A micro station deployment method and device, electronic equipment, storage medium and product

Abstract

The present disclosure provides a micro station deployment method and device, electronic equipment, storage medium and product, wherein the method comprises: obtaining index parameter values of each attribute information of a micro station in various micro station deployment scenarios; determining a first weight of each attribute information; wherein the first weight is used to indicate the importance of the attribute information; determining target decision data of each micro station deployment scenario based on the index parameter values and the first weight; wherein the target decision data is used to indicate the importance of each attribute information in the corresponding micro station deployment scenario; based on the target decision data, determining a target deployment scheme of the micro station for a to-be-deployed area among multiple micro station deployment schemes, and deploying the target deployment scheme in the to-be-deployed area. While improving the accuracy of the target deployment scheme, the time efficiency of the target deployment scheme selection is improved.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of communication, and in particular, to a micro station deployment method and device, electronic equipment, storage medium and product. BACKGROUND

[0002] With the development of mobile networks, low-frequency resources are becoming less and less, and high-frequency resources are being used more and more frequently. As the frequency band increases, the penetration ability of the micro station becomes weaker. Different micro station deployment schemes can be selected for different micro station deployment scenarios to improve the network and coverage range of the micro station, so that the micro station can provide higher transmission rate and network capacity. Therefore, which micro station deployment scheme to choose for the micro station of high-frequency resources has always been a research hotspot in the field of mobile networks.

[0003] At present, when selecting a micro station deployment scheme for different micro station deployment scenarios, it is usually dependent on a single micro station deployment factor such as network coverage and capacity. Alternatively, the micro station deployment scheme is determined subjectively by the experience of a planning personnel. However, relying only on a single micro station deployment factor or relying on the subjective determination of a planning personnel results in the problem of great limitations and low selection efficiency of the selected micro station deployment scheme. In view of this situation, it is necessary to provide a high-efficiency micro station deployment scheme selection method while overcoming the limitations of micro station deployment scheme selection. SUMMARY

[0004] The present disclosure provides at least a micro station deployment method, device, electronic equipment, storage medium and product.

[0005] In a first aspect, the present disclosure provides a micro station deployment method, comprising:

[0006] obtaining an index parameter value of each attribute information of a micro station in each micro station deployment scenario;

[0007] determining a first weight of each attribute information; wherein the first weight is used to indicate the importance of the attribute information;

[0008] determining target decision data of each micro station deployment scenario based on the index parameter value and the first weight; wherein the target decision data is used to indicate the importance of each attribute information in the corresponding micro station deployment scenario;

[0009] determining a target deployment scheme of the micro station for a to-be-deployed area in a plurality of micro station deployment schemes based on the target decision data, and deploying the target deployment scheme in the to-be-deployed area.

[0010] In an optional implementation, the deploying the target deployment scheme in the to-be-deployed area comprises:

[0011] Determine the grid cells to be deployed in the area to be deployed for the target deployment scheme;

[0012] The target deployment scheme for deploying the micro-stations in the deployment grid of the deployment area.

[0013] In one optional implementation, determining the grid cells to be deployed in the area to be deployed for the target deployment scheme includes:

[0014] The area to be deployed is rasterized to obtain multiple target rasters;

[0015] Determine the raster value for each of the target raster cells;

[0016] The target grid that meets the preset grid value conditions is determined as the grid to be deployed.

[0017] In one optional implementation, determining the raster value of each of the target raster cells includes:

[0018] Obtain the analysis dimension value for each target raster; wherein the analysis dimension value is used to indicate the raster attribute value of the target raster;

[0019] Determine the importance of each value in the analysis dimension;

[0020] The raster value of each target raster is determined based on the analysis dimension value and the importance of that analysis dimension value.

[0021] In one optional implementation, determining the target decision data for each micro-site deployment scenario based on the indicator parameter value and the first weight includes:

[0022] Based on the aforementioned indicator parameter values, the correlation between any two attribute information for each of the micro-site deployment scenarios is determined;

[0023] Based on the correlation, the attribute information associated with each micro-site deployment scenario is filtered to obtain filtered attribute information; wherein, the correlation between any two filtered attribute information is less than or equal to a preset correlation threshold.

[0024] Based on the index parameter values ​​of the filtered attribute information and the first weight of the filtered attribute information, the target decision data for each micro-site deployment scenario is determined.

[0025] In one optional implementation, determining the first weight of each attribute information includes:

[0026] Obtain the weight reference value of the attribute information; wherein, the weight reference value is used to indicate the importance of each attribute information under the micro-site deployment scheme;

[0027] The weight reference values ​​of the same attribute information for different micro-site deployment schemes are processed to obtain the first weight of the attribute information.

[0028] In one optional implementation, the process of processing the weight reference values ​​of the same attribute information for different micro-site deployment schemes to obtain the first weight of the attribute information includes:

[0029] The weight reference values ​​of the same attribute information for different micro-site deployment schemes are averaged to obtain the averaged result;

[0030] The mean processing result is normalized to obtain the first weight of each attribute information.

[0031] In one optional implementation, determining the target deployment scheme for the micro-site to be deployed in the area based on the target decision data among multiple micro-site deployment schemes includes:

[0032] Determine the maximum and minimum decision data from the target decision data in each micro-station deployment scenario;

[0033] Based on the maximum and minimum decision data, the decision value for this micro-site deployment scenario is determined;

[0034] The micro-site deployment scheme corresponding to the largest decision value among the decision values ​​of each micro-site deployment scenario is determined as the target deployment scheme.

