Method, device and equipment for pre-evaluating network construction effect and storage medium

Abstract

The application provides a network construction effect pre-evaluation method and device, equipment and a storage medium, relates to the technical field of communication, and is used for solving the problem of low accuracy of network construction effect pre-evaluation. The method comprises the following steps: obtaining a measurement report of a constructed network in a target area. Based on the measurement report of the constructed network, the path loss and the antenna gain difference between the constructed network and a network to be constructed in the target area are determined. Based on the path loss and the antenna gain difference, the measurement report of the constructed network is processed to obtain a measurement report of the network to be constructed. Based on the measurement report of the network to be constructed, pre-evaluation information is determined, and the pre-evaluation information is used to indicate the demand degree of the target area for the network to be constructed.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a method, apparatus, device and storage medium for pre-evaluating the effectiveness of network construction. Background Technology

[0002] Preliminary assessment of network construction effectiveness is an important step before the formal deployment and infrastructure implementation of a new network. It helps operators and network providers understand key indicators such as network performance and coverage before actual construction, and conduct a comprehensive and systematic analysis and prediction of expected construction results.

[0003] Traditional wireless network analysis, when conducting a preliminary assessment of the network construction effect, relies on the operator collecting measurement reports (MRs) for the area to be constructed. This allows for the evaluation of the network service quality in the area before network construction, determining the network requirements of the area, and thus achieving a preliminary assessment of the network construction effect.

[0004] However, in the above technical solutions, since the network type (such as frequency band, mobile communication network type, operator) corresponding to the collected MR may differ from the network type to be built, it cannot provide an accurate reference for evaluating the network service quality of network construction, which in turn affects the determination of the network demand in the area to be built and reduces the accuracy of the pre-evaluation of the network construction effect. Summary of the Invention

[0005] This application provides a method, apparatus, device, and storage medium for pre-evaluating the effectiveness of network construction, which addresses the problem of low accuracy in pre-evaluating the effectiveness of network construction.

[0006] To achieve the above objectives, this application adopts the following technical solution:

[0007] Firstly, this application provides a method for pre-evaluating the effectiveness of network construction. The method includes: a pre-evaluation device (hereinafter referred to as the "pre-evaluation device") acquiring measurement reports of existing networks in a target area; the pre-evaluation device determining the path loss and antenna gain difference between the existing networks and the network to be constructed in the target area based on the measurement reports of the existing networks; the pre-evaluation device processing the measurement reports of the existing networks based on the path loss and antenna gain difference to obtain a measurement report of the network to be constructed; and the pre-evaluation device determining pre-evaluation information based on the measurement reports of the network to be constructed, the pre-evaluation information being used to indicate the demand for the network to be constructed in the target area.

[0008] The technical solution provided in this application offers at least the following beneficial effects: By obtaining measurement reports of existing networks in the target area, the path loss and antenna gain differences between the existing networks and the networks to be built in the target area are determined. Based on the path loss and antenna gain differences, the measurement reports of the existing networks are processed to obtain the measurement reports of the networks to be built. Then, pre-assessment information is determined, which indicates the demand for the networks to be built in the target area. In other words, based on the path loss and antenna gain differences between different networks, the discrepancies between the measurement reports of different networks can be eliminated. Therefore, before the construction of the networks to be built in the target area is completed, the measurement reports of the networks to be built after construction are simulated based on the measurement reports of other networks in the target area, providing an accurate reference for the pre-assessment of the network service quality after construction and determining the demand for the networks to be built in the target area. Thus, the accuracy of the pre-assessment of network construction effectiveness can be improved.

[0009] Optionally, the measurement report includes: the reference signal received power of the sampling point. The target area includes multiple first sampling points, and the network type of the first sampling points is an established network. The method described above, "processing the measurement report of the established network based on path loss and antenna gain difference to obtain the measurement report of the network to be built," includes: processing the reference signal received power of each of the multiple first sampling points based on path loss and antenna gain difference to obtain the reference signal received power of multiple second sampling points in the target area. Here, one second sampling point corresponds to one first sampling point, the network type of the second sampling point is the network to be built, and the reference signal received power of the second sampling point is equal to the processed reference signal received power of the corresponding first sampling point.

[0010] Optionally, the method further includes: when the established network is a preset network, selecting at least one third sampling point from multiple first sampling points based on a first preset received power threshold, wherein the reference signal received power of the third sampling point is less than the first preset received power threshold. Processing the reference signal received power of each of the multiple first sampling points based on path loss and antenna gain difference to obtain the reference signal received power of multiple second sampling points in the target area includes: processing the reference signal received power of each of the at least one third sampling point based on path loss and antenna gain difference to obtain the reference signal received power of multiple second sampling points.

[0011] Optionally, the measurement report may also include: the signal-to-interference-plus-noise ratio (SNR) and uplink rate of the sampling point. The method described above, which "processes the measurement report of the established network based on path loss and antenna gain difference to obtain the measurement report of the network to be built," further includes: for each second sampling point, determining the SNR and uplink rate of each second sampling point according to a first operation, wherein the first operation includes: determining the SNR of the target sampling point based on the reference signal received power of the target sampling point and the reference signal received power of multiple fourth sampling points, wherein the target sampling point is any one of the multiple second sampling points, and the fourth sampling point is a sampling point adjacent to the target sampling point among the multiple second sampling points; and determining the uplink rate of the target sampling point based on the reference signal received power and SNR of the target sampling point.

[0012] Optionally, the method for "determining pre-assessment information based on the measurement report of the network to be constructed" includes: selecting at least one fifth sampling point from multiple second sampling points based on a first preset rate threshold, wherein the uplink rate of the fifth sampling point is greater than the first preset rate threshold; and determining pre-assessment information based on a first ratio between the number of fifth sampling points and the number of second sampling points, wherein the first ratio is positively correlated with the demand for the network to be constructed in the target area.

[0013] Optionally, the method further includes: rasterizing the target area to obtain multiple first grids; acquiring application service data for each first sampling point; locating the multiple first sampling points in the target area based on the application service data of each first sampling point, and determining the first sampling point in each first grid; determining pre-evaluation information based on the measurement report of the network to be built, including: determining a second ratio corresponding to each first grid based on a second preset rate threshold, wherein the second ratio is the ratio between the number of sixth sampling points in the first grid and the number of second sampling points, and the sixth sampling point is a sampling point among the multiple second sampling points whose uplink rate is greater than the second preset rate threshold; selecting at least one second grid from the multiple first grids based on the first preset ratio threshold, wherein the second ratio corresponding to the second grid is greater than the first preset ratio threshold; and determining pre-evaluation information based on the distribution of at least one second grid in the target area.

[0014] Secondly, this application provides an apparatus for pre-evaluating the effectiveness of network construction, the apparatus comprising: an acquisition module and a processing module.

[0015] The acquisition module acquires measurement reports of existing networks in the target area. The processing module, based on these reports, determines the path loss and antenna gain difference between the existing networks and the network to be built in the target area. The processing module also processes the measurement reports of the existing networks based on the path loss and antenna gain difference to obtain measurement reports for the network to be built. Furthermore, the processing module determines pre-assessment information based on the measurement reports of the network to be built, which indicates the demand for the network to be built in the target area.

[0016] Thirdly, this application provides a device for pre-evaluating the effectiveness of network construction. The device includes a processor and a memory coupled together. The memory is used to store one or more programs, which include computer-executable instructions. When the device for pre-evaluating the effectiveness of network construction is running, the processor executes the computer-executable instructions stored in the memory to implement the method for pre-evaluating the effectiveness of network construction as described in the first aspect or any optional method in the first aspect.

[0017] Fourthly, this application provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the method for pre-evaluating the network construction effect described in the first aspect or any optional method in the first aspect.

[0018] Fifthly, this application provides a computer program product applied to a server. The computer program product includes computer instructions, which, when executed on the server, enable the server to implement the method for pre-evaluating the network construction effect described in the first aspect or any optional method in the first aspect.

[0019] The technical problems that can be solved and the technical effects that can be achieved by the network construction effect pre-evaluation device, equipment, computer storage medium or computer program product can be referred to the technical problems and technical effects solved in the first aspect above, and will not be repeated here. Attached Figure Description

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

[0021] Figure 2 A flowchart illustrating a method for pre-evaluating the effectiveness of network construction, provided in an embodiment of this application;

[0022] Figure 3 A flowchart illustrating another method for pre-evaluating network construction effectiveness provided in an embodiment of this application;

[0023] Figure 4A flowchart illustrating another method for pre-evaluating network construction effectiveness provided in an embodiment of this application;

[0024] Figure 5 A flowchart illustrating another method for pre-evaluating network construction effectiveness provided in an embodiment of this application;

[0025] Figure 6 A flowchart illustrating another method for pre-evaluating network construction effectiveness provided in an embodiment of this application;

[0026] Figure 7 A flowchart illustrating another method for pre-evaluating network construction effectiveness provided in an embodiment of this application;

[0027] Figure 8 A schematic diagram of the structure of a pre-evaluation device for network construction effectiveness provided in an embodiment of this application;

[0028] Figure 9 A schematic diagram of the structure of a pre-evaluation device for network construction effectiveness provided in an embodiment of this application;

[0029] Figure 10 A conceptual partial view of a computer program product provided for an embodiment of this application. Detailed Implementation

[0030] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0031] In this article, the character " / " generally indicates that the objects before and after it are in an "or" relationship. For example, A / B can be understood as A or B.

[0032] The terms “first” and “second” in the specification and claims of this application are used to distinguish different objects, rather than to describe a specific order of objects.

[0033] Furthermore, the terms "comprising" and "having," and any variations thereof, used in the description of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or modules is not limited to the steps or modules listed, but may optionally include other steps or modules not listed, or may optionally include other steps or modules inherent to such process, method, product, or device.

[0034] Furthermore, in the embodiments of this application, the words "exemplary" or "for example" are used to indicate that they are examples, illustrations, or descriptions. Any embodiment or design that is described as "exemplary" or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or design options. Specifically, the use of the words "exemplary" or "for example" is intended to present concepts in a concrete manner.

[0035] Before providing a detailed description of the method for pre-evaluating the network construction effect provided in the embodiments of this application, the implementation environment and application scenarios of the embodiments of this application will be introduced first.

[0036] First, the application scenarios of the embodiments of this application will be introduced.

[0037] Network construction effectiveness pre-assessment is an indispensable and crucial step before deploying new networks and their infrastructure. It provides operators and network service providers with a forward-looking perspective, enabling them to fully grasp the expected performance of core elements such as network performance and coverage through in-depth analysis and prediction before formal construction begins.

