CN111294809A - Method, apparatus, device and medium for identifying problem concentrated area - Google Patents

Method, apparatus, device and medium for identifying problem concentrated area Download PDF

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CN111294809A
CN111294809A CN201811487349.7A CN201811487349A CN111294809A CN 111294809 A CN111294809 A CN 111294809A CN 201811487349 A CN201811487349 A CN 201811487349A CN 111294809 A CN111294809 A CN 111294809A
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CN111294809B (en
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李伶
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China Mobile Communications Group Co Ltd
China Mobile Group Hainan Co Ltd
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Abstract

The application discloses a method, a device, equipment and a medium for identifying problem concentration areas. The method comprises the following steps: determining a whole network adjacency relation table based on a whole network engineering parameter table and a Delaunay triangle rule; determining a problem base station in the whole network adjacency list according to the communication parameters of the base stations in the whole network adjacency list; associating the problem base station with the problem characteristics in the whole network employee participation table to obtain a problem element set; and obtaining a problem concentration area based on the problem element set. According to the embodiment of the invention, the problem concentration area can be identified more accurately.

Description

Method, apparatus, device and medium for identifying problem concentrated area
Technical Field
The present invention relates to the field of computer technologies, and in particular, to a method, an apparatus, a device, and a medium for identifying a problem concentration area.
Background
In order to improve the solving efficiency of the cell communication problem, the problem concentration area can be identified, and a solution is found by analyzing the problem reason of the problem concentration area, so that the solving efficiency of the problem is improved.
Currently, the identification of the problem concentration area is usually based on the neighborhood rule. However, the adjacency relation set according to the adjacent region rule is not changed in general, and needs manual maintenance, and once the wireless environment is changed greatly or the manual maintenance is not timely, the problem concentration area cannot be identified effectively.
Therefore, the technical problem that the problem concentration area cannot be accurately identified exists at present.
Disclosure of Invention
The embodiment of the invention provides a method, a device, equipment and a medium for identifying a problem concentration area, which can accurately identify the problem concentration area.
In one aspect of the embodiments of the present invention, a method for identifying a problem concentration area is provided, where the method includes:
determining a whole network adjacency relation table based on a whole network engineering parameter table and a Delaunay (Delaunay) triangle rule;
determining a problem base station in the whole network adjacency list according to the communication parameters of the base stations in the whole network adjacency list;
associating the problem base station with the problem characteristics in the whole network employee participation table to obtain a problem element set;
and obtaining a problem concentration area based on the problem element set.
In another aspect of the embodiments of the present invention, an apparatus for identifying a problem concentration area is provided, where the apparatus includes:
the relation table module is used for determining a whole-network adjacency relation table based on a whole-network engineering parameter table and a Delaunay triangle rule;
the base station module is used for determining a problem base station in the whole network adjacency list according to the communication parameters of the base stations in the whole network adjacency list;
the element set module is used for correlating the problem base station with the problem characteristics in the whole network employee participation table to obtain a problem element set;
and the region module is used for obtaining a problem concentrated region based on the problem element set.
According to another aspect of the embodiments of the present invention, there is provided an apparatus for problem concentration area identification, the apparatus including:
a processor and a memory storing computer program instructions;
the processor, when executing the computer program instructions, implements the method of problem concentration area identification as provided by any of the aspects of the embodiments of the present invention described above.
According to another aspect of embodiments of the present invention, there is provided a computer storage medium having stored thereon computer program instructions which, when executed by a processor, implement the method of problem concentration area identification as provided by any one of the aspects of embodiments of the present invention described above.
