CN113950082B - Method and equipment for determining network operation and maintenance strategy - Google Patents
Method and equipment for determining network operation and maintenance strategy Download PDFInfo
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- CN113950082B CN113950082B CN202111190975.1A CN202111190975A CN113950082B CN 113950082 B CN113950082 B CN 113950082B CN 202111190975 A CN202111190975 A CN 202111190975A CN 113950082 B CN113950082 B CN 113950082B
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- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Abstract
The application provides a method and equipment for determining a network operation and maintenance strategy, and relates to the technical field of communication. The method may include: acquiring importance parameters corresponding to at least two grids to be evaluated respectively, wherein the grids to be evaluated comprise at least one cell, and the importance parameters are used for describing the importance of the grids to be evaluated from at least one dimension; determining at least one target grid to be operated and maintained from at least two grids to be evaluated according to the importance parameters; determining a network state of a target grid; and determining operation and maintenance strategies of the target grids according to the network states, wherein the target grids in different network states correspond to different operation and maintenance strategies, and the operation and maintenance strategies are used for determining priorities between at least two operation and maintenance modes. According to the method and the device for determining the operation and maintenance of the grid, important target grids can be determined according to importance parameters of the grids to be evaluated, operation and maintenance strategies are determined for the target grids according to network states of the target grids, and different network states correspond to different operation and maintenance strategies. Thus, the accuracy of the operation and maintenance strategy is improved.
Description
Technical Field
The embodiment of the application relates to the technical field of communication, in particular to a method and equipment for determining a network operation and maintenance strategy.
Background
With the continuous development of communication technology, the number of users and service requirements of communication networks are continuously increased. The communication network may be divided into a number of sub-networks by area. E.g. a cell, a grid comprising a plurality of cells under one or more base stations. The network states of the different regions are different, wherein the network states include: network coverage degree, network signal strength. For example, when the network coverage is poor, the network signal strength at a part of the location in the area is poor or even no network signal. Poor network coverage and network signal strength can degrade the communication quality of the user.
In order to improve the communication quality, how to determine an accurate operation and maintenance policy for each area is a problem to be solved.
Disclosure of Invention
The application provides a method and equipment for determining a network operation and maintenance strategy so as to improve the accuracy of the operation and maintenance strategy.
In a first aspect, the present application provides a method for determining a network operation and maintenance policy, including:
acquiring importance parameters corresponding to at least two grids to be evaluated respectively, wherein the grids to be evaluated comprise at least one cell, and the importance parameters are used for describing the importance of the grids to be evaluated from at least one dimension;
Determining at least one target grid to be operated and maintained from the at least two grids to be evaluated according to the importance parameters;
determining a network state of the target grid;
and determining operation and maintenance strategies of the target grids according to the network states, wherein the target grids in different network states correspond to different operation and maintenance strategies, and the operation and maintenance strategies are used for determining priorities between at least two operation and maintenance modes.
Optionally, the importance parameters are at least two kinds, and the determining at least one target grid to be operated from the at least two grids to be evaluated according to the importance parameters includes:
for each importance parameter, dividing the at least two grids to be evaluated according to the importance parameter to obtain at least one first set corresponding to the importance parameter, wherein each first set corresponds to a first score;
for each grid to be evaluated, carrying out weighted summation on the first scores corresponding to at least two first sets of the grid to be evaluated, and obtaining a second score of the grid to be evaluated;
and determining at least one target grid to be operated and maintained from the at least two grids to be evaluated according to the second score.
Optionally, each importance parameter includes sub-parameters corresponding to at least two network types, and dividing the at least two grids to be evaluated according to the importance parameter to obtain at least one first set corresponding to the importance parameter, where the dividing includes:
constructing a coordinate system by taking an average value of the sub-parameters of each grid to be evaluated as an origin, wherein each network type corresponds to one coordinate axis of the coordinate system, and each grid to be evaluated is positioned in one quadrant of the coordinate axes according to each sub-parameter;
at least one of the grids under evaluation in each of the quadrants is determined as one of the first sets.
Optionally, each of the importance parameters corresponds to one of the coordinate systems, and after determining at least one grid to be evaluated in each quadrant as one of the first sets, the method further includes:
dividing the first set into at least two subsets, wherein for any two subsets, the subparameter of any one grid to be evaluated in one subset is greater than or equal to the subparameter of any grid to be evaluated in the other subset.
Optionally, the determining the operation and maintenance policy of the target grid according to the network state includes:
dividing the at least one target grid into at least one second set according to the network state, wherein the network state of any one target grid in one second set is better than the network state of any one target grid in the other second set for any two second sets;
and determining the operation and maintenance strategies of the target grids according to the second set, wherein the target grids belonging to different second sets correspond to different operation and maintenance strategies.
Optionally, the network state is represented by at least two state parameters, and the dividing the at least one target grid into at least one second set according to the network state includes:
for each state parameter, dividing at least one target grid into at least one third set through the state parameters, wherein each third set corresponds to one third score, and for any two third sets, the state parameter of any one target grid in one third set is larger than the state parameter of any one target grid in the other third set;
For each target grid, weighting the third scores corresponding to at least two third sets of the target grids to obtain fourth scores of the target grids;
the at least one target mesh is partitioned into at least one second set according to the fourth score of the target mesh.
Optionally, the at least two status parameters include: weak coverage grid duty cycle, signal to noise ratio.
Optionally, the importance parameters include: a resident user parameter of a unit area and a value parameter of a unit area, wherein the resident user parameter is divided into a 5G resident user parameter and a non-5G resident user parameter according to a network type, and the value parameter is divided into a 5G value parameter and a non-5G value parameter.
