Cell coordination method, apparatus, electronic device, and medium

Abstract

The application provides a cell coordination method, device, electronic equipment and medium. The method comprises the following steps: acquiring parameter values of each cell under a preset parameter type, wherein the parameter type comprises unit flow value; calculating the weight values of the cells under the parameter type according to the parameter values of the cells under the preset parameter type; summing the weight values of each cell under the parameter type to obtain total weight values of the cells; taking the cell with the lowest total weight value as a cell to be moved, and performing cell coordination. The method can accurately perform cell coordination and improve the rationality of resource allocation.

Description

Technical Field

[0001] This application relates to communication technology, and more particularly to a cell coordination method, apparatus, electronic device, and medium. Background Technology

[0002] The procurement of base station resources by operators involves many processes and takes a long time. When a certain base station cell in the existing network urgently needs a certain type of base station resource but there is no inventory, it is necessary to coordinate with other cells to free up the corresponding resources from other base stations for emergency use until the resources are replenished.

[0003] Currently, the method of resource reallocation mainly depends on the importance of the area covered by the base station to be reallocated and the load of the base station, reallocating base station resources from cells with low load and unimportant coverage scenarios.

[0004] The drawback of this extensive approach is that it fails to accurately coordinate within communities and lacks rationality in resource allocation. Summary of the Invention

[0005] This application provides a cell coordination method, apparatus, electronic device, and medium to solve the problems of inaccurate cell coordination and insufficient rationality in resource allocation.

[0006] On the one hand, this application provides a cell coordination method, including: obtaining parameter values ​​of each cell under a preset parameter type, wherein the parameter type includes unit flow value; calculating the weight of each cell under the preset parameter type based on the parameter values ​​of each cell; summing the weights of each cell under the parameter type to obtain the total weight of each cell; and selecting the cell with the lowest total weight as the cell to be relocated and performing cell coordination.

[0007] In one possible implementation, obtaining the parameter values ​​of each cell under a preset parameter type includes: obtaining the traffic value parameters of each cell within a first time period, wherein the traffic value parameters include the total traffic generated by the cell within the first time period, the traffic generated by each access user accessing the cell, and the package price of each access user; for each cell, calculating the ratio of the traffic generated by each access user to the total traffic, multiplying the ratio by the package price of the access user to obtain the unit traffic value of each access user; summing the unit traffic values ​​of all access users accessing the cell within the first time period to obtain the parameter value of the unit traffic value of the cell; and calculating the weight of each cell under the preset parameter type based on the parameter values ​​of each cell includes: calculating the ratio of the parameter value of the unit traffic value of each cell to a preset first value to obtain the weight of each cell under the unit traffic value.

[0008] In one possible implementation, the parameter type further includes signal strength; obtaining the parameter value of each cell under the preset parameter type includes: selecting sampling points in each cell for sampling to obtain the MR coverage rate of each cell, which is used as the parameter value of the signal strength of each cell; calculating the weight of each cell under the preset parameter type based on the parameter value of each cell includes: using the weight corresponding to the parameter value of the signal strength of each cell as the weight of each cell under the signal strength according to the weight corresponding to different MR coverage rates.

[0009] In one possible implementation, the parameter type further includes the average number of access users; obtaining the parameter value of each cell under the preset parameter type includes: counting the number of access users of each cell in multiple preset time periods; for each cell, calculating the average number of access users in the multiple time periods to obtain the parameter value of the average number of access users of the cell; calculating the weight of each cell under the preset parameter type based on the parameter value of each cell includes: calculating the ratio of the parameter value of the average number of access users of each cell to a preset second value to obtain the weight of each cell under the average number of access users.

[0010] In one possible implementation, the parameter type further includes a scene type; obtaining the parameter value of each cell under the preset parameter type includes: taking the scene of the coverage area of ​​each cell as the parameter value of the scene type of each cell; calculating the weight of each cell under the parameter type based on the parameter value of each cell under the preset parameter type includes: taking the weight corresponding to the parameter value of the scene type of each cell as the weight of each cell under the scene type based on the weight corresponding to different scenes.

[0011] In one possible implementation, the parameter type further includes network performance; obtaining the parameter values ​​of each cell under the preset parameter type includes: calculating the call access success rate and call hold success rate of each cell in the first time period; for each cell, calculating the product of the call access success rate and call hold success rate of the cell to obtain the parameter value of the network performance of the cell; calculating the weight of each cell under the preset parameter type based on the parameter values ​​of each cell includes: calculating the ratio of the parameter value of the network performance of each cell to a preset third value to obtain the weight of each cell under the network performance.

[0012] In one possible implementation, the step of designating the cell with the lowest total weight as the cell to be relocated includes: if there is only one cell with the lowest total weight, then that cell is designated as the cell to be relocated; if there are multiple cells with the lowest total weight, then the weights of these multiple cells under the current parameter type are compared sequentially according to the priority of the parameter type until there is only one cell with the lowest weight under the current parameter type, then that cell is designated as the cell to be relocated.

[0013] On the other hand, this application provides a cell coordination device, comprising: a parameter acquisition module, configured to acquire parameter values ​​of each cell under a preset parameter type, wherein the parameter type includes unit traffic value; a weight acquisition module, configured to calculate the weight of each cell under the preset parameter type based on the parameter values ​​of each cell; and to sum the weights of each cell under the preset parameter type to obtain the total weight of each cell; and a coordination module, configured to select the cell with the lowest total weight as the cell to be relocated and perform cell coordination.

