Base station site selection method and device, electronic equipment and storage medium

Abstract

The invention provides a base station site selection method and device, electronic equipment and a storage medium, and belongs to the technical field of wireless communication, and the method comprises the steps: determining the number of cells based on the service information of a to-be-planned region, the service information representing the service requirements of the to-be-planned region, and the number of cells being the number of cells needing the to-be-planned region; based on the number of the cells, clustering the ToB terminals by using a K-means clustering algorithm to obtain a clustering result, the clustering result comprising a plurality of class clusters; and taking the center point of each class cluster as a base station address. According to the base station site selection method and device, the electronic equipment and the storage medium provided by the invention, the characteristics of the ToB service are comprehensively considered, the 5G private network planning is quantitatively evaluated, and the automatic planning of the 5G site is realized.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technology, and in particular to a base station site selection method, device, electronic equipment and storage medium. Background Art

[0002] With the continuous emergence of 5G industry applications, 5G private network planning has become a new topic. 5G private network refers to a mobile communication network tailored for a specific industry or enterprise to meet their specific business needs. When planning a 5G private network, it is necessary to comprehensively consider the coverage, capacity requirements, latency requirements, cost control and other issues of the 5G private network.

[0003] At present, 5G site planning is usually based on the existing 4G site, combined with coverage simulation requirements, and based on expert experience. However, ToB business needs are different from ToC business needs. A considerable proportion of ToB terminal locations and business needs are relatively fixed (such as video surveillance backhaul). The existing 5G site planning method does not take into account the characteristics of ToB 5G services. In addition, site planning based on expert experience relies on expert experience and cannot be quantitatively analyzed. Moreover, the level of automation and intelligence of this method is not high.

[0004] Therefore, how to automatically plan 5G sites based on the characteristics of ToB services has become a technical problem that needs to be solved urgently. Summary of the invention

[0005] The present invention provides a base station site selection method, device, electronic device and storage medium to address the defects in the prior art that the 5G site planning method does not take the characteristics of ToB services into consideration sufficiently, relies on expert experience and cannot perform quantitative analysis.

[0006] The present invention provides a base station site selection method, comprising: Determining the number of cells based on service information of the area to be planned, wherein the service information represents the service demand of the area to be planned, and the number of cells is the number of cells required in the area to be planned; Based on the number of cells, clustering the ToB terminals using a K-means clustering algorithm to obtain a clustering result, wherein the clustering result includes a plurality of clusters; The center point of each cluster is used as the base station address.

[0007] According to a base station site selection method provided by the present invention, the determining of the number of cells based on the service information of the area to be planned includes: The number of cells is determined based on the area of ​​the area to be planned, the uplink air interface resource demand, the service concurrency rate, the coverage area of ​​the cells in the used frequency band, the coverage area redundancy coefficient, the maximum uplink air interface resource of the cells in the used frequency band and the uplink capacity redundancy coefficient, wherein the coverage area of ​​the cells in the used frequency band is the maximum value of the coverage area of ​​a single cell in the frequency band used for networking.

[0008] According to a base station site selection method provided by the present invention, the number of cells is calculated based on the following formula: ; in, Indicates the number of cells, Indicates the area of ​​the area to be planned. represents the coverage area redundancy coefficient, Indicates the coverage area of ​​the cell using the frequency band. Indicates the uplink air interface resource requirements. Indicates the business concurrency rate. represents the uplink capacity redundancy factor, Indicates the maximum uplink air interface resources of the cell in the used frequency band.

[0009] According to a base station site selection method provided by the present invention, clustering the ToB terminals based on the number of cells using a K-means clustering algorithm to obtain a clustering result includes: Using the number of cells as an initial K value, clustering the ToB terminals based on preset restriction conditions; If a valid clustering result can be obtained under the preset restriction condition, the number of cells is used as the planned number of base stations, and the valid clustering result is used as the clustering result; If a valid clustering result cannot be obtained under the preset restriction condition, the number of cells is updated based on a preset method, and the process returns to the step of using the number of cells as the initial K value and clustering the ToB terminals based on the preset restriction condition.

[0010] According to a base station site selection method provided by the present invention, the preset restriction conditions include: The capacity of each of the clusters is less than or equal to the product of the cell capacity threshold and the single cell capacity.

