CN112996011B - Cell value evaluation method, device, computer equipment and readable storage medium - Google Patents
Cell value evaluation method, device, computer equipment and readable storage medium Download PDFInfo
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- CN112996011B CN112996011B CN201911272014.8A CN201911272014A CN112996011B CN 112996011 B CN112996011 B CN 112996011B CN 201911272014 A CN201911272014 A CN 201911272014A CN 112996011 B CN112996011 B CN 112996011B
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Abstract
The invention discloses a cell value evaluation method, a cell value evaluation device, computer equipment and a readable storage medium. The cell value evaluation method comprises the following steps: calculating to obtain the service weight of the cell based on the service data; calculating to obtain a region association strength value between the cell and the adjacent cell of the cell based on the switching information between the regions; calculating to obtain the influence capacity value of the adjacent cell based on the resource information transferred from the adjacent cell to the cell; obtaining a cell value weight according to the service weight, the area correlation strength value and the adjacent cell influence capacity value; and obtaining the cell value presentation information according to the cell value weight. By adopting the cell value evaluation method, the cell value can be accurately evaluated in a communication network.
Description
[ technical field ] A method for producing a semiconductor device
The present invention relates to the field of wireless communication technologies, and in particular, to a method and an apparatus for evaluating a cell value, a computer device, and a readable storage medium.
[ background of the invention ]
With the large-scale deep deployment of an LTE (Long Term Evolution) wireless network and the reference demand of 5G network development, the detailed operation of the LTE network and the important guarantee of high-value cells in the LTE network become one of the important works of network and market operation. At present, the evaluation of the cell value in the communication network in the market is too rough, and the cell value cannot be accurately evaluated in the communication network.
[ summary of the invention ]
In view of this, embodiments of the present invention provide a method, an apparatus, a computer device and a readable storage medium for evaluating a cell value, so as to solve the problem that the cell value cannot be evaluated more accurately in a communication network at present.
In a first aspect, an embodiment of the present invention provides a method for evaluating a cell value, including:
calculating to obtain the service weight of the cell based on the service data;
calculating to obtain a region association strength value between the cell and a neighboring cell of the cell based on switching information between the regions;
calculating to obtain the influence capacity value of the adjacent cell based on the resource information transferred from the adjacent cell to the cell;
obtaining a cell value weight according to the service weight, the region association strength value and the neighbor cell influence capacity value;
and obtaining the community value presentation information according to the community value weight.
The foregoing aspects and any possible implementation manners further provide an implementation manner, where the service data includes a number of data service users and a number of voice service users, and the calculating to obtain the service weight of the cell based on the service data includes:
acquiring the number of the data service users and the number of the voice service users in a first preset time period;
calculating the service weight of the cell according to the number of the data service users and the number of the voice service users, wherein the formula of the calculation is as follows:
wherein f is i Indicating the traffic carried by cell i,
represents the total traffic flow carried in the communication network, t represents the time length corresponding to the first preset time period,
indicating cell i is in the first presetThe number of data traffic users carried in a time period,
and indicating the number of the voice service users carried by the cell i in the first preset time period.
As to the above-mentioned aspect and any possible implementation manner, there is further provided an implementation manner, where the neighboring cells of the cell include a primary neighboring cell and a secondary neighboring cell, and the calculating, based on the handover information between the regions, to obtain the region association strength value between the cell and the neighboring cells of the cell includes:
acquiring switching information from the cell to the first-level neighboring cell and from the first-level neighboring cell to the second-level neighboring cell within a second preset time period, and acquiring a switching success rate according to the switching information;
according to the switching success rate and the pre-acquired geographic distance between the regions, calculating to obtain a region association strength value between the cell and the adjacent region of the cell, wherein the formula of the calculation is represented as: l is a radical of an alcohol i ＝∑ jeneighbour(i) ∑ keneighbour(j) P jk *δ jk +∑ jeneighbour(i) P ij *δ ij Wherein j represents a first-level neighboring cell of the cell i, keneigbour (j) represents a second-level neighboring cell of the cell i, k represents a first-level neighboring cell of the cell j, and P represents a second-level neighboring cell of the cell i jk Indicating the handover success rate of cell j to neighbor k,
d jk represents the geographical distance, δ, between cells j and k jk Representing a first distance weight, P ij Indicating the handover success rate from cell i to neighbor j,
d ij representing the geographical position between cells i and j, δ ij Representing a second distance weight.