[0038] Traditional wireless network analysis, when conducting a preliminary assessment of the network construction effect, is based on the operator collecting the corresponding MR (Mobile Location) data for the area to be constructed. This data is used to evaluate the network service quality of the area before network construction, determine the network demand of the area, and thus achieve a preliminary assessment of the network construction effect.

[0039] In other words, the planning and construction of wireless base stations can utilize the wireless coverage field strength information reported by MR combined with location information to accurately assess the existing network basic coverage performance, identify coverage gaps or weak coverage areas, and fill coverage gaps through blind spot construction to achieve the goal of network optimization.

[0040] However, MR data has certain drawbacks. Within the same grid, it can only obtain coverage information for cells belonging to the same operator, and cannot obtain coverage information for cells belonging to different operators. Furthermore, traditional wireless network analysis mainly relies on backend network management key performance indicators (KPIs) collection and analysis, drive tests (DT), call quality tests (CQT), and MR data. The data in these analytical methods largely comes from their respective operators, and traditional testing methods such as DT drive tests and CQT tests select relatively fixed routes or locations for testing. Therefore, the data has the limitation of a single operator and cannot comprehensively simulate the user's real-world usage environment and scenarios.

[0041] In summary, since the network type (such as frequency band, mobile communication network type, operator) corresponding to the collected MR may differ from the network type to be constructed, it cannot provide an accurate reference for assessing the network service quality of network construction, thus affecting the determination of network demand in the area to be constructed and reducing the accuracy of the pre-assessment of network construction effectiveness.

[0042] To address the aforementioned issues, this application provides a method for pre-evaluating network construction effectiveness. This method is applied to scenarios involving the pre-evaluation of network construction effectiveness. Based on path loss (PL) and antenna gain difference (AGD) between different networks, this application can eliminate discrepancies in measurement reports from different networks. Furthermore, before the network to be constructed is completed in the area to be constructed, the measurement reports of the network to be constructed after construction are simulated based on the measurement reports of other networks in the area. This provides an accurate reference for the pre-evaluation of the network service quality after construction and determines the demand for the network in the area to be constructed. Therefore, the accuracy of the pre-evaluation of network construction effectiveness can be improved.

[0043] The implementation environment of the embodiments of this application is described below.

[0044] like Figure 1 The diagram shown is a schematic of a communication system provided in an embodiment of this application. The communication system may include: a pre-evaluation device 101 and at least one acquisition device (such as acquisition device 102 or acquisition device 103). The pre-evaluation device 101 may be wired / wirelessly connected to the acquisition device 102 or acquisition device 103.

[0045] Specifically, the acquisition device 102 can collect measurement reports of the networks served in the area to be constructed and upload the collected measurement reports to the pre-evaluation device 101. Then, the pre-evaluation device 101 can receive the measurement reports from the acquisition device 102 and modify the measurement reports based on the path loss and antenna gain difference between the network to be constructed and the network served by the acquisition device 102. Based on the modified measurement reports, the pre-evaluation device 101 determines the demand for the network to be constructed in the area to be constructed, thereby pre-evaluating the network construction effect in the area to be constructed.

[0046] Optionally, the network to be built can be a 5G low-frequency network. Due to the characteristics of lower electromagnetic spectrum, stronger wall penetration, less spatial loss over long distances, and stronger coverage, operators consider steeply lower frequency bands as "golden frequency bands," and these "golden frequency bands" vary from operator to operator. However, low-frequency networks generally have smaller bandwidth resources, and their service experience is far inferior to the main 5G mid-frequency network, leading to situations where there are many users clustered together or resource congestion, resulting in limited user service experience. Therefore, in high-low frequency networking scenarios, low-frequency networks are usually set as a lower priority; that is, when the main frequency band coverage is insufficient, the network will guide users to access the 5G low-frequency network through interoperability configuration. Therefore, how to pre-assess the 5G network before its construction, and thus build a targeted 5G low-frequency foundation network, has become a key issue that operators need to solve. The 5G low-frequency network can be used as the network to be built, thereby effectively enhancing network coverage and improving the experience for edge users.

[0047] Similarly, the acquisition device 103 can acquire measurement reports of the networks served in the area to be constructed and upload the acquired measurement reports to the pre-evaluation device 101. Then, the pre-evaluation device 101 can receive the measurement reports from the acquisition device 103 and modify the measurement reports based on the path loss and antenna gain difference between the network to be constructed and the network served by the acquisition device 103. Based on the modified measurement reports, the pre-evaluation device 101 determines the demand for the network to be constructed in the area to be constructed, thereby pre-evaluating the network construction effect of the network to be constructed in the area.

[0048] Optionally, in this embodiment of the application, the network served by the data acquisition device 102 and the network served by the data acquisition device 103 can be the same network, or the network served by the data acquisition device 102 and the network served by the data acquisition device 103 can be two different networks.

[0049] It should be noted that the embodiments of this application do not limit the pre-evaluation device (i.e., pre-evaluation device 101) and the data acquisition device (i.e., data acquisition device 102 and data acquisition device 103). For example, the pre-evaluation device can be a server, and the data acquisition device can be a base station. Another example is that the pre-evaluation device can be a terminal, and the data acquisition device can be a server. Yet another example is that the pre-evaluation device can be a base station, and the data acquisition device can be a core network element.

[0050] The server can be a single physical server or a server cluster consisting of multiple servers. Alternatively, the server cluster can be a distributed cluster. Alternatively, the server can be a cloud server. This application does not limit the specific implementation of the server.

[0051] The terminal can be a mobile phone, tablet computer, desktop computer, laptop computer, handheld computer, notebook computer, ultra-mobile personal computer (UMPC), netbook, or other device with sending and receiving functions. This application does not impose any special restrictions on the specific form of the terminal. It can interact with the user through one or more methods such as keyboard, touchpad, touch screen, remote control, voice interaction, or handwriting device.

[0052] Base stations can include various forms, such as macro base stations, micro base stations (also known as small stations), relay stations, and access points. Specifically, they can be: access points (APs) in Wireless Local Area Networks (WLANs), base stations (BTSs) in Global System for Mobile Communications (GSM) or Code Division Multiple Access (CDMA), base stations (NodeBs, NBs) in Wideband Code Division Multiple Access (WCDMA), evolved base stations (eNBs or eNodeBs) in LTE, relay stations or access points, and base stations in future 6th Generation Mobile Communication Technology (6G) networks or future Public Land Mobile Network (PLMN) networks, etc.

[0053] Core network elements can include various network functions, such as access and mobility management function (AMF), session management function (SMF), user plane function (UPF), policy control function (PCF), unified data management (UDM), location management function (LMF), etc.

[0054] After introducing the application scenarios and implementation environment of the embodiments of this application, the pre-evaluation method for network construction effect provided by the embodiments of this application will be described in detail below in conjunction with the above implementation environment.

[0055] The methods in the following embodiments can all be implemented in the above application scenarios and implementation environments. The embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0056] Figure 2 This is a flowchart illustrating a method for pre-evaluating the effectiveness of network construction, as provided in an embodiment of this application. Figure 2 As shown, the method may include: S201-S204.

[0057] S201. Obtain measurement reports of the networks already established in the target area.

[0058] The target area is the area where a new network (i.e., the network to be built) needs to be constructed.

[0059] For example, if region A has completed the construction of a 4G network but has not built a 5G network, then the 5G network is the network to be built, and region A is the target region.

[0060] It should be noted that the existing network is not limited in this embodiment. For example, the existing network can be a 4G low-frequency network. Another example is a 5G low-frequency network operated by a certain operator. Yet another example is a 4G mid-frequency network.

[0061] In this embodiment of the application, the network to be built and the network already built are two different networks, that is, the network type (such as frequency band, mobile communication network type, operator) corresponding to the network to be built is different from the network type corresponding to the network already built.

[0062] For example, the network to be built is a 5G network, and the network already built is a 4G network. Another example is that the network to be built is a 5G low-frequency network, and the network already built is a 4G low-frequency network. Yet another example is that the network to be built is operator A's 5G low-frequency network, and the network already built is operator B's 5G low-frequency network.

[0063] As one possible implementation, the pre-evaluation device can interact with the base station corresponding to the established network to obtain the measurement report of the established network collected by the base station.

[0064] As another possible implementation, the pre-evaluation device can interact with the server to obtain measurement reports of the constructed network uploaded by the base stations corresponding to the constructed network to the server.

[0065] S202. Based on the measurement report of the existing network, determine the path loss and antenna gain difference between the existing network and the network to be built in the target area.

[0066] Among them, the path loss between the established network and the network to be built is used to indicate the deviation between the energy attenuation corresponding to the established network and the energy attenuation corresponding to the network to be built during wireless signal transmission.

[0067] The antenna gain difference between an existing network and a network to be built is used to measure the deviation between the antennas of the existing network and the antennas of the network to be built in a specific direction in terms of their ability to transmit or receive signals.

[0068] As one possible approach, for the path loss between an existing network and a network to be built, the pre-evaluation device can determine the path loss between the existing network and the network to be built based on the frequency of the network to be built, the frequency of the existing network in the measurement report of the existing network, and the distance between the base station corresponding to the existing network and the target area.

[0069] As one possible design, the path loss between the existing network and the network to be built can be expressed by the following formulas 1, 2 and 3.

[0070] PL f =[46.3+33.9*LOG(f)-13.82*LOG(25)-(1.1*LOG(f)-0.7)*1.5-(1.56*LOG(f)-0.8)+(44.9-6.55*LOG(25))*LOG(D)+3] Formula 1.

[0071] PL f′ =[46.3+33.9*LOG(f′)-13.82*LOG(25)-(1.1*LOG(f′)-0.7)*1.5-(1.56*LOG(f′)-0.8)+(44.9-6.55*LOG(25))*LOG(D)+3] Formula 2.

[0072] PL f-f′ =PL f -PL f′ Formula 3.

[0073] Where f is the frequency of the existing network, f′ is the frequency of the network to be built, D is the distance between the base station corresponding to the existing network and the target area (or the center point of the target area), and PLf2 For the path loss of the established network, PL f1 This refers to the path loss of the network to be built.

[0074] It should be noted that f and f′ are calculated using the COST-231Hata model (a model used to predict the propagation loss of radio signals in urban environments). For other frequency bands, the link budget model used in the actual engineering simulation can be used for calculation. For example, 3.5 GHz new radio (NR) / 2.1 GHz NR can use either the 38.901 urban macro-cellular (Uma) model (a model used to simulate the propagation characteristics of wireless signals in urban macro base station scenarios) or the 36.873 Uma model. These two Uma model versions are different.

[0075] The following examples illustrate the path loss between existing and planned networks, using the different network types mentioned above as examples.

