal 10 (or mobile device).

[0047] Under the above operating environment, this application embodiment provides a tracking region division method, such as... Figure 2 As shown, the method includes the following steps:

[0048] Step S202: Obtain the business data of the target area within a preset time period, wherein the business data includes the paging volume and update volume of each tracking area within the preset time period.

[0049] As an optional implementation method, the following division rules must be followed when dividing the tracking area:

[0050] Paging and location update balancing:

[0051] The coverage size of a Location Address List (TA) needs to be set in a balance between the paging capacity of the MME and the signaling load of the network. An excessively large TA will increase the paging burden on the MME, while an excessively small TA will lead to frequent location updates. Using a Location Address List (TAL) can reduce the frequency of location updates within a certain range, thereby improving network efficiency.

[0052] Geographical and demographic factors to consider:

[0053] The boundaries of a Location Tracker (TA) should ideally avoid high-traffic areas, such as commercial districts or densely populated areas, to reduce the frequency of location updates. Utilizing natural geographical boundaries, such as mountains or rivers, to delineate TA boundaries helps reduce the overlap depth of cells at the boundaries, thereby reducing update costs.

[0054] Synergy with existing network architecture:

[0055] The planning of TA and TAL should be kept as consistent as possible with the existing 2G / 3G network architecture (such as LAC) to facilitate network management and subsequent technology migration. In addition, considering future network expansion and the addition of frequency bands, the planning of TA should have a certain degree of foresight and flexibility.

[0056] Optimization of signaling overhead:

[0057] By optimizing the TAL size, location update signaling caused by UE movement can be reduced. For example, in a multi-MME environment, clustering can be used to optimize signaling transmission and load balancing.

[0058] Easy to manage and maintain:

[0059] The design of a TA (Transmission Area) should be simple and clear, avoiding complex boundary divisions to facilitate daily network operation and maintenance. For example, continuous geographical areas should be used as TAs whenever possible, avoiding scattered cell distributions, which can reduce management difficulty and potential errors.

[0060] Dynamic adjustment and optimization:

[0061] Based on actual network load and user behavior, network operators should periodically review and adjust traffic assignment (TA) allocation to adapt to constantly changing network conditions and user needs. For example, data analytics and machine learning techniques can be used to predict traffic volume changes, thereby guiding the dynamic optimization of TA.

[0062] Based on the above conditions, the tracking area in the target area can be planned according to the business data of the target area.

[0063] In the technical solution provided in step S202, the business data can be historical business data corresponding to the current date. For example, it can be historical business data containing the current date extracted from historical business data from last year or the year before. That is, when dividing the tracking area of ​​the target area on a certain day in October, historical business data from last year or the year before containing October data can be obtained as training data for the division model. In addition, the model structure used in this application embodiment is not limited, and it can be any machine learning model. Selecting historical business data containing the current date can better cope with the increase in communication traffic caused by various large-scale events that may lead to gatherings of people, or the increase in communication traffic caused by periodic gathering activities such as high-speed rail.

[0064] As an optional implementation, the paging and location update traffic of each TA in the existing network can be collected within a preset time period. In this way, each TA can obtain its peak paging traffic Pmax and peak tracking area update (TAU) traffic Tmax within a certain period of time.

[0065] In some embodiments of this application, after obtaining the peak traffic volume of each TA, the peak traffic volume of each TA can be adjusted during the iterative update process according to the preset coverage area planned for each TA, including paging peak traffic volume and tracking area update peak traffic volume. When adjusting the peak traffic volume, as the coverage area of ​​a TA increases, its paging peak traffic volume will increase, while its tracking area update peak traffic volume will decrease.

[0066] Step S204: Iteratively update the tracking area range of each tracking area in the target area based on the business data until the comprehensive coefficient of the target area converges. Here, the tracking area range includes the coverage area of ​​the tracking area, and the comprehensive coefficient of the target area is determined by the tracking area range of each tracking area and the business data of the tracking area in the preset time period.