As to the above-mentioned aspect and any possible implementation manner, there is further provided an implementation manner, where the resource information transferred from the neighboring cell to the cell includes the number of users and traffic generated by the users, and the calculating, based on the resource information transferred from the neighboring cell to the cell, obtains the neighboring cell influence capability value, including:
acquiring the number of users transferring the neighbor cell to the cell within a third preset time period;
acquiring the flow generated by the user transferring the neighboring cell to the cell within a third preset time period;
calculating to obtain the neighbor cell influence capacity value based on the number of the users transferred from the neighbor cell to the cell and the flow generated by the users transferred from the neighbor cell to the cell, wherein the calculation formula is represented as: g i ＝∑ jeneighbour(i) H ji *E ji *W j Wherein H is ji Representing the proportion of the total number of users of the adjacent cell j to the cell i, E ji Represents the proportion of the flow generated by the user transferred from the adjacent cell j to the cell i to the total flow of the adjacent cell j, W j Representing the traffic weight of the cell of the neighbor j.
As to the above-mentioned aspect and any possible implementation manner, there is further provided an implementation manner, where obtaining a cell value weight according to the service weight, the area association strength value, and the neighboring cell influence capability value includes:
multiplying the service weight, the area association strength value and the neighboring cell influence capacity value to obtain the cell value weight, and expressing the cell value weight as R by adopting a formula i ＝W i *L i *G i 。
The above aspect and any possible implementation manner further provide an implementation manner, where the cell value presentation information includes a cell value sequence, and the obtaining of the cell value presentation information according to the cell value weight includes:
and sequencing the cells in the communication network according to the cell value weight from high to low to obtain the cell value sequence.
The above-mentioned aspect and any possible implementation manner further provide an implementation manner, after obtaining the cell value presentation information according to the cell value weight, further including:
determining a target cell value weight, wherein the target cell value weight is a cell value weight which is greater than a preset threshold value in the cell value presentation information;
and taking the cell corresponding to the target cell value weight as a first step guarantee object in the communication network.
In a second aspect, an embodiment of the present invention provides a cell value evaluation apparatus, including:
the cell service weight acquisition module is used for calculating and obtaining the service weight of the cell based on the service data;
a region association strength value obtaining module, configured to calculate a region association strength value between the cell and a neighboring cell of the cell based on handover information between regions;
the neighbor cell influence capacity value acquisition module is used for calculating to obtain a neighbor cell influence capacity value based on the resource information transferred from the neighbor cell to the cell;
the cell value weight acquisition module is used for obtaining a cell value weight according to the service weight, the region association strength value and the neighboring cell influence capacity value;
and the cell value presentation information acquisition module is used for acquiring cell value presentation information according to the cell value weight.
In a third aspect, a computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above cell value evaluation method when executing the computer program.
In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, including: computer program which, when being executed by a processor, carries out the steps of the above-mentioned cell value evaluation method.
In the embodiment of the invention, firstly, the service weight of the cell is obtained based on the service data calculation, the proportion of the service flow of a single cell in the whole communication network can be reflected, and the importance of the cell is highlighted through the data service and voice service user number of the cell, and when the two are larger, the cell is more important; then, based on the switching information between the areas, calculating to obtain an area association strength value between the cell and the adjacent area of the cell, and effectively embodying the association strength between the cell and the adjacent area; then, based on the resource information transferred from the neighboring cell to the cell, the influence capability value of the neighboring cell is obtained through calculation, and the influence capability of the cell on the neighboring cell, such as the number of users and the user flow, can be reflected; and finally, obtaining a cell value weight according to the service weight, the area association strength value and the adjacent cell influence capacity value, obtaining cell value presentation information according to the cell value weight, comprehensively considering the association strength among cells, the influence capacity of the cells on the surrounding adjacent cells and the importance embodied by the self-bearing service of the cells, and further depicting the area influence capacity of the cells in the network topology. The embodiment of the invention can accurately evaluate the cell value in the communication network from the aspect of communication network topology.
[ description of the drawings ]
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive labor.