In a second aspect, the present application provides a device for determining a network operation and maintenance policy, including:
an importance parameter obtaining module, configured to obtain importance parameters corresponding to at least two grids to be evaluated, where the grids to be evaluated include at least one cell, and the importance parameters are used to describe importance of the grids to be evaluated in at least one dimension;
the target grid determining module is used for determining at least one target grid to be operated and maintained from the at least two grids to be evaluated according to the importance parameters;
A network state determining module, configured to determine a network state of the target mesh;
and the operation and maintenance strategy determining module is used for determining the operation and maintenance strategy of the target grid according to the network state, the target grids in different network states correspond to different operation and maintenance strategies, and the operation and maintenance strategies are used for determining the priority between at least two operation and maintenance modes.
Optionally, the importance parameters are at least two, and the target grid determining module is further configured to:
for each importance parameter, dividing the at least two grids to be evaluated according to the importance parameter to obtain at least one first set corresponding to the importance parameter, wherein each first set corresponds to a first score;
for each grid to be evaluated, carrying out weighted summation on the first scores corresponding to at least two first sets of the grid to be evaluated, and obtaining a second score of the grid to be evaluated;
and determining at least one target grid to be operated and maintained from the at least two grids to be evaluated according to the second score.
Optionally, each importance parameter includes sub-parameters corresponding to at least two network types, and the target mesh determining module is further configured to:
When dividing the at least two grids to be evaluated according to the importance parameters to obtain at least one first set corresponding to the importance parameters, taking an average value of the sub-parameters of each grid to be evaluated as an origin to construct a coordinate system, wherein each network type corresponds to one coordinate axis of the coordinate system, and each grid to be evaluated is positioned in one quadrant of the coordinate axes according to each sub-parameter;
at least one of the grids under evaluation in each of the quadrants is determined as one of the first sets.
Optionally, each of the importance parameters corresponds to one of the coordinate systems, and the target grid determining module is further configured to:
after determining at least one of the grids under evaluation in each quadrant as one of the first sets, dividing the first set into at least two subsets, wherein for any two subsets, the sub-parameter of any one of the grids under evaluation in one subset is greater than or equal to the sub-parameter of any one of the grids under evaluation in the other subset.
Optionally, the operation and maintenance policy determining module is further configured to:
Dividing the at least one target grid into at least one second set according to the network state, wherein the network state of any one target grid in one second set is better than the network state of any one target grid in the other second set for any two second sets;
and determining the operation and maintenance strategies of the target grids according to the second set, wherein the target grids belonging to different second sets correspond to different operation and maintenance strategies.
Optionally, the network state is represented by at least two state parameters, and the operation and maintenance policy determining module is further configured to:
dividing at least one target grid into at least one second set according to network states, dividing at least one target grid into at least one third set by the state parameters for each state parameter, wherein each third set corresponds to one third score, and the state parameter of any one target grid in one third set is larger than the state parameter of any one target grid in the other third set for any two third sets;
for each target grid, weighting the third scores corresponding to at least two third sets of the target grids to obtain fourth scores of the target grids;
The at least one target mesh is partitioned into at least one second set according to the fourth score of the target mesh.
Optionally, the at least two status parameters include: weak coverage grid duty cycle, signal to noise ratio.
Optionally, the importance parameters include: a resident user parameter of a unit area and a value parameter of a unit area, wherein the resident user parameter is divided into a 5G resident user parameter and a non-5G resident user parameter according to a network type, and the value parameter is divided into a 5G value parameter and a non-5G value parameter.
In a third aspect, the present application provides an electronic device, comprising: at least one processor and memory;
the memory stores computer-executable instructions;
the at least one processor executes computer-executable instructions stored by the memory to cause the electronic device to implement a method as described in the foregoing first aspect.
In a fourth aspect, the present application provides a computer-readable storage medium having stored therein computer-executable instructions that, when executed by a processor, cause a computing device to implement a method as in the first aspect.
In a fifth aspect, the present application provides a computer program for implementing the method of the first aspect as described above.
The application provides a method and equipment for determining a network operation and maintenance strategy, which can acquire importance parameters corresponding to at least two grids to be evaluated respectively, wherein the grids to be evaluated comprise at least one cell, and the importance parameters are used for describing the importance of the grids to be evaluated from at least one dimension; determining at least one target grid to be operated and maintained from at least two grids to be evaluated according to the importance parameters; determining a network state of a target grid; and determining operation and maintenance strategies of the target grids according to the network states, wherein the target grids in different network states correspond to different operation and maintenance strategies, and the operation and maintenance strategies are used for determining priorities between at least two operation and maintenance modes. According to the method and the device for determining the operation and maintenance of the grid, important target grids can be determined according to importance parameters of the grids to be evaluated, operation and maintenance strategies are determined for the target grids according to network states of the target grids, and different network states correspond to different operation and maintenance strategies. Therefore, the accuracy of the operation and maintenance strategy is improved, and the communication quality after operation and maintenance is improved.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief description will be given below of the drawings that are needed in the embodiments or the prior art descriptions, it being obvious that the drawings in the following description are some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort to a person skilled in the art.
Fig. 1 is a schematic structural diagram of a wireless communication system according to an embodiment of the present application;
fig. 2 is a flowchart of specific steps of a method for determining a network operation and maintenance policy according to an embodiment of the present application;
FIG. 3 is a schematic diagram of partitioning a first set according to an embodiment of the present application;
FIG. 4 is a schematic diagram of partitioning another first set according to an embodiment of the present disclosure;
fig. 5 is a block diagram of a network operation policy determining device according to an embodiment of the present application;
fig. 6 is a block diagram of an electronic device according to an embodiment of the present application.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.