[0035] Secondly, embodiments of this disclosure also provide a micro-station deployment device, comprising:

[0036] The acquisition module is used to obtain the indicator parameter values ​​of each attribute information of the micro-site in various micro-site deployment scenarios;

[0037] A first determining module is configured to determine a first weight for each of the attribute information; wherein the first weight is used to indicate the importance of the attribute information;

[0038] The second determining module is used to determine target decision data for each micro-site deployment scenario based on the indicator parameter value and the first weight; wherein the target decision data is used to indicate the importance of each attribute information in the corresponding micro-site deployment scenario;

[0039] The deployment module is used to determine the target deployment scheme for the micro-site to be deployed in the area to be deployed based on the target decision data among multiple micro-site deployment schemes, and to deploy the target deployment scheme in the area to be deployed.

[0040] Thirdly, embodiments of this disclosure also provide an electronic device, including: a processor, a memory, and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor communicates with the memory via the bus, and when the machine-readable instructions are executed by the processor, the steps of the first aspect above, or any possible implementation of the first aspect, are performed.

[0041] Fourthly, embodiments of this disclosure also provide a computer-readable storage medium storing a computer program that, when executed by a processor, performs the steps of the first aspect or any possible implementation of the first aspect.

[0042] Fifthly, embodiments of this disclosure also provide a computer program product, which is stored in a storage medium and is executed by at least one processor, along with the steps described in the first aspect or any possible implementation of the first aspect.

[0043] In the embodiments of this disclosure, firstly, the indicator parameter values ​​of each attribute information of the micro-site in each micro-site deployment scenario are obtained; secondly, the first weight of each attribute information is determined; thirdly, based on the indicator parameter values ​​and the first weight, the target decision data for each micro-site deployment scenario is determined; finally, based on the target decision data, the target deployment scheme for the micro-site to be deployed in the area to be deployed is determined among multiple micro-site deployment schemes, and the target deployment scheme is deployed in the area to be deployed.

[0044] In the above embodiments, target decision data for each micro-site deployment scenario is determined by considering the indicator parameter values ​​of each attribute information of the micro-site in various micro-site deployment scenarios and the importance of each attribute information. After determining the target decision data, the target deployment scheme for the micro-site to be deployed in the desired area is determined from multiple micro-site deployment schemes based on the target decision data. This embodiment does not determine the target deployment scheme through subjective judgment, and each attribute information of the micro-site is considered when determining the target deployment scheme. Therefore, the accuracy of the target deployment scheme is improved while the time efficiency of the target deployment scheme selection is increased.

[0045] To make the above-mentioned objects, features and advantages of this disclosure more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0046] To more clearly illustrate the technical solutions of the embodiments of this disclosure, the accompanying drawings used in the embodiments will be briefly described below. These drawings are incorporated in and constitute a part of this specification. They illustrate embodiments conforming to this disclosure and, together with the specification, serve to explain the technical solutions of this disclosure. It should be understood that the following drawings only show some embodiments of this disclosure and should not be considered as limiting the scope. Those skilled in the art can obtain other related drawings based on these drawings without creative effort.

[0047] Figure 1 A flowchart of a micro-site deployment method provided by an embodiment of this disclosure is shown;

[0048] Figure 2 This invention discloses an overall flowchart of the micro-site deployment method provided in an embodiment of the present invention;

[0049] Figure 3 A schematic diagram of a micro-site deployment device provided in an embodiment of this disclosure is shown;

[0050] Figure 4 A schematic diagram of an electronic device provided in an embodiment of the present disclosure is shown. Detailed Implementation

[0051] To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this disclosure, and not all of them. The components of the embodiments of this disclosure described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this disclosure provided in the accompanying drawings is not intended to limit the scope of the claimed disclosure, but merely represents selected embodiments of this disclosure. All other embodiments obtained by those skilled in the art based on the embodiments of this disclosure without inventive effort are within the scope of protection of this disclosure.

[0052] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0053] In this document, the term "and / or" merely describes a relationship, indicating that three relationships can exist. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Furthermore, the term "at least one" in this document means any combination of at least two of any one or more elements. For example, including at least one of A, B, and C can mean including any one or more elements selected from the set consisting of A, B, and C.

[0054] Research has shown that with the development of mobile networks, low-frequency resources are becoming increasingly scarce, while high-frequency resources are being used more frequently. As the frequency band increases, the penetration capability of microcells weakens. Different microcell deployment schemes can be selected for different deployment scenarios to improve the network coverage and enable microcells to provide higher transmission rates and network capacity. Therefore, choosing the right microcell deployment scheme for high-frequency resources has always been a research hotspot in the field of mobile networks.

[0055] Currently, when selecting a microsite deployment solution for different scenarios, the choice typically relies on a single factor such as network coverage and capacity. Alternatively, it may depend on the subjective experience of planners. However, relying solely on a single factor or subjective experience leads to limitations and inefficiency in selecting the right microsite deployment solution. To address this, a more efficient method for selecting a microsite deployment solution is needed, overcoming these limitations.