[0076] If the existing network uses a 4G low-frequency network (i.e., f = f2), and the network to be built uses a 5G low-frequency network (i.e., f′ = f1), then PL f-f′ The antenna gain difference between 4G low-frequency network points and 5G low-frequency network points can be expressed as PL. f2-f1 .

[0077] If the existing network uses the 5G low-frequency network frequency of operator B (i.e., f = f3), and the network to be built uses the 5G low-frequency network frequency of operator A (i.e., f′ = f1), then PL f-f′ The antenna gain difference between the 5G low-frequency network frequency of operator B and the 5G low-frequency network frequency of operator A can be expressed as PL. f3-f1 .

[0078] If the existing network uses 4G mid-band frequencies (i.e., f = f4), and the network to be built uses 5G low-band frequencies (i.e., f′ = f1), then PL f-f′ The antenna gain difference between the 4G intermediate frequency network and the 5G low frequency network can be expressed as PL. f4-f1 .

[0079] Optionally, for the antenna gain difference between the established network and the network to be built, the pre-evaluation device can determine the antenna gain difference between the established network and the network to be built based on the frequency of the network to be built and the frequency of the established network in the measurement report of the established network.

[0080] Where f represents the frequency points of the existing network, and f′ represents the frequency points of the network to be built. AG f-f′ The difference in antenna gain between the existing network and the network to be built, and AGf-f′ Calculations are performed based on actual engineering parameter data of the target area.

[0081] For example, if the existing network uses 4G low-frequency network points (i.e., f = f2), and the network to be built uses 5G low-frequency network points (i.e., f′ = f1), then AG f-f′ The antenna gain difference between 4G low-frequency network points and 5G low-frequency network points can be expressed as AG. f2-f1 .

[0082] If the existing network uses the 5G low-frequency network frequency of operator B (i.e., f = f3), and the network to be built uses the 5G low-frequency network frequency of operator A (i.e., f′ = f1), then AG f-f′ The antenna gain difference between the 5G low-frequency network frequencies of operator B and operator A can be expressed as AG. f3-f1 .

[0083] If the existing network uses 4G mid-frequency bands (i.e., f = f4), and the network to be built uses 5G low-frequency bands (i.e., f′ = f1), then AG f-f′ The antenna gain difference between the 4G intermediate frequency network and the 5G low frequency network can be expressed as AG. f4-f1 .

[0084] S203. Based on path loss and antenna gain difference, the measurement report of the established network is processed to obtain the measurement report of the network to be built.

[0085] As one possible implementation, the pre-evaluation device can determine a first correction factor for processing the test report based on path loss and antenna gain difference. Then, the pre-evaluation device can process the measurement report of the already constructed network based on the first correction factor to obtain the measurement report of the network to be constructed.

[0086] It should be noted that the embodiments of this application do not limit the mathematical relationship between the first correction factor and the path loss and antenna gain difference. For example, the first correction factor is equal to the sum of the path loss and the antenna gain difference. Another example is that the first correction factor is equal to the product of the path loss and the antenna gain difference. Yet another example is that the first correction factor is equal to the difference between the path loss and the antenna gain difference.

[0087] In this embodiment of the application, during the process of the pre-evaluation device processing the measurement report of the constructed network based on the first correction factor, the pre-evaluation device can process any index value in the measurement report of the constructed network with the first correction factor based on a preset calculation method.

[0088] It should be noted that the embodiments of this application do not limit the preset calculation method. For example, the preset calculation method can be a method for calculating the difference. Another example is a method for calculating the sum. Yet another example is a method for calculating the product.

[0089] Optionally, during the process of the pre-evaluation device processing any index value and the first correction factor in the measurement report of the constructed network based on the preset calculation method, the pre-evaluation device can process each index value and the first correction factor in the measurement report of the constructed network based on the preset calculation method corresponding to each index in the measurement report of the constructed network.

[0090] For example, a measurement report may include: Indicator A, Indicator B, and Indicator C, where the value of Indicator A is 1, the value of Indicator B is 2, and the value of Indicator C is 3. The preset calculation method for Indicator A is a difference calculation, the preset calculation method for Indicator B is a summation calculation, and the preset calculation method for Indicator C is a product calculation. If the first correction factor is 0.5, then in the processed measurement report, the value of Indicator A is 0.5 (or -0.5), the value of Indicator B is 2.5, and the value of Indicator C is 1.5.

[0091] S204. Based on the measurement report of the network to be built, determine the pre-assessment information.

[0092] Among them, the pre-assessment information is used to indicate the degree of need for the network to be built in the target area.

[0093] It should be noted that the process of determining pre-assessment information based on the measurement report of the network to be built can refer to the existing technology for determining network service quality in conjunction with the measurement report to reflect the degree of network demand in the network service area, which will not be elaborated here.

[0094] The technical solution provided by the above embodiments brings at least the following beneficial effects: By obtaining measurement reports of the existing network in the target area, the path loss and antenna gain difference between the existing network and the network to be built in the target area are determined. Based on the path loss and antenna gain difference, the measurement reports of the existing network are processed to obtain the measurement report of the network to be built. Then, pre-evaluation information is determined, which is used to indicate the demand for the network to be built in the target area. That is, based on the path loss and antenna gain difference between different networks, the differences between the measurement reports of different networks can be eliminated. Therefore, before the network to be built is completed in the target area, the measurement reports of the network to be built after completion are simulated based on the measurement reports of other networks in the target area, providing an accurate reference for the pre-evaluation of the network service quality after the network to be built, and determining the demand for the network to be built in the target area. Therefore, the accuracy of the pre-evaluation of the network construction effect can be improved.

[0095] It should be noted that in evaluating the effectiveness of network construction in a region, it is necessary to comprehensively consider the user experience of each user device. This means refining the evaluation object from the entire region to each user device, thereby increasing the reference value of the evaluation results for the effectiveness of network construction.

[0096] In some embodiments, such as Figure 3 As shown, prior to S203, the pre-evaluation method for the network construction effect may also include: S301.

[0097] S301. Determine multiple first sampling points in the target area.

[0098] The sampling point is the spatial location of the user equipment using the network, and the network type of the first sampling point is the established network.

[0099] It should be noted that in this embodiment of the disclosure, the number of established networks can be one, or the number of established networks can be at least two. One established network corresponds to multiple first sampling points.

[0100] For example, the target area includes: user equipment A, user equipment B and user equipment C, and the network type of user equipment A and the network type of user equipment B are both operator A (i.e., the network is already built), and the network type of user equipment C is operator B (i.e., the network is already built). Then, the multiple first sampling points corresponding to operator A include the location of user equipment A and the location of user equipment B, and the multiple first sampling points corresponding to operator B include the location of user equipment C.

[0101] The following explanation uses the number of networks already built in the target area as a unit.

[0102] As one possible implementation, the pre-evaluation device can acquire DT test data and CQT test data of the established network in the target area to determine multiple first sampling points in the target area.

[0103] It should be noted that the DT test data and CQT test data are obtained by conducting DT tests and CQT tests on preset routes or preset locations. Therefore, the first sampling point is the sampling point in the preset route or preset location corresponding to the DT test and CQT test in the target area.

[0104] In other words, the first sampling point determined by DT test and CQT test is the sampling point obtained by simulating user equipment test in a preset route or preset location.

[0105] In some embodiments, the measurement report may include: the reference signal received power (RSRP) at the sampling point.

[0106] In other words, the measurement report can include the reference signal reception power of user equipment at different locations to the communication network.

[0107] In this embodiment of the disclosure, S203 may include: S302.

[0108] S302. Based on path loss and antenna gain difference, the reference signal received power of each of the multiple first sampling points is processed to obtain the reference signal received power of multiple second sampling points in the target area.

[0109] In this system, one second sampling point corresponds to one first sampling point, the network type of the second sampling point is the network to be built, and the reference signal received power of the second sampling point is equal to the processed reference signal received power of the corresponding first sampling point.

[0110] In other words, by correcting the RSRP of the first sampling point, the network type of the first sampling point is transformed from an existing network to a network to be built, thus obtaining the RSRP of the second sampling point corresponding to the network to be built.

[0111] As one possible implementation, in conjunction with the above embodiments, the first correction factor corresponding to the reference signal received power can be the RSRP correction factor, and the RSRP correction factor is the sum of path loss and antenna gain difference. The pre-evaluation device can sum the reference signal received power and the RSRP correction factor at each first sampling point to obtain the reference signal received power at multiple second sampling points.

[0112] It should be noted that since the reference signal received power is affected by the penetration loss of buildings, in the process of determining the RSRP correction factor, the sampling points need to be divided into two categories: indoor sampling points and outdoor sampling points based on the location of different sampling points. The RSRP correction factor corresponding to each first sampling point is determined by combining the penetration loss of the building where the indoor sampling point is located on the reference signal received power.

[0113] As one possible design, the reference signal received power at the second sampling point can be expressed by the following formulas four and five.

[0114]

[0115]

[0116] Among them, RSRP f-f′ RSRP correction factor This is the RSRP correction factor corresponding to the outdoor sampling point. Penetration is the RSRP correction factor corresponding to the indoor sampling points. f-f′ RSRP represents the penetration loss of the building to the received power of the reference signal, RSRP is the received power of the reference signal at the first sampling point, and RSRP′ is the received power of the reference signal at the second sampling point.

[0117] It should be noted that the penetration loss of different frequency bands in different scenarios can be referred to Table 1 below.

[0118] Table 1. Penetration loss at different frequency bands under different scenarios (unit: dB)

[0119] 700MHz 15 13.5 8.5 5.5 800MHz 15.2 13.7 8.7 5.7 900MHz 15.5 14 9 6 1800MHz 18 16 11 8 2.1GHz 19 17 12 9 2.6GHz 21 19 13.5 10.5 3.5GHz 23 21 15.5 12.5 4.9GHz 26 23 17 14

[0120] The following examples, based on the existing networks of different network types, illustrate the reference signal received power of the second sampling point of indoor sampling points and the reference signal received power of the second sampling point of outdoor sampling points between the existing network and the network to be built.

[0121] For example, if the existing network uses 4G low-frequency network points (i.e., f = f2), and the network to be built uses 5G low-frequency network points (i.e., f′ = f1), then PL f-f′ The antenna gain difference between 4G low-frequency network points and 5G low-frequency network points can be expressed as PL. f2-f1 AG f-f′ The antenna gain difference between 4G low-frequency network points and 5G low-frequency network points can be expressed as AG. f2-f1 RSRP f-f′ The RSRP correction factor between 4G low-frequency network points and 5G low-frequency network points can be expressed as RSRP. f2-f1 It is divided into two types: indoor sampling points and outdoor sampling points.