The embodiment of the invention provides a method, a device, equipment and a medium for identifying problem concentrated areas. The system automatically generates a whole-network adjacency relation table based on the whole-network employee parameter table and the Delaunay triangle rule. And determining problem base stations based on the whole network adjacency relation table, and finally performing area division on the determined problem base stations, so that the problem concentrated area can be identified more accurately.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required to be used in the embodiments of the present invention will be briefly described below, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 illustrates a flow diagram of a method of problem focus area identification in accordance with an embodiment of the present invention;
FIG. 2 is a diagram illustrating a full network adjacency table according to an embodiment of the present invention;
FIG. 3 illustrates a Manhattan distance diagram of an embodiment of the invention;
FIG. 4 illustrates a schematic diagram of a greedy algorithm of an embodiment of the present invention;
FIG. 5 is a diagram illustrating the results of a problem concentration area according to an embodiment of the present invention;
FIG. 6 is a schematic structural diagram of an apparatus for identifying problem concentrated areas according to an embodiment of the present invention
FIG. 7 sets forth a block diagram of an exemplary hardware architecture of a computing device capable of implementing the method and apparatus for problem concentration area identification according to embodiments of the present invention;
Detailed Description
Features and exemplary embodiments of various aspects of the present invention will be described in detail below, and in order to make objects, technical solutions and advantages of the present invention more apparent, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not to be construed as limiting the invention. It will be apparent to one skilled in the art that the present invention may be practiced without some of these specific details. The following description of the embodiments is merely intended to provide a better understanding of the present invention by illustrating examples of the present invention.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
A method, apparatus, device, and medium for problem concentrated region identification according to embodiments of the present invention are described in detail below with reference to the accompanying drawings. It should be noted that these examples are not intended to limit the scope of the present disclosure.
The method for identifying the problem concentration area according to the embodiment of the present invention is described in detail below with reference to fig. 1 to 5.
For better understanding of the present invention, the method for identifying a problem concentrated area according to an embodiment of the present invention is described in detail below with reference to fig. 1, and fig. 1 is a flowchart illustrating the method for identifying a problem concentrated area according to an embodiment of the present invention.
As shown in fig. 1, a method 100 for identifying a problem concentration area in an embodiment of the present invention includes the following steps:
s110, determining a whole network adjacency relation table based on the whole network join table and Delaunay triangle rules.
Specifically, the full-network employee participation table may include: location information of the base station, which may be longitude and latitude of the base station, communication parameters of the base station, problem characteristics of the base station, and the like.
In one embodiment of the present invention, first, base stations having longitude information and latitude information in the full-network reference table are projected onto a two-dimensional plane, so that a plurality of base stations having two-dimensional location points can be obtained.
In the Delaunay triangulation, V is a finite point set on a two-dimensional real number domain, an edge E is a closed line segment formed by points in the point set as end points, and E is a set of E. Then a triangulation T ═ (V, E) of the set of points V is a plan G which satisfies the condition: edges in the plan view do not contain any points in the set of points, except for the endpoints; there are no intersecting edges; all the faces in the plan view are triangular faces, and the collection of all the triangular faces is the convex hull of the scatter set V. If a triangulation T of the set of points V contains only Delaunay edges, the triangulation is referred to as a Delaunay triangulation.
Dirichlet (Dirichlet) domain partitioning is a process in which n non-identical scattered data points on a given plane are constructed, and a neighborhood Kp is constructed for each scattered point p, so that the Euclidean distance between any point q in Kp and the point p is not greater than the Euclidean distance between q and other scattered points p, and the domain partitioning is called Dirichlet domain partitioning and is also called a Thiessen polygon Voronoi diagram. By this definition, a domain boundary is the perpendicular bisector of a straight line connecting two adjacent scattered data points.
After domain segmentation is performed on the scattered data points on the plane, as shown in fig. 2, fig. 2 is a schematic diagram illustrating a full-network adjacency table in an embodiment of the present invention. And forming a triangulation by connecting scattered point pairs with a public domain boundary into a full-network adjacency table.
In one embodiment of the invention, a plurality of base stations with two-dimensional location points are taken as a finite set of points on a two-dimensional real number domain in the Delaunay triangle rule. And on the basis of a finite point set formed by two-dimensional coordinate points of the base station, carrying out Delaunay triangulation and Dirichlet domain segmentation according to a Delaunay triangle rule to obtain a whole network adjacency relation table.
In the embodiment of the invention, the system automatically generates the whole-network adjacency list based on the whole-network employee participation list and the Delaunay triangle rule. The adjacency relation can be maintained without manpower, the identification efficiency is improved, and meanwhile, the accuracy of region identification is also improved.
And S120, determining the problem base station in the whole network adjacency list according to the communication parameters of the base stations in the whole network adjacency list.
Specifically, the problem parameter may be an interference value or a Long Term Evolution (LTE) handover success rate.
In one embodiment of the present invention, based on the problem concentration area to be identified, first, the problem parameter in the communication parameters of the base stations in the whole network adjacency list is confirmed, and the threshold value of the problem parameter is set. Secondly, according to the determined problem parameters, a judgment rule is selected. And finally, determining the problem base station in the whole network adjacency relation table based on the threshold value of the problem parameter, the actual value of the problem parameter and the judgment rule.