[0056] Based on the above research, this disclosure provides a micro-site deployment method. By determining the target decision data for each micro-site deployment scenario based on the indicator parameter values ​​of each attribute information of the micro-site in various deployment scenarios and the importance of each attribute information, the method then determines the target deployment scheme for the micro-site in the area to be deployed, from multiple micro-site deployment options. This embodiment does not determine the target deployment scheme through subjective judgment, and it considers each attribute information of the micro-site when determining the target deployment scheme. Therefore, it improves both the accuracy of the target deployment scheme and the time efficiency of target deployment scheme selection.

[0057] To facilitate understanding of this embodiment, a micro-site deployment method disclosed in this disclosure will first be described in detail. The execution subject of the micro-site deployment method provided in this disclosure is generally a computer device with certain computing capabilities. This computer device may include, for example, a terminal device, a server, or other processing devices. The terminal device may be a user equipment (UE), mobile device, user terminal, terminal, cellular phone, cordless phone, personal digital assistant (PDA), handheld device, computing device, vehicle-mounted device, wearable device, etc. In some possible implementations, this micro-site deployment method can be implemented by a processor calling computer-readable instructions stored in memory.

[0058] See Figure 1 The diagram shows a flowchart of a micro-site deployment method provided in this embodiment of the present disclosure. The method includes steps S101 to S104, wherein:

[0059] S101. Obtain the indicator parameter values ​​of each attribute information of the micro-site in each micro-site deployment scenario.

[0060] In the embodiments of this disclosure, the attribute information of the micro-station includes the micro-station establishment cost, micro-station coverage area, micro-station transmission distance, and the difficulty of coordinating with property management companies for the micro-station.

[0061] Here, the deployment scenarios for micro-sites include residential areas, commercial streets, and areas with high pedestrian traffic (such as schools, hospitals, and shopping malls).

[0062] Here, the metric parameter values ​​corresponding to the same attribute information may differ in different micro-site deployment scenarios.

[0063] Here, for non-measurable attribute information, such as the difficulty of property coordination, the attribute information can be transformed into a measurable quantity as the indicator parameter value of the attribute information.

[0064] First, the membership function of the attribute information can be determined based on its characteristics. Then, based on the membership function, the attribute information is transformed into a measurable value. Finally, the measurable value can be normalized to obtain the index parameter value of the attribute information. The measurable value x of the attribute information can be obtained through the following formula:

[0065]

[0066] Where x is the variable in the membership function of the attribute information, and μ(x) is the membership function of the attribute information.

[0067] Here, the normalized result obtained by normalizing the value corresponding to the measurable attribute information can be used as the index parameter value of the attribute information.

[0068] S102. Determine a first weight for each of the attribute information; wherein the first weight is used to indicate the importance of the attribute information.

[0069] In the embodiments of this disclosure, firstly, the importance of each attribute information under different micro-site deployment schemes can be obtained. Secondly, the importance of the same attribute information under different micro-site deployment schemes can be processed to obtain the intermediate weight of the attribute information. Next, the intermediate weight of each attribute information is subjected to a consistency check. Next, if the intermediate weight passes the consistency check, the intermediate weight is used as the first weight. Finally, if the intermediate weight fails the consistency check, the intermediate weight is recalculated until the intermediate weight passes the consistency check.

[0070] Here, the consistency check of intermediate weights can be performed in the following way:

[0071] C R =C I / R I ;

[0072] Among them, C I R is a consistency index for intermediate weights. I This is the average consistency index.

[0073] Among them, the consistency index CI of the intermediate weights meets the following conditions:

[0074]

[0075] Where, λ max is the maximum intermediate weight, and n is the number of intermediate weights.

[0076] Among them, the average consistency index R I The number of intermediate weights, n, can be determined by looking up Table 1.

[0077] For example, when the number of intermediate weights n is 3, the average consistency index R I It is 0.52.

[0078] n 1 2 3 4 5 6 7 8 9 10 11 Values 0 0 0.52 0.89 1.12 1.26 1.36 1.41 1.46 1.49 1.54

[0079] Table 1

[0080] S103. Based on the indicator parameter values ​​and the first weight, determine the target decision data for each micro-site deployment scenario; wherein, the target decision data is used to indicate the importance of each attribute information in the corresponding micro-site deployment scenario.

[0081] In the embodiments of this disclosure, the index parameter value and the corresponding first weight under each micro-site deployment scenario can be multiplied together, and the product result can be used as the target decision data for that micro-site deployment scenario.

[0082] Here, before multiplying the indicator parameter values ​​and corresponding first weights for each micro-site deployment scenario, the indicator parameter values ​​can be filtered to remove those corresponding to any highly correlated attribute information in each micro-site deployment scenario. In other words, the target decision data corresponding to any highly correlated attribute information is not included in this micro-site deployment scenario.

[0083] S104. Based on the target decision data, determine the target deployment scheme for the micro-site in the area to be deployed among multiple micro-site deployment schemes, and deploy the target deployment scheme in the area to be deployed.

[0084] In the embodiments of this disclosure, firstly, the target decision data for each micro-site deployment scenario can be processed to obtain a decision value for each micro-site deployment scenario. Then, based on the decision values ​​for each micro-site deployment scenario, a target deployment scheme for the micro-site in the area to be deployed can be determined from multiple micro-site deployment schemes. Finally, the target deployment scheme can be deployed in the area to be deployed.

[0085] Among them, the micro-site deployment scheme includes a variety of deployment schemes such as the distributed micro-site deployment scheme.

[0086] Here, when the area to be deployed includes multiple grids to be deployed, the target deployment scheme for each grid to be deployed can be determined based on the micro-site deployment scenario to which each grid belongs.