[0122] For outdoor sampling points, use This represents the RSRP correction factor corresponding to outdoor sampling points between 4G low-frequency network points and 5G low-frequency network points, i.e. So, The received power of the reference signal at the second sampling point, categorized as an outdoor sampling point, between 4G low-frequency network points and 5G low-frequency network points can be expressed as: For indoor sampling points, use This represents the RSRP correction factor corresponding to indoor sampling points between 4G low-frequency network points and 5G low-frequency network points, i.e. So, The received power of the reference signal at the second sampling point, categorized as an indoor sampling point, between 4G low-frequency network points and 5G low-frequency network points can be expressed as:

[0123] For example, if the existing network is a 5G low-frequency network of operator B (i.e., f = f3), and the network to be built is a 5G low-frequency network of operator A (i.e., f′ = f1), then PL f-f′ The antenna gain difference between the 5G low-frequency network frequency of operator B and the 5G low-frequency network frequency of operator A can be expressed as PL. f3-f1 AG f-f′ The antenna gain difference between the 5G low-frequency network frequency of operator B and the 5G low-frequency network frequency of operator A can be expressed as AG. f3-f1 RSRP f-f′ The RSRP correction factor between the 5G low-frequency network frequency points of operator B and the 5G low-frequency network frequency points of operator A can be expressed as RSRP. f3-f1 It is divided into two types: indoor sampling points and outdoor sampling points.

[0124] For outdoor sampling points, use This represents the RSRP correction factor corresponding to the outdoor sampling points between the 5G low-frequency network frequency points of operator B and the 5G low-frequency network frequency points of operator A, i.e. So, The reference signal received power at the second sampling point (category: outdoor sampling point) between the 5G low-frequency network frequency points of operator B and the 5G low-frequency network frequency points of operator A can be expressed as: For indoor sampling points, use This represents the RSRP correction factor for indoor sampling points between operator B's 5G low-frequency network frequency and operator A's 5G low-frequency network frequency. So, The reference signal received power at the second sampling point, categorized as an indoor sampling point, between the 5G low-frequency network frequency points of operator B and the 5G low-frequency network frequency points of operator A can be expressed as:

[0125] For example, if the existing network is a 4G mid-frequency network (i.e., f = f4), and the network to be built is a 5G low-frequency network (i.e., f′ = f1), then PL f-f′ The antenna gain difference between the 4G intermediate frequency network and the 5G low frequency network can be expressed as PL. f4-f1 AG f-f′ The antenna gain difference between the 4G intermediate frequency network and the 5G low frequency network can be expressed as AG. f4-f1 RSRP f-f′The RSRP correction factor between 4G mid-frequency network points and 5G low-frequency network points can be expressed as RSRP. f4-f1 It is divided into two types: indoor sampling points and outdoor sampling points.

[0126] For outdoor sampling points, use This represents the RSRP correction factor corresponding to outdoor sampling points between 4G mid-frequency network points and 5G low-frequency network points, i.e. So, The received power of the reference signal at the second sampling point, categorized as an outdoor sampling point, between the 4G intermediate frequency network and the 5G low frequency network can be expressed as: For indoor sampling points, use This represents the RSRP correction factor corresponding to indoor sampling points between 4G intermediate frequency network points and 5G low frequency network points, i.e. So, The received power of the reference signal at the second sampling point, categorized as an indoor sampling point, between the 4G intermediate frequency network and the 5G low frequency network can be expressed as:

[0127] Understandably, by correcting the RSRP of the first sampling point, the network type of the first sampling point can be simulated from an existing network to a network to be built, thus obtaining the RSRP of the second sampling point corresponding to the network to be built. This allows for the acquisition of the reference signal received power of user equipment at different locations in the target area for the network to be built before its construction is completed. This enables a comprehensive consideration of each user equipment's network usage experience, refining the evaluation object from the entire area to each user equipment. This provides an accurate reference for subsequent evaluation of the demand for the network to be built in the target area, thereby improving the reference value of the evaluation results for the network construction effectiveness.

[0128] In some embodiments, for the process of determining multiple first sampling points in the target area (i.e., S301) described above, the pre-evaluation device can acquire OTT data of each user device in the target area and determine multiple first sampling points in the target area based on the OTT data of each user device.

[0129] The pre-evaluation device acquires all OTT data (i.e., OTT sampling points) in the target area and determines the OTT data corresponding to each user device based on the user IMEI data in each OTT data. Next, for each user device, based on the location and time information in each OTT data corresponding to the user device, a seventh sampling point for the user device in the target area is determined; one seventh sampling point corresponds to at least one OTT data. Then, based on the network type in the OTT data corresponding to each seventh sampling point, multiple first sampling points are selected from the multiple seventh sampling points in the target area.

[0130] It should be noted that the network types in at least one OTT data corresponding to a seventh sampling point may be different. Therefore, in the process of selecting multiple first sampling points from multiple seventh samples of the target area based on the network type in the OTT data corresponding to each seventh sampling point, the pre-evaluation device can take the network type with the highest frequency of occurrence in at least one OTT data corresponding to the seventh sampling point as the network type corresponding to the seventh sampling point.

[0131] For example, if all OTT data in the target area includes: OTT data 1, OTT data 2 and OTT data 3, and OTT data 1 is the OTT data of user device A at location 1 at time 1, OTT data 2 is the OTT data of user device A at location 1 at time 2, and OTT data 3 is the OTT data of user device A at location 2 at time 1, then the sampling point of user device A at location 1 (i.e. the seventh sampling point) corresponds to OTT data 1 and OTT data 2, and the sampling point of user device A at location 2 (i.e. the seventh sampling point) corresponds to OTT data 2.

[0132] Optionally, during the process of the pre-evaluation device selecting the network type with the highest frequency of occurrence in at least one OTT data corresponding to the seventh sampling point as the network type corresponding to the seventh sampling point, the pre-evaluation device may prioritize determining the network standard (i.e., mobile communication network type, such as 4G, 5G, 5G low frequency, 5G mid frequency) in the OTT data, and select the operator with the highest frequency of occurrence in the OTT data under the network standard corresponding to the network to be built as the assigned operator of the corresponding seventh sampling point, thereby determining the network type corresponding to the seventh sampling point. Alternatively, if the network standard in at least one OTT data corresponding to the seventh sampling point is different from the network standard corresponding to the network to be built, the operator with the highest frequency of occurrence in the OTT data under the same network standard may be selected as the assigned operator of the corresponding seventh sampling point, thereby determining the network type corresponding to the seventh sampling point.

[0133] For example, the OTT data corresponding to the seventh sampling point includes: OTT data 1, OTT data 2, OTT data 3, OTT data 4, OTT data 5, OTT data 6, and OTT data 7. Specifically, the network type of OTT data 1 is the 5G low-frequency network of operator A; the network type of OTT data 2 is the 5G low-frequency network of operator A; the network type of OTT data 3 is the 4G network of operator B; the network type of OTT data 4 is the 5G low-frequency network of operator B; the network type of OTT data 5 is the 5G mid-frequency network of operator C; the network type of OTT data 6 is the 4G network of operator B; and the network type of OTT data 7 is the 4G network of operator B. If the network standard corresponding to the network to be constructed is 5G low-frequency, then the network type corresponding to the seventh sampling point is the 5G low-frequency network of operator A. If the network standard corresponding to the network to be constructed is 5G high-frequency, then the network type corresponding to the seventh sampling point is the 4G network of operator B.

[0134] In other words, all user IMEI data in the OTT data is deduplicated, and all OTT sampling points generated for that user are selected. The operator name ("OPERATOR" field) (i.e., network type) that appears most frequently among these network sampling points is recorded as the user's affiliated operator. Alternatively, if no sampling point with a predefined network type (such as 5G) appears among these OTT sampling points, the operator name that appears most frequently among the remaining sampling points is recorded as the user's affiliated operator.

[0135] Understandably, compared to the first sampling point determined based on DT and CQT test data, OTT data can be directly collected from mobile user terminals, without being limited by the network type of the operator. Therefore, it naturally possesses the characteristic of full network coverage, enabling a comprehensive understanding of the coverage situation. This allows for independent full-scale analysis of wireless networks, as well as competitive analysis across operators. Furthermore, OTT data is collected precisely when the mobile terminal is performing actual services, thus accurately reflecting the user's experience and perception of the environment, resulting in a more objective and realistic picture that is closer to customer experience.

[0136] It should be noted that switching (or simulating) between different network types will affect transmission speed and connection quality. In order to ensure network service quality, user experience, and effective utilization of network resources, and to provide an accurate reference for subsequent evaluation of network construction needs, the following embodiments can be used to obtain data from better sampling points from multiple sampling points for correction.

[0137] In some embodiments, such as Figure 4 As shown, after S301, the pre-evaluation methods for the network construction effect can also include: S401-S402.

[0138] S401. Determine whether the established network is the default network.

[0139] Among them, the impact of switching (or simulating) between the preset network and the network to be built on the transmission speed and connection quality is greater than the preset impact threshold.

[0140] In other words, the switching (or simulation) between the preset network and the network to be built has a significant impact on transmission speed and connection quality.

[0141] As one possible implementation, the pre-evaluation device can store the identifiers of preset networks. The pre-evaluation device can determine whether an existing network is a preset network by comparing the identifier of the existing network with the identifier of the preset network.

[0142] In some embodiments, if the pre-evaluation device determines that the constructed network is not a preset network, the pre-evaluation device may execute S203.

[0143] In other embodiments, if the pre-evaluation device determines that the constructed network is a preset network, the pre-evaluation device may execute S402.

[0144] S402. Based on the first preset received power threshold, at least one third sampling point is selected from multiple first sampling points.

[0145] Among them, the reference signal received power at the third sampling point is less than the first preset received power threshold.

[0146] As one possible implementation, the pre-evaluation device can store a first preset received power threshold. The pre-evaluation device can determine the relationship between the received reference signal power of each of the multiple first sampling points and the first preset received power threshold, and then select the first sampling points whose received reference signal power is greater than the first preset received power threshold as third sampling points, thereby obtaining at least one third sampling point.

[0147] In this embodiment of the disclosure, the pre-evaluation device can execute S203 based on a third sampling point among a plurality of first sampling points. That is, the pre-evaluation device processes the reference signal received power of each third sampling point among at least one third sampling point based on path loss and antenna gain difference to obtain the reference signal received power of a plurality of second sampling points.