[0011] According to a base station site selection method provided by the present invention, the preset restriction conditions include: The sum of the squares of the distances of all ToB terminals in all clusters to the center points of each cluster is the smallest.

[0012] The present invention also provides a base station site selection device, comprising the following modules: A calculation module, used to: determine the number of cells based on the service information of the area to be planned, wherein the service information represents the service demand of the area to be planned, and the number of cells is the number of cells required in the area to be planned; A clustering module, used to: cluster the ToB terminals using a K-means clustering algorithm based on the number of cells to obtain a clustering result, wherein the clustering result includes a plurality of clusters; The site selection module is used to: use the center point of each cluster as the base station address.

[0013] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, any of the base station site selection methods described above is implemented.

[0014] The present invention also provides a non-transitory computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the base station site selection method described in any one of the above is implemented.

[0015] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the base station site selection method described above is implemented.

[0016] The base station site selection method, device, electronic device and storage medium provided by the present invention determine the number of cells based on the business information of the area to be planned, the business information represents the business demand of the area to be planned, and the number of cells is the number of cells required in the area to be planned, that is, according to the business characteristics of the area to be planned, the number of cells to be planned is preliminarily determined, so that when planning a 5G private network, the number of cells can be determined according to the business characteristics of the 5G private network, and there is no demand for satisfying the 5G private network; based on the number of cells, the K-means clustering algorithm is used to cluster the ToB terminal to obtain a clustering result, and the clustering result includes multiple clusters, that is, clustering is performed according to the determined number of cells, and a cluster in the clustering result corresponds to a cell, so that the ToB terminal is divided into the corresponding cell, and the quantitative analysis of the cell planning is realized, which provides a basis for the subsequent base station address determination; the center point of each of the clusters is used as the base station address, so that the base station maximizes the coverage of the cell. In summary, the base station site selection method provided by the present invention comprehensively considers the characteristics of the ToB business, quantitatively evaluates the 5G private network planning, and realizes automatic planning of the 5G site. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 This is one of the flow charts of the base station site selection method provided by the present invention.

[0019] Figure 2 This is the second flow chart of the base station site selection method provided by the present invention.

[0020] Figure 3 It is a structural schematic diagram of the base station site selection device provided by the present invention.

[0021] Figure 4 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0023] It should be noted that in the description of the embodiments of the present invention, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "include one..." do not exclude the existence of other identical elements in the process, method, article or device including the elements. The orientation or position relationship indicated by the terms "upper", "lower" and the like is based on the orientation or position relationship shown in the drawings, which is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention. Unless otherwise clearly specified and limited, the terms "installed", "connected" and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected, or indirectly connected through an intermediate medium, or it can be a connection between two elements. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0024] The terms "first", "second", etc. in this application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0025] Combine the following Figure 1-Figure 4 The present invention describes a base station site selection method, device, electronic device and storage medium provided in an embodiment of the present invention.

[0026] Figure 1 This is one of the flow charts of the base station site selection method provided by the present invention; Figure 2 This is the second flow chart of the base station site selection method provided by the present invention; like Figure 1 and Figure 2 As shown, including but not limited to the following steps: S110, determining the number of cells based on service information of the area to be planned, where the service information represents service demand of the area to be planned, and the number of cells is the number of cells required in the area to be planned; S120, clustering the ToB terminals using a K-means clustering algorithm based on the number of cells to obtain a clustering result, where the clustering result includes a plurality of clusters; S130: Taking the center point of each cluster as a base station address.

[0027] It should be noted that the execution subject of the base station site selection method provided in the embodiment of the present application can be a server, a computer device, such as a tablet computer, a laptop computer, an ultra-mobile personal computer (UMPC), a netbook, etc.

[0028] In S110, the area to be planned is an area that requires 5G private network planning; the business information of the area to be planned represents the business characteristics of the area to be planned, for example, it may include but is not limited to the business attributes of the area to be planned (video surveillance, remote control, etc.), business demand, real-time coefficient (sensitivity of the business in the area to be planned to delay), etc.

[0029] Optionally, the real-time coefficient Msi is ≥ 1. For the service with the lowest delay sensitivity, the real-time coefficient Msi is set to 1. The real-time coefficient Msi for other types of services can be set according to actual needs.

[0030] In S120, the number of cells is taken as K value, and the ToB terminals are clustered according to the location information of the ToB terminals to obtain a clustering result including multiple clusters, wherein each cluster is a cell, and a base station is planned for each cell.