[0014] In one possible implementation, the parameter acquisition module is specifically used to: acquire traffic value parameters for each cell within a first time period, the traffic value parameters including the total traffic generated by the cell within the first time period, the traffic generated by each access user accessing the cell, and the package price of each access user; for each cell, calculate the ratio of the traffic generated by each access user to the total traffic, multiply the ratio by the package price of the access user to obtain the unit traffic value of each access user; sum the unit traffic values ​​of all access users accessing the cell within the first time period to obtain the unit traffic value generated by the cell; the weight acquisition module is specifically used to: calculate the ratio of the unit traffic value generated by each cell to a preset first value to obtain the weight of each cell under the unit traffic value.

[0015] In one possible implementation, the parameter type further includes signal strength; the parameter acquisition module is further specifically used to: select sampling points in each cell for sampling, and obtain the MR coverage rate of each cell as the parameter value of the signal strength of each cell; the weight acquisition module is further specifically used to: according to the weights corresponding to different MR coverage rates, take the weights corresponding to the parameter values ​​of the signal strength of each cell as the weights of each cell under the signal strength.

[0016] In one possible implementation, the parameter type further includes the average number of access users. The parameter acquisition module is further specifically used to: count the number of access users in each cell within a preset number of time periods; for each cell, calculate the average number of access users within the multiple time periods to obtain the parameter value of the average number of access users in the cell; the weight acquisition module is further specifically used to: calculate the ratio of the parameter value of the average number of access users in each cell to a preset second value to obtain the weight of each cell under the average number of access users.

[0017] In one possible implementation, the parameter type further includes a scene type, and the parameter acquisition module is further specifically used to: use the scene of the coverage area of ​​each cell as the parameter value of the scene type of each cell; the weight acquisition module is further specifically used to: use the weight corresponding to the parameter value of the scene type of each cell as the weight of each cell under the scene type according to the weight corresponding to different scenes.

[0018] In one possible implementation, the parameter type further includes network performance, and the parameter acquisition module is further specifically used to: calculate the call access success rate and call hold success rate of each cell in the first time period; for each cell, calculate the product of the call access success rate and call hold success rate of the cell to obtain the network performance of the cell; the weight acquisition module is further specifically used to: calculate the ratio of the network performance of each cell to a preset third value to obtain the weight of each cell under the network performance.

[0019] In one possible implementation, the coordination module is specifically used to: if there is only one cell with the lowest total weight, then that cell is designated as a cell to be relocated; if there are multiple cells with the lowest total weight, then the weights of these multiple cells under the current parameter type are compared sequentially according to the priority of the parameter type, until there is only one cell with the lowest weight under the current parameter type, then that cell is designated as a cell to be relocated.

[0020] In another aspect, this application provides an electronic device, including: a processor, and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the method described above.

[0021] In another aspect, this application provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, are used to implement the method described above.

[0022] The cell coordination method, apparatus, electronic device, and medium provided in this application acquire parameter values ​​for each cell under preset parameter types, including unit traffic value; calculate the weight of each cell under all parameter types based on the parameter values; sum the weights of each cell under all parameter types to obtain the total weight of each cell; and select the cell with the lowest total weight as the cell to be relocated for cell coordination. This scheme considers the dimension of unit traffic value to evaluate base station cells, more accurately and reasonably determining the cells to be relocated in cell coordination, thereby achieving effective and accurate cell coordination and improving the rationality of resource allocation. Attached Figure Description

[0023] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0024] Figure 1 The diagram above illustrates a flowchart of a cell coordination method provided in Embodiment 1 of this application.

[0025] Figure 2 The diagram below exemplarily illustrates a structural schematic of a cell coordination device provided in Embodiment 2 of this application;

[0026] Figure 3 The diagram below illustrates a structural schematic of a cell coordination electronic device provided in Embodiment 3 of this application.

[0027] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0028] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0029] In this application, a module refers to a functional module or a logical module. It can be in software form, where its function is implemented by a processor executing program code; or it can be in hardware form. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone.

[0030] Base station resources are categorized into several types, including hardware resources such as remote radio units and baseband resource boards, and software resources such as expansion licenses and licenses allowing a certain number of user accesses. By purchasing different licenses, operators can flexibly select specific network functions to maximize investment protection. When a base station in a certain cell urgently needs a particular base station resource but has no inventory, due to the numerous and time-consuming processes involved in procuring base station resources, operators can only coordinate with other cells to free up the corresponding resources from base stations in other cells for emergency use until the resources are replenished.

[0031] Currently, the selection of base station cells for resource reallocation mainly depends on the importance of the area covered by the cell being reallocated and the base station's load. The drawback of these methods is that they are extensive and lack comprehensive consideration, failing to accurately select cooperating cells for base station resource reallocation, thus failing to maximize the value of resource allocation.

[0032] The technical solutions of this application are illustrated below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0033] Example 1

[0034] Figure 1 This is a flowchart illustrating a cell coordination method provided in one embodiment of this application. Figure 1 As shown, the cell coordination method provided in this embodiment may include:

[0035] S101, Obtain the parameter values ​​of each cell under a preset parameter type, wherein the parameter type includes unit traffic value;

[0036] S102, calculate the weight of each cell under the preset parameter type based on the parameter value of each cell; and sum the weight of each cell under the parameter type to obtain the total weight of each cell.