[0148] Understandably, by referencing the impact of transmission speed and connection quality during switching (or simulation) between different network types, the RSRP of the third sampling points (i.e., sampling points where RSRP is less than the first preset received power threshold) among multiple first sampling points of the network with significant impact (i.e., the preset network) is corrected. This process transforms the network type of the third sampling point from an existing network to the network to be built, thus obtaining the RSRP of the second sampling point corresponding to the network to be built. This ensures network service quality, user experience, and effective utilization of network resources, providing an accurate reference for subsequent evaluation of network construction needs.

[0149] In some embodiments, the measurement report may also include: signal-to-interference-plus-noise ratio (SINR) and uplink rate (UL) at the sampling points.

[0150] In other words, the measurement report can include the signal-to-interference-plus-noise ratio and uplink speed of user equipment at different locations on the communication network.

[0151] It should be noted that the types of indicators included in the measurement reports for different network types vary (e.g., the measurement report for 4G cells does not include SINR values). This means that the processed measurement report is insufficient to provide a complete evaluation reference for the construction needs of other networks.

[0152] In the embodiments disclosed herein, such as Figure 5 As shown, after S302, the pre-evaluation method for the network construction effect may also include: S501.

[0153] S501. For each second sampling point, determine the signal-to-interference-plus-noise ratio and uplink rate of each second sampling point according to the first operation.

[0154] The first operation may include the following steps: Step 1 and Step 2:

[0155] Step 1: The pre-evaluation device determines the signal-to-interference-plus-noise ratio of the target sampling point based on the reference signal received power of the target sampling point and the reference signal received power of multiple fourth sampling points.

[0156] The target sampling point is any one of the multiple second sampling points, and the fourth sampling point is the sampling point adjacent to the target sampling point among the multiple second sampling points.

[0157] As one possible implementation, the pre-evaluation device stores a second preset received power threshold. Based on the second preset received power threshold, the pre-evaluation device can select multiple fourth sampling points from multiple eighth sampling points adjacent to the target sampling point among multiple second sampling points. The fourth sampling points are the sampling points among the multiple eighth sampling points where the received power of the reference signal is greater than the second preset received power threshold.

[0158] For example, the adjacent sampling points (i.e., the eighth sampling point) of the target sampling point include: sampling point A, sampling point B, sampling point C, and sampling point D, and the RSRP of sampling point A is 1, the RSRP of sampling point B is 2, the RSRP of sampling point C is 3, and the RSRP of sampling point D is 4. If the second preset received power threshold is 2.5, then the multiple fourth sampling points corresponding to the target sampling point include: sampling point C and sampling point D.

[0159] As one possible design, the signal-to-interference-plus-noise ratio at the target sampling point can be expressed by the following formulas six and seven.

[0160]

[0161] PN = 10·log 10 (K·T·W)+NF Formula 7.

[0162] Where SINR is the signal-to-interference-plus-noise ratio at the target sampling point, and RSRP′ i denoted as , where n is the number of fourth sampling points, PN is the receiver white noise constant, K is the Boltzmann constant (i.e., 1.38 × 10⁻²³ J / K), T is the Kelvin temperature (290 K at room temperature), W is the signal bandwidth, and NF is the receiver noise figure.

[0163] It should be noted that for LTE systems, the subcarrier spacing is 15kHz, and the system noise figure NF is 9dB. According to Formula 7, the system noise floor within one subcarrier bandwidth is approximately -123.22dBm, which can be expressed as PN = 10·log 10 (K·T·W)+NF=10(1.38×10-23J / K*290K*15*1000Nz)+NF=-123.22dBm.

[0164] Optionally, for an NR system, with a subcarrier spacing of 30kHz and a system noise figure NF of 10dB, according to Formula 7, the system noise floor within one subcarrier bandwidth is approximately -119.21dBm, which can be expressed as PN = 10·log 10 (K·T·W)+NF=10(1.38×10-23J / K*290K*30*1000Hz)+NF=-119.21dBm.

[0165] Step 2: The pre-evaluation device determines the uplink rate of the target sampling point based on the reference signal received power and the signal-to-interference-plus-noise ratio of the target sampling point.

[0166] As one possible implementation, the pre-evaluation device can process the reference signal received power and signal-to-interference-plus-noise ratio of the target sampling point based on a preset calculation method to obtain the uplink rate of the target sampling point.

[0167] Optionally, the preset calculation method between uplink rate and RSRP and SINR can be obtained by training sample data composed of DT test data and CQT test data, and the preset calculation method is different for different scenarios (i.e. indoor and outdoor).

[0168] For example, the pre-evaluation device can acquire DT test data and CQT test data of the established network in the target area, and obtain multi-input fitting curves of the reference signal received power, signal-to-interference-plus-noise ratio and uplink rate of the target sampling point in both outdoor and indoor scenarios through training.

[0169] As one possible design, the uplink rate of the target sampling point can be represented by Equations 8, 9, and 10 of the following propagation model weighted algorithm.

[0170] THP UL，室外 =f UL，室外 (RSRP′,SINR)+C UL，室外 Formula 8.

[0171] THP UL，室内 =f UL，室内 (RSRP′,SINR)+C UL，室内 Formula Nine.

[0172] f(X,Y)=α X *Ln(X)+α Y *Ln(Y)+β Formula 10.

[0173] Where RSRP′ is the reference signal received power at the second sampling point (e.g., indoor or outdoor), and SINR is the signal-to-interference-plus-noise ratio at the target sampling point (e.g., indoor or outdoor). C UL，室外 C is the uplink constant under outdoor conditions. UL，室内 THP is the uplink constant under indoor conditions. UL，室外 THPU is the uplink rate of the target sampling point in an outdoor scene. UL，室内Let f be the uplink rate of the target sampling point in an indoor scene, α and β represent the best-fit values ​​of the reference signal received power, signal-to-interference-plus-noise ratio, and uplink rate of the target sampling point, respectively. UL，室外 (RSRP, SINR) represents the mathematical relationship between the received reference signal power and the signal-to-interference-plus-noise ratio at the target sampling point in an outdoor scene. UL，室内 (RSRP, SINR) represents the mathematical relationship between the received power of the reference signal and the signal-to-interference-plus-noise ratio at the target sampling point in an indoor scene.

[0174] The following examples illustrate the uplink rates of the target sampling points in different scenarios (such as indoors and outdoors), based on the reference signal received power and the signal-to-interference-plus-noise ratio of the target sampling points.

[0175] For example, in conjunction with the above embodiments, the existing network uses 4G low-frequency network frequencies, and the network to be built uses 5G low-frequency network frequencies. For outdoor sampling points, f UL，室外 (RSRP, SINR) is a mathematical relationship between the reference signal received power and the signal-to-interference-plus-noise ratio of a target sampling point classified as an outdoor sampling point between 4G low-frequency network points and 5G low-frequency network points. RSRP is the reference signal received power of the target sampling point classified as an outdoor sampling point between 4G low-frequency network points and 5G low-frequency network points, and SINR is the signal-to-interference-plus-noise ratio of the target sampling point classified as an outdoor sampling point between 4G low-frequency network points and 5G low-frequency network points.

[0176] For indoor sampling points, use f UL，室内 (RSRP, SINR) represents the mathematical relationship between the reference signal received power and the signal-to-interference-plus-noise ratio (SNR) of a target sampling point classified as an indoor sampling point between 4G and 5G low-frequency network points. Specifically, RSRP is the reference signal received power of the target sampling point classified as an indoor sampling point between 4G and 5G low-frequency network points, and SINR is the SNR of the target sampling point classified as an indoor sampling point between 4G and 5G low-frequency network points.

[0177] So, THP UL，室外 THP represents the uplink rate of a target sampling point categorized as an outdoor sampling point between 4G low-frequency network points and 5G low-frequency network points. UL，室内 The uplink rate of the target sampling point, categorized as an indoor sampling point, between 4G low-frequency network points and 5G low-frequency network points.

[0178] For example, combining the above embodiments, the existing network uses the 5G low-frequency network frequency of operator B, and the network to be built uses the 5G low-frequency network frequency of operator A. For outdoor sampling points, f UL，室外(RSRP, SINR) represents the mathematical relationship between the reference received power and the signal-to-interference-plus-noise ratio (SNR) of a target sampling point (classified as an outdoor sampling point) between the 5G low-frequency network points of operator B and the 5G low-frequency network points of operator A. RSRP is the reference received power of the target sampling point (classified as an outdoor sampling point) between the 5G low-frequency network points of operator B and operator A, and SINR is the SNR of the target sampling point (classified as an outdoor sampling point) between the 5G low-frequency network points of operator B and operator A.

[0179] For indoor sampling points, use f UL，室内 (RSRP, SINR) represents the mathematical relationship between the reference received signal power and the signal-to-interference-plus-noise ratio (SNR) of a target sampling point (classified as an indoor sampling point) between the 5G low-frequency network points of operator B and operator A. Specifically, RSRP is the reference received signal power of the target sampling point (classified as an indoor sampling point) between the 5G low-frequency network points of operator B and operator A, and SINR is the SNR of the target sampling point (classified as an indoor sampling point) between the 5G low-frequency network points of operator B and operator A.

[0180] So, THP UL，室外 The uplink rate (THP) of the target sampling point (category: outdoor sampling point) between the 5G low-frequency network frequency points of operator B and the 5G low-frequency network frequency points of operator A. UL，室内 The uplink rate of the target sampling point, categorized as an indoor sampling point, between the 5G low-frequency network frequency points of operator B and the 5G low-frequency network frequency points of operator A.

[0181] For example, in conjunction with the above embodiments, the existing network uses 4G mid-frequency network frequencies, and the network to be built uses 5G low-frequency network frequencies. For outdoor sampling points, f UL，室外 (RSRP, SINR) is a mathematical relationship between the reference signal received power and the signal-to-interference-plus-noise ratio of a target sampling point classified as an outdoor sampling point between 4G intermediate frequency network points and 5G low frequency network points. RSRP is the reference signal received power of the target sampling point classified as an outdoor sampling point between 4G intermediate frequency network points and 5G low frequency network points, and SINR is the signal-to-interference-plus-noise ratio of the target sampling point classified as an outdoor sampling point between 4G intermediate frequency network points and 5G low frequency network points.

[0182] For indoor sampling points, use f UL，室内(RSRP, SINR) represents the mathematical relationship between the reference signal received power and the signal-to-interference-plus-noise ratio (SNR) of a target sampling point classified as an indoor sampling point between a 4G intermediate frequency network and a 5G low frequency network. Specifically, RSRP is the reference signal received power of the target sampling point classified as an indoor sampling point between the 4G intermediate frequency network and the 5G low frequency network, and SINR is the SNR of the target sampling point classified as an indoor sampling point between the 4G intermediate frequency network and the 5G low frequency network.