[0067] In the technical solution provided in step S204, the service data of the tracking area during the preset time period includes the peak paging traffic volume and the peak tracking area update traffic volume during the preset time period. The step of iteratively updating the tracking area range of each tracking area in the target area based on the service data includes: determining the preset tracking area range of each tracking area; determining the peak paging traffic volume and the peak tracking area update traffic volume of each tracking area based on the preset tracking area range; determining the sub-comprehensive coefficient of each tracking area based on the peak paging traffic volume and the peak tracking area update traffic volume of each tracking area, and determining the comprehensive coefficient of the target area as the sum of the sub-comprehensive coefficients of each tracking area, wherein the magnitude of the comprehensive coefficient is used to indicate the preset division of each tracking area; if the comprehensive coefficient does not converge, iteratively updating the preset tracking area range of each tracking area until the comprehensive coefficient converges.

[0068] Optionally, when iteratively updating the tracking area range of each tracking area, historical service data can be used in conjunction with signaling / network load parameters, and an iterative machine learning algorithm can be used to iteratively update the tracking area range to determine the final tracking area division result.

[0069] The formula for calculating the above sub-comprehensive coefficient k is as follows:

[0070] K = i * Pmax + j * Tmax

[0071] In the above formula, Pmax is the peak paging traffic volume, and Tmax is the peak tracking area update traffic volume. i and j are coefficients determined based on the coverage of each tracking area, and the corresponding i and j are the same for each tracking area in the target area A during the same iteration.

[0072] As an optional implementation, when iteratively updating the tracking region, coefficients i and j are also updated, and i and j satisfy the following constraints:

[0073] i+j=M

[0074] Where M is a preset value and is a positive number.

[0075] Alternatively, i and j can be preset values ​​without iterative updates. When presetting i and j, the characteristics of historical data in the target area can be considered. For example, if the paging traffic in the target area is more prone to overload, i can be set larger, j can be set smaller, and i should be greater than j. When the target area is a high-speed rail line area or other areas where tracking update traffic is more prone to overload, i can be set smaller, j can be set larger, and i should be less than j.

[0076] During the iteration process, when the comprehensive coefficient KA of the target region is the smallest (that is, when KA converges), the coverage range of each tracking region can be considered as the final division result.

[0077] The relationship between the above-mentioned comprehensive coefficient KA and the sub-comprehensive coefficient K of each tracking area is as follows:

[0078]

[0079] In the above formula, This represents the sub-comprehension coefficient of the i-th tracking region.

[0080] In some embodiments of this application, the step of determining the sub-comprehensive coefficient of each tracking area based on the peak paging traffic volume and the peak update traffic volume of each tracking area includes: determining the user perception index of each tracking area based on the preset tracking area range; determining the user perception coefficient based on the user perception index, wherein the user perception coefficient is negative when the user perception index indicates a reduction in the preset tracking area range, and positive when the user perception index indicates an expansion of the preset tracking area range; and updating the sub-comprehensive coefficient based on the user perception coefficient, wherein the updated sub-comprehensive coefficient is equal to the sum of the original sub-comprehensive coefficient and the user perception coefficient.

[0081] As an optional implementation, user perception metrics include at least one of the following: user complaints, key quality indicators.

[0082] Specifically, after determining the minimum Key Account (KA), upon receiving user perception metrics, a coefficient Cust_q can be generated based on user perception metrics such as complaints and KQI performance. If the user perception metrics require narrowing the Key Account (TA), for example, when paging congestion leads to related complaints, Cust_q is negative; otherwise, it is positive. The absolute value of the coefficient Cust_q is influenced by the size of the perception metrics. For example, if the analysis indicates that user complaints are caused by an excessively large tracking area, the coefficient Cust_q can be set to negative. Then, the absolute value of Cust_q can be determined based on the number of related complaints caused by an excessively large tracking area over a period of time.