[0031] In S130, for any cluster, the center point is the average value of the position coordinates of the ToB terminals in the cluster, and the center point is used as the address of the base station in the cluster to ensure that the base station can cover the cell.

[0032] The base station site selection method provided by the embodiment of the present invention determines the number of cells based on the business information of the area to be planned, the business information represents the business demand of the area to be planned, and the number of cells is the number of cells required in the area to be planned, that is, according to the business characteristics of the area to be planned, the number of cells to be planned is preliminarily determined, so that when planning a 5G private network, the number of cells can be determined according to the business characteristics of the 5G private network, and there is no demand for the 5G private network; based on the number of cells, the K-means clustering algorithm is used to cluster the ToB terminal to obtain a clustering result, and the clustering result includes multiple clusters, that is, clustering is performed according to the determined number of cells, and a cluster in the clustering result corresponds to a cell, so that the ToB terminal is divided into the corresponding cell, and the quantitative analysis of the cell planning is realized, which provides a basis for the subsequent base station address determination; the center point of each of the clusters is used as the base station address, so that the base station coverage of the cell is maximized. In summary, the base station site selection method provided by the present invention comprehensively considers the characteristics of the ToB business, quantitatively evaluates the 5G private network planning, and realizes automatic planning of 5G site.

[0033] In an optional embodiment, determining the number of cells based on the service information of the area to be planned includes: The number of cells is determined based on the area of ​​the area to be planned, the uplink air interface resource demand, the service concurrency rate, the coverage area of ​​the cells in the used frequency band, the coverage area redundancy coefficient, the maximum uplink air interface resource of the cells in the used frequency band and the uplink capacity redundancy coefficient, wherein the coverage area of ​​the cells in the used frequency band is the maximum value of the coverage area of ​​a single cell in the frequency band used for networking.

[0034] Here, considering that ToB services are basically uplink-restricted, the uplink capacity (i.e., uplink air interface resource demand) is used as the evaluation basis.

[0035] In an embodiment of the present invention, the coverage area of ​​the cell in the frequency band used is the maximum coverage area of ​​a single cell in the frequency band used for networking, which can be determined according to the actual network coverage situation; the coverage area redundancy coefficient is greater than 1, which is used to reserve additional coverage area to ensure that the 5G base station of a single cell can stably cover the cell.

[0036] In an embodiment of the present invention, the maximum uplink air interface resources of the cell in the used frequency band can be determined according to the actual uplink capacity of the network; the uplink capacity redundancy coefficient is greater than 1, which is used to reserve additional uplink capacity to ensure that the 5G base station of a single cell can meet the uplink air interface resource requirements of the cell.

[0037] The base station site selection method provided in the embodiment of the present invention comprehensively considers the area of ​​the area to be planned, the uplink capacity, the service concurrency rate, and the cell coverage area of ​​the used frequency band, accurately determines the number of cells, and reserves additional resources through the redundancy coefficient to ensure that the 5G base station of a single cell can meet the communication needs of one cell.

[0038] Furthermore, the number of cells is calculated based on the following formula: ; in, Indicates the number of cells, Indicates the area of ​​the area to be planned. represents the coverage area redundancy coefficient, Indicates the coverage area of ​​the cell using the frequency band. Indicates the uplink air interface resource requirements. Indicates the business concurrency rate. represents the uplink capacity redundancy factor, Indicates the maximum uplink air interface resources of the cell in the used frequency band.

[0039] In an optional embodiment, clustering the ToB terminals based on the number of cells using a K-means clustering algorithm to obtain a clustering result includes: Using the number of cells as an initial K value, clustering the ToB terminals based on preset restriction conditions; If a valid clustering result can be obtained under the preset restriction condition, the number of cells is used as the planned number of base stations, and the valid clustering result is used as the clustering result; If a valid clustering result cannot be obtained under the preset restriction condition, the number of cells is updated based on a preset method, and the process returns to the step of using the number of cells as the initial K value and clustering the ToB terminals based on the preset restriction condition.

[0040] Specifically, the initial K value is set to , cluster the ToB terminals. If the clustering result of the preset restriction conditions can be obtained, the process ends. To plan the number of base stations, the center points of various clusters are set as reference locations for base station site selection; if the clustering result that meets the preset constraints cannot be obtained, the number of cells, that is, the K value, is updated, and the ToB terminals are clustered based on the new K value until a valid clustering result is obtained.