[0183] So, THP UL，室外 THP represents the uplink rate of a target sampling point categorized as an outdoor sampling point between 4G mid-frequency network points and 5G low-frequency network points. UL，室内 The uplink rate of the target sampling point, which is an indoor sampling point, between 4G mid-frequency network points and 5G low-frequency network points.

[0184] Understandably, by referencing the reference signal received power of the target sampling point and the reference signal received power of multiple fourth sampling points, the signal-to-interference-plus-noise ratio (SNR) of the target sampling point is determined. Then, based on the reference signal received power and SNR of the target sampling point, the uplink rate of the target sampling point is determined. This approach resolves the issue of inconsistencies in the types of indicators included in measurement reports for different network types, enabling the processed measurement reports to provide a comprehensive evaluation reference for the construction needs of other networks.

[0185] It should be noted that after obtaining the measurement reports corresponding to different network types in the area to be constructed, in order to better pre-evaluate the service quality of the network and determine the demand for the network to be constructed in the target area, the data of the second sampling point can be evaluated through the following embodiments.

[0186] In some embodiments, such as Figure 6 As shown, in the pre-evaluation method for the network construction effect, S204 may include: S601-S602.

[0187] S601. Based on the first preset rate threshold, at least one fifth sampling point is selected from multiple second sampling points.

[0188] Among them, the uplink rate of the fifth sampling point is greater than the first preset rate threshold.

[0189] As one possible implementation, the pre-evaluation device can store a first preset rate threshold. The pre-evaluation device can determine the relationship between the uplink rate of each second sampling point and the first preset rate threshold, and select the second sampling points among the multiple second sampling points whose uplink rate is greater than the first preset rate threshold as fifth sampling points, thereby obtaining at least one fifth sampling point.

[0190] For example, the plurality of second sampling points include: sampling point A, sampling point B, and sampling point C, wherein the uplink rate of sampling point A is 1 / 3 megabits per second (Mbps), the uplink rate of sampling point B is 1 / 2 Mbps, and the uplink rate of sampling point C is 2 Mbps. If the first preset rate threshold is 1 Mbps, then sampling point C is the fifth sampling point.

[0191] S602. Determine the pre-evaluation information based on the first ratio between the number of the fifth sampling point and the number of the second sampling point.

[0192] The first ratio is positively correlated with the target area's demand for the network to be built. The target area's demand for the network to be built refers to the degree to which the network in the area to be built meets its requirements in terms of bandwidth rate and coverage.

[0193] In other words, the first ratio is the ratio between the number of second sampling points that satisfy the uplink rate greater than the first preset rate threshold and the total number of second sampling points. Furthermore, the more second sampling points that satisfy the uplink rate greater than the first preset rate threshold, the larger the first ratio, and the higher the degree to which the bandwidth rate of the network to be constructed is satisfied.

[0194] For example, if the number of fifth sampling points is 2 and the number of second sampling points is 4, then the first ratio is If the number of fifth sampling points is 1, then the first ratio is That is, the more fifth sampling points there are, the more second sampling points in the area to be built that meet the first preset rate threshold, the larger the first ratio, and the higher the demand for the network to be built in the target area.

[0195] The following example illustrates the number of fifth sampling points between existing and future networks, using the different network types mentioned above as examples.

[0196] For example, if the existing network uses 4G low-frequency network points (i.e., f = f2), and the network to be built uses 5G low-frequency network points (i.e., f′ = f1), then the number of the fifth sampling points is the total number of the second sampling points whose uplink rate is greater than Threshold1 (i.e., the first preset rate threshold). This can be represented by M. f2-f1 express.

[0197] If the existing network is a 5G low-frequency network of operator B (i.e., f = f3), and the network to be built is a 5G low-frequency network of operator A (i.e., f′ = f1), then the number of the five sampling points is the total number of the second sampling points whose uplink rate is greater than Threshold1, which can be represented by M. f3-f1 express.

[0198] If the existing network uses a 4G mid-frequency network (f = f4), and the network to be built uses a 5G low-frequency network (f′ = f1), then the number of the fifth sampling points is the total number of the second sampling points whose uplink rate is greater than Threshold1. This can be represented by M. f4-f1 express.

[0199] In summary, the number of fifth sampling points is the sum of all second sampling points whose uplink rate is greater than the first preset rate threshold, which can be represented by M. f2-f1 +M f3-f1 +M f4-f1 express.

[0200] Understandably, by determining the ratio of sampling points with better uplink speeds to all sampling points in the area to be built, the user experience of the network in the area to be built can be simulated to predict the service quality of the network in the area after its construction is completed, thereby determining the demand for the network in the area.

[0201] In some embodiments, during the process of determining pre-evaluation information (i.e., S602) based on the first ratio between the number of fifth sampling points and the number of second sampling points, the pre-evaluation device can determine the first network associated with the network to be built in the existing network, and determine the pre-evaluation information based on the number of fifth sampling points, the number of second sampling points, the number of ninth sampling points corresponding to the first network, the number of tenth sampling points among the ninth sampling points whose uplink rate is greater than the third preset rate threshold, and the number of users in the target area of ​​the existing network.

[0202] As one possible design, the pre-evaluation information can be represented by the following formulas eleven, twelve, thirteen, fourteen, and fifteen.

[0203]

[0204]

[0205]

[0206] F1 业务满足度 =[F A +F B +F C Formula Fourteen: 100%

[0207]

[0208] Where M is the number of sampling points in the denominator, and M is the total number of sampling points that satisfy the uplink rate threshold Threshold1 in the numerator. There is network coverage from two operators in this area: Operator A is the local operator, and Operator B is a different operator. The frequency of the 5G low-frequency network to be built in this area is f1. The number of 5G users of Operator A in this target area is N. 运营商A,5G The number of non-5G users of operator A is N. 运营商A,非5G Operator B has N 5G users. 运营商B,5G The number of non-5G users of operator B is N. 运营商B,非5G The number of non-5G users can be the number of 4G users.

[0209] For formula eleven, M f2-f1 This indicates the number of fifth sampling points within the target area when the existing network is a 4G low-frequency network and the network to be built is a 5G low-frequency network. The 5G mid-frequency network is the first network, and M in the numerator... 运营商A,5G中频 This represents the number of tenth sampling points in the ninth sampling point within the first network of target area A of this operator, whose uplink rate is greater than the third preset rate threshold. The M in the denominator... 运营商A，5G中频 This indicates the number of ninth sampling points for operator A. M 运营商A，f2 This indicates the number of second sampling points in the target area when the existing network is a 4G low-frequency network and the network to be built is a 5G low-frequency network. N 运营商A,5G N represents the number of 5G users of operator A within the target area. 运营商A,4G This indicates the number of 4G users of operator A within the target area.

[0210] For formula 12, M f3-f1 This represents the number of fifth sampling points when the target area already has a 5G low-frequency network of a different operator (B) and the network to be built is a 5G low-frequency network of operator A. The 5G mid-frequency network is the first network, and M in the numerator... 运营商A,5G中频 This represents the number of tenth sampling points in the ninth sampling point within the first network of target area A of this operator, whose uplink rate is greater than the third preset rate threshold. The M in the denominator... 运营商A，5G中频 This indicates the number of ninth sampling points for operator A. M 运营商A，f3 N represents the number of second sampling points when the target area already has a 5G low-frequency network of a different operator (B) and the network to be built is a 5G low-frequency network of operator A. 运营商B,5G N represents the number of 5G users of different operator B within the target area. 运营商B,4G This indicates the number of 4G users of different operator B within the target area.

[0211] For formula thirteen, M f4-f1This indicates the number of fifth sampling points within the target area when the existing network is a 4G mid-frequency network and the network to be built is a 5G low-frequency network. The 5G mid-frequency network is the first network, and M in the numerator... 运营商A,5G中频 This represents the number of tenth sampling points in the ninth sampling point within the first network of target area A of this operator, whose uplink rate is greater than the third preset rate threshold. The M in the denominator... 运营商A，5G中频 This indicates the number of ninth sampling points for operator A. M 运营商A，f4 This indicates the number of second sampling points in the target area when the existing network is a 4G mid-frequency network and the network to be built is a 5G low-frequency network. N 运营商B,5G N represents the number of 5G users of different operator B within the target area. 运营商B,4G This indicates the number of 4G users of different operator B within the target area.

[0212] For formula fourteen, F1 业务满足度 This indicates the level of business satisfaction under three scenarios within the target area.

[0213] For formula 15, Δ 业务满足度 This indicates the estimated improvement in business satisfaction across three scenarios within the target area.

[0214] It should be noted that, in order to achieve accurate pre-assessment of the network construction effect of 5G low-frequency network points, priority is given to areas with the most significant improvement in effect, so as to rationally guide network investment efficiency and improve the accuracy of network planning. The above embodiments propose three scenarios for the target area. In Scenario 1, the target area has 4G low-frequency network coverage, and frequency rotation is considered based on existing site resources to form a new 5G low-frequency coverage base network. In Scenario 2, the target area has 5G low-frequency network coverage from different operators. In Scenario 3, the target area does not have 4G low-frequency network coverage, but has 4G mid-frequency network coverage.

[0215] It should be noted that there are no restrictions on the type of network used for the preliminary evaluation of network construction effectiveness. For example, the network used for the preliminary evaluation of network construction effectiveness can be a 5G low-frequency network, or a 5G mid-frequency network, or even a 4G low-frequency network.

[0216] Understandably, by determining the service satisfaction level and the estimated improvement in service satisfaction in the area to be built, the problem that wireless coverage data is difficult to accurately assess the actual service capabilities can be solved. By strongly correlating wireless coverage data and service perception, a precise and reasonable service carrying capacity assessment model can be formed to predict the service quality of the area to be built after the network is completed, thereby determining the demand for the network in the area to be built.

[0217] It should be noted that after obtaining the measurement reports corresponding to different network types in the area to be constructed, in order to accurately determine the specific location information of the target sampling points, better conduct pre-evaluation, and improve the demand for the network to be constructed in the target area, the data of the second sampling point can be evaluated through the following embodiments.

[0218] In some embodiments, such as Figure 7 As shown, prior to S301, the pre-evaluation methods for the network construction effect may also include: S701-S702.

[0219] S701. Rasterize the target area to obtain multiple first grids.

[0220] In other words, the target area is defined and then decomposed into a grid according to a certain area size.

[0221] It should be noted that there is no limitation on the size of the first grid when decomposing it. For example, the size of the target area decomposition can be 50 meters (m) × 50m, or 50m × 100m, or 100m × 50m.

[0222] S702. Obtain application service data for each first sampling point.

[0223] It should be noted that the process of the pre-evaluation device acquiring the OTT data of the first sampling point can be referred to the introduction of OTT data acquisition in the existing technology, and will not be repeated here.