[0083] K and KA can then be corrected using the following formula:

[0084] K Final =K+Cust_q

[0085]

[0086] In some embodiments of this application, a method such as... is also provided. Figure 3 The tracking area division process is shown below:

[0087] Step S302: Based on historical business data, determine the initial tracking area range, taking into account geographical continuity, population distribution, and network expansion coordination.

[0088] Step S304: With the goal of balancing the ratio of peak paging traffic to peak tracking area update traffic, iterative updates are performed using the initial tracking area range as the initial value.

[0089] Step S306: Determine whether the signaling / network load has increased, and adjust the iteration results of the tracking area range according to the load.

[0090] In the technical solution provided in step S306, the purpose of adjusting the iteration results is to ensure load balance in each tracking zone.

[0091] Step S308: Obtain user perception metrics, and iterate and update the adjusted tracking area range iteration results again based on user perception metrics.

[0092] Step S206: Based on the tracking range of each tracking region when the comprehensive coefficient converges, divide each tracking region in the target region.

[0093] In the technical solution provided in step S206, before iteratively updating the tracking area range of each tracking area in the target area based on the business data, the tracking area division method further includes: determining the business growth area in the target area; determining the first geographical center point of the business growth area and using the first geographical center point as the anchor point of the newly established tracking area; determining the geographical center point of each existing tracking area, and iteratively updating the coverage of each tracking area based on the geographical center point and the anchor point using a clustering algorithm until the difference between the historical load data of any two tracking areas is within a preset threshold range, wherein the historical load data includes at least one of the following: historical business load, historical network signaling overhead.

[0094] Specifically, in the current network environment, there are sometimes situations where a TA cannot be optimized, and incremental planning for the TA is required. Existing technology usually involves splitting a TA. This method can effectively reduce the business burden of the original TA, but it does not balance the business of other TAs.

[0095] To address this issue, this application provides the following incremental load balancing planning method for TAs within region A (typically counties, districts, and townships, defined by geographical and demographic factors), thereby improving the overall service load of each TA within region A.

[0096] Specifically, for business growth areas, a geographic center point is set as the anchor point for new target agents (TAs). At the same time, the coverage of each tracking area is adjusted using the K-MEANS algorithm, combined with the geographic center point of existing TAs. Then, the tracking area range is iteratively updated based on business data, using the adjusted tracking area coverage as the initial value.

[0097] In some embodiments of this application, Figure 4 This is a comparative diagram showing the difference before and after the tracking area is divided. After setting the anchor point (also known as the traffic center point) for the newly added TA, multiple iterations using clustering algorithms such as K-MEANS ensure that the service load and network signaling overhead of each TA are roughly the same. Then, the minimum value of Kfinal within the area can be calculated using the Pmax, Tmax, and Cust_q parameters, allowing for local adjustments such as scaling up or down the TA. When determining whether the service load and network signaling overhead of each TA meet the preset requirements, the absolute value of the difference in service load or network signaling overhead between each TA can be determined. If the absolute value of the difference between any two TAs is within a preset threshold range, then the service load and network signaling overhead of each TA are considered to meet the preset requirements.

[0098] In some embodiments of this application, the tracking area division method further includes: determining an initial tracking area list corresponding to the target terminal device; determining the distance between the geographical center point of the tracking area where the target terminal device is located and the geographical center points of each initial tracking area in the initial tracking area list; for each initial tracking area, determining the location update parameters corresponding to the initial tracking area based on the paging service peak value and the tracking area update service peak value of the initial tracking area within a preset time period, as well as the distance; and adjusting the initial tracking area list of the target terminal device according to the location update parameters when the initial tracking area list where the target terminal device is located changes.

[0099] As an optional implementation, the step of adjusting the initial tracking area list of the target terminal device based on the location update parameters includes: determining a preset threshold based on the traffic volume of the target area, wherein the preset threshold is positively correlated with the traffic volume; and removing the initial tracking area with the largest corresponding location update parameter from the initial tracking area list when the sum of the location update parameters corresponding to each initial tracking area in the initial tracking area list is greater than the preset threshold.