FIG. 1 is a flowchart of a method for cell worth evaluation according to an embodiment of the present invention;
FIG. 2 is a diagram of a cell worth evaluation device according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a computer device according to an embodiment of the present invention.
[ detailed description ] A
For better understanding of the technical solutions of the present invention, the following detailed descriptions of the embodiments of the present invention are provided with reference to the accompanying drawings.
It should be understood that the described embodiments are only some embodiments of the invention, and not all embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
The terminology used in the embodiments of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the examples of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be understood that the term "and/or" as used herein is merely a field that describes the same of an associated object, meaning that three relationships may exist, e.g., A and/or B, may indicate: a is present alone, and A and B are present, B is present alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.
It should be understood that although the terms first, second, third, etc. may be used to describe preset ranges, etc. in embodiments of the present invention, these preset ranges should not be limited to these terms. These terms are only used to distinguish preset ranges from each other. For example, the first preset range may also be referred to as a second preset range, and similarly, the second preset range may also be referred to as the first preset range, without departing from the scope of the embodiments of the present invention.
The word "if," as used herein, may be interpreted as "at … …" or "at … …" or "in response to a determination" or "in response to a detection," depending on context. Similarly, the phrase "if determined" or "if detected (a stated condition or event)" may be interpreted as "upon determining" or "in response to determining" or "upon detecting (a stated condition or event)" or "in response to detecting (a stated condition or event)", depending on the context.
Fig. 1 shows a flowchart of the cell value evaluation method in the present embodiment. The cell value evaluation method can be applied to a cell value evaluation system, and can be realized by adopting the cell value evaluation system when the cell value evaluation is carried out. The cell value evaluation system can be specifically applied to computer equipment, wherein the computer equipment can perform human-computer interaction with a user, and the computer equipment comprises but is not limited to computers, smart phones, tablets and other equipment. As shown in fig. 1, the method for evaluating the cell value includes the following steps:
s10: and calculating the service weight of the cell based on the service data.
It will be appreciated that there are a number of different cells divided in the communication network, each cell having its own importance in the communication network that is different.
In an embodiment, the service weight of the cell may be calculated through service data of the cell itself, including data of the number of users, traffic, and the like carried by the cell, and the importance of the cell service in the entire communication network is embodied through the service weight of the cell.
Further, in step S10, the service data includes a number of data service users and a number of voice service users, and the calculating based on the service data obtains the service weight of the cell, which specifically includes:
s11: and acquiring the number of data service users and the number of voice service users in a first preset time period.
In an embodiment, the importance of a cell in a communication network is measured by adopting the number of data service users and the number of voice service users which can better highlight the service volume of the cell. Specifically, the number of data service users and the number of voice service users in a first preset time period are taken as calculation data, the first preset time period can be a period of time intercepted in an off-peak period, generality is achieved, and calculation accuracy can be improved.
S12: calculating to obtain the service weight of the cell according to the number of the data service users and the number of the voice service users, wherein the formula of the calculation is as follows:
wherein f is i Indicating the traffic carried by cell i,
represents the total traffic flow carried in the communication network, t represents the duration corresponding to the first preset time period,
indicating the number of data service users carried by the cell i in the first preset time period,
and indicating the number of the voice service users carried by the cell i in the first preset time period.
In an embodiment, the importance of the cell in the whole communication network is comprehensively embodied by the ratio of the traffic flow carried by the cell i to the total traffic flow carried in the communication network and the traffic distribution condition combining the number of data traffic users and the number of voice traffic users.
S20: and calculating to obtain the area association strength value between the cell and the adjacent cell of the cell based on the switching information between the areas.
It can be understood that, in the embodiment, the close connection degree between the cell and the neighboring cell is reflected by the handover between the cell and the neighboring cell, and the strength of the area association between the cell and the neighboring cell is reflected by the handover between the cell and the neighboring cell. The area association strength is also one of the important reference conditions for measuring the importance of a cell in a communication network.
Further, in step S20, the neighboring cells of the cell include a primary neighboring cell and a secondary neighboring cell, and the region association strength value between the cell and the neighboring cells of the cell is calculated based on the handover information between the regions, which specifically includes:
s21: and acquiring switching information from the cell to the first-level adjacent cell and from the first-level adjacent cell to the second-level adjacent cell in a second preset time period, and acquiring the switching success rate according to the switching information.