[0041] Optionally, the preset method is to increase the K value by a preset amount, taking the preset amount being 1 as an example, that is, the new K value is the original K value plus 1.

[0042] The following takes the preset mode of adding 1 to the K value as an example to illustrate the base station site selection method provided by the embodiment of the present invention: The ToB terminals are clustered based on the K-means clustering algorithm, where the initial K value is set to ; If a clustering result that meets the preset constraints can be obtained, the process ends. The number of planned base stations is the center point of each cluster in the clustering result, which is the reference location for base station site selection; If a clustering result that meets the preset constraints cannot be obtained, the K value is increased by 1 as the new K value, and the process returns to the step of clustering the ToB terminals based on the K-means clustering algorithm until a clustering result that meets the preset constraints can be obtained.

[0043] The base station site selection method provided by the embodiment of the present invention uses the number of cells as the initial K value, adjusts the K value according to the clustering result, improves the reliability of the clustering analysis result, and achieves optimal base station coverage.

[0044] Furthermore, the preset restriction conditions include: The capacity of each of the clusters is less than or equal to the product of the cell capacity threshold and the single cell capacity.

[0045] Specifically, let the Euclidean distance between each node (ToB terminal) and the center point of its cluster be d i , let K3 be the cell capacity threshold, the single cell capacity be P, let the equivalent capacity of all sampling points in each cluster be R, then R<P*K3.

[0046] Here, the value of the cell capacity threshold value K3 can refer to the uplink super busy cell single user rate deterioration standard. Specifically, when the uplink resource utilization rate of the cell approaches or exceeds the preset threshold, the network will consider the cell to be in an over-busy state. At this time, if the uplink rate felt by a single user drops to a certain extent, such as lower than a certain minimum guaranteed rate, or key performance indicators such as call drop rate, connection rate, and bit error rate deteriorate significantly, it can be considered that the single user rate deterioration has reached the standard for early warning or intervention. Optionally, K3=0.75.

[0047] Optionally, the capacity R is calculated based on the following formula: ; in, Indicates the uplink air interface resource requirements. Indicates the business concurrency rate. is the path calculation compensation parameter. In the case of free space propagation, when the distance between the terminal and the cluster center increases, the RSRP (Reference Signal Received Power) received in the uplink decreases, the corresponding SINR (Signal-to-Interference-plus-Noise Ratio) decreases, the CQI (Channel Quality Indicator) decreases, and the MCS (Modulation and Coding Scheme) modulation order decreases, resulting in a decrease in the coding rate. Set T as the path calculation compensation parameter (T<=1), where T is related to log(d i ) is related to each other, which can be referred to the coding rate conversion in the 3gpp protocol, where the closest point in the cluster (i.e., d i Minimum) T value is 1.

[0048] The base station site selection method provided in an embodiment of the present invention sets a cluster capacity threshold, so as to ensure optimal coverage while meeting capacity when using the K-means clustering method for 5G private network planning.

[0049] In an optional embodiment, the preset restriction condition includes: The sum of the squares of the distances of all ToB terminals in all clusters to the center points of each cluster is the smallest.

[0050] Here, the sum of the squares of the distances of all ToB terminals in all clusters from the center points of all clusters is the smallest, which means that the sum of the squares of the Euclidean distances of all ToB terminals in all clusters from the center points of the clusters is the smallest, that is, ΣΣd i 2 For ease of understanding, the following is an explanation in conjunction with a specific embodiment: Assuming K=2, that is, the clustering result includes 2 clusters, the following two clustering results can be obtained: Suppose the first clustering result is: the first cluster contains 2 ToB terminals, namely ToB1 and ToB2, whose Euclidean distances to the center point of the cluster are d11 and d12 respectively; the second cluster contains 2 ToB terminals, namely ToB3 and ToB4, whose Euclidean distances to the center point of the cluster are d13 and d14 respectively; then in the first clustering result, the sum of the squares of the distances of each ToB terminal in all clusters to the center point of each cluster is ; Assume that the second clustering result is: the first cluster contains one ToB terminal, ToB1, whose Euclidean distance to the center point of the cluster is d21; the second cluster contains three ToB terminals, ToB2, ToB3 and ToB4, whose Euclidean distances to the center point of the cluster are d22, d23 and d24 respectively; then in the second clustering result, the sum of the squares of the distances of all ToB terminals in all clusters from the center points of each cluster is ; like , then the first clustering result is selected as the final clustering result; if , then the second clustering result is selected as the final clustering result.