As a specific example, when the problem parameter is an interference value, the determination rule is to use a base station, of which the actual value of the problem parameter is greater than the threshold value of the problem parameter, as the problem base station. I.e. when the actual value of the interference value is larger than the threshold value of the interference value, the base station with the interference value parameter is taken as the problem base station. And when the problem parameter is the LTE switching success rate, determining that the judgment rule is that the base station of which the actual value of the problem parameter is less than or equal to the threshold value of the problem parameter is used as the problem base station. Namely, when the actual value of the LTE switching success rate is less than or equal to the threshold value of the LTE switching success rate, the base station with the LTE switching success rate parameter is taken as the problem base station.
In another embodiment of the present invention, the communication parameters of the base stations in the whole network adjacency list can be sequenced and predicted by a time series algorithm, so as to obtain the problem base station.
As a specific example, the 11 th symbol of the atmospheric waveguide interference is not interfered, the average interference noise per Physical Resource Block (PRB) subcarrier of the system uplink is generally not large, and the interference value strength relationship of the related symbols is as follows: uplink pilot time slot (UPPTS) > symbol 1 > symbol 6. Auto-convergence with such features is a problematic base station.
In the embodiment of the invention, the base station needing area identification can be accurately positioned by setting the threshold value of the problem parameter, and the error caused by manual division is effectively avoided, thereby improving the accuracy of area identification.
And S130, associating the problem base station with the problem features in the whole network employee participation table to obtain a problem element set.
In one embodiment of the invention, the problem feature may be an elevated interference level, a degraded wireless signal quality or a degraded customer perception.
And associating the problem base station with the problem features in the whole network employee list to obtain a problem element set comprising the base station and the problem features associated with the base station.
And S140, obtaining a problem concentrated area based on the problem element set.
In one embodiment of the invention, based on problem characteristics associated with base stations in the problem element set, a greedy optimal algorithm is used for carrying out region division on the base stations in the problem element set to obtain a problem set region.
The greedy algorithm is to always make the best choice when solving the problem. And searching for adjacent nodes at each step of the greedy optimal priority search, and calculating the Manhattan distance between the nodes and the end point, namely the heuristic method of the lowest cost. The greedy best first search is fast enough when there are few obstacles, but the best first search results in a suboptimal path.
As shown in FIG. 3, FIG. 3 shows Manhattan distance of an embodiment of the present inventionSchematic representation. The three paths a, b and c in fig. 3 all represent manhattan paths, the length of which is the manhattan distance value. In a plane, e.g. coordinate (x)i，yi) And the coordinate (x)j，yj) The manhattan distance of (a) can be calculated according to expression (1).
D(i，j)＝|xi-xj|+|yi-yj| (1)
Wherein D (i, j) represents the coordinate (x)i，yi) And the coordinate (x)j，yj) Manhattan distance of.
FIG. 4, as shown in FIG. 4, is a schematic diagram illustrating a greedy algorithm according to an embodiment of the invention. The algorithm is constantly looking for the minimum of the current heuristic (h), but this path is clearly not optimal.
As shown in fig. 5, fig. 5 is a diagram illustrating the result of the problem concentration area according to an embodiment of the present invention. For example, the problem base stations are divided into 7 concentration areas by a greedy algorithm.
In the embodiment of the invention, a greedy optimal priority routing algorithm is adopted, namely, a plurality of adjacent points behind each point are confirmed to be problem base stations, as an example, if the number of the problem base stations in the adjacent points is more than 5, the problem is recorded, and a problem concentrated area identification method is fully determined in a more flexible and reliable mode.
In another embodiment of the present invention, the areas in the problem set are classified based on characteristics of problems associated with base stations in the areas in the problem set. For example, the problem concentration area may be classified by the backend server. The classification results can be as shown in Table 1
TABLE 1
Figure BDA0001894865580000071
In one embodiment of the invention, the identified interference problem concentration area and the interference reason of analysis and positioning are sent to responsible personnel for processing, and the problem solving efficiency is improved.
By the method for identifying the problem concentration area, the system automatically generates the whole-network adjacency list based on the whole-network employee participation list and the Delaunay triangle rule. And determining problem base stations based on the whole network adjacency relation table, and finally performing area division on the determined problem base stations, so that the problem concentrated area can be identified more accurately.
The apparatus for problem concentrated area identification according to an embodiment of the present invention, which corresponds to the method for problem concentrated area identification, is described in detail below with reference to fig. 6.