[0037] S103: The community with the lowest total weight value is designated as the community to be relocated, and community coordination is carried out.

[0038] In practical applications, the execution entity of this embodiment can be a cell coordination device, which can be implemented by a computer program, such as application software; or it can be implemented as a medium storing relevant computer programs, such as a USB flash drive or cloud drive; or it can be implemented by a physical device that integrates or installs relevant computer programs, such as a chip or server.

[0039] Specifically, the cell coordination device sets different parameter types and obtains parameter values ​​for each type. There can be multiple parameter types, including but not limited to unit traffic value. The selection of other parameter types can be based on actual production needs, evaluating each base station cell from multiple dimensions to determine the optimal coordination cell; no restrictions are placed on this. Based on the parameter values ​​of each cell under the preset parameter types, a weight is assigned to that parameter type. The weights of all parameter types for each cell are added together to obtain the total weight of each base station cell. The base station cell with the lowest total weight is designated as the cell to be relocated, freeing up base station resources for emergency use until resources are replenished. This method determines the optimal cell to be relocated for cell coordination, improving the rationality of resource allocation.

[0040] For example, if a base station cell in the existing network needs a certain base station resource, calculate the parameter value of the unit traffic value of the other base station cells, determine the corresponding weight based on the parameter value, and select the base station cell with the lowest total weight as the cell to be transferred, and perform resource transfer.

[0041] There are several ways to obtain the parameter values ​​of each cell under the unit traffic value. In one example, S101 may specifically include:

[0042] Obtain the traffic value parameters of each cell in the first time period. The traffic value parameters include the total traffic generated by the cell in the first time period, the traffic generated by each access user accessing the cell, and the package price of each access user.

[0043] For each cell, the ratio of traffic generated by each access user to the total traffic is calculated, and the ratio is multiplied by the package price of the access user to obtain the unit traffic value of each access user; the unit traffic value of all access users accessing the cell during the first time period is summed to obtain the parameter value of the unit traffic value of the cell.

[0044] The step of calculating the weight of each cell under the preset parameter type based on the parameter values ​​of each cell includes:

[0045] The ratio of the parameter value of unit traffic value of each cell to a preset first value is calculated to obtain the weight of each cell under unit traffic value.

[0046] Specifically, the cell coordination device obtains the traffic value parameters of base station cell m within a certain period of time, including the total traffic L generated by the base station cell. m Traffic K generated by user n out of N access users n And the package price P corresponding to user n. nFor each base station cell, calculate the unit traffic value for each access user n, and sum the unit traffic values ​​of all users accessing base station cell m within that time period to obtain the average value P corresponding to 1 Gbit of traffic generated by that base station cell. m The specific formula is as follows:

[0047]

[0048] Based on the value corresponding to each Gbit of traffic generated by base station cell m, a weight is assigned, denoted as K1, which is the weight under the unit traffic value. K1 is P m The ratio to the first value, where the magnitude of the first value affects the weight of the base station cell under each parameter type and its proportion in the total weight, can be set according to the importance and value of each parameter type in actual application. This weight has no upper limit and can accurately reflect the user package level accessed by the base station cell. The larger the value, the more high-value users are accessing the base station cell, thus minimizing resource redundancy. By setting the parameter type to unit traffic value, the priority of base station cell resource redundancy is accurately assessed from the perspective of cell value, which helps improve the rationality of resource allocation during cell coordination.

[0049] For example, Table 1 shows an example of parameter values ​​and weights for a base station cell under unit traffic value provided in Embodiment 1 of this application. As shown in Table 1, the weight K1 = P m / 10, with no upper limit.

[0050] Table 1

[0051] Pm value K1 36 3.6 68 6.8 83 8.3 257 25.7 …… ……

[0052] To more comprehensively and accurately determine the priority of base station resource reallocation, in one example, the parameter type also includes signal strength; obtaining the parameter values ​​of each cell under the preset parameter type includes:

[0053] Sampling points are selected in each cell for sampling to obtain the MR coverage of each cell, which is used as the parameter value of the signal strength of each cell;

[0054] The step of calculating the weight of each cell under the preset parameter type based on the parameter values ​​of each cell includes:

[0055] Based on the weights corresponding to different MR coverage rates, the weights corresponding to the parameter values ​​of the signal strength of each cell are used as the weights of each cell under the signal strength.

[0056] Specifically, sampling points are selected within each base station cell for sampling, and the Reference Signal Receiving Power (RSRP) of each sampling point is calculated. To avoid misjudgment due to an insufficient number of sampling points, the number of sampling points in each base station cell is generally no less than 1000. The ratio of the number of sampling points with RSRP greater than or equal to a certain threshold to the total number of sampling points is calculated. The threshold is generally set to 110 dBm to obtain the MR coverage rate, which is used as a parameter value for the signal strength of the base station cell. Different weights are assigned to different MR coverage rates to obtain the weight K2 of each base station cell under the signal strength. For example, Table 2 shows an example of the correspondence between the parameter value and weight of a base station cell under the signal strength provided in Embodiment 1 of this application. As shown in Table 2, the correspondence between MR coverage rate and weight K2 is as follows.