It can be understood that, in this embodiment, a first-level neighboring cell and a second-level neighboring cell are specifically taken as neighboring cells of a cell, where a function of enabling direct handover between the first-level neighboring cell (j) and the cell (i) can be implemented, a function of enabling direct handover between the second-level neighboring cell (k) and the first-level neighboring cell (j) can be implemented, and the second-level neighboring cell can still greatly affect the area association strength between neighboring cells of the cell, and therefore, in this embodiment, the second-level neighboring cell is also treated as an important object.
S22: according to the switching success rate and the pre-acquired geographic distance between the regions, calculating to obtain a region association strength value between the cell and the adjacent regions of the cell, wherein the formula of the calculation is represented as: l is i ＝∑ jeneighbour(i) ∑ keneighbour(j) P jk *δ jk +∑ jeneighbour(i) P jk *δ jk Wherein jeneighbour (i) represents j as the first-level neighboring cell of the cell i, keneighbour (j) represents k as the first-level neighboring cell of the cell j and the second-level neighboring cell of the cell i, and P jk Indicating the handover success rate of cell j to neighbor k,
d jk represents the geographical distance, δ, between cells j and k jk Representing a first distance weight, P ij Indicating the handover success rate from cell i to neighbor j,
d ij representing the geographical position, δ, between cells i and j jk Representing a second distance weight.
It can be understood that, in this embodiment, the handover success rate and the geographic distance between the regions are used as important parameters for calculating the region association strength value, and the handover success rate and the geographic distance between the regions can respectively show the close relationship between the regions in the relation frequency and the spatial position, and can better express the region association strength between the neighboring regions of the cell.
S30: and calculating to obtain the influence capacity value of the adjacent cell based on the resource information transferred from the adjacent cell to the cell.
It can be understood that, besides the area association between the cell and its neighboring cells, the cell has a certain influence capability (or attraction capability) on its neighboring cells, and the influence capability can also reflect the importance (value) of the cell in the communication network.
Further, in step S30, the resource information transferred from the neighboring cell to the cell includes the number of users and traffic generated by the users, and the neighboring cell influence capability value is calculated based on the resource information transferred from the neighboring cell to the cell, which specifically includes:
s31: and acquiring the number of users transferring the adjacent cell to the cell in a third preset time period.
The third preset time period and the first preset time period and the second preset time period mentioned above may be the same, and the same preset time period is adopted to eliminate errors caused by time in the calculation process and improve the accuracy of the calculation result.
S32: and acquiring the flow generated by the user transferring the adjacent cell to the cell in the third preset time period.
In an embodiment, steps S31 to S32 specifically use the number of users and the traffic generated by the users as main resource information for calculation, so as to embody the attraction capability of the cell (i) to its neighboring cells.
S33: and calculating to obtain a neighbor cell influence capacity value based on the number of the users transferred from the neighbor cell to the cell and the flow generated by the users transferred from the neighbor cell to the cell, wherein the calculation formula is represented as: g i ＝∑ jeneighbour(i) H ji *E ji *W j Wherein H is ji Representing the proportion of the total number of users of the adjacent cell j to the cell i, E ji Represents the proportion of the flow generated by the user transferred from the adjacent cell j to the cell i to the total flow of the adjacent cell j, W j Representing the traffic weight of the cell of the neighbor j.
Understandably, H ji Can be determined according to the number u of users residing in the adjacent region j j And the number u of users transferred from the adjacent cell j to the cell i ji Is obtained by a specific formula as
Similarly, E ji Can be based on the total flow S generated by the users in the adjacent region j j And the total flow S generated by the user on the adjacent region j transferred to the cell i in the adjacent region j ji Is obtained by a specific formula as
S40: and obtaining the cell value weight according to the service weight, the area association strength value and the adjacent cell influence capacity value.