The embodiment of the application can be used in a wireless communication system. Fig. 1 is a schematic structural diagram of a wireless communication system according to an embodiment of the present application. Referring to fig. 1, the wireless communication system includes a core network device 110, a radio access network device 120, and at least one terminal device (e.g., terminal device 130 and terminal device 140 in fig. 1). The terminal equipment is connected with the wireless access network equipment in a wireless mode, and the wireless access network equipment is connected with the core network equipment in a wireless or wired mode. The core network device and the radio access network device may be separate physical devices, or may integrate the functions of the core network device and the logic functions of the radio access network device on the same physical device, or may integrate the functions of part of the core network device and part of the radio access network device on one physical device. The terminal device may be fixed in position or may be movable. Fig. 1 is only a schematic diagram, and other radio access network devices may be further included in the communication system, for example, a wireless relay device and a wireless backhaul device may also be included, which are not shown in fig. 1. The embodiments of the present application do not limit the number of core network devices, radio access network devices, and terminal devices included in the wireless communication system.
The radio access network device is an access device that a terminal device accesses to the wireless communication system in a wireless manner, and may be a base station (base station), an evolved NodeB (eNodeB), a transmission and reception point (transmission reception point, TRP), a next generation NodeB (gNB) in a 5G wireless communication system, a base station in a future wireless communication system, or an access node in a WiFi system, etc.; the present invention may also be a module or unit that performs a function of a base station part, for example, a Central Unit (CU) or a Distributed Unit (DU). The embodiment of the application does not limit the specific technology and the specific equipment form adopted by the wireless access network equipment.
In the embodiment of the present application, the means for implementing the function of the radio access network device may be the radio access network device; or may be a device, such as a chip system, capable of supporting the radio access network device to perform this function, which may be installed in the radio access network device or used in cooperation with the radio access network device. In the technical solution provided in the embodiments of the present application, the device for implementing the function of the radio access network device is taken as an example of the radio access network device, and the technical solution provided in the embodiments of the present application is described.
The Terminal device according to the embodiments of the present application may also be referred to as a Terminal, a User Equipment (UE), a Mobile Station (MS), a Mobile Terminal (MT), or the like. The terminal device may be a mobile phone, a tablet computer, a computer with a wireless transceiving function, a virtual reality terminal device, an augmented reality terminal device, a wireless terminal in industrial control, a wireless terminal in unmanned operation, a wireless terminal in teleoperation, a wireless terminal in smart grid, a wireless terminal in transportation security, a wireless terminal in smart city, a wireless terminal in smart home, or the like. The embodiment of the application does not limit the specific technology and the specific equipment form adopted by the terminal equipment.
In the prior art, in order to ensure the communication quality of the user, operations and maintenance can be performed for each area, including but not limited to: adding base station for the area, optimizing the existing base station, guiding the user to select the service type with better communication quality.
However, the above solution does not consider the importance of the area and the network status, resulting in poor accuracy of the operation and maintenance policy.
In order to solve the above problem, the embodiment of the present application may determine relatively important target grids according to importance parameters of the grids to be evaluated, and determine operation and maintenance policies for the target grids according to network states of the target grids, where different network states correspond to different operation and maintenance policies. Therefore, the accuracy of the operation and maintenance strategy is improved, and the communication quality after operation and maintenance is improved.
The following describes in detail, with specific embodiments, a technical solution of an embodiment of the present application and how the technical solution of the present application solves the foregoing technical problems. The following embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments. Embodiments of the present application will be described below with reference to the accompanying drawings.
Fig. 2 is a flowchart of specific steps of a method for determining a network operation and maintenance policy according to an embodiment of the present application. Referring to fig. 2, the method may include:
s201: and acquiring importance parameters corresponding to at least two grids to be evaluated respectively, wherein the grids to be evaluated comprise at least one cell, and the importance parameters are used for describing the importance of the grids to be evaluated in at least one dimension.
Wherein the at least two grids to be evaluated are all grids of the whole network or grids of partial areas.
The importance parameter of the grid is used for representing the importance of the grid to be evaluated. It will be appreciated that the greater the importance parameter, the higher the importance. In the embodiment of the present application, the importance parameters may be various, and one importance parameter corresponds to one dimension.
The importance parameters described above may include, but are not limited to: a resident user parameter per unit area and a value parameter per unit area. Wherein, the resident user parameter of unit area is the importance of evaluating from the user dimension, and the value parameter of unit area is the importance of evaluating from the value dimension.
Alternatively, the resident user parameters of the unit area may be divided into 5G resident user parameters of the unit area and non-5G resident user parameters of the unit area according to the network type, and the value parameters are divided into 5G value parameters of the unit area and non-5G value parameters of the unit area.
The 5G resident user parameter of the unit area may be the number of 5G resident users of the unit area, and may be a ratio of the total number of 5G resident users of the grid to be evaluated to the area of the grid to be evaluated.
The non-5G resident user parameter per unit area may be the number of non-5G resident users per unit area, and may be a ratio of the total number of non-5G resident users of the grid under evaluation to the area of the grid under evaluation.
The 5G value parameter per unit area may be a ratio of a total 5G value parameter of the grid under evaluation to an area of the grid under evaluation.
The non-5G value parameter per unit area may be a ratio of the total non-5G value parameter of the grid under evaluation to the area of the grid under evaluation.