Fig. 6 is a schematic structural diagram of an apparatus for identifying a problem concentration area according to an embodiment of the present invention.
As shown in fig. 6, the apparatus 600 for problem concentration area identification includes:
and the relation table module 610 is used for determining a whole-network adjacency relation table based on the whole-network engineering parameter table and the Delaunay triangle rule.
And the base station module 620 is configured to determine a problematic base station in the whole network adjacency list according to the communication parameters of the base stations in the whole network adjacency list.
And an element set module 630, configured to associate the problem base station with the problem features in the full-network employee list, so as to obtain a problem element set.
An area module 640, configured to obtain an area in the problem set based on the problem element set.
With the apparatus for identifying problem concentrated areas according to the above embodiment, the relationship table module 610 automatically generates the adjacency table of the whole network, so that the adjacency can be maintained without manual work, the efficiency of identification is improved, and the accuracy of area identification is also improved. Through the base station module 620, the threshold value of the problem parameter is set, the base station which needs to be subjected to area identification can be accurately positioned, and errors caused by manual division are effectively avoided, so that the accuracy of area identification is improved. By the element set module 630 and the area module 640, the problem set area can be identified more accurately.
In an embodiment of the present invention, the relation table module 610 is specifically configured to project the base stations having longitude information and latitude information in the full-web parameter table to a two-dimensional plane, so as to obtain a plurality of base stations having two-dimensional location points. And taking a plurality of base stations with two-dimensional position points as end points in a Delaunay triangular rule, and carrying out Delaunay triangulation and Dirichlet domain segmentation on the basis of the end points and the Delaunay triangular rule to obtain a whole network adjacency relation table.
In an embodiment of the present invention, the base station module 620 is specifically configured to determine a problem parameter in the communication parameters, and set a threshold of the problem parameter. And determining a judgment rule according to the problem parameter. Determining the problem base station in the whole network adjacency relation table based on the threshold value of the problem parameter, the actual value of the problem parameter and the judgment rule corresponding to the problem parameter, wherein the judgment rule comprises the following steps: and taking the base station with the actual value of the problem parameter larger than the threshold value of the problem parameter as the problem base station, or taking the base station with the actual value of the problem parameter smaller than or equal to the threshold value of the problem parameter as the problem base station.
In an embodiment of the present invention, the base station module 620 is further configured to determine the problematic base station according to a time series algorithm and communication parameters of the base stations in the whole network adjacency list.
In an embodiment of the present invention, the area module 640 is specifically configured to perform area division on the base stations in the problem element set by using a greedy optimization algorithm based on problem features associated with the base stations in the problem element set, so as to obtain a problem set area.
In one embodiment of the present invention, the apparatus 600 for problem concentration area identification further comprises:
a classification module 650 configured to classify the region in the problem set based on the problem features associated with the base stations in the region in the problem set.
FIG. 7 sets forth a block diagram of an exemplary hardware architecture of a computing device capable of implementing the method and apparatus for problem concentration area identification according to embodiments of the present invention.
As shown in fig. 7, computing device 700 includes an input device 701, an input interface 702, a central processor 703, a memory 704, an output interface 705, and an output device 706. The input interface 702, the central processing unit 703, the memory 704, and the output interface 705 are connected to each other via a bus 710, and the input device 701 and the output device 706 are connected to the bus 710 via the input interface 702 and the output interface 705, respectively, and further connected to other components of the computing device 700.
Specifically, the input device 701 receives input information from the outside, and transmits the input information to the central processor 703 through the input interface 702; the central processor 703 processes input information based on computer-executable instructions stored in the memory 704 to generate output information, stores the output information temporarily or permanently in the memory 704, and then transmits the output information to the output device 706 through the output interface 705; the output device 706 outputs output information external to the computing device 700 for use by a user.
That is, the computing device shown in fig. 7 may also be implemented with a problem concentration area identification device, which may include: a memory storing computer-executable instructions; and a processor which, when executing computer executable instructions, may implement the method and apparatus for problem concentration area identification described in connection with fig. 1-6.
An embodiment of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium has computer program instructions stored thereon; the computer program instructions, when executed by a processor, implement the method and apparatus for problem concentration area identification provided by embodiments of the present invention.