[0100] Specifically, after updating the tracking area using the above method, there may still be situations where peak traffic leads to an increase in paging or location update signaling. In such cases, the length of the TAL can be increased or decreased by setting a temporary offset P for each TA in the TAL, thereby mitigating the impact of peak traffic.

[0101] Furthermore, to reduce the burden on the existing network, the larger the paging traffic volume, the smaller the recommended TA (Target Address) should be, while the more location updates occur, the larger the recommended TA should be. The increase in traffic volume for both types of traffic has an opposite effect on TA planning. To cope with sudden peak traffic in the network, this application provides a location update parameter O, which can temporarily adjust the length and composition of the TA based on the magnitude of existing network location updates and paging traffic.

[0102] For each tracking region TA:TA_1,TA_2…TA_n, the calculation formula for the position update parameters is as follows:

[0103] O_TA_n = i*Pmax - j*Tmax + K*DIS

[0104] Here, i, j, and K refer to i, j, and the sub-comprehensive coefficient K mentioned above. DIS represents the distance between the geographic center of the TA and the geographic center of the user's TA.

[0105] To adjust TAL, a preset threshold TAL_MAX can be set based on the network traffic volume in the target area, and TAL can be adjusted according to the following constraint formula:

[0106] TAL_MAX≥ O_TA_1+ O_TA_2…O_TA_n

[0107] Where O_TA_n represents the position update parameter of the nth tracking region. If the sum of O_TA_n of all tracking regions is greater than TAL_MAX, then the TA with the largest position update parameter is moved out of TAL first, until the above constraint formula is satisfied.

[0108] Specifically, Figure 5 This is the initial TAL. For ease of explanation, the values ​​of i, j, and K are all 1 here. From Figure 5 As can be seen from the data, before the update, TAL contained 6 TAs: TA_1, TA_3, TA_4, TA_5, TA_6, and TA_7. Therefore, the sum of O_TA_n for these TAs is 13. For example... Figure 6 As shown in the table below, when the location of a terminal device is updated, the location update parameters of each TA will also change:

[0109]

[0110] If TAL_MAX is set to 16, then the sum of O_TA_n of the 7 TAs is 19, which is greater than TAL_MAX. Therefore, in TAL optimization, TA_3 should be removed first because it has the largest TA.

[0111] In the example, assuming that the peak paging traffic parameter Pmax of TA_3 is 5 and the tracking area update traffic parameter Tmax is 1, compared with TA_4, which has Pmax of 1 and Tmax of 3 under the same DIS, it is more necessary to remove it from TAL to reduce the paging load of TA_3 and reduce the location update of TA_4.

[0112] By acquiring business data of the target area within a preset time period, including paging volume and update volume of each tracking area within that period, and iteratively updating the tracking area range of each tracking area within the target area based on this data until the overall coefficient of the target area converges (where the tracking area range includes the coverage area of ​​the tracking area, and the overall coefficient of the target area is determined by the tracking area range of each tracking area and the business data of the tracking area within the preset time period), and dividing the target area into tracking areas based on the tracking range of each tracking area corresponding to the convergence of the overall coefficient, the iterative update of the tracking area range of each tracking area is guided by business data. This achieves the goal of matching the final planned tracking area coverage with actual business needs, thereby balancing and reducing the overall business burden of the region. Furthermore, it solves the technical problem of heavy overall business burden in the region caused by the failure to consider the impact of business data when dividing tracking areas in related technologies.