[0087] In the embodiments of this disclosure, firstly, the indicator parameter values ​​of each attribute information of the micro-site in each micro-site deployment scenario are obtained; secondly, the first weight of each attribute information is determined; thirdly, based on the indicator parameter values ​​and the first weight, the target decision data for each micro-site deployment scenario is determined; finally, based on the target decision data, the target deployment scheme for the micro-site to be deployed in the area to be deployed is determined among multiple micro-site deployment schemes, and the target deployment scheme is deployed in the area to be deployed.

[0088] In the above embodiments, target decision data for each micro-site deployment scenario is determined by considering the indicator parameter values ​​of each attribute information of the micro-site in various micro-site deployment scenarios and the importance of each attribute information. After determining the target decision data, the target deployment scheme for the micro-site to be deployed in the desired area is determined from multiple micro-site deployment schemes based on the target decision data. This embodiment does not determine the target deployment scheme through subjective judgment, and each attribute information of the micro-site is considered when determining the target deployment scheme. Therefore, the accuracy of the target deployment scheme is improved while the time efficiency of the target deployment scheme selection is increased.

[0089] In an optional embodiment, the above steps deploy the target deployment scheme in the area to be deployed, specifically including the following steps:

[0090] First, identify the grid cells to be deployed in the area to be deployed for the target deployment plan;

[0091] Then, the target deployment scheme for the micro-sites is deployed in the deployment grid of the deployment area.

[0092] In embodiments of this disclosure, the area to be deployed includes multiple grids. Here, grids in the area to be deployed that meet preset grid conditions can be identified as grids to be deployed.

[0093] Here, a target deployment scheme can be used to deploy micro-sites in the deployment grid of the area to be deployed.

[0094] Here, when there are multiple grids to be deployed in the area to be deployed, each grid can be deployed with the target deployment scheme to deploy the micro-site.

[0095] In an optional embodiment, the above steps determine the grid cells to be deployed in the area to be deployed for the target deployment scheme, specifically including the following steps:

[0096] First, the area to be deployed is rasterized to obtain multiple target rasters;

[0097] Secondly, determine the raster value of each target raster;

[0098] Finally, target rasters that meet the preset raster value conditions are identified as rasters to be deployed.

[0099] In the embodiments of this disclosure, the area to be deployed can be rasterized based on the coverage radius of the micro-station to obtain multiple target grids. For example, assuming the coverage radius of the micro-station is 50m, the side length of the rasterization process is set to 50m, that is, a 50m*50m target grid is obtained.

[0100] Here, the raster value of each target raster can be determined based on the raster's attributes.

[0101] Here, after obtaining the raster value of each target raster, the raster values ​​of the target raster can be sorted. If the raster value of a target raster ranks first among the preset percentage thresholds, that target raster is considered to meet the preset raster value condition and is designated as a raster to be deployed. The preset percentage threshold can be in the range of [10%, 20%].

[0102] In an optional embodiment, the above steps for determining the raster value of each target raster specifically include the following steps:

[0103] First, obtain the analysis dimension value for each target raster; where the analysis dimension value is used to indicate the raster attribute value of the target raster.

[0104] Secondly, determine the importance of each analysis dimension value;

[0105] Finally, based on the analysis dimension value and the importance of that analysis dimension value, the raster value of each target raster is determined.

[0106] In the embodiments of this disclosure, firstly, the weight of each target raster's raster attribute among all raster attributes of that target raster can be determined based on the analysis dimension value of each target raster. Here, raster attributes include the number of users, the number of complaints, and traffic, etc. The weight e of the g-th raster attribute of the f-th target raster is... fg Meets the following conditions:

[0107]

[0108] Among them, t fg Let f be the analysis dimension value of the g-th grid attribute of the f-th target grid, where f ranges from 1 to F, F is the number of target grids, and g ranges from 1 to G, where G is the number of grid attributes of the target grid.

[0109] Secondly, the importance of each raster attribute can be determined based on its weight among all raster attributes of that target raster. Specifically, the importance d of the g-th raster attribute... g Meets the following conditions:

[0110]

[0111] Secondly, the intermediate grid value of each target raster can be determined based on the importance of each grid attribute and the weight of each target raster's attribute among all grid attributes of that target raster. Wherein, the intermediate grid value h of the f-th target raster... f Meets the following conditions:

[0112]

[0113] Finally, the intermediate grid values ​​of each target grid can be normalized to obtain the grid value of each target grid. Among them, the grid value H of the f-th target grid is... f Meets the following conditions:

[0114]

[0115] In the above embodiments, target decision data for each micro-site deployment scenario is determined by analyzing the indicator parameter values ​​and importance of each attribute information of the micro-site in various micro-site deployment scenarios. After determining the target decision data, based on the target decision data, the target deployment scheme for the micro-site in the area to be deployed is determined among multiple micro-site deployment schemes. Furthermore, based on the grid attributes of the grid, a suitable grid for deploying the micro-site is determined in the area to be deployed, thereby improving the service performance of the micro-site after deployment.

[0116] In an optional embodiment, the above steps determine the target decision data for each micro-site deployment scenario based on the indicator parameter value and the first weight, specifically including the following steps:

[0117] First, based on the indicator parameter values, determine the correlation between any two attribute information for each micro-site deployment scenario;

[0118] Secondly, the attribute information associated with each micro-site deployment scenario is filtered based on relevance to obtain filtered attribute information; wherein, the relevance between any two filtered attribute information is less than or equal to a preset relevance threshold.