[0224] In this embodiment of the disclosure, S204 may include: S703-S706.

[0225] S703. Based on the application service data of each first sampling point, locate multiple first sampling points to the target area and determine the first sampling point in each first grid.

[0226] As one possible implementation, the pre-evaluation device can map multiple first sampling points to a target area based on the location information in the OTT data of each first sampling point, and determine the first sampling point in each first grid according to the coverage of each first grid in the target area.

[0227] Optionally, all OTT data within a maintenance period (such as 7 days or 14 days) can be taken, and the location information (usually GPS information of the mobile phone) contained in the OTT data can be decomposed into each grid. This will give you M grids containing all OTT data within the target area.

[0228] It should be noted that OTT data contains coordinate information fields. Based on the coordinate information fields in OTT data (see the "INDOOR" field in the location information), all rasters are classified into two categories: outdoor rasters and indoor rasters.

[0229] S704. Based on the second preset rate threshold, determine the second ratio corresponding to each first grid.

[0230] The second ratio is the ratio between the number of sixth sampling points in the first grid and the number of second sampling points. The sixth sampling point is a sampling point among multiple second sampling points whose uplink rate is greater than the second preset rate threshold.

[0231] In other words, the second ratio is the ratio between the number of second sampling points that satisfy the uplink rate being greater than the second preset rate threshold and the total number of second sampling points.

[0232] As one possible implementation, the pre-evaluation device can store a second preset rate threshold. The pre-evaluation device can determine the relationship between the uplink rate of each second sampling point and the second preset rate threshold, and designate the sampling points among the multiple second sampling points whose uplink rate is greater than the second preset rate threshold as sixth sampling points, thereby obtaining at least one sixth sampling point.

[0233] S705. Based on a first preset ratio threshold, at least one second grid is selected from a plurality of first grids, wherein the second ratio corresponding to the second grid is greater than the first preset ratio threshold.

[0234] As one possible implementation, the pre-evaluation device can store a first preset ratio threshold. The pre-evaluation device can determine the relationship between the second ratio corresponding to each first grid and the first preset ratio threshold, and then select the first grids among the multiple first grids whose second ratio is greater than the first preset ratio threshold as second grids, thereby obtaining at least one second grid.

[0235] In other words, the second grid is the grid with a larger number of sampling points with better uplink rates among the multiple first grids.

[0236] S706. Determine pre-evaluation information based on the distribution of at least one second grid cell in the target area.

[0237] As one possible implementation, the pre-evaluation device can determine the distribution of at least one second grid cell in the target area based on a third ratio between the number of second grid cells and the number of first grid cells in the target area, and then determine pre-evaluation information based on the third ratio. The third ratio is positively correlated with the degree of need for network construction in the target area.

[0238] In other words, the more second grids there are in a plurality of first grids, the larger the third ratio will be, and the higher the degree to which the network bandwidth rate of the area to be built will be satisfied.

[0239] As another possible implementation, the pre-evaluation device can use a clustering algorithm to determine the degree of clustering of the second grid in the target area, and based on the degree of clustering of the second grid, determine the distribution of at least one second grid in the target area, and then determine the pre-evaluation information based on the degree of clustering of the second grid. The degree of clustering of the second grid is positively correlated with the demand for network construction in the target area.

[0240] In other words, the greater the degree of clustering of the second grid in the target area, the higher the degree to which the network bandwidth rate of the area to be built is satisfied.

[0241] It should be noted that the embodiments of this application do not limit the degree of clustering corresponding to the second grid. For example, the degree of clustering corresponding to the second grid can be determined by the number of clusters corresponding to at least one second grid. Alternatively, the degree of clustering corresponding to the second grid can be determined by the number of grids in each cluster corresponding to at least one second grid. Or, the degree of clustering corresponding to the second grid can be determined by the number of clusters corresponding to at least one second grid and the number of grids in each cluster.

[0242] In this embodiment of the application, the pre-evaluation information can be used to indicate the degree of demand for the network to be constructed for at least one second grid in the target area.

[0243] As one possible implementation, based on S602, the service satisfaction level of each first grid can be calculated, and each first grid contains at least one second sampling point. The pre-evaluation device can store a preset satisfaction threshold. The pre-evaluation device can determine the relationship between the service satisfaction level of each first grid and the preset satisfaction threshold, and select the first grids among the multiple first grids whose service satisfaction level is less than the preset satisfaction threshold as third grids to obtain at least one third grid.

[0244] In other words, the third grid is the grid with the poorest service satisfaction among multiple first grids.

[0245] Optionally, the pre-evaluation device can determine the distribution of at least one third grid cell in the target area based on a fourth ratio between the number of third grid cells and the number of first grid cells, and then determine pre-evaluation information based on the fourth ratio. The fourth ratio is negatively correlated with the demand for network construction in the target area.

[0246] The pre-evaluation device can store a second preset ratio threshold. The pre-evaluation device can determine the pre-evaluation information by determining the relationship between a fourth ratio and the second preset ratio threshold. If the third ratio is greater than the second preset ratio threshold, the pre-evaluation information can indicate that the target area has a low demand for the network to be built (i.e., the area to be built does not need to build the network).

[0247] It should be noted that for some areas in the target area that do not meet the requirements of the network to be built (i.e., the area corresponding to the third grid in the target area), density clustering methods such as density-based spatial clustering of applications with noise (DBSCAN) can be used to cluster poor-quality grids (equivalent to determining the distribution of grids). In areas where poor-quality grids are densely clustered, key measures such as increasing site locations and optimizing radio frequency (RF) can be taken to improve network coverage, thereby accurately guiding the construction of the network to be built.

[0248] Understandably, by rasterizing the target area, multiple first sampling points are mapped to the target area. Second grids are then selected, and the network bandwidth rate requirement of the area to be constructed is determined based on the ratio between the second ratio corresponding to the second grid and the first preset ratio threshold. Alternatively, pre-assessment information can be determined based on the distribution of the second grids within the target area. This allows for precise location information of the target sampling points, better acquisition of pre-assessment information, and determination of the network requirements of the area to be constructed, thus improving the accuracy of the pre-assessment of network construction effectiveness in the target area.

[0249] The foregoing primarily describes the solutions provided in the embodiments of this application from the perspective of computer devices. It is understood that, in order to achieve the aforementioned functions, the computer device includes corresponding hardware structures and / or software modules for executing each function. Those skilled in the art should readily recognize that, based on the methods and steps for pre-evaluating the network construction effects of the various examples described in the embodiments disclosed in this application, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0250] This application also provides a pre-evaluation device for network construction effectiveness. This pre-evaluation device can be a computer device, a CPU within the aforementioned computer device, a processing module within the aforementioned computer device for pre-evaluating network construction effectiveness, or a client within the aforementioned computer device for pre-evaluating network construction effectiveness.

[0251] This application embodiment can divide the pre-evaluation device for network construction effectiveness into functional modules or functional units based on the above method example. For example, each function can be divided into its own functional modules or functional units, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware or as a software functional module or functional unit. The module or unit division in this application embodiment is illustrative and represents only one logical functional division; other division methods may be used in actual implementation.

[0252] like Figure 8 The diagram shown is a structural schematic of a pre-evaluation device for network construction effectiveness provided in an embodiment of this application. The pre-evaluation device for network construction effectiveness is used to perform... Figure 2 , Figure 3 , Figure 4 , Figure 5 , Figure 6 or Figure 7 The network construction effect pre-evaluation method shown may include an acquisition module 801 and a processing module 802.

[0253] Acquisition module 801 is used to acquire measurement reports of the existing network in the target area. Processing module 802 is used to determine the path loss and antenna gain difference between the existing network and the network to be built in the target area based on the measurement reports of the existing network. Processing module 802 is also used to process the measurement reports of the existing network based on the path loss and antenna gain difference to obtain the measurement reports of the network to be built. Processing module 802 is also used to determine pre-assessment information based on the measurement reports of the network to be built, which is used to indicate the demand for the network to be built in the target area.

[0254] Optionally, the measurement report includes: the reference signal received power of the sampling points. The target area includes multiple first sampling points, and the network type of the first sampling points is an established network. The processing module 802 is specifically used to process the reference signal received power of each of the multiple first sampling points based on path loss and antenna gain difference to obtain the reference signal received power of multiple second sampling points in the target area. Here, one second sampling point corresponds to one first sampling point, the network type of the second sampling point is a network to be established, and the reference signal received power of the second sampling point is equal to the processed reference signal received power of the corresponding first sampling point.

[0255] Optionally, the processing module 802 is further configured to, when the established network is a preset network, select at least one third sampling point from multiple first sampling points based on a first preset received power threshold, wherein the reference signal received power of the third sampling point is less than the first preset received power threshold. Based on path loss and antenna gain difference, the reference signal received power of each of the multiple first sampling points is processed to obtain the reference signal received power of multiple second sampling points in the target area, including: processing the reference signal received power of each of the at least one third sampling point based on path loss and antenna gain difference to obtain the reference signal received power of multiple second sampling points.

[0256] Optionally, the measurement report may also include: the signal-to-interference-plus-noise ratio (SNR) and uplink rate of the sampling point. The processing module 802 is further configured to, for each second sampling point, determine the SNR and uplink rate of each second sampling point according to a first operation. The first operation includes: determining the SNR of the target sampling point based on the reference signal received power of the target sampling point and the reference signal received power of multiple fourth sampling points, where the target sampling point is any one of the multiple second sampling points, and the fourth sampling points are sampling points adjacent to the target sampling point among the multiple second sampling points; and determining the uplink rate of the target sampling point based on the reference signal received power and SNR of the target sampling point.

[0257] Optionally, the processing module 802 is further configured to, based on a first preset rate threshold, select at least one fifth sampling point from a plurality of second sampling points, wherein the uplink rate of the fifth sampling point is greater than the first preset rate threshold. Based on a first ratio between the number of fifth sampling points and the number of second sampling points, pre-assessment information is determined, wherein the first ratio is positively correlated with the demand for the network to be constructed in the target area.

[0258] Optionally, the processing module 802 is further configured to rasterize the target area to obtain multiple first grids. It acquires application service data for each first sampling point. Based on the application service data of each first sampling point, it locates the multiple first sampling points in the target area, determining the first sampling point in each first grid. Based on the measurement report of the network to be built, it determines pre-evaluation information, including: determining a second ratio corresponding to each first grid based on a second preset rate threshold, where the second ratio is the ratio between the number of sixth sampling points in the first grid and the number of second sampling points, and the sixth sampling point is a sampling point among the multiple second sampling points whose uplink rate is greater than the second preset rate threshold. Based on the first preset ratio threshold, it selects at least one second grid from the multiple first grids, where the second ratio corresponding to the second grid is greater than the first preset ratio threshold. Based on the distribution of at least one second grid in the target area, it determines pre-evaluation information.