[0113] This application provides a tracking area division device. Figure 7 This is a schematic diagram of the device. From Figure 7 As can be seen from the diagram, the device includes: a first processing module 70, used to acquire business data of the target area within a preset time period, wherein the business data includes paging traffic and tracking area update traffic of each tracking area within the preset time period; a second processing module 72, used to iteratively update the tracking area range of each tracking area in the target area based on the business data until the comprehensive coefficient of the target area converges, wherein the tracking area range includes the coverage area of ​​the tracking area, and the comprehensive coefficient of the target area is determined by the tracking area range of each tracking area and the business data of the tracking area within the preset time period; and a third processing module 74, used to divide each tracking area in the target area based on the tracking range of each tracking area corresponding to the convergence of the comprehensive coefficient.

[0114] In some embodiments of this application, the service data of the tracking area during a preset time period includes the peak paging traffic volume and the peak tracking area update traffic volume during the preset time period. The step of the second processing module 72 iteratively updating the tracking area range of each tracking area in the target area based on the service data includes: determining the preset tracking area range of each tracking area; determining the peak paging traffic volume and the peak tracking area update traffic volume of each tracking area based on the preset tracking area range; determining the sub-comprehensive coefficient of each tracking area based on the peak paging traffic volume and the peak tracking area update traffic volume of each tracking area, and determining the comprehensive coefficient of the target area as the sum of the sub-comprehensive coefficients of each tracking area, wherein the magnitude of the comprehensive coefficient is used to indicate the preset division of each tracking area; if the comprehensive coefficient does not converge, iteratively updating the preset tracking area range of each tracking area until the comprehensive coefficient converges.

[0115] In some embodiments of this application, the step of the second processing module 72 determining the sub-comprehensive coefficient of each tracking area based on the peak paging traffic volume and the peak update traffic volume of each tracking area includes: determining the user perception index of each tracking area based on the preset tracking area range; determining the user perception coefficient based on the user perception index, wherein the user perception coefficient is negative when the user perception index indicates a reduction in the preset tracking area range, and positive when the user perception index indicates an expansion of the preset tracking area range; and updating the sub-comprehensive coefficient based on the user perception coefficient, wherein the updated sub-comprehensive coefficient is equal to the sum of the sub-comprehensive coefficient before the update and the user perception coefficient.

[0116] In some embodiments of this application, user perception metrics include at least one of the following: user complaints, key quality indicators.

[0117] In some embodiments of this application, before iteratively updating the tracking area range of each tracking area in the target area based on business data, the tracking area division device is further configured to: determine the business growth area in the target area; determine the first geographical center point of the business growth area and use the first geographical center point as the anchor point of the newly established tracking area; determine the geographical center point of each existing tracking area, and iteratively update the coverage of each tracking area based on the geographical center point and the anchor point using a clustering algorithm until the difference between the historical load data of any two tracking areas is within a preset threshold range, wherein the historical load data includes at least one of the following: historical business load, historical network signaling overhead.

[0118] In some embodiments of this application, the tracking area division device is further configured to: determine an initial tracking area list corresponding to the target terminal device; determine the distance between the geographical center point of the tracking area where the target terminal device is located and the geographical center points of each initial tracking area in the initial tracking area list; for each initial tracking area, determine the location update parameters corresponding to the initial tracking area based on the paging service peak value and the tracking area update service peak value of the initial tracking area within a preset time period, as well as the distance; and adjust the initial tracking area list of the target terminal device according to the location update parameters when the initial tracking area list where the target terminal device is located changes.

[0119] In some embodiments of this application, the step of the tracking area division device adjusting the initial tracking area list of the target terminal device according to the location update parameters includes: determining a preset threshold based on the traffic volume of the target area, wherein the preset threshold and the traffic volume are positively correlated; and removing the initial tracking area with the largest corresponding location update parameter from the initial tracking area list when the sum of the location update parameters corresponding to each initial tracking area in the initial tracking area list is greater than the preset threshold.

[0120] It should be noted that each module in the above-mentioned tracking area division device can be a program module (for example, a set of program instructions that implement a certain function) or a hardware module. For the latter, it can be manifested in the following forms, but is not limited to them: each of the above modules is manifested as a processor, or the functions of each of the above modules are implemented by a processor.