[0119] Finally, based on the index parameter values ​​and the first weight of the filtered attribute information, the target decision data for each micro-site deployment scenario is determined.

[0120] In the embodiments of this disclosure, the correlation between any two attribute information within a micro-site deployment scenario can be determined based on the parameter values ​​of each indicator under each micro-site deployment scenario. For example, the correlation between any two attribute information within a micro-site deployment scenario can be determined using grey relational analysis.

[0121] Here, if there is a correlation greater than the preset correlation threshold in the micro-site deployment scenario, one of the attribute information corresponding to the correlation greater than the preset correlation threshold can be selected for deletion (that is, the attribute information associated with each micro-site deployment scenario is filtered based on the correlation) to obtain the filtered attribute information.

[0122] Here, the index parameter values ​​of the filtered attribute information and the first weight of the filtered attribute information can be multiplied in the micro-site deployment scenario to obtain the product result, and the product result can be used as the target decision data for the micro-site deployment scenario.

[0123] In the above embodiments, different micro-site attribute information has varying degrees of influence on different micro-site deployment scenarios. The above method can filter attribute information in each micro-site deployment scenario, and calculate the target decision data for that micro-site deployment scenario using indicator parameter values ​​whose correlation is less than or equal to a preset correlation threshold. However, using attribute information with excessively high correlation within the same micro-site deployment scenario can lead to duplicate calculations and inaccurate subsequent calculations. Therefore, this embodiment can improve time efficiency while avoiding the problem of inaccurate target deployment scheme selection due to excessively high correlation between attribute information.

[0124] In an optional embodiment, the above steps determine a first weight for each attribute information, specifically including the following steps:

[0125] First, obtain the weight reference values ​​for the attribute information; these weight reference values ​​are used to indicate the importance of each attribute information under the micro-site deployment plan.

[0126] Then, the weight reference values ​​of the same attribute information for different micro-site deployment schemes are processed to obtain the first weight of the attribute information.

[0127] In the embodiments of this disclosure, firstly, the historical weight values ​​of each attribute information for different micro-site deployment schemes can be obtained. Then, the historical weight values ​​of the same attribute information under different micro-site deployment schemes can be processed to obtain the weight reference value corresponding to that attribute information.

[0128] Here, after obtaining the weight reference value for each attribute, an intermediate weight value for each attribute can be calculated based on that reference value. After obtaining the intermediate weight value, it can be processed to obtain the first weight for each attribute.

[0129] In an optional embodiment, the above steps process the weight reference values ​​of the same attribute information for different micro-site deployment schemes to obtain the first weight of the attribute information, specifically including the following steps:

[0130] First, the weight reference values ​​of the same attribute information for different micro-site deployment schemes are averaged to obtain the averaged result;

[0131] Then, the mean processing result is normalized to obtain the first weight of each attribute information.

[0132] In the embodiments of this disclosure, firstly, the historical weight values ​​of each of the different micro-site deployment schemes under the same attribute information can be averaged to obtain the weight reference values ​​of the same attribute information for different micro-site deployment schemes. Secondly, the weight reference values ​​of the same attribute information for different micro-site deployment schemes can be averaged to obtain the averaged result.

[0133] Here, after obtaining the mean processing result, the mean processing result can be further processed to obtain the intermediate weight value of each attribute information. The intermediate weight value W for the i-th attribute information is... i Meets the following conditions:

[0134]

[0135] Among them, c ij This represents the average processing result of the i-th attribute information for the j-th micro-site deployment scheme, where i ranges from 1 to n, n is the number of attribute information, and j ranges from 1 to m, where m is the number of micro-site deployment schemes.

[0136] Here, after obtaining the intermediate weight values, we can normalize them to obtain the first weight for each attribute. The first weight of the i-th attribute satisfies the following condition:

[0137]

[0138] In an optional embodiment, the above steps, based on target decision data, determine the target deployment scheme for the micro-site to be deployed in the region among multiple micro-site deployment schemes, specifically including the following steps:

[0139] First, determine the maximum and minimum decision data in the target decision data for each micro-site deployment scenario;

[0140] Secondly, based on the maximum and minimum decision data, the decision value for this micro-site deployment scenario is determined;

[0141] Finally, the micro-site deployment scheme corresponding to the largest decision value among the decision values ​​of each micro-site deployment scenario is determined as the target deployment scheme.

[0142] In the embodiments of this disclosure, the target decision data of each micro-site deployment scenario can be sorted from largest to smallest, and the largest target decision data in each micro-site deployment scenario can be determined as the largest decision data, and the smallest target decision data in each micro-site deployment scenario can be determined as the smallest decision data.

[0143] Here, the maximum and minimum decision values ​​under the same micro-site deployment scenario can be processed according to a preset calculation formula to obtain the decision value of the micro-site deployment scenario.

[0144] Here, after obtaining the decision value for each micro-site deployment scenario, the decision values ​​for each micro-site deployment scenario can be sorted from largest to smallest, and the largest decision value can be obtained.

[0145] Here, after obtaining the maximum decision value, the target deployment scheme can be selected from multiple micro-site deployment schemes based on the maximum decision value.

[0146] Here, each micro-site deployment scheme corresponds to a specific numerical range, and the numerical range for each micro-site deployment scheme is different. The micro-site deployment scheme corresponding to the numerical range containing the maximum decision value can be determined as the target deployment scheme.