S202: at least one target grid to be operated and maintained is determined from at least two grids to be evaluated according to the importance parameter.
The target grid may be a grid to be evaluated with higher importance parameters. Embodiments of the present disclosure provide for determining a target grid using a variety of strategies as follows.
In the first strategy, if the importance parameter is one, the grid to be evaluated with the importance parameter greater than or equal to the preset threshold may be determined as the target grid, and/or one or more grids to be evaluated with higher importance parameters may be determined as the target grid.
In the second strategy, if the importance parameters are at least two kinds, a score may be determined according to the two importance parameters, then a grid to be evaluated with the score greater than or equal to a preset threshold value is determined as a target grid, and/or one or more grids to be evaluated with the score higher are determined as target grids.
Wherein the score may be a weighted sum of two importance parameters.
In a third strategy, if the importance parameters are at least two, firstly, dividing at least two grids to be evaluated according to the importance parameters for each importance parameter to obtain at least one first set corresponding to the importance parameters, wherein each first set corresponds to a first score; then, for each grid to be evaluated, carrying out weighted summation on first scores corresponding to at least two first sets of the grid to be evaluated to obtain second scores of the grid to be evaluated; finally, at least one target grid to be operated and maintained is determined from the at least two grids to be evaluated according to the second score.
Wherein, for any two first sets, the importance parameter of any grid to be evaluated in one first set is larger than any grid to be evaluated in the other first set.
In order to obtain the first set, for each importance parameter, at least one grid to be evaluated can be divided by at least one threshold value corresponding to the importance parameter and the importance parameter, so as to obtain at least one first set corresponding to the importance parameter. For example, there are two thresholds TH1 and TH2, and TH1 is greater than TH2, so that the following three first sets can be obtained: a first set of at least one mesh under evaluation having an importance parameter greater than or equal to TH1, a first set of at least one mesh under evaluation having an importance parameter less than TH2 and greater than or equal to TH1, a first set of at least one mesh under evaluation having an importance parameter less than TH 1.
The threshold may be preset, or may be an average value of importance parameters of all grids to be evaluated.
It can be seen that each of the importance parameters described above is not divided by network type. In practical applications, each of the above importance parameters may be divided into two sub-parameters according to the network type. For example, the resident user parameter per unit area may be divided into a 5G resident user number per unit area and a non-5G resident user number per unit area according to whether or not the resident user parameter is a 5G network. Similarly, the value parameter per unit area may be divided into a 5G value parameter per unit area and a non-5G value parameter per unit area according to whether or not it is a 5G network.
When the importance parameters are divided into at least two sub-parameters according to the network type, the embodiment of the application can divide the grid to be evaluated through a coordinate system to obtain at least one first set of the importance parameters. Specifically, firstly, taking an average value of sub-parameters of each grid to be evaluated as an origin to construct a coordinate system, wherein each network type corresponds to one coordinate axis of the coordinate system, and each grid to be evaluated is positioned in one quadrant of the coordinate axis according to each sub-parameter; at least one grid to be evaluated in each quadrant is then determined as a first set.
Wherein the dimension of the coordinate system is determined by the number of network types, and the two are the same. For example, when the network type includes 5G and non-5G, the dimension of the coordinate system is 2, that is, the coordinate system is a two-dimensional coordinate system. For another example, when the network type includes 5G, 4G, and 3G or less, the dimension of the coordinate system may be 3, that is, the coordinate system is a three-dimensional coordinate system.
The process of dividing the first set is described below with the number of resident users per unit area as an example.
Fig. 3 is a schematic diagram of partitioning a first set according to an embodiment of the present application. Referring to fig. 3, the horizontal axis corresponds to the number of non-5G resident users per unit area, and the vertical axis corresponds to the number of 5G resident users per unit area. The abscissa of the origin is the average value of the number of non-5G resident users of the unit area of each grid to be evaluated, and the ordinate of the origin is the average value of the number of 5G resident users of the unit area of each grid to be evaluated.
As can be seen from fig. 3, since the larger the number of resident users per unit area represents the higher the importance of the grids to be evaluated, the importance of each grid to be evaluated in the first set A1 is the highest, the importance of each grid to be evaluated in the first set C1 is the lowest, and the importance of the grids to be evaluated in the first sets B1 and D1 is centered. Thus, the first score corresponding to the first set A1 is highest, the first scores corresponding to B1 and D1 are respectively lowest, and the first score corresponding to C1 is lowest.
Fig. 4 is a schematic diagram of partitioning another first set according to an embodiment of the present application. Referring to fig. 4, the horizontal axis corresponds to a non-5G value parameter per unit area, and the vertical axis corresponds to a 5G value parameter per unit area. The abscissa of the origin is the average value of the non-5G value parameters of the unit area of each grid to be evaluated, and the ordinate of the origin is the average value of the 5G value parameters of the unit area of each grid to be evaluated.
As can be seen from fig. 3, since a larger value parameter per unit area represents a higher importance of the grids to be evaluated, the importance of each grid to be evaluated in the first set A2 is highest, the importance of each grid to be evaluated in the first set C2 is lowest, and the importance of the grids to be evaluated in the first sets B2 and D2 is centered. Thus, the first score corresponding to the first set A2 is highest, the first scores corresponding to B2 and D2 are inferior, and the first score corresponding to C2 is lowest.
Optionally, the set corresponding to the quadrants may be further refined, that is, the set corresponding to the quadrants is further divided into a plurality of subsets. Specifically, the set corresponding to one or more quadrants may be divided into subsets, such that the set corresponding to one or more subsets and the quadrants not originally divided into subsets constitute a final first set.