[0057] Table 2

[0058] MR coverage K2 (0,60] 2 (60,70] 4 (70,80] 6 (80,90] 8 (90,100] 10

[0059] The higher the MR coverage, the higher the weight. This is because a higher MR coverage indicates a stronger signal strength from the base station cell, resulting in a better signal experience for users, making it less advisable to relocate resources from that cell. Conversely, a lower MR coverage indicates a weaker signal for users, making it less risky to relocate resources from that cell.

[0060] This embodiment uses MR coverage to describe signal strength, but other indicators can also be used to characterize signal strength in practical applications, and no restrictions are imposed here. By setting the parameter type to signal strength, the priority of base station cell resource reallocation can be accurately assessed from the perspective of signal strength, which is beneficial to improving the rationality of resource allocation during cell coordination.

[0061] Furthermore, in one example, the parameter type also includes the average number of access users; obtaining the parameter values ​​of each cell under the preset parameter type includes:

[0062] Count the number of users accessing the network in each community during multiple preset time periods;

[0063] For each cell, the average number of access users within the multiple time periods is calculated to obtain the parameter value of the average number of access users for that cell;

[0064] The step of calculating the weight of each cell under the preset parameter type based on the parameter values ​​of each cell includes:

[0065] The ratio of the average number of access users in each cell to a preset second value is calculated to obtain the weight of each cell under the average number of access users.

[0066] Specifically, the cell coordination device obtains the number of access users of the base station cell in different time periods and takes the average value as the parameter value U of the average number of access users. The number of access users can be obtained from the base station network management software, or other acquisition methods can be selected according to the actual application; there are no restrictions here. The ratio of the parameter value U of the average number of access users to a preset second value is calculated and denoted as the weight K3 of the base station cell under the average number of access users. The magnitude of the second value affects the weight of the base station cell under each parameter type and its proportion in the total weight. It can be set according to the importance of each parameter type and the magnitude of the parameter value in the actual application. The larger K3 is, the more access users there are, and it is not advisable to reallocate resources from that cell. By setting the parameter type to the average number of access users, the priority of base station cell resource reallocation can be accurately assessed from the dimension of scenario type importance, which is beneficial to improving the rationality of resource allocation during cell coordination.

[0067] Table 3

[0068]

[0069]

[0070] For example, Table 3 shows the parameter values ​​and weights of a base station cell under the average number of access users provided in Embodiment 1 of this application. As shown in Table 3, the weight K3 = U / 10. In order to avoid the weight being too large due to too many access users, the weight does not exceed 20.

[0071] Furthermore, in one example, the parameter type also includes a scenario type; obtaining the parameter values ​​of each cell under the preset parameter type includes:

[0072] The scene of each cell's coverage area is used as the parameter value for the scene type of each cell;

[0073] The step of calculating the weight of each cell under the preset parameter type based on the parameter values ​​of each cell includes:

[0074] Based on the weights corresponding to different scenarios, the weights corresponding to the parameter values ​​of the scenario type of each cell are used as the weights of each cell under the scenario type.

[0075] Specifically, based on the coverage area of ​​each base station cell, the scenario type of the coverage area is determined and used as the parameter value for the base station cell scenario type. This parameter value is not necessarily a numerical value but can be actual data, such as specific scenarios like schools, hospitals, or public places. Based on the importance of the scenario type, a weight K4 is assigned to the base station cell under that scenario type; this is the weight of the base station cell under that scenario type. By setting the parameter type to scenario type, the priority of base station cell resource reallocation can be accurately assessed from the perspective of scenario type importance.

[0076] For example, as shown in Table 4, Table 4 provides an example of parameter values ​​and weights for a scenario type of base station cell provided in Embodiment 1 of this application. Table 4 lists some scenario types, and the weight K4 ranges from 0 to 10. The higher the weight K4, the more important the scenario, and resource reallocation is not recommended.

[0077] Table 4

[0078]

[0079]

[0080] Furthermore, in one example, the parameter type also includes network performance; obtaining the parameter values ​​of each cell under the preset parameter type includes:

[0081] Calculate the call access success rate and call hold success rate for each cell during the first time period;

[0082] For each cell, the product of the call access success rate and the call hold success rate of that cell is calculated to obtain the parameter value of the network performance of that cell;

[0083] The step of calculating the weight of each cell under the preset parameter type based on the parameter values ​​of each cell includes:

[0084] The ratio of the network performance parameter value of each cell to a preset third value is calculated to obtain the weight of each cell under network performance.

[0085] Specifically, the cell coordination device statistically analyzes the performance indicators of the base station cell during this period. Depending on the different aspects applicable to measuring network performance, performance indicators can be categorized into many types. Here, we take the call access success rate and call hold success rate as indicators. In practical applications, other network performance indicators can also be selected, and there are no restrictions on them here. The call access success rate and call hold success rate indicate the success rate of a user accessing and staying on the network. The higher these two indicator values, the better the network performance, with a maximum value of 1. The ratio of the product of these two indicators to a set third value is recorded as the weight K5, which is the weight of the base station cell under network performance. The magnitude of the third value affects the weight of the base station cell under each parameter type and its proportion in the total weight. It can be set according to the importance of each parameter type and the parameter value of each parameter type in practical applications. For example, Table 5 shows the weight of a base station cell under network performance provided in Embodiment 1 of this application. As shown in Table 5, K5 = access success rate * call hold success rate * 10.