Further, in step S40, the cell value presentation information includes a cell value sequence, and the cell value weight is obtained according to the service weight, the area association strength value, and the neighboring cell influence capability value, which specifically includes:
multiplying the service weight, the area correlation strength value and the adjacent area influence capacity value to obtain a cell value weight, and expressing the cell value weight as R by adopting a formula i ＝W i *L i *G i 。
Understandably, R i Is the value weight of the cell i to measure the area influence of the cell i when the service weight W of the cell i is i The larger the cell i is, the more important the cell i is in the communication network, the more valuable the cell i is; when the correlation strength between the cell i and the adjacent cell is higher, the greater the importance of the cell i in the communication network is, the higher the value is; when the influence capability of the cell i on the neighboring cell is larger, the greater the importance of the cell i in the communication network is, the more the cell i is a high-value cell. W i 、L i And G i Respectively at R i In a proportional relationship. Through the R i The importance of different cells in the communication network can be determined more accurately.
S50: and obtaining the cell value presentation information according to the cell value weight.
The cell value presentation information may specifically be a cell value weight represented by a sequence, a table, an illustration, and the like. The user can quickly acquire effective information on the cell value through the cell value presentation information.
Further, in step S50, obtaining the cell value presentation information according to the cell value weight specifically includes:
and sequencing the cells in the communication network according to the cell value weight from high to low to obtain a cell value sequence.
Further, the cell value sequence may also be obtained by a low-to-high ordering mode, which is not limited herein. In the implementation, the cell value weights are arranged together and presented according to certain logic, so that a user can quickly extract effective information about the cell value from the cell value weights.
Further, after step S50, that is, after the step of obtaining the cell value presentation information according to the cell value weight, the method further includes:
s51: and determining a target cell value weight, wherein the target cell value weight is the cell value weight which is larger than a preset threshold value in the cell value presentation information.
S52: and taking the cell corresponding to the value weight of the target cell as a first step guarantee object in the communication network.
The first step guarantee object may be understood as an object for which maintenance guarantee is preferentially performed in network maintenance scheduling.
In an embodiment, the steps S51 to S52 specifically employ a cell value weight greater than a preset threshold in the cell value presentation information as a target cell value weight, and a cell corresponding to the target cell value weight as a first step guarantee object in the communication network, so as to perform reasonable network maintenance arrangement according to the level of the cell value.
Further, a cell corresponding to the cell value weight with the numerical value of the first 5% (top 5%) can be used as the first step guarantee object.
In the embodiment of the invention, firstly, the service weight of the cell is obtained based on the service data calculation, the proportion of the service flow of a single cell in the whole communication network can be reflected, and the importance of the cell is highlighted through the data service and voice service user number of the cell, and when the two are larger, the cell is more important; then, based on the switching information between the areas, calculating to obtain an area association strength value between the cell and the adjacent area of the cell, and effectively embodying the association strength between the cell and the adjacent area; then, based on the resource information transferred from the adjacent cell to the cell, calculating to obtain an influence capacity value of the adjacent cell, and reflecting the influence capacity of the cell on the adjacent cell on the user number and the user flow; and finally, obtaining a cell value weight according to the service weight, the area association strength value and the adjacent cell influence capacity value, obtaining cell value presentation information according to the cell value weight, comprehensively considering the association strength among cells, the influence capacity of the cells on the surrounding adjacent cells and the importance embodied by the self-bearing service of the cells, and further depicting the area influence capacity of the cells in the network topology. The embodiment of the invention can more accurately evaluate the value of the cell in the communication network from the aspect of the communication network topology.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
Based on the cell value evaluation method provided in the embodiment, the embodiment of the invention further provides an embodiment of a device for realizing the steps and the method in the embodiment of the method.
Fig. 2 is a schematic block diagram of a cell value evaluation device corresponding to the cell value evaluation method in one-to-one embodiment. As shown in fig. 2, the cell value evaluation apparatus includes a cell service weight obtaining module 10, a region association strength value obtaining module 20, a neighboring cell influence capability value obtaining module 30, a cell value weight obtaining module 40, and a cell value presentation information obtaining module 50. The implementation functions of the cell service weight obtaining module 10, the area association strength value obtaining module 20, the neighboring cell influence capability value obtaining module 30, the cell value weight obtaining module 40, and the cell value presentation information obtaining module 50 correspond to the steps corresponding to the cell value evaluation method in the embodiment one by one, and for avoiding repeated description, detailed description is not needed in this embodiment.
And a cell service weight obtaining module 10, configured to obtain a cell service weight based on service data.
A module 20 for obtaining a region association strength value, configured to calculate a region association strength value between a cell and a neighboring cell of the cell based on handover information between regions.