The above-mentioned process of further dividing the set corresponding to the quadrant may include: the first set is divided into at least two subsets, for any two subsets, the subparameter of any one grid to be evaluated in one subset is greater than or equal to the subparameter of any grid to be evaluated in the other subset.
For the first set A1 in fig. 3, it can be divided into two subsets a11 and a12. Wherein the grid under evaluation in a11 comprises at least one of: the first 10% of grids to be evaluated in descending order of 5G resident users per unit area, and the first 10% of grids to be evaluated in descending order of non-5G resident users per unit area. The grid under evaluation in a12 includes at least one of: a grid to be evaluated of the last 90% in descending order of 5G resident users per unit area, a grid to be evaluated of the last 90% in descending order of non-5G resident users per unit area. Thus, a11 corresponds to a first score that is greater than a12.
For the first set A2 in fig. 4, it can be divided into two subsets a21 and a22. Wherein the grid under evaluation in a21 comprises at least one of: the first 10% of grids under evaluation arranged in descending order of 5G value parameters per unit area, the first 10% of grids under evaluation arranged in descending order of non-5G value parameters per unit area. The grid under evaluation in a22 includes at least one of: the last 90% of grids to be evaluated, arranged in descending order of 5G value parameters per unit area, the last 90% of grids to be evaluated, arranged in descending order of non-5G value parameters per unit area. Thus, a21 corresponds to a first score that is greater than a22.
Since the first sets A1 and A2 are divided into subsets, the final first set corresponding to the resident 5G user number is: a11, A12, B1, C1 and D1, the final first set of value parameters is: a21, a22, B2, C2, and D2.
The first score of A11 is larger than the first score of A12, the first score of A12 is larger than the first scores of B1 and D1, and the first score of C1 is the smallest. For example, a first score of 100 for a11, 90 for a12, 80 for D1, 70 for B1, and 60 for C1.
The first score of a21 is greater than the first score of a22, the first score of a22 is greater than the first scores of B2 and D2, and the first score of C2 is the smallest. For example, a first score of 100 for a21, 90 for a22, 80 for D2, 70 for B2, and 60 for C2.
From the above process, it can be seen that at least one grid to be evaluated is divided according to each importance parameter, so as to obtain at least one first set corresponding to one division result, so that multiple importance parameters correspond to multiple division results. That is, each grid to be evaluated belongs to at least two first sets, and each first set corresponds to a division result of one importance parameter. Since each first set corresponds to one first score, a second score can be obtained by combining the first scores of at least two first sets.
The second score may be a weighted sum of the two first scores. For example, for a grid to be evaluated, if it belongs to the aforementioned first set a11 and B2, the second score is thus the first score of a11, the weight of the number of resident users+the weight of the first score of B2, the weight of the value parameter is 100×0.4+70×0.6=82.
After the second score is obtained, the grid to be evaluated with the second score higher may be determined as the target grid. For example, a number of grids to be evaluated that are ranked first by the second score may be determined as target grids, and/or a number of grids to be evaluated that have the second score greater than or equal to a preset threshold may be determined as target grids. That is, the target mesh is a mesh of relatively high importance.
S203: the network state of the target mesh is determined.
Wherein the network state may be represented by at least two state parameters: weak coverage grid duty cycle, SINR (signal to interference plus noise ratio, signal to noise ratio).
For the weak coverage cell duty cycle described above to be the ratio of the number of weak coverage cells in one grid to the number of all the cells in that grid, the weak coverage cell is the one where RSRP (reference signal receiving power, reference signal received power) is less than the preset power threshold. The RSRP of the grid may be an average of RSRP of a plurality of sampling points within the grid, and the RSRP may be extracted from the MR (messurement report, measurement report) of the sampling points. It can be seen that the smaller the weak coverage grid duty cycle, the better the network coverage representing the grid, and the better the network state.
The signal-to-noise ratio is the ratio between the signal strength and the noise strength. The signal-to-noise ratio of the grid may be an average of the signal-to-noise ratios of all the sampling points in the grid. The signal-to-noise ratio of the sample point can be extracted from the MR of the sample point. It can be seen that the smaller the signal-to-noise ratio, the less interference that represents the grid, and the better the network state.
S204: and determining operation and maintenance strategies of the target grids according to the network states, wherein the target grids in different network states correspond to different operation and maintenance strategies, and the operation and maintenance strategies are used for determining priorities between at least two operation and maintenance modes.
Wherein, at least two operation and maintenance modes are used for carrying out various operation and maintenance on the network service of the target grid, including but not limited to: optimizing network, newly building base station, guiding user to select network service type. The operation and maintenance strategy is thus used to determine the priority between, i.e. order, the three modes.
It can be appreciated that each target grid needs to be operated and maintained in the three manners described above, but the priority order among the three manners corresponding to the target grids in different network states is different. For example, for a target grid with a better network state, the user can be preferentially guided to select a network service type, and then the network and a newly-built base station are optimized. For the target grid with poor network state, the network and the newly built base station can be optimized preferentially, and then the user is guided to select the network service type.
When the user is guided to select the network service type, the sub-parameters after the network type division can be performed according to the importance parameters of the target grid.
For example, for a target grid with a higher 5G resident user number and a higher non-5G resident user number, or a target grid with a higher 5G value parameter and a higher non-5G value parameter, a user who is newly connected to the network may be guided to preferentially select a 5G network service, perform 5G network optimization, and perform VIP (very important person ) key guarantee.