[0086] Table 5

[0087]

[0088]

[0089] By setting the parameter type to network performance, the priority of base station cell resource reallocation can be accurately assessed from the perspective of network performance, which helps to improve the rationality of resource allocation during cell coordination.

[0090] In cases where multiple cells have the lowest total weight, to achieve cell coordination, in one example, the cell with the lowest total weight is designated as the cell to be relocated, including:

[0091] If there is only one cell with the lowest total weight, then that cell will be designated as the cell to be relocated.

[0092] If there are multiple cells with the lowest total weight, then the weights of these cells under the current parameter type are compared sequentially according to the priority of the parameter type until there is only one cell with the lowest weight under the current parameter type. Then, that cell is designated as the cell to be relocated.

[0093] Specifically, the cell coordination device compares the total weight of each base station cell and selects the base station cell with the lowest total weight to perform cell coordination and resource reallocation. If the number of cells with the lowest total weight is greater than one, the weight of the base station cells under a certain parameter type is compared, and the base station cell with the lowest weight under that parameter type is selected to perform cell coordination. If the number of base station cells with the lowest weight under that parameter type is greater than one, the weight of each base station cell under the next parameter type is compared. The order of comparison is determined according to the priority of the parameter type, and the priority of the parameter type is set according to the importance of each parameter type in actual application.

[0094] For example, when a base station cell in the existing network needs a certain base station resource, the cell coordination device calculates the total weight of each base station cell and determines the cell to be relocated based on the total weight. The cell with the lowest total weight is selected as the base station cell to be relocated. If the total weights are equal, the base station cells are compared in the order of their weights under signal strength, unit traffic value, average number of access users, scenario type, and network performance indicators, and the base station cell with the lowest weight is selected as the base station cell to be relocated. For example, suppose cells A and B are the two cells with the lowest total weights, and their total weights are equal. Then, the weights of cells A and B under signal strength are compared first. If they are different, the cell with the smaller weight is selected as the cell to be relocated. Conversely, if the weights of cells A and B under signal strength are the same, the weights of cells A and B under unit traffic value are further compared, and the cell with the smaller weight is selected as the cell to be relocated. This process continues until the cell to be relocated is determined from cells A and B.

[0095] For another example, suppose a certain base station cell w requires a certain type of base station resource. Now, suppose there are four base station cells A, B, C, and D in the entire network that possess this type of base station resource. Then, calculate the weights of these four base station cells. The parameter values ​​and weight calculation methods for each parameter type are as described above. The information for each base station cell is shown in Table 6. The statistical time period is assumed to be the past week.

[0096] Table 6

[0097]

[0098] Finally, the total weights of A, B, C, and D are calculated to be 36.4, 42.2, 37.7, and 38.6, respectively. Base station cell A has the smallest weight, therefore the cell coordination device can free up base station resources from A for use by base station cell w. It should be noted that the above examples can be implemented individually or in combination, and the parameter types, in addition to unit traffic value, can include, but are not limited to, any one or more of the parameter types mentioned in the examples above.

[0099] This embodiment provides a cell coordination method. The cell coordination method, apparatus, electronic device, and medium provided in this application acquire parameter values ​​for each cell under preset parameter types, including unit traffic value. Based on the parameter values, the weights of each cell under all parameter types are calculated. The weights of each cell under all parameter types are summed to obtain the total weight of each cell. The cell with the lowest total weight is designated as the cell to be relocated, and cell coordination is performed. This scheme considers the dimension of unit traffic value to evaluate base station cells, more accurately and reasonably determining the cells to be relocated in cell coordination, thereby achieving effective and accurate cell coordination and improving the rationality of resource allocation.

[0100] Example 2

[0101] Figure 2 This is a schematic diagram of a cell coordination device provided in one embodiment of this application. Figure 2 As shown, the cell coordination method apparatus provided in this embodiment may include:

[0102] Parameter acquisition module 21 is used to acquire parameter values ​​of each cell under a preset parameter type, wherein the parameter type includes unit traffic value;

[0103] The weight acquisition module 22 is used to calculate the weight of each cell under the preset parameter type based on the parameter value of each cell; and to sum the weight of each cell under the parameter type to obtain the total weight of each cell.

[0104] Coordination module 23 is used to select the cell with the lowest total weight as the cell to be relocated and to perform cell coordination.

[0105] In practical applications, community coordination devices can be implemented through computer programs, such as application software; or they can be implemented as media storing relevant computer programs, such as USB flash drives or cloud drives; or they can be implemented through physical devices that integrate or install relevant computer programs, such as chips or servers.

[0106] Specifically, the parameter acquisition module 21 sets different parameter types and acquires the parameter values ​​for each type. There can be multiple parameter types, including but not limited to unit traffic value. The selection of other parameter types can be based on actual production needs, evaluating each base station cell from multiple dimensions to determine the optimal coordination cell; no restrictions are placed on this. The weight acquisition module 22 assigns a weight to each cell based on its parameter value under the preset parameter type, and adds the weights of all parameter types for each cell to obtain the total weight for each base station cell. The coordination module 23 designates the base station cell with the lowest total weight as the cell to be relocated, freeing up base station resources for emergency use until resources are replenished. This method determines the optimal cell to be relocated for cell coordination, improving the rationality of resource allocation.