And the neighboring cell influence ability value obtaining module 30 is configured to calculate a neighboring cell influence ability value based on the resource information transferred from the neighboring cell to the cell.
And the cell value weight obtaining module 40 is configured to obtain a cell value weight according to the service weight, the area association strength value, and the neighboring cell influence capability value.
A cell value presentation information obtaining module 50, configured to obtain cell value presentation information according to the cell value weight.
Optionally, the service data includes a number of data service users and a number of voice service users, and the cell service weight obtaining module 10 is further specifically configured to:
acquiring the number of data service users and the number of voice service users in a first preset time period;
calculating to obtain the service weight of the cell according to the number of the data service users and the number of the voice service users, wherein the formula of the calculation is as follows:
wherein f is i Indicating the traffic carried by cell i,
represents the total traffic flow carried in the communication network, t represents the duration corresponding to the first preset time period,
indicating the number of data service users carried by the cell i in the first preset time period,
and indicating the number of the voice service users loaded in the cell i in the first preset time period.
Optionally, the neighboring cells of the cell include a first-level neighboring cell and a second-level neighboring cell, and the region association strength value obtaining module 20 is further specifically configured to:
acquiring switching information from the cell to the first-level adjacent cell and from the first-level adjacent cell to the second-level adjacent cell in a second preset time period, and acquiring a switching success rate according to the switching information;
according to the switching success rate and the pre-acquired geographic distance between the regions, calculating to obtain a region correlation strength value between the cell and the adjacent region of the cell, wherein the formula of the calculation is represented as follows: l is i ＝∑ jeneighbour(i) ∑ keneighbour(j) P jk *δ jk +∑ jeneighbour(i) P ij *δ ij Wherein jeneighbour (i) represents j as the first-level neighboring cell of the cell i, keneighbour (j) represents k as the first-level neighboring cell of the cell j and the second-level neighboring cell of the cell i, and P jk Indicating the handover success rate of cell j to neighbor k,
d jk denotes the geographical distance, δ, between cells j and k jk Representing a first distance weight, P ij Indicating the handover success rate from cell i to neighbor j,
d ij representing the geographical position, δ, between cells i and j ij Representing a second distance weight.
Optionally, the resource information transferred from the neighboring cell to the cell includes the number of users and traffic generated by the users, and the neighboring cell influence capability value obtaining module 30 is further specifically configured to:
acquiring the number of users transferring the neighbor cells to the cell within a third preset time period;
acquiring the flow generated by the user transferring the adjacent cell to the cell within a third preset time period;
and calculating to obtain a neighbor cell influence capacity value based on the number of the users transferred from the neighbor cell to the cell and the flow generated by the users transferred from the neighbor cell to the cell, wherein the calculation formula is represented as: g i ＝∑ jeneighbour(i) H ji *E ji *W j Wherein H is ji Representing the proportion of the total number of users of the adjacent cell j to the cell i, E ji Represents the proportion of the flow generated by the user transferred from the adjacent cell j to the cell i to the total flow of the adjacent cell j, W j Representing the traffic weight of the cell of the neighbor j.
Optionally, the cell value weight obtaining module 40 is further specifically configured to:
multiplying the service weight, the area association strength value and the adjacent area influence capacity value to obtain a cell value weight, and expressing the cell value weight as R by adopting a formula i ＝W i *L i *G i 。
Optionally, the cell value presentation information includes a cell value sequence, and the cell value presentation information obtaining module 50 is further specifically configured to:
and sequencing the cells in the communication network according to the cell value weight from high to low to obtain a cell value sequence.
Optionally, the cell value evaluation apparatus is further specifically configured to:
determining a target cell value weight, wherein the target cell value weight is a cell value weight which is larger than a preset threshold value in the cell value presentation information;
and taking the cell corresponding to the value weight of the target cell as a first step guarantee object in the communication network.