For another example, for a target grid with a small number of 5G resident users and a large number of non-5G resident users, or a target grid with a low 5G value parameter and a high non-5G value parameter, a non-5G network user may be guided to change to a 5G network, and a newly-accessed user may be guided to select a 5G network.
For another example, for a target grid with a large number of 5G resident users and a small number of non-5G resident users, or a target grid with a high 5G value parameter and a non-5G value parameter, 5G package upgrade and VIP user guarantee can be provided preferentially, and new users are attracted to access the network.
Also for example, for a target grid with a lower number of 5G resident users and a lower number of non-5G resident users, or a target grid with a lower 5G value parameter and a lower non-5G value parameter, a new user may be attracted to the network.
Optionally, when determining the operation and maintenance policy, at least one target grid may be first divided into at least one second set according to a network state, where, for any two second sets, the network state of any target grid in one second set is better than the network state of any target grid in the other second set; and then, determining the operation and maintenance strategies of the target grids according to the second set, wherein the target grids belonging to different second sets correspond to different operation and maintenance strategies.
When the network state is represented by a state parameter, the target mesh may be partitioned into at least one second set by the state parameter and at least one preset threshold. For example, there are three preset thresholds TH1, TH2, and TH3, and TH1> TH2> TH3. Thus, at least one target mesh having a state parameter greater than or equal to TH1 may be divided into a second set, at least one target mesh having a state parameter less than TH1 and greater than or equal to TH2 may be divided into a second set, at least one target mesh having a state parameter less than TH2 and greater than or equal to TH3 may be divided into a second set, and at least one target mesh having a state parameter less than TH3 may be divided into a second set.
For example, when the above state parameter is a weak coverage grid duty cycle, the following four second sets may be obtained: a set of at least one target mesh with a weak coverage grid ratio of greater than or equal to 15%, a set of at least one target mesh with a weak coverage grid ratio of less than 15% and greater than or equal to 10%, a set of at least one target mesh with a weak coverage grid ratio of less than 10% and greater than or equal to 5%, a set of at least one target mesh with a weak coverage grid ratio of less than 5%.
For another example, when the above state parameter is signal to noise ratio, the following four second sets may be obtained: a set of at least one target mesh having a signal to noise ratio of greater than or equal to 10, a set of at least one target mesh having a signal to noise ratio of less than 10 and greater than or equal to 5, a set of at least one target mesh having a signal to noise ratio of less than 5 and greater than or equal to 0, a set of at least one target mesh having a signal to noise ratio of less than 0.
When the network state is represented by at least two state parameters, firstly, dividing at least one target grid into at least one third set by the state parameters for each state parameter, wherein each third set corresponds to one third score, and for any two third sets, the state parameter of any target grid in one third set is larger than the state parameter of any target grid in the other third set; then, for each target grid, weighting third scores corresponding to at least two third sets of the target grids to obtain fourth scores of the target grids; finally, partitioning the at least one target mesh into at least one second set according to a fourth score of the target mesh.
It will be appreciated that the principle of dividing at least one object grid into at least one third set per state parameter is the same as the principle of dividing at least one object grid into at least one second set per one state parameter.
Furthermore, each state parameter may divide at least one target mesh to obtain a division result, that is, at least one third set corresponding to the state parameter. Thus, for one target grid it may belong to at least two third sets of at least two state parameters respectively. For example, the state parameters include a weak coverage grid duty cycle and a signal-to-noise ratio, such that one target grid may be partitioned into one third set according to the weak coverage grid duty cycle, and may be partitioned into another third set according to the signal-to-noise ratio. At this time, the third scores of the two sets may be weighted and summed to obtain a fourth score of the target grid.
After the fourth score is obtained, the at least one target mesh may also be partitioned into at least one second set. Specifically, the second set may be obtained by dividing the fourth score by at least one threshold corresponding to the fourth score. The principle is the same as that of dividing the first set and the third set, and will not be described in detail here.
Fig. 5 is a block diagram of a network operation policy determining device according to an embodiment of the present application, corresponding to the method for determining a network operation policy in the above embodiment. For convenience of explanation, only portions relevant to the embodiments of the present application are shown. Referring to fig. 5, the network operation policy determining apparatus 300 includes: an importance parameter acquisition module 301, a target grid determination module 302, a network state determination module 303, and an operation and maintenance policy determination module 304.
The importance parameter obtaining module 301 is configured to obtain importance parameters corresponding to at least two grids to be evaluated, where the grids to be evaluated include at least one cell, and the importance parameters are used to describe importance of the grids to be evaluated in at least one dimension.
A target grid determining module 302, configured to determine at least one target grid to be operated from the at least two grids to be evaluated according to the importance parameter.
A network state determining module 303, configured to determine a network state of the target mesh.
The operation and maintenance policy determining module 304 is configured to determine operation and maintenance policies of the target grid according to the network state, where the target grids in different network states correspond to different operation and maintenance policies, and the operation and maintenance policies are used to determine priorities between at least two operation and maintenance modes.
Optionally, the importance parameters are at least two, and the target mesh determining module 302 is further configured to:
for each importance parameter, dividing the at least two grids to be evaluated according to the importance parameter to obtain at least one first set corresponding to the importance parameter, wherein each first set corresponds to a first score; for each grid to be evaluated, carrying out weighted summation on the first scores corresponding to at least two first sets of the grid to be evaluated, and obtaining a second score of the grid to be evaluated; and determining at least one target grid to be operated and maintained from the at least two grids to be evaluated according to the second score.