[0107] There are multiple ways to obtain the parameter values ​​of each cell under the unit traffic value. In one example, the parameter acquisition module 21 is specifically used for:

[0108] Obtain the traffic value parameters of each cell in the first time period. The traffic value parameters include the total traffic generated by the cell in the first time period, the traffic generated by each access user accessing the cell, and the package price of each access user.

[0109] For each cell, the ratio of traffic generated by each access user to the total traffic is calculated, and the ratio is multiplied by the package price of the access user to obtain the unit traffic value of each access user; the unit traffic value of all access users accessing the cell during the first time period is summed to obtain the unit traffic value generated by the cell.

[0110] The weight acquisition module 22 is specifically used for:

[0111] Calculate the ratio of the value of a unit flow generated by each cell to a preset first value to obtain the weight of each cell under the unit flow value.

[0112] Specifically, the parameter acquisition module 21 acquires the traffic value parameters of base station cell m within a certain period of time, including the total traffic L generated by the base station cell. m Traffic K generated by user n out of N access users n And the package price P corresponding to user n. n For each base station cell, calculate the unit traffic value for each access user n, and sum the unit traffic values ​​of all users accessing base station cell m within that time period to obtain the average value P corresponding to 1 Gbit of traffic generated by that base station cell. m The specific formula is as follows:

[0113]

[0114] The weight acquisition module 22 assigns a weight, denoted as K1, to each 1 Gbit of traffic generated by base station cell m, based on the value of that traffic. K1 represents the weight per unit traffic value. m The ratio to the first value, where the magnitude of the first value affects the weight of the base station cell under each parameter type and its proportion in the total weight, can be set according to the importance and value of each parameter type in actual application. This weight has no upper limit and can accurately reflect the user package level accessed by the base station cell. The larger the value, the more high-value users are accessing the base station cell, thus minimizing resource redundancy. By setting the parameter type to unit traffic value, the priority of base station cell resource redundancy is accurately assessed from the perspective of cell value, which helps improve the rationality of resource allocation during cell coordination.

[0115] To more comprehensively and accurately determine the priority of base station resource reallocation, in one example, the parameter type also includes signal strength; the parameter acquisition module 21 is further specifically used for:

[0116] Sampling points are selected in each cell for sampling to obtain the MR coverage of each cell, which is used as the parameter value of the signal strength of each cell;

[0117] The weight acquisition module 22 is also specifically used for:

[0118] Based on the weights corresponding to different MR coverage rates, the weights corresponding to the parameter values ​​of the signal strength of each cell are used as the weights of each cell under the signal strength.

[0119] Specifically, the parameter acquisition module 21 selects sampling points within each base station cell for sampling and calculates the Reference Signal Receiving Power (RSRP) for each sampling point. To avoid misjudgment due to an insufficient number of sampling points, the number of sampling points for each base station cell is generally no less than 1000. The weight acquisition module 22 calculates the ratio of the number of sampling points with RSRP greater than or equal to a certain threshold to the total number of sampling points. The threshold is generally set to -110dBm to obtain the MR coverage rate, which is used as a parameter value for the signal strength of the base station cell. Different weights are assigned to different MR coverage rates to obtain the weight K2 for each base station cell under the signal strength.

[0120] The higher the MR coverage, the higher the weight. This is because a higher MR coverage indicates a stronger signal strength from the base station cell, resulting in a better signal experience for users, making it less advisable to relocate resources from that cell. Conversely, a lower MR coverage indicates a weaker signal for users, making it less risky to relocate resources from that cell.

[0121] This embodiment uses MR coverage to describe signal strength, but other indicators can also be used to characterize signal strength in practical applications, and no restrictions are imposed here. By setting the parameter type to signal strength, the priority of base station cell resource reallocation can be accurately assessed from the perspective of signal strength, which is beneficial to improving the rationality of resource allocation during cell coordination.

[0122] Furthermore, in one example, the parameter type also includes the average number of connected users; the parameter acquisition module 21 is also specifically used for:

[0123] Count the number of users accessing the network in each community during multiple preset time periods;

[0124] For each cell, the average number of access users within the multiple time periods is calculated to obtain the parameter value of the average number of access users for that cell;

[0125] The weight acquisition module 22 is also specifically used for:

[0126] The ratio of the average number of access users in each cell to a preset third value is calculated to obtain the weight of each cell under the average number of access users.

[0127] Specifically, the parameter acquisition module 21 acquires the number of access users of the base station cell in different time periods and takes the average value as the parameter value U of the average number of access users. The number of access users can be obtained from the base station network management software, or other acquisition methods can be selected according to the actual application; there are no restrictions on this. The weight acquisition module 22 calculates the ratio of the parameter value U of the average number of access users to a preset second value, denoted as the weight K3 of the base station cell under the average number of access users. The magnitude of the second value affects the weight of the base station cell under each parameter type and its proportion in the total weight. It can be set according to the importance of each parameter type and the magnitude of the parameter value in the actual application. The larger K3 is, the more access users there are, and it is not advisable to reallocate resources from this cell. By setting the parameter type to the average number of access users, the priority of resource reallocation of the base station cell is accurately assessed from the dimension of the importance of the scenario type, which is beneficial to improving the rationality of resource allocation during cell coordination.