[0121] According to an embodiment of this application, a non-volatile storage medium is provided. The non-volatile storage medium stores a program that, when running, controls the device containing the non-volatile storage medium to execute the following tracking area division method: acquiring service data of a target area within a preset time period, wherein the service data includes paging traffic and tracking area update traffic of each tracking area within the preset time period; iteratively updating the tracking area range of each tracking area in the target area based on the service data until the comprehensive coefficient of the target area converges, wherein the tracking area range includes the coverage area of ​​the tracking area, and the comprehensive coefficient of the target area is determined by the tracking area range of each tracking area and the service data of the tracking area within the preset time period; and dividing the target area into tracking areas based on the tracking range of each tracking area corresponding to the convergence of the comprehensive coefficient.

[0122] According to an embodiment of this application, an electronic device is provided, including a memory and a processor. The processor is used to run a program stored in the memory, wherein the program executes the following tracking area division method during runtime: acquiring service data of a target area within a preset time period, wherein the service data includes paging service volume and tracking area update service volume of each tracking area within the preset time period; iteratively updating the tracking area range of each tracking area in the target area based on the service data until the comprehensive coefficient of the target area converges, wherein the tracking area range includes the coverage area of ​​the tracking area, and the comprehensive coefficient of the target area is determined by the tracking area range of each tracking area and the service data of the tracking area within the preset time period; and dividing each tracking area in the target area according to the tracking range of each tracking area when the comprehensive coefficient converges.

[0123] According to an embodiment of this application, a computer program product is provided, including a computer program. When executed by a processor, the computer program implements the following tracking area division method: acquiring business data of a target area within a preset time period, wherein the business data includes paging traffic and tracking area update traffic of each tracking area within the preset time period; iteratively updating the tracking area range of each tracking area in the target area based on the business data until the comprehensive coefficient of the target area converges, wherein the tracking area range includes the coverage area of ​​the tracking area, and the comprehensive coefficient of the target area is determined by the tracking area range of each tracking area and the business data of the tracking area within the preset time period; and dividing each tracking area in the target area according to the tracking range of each tracking area corresponding to the convergence of the comprehensive coefficient.

[0124] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0125] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0126] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0127] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0128] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to related technologies, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0129] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for dividing a tracking region, characterized in that, include: Obtain service data of the target area within a preset time period, wherein the service data includes paging service volume and tracking area update service volume of each tracking area within the preset time period; Determine the preset tracking area range for each of the aforementioned tracking areas; The peak paging traffic volume and the peak tracking update traffic volume of each tracking area are determined based on the preset tracking area range, wherein the peak paging traffic volume and the peak tracking update traffic volume of each tracking area are used to determine the sub-comprehensive coefficient of each tracking area; Based on the preset tracking area range, determine the user perception indicators for each tracking area; The user perception coefficient is determined based on the user perception index, wherein the user perception coefficient is negative when the user perception index indicates that the preset tracking area range is narrowed, and the user perception coefficient is positive when the user perception index indicates that the preset tracking area range is expanded. The user perception index includes at least one of the following: user complaints, key quality indicators. The sub-comprehensive coefficient is updated based on the user perception coefficient, wherein the updated sub-comprehensive coefficient is equal to the sum of the original sub-comprehensive coefficient and the user perception coefficient; The comprehensive coefficient of the target region is determined to be the sum of the sub-comprehensive coefficients of each of the tracking regions, wherein the magnitude of the comprehensive coefficient is used to indicate the preset division of each of the tracking regions; If the comprehensive coefficient does not converge, the preset tracking area range of each tracking area is iteratively updated until the comprehensive coefficient of the target area converges. The tracking area range includes the coverage area of ​​the tracking area, and the comprehensive coefficient of the target area is determined by the tracking area range of each tracking area and the business data of the tracking area in the preset time period. Based on the tracking range of each tracking region corresponding to the convergence of the comprehensive coefficient, the target region is divided into each tracking region.