[0259] Figure 9 This is a schematic diagram illustrating the structure of a pre-evaluation device for network construction effectiveness according to an exemplary embodiment. The device may include a processor 902, which executes application code to implement the pre-evaluation method for network construction effectiveness in this application.

[0260] The processor 902 may be a CPU, a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits used to control the execution of the program of the present application.

[0261] like Figure 9 As shown, the pre-evaluation device for network construction effectiveness may further include a memory 903. The memory 903 stores the application code that executes the scheme of this application, and its execution is controlled by the processor 902.

[0262] Memory 903 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital versatile optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. Memory 903 may exist independently and be connected to processor 902 via bus 904. Memory 903 may also be integrated with processor 902.

[0263] like Figure 9 As shown, the pre-evaluation device for network construction effectiveness may further include a communication interface 901, wherein the communication interface 901, processor 902, and memory 903 can be coupled to each other, for example, through a bus 904. The communication interface 901 is used for information exchange with other devices, such as supporting information exchange between the pre-evaluation device for network construction effectiveness and other devices.

[0264] It should be pointed out that, Figure 9 The equipment structure shown does not constitute a limitation on the equipment for pre-evaluation of the network construction effect, except... Figure 9 In addition to the components shown, the pre-evaluation equipment for the network construction effect may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0265] In actual implementation, all the functions implemented by the processing module 802 can be provided by... Figure 9 The processor 902 shown calls the program code in memory 903 to implement this.

[0266] This application also provides a computer-readable storage medium storing instructions that, when executed by a processor of a computer device, enable the computer to perform the pre-evaluation method for network construction effectiveness provided in the embodiments described above. For example, the computer-readable storage medium may be a memory 903 including instructions, which may be executed by a processor 902 of a computer device to complete the method. Optionally, the computer-readable storage medium may be a non-transitory computer-readable storage medium, such as ROM, RAM, CD-ROM, magnetic tape, floppy disk, and optical data storage devices.

[0267] Figure 10 A conceptual partial view of a computer program product provided in an embodiment of this application is shown as an example. The computer program product includes a computer program for executing computer processes on a computing device.

[0268] In one embodiment, a computer program product is provided using a signal bearer medium 1000. The signal bearer medium 1000 may include one or more program instructions that, when executed by one or more processors, can provide the above-mentioned... Figure 2 , Figure 3 , Figure 4 , Figure 5 , Figure 6 or Figure 7 The described function or part of the function. Therefore, for example, refer to... Figure 2 In the embodiment shown, one or more features of S201 to S204 can be fulfilled by one or more instructions associated with the signal carrying medium 1000. Furthermore, Figure 10 The program instructions in the document also describe example instructions.

[0269] In some examples, the signal carrying medium 1000 may include a computer-readable medium 1001, such as, but not limited to, a hard disk drive, a compact disc (CD), a digital video disc (DVD), a digital magnetic tape, a memory, a read-only memory (ROM), or a random access memory (RAM), etc.

[0270] In some implementations, the signal carrying medium 1000 may include a computer recordable medium 1002, such as, but not limited to, a memory, a read / write (R / W) CD, a R / W DVD, etc.

[0271] In some implementations, the signal carrying medium 1000 may include a communication medium 1003, such as, but not limited to, digital and / or analog communication media (e.g., fiber optic cables, waveguides, wired communication links, wireless communication links, etc.).

[0272] The signal-bearing medium 1000 can be transmitted by a wireless communication medium 1003. One or more program instructions may be, for example, computer-executable instructions or logical implementation instructions.

[0273] In some examples, such as targeting Figure 8 The network construction effect pre-evaluation device described can be configured to provide various operations, functions, or actions in response to one or more program instructions in a computer-readable medium 1001, a computer-recordable medium 1002, and / or a communication medium 1003.

[0274] Through the above description of the embodiments, those skilled in the art can clearly understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0275] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another apparatus, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0276] The units described as separate components may or may not be physically separate. A component shown as a unit can be one or more physical units; that is, it can be in one place or distributed in multiple different locations. Some or all of the constituent units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0277] 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.

[0278] 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 readable storage medium. Based on this understanding, the technical solution of the embodiments of this application, essentially, or the part that contributes to the prior art, or a complete or partial classification of the technical solution, can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to cause a device (which may be a microcontroller, chip, etc.) or processor to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0279] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for pre-evaluating the effectiveness of network construction, characterized in that, The method includes: Obtain a measurement report of the established network in the target area. The measurement report includes: reference signal received power of the sampling points. The target area includes multiple first sampling points, and the network type of the first sampling points is the established network. Based on the measurement report of the established network, determine the path loss and antenna gain difference between the established network and the network to be built in the target area; Based on the path loss and the antenna gain difference, the measurement report of the established network is processed to obtain the measurement report of the network to be built. The reference signal received power of each of the plurality of first sampling points is processed to obtain the reference signal received power of a plurality of second sampling points in the target area; The reference signal received power of each first sampling point is processed, including: dividing the first sampling point into indoor sampling points and outdoor sampling points based on the location of the sampling point; the indoor sampling point is further processed based on the penetration loss of the building where the first sampling point is located. Wherein, one second sampling point corresponds to one first sampling point, the network type of the second sampling point is the network to be built, and the reference signal received power of the second sampling point is equal to the processed reference signal received power of the corresponding first sampling point. The measurement report also includes: the signal-to-interference-plus-noise ratio and uplink rate at the sampling points; The step of processing the measurement report of the established network based on the path loss and the antenna gain difference to obtain the measurement report of the network to be built further includes: For each second sampling point, the signal-to-interference-plus-noise ratio and uplink rate of each second sampling point are determined according to the first operation. The first operation includes: determining the signal-to-interference-plus-noise ratio of the target sampling point based on the reference signal received power of the target sampling point and the reference signal received power of a plurality of fourth sampling points. The target sampling point is any sampling point among the plurality of second sampling points, and the fourth sampling point is a sampling point among the plurality of second sampling points that is adjacent to the target sampling point. Based on the reference signal received power and the signal-to-interference-plus-noise ratio of the target sampling point, the uplink rate of the target sampling point is determined. Based on the measurement report of the network to be built, pre-assessment information is determined, which is used to indicate the demand of the target area for the network to be built.

2. The method according to claim 1, characterized in that, After obtaining a measurement report of the network already established in the target area, the method further includes: In the case that the established network is a preset network, at least one third sampling point is selected from the plurality of first sampling points based on a first preset received power threshold, wherein the received power of the reference signal of the third sampling point is less than the first preset received power threshold. The step of processing the reference signal received power of each of the plurality of first sampling points based on the path loss and the antenna gain difference to obtain the reference signal received power of a plurality of second sampling points in the target area includes: Based on the path loss and the antenna gain difference, the reference signal received power of each of the at least one third sampling points is processed to obtain the reference signal received power of the plurality of second sampling points.

3. The method according to claim 1, characterized in that, The pre-assessment information determined based on the measurement report of the network to be built includes: Based on a first preset rate threshold, at least one fifth sampling point is selected from the plurality of second sampling points, wherein the uplink rate of the fifth sampling point is greater than the first preset rate threshold. The pre-evaluation information is determined based on a first ratio between the number of the fifth sampling point and the number of the second sampling point, wherein the first ratio is positively correlated with the demand of the target area for the network to be built.

4. The method according to claim 1, characterized in that, The method further includes: The target area is rasterized to obtain multiple first grids; Obtain application service data for each of the first sampling points; Based on the application service data of each first sampling point, the plurality of first sampling points are located in the target area, and the first sampling points in each first grid are determined; The pre-assessment information determined based on the measurement report of the network to be built includes: Based on the second preset rate threshold, a second ratio is determined for each of the first grids. The second ratio is the ratio between the number of sixth sampling points in the first grid and the number of second sampling points. The sixth sampling point is a sampling point among the plurality of second sampling points whose uplink rate is greater than the second preset rate threshold. Based on a first preset ratio threshold, at least one second grid is selected from the plurality of first grids, wherein the second ratio corresponding to the second grid is greater than the first preset ratio threshold; The pre-evaluation information is determined based on the distribution of the at least one second grid in the target area.

5. A pre-evaluation device for network construction effectiveness, characterized in that, The device includes: The acquisition module is used to acquire a measurement report of the network already built in the target area, the measurement report including the reference signal received power of multiple first sampling points; The processing module is used to determine the path loss and antenna gain difference between the existing network and the network to be built in the target area based on the measurement report of the existing network. The processing module is further configured to process the measurement report of the established network based on the path loss and the antenna gain difference to obtain the measurement report of the network to be built. The processing module is further configured to process the reference signal received power of each of the plurality of first sampling points to obtain the reference signal received power of a plurality of second sampling points in the target area; the processing of the reference signal received power of each first sampling point includes: dividing the first sampling point into indoor sampling points and outdoor sampling points based on the location of the sampling point; for the indoor sampling point, the processing of the reference signal received power of the first sampling point is further based on the penetration loss of the building where the first sampling point is located; one second sampling point corresponds to one first sampling point, the network type of the second sampling point is the network to be built, and the reference signal received power of the second sampling point is equal to the processed reference signal received power of the corresponding first sampling point; The processing module is further configured to determine the signal-to-interference-plus-noise ratio of the target sampling point based on the reference signal received power of the target sampling point and the reference signal received power of a plurality of fourth sampling points, wherein the target sampling point is any one of the plurality of second sampling points, and the fourth sampling point is a sampling point adjacent to the target sampling point among the plurality of second sampling points; Based on the reference signal received power and signal-to-interference-plus-noise ratio of the target sampling point, the uplink rate of the target sampling point is determined; the processing module is also used to determine pre-evaluation information based on the measurement report of the network to be built, the pre-evaluation information being used to indicate the demand of the target area for the network to be built.

6. A device for pre-evaluating the effectiveness of network construction, characterized in that, include: Processor and memory; The processor and the memory are coupled; The memory is used to store one or more programs, the one or more programs including computer execution instructions. When the network construction effect pre-evaluation device is running, the processor executes the computer execution instructions stored in the memory to cause the network construction effect pre-evaluation device to perform the method as described in any one of claims 1-4.

7. A computer-readable storage medium storing instructions, characterized in that, When the computer executes the instructions, the computer performs the method as described in any one of claims 1-4.

8. A computer program product, characterized in that, The computer program product includes computer program instructions that, when executed, implement the method as described in any one of claims 1-4.

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