[0051] Optionally, the preset restriction condition also includes: The distance between each ToB terminal in each cluster is Σd from the cluster center point i 2 Minimum variance.

[0052] Specifically, for any cluster, the sum of the distances between each ToB terminal and the center point of the cluster is Σd i 2 , Σd of each cluster i 2 The variance is the smallest. For ease of understanding, the following is described in conjunction with a specific embodiment: Assuming K=2, that is, the clustering result includes 2 clusters, the following two clustering results can be obtained: Assume that the first clustering result is: the first cluster contains 3 ToB terminals, namely ToB1, ToB2 and ToB3, whose Euclidean distances to the center point of the cluster are d11, d12 and d13 respectively; the second cluster contains 2 ToB terminals, namely ToB4 and ToB5, whose Euclidean distances to the center point of the cluster are d14 and d15 respectively; then in the first clustering result, the first cluster , the second cluster , the first cluster and the second cluster The variance of is σ1; Assume that the second clustering result is: the first cluster contains two ToB terminals, namely ToB1 and ToB2, whose Euclidean distances to the center point of the cluster are d21 and d22 respectively; the second cluster contains three ToB terminals, namely ToB3, ToB4 and ToB5, whose Euclidean distances to the center point of the cluster are d23, d24 and d25 respectively; then in the second clustering result, the first cluster , the second cluster , the first cluster and the second cluster The variance of is σ2; like , then the first clustering result is selected as the final clustering result; if , then the second clustering result is selected as the final clustering result.

[0053] The base station site selection method provided in the embodiment of the present invention adopts grid-level data analysis to greatly reduce the granularity of network analysis and improve the reliability of analysis results; and uses cell coverage consistency as a quantitative evaluation method, so that the result is more accurate.

[0054] The base station site selection device provided in an embodiment of the present application is described below. The base station site selection device described below and the base station site selection method described above can be referenced to each other.

[0055] Figure 3 is a schematic diagram of the structure of the base station site selection device provided by the present invention, such as Figure 3 As shown, the base station site selection device may include but is not limited to; The calculation module 310 is used to determine the number of cells based on the service information of the area to be planned, wherein the service information represents the service demand of the area to be planned, and the number of cells is the number of cells required in the area to be planned; A clustering module 320 is used to: cluster the ToB terminals using a K-means clustering algorithm based on the number of cells to obtain a clustering result, where the clustering result includes a plurality of clusters; The site selection module 330 is used to: use the center point of each cluster as the base station address.

[0056] It should be noted that the base station site selection device provided in the embodiment of the present invention can execute the base station site selection method described in any of the above embodiments during specific operation, which will not be elaborated in this embodiment.

[0057] The base station site selection device provided by the embodiment of the present invention determines the number of cells based on the business information of the area to be planned, the business information represents the business demand of the area to be planned, and the number of cells is the number of cells required in the area to be planned, that is, according to the business characteristics of the area to be planned, the number of cells to be planned is preliminarily determined, so that when planning a 5G private network, the number of cells can be determined according to the business characteristics of the 5G private network, and there is no demand for the 5G private network; based on the number of cells, the K-means clustering algorithm is used to cluster the ToB terminal to obtain a clustering result, and the clustering result includes multiple clusters, that is, clustering is performed according to the determined number of cells, and one cluster in the clustering result corresponds to one cell, so that the ToB terminal is divided into the corresponding cell, and the quantitative analysis of the cell planning is realized, which provides a basis for the subsequent base station address determination; the center point of each of the clusters is used as the base station address, so that the base station maximizes the coverage of the cell. In summary, the base station site selection method provided by the present invention comprehensively considers the characteristics of the ToB business, quantitatively evaluates the 5G private network planning, and realizes automatic planning of 5G site.

[0058] Figure 4 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 4 As shown, the electronic device may include: a processor 410, a communications interface 420, a memory 430 and a communication bus 440, wherein the processor 410, the communications interface 420 and the memory 430 communicate with each other through the communication bus 440. The processor 410 may call the logic instructions in the memory 430 to execute the base station site selection method, which includes: determining the number of cells based on the service information of the area to be planned, the service information represents the service demand of the area to be planned, and the number of cells is the number of cells required in the area to be planned; based on the number of cells, clustering the ToB terminals using the K-means clustering algorithm to obtain a clustering result, the clustering result includes multiple clusters; and taking the center point of each cluster as the base station address.