2. The tracking area division method according to claim 1, characterized in that, The service data of the tracking area during the preset time period includes the peak paging volume and the peak update volume of the tracking area during the preset time period.

3. The tracking area division method according to claim 1, characterized in that, Before iteratively updating the tracking area range of each tracking area in the target area based on the business data, the tracking area division method further includes: Identify business growth areas within the target region; Determine the first geographic center point of the business growth area and use the first geographic center point as the anchor point of the newly established tracking area; The geographic center point of each existing tracking area is determined, and the coverage of each tracking area is iteratively updated using a clustering algorithm based on the geographic center point and the anchor point until the difference in historical load data between any two tracking areas is within a preset threshold range. The historical load data includes at least one of the following: historical service load and historical network signaling overhead.

4. The tracking area division method according to claim 1, characterized in that, The tracking area division method also includes: Determine the initial tracking area list corresponding to the target terminal device; Determine the distance between the geographic center point of the tracking area where the target terminal device is located and the geographic center point of each initial tracking area in the initial tracking area list; For each initial tracking zone, the location update parameters corresponding to the initial tracking zone are determined based on the paging service peak value and tracking zone update service peak value of the initial tracking zone within the preset time period, as well as the distance. If the initial tracking area list of the target terminal device changes, the initial tracking area list of the target terminal device shall be adjusted according to the location update parameters.

5. The tracking area division method according to claim 4, characterized in that, Adjusting the initial tracking area list of the target terminal device based on the location update parameters includes: A preset threshold is determined based on the traffic volume of the target area, wherein the preset threshold and the traffic volume are positively correlated; If the sum of the position update parameters corresponding to each initial tracking region in the initial tracking region list is greater than the preset threshold, the initial tracking region with the largest corresponding position update parameter is removed from the initial tracking region list.

6. A tracking area division transposition method, characterized in that, include: The first processing module is used to acquire business data of the target area within a preset time period, wherein the business data includes paging traffic and tracking area update traffic of each tracking area within the preset time period. The second processing module is configured to: determine a preset tracking area range for each tracking area; determine the peak paging traffic volume and peak tracking area update traffic volume for each tracking area based on the preset tracking area range, wherein the peak paging traffic volume and peak tracking area update traffic volume for each tracking area are used to determine the sub-synthesis coefficient for each tracking area; determine a user perception index for each tracking area based on the preset tracking area range; and determine a user perception coefficient based on the user perception index, wherein the user perception coefficient is negative when the user perception index indicates a reduction in the preset tracking area range, and positive when the user perception index indicates an expansion of the preset tracking area range. The user perception index includes at least one of the following:

1. User complaints, key quality indicators; update the sub-comprehensive coefficient based on the user perception coefficient, wherein the updated sub-comprehensive coefficient is equal to the sum of the original sub-comprehensive coefficient and the user perception coefficient; determine the comprehensive coefficient of the target area as the sum of the sub-comprehensive coefficients of each tracking area, wherein the magnitude of the comprehensive coefficient is used to indicate the preset division of each tracking area; if the comprehensive coefficient does not converge, iteratively update the preset tracking area range of each tracking area until the comprehensive coefficient of the target area converges, wherein the tracking area range includes the coverage area of ​​the tracking area, and the comprehensive coefficient of the target area is determined by the tracking area range of each tracking area and the business data of the tracking area in the preset time period; The third processing module is used to divide each tracking region in the target region according to the tracking range of each tracking region when the comprehensive coefficient converges.

7. A non-volatile storage medium, characterized in that, The non-volatile storage medium stores a program, wherein when the program is executed, it controls the device where the non-volatile storage medium is located to execute the tracking area partitioning method according to any one of claims 1 to 5.

8. An electronic device, characterized in that, include: A memory and a processor, the processor being configured to run a program stored in the memory, wherein the program, when running, executes the tracking region partitioning method according to any one of claims 1 to 5.

9. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the tracking region division method according to any one of claims 1 to 5.

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