[0128] Furthermore, in one example, the parameter type also includes a scene type; the parameter acquisition module 21 is also specifically used for:

[0129] The scene of each cell's coverage area is used as the parameter value for the scene type of each cell;

[0130] The weight acquisition module 22 is also specifically used for:

[0131] Based on the weights corresponding to different scenarios, the weights corresponding to the parameter values ​​of the scenario type of each cell are used as the weights of each cell under the scenario type.

[0132] Specifically, based on the coverage area of ​​each base station cell, the scenario type of the coverage area is determined and used as the parameter value for the base station cell scenario type. This parameter value is not necessarily a numerical value but can be actual data, such as specific scenarios like schools, hospitals, or public places. Based on the importance of the scenario type, a weight K4 is assigned to the base station cell under that scenario type; this is the weight of the base station cell under that scenario type. By setting the parameter type to scenario type, the priority of base station cell resource reallocation can be accurately assessed from the perspective of scenario type importance.

[0133] Furthermore, in one example, the parameter type also includes network performance; the parameter acquisition module 21 is also specifically used for:

[0134] Calculate the call access success rate and call hold success rate for each cell during the first time period;

[0135] For each cell, the network performance of the cell is obtained by multiplying the call access success rate and the call hold success rate of that cell.

[0136] The weight acquisition module 22 is also specifically used for:

[0137] Calculate the ratio of the network performance of each cell to a preset fourth value to obtain the weight of each cell under network performance.

[0138] Specifically, the cell coordination device statistically analyzes the performance indicators of the base station cell during this period. Depending on the different aspects applicable to measuring network performance, performance indicators can be categorized into many types. Here, we use call access success rate and call hold success rate. In practical applications, other network performance indicators can also be selected; there are no restrictions here. Call access success rate and call hold success rate indicate the success rate of a user accessing and staying on the network. The higher these two indicator values, the better the network performance, with a maximum value of 1. The ratio of the product of these two indicators to a set third value is recorded as the weight K5, which is the weight of the base station cell under network performance. The magnitude of this third value affects the weight of the base station cell under each parameter type and its proportion in the total weight. It can be set according to the importance and value of each parameter type in practical applications. The third value...

[0139] In cases where multiple cells have the lowest total weight, to achieve cell coordination, in one example, the coordination module 23 is specifically used for:

[0140] If there is only one cell with the lowest total weight, then that cell will be designated as the cell to be relocated.

[0141] If there are multiple cells with the lowest total weight, then the weights of these cells under the current parameter type are compared sequentially according to the priority of the parameter type until there is only one cell with the lowest weight under the current parameter type. Then, that cell is designated as the cell to be relocated.

[0142] Specifically, the coordination module 23 compares the total weight of each base station cell and selects the base station cell with the lowest total weight to perform cell coordination and resource reallocation. If the number of cells with the lowest total weight is greater than one, the weight of the base station cell under a certain parameter type is compared, and the base station cell with the lowest weight under that parameter type is selected to perform cell coordination. If the number of base station cells with the lowest weight under that parameter type is greater than one, the weight of each base station cell under the next parameter type is compared. The order of comparison is determined according to the priority of the parameter type, and the priority of the parameter type is set according to the importance of each parameter type in actual application.

[0143] It should be noted that the above examples can be implemented individually or in combination. The parameter types, besides unit traffic value, can also include, but are not limited to, any one or more parameter types mentioned in the examples. In the cell coordination device provided in this embodiment, the cell coordination method, device, electronic device, and medium provided in this application acquire the parameter values ​​of each cell under preset parameter types, including unit traffic value; calculate the weight of each cell under all parameter types based on the parameter values; and sum the weights of each cell under all parameter types to obtain the total weight of each cell; the cell with the lowest total weight is designated as the cell to be relocated, and cell coordination is performed. This scheme considers the dimension of unit traffic value to evaluate base station cells, more accurately and reasonably determining the cells to be relocated in cell coordination, thereby achieving effective and accurate cell coordination and improving the rationality of resource allocation.

[0144] Example 3

[0145] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application, such as... Figure 3 As shown, the electronic device includes:

[0146] The electronic device includes a processor 291 and a memory 292; it may also include a communication interface 293 and a bus 294. The processor 291, memory 292, and communication interface 293 can communicate with each other via the bus 294. The communication interface 293 can be used for information transmission. The processor 291 can invoke logical instructions stored in the memory 292 to execute the methods of the above embodiments.

[0147] Furthermore, the logic instructions in the aforementioned memory 292 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium.

[0148] The memory 292, as a computer-readable storage medium, can be used to store software programs and computer-executable programs, such as program instructions / modules corresponding to the methods in the embodiments of this disclosure. The processor 291 executes functional applications and data processing by running the software programs, instructions, and modules stored in the memory 292, thereby implementing the methods in the above-described method embodiments.

[0149] The memory 292 may include a program storage area and a data storage area. The program storage area may store the operating system and application programs required for at least one function; the data storage area may store data created based on the use of the terminal device. Furthermore, the memory 292 may include high-speed random access memory and may also include non-volatile memory.

[0150] This disclosure provides a non-transitory computer-readable storage medium storing computer-executable instructions that, when executed by a processor, are used to implement the methods described in the foregoing embodiments.