It is to be understood that the invention is not limited to the specific arrangements and instrumentality described above and shown in the drawings. A detailed description of known methods is omitted herein for the sake of brevity. In the above embodiments, several specific steps are described and shown as examples. However, the method processes of the present invention are not limited to the specific steps described and illustrated, and those skilled in the art can make various changes, modifications and additions or change the order between the steps after comprehending the spirit of the present invention. The functional blocks shown in the above-described structural block diagrams may be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, it may be, for example, an electronic circuit, an Application Specific Integrated Circuit (ASIC), suitable firmware, plug-in, function card, or the like. When implemented in software, the elements of the invention are the programs or code segments used to perform the required tasks. The program or code segments may be stored in a machine-readable medium or transmitted by a data signal carried in a carrier wave over a transmission medium or a communication link. A "machine-readable medium" may include any medium that can store or transfer information. Examples of a machine-readable medium include electronic circuits, semiconductor memory devices, ROM, flash memory, Erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, Radio Frequency (RF) links, and so forth. The code segments may be downloaded via computer networks such as the internet, intranet, etc.
The present invention may be embodied in other specific forms without departing from its spirit or essential characteristics. For example, the algorithms described in the specific embodiments may be modified without departing from the basic spirit of the invention. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.

Claims (10)

1. A method for problem concentration area identification, comprising:
determining a whole network adjacency relation table based on a whole network engineering parameter table and a Delaunay triangle rule;
determining a problem base station in the whole network adjacency list according to the communication parameters of the base stations in the whole network adjacency list;
associating the problem base station with the problem features in the whole network employee participation table to obtain a problem element set;
and obtaining a problem concentration area based on the problem element set.
2. The method for problem concentration area identification according to claim 1, wherein the determining a network-wide adjacency list based on the network-wide employee parameter list and the Delaunay triangle rule comprises:
projecting base stations with longitude information and latitude information in a full-network engineering parameter table to a two-dimensional plane to obtain a plurality of base stations with two-dimensional position points;
and taking the base stations with the two-dimensional position points as end points in the Delaunay triangle rule, and performing Delaunay triangulation and Dirichlet domain segmentation on the basis of the end points and the Delaunay triangle rule to obtain the whole network adjacency relation table.
3. The method for identifying the problem concentration area according to claim 1, wherein the determining the problem base station in the network-wide adjacency list according to the communication parameters of the base stations in the network-wide adjacency list comprises:
determining a problem parameter in the communication parameters, and setting a threshold value of the problem parameter;
determining a judgment rule according to the problem parameter;
determining the problem base station in the whole network adjacency relation table based on the threshold value of the problem parameter, the actual value of the problem parameter and the judgment rule, wherein the judgment rule comprises:
the base station with the actual value of the problem parameter larger than the threshold value of the problem parameter is taken as the problem base station, or
And taking the base station of which the actual value of the problem parameter is less than or equal to the threshold value of the problem parameter as the problem base station.
4. The method of claim 1, wherein determining the problem base station in the network-wide adjacency list according to the communication parameters of the base stations in the network-wide adjacency list comprises:
and determining the problem base station according to a time sequence algorithm and the communication parameters of the base stations in the whole network adjacency table.
5. The method for identifying the problem concentration area according to claim 1, wherein the obtaining the problem concentration area based on the problem element set comprises:
and based on the problem characteristics associated with the base stations in the problem element set, carrying out region division on the base stations in the problem element set by using a greedy optimal algorithm to obtain the problem set region.
6. The method of problem concentration area identification according to claim 1, further comprising:
and classifying the problem concentrated area based on the problem characteristics associated with the base station in the problem concentrated area.
7. The method of problem concentration area identification according to claim 1, wherein said full net work participation table comprises: location information of the base station, communication parameters of the base station, and problem characteristics of the base station.
8. An apparatus for problem concentration area identification, comprising:
the relation table module is used for determining a whole-network adjacency relation table based on a whole-network engineering parameter table and a Delaunay triangle rule;
the base station module is used for determining a problem base station in the whole network adjacency list according to the communication parameters of the base stations in the whole network adjacency list;
the element set module is used for correlating the problem base station with the problem features in the whole network employee participation table to obtain a problem element set;
and the region module is used for obtaining a problem concentrated region based on the problem element set.
9. An apparatus for problem concentration area identification, the apparatus comprising: a processor and a memory storing computer program instructions;
the processor, when executing the computer program instructions, implements a method of problem concentration area identification as recited in any of claims 1-7.
10. A computer storage medium having computer program instructions stored thereon which, when executed by a processor, implement a method of problem concentration area identification as claimed in any one of claims 1 to 7.
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