In the embodiment of the invention, firstly, the service weight of the cell is obtained based on the service data calculation, so that the proportion of the service flow of a single cell in the whole communication network can be reflected, and the importance of the cell is highlighted by the number of the data service users and the voice service users of the cell, and when the number of the data service users and the number of the voice service users of the cell is larger, the cell is more important; then, based on the switching information between the areas, calculating to obtain an area association strength value between the cell and the adjacent area of the cell, and effectively embodying the association strength between the cell and the adjacent area; then, based on the resource information transferred from the adjacent cell to the cell, calculating to obtain an influence capacity value of the adjacent cell, and reflecting the influence capacity of the cell on the adjacent cell on the user number and the user flow; and finally, obtaining a cell value weight according to the service weight, the area correlation strength value and the influence capacity value of the adjacent cell, obtaining cell value presentation information according to the cell value weight, comprehensively considering the correlation strength among the cells, the influence capacity of the cells on the adjacent cells and the importance embodied by the self-bearing service of the cells, and further depicting the area influence capacity of the cells in network topology. The embodiment of the invention can more accurately evaluate the value of the cell in the communication network from the aspect of the communication network topology.
The present embodiment provides a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the method for evaluating a cell value in an embodiment is implemented, which is not repeated herein. Alternatively, the computer program is executed by the processor to implement the functions of each module/unit in the cell value evaluation apparatus in the embodiments, which are not repeated herein to avoid repetition.
Fig. 3 is a schematic diagram of a computer device according to an embodiment of the present invention. As shown in fig. 3, the computer device 60 of this embodiment includes: the processor 61, the memory 62, and the computer program 63 stored in the memory 62 and capable of running on the processor 61, where the computer program 63 is executed by the processor 61 to implement the cell value evaluation method in the embodiment, and in order to avoid repetition, details are not repeated herein. Alternatively, the computer program 63 is executed by the processor 61 to implement the functions of each model/unit in the cell value evaluation apparatus in the embodiments, which are not described herein for avoiding redundancy.
The computing device 60 may be a desktop computer, a notebook, a palm top computer, a cloud server, or other computing device. The computer device 60 may include, but is not limited to, a processor 61, a memory 62. Those skilled in the art will appreciate that fig. 3 is merely an example of a computer device 60 and is not intended to limit the computer device 60 and that it may include more or fewer components than shown, or some of the components may be combined, or different components, e.g., the computer device may also include input output devices, network access devices, buses, etc.
The Processor 61 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The storage 62 may be an internal storage unit of the computer device 60, such as a hard disk or a memory of the computer device 60. The memory 62 may also be an external storage device of the computer device 60, such as a plug-in hard disk provided on the computer device 60, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like. Further, memory 62 may also include both internal and external storage devices for computer device 60. The memory 62 is used for storing computer programs and other programs and data required by the computer device. The memory 62 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules, so as to perform all or part of the functions described above.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit and scope of the embodiments of the present invention, and they should be construed as being included therein.
Claims (9)
1. A method for cell value assessment, the method comprising:
calculating to obtain a cell service weight based on service data, wherein the cell service weight is used for determining the importance degree of cell services in a communication network;
based on switching information between the regions, calculating to obtain a region association strength value between the cell and a neighboring cell of the cell, wherein the region association strength value is used for determining the close contact degree between the cell and the neighboring cell;
calculating to obtain a neighbor cell influence capacity value based on resource information transferred from a neighbor cell to a cell, wherein the resource information transferred from the neighbor cell to the cell comprises: the number of users and the traffic generated by the users;
obtaining a cell value weight according to the service weight, the area correlation strength value and the neighbor cell influence capacity value;
obtaining the cell value presentation information according to the cell value weight;
the obtaining of the cell value weight according to the service weight, the area correlation strength value and the neighbor cell influence capacity value includes:
multiplying the service weight, the area association strength value and the neighboring cell influence capacity value to obtain the cell value weight, and expressing the cell value weight as R by adopting a formula i ＝W i *L i *G i 。
2. The method of claim 1, wherein the service data includes a number of data service users and a number of voice service users, and the calculating the cell service weight based on the service data includes:
acquiring the number of the data service users and the number of the voice service users in a first preset time period;
calculating to obtain the cell service weight according to the number of the data service users and the number of the voice service users, wherein the formula of the calculation is as follows:
wherein f is i Indicating the traffic carried by cell i,
represents the total traffic flow carried in the communication network, t represents the time length corresponding to the first preset time period,
indicating the number of data service users carried by the cell i in the first preset time period,
and indicating the number of the voice service users carried by the cell i in the first preset time period.