[0147] In an optional embodiment, the above steps determine the decision value for the micro-site deployment scenario based on the maximum and minimum decision data, specifically including the following steps:

[0148] First, calculate the sum between the maximum and minimum decision data for each micro-site deployment scenario to obtain the sum value;

[0149] Secondly, calculate the ratio between the minimum decision data of the micro-site deployment scenario and the sum value corresponding to the micro-site deployment scenario, and determine the decision value of the micro-site deployment scenario based on the ratio calculation result.

[0150] In the embodiments of this disclosure, after determining the maximum and minimum decision values ​​for each micro-site deployment scenario, the maximum and minimum decision values ​​for each micro-site deployment scenario can be processed to determine the decision value under each micro-site deployment scenario.

[0151] Here, the decision value for the r-th micro-site deployment scenario meets the following conditions:

[0152]

[0153] in, Let r be the minimum decision value for the deployment scenario of the r-th micro-site. Let r be the maximum decision value for the r-th micro-site deployment scenario, where r ranges from 1 to R, and R is the number of micro-site deployment scenarios.

[0154] See Figure 2 The diagram shown is an overall flowchart of the micro-site deployment method provided in this embodiment of the disclosure, wherein:

[0155] S10. The area to be deployed is rasterized to obtain multiple target rasters.

[0156] S20. Determine the raster value of each target raster based on the raster's attributes.

[0157] S30. Target rasters that meet the preset raster value conditions are identified as rasters to be deployed.

[0158] Here, after obtaining the raster value of each target raster, the raster values ​​of the target raster can be sorted. If the raster value of a target raster ranks first among the preset percentage thresholds, that target raster is considered to meet the preset raster value condition and is designated as a raster to be deployed. The preset percentage threshold can be in the range of [10%, 20%].

[0159] S40. Obtain the indicator parameter values ​​of each attribute information of the micro-site in each micro-site deployment scenario.

[0160] S50. Determine the first weight for each attribute information.

[0161] S60. Based on the indicator parameter values, determine the correlation between any two attribute information for each micro-site deployment scenario.

[0162] S70. Based on the correlation, filter the attribute information associated with each micro-site deployment scenario to obtain the filtered attribute information.

[0163] S80. Based on the index parameter values ​​and the first weight of the filtered attribute information, determine the target decision data for each micro-site deployment scenario.

[0164] S90. Based on the target decision data, determine the target deployment scheme for the micro-site in the area to be deployed among multiple micro-site deployment schemes, and deploy the target deployment scheme in the area to be deployed.

[0165] In the above embodiments, target decision data for each micro-site deployment scenario is determined by considering the indicator parameter values ​​of each attribute information of the micro-site in various micro-site deployment scenarios and the importance of each attribute information. After determining the target decision data, the target deployment scheme for the micro-site to be deployed in the desired area is determined from multiple micro-site deployment schemes based on the target decision data. This embodiment does not determine the target deployment scheme through subjective judgment, and each attribute information of the micro-site is considered when determining the target deployment scheme. Therefore, the accuracy of the target deployment scheme is improved while the time efficiency of the target deployment scheme selection is increased.

[0166] Those skilled in the art will understand that, in the above-described method of the specific implementation, the order in which each step is written does not imply a strict execution order and does not constitute any limitation on the implementation process. The specific execution order of each step should be determined by its function and possible internal logic.

[0167] Based on the same inventive concept, this disclosure also provides a micro-site deployment device corresponding to the micro-site deployment method. Since the principle of the device in this disclosure for solving the problem is similar to the micro-site deployment method described above in this disclosure, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be described again.

[0168] Reference Figure 3 The diagram shown is a schematic of a micro-site deployment device provided in an embodiment of this disclosure. The device includes: an acquisition module 11, a first determination module 12, a second determination module 13, and a deployment module 14; wherein,

[0169] The acquisition module is used to obtain the indicator parameter values ​​of each attribute information of the micro-site in various micro-site deployment scenarios;

[0170] A first determining module is configured to determine a first weight for each of the attribute information; wherein the first weight is used to indicate the importance of the attribute information;

[0171] The second determining module is used to determine target decision data for each micro-site deployment scenario based on the indicator parameter value and the first weight; wherein the target decision data is used to indicate the importance of each attribute information in the corresponding micro-site deployment scenario;

[0172] The deployment module is used to determine the target deployment scheme for the micro-site to be deployed in the area to be deployed based on the target decision data among multiple micro-site deployment schemes, and to deploy the target deployment scheme in the area to be deployed.

[0173] This embodiment determines the target decision data for each micro-site deployment scenario by considering the indicator parameter values ​​of each attribute information of the micro-site in various micro-site deployment scenarios and the importance of each attribute information. After determining the target decision data, a target deployment scheme for the micro-site in the area to be deployed is determined from multiple micro-site deployment schemes based on the target decision data. This embodiment does not determine the target deployment scheme through subjective judgment, and it takes into account each attribute information of the micro-site when determining the target deployment scheme. Therefore, it improves both the accuracy of the target deployment scheme and the time efficiency of the target deployment scheme selection.

[0174] In one possible implementation, the deployment module is further configured to: determine the grid to be deployed in the area to be deployed for the target deployment scheme;

[0175] The target deployment scheme for deploying the micro-stations in the deployment grid of the deployment area.