Optionally, each importance parameter includes sub-parameters corresponding to at least two network types, and the target mesh determining module 302 is further configured to:
when dividing the at least two grids to be evaluated according to the importance parameters to obtain at least one first set corresponding to the importance parameters, taking an average value of the sub-parameters of each grid to be evaluated as an origin to construct a coordinate system, wherein each network type corresponds to one coordinate axis of the coordinate system, and each grid to be evaluated is positioned in one quadrant of the coordinate axes according to each sub-parameter; at least one of the grids under evaluation in each of the quadrants is determined as one of the first sets.
Optionally, each of the importance parameters corresponds to one of the coordinate systems, and the target grid determining module 302 is further configured to:
after determining at least one of the grids under evaluation in each quadrant as one of the first sets, dividing the first set into at least two subsets, wherein for any two subsets, the sub-parameter of any one of the grids under evaluation in one subset is greater than or equal to the sub-parameter of any one of the grids under evaluation in the other subset.
Optionally, the operation and maintenance policy determining module 304 is further configured to:
dividing the at least one target grid into at least one second set according to the network state, wherein the network state of any one target grid in one second set is better than the network state of any one target grid in the other second set for any two second sets; and determining the operation and maintenance strategies of the target grids according to the second set, wherein the target grids belonging to different second sets correspond to different operation and maintenance strategies.
Optionally, the network state is represented by at least two state parameters, and the operation and maintenance policy determining module 304 is further configured to:
Dividing at least one target grid into at least one second set according to network states, dividing at least one target grid into at least one third set by the state parameters for each state parameter, wherein each third set corresponds to one third score, and the state parameter of any one target grid in one third set is larger than the state parameter of any one target grid in the other third set for any two third sets; for each target grid, weighting the third scores corresponding to at least two third sets of the target grids to obtain fourth scores of the target grids; the at least one target mesh is partitioned into at least one second set according to the fourth score of the target mesh.
Optionally, the at least two status parameters include: weak coverage grid duty cycle, signal to noise ratio.
Optionally, the importance parameters include: a resident user parameter of a unit area and a value parameter of a unit area, wherein the resident user parameter is divided into a 5G resident user parameter and a non-5G resident user parameter according to a network type, and the value parameter is divided into a 5G value parameter and a non-5G value parameter.
The determination device of the network operation and maintenance policy provided in this embodiment may be used to execute the technical scheme of the method embodiment shown in fig. 2, and its implementation principle and technical effect are similar, and this embodiment is not repeated here.
Fig. 6 is a block diagram of an electronic device according to an embodiment of the present application. The electronic device 600 comprises a memory 602 and at least one processor 601.
Wherein the memory 602 stores computer-executable instructions. At least one processor 601 executes computer-executable instructions stored in a memory 602, causing the electronic device 601 to implement the method of fig. 2 as previously described.
The electronic device may further comprise a receiver 603 for receiving information from the remaining means or devices and forwarding to the processor 601, and a transmitter 604 for transmitting information to the remaining means or devices.
Embodiments of the present application also provide a computer-readable storage medium having stored therein computer-executable instructions that, when executed by a processor, cause a computing device to implement the method of fig. 2.
The embodiment of the application also provides a computer program for implementing the method in fig. 2.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application.
Claims (9)
1. A method for determining a network operation policy, comprising:
acquiring importance parameters corresponding to at least two grids to be evaluated respectively, wherein the grids to be evaluated comprise at least one cell, and the importance parameters are used for describing the importance of the grids to be evaluated from at least one dimension;
determining at least one target grid to be operated and maintained from the at least two grids to be evaluated according to the importance parameters;
determining a network state of the target grid;
determining operation and maintenance strategies of the target grids according to the network states, wherein the target grids in different network states correspond to different operation and maintenance strategies, and the operation and maintenance strategies are used for determining priorities between at least two operation and maintenance modes;
The importance parameters are at least two kinds, and the determining at least one target grid to be operated from the at least two grids to be evaluated according to the importance parameters comprises the following steps:
for each importance parameter, dividing the at least two grids to be evaluated according to the importance parameter to obtain at least one first set corresponding to the importance parameter, wherein each first set corresponds to a first score;
for each grid to be evaluated, carrying out weighted summation on the first scores corresponding to at least two first sets of the grid to be evaluated, and obtaining a second score of the grid to be evaluated;
determining at least one target grid to be operated and maintained from the at least two grids to be evaluated according to the second score;
each importance parameter comprises at least two sub-parameters corresponding to network types, the dividing the at least two grids to be evaluated according to the importance parameters to obtain at least one first set corresponding to the importance parameters comprises:
constructing a coordinate system by taking an average value of the sub-parameters of each grid to be evaluated as an origin, wherein each network type corresponds to one coordinate axis of the coordinate system, and each grid to be evaluated is positioned in one quadrant of the coordinate axes according to each sub-parameter;
At least one of the grids under evaluation in each of the quadrants is determined as one of the first sets.
2. The method of claim 1, wherein each of said importance parameters corresponds to one of said coordinate systems, and wherein said determining at least one of said grids to be evaluated in each of said quadrants as one of said first sets further comprises:
dividing the first set into at least two subsets, wherein for any two subsets, the subparameter of any one grid to be evaluated in one subset is greater than or equal to the subparameter of any grid to be evaluated in the other subset.