3. The method of claim 1, wherein the neighboring cells of the cell include a primary neighboring cell and a secondary neighboring cell, and the calculating the area association strength value between the cell and the neighboring cell of the cell based on the inter-area handover information includes:
acquiring switching information from the cell to the primary adjacent cell and from the primary adjacent cell to the secondary adjacent cell within a second preset time period, and acquiring a switching success rate according to the switching information;
according to the switching success rate and the pre-acquired geographic distance between the regions, calculating to obtain a region association strength value between the cell and a neighboring region of the cell, wherein the formula of the calculation is represented as: l is i ＝∑ je neighbou (i) ∑ ke neighbour (j) P jk *δ jk +∑ je neighbour (i) P ij *δ ij Wherein j represents the first-level neighboring cell of the cell i, ke represents the second-level neighboring cell of the cell i, and P represents k represents the first-level neighboring cell of the cell j and k represents the second-level neighboring cell of the cell i jk Indicating the handover success rate of cell j to neighbor k,
d jk represents the geographical distance, δ, between cells j and k jk Representing a first distance weight, P ij Indicating the handover success rate from cell i to neighbor j,
d ij indicates between cells i and jGeographic position of δ ij Representing a second distance weight.
4. The method of claim 1, wherein the resource information transferred from the neighboring cell to the cell includes the number of users and traffic generated by the users, and the calculating the neighboring cell influence capability value based on the resource information transferred from the neighboring cell to the cell includes:
acquiring the number of users transferring the neighbor cell to the cell within a third preset time period;
acquiring the flow generated by the user transferring the neighboring cell to the cell within a third preset time period;
calculating to obtain the neighbor cell influence capacity value based on the number of the users transferred from the neighbor cell to the cell and the flow generated by the users transferred from the neighbor cell to the cell, wherein the calculation formula is represented as: g i ＝∑ jeneighbou(i) H ji *E ji *W j Wherein H is ji Representing the proportion of the total number of users of the adjacent cell j to the cell i, E ji Represents the proportion of the flow generated by the user transferred from the adjacent cell j to the cell i to the total flow of the adjacent cell j, W j Representing the cell traffic weight of the neighbor cell j.
5. The method of claim 1, wherein the cell value presentation information comprises a cell value sequence, and wherein obtaining cell value presentation information according to the cell value weights comprises:
and sequencing the cells in the communication network according to the cell value weight from high to low to obtain the cell value sequence.
6. The method according to any of claims 1-5, further comprising, after the obtaining of the cell value presentation information according to the cell value weight:
determining a target cell value weight, wherein the target cell value weight is a cell value weight which is larger than a preset threshold value in the cell value presentation information;
and taking the cell corresponding to the target cell value weight as a first step guarantee object in the communication network.
7. An apparatus for evaluating a cell value, the apparatus comprising:
the system comprises a cell service weight acquisition module, a cell service weight calculation module and a communication network management module, wherein the cell service weight acquisition module is used for calculating and obtaining a cell service weight based on service data, and the cell service weight is used for determining the importance degree of a cell service in the communication network;
a region association strength value obtaining module, configured to calculate a region association strength value between the cell and a neighboring cell of the cell based on handover information between the regions, where the region association strength value is used to determine a close connection degree between the cell and the neighboring cell;
the neighbor cell influence ability value obtaining module is used for calculating to obtain a neighbor cell influence ability value based on resource information transferred from a neighbor cell to a cell, wherein the resource information transferred from the neighbor cell to the cell comprises: the number of users and the traffic generated by the users;
a cell value weight obtaining module, configured to obtain a cell value weight according to the service weight, the region correlation strength value, and the neighboring cell influence capability value;
the cell value presentation information acquisition module is used for acquiring cell value presentation information according to the cell value weight;
the obtaining of the cell value weight according to the service weight, the area association strength value and the neighboring cell influence capacity value includes:
multiplying the service weight, the area correlation strength value and the neighbor cell influence capacity value to obtain the cell value weight, and expressing the cell value weight as R by adopting a formula i ＝W i *L i *G i 。
8. A computer arrangement comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor when executing the computer program carries out the steps of the cell value evaluation method according to any of claims 1 to 6.
9. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the cell-value assessment method according to any one of claims 1 to 6.
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