[0176] In one possible implementation, the deployment module is further configured to: rasterize the area to be deployed to obtain multiple target grids;

[0177] Determine the raster value for each of the target raster cells;

[0178] The target grid that meets the preset grid value conditions is determined as the grid to be deployed.

[0179] In one possible implementation, the deployment module is further configured to: obtain the analysis dimension value of each of the target graticles; wherein the analysis dimension value is used to indicate the graticle attribute value of the target graticle;

[0180] Determine the importance of each value in the analysis dimension;

[0181] The raster value of each target raster is determined based on the analysis dimension value and the importance of that analysis dimension value.

[0182] In one possible implementation, the second determining module is specifically used to: determine the correlation between any two attribute information for each of the micro-station deployment scenarios based on the index parameter values;

[0183] Based on the correlation, the attribute information associated with each micro-site deployment scenario is filtered to obtain filtered attribute information; wherein, the correlation between any two filtered attribute information is less than or equal to a preset correlation threshold.

[0184] Based on the index parameter values ​​of the filtered attribute information and the first weight of the filtered attribute information, the target decision data for each micro-site deployment scenario is determined.

[0185] In one possible implementation, the first determining module is specifically used to: obtain weight reference values ​​for the attribute information; wherein the weight reference values ​​are used to indicate the importance of each attribute information under the micro-site deployment scheme;

[0186] The weight reference values ​​of the same attribute information for different micro-site deployment schemes are processed to obtain the first weight of the attribute information.

[0187] In one possible implementation, the first determining module is specifically used to: perform mean processing on the weight reference values ​​of the same attribute information for different micro-site deployment schemes to obtain the mean processing result;

[0188] The mean processing result is normalized to obtain the first weight of each attribute information.

[0189] In one possible implementation, the deployment module is specifically used to: determine the maximum and minimum decision data in the target decision data for each micro-station deployment scenario;

[0190] Based on the maximum and minimum decision data, the decision value for this micro-site deployment scenario is determined;

[0191] The micro-site deployment scheme corresponding to the largest decision value among the decision values ​​of each micro-site deployment scenario is determined as the target deployment scheme.

[0192] In one possible implementation, the deployment module is specifically used to: calculate the sum between the maximum decision data and the minimum decision data for each micro-site deployment scenario, and obtain a sum value;

[0193] Calculate the ratio between the minimum decision data of the micro-site deployment scenario and the sum value corresponding to the micro-site deployment scenario, and determine the decision value of the micro-site deployment scenario based on the ratio calculation result.

[0194] The processing flow of each module in the device and the interaction flow between each module can be referred to the relevant descriptions in the above method embodiments, and will not be detailed here.

[0195] Corresponding to Figure 1 In addition to the micro-site deployment method, this disclosure also provides an electronic device 400, such as... Figure 4 The diagram shown is a structural schematic of an electronic device 400 provided in an embodiment of this disclosure, including:

[0196] The system includes a processor 41, a memory 42, and a bus 43. The memory 42 stores execution instructions and includes main memory 421 and external memory 422. The main memory 421, also called internal memory, temporarily stores the computational data in the processor 41, as well as data exchanged with external memory such as a hard disk. The processor 41 exchanges data with the external memory 422 through the main memory 421. When the electronic device 400 is running, the processor 41 communicates with the memory 42 through the bus 43, causing the processor 41 to execute the following instructions:

[0197] Obtain the indicator parameter values ​​of each attribute information of the micro-site in various micro-site deployment scenarios;

[0198] A first weight is determined for each of the attribute information; wherein the first weight is used to indicate the importance of the attribute information;

[0199] Based on the indicator parameter values ​​and the first weight, target decision data for each micro-site deployment scenario is determined; wherein, the target decision data is used to indicate the importance of each attribute information in the corresponding micro-site deployment scenario;

[0200] Based on the target decision data, the target deployment scheme for the micro-site to be deployed in the region is determined among multiple micro-site deployment schemes, and the target deployment scheme is deployed in the region to be deployed.

[0201] This disclosure also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the micro-site deployment method described in the above-described method embodiments. The storage medium can be a volatile or non-volatile computer-readable storage medium.

[0202] This disclosure also provides a computer program product carrying program code. The program code includes instructions that can be used to execute the steps of the micro-site deployment method described in the above method embodiments. For details, please refer to the above method embodiments, which will not be repeated here.

[0203] The aforementioned computer program product can be implemented through hardware, software, or a combination thereof. In one optional embodiment, the computer program product is specifically embodied in a computer storage medium; in another optional embodiment, the computer program product is specifically embodied in a software product, such as a software development kit (SDK), etc.

[0204] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems and devices described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. In the several embodiments provided in this disclosure, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division; in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Another point is that the displayed or discussed mutual coupling or direct coupling or communication connection may be through some communication interfaces; the indirect coupling or communication connection of devices or units may be electrical, mechanical, or other forms.

[0205] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0206] In addition, the functional units in the various embodiments of this disclosure 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.

[0207] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a processor-executable, non-volatile, computer-readable storage medium. Based on this understanding, the technical solution of this disclosure, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this disclosure. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0208] Finally, it should be noted that the above-described embodiments are merely specific implementations of this disclosure, used to illustrate the technical solutions of this disclosure, and not to limit it. The protection scope of this disclosure is not limited thereto. Although this disclosure has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some of the technical features, within the scope of the technology disclosed in this disclosure. Such modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this disclosure, and should all be covered within the protection scope of this disclosure. Therefore, the protection scope of this disclosure should be determined by the protection scope of the claims.