[0151] Example 4

[0152] This disclosure provides a computer program product, including a computer program that, when executed by a processor, implements the methods provided in any of the embodiments described above.

[0153] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0154] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method for coordinating communities, characterized in that, include: Obtain the parameter values ​​of each cell under preset parameter types, including unit traffic value, signal strength, average number of access users, scenario type, and network performance; The weight of each cell under the preset parameter type is calculated based on the parameter values ​​of each cell under the preset parameter type. In addition, the weights of each cell under the preset parameter type are summed to obtain the total weight of each cell; The community with the lowest total weight value will be designated as the community to be relocated, and community coordination will be carried out. The preset parameter type is unit traffic value, and obtaining the parameter values ​​of each cell under the preset parameter type includes: Obtain the traffic value parameters of each cell in the first time period. The traffic value parameters include the total traffic generated by the cell in the first time period, the traffic generated by each access user accessing the cell, and the package price of each access user. For each cell, the ratio of traffic generated by each access user to the total traffic is calculated, and the ratio is multiplied by the package price of the access user to obtain the unit traffic value of each access user; the unit traffic value of all access users accessing the cell during the first time period is summed to obtain the parameter value of the unit traffic value of the cell. The step of calculating the weight of each cell under the preset parameter type based on the parameter values ​​of each cell under the preset parameter type includes: The ratio of the parameter value of unit traffic value of each cell to a preset first value is calculated to obtain the weight of each cell under unit traffic value.

2. The method according to claim 1, characterized in that, The preset parameter type is signal strength, and obtaining the parameter values ​​of each cell under the preset parameter type includes: Sampling points are selected in each cell for sampling to obtain the MR coverage of each cell, which is used as the parameter value of the signal strength of each cell; The step of calculating the weight of each cell under the preset parameter type based on the parameter values ​​of each cell under the preset parameter type includes: Based on the weights corresponding to different MR coverage rates, the weights corresponding to the parameter values ​​of the signal strength of each cell are used as the weights of each cell under the signal strength.

3. The method according to claim 1, characterized in that, The preset parameter type is the average number of access users, and obtaining the parameter values ​​of each cell under the preset parameter type includes: Count the number of users accessing the network in each community during multiple preset time periods; For each cell, the average number of access users within the multiple time periods is calculated to obtain the parameter value of the average number of access users for that cell; The step of calculating the weight of each cell under the preset parameter type based on the parameter values ​​of each cell under the preset parameter type includes: The ratio of the average number of access users in each cell to a preset third value is calculated to obtain the weight of each cell under the average number of access users.

4. The method according to claim 1, characterized in that, The preset parameter type is a scenario type, and obtaining the parameter values ​​of each cell under the preset parameter type includes: The scene of each cell's coverage area is used as the parameter value for the scene type of each cell; The step of calculating the weight of each cell under the preset parameter type based on the parameter values ​​of each cell under the preset parameter type includes: Based on the weights corresponding to different scenarios, the weights corresponding to the parameter values ​​of the scenario type of each cell are used as the weights of each cell under the scenario type.

5. The method according to claim 1, characterized in that, The preset parameter type is network performance, and obtaining the parameter values ​​of each cell under the preset parameter type includes: Calculate the call access success rate and call hold success rate for each cell during the first time period; For each cell, the product of the call access success rate and the call hold success rate of that cell is calculated to obtain the parameter value of the network performance of that cell; The step of calculating the weight of each cell under the preset parameter type based on the parameter values ​​of each cell under the preset parameter type includes: The ratio of the network performance parameter value of each cell to the preset fourth value is calculated to obtain the weight of each cell under network performance.

6. The method according to any one of claims 1-5, characterized in that, The step of designating the cell with the lowest total weight as the cell to be relocated includes: If there is only one cell with the lowest total weight, then that cell will be designated as the cell to be relocated. If there are multiple cells with the lowest total weight, then the weights of these multiple cells under the current preset parameter type are compared sequentially according to the priority of the preset parameter type until there is only one cell with the lowest weight under the current preset parameter type. Then, that cell is designated as the cell to be relocated.

7. A community coordination device, characterized in that, include: The parameter acquisition module is used to acquire the parameter values ​​of each cell under preset parameter types, including unit traffic value, signal strength, average number of access users, scenario type and network performance. The weight acquisition module is used to calculate the weight of each cell under the preset parameter type based on the parameter values ​​of each cell under the preset parameter type. In addition, the weights of each cell under the preset parameter type are summed to obtain the total weight of each cell; The coordination module is used to identify the cell with the lowest total weight as the cell to be relocated and to perform cell coordination. The preset parameter type is unit traffic value, and the parameter acquisition module is specifically used for: Obtain the traffic value parameters of each cell in the first time period. The traffic value parameters include the total traffic generated by the cell in the first time period, the traffic generated by each access user accessing the cell, and the package price of each access user. For each cell, the ratio of the traffic generated by each access user to the total traffic is calculated, and the ratio is multiplied by the package price of the access user to obtain the unit traffic value of each access user; The unit traffic value of the cell is obtained by summing the unit traffic value of all users accessing the cell during the first time period. The weight acquisition module is specifically used for: The ratio of the parameter value of unit traffic value of each cell to a preset first value is calculated to obtain the weight of each cell under unit traffic value.

8. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-6.

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