[0059] In addition, the logic instructions in the above-mentioned memory 430 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0060] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the base station site selection method provided by the above methods, the method including: determining the number of cells based on the business information of the area to be planned, the business information represents the business demand of the area to be planned, and the number of cells is the number of cells required in the area to be planned; based on the number of cells, using the K-means clustering algorithm to cluster the ToB terminals to obtain a clustering result, the clustering result includes multiple clusters; and using the center point of each of the clusters as the base station address.

[0061] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the base station site selection method provided by the above-mentioned methods, the method comprising: determining the number of cells based on the business information of the area to be planned, the business information representing the business demand of the area to be planned, and the number of cells being the number of cells required in the area to be planned; based on the number of cells, clustering the ToB terminals using a K-means clustering algorithm to obtain a clustering result, the clustering result comprising a plurality of clusters; and using the center point of each of the clusters as the base station address.

[0062] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0063] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0064] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A base station site selection method, It is characterized in that include: Determining the number of cells based on service information of the area to be planned, wherein the service information represents the service demand of the area to be planned, and the number of cells is the number of cells required in the area to be planned; Based on the number of cells, clustering the ToB terminals using a K-means clustering algorithm to obtain a clustering result, wherein the clustering result includes a plurality of clusters; The center point of each cluster is used as the base station address.

2. The base station site selection method according to claim 1, It is characterized in that The determining the number of cells based on the service information of the area to be planned includes: The number of cells is determined based on the area of ​​the area to be planned, the uplink air interface resource demand, the service concurrency rate, the coverage area of ​​the cells in the used frequency band, the coverage area redundancy coefficient, the maximum uplink air interface resource of the cells in the used frequency band and the uplink capacity redundancy coefficient, wherein the coverage area of ​​the cells in the used frequency band is the maximum value of the coverage area of ​​a single cell in the frequency band used for networking.

3. The base station site selection method according to claim 2, It is characterized in that The number of cells is calculated based on the following formula: ； in, Indicates the number of cells, Indicates the area of ​​the area to be planned. represents the coverage area redundancy coefficient, Indicates the coverage area of ​​the cell using the frequency band. Indicates the uplink air interface resource requirements. Indicates the business concurrency rate. represents the uplink capacity redundancy factor, Indicates the maximum uplink air interface resources of the cell in the used frequency band.

4. The base station site selection method according to claim 2 or 3, It is characterized in that The clustering of the ToB terminals using the K-means clustering algorithm based on the number of cells to obtain a clustering result includes: Using the number of cells as an initial K value, clustering the ToB terminals based on preset restriction conditions; If a valid clustering result can be obtained under the preset restriction condition, the number of cells is used as the planned number of base stations, and the valid clustering result is used as the clustering result; If a valid clustering result cannot be obtained under the preset restriction condition, the number of cells is updated based on a preset method, and the process returns to the step of using the number of cells as the initial K value and clustering the ToB terminals based on the preset restriction condition.

5. The base station site selection method according to claim 4, It is characterized in that The preset restriction conditions include: The capacity of each of the clusters is less than or equal to the product of the cell capacity threshold and the single cell capacity.

6. The base station site selection method according to claim 1, It is characterized in that The preset restriction conditions include: The sum of the squares of the distances of all ToB terminals in all clusters to the center points of each cluster is the smallest.

7. A base station site selection device, It is characterized in that include: A calculation module, used to: determine the number of cells based on the service information of the area to be planned, wherein the service information represents the service demand of the area to be planned, and the number of cells is the number of cells required in the area to be planned; A clustering module, used to: cluster the ToB terminals using a K-means clustering algorithm based on the number of cells to obtain a clustering result, wherein the clustering result includes a plurality of clusters; The site selection module is used to: use the center point of each cluster as the base station address.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, It is characterized in that When the processor executes the program, the base station site selection method according to any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, It is characterized in that When the computer program is executed by a processor, the base station site selection method according to any one of claims 1 to 6 is implemented.

10. A computer program product comprising a computer program, It is characterized in that When the computer program is executed by a processor, the base station site selection method according to any one of claims 1 to 6 is implemented.

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