Claims

1. A method for deploying a micro-site, characterized in that, include: Obtain the indicator parameter values ​​of each attribute information of the micro-site in various micro-site deployment scenarios; A first weight is determined for each of the attribute information; wherein the first weight is used to indicate the importance of the attribute information; Based on the indicator parameter values ​​and the first weight, target decision data for each micro-site deployment scenario is determined; wherein, the target decision data is used to indicate the importance of each attribute information in the corresponding micro-site deployment scenario; Based on the target decision data, the target deployment scheme for the micro-site to be deployed in the area to be deployed is determined among multiple micro-site deployment schemes, and the target deployment scheme is deployed in the area to be deployed. Based on the aforementioned indicator parameter values, the correlation between any two attribute information for each of the micro-site deployment scenarios is determined; Based on the correlation, the attribute information associated with each micro-site deployment scenario is filtered to obtain filtered attribute information; wherein, the correlation between any two filtered attribute information is less than or equal to a preset correlation threshold. Based on the index parameter values ​​of the filtered attribute information and the first weight of the filtered attribute information, the target decision data for each micro-site deployment scenario is determined.

2. The method according to claim 1, characterized in that, Deploying the target deployment scheme in the area to be deployed includes: Determine the grid cells to be deployed in the area to be deployed for the target deployment scheme; The target deployment scheme for deploying the micro-stations in the deployment grid of the deployment area.

3. The method according to claim 2, characterized in that, Determining the grid cells to be deployed in the area to be deployed for the target deployment scheme includes: The area to be deployed is rasterized to obtain multiple target rasters; Determine the raster value for each of the target raster cells; The target grid that meets the preset grid value conditions is determined as the grid to be deployed.

4. The method according to claim 3, characterized in that, Determining the raster value of each of the target raster cells includes: Obtain the analysis dimension value for each target raster; wherein the analysis dimension value is used to indicate the raster attribute value of the target raster; Determine the importance of each value in the analysis dimension; The raster value of each target raster is determined based on the analysis dimension value and the importance of that analysis dimension value.

5. The method according to claim 1, characterized in that, Determining the first weight for each of the attribute information includes: Obtain the weight reference value of the attribute information; wherein, the weight reference value is used to indicate the importance of each attribute information under the micro-site deployment scheme; The weight reference values ​​of the same attribute information for different micro-site deployment schemes are processed to obtain the first weight of the attribute information.

6. The method according to claim 5, characterized in that, The process of processing the weight reference values ​​of the same attribute information for different micro-site deployment schemes to obtain the first weight of the attribute information includes: The weight reference values ​​of the same attribute information for different micro-site deployment schemes are averaged to obtain the averaged result; The mean processing result is normalized to obtain the first weight of each attribute information.

7. The method according to claim 1, characterized in that, The step of determining the target deployment scheme for the micro-site to be deployed in the region based on the target decision data includes: Determine the maximum and minimum decision data from the target decision data in each micro-station deployment scenario; Based on the maximum and minimum decision data, the decision value for this micro-site deployment scenario is determined; The micro-site deployment scheme corresponding to the largest decision value among the decision values ​​of each micro-site deployment scenario is determined as the target deployment scheme.

8. The method according to claim 7, characterized in that, The determination of the decision value for the micro-site deployment scenario based on the maximum decision data and the minimum decision data includes: Calculate the sum between the maximum and minimum decision data for each micro-site deployment scenario to obtain the sum value; Calculate the ratio between the minimum decision data of the micro-site deployment scenario and the sum value corresponding to the micro-site deployment scenario, and determine the decision value of the micro-site deployment scenario based on the ratio calculation result.

9. A micro-station deployment device, characterized in that, include: The acquisition module is used to obtain the indicator parameter values ​​of each attribute information of the micro-site in various micro-site deployment scenarios; A first determining module is configured to determine a first weight for each of the attribute information; wherein the first weight is used to indicate the importance of the attribute information; The second determining module is used to determine target decision data for each micro-site deployment scenario based on the indicator parameter value and the first weight; wherein the target decision data is used to indicate the importance of each attribute information in the corresponding micro-site deployment scenario; The deployment module is used to determine the target deployment scheme for the micro-site to be deployed in the area to be deployed based on the target decision data and among multiple micro-site deployment schemes, and to deploy the target deployment scheme in the area to be deployed. The second determining module is further configured to determine the correlation between any two attribute information for each of the micro-station deployment scenarios based on the index parameter values; Based on the correlation, the attribute information associated with each micro-site deployment scenario is filtered to obtain filtered attribute information; wherein, the correlation between any two filtered attribute information is less than or equal to a preset correlation threshold. Based on the index parameter values ​​of the filtered attribute information and the first weight of the filtered attribute information, the target decision data for each micro-site deployment scenario is determined.

10. An electronic device, characterized in that, include: The device includes a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the memory via the bus. When the machine-readable instructions are executed by the processor, the steps of the micro-site deployment method as described in any one of claims 1 to 8 are performed.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, performs the steps of the micro-site deployment method as described in any one of claims 1 to 8.

12. A computer program product, characterized in that, The computer program product is stored in a storage medium, and the program product is executed by at least one processor to implement the steps of the micro-site deployment method as described in any one of claims 1 to 8.

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