3. The method according to claim 1 or 2, wherein said determining an operation and maintenance policy of the target grid according to the network state comprises:
dividing the at least one target grid into at least one second set according to the network state, wherein the network state of any one target grid in one second set is better than the network state of any one target grid in the other second set for any two second sets;
and determining the operation and maintenance strategies of the target grids according to the second set, wherein the target grids belonging to different second sets correspond to different operation and maintenance strategies.
4. A method according to claim 3, wherein the network state is represented by at least two state parameters, said dividing the at least one target grid into at least one second set according to network state comprising:
for each state parameter, dividing at least one target grid into at least one third set through the state parameters, wherein each third set corresponds to one third score, and for any two third sets, the state parameter of any one target grid in one third set is larger than the state parameter of any one target grid in the other third set;
for each target grid, weighting the third scores corresponding to at least two third sets of the target grids to obtain fourth scores of the target grids;
the at least one target mesh is partitioned into at least one second set according to the fourth score of the target mesh.
5. The method of claim 4, wherein the at least two state parameters comprise: weak coverage grid duty cycle, signal to noise ratio.
6. The method of claim 1, wherein the importance parameter comprises: a resident user parameter of a unit area and a value parameter of a unit area, wherein the resident user parameter is divided into a 5G resident user parameter and a non-5G resident user parameter according to a network type, and the value parameter is divided into a 5G value parameter and a non-5G value parameter.
7. A network operation and maintenance policy determining apparatus, comprising:
an importance parameter obtaining module, configured to obtain importance parameters corresponding to at least two grids to be evaluated, where the grids to be evaluated include at least one cell, and the importance parameters are used to describe importance of the grids to be evaluated in at least one dimension;
the target grid determining module is used for determining at least one target grid to be operated and maintained from the at least two grids to be evaluated according to the importance parameters;
a network state determining module, configured to determine a network state of the target mesh;
the operation and maintenance strategy determining module is used for determining operation and maintenance strategies of the target grid according to the network state, the target grids in different network states correspond to different operation and maintenance strategies, and the operation and maintenance strategies are used for determining priorities between at least two operation and maintenance modes;
the importance parameters are at least two kinds, and the target grid determining module is further configured to:
for each importance parameter, dividing the at least two grids to be evaluated according to the importance parameter to obtain at least one first set corresponding to the importance parameter, wherein each first set corresponds to a first score;
For each grid to be evaluated, carrying out weighted summation on the first scores corresponding to at least two first sets of the grid to be evaluated, and obtaining a second score of the grid to be evaluated;
determining at least one target grid to be operated and maintained from the at least two grids to be evaluated according to the second score;
each importance parameter comprises at least two sub-parameters corresponding to the network types, and the target grid determining module is further configured to:
constructing a coordinate system by taking an average value of the sub-parameters of each grid to be evaluated as an origin, wherein each network type corresponds to one coordinate axis of the coordinate system, and each grid to be evaluated is positioned in one quadrant of the coordinate axes according to each sub-parameter;
at least one of the grids under evaluation in each of the quadrants is determined as one of the first sets.
8. An electronic device, the electronic device comprising: at least one processor and memory;
the memory stores computer-executable instructions;
the at least one processor executing computer-executable instructions stored in the memory causes the electronic device to implement the method of any one of claims 1 to 6.
9. A computer readable storage medium having stored therein computer executable instructions which, when executed by a processor, cause a computing device to implement the method of any of claims 1 to 6.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA2551638A1 (en) * | 2005-07-08 | 2007-01-08 | Cta Communications, Inc. | Method and system for evaluating radio coverage |
| CN103136393A (en) * | 2011-11-28 | 2013-06-05 | 中国电子科技集团公司第五十四研究所 | Area coverage rate calculating method based on mesh division |
| CN105744535A (en) * | 2016-05-02 | 2016-07-06 | 北京联合大学 | Cell information detection and cell coverage calibration method for mobile network |
| CN106937299A (en) * | 2015-12-30 | 2017-07-07 | 中国移动通信集团北京有限公司 | A kind of antenna adjusting method and device |
| CN109661001A (en) * | 2019-01-11 | 2019-04-19 | 中国联合网络通信集团有限公司 | A kind of network optimized approach and server |
| CN110167037A (en) * | 2019-05-24 | 2019-08-23 | 中国联合网络通信集团有限公司 | LTE network interference estimation method, device, system and storage medium |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8675553B2 (en) * | 2009-03-26 | 2014-03-18 | Qualcomm Incorporated | Regulating the scope of service geographically in wireless networks based on priority |
-
2021
- 2021-10-13 CN CN202111190975.1A patent/CN113950082B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA2551638A1 (en) * | 2005-07-08 | 2007-01-08 | Cta Communications, Inc. | Method and system for evaluating radio coverage |
| CN103136393A (en) * | 2011-11-28 | 2013-06-05 | 中国电子科技集团公司第五十四研究所 | Area coverage rate calculating method based on mesh division |
| CN106937299A (en) * | 2015-12-30 | 2017-07-07 | 中国移动通信集团北京有限公司 | A kind of antenna adjusting method and device |
| CN105744535A (en) * | 2016-05-02 | 2016-07-06 | 北京联合大学 | Cell information detection and cell coverage calibration method for mobile network |
| CN109661001A (en) * | 2019-01-11 | 2019-04-19 | 中国联合网络通信集团有限公司 | A kind of network optimized approach and server |
| CN110167037A (en) * | 2019-05-24 | 2019-08-23 | 中国联合网络通信集团有限公司 | LTE network interference estimation method, device, system and storage medium |
Non-Patent Citations (1)
| Title |
|---|
| 尹静萍.《中国优秀硕士学位论文全文数据库》.2019,全文. * |
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