CN106879003B - network optimization quality evaluation method and device - Google Patents
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/02—Arrangements for optimising operational condition
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
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- H—ELECTRICITY
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Abstract
The invention discloses a method and a device for evaluating network optimization quality, which comprises the following steps: acquiring an index value corresponding to the network quality index of each cell in a target area; counting the number of cells corresponding to each index value, and taking the index value of the maximum value of the number of the cells corresponding to all the index values as the maximum number index value; determining a worst index value according to the maximum number index value and a threshold value, and determining the number of worst cells in the target region according to the worst index value, wherein the worst cells are cells of which the index values corresponding to the network quality indexes of the cells are smaller than the worst index value; and evaluating the network optimization quality of the target area according to the number of the worst cells.
Description
Technical Field
The invention relates to the technical field of mobile communication, in particular to a network optimization quality evaluation method and device.
background
generally, in the field of communication network optimization service, when evaluating the wireless network optimization quality of each regional branch company and third party optimization manufacturer, the quality of the network optimization quality is usually evaluated according to the quality of an index absolute value. This approach has the following limitations:
(1) The wireless main equipment used in each area is different, some factory equipment has better indexes, some factory equipment has worse indexes, and the difference of the wireless main equipment causes the index difference.
(2) each regional wireless main device is hung under the core network devices of different manufacturers through different transmission routes, and index difference is caused by the difference between a transmission network and the core network.
(3) The social development level of each region is different, the use habits of users are different, the geographic landforms are different, and the index difference is caused by the region difference.
(4) The construction progress of each regional network is different, the index is relatively good if the network coverage is good, the index is relatively poor if the network coverage is poor, and the index difference is caused by the network coverage difference.
in summary, the existing method for evaluating network optimization quality according to the absolute value of the index is greatly influenced by external factors such as equipment, area, coverage and the like, and cannot objectively and fairly reflect the actual network optimization quality.
Disclosure of Invention
The embodiment of the invention provides a network optimization quality evaluation method and a device thereof, which are used for objectively and fairly evaluating the actual network optimization quality.
the embodiment of the invention provides a network optimization quality evaluation method, which comprises the following steps:
acquiring an index value corresponding to the network quality index of each cell in a target area;
Counting the number of cells corresponding to each index value, and taking the index value of the maximum value of the number of the cells corresponding to all the index values as the maximum number index value;
determining a worst index value according to the maximum number index value and a threshold value, and determining the number of worst cells in the target region according to the worst index value, wherein the worst cells are cells of which the index values corresponding to the network quality indexes of the cells are smaller than the worst index value;
and evaluating the network optimization quality of the target area according to the number of the worst cells.
Optionally, the counting the number of cells corresponding to each index value, and taking the index value corresponding to the maximum value of the number of cells in all the index values as the maximum index value, includes:
Establishing a two-dimensional bar graph according to an index value corresponding to the network quality index of each cell, wherein each value in an abscissa of the two-dimensional bar graph represents the index value, and each value in an ordinate represents the number of cells with the same index value;
And determining a maximum number index value according to the two-dimensional column diagram, wherein the maximum number index value is an index value corresponding to the maximum value of the number of the cells with the same index value.
optionally, the determining a worst index value according to the maximum number index value and a threshold includes:
taking an index value which is smaller than the maximum number index value and has an absolute value of a difference value with the maximum number index value as the threshold value as the worst index value; or,
And taking the index value with the ratio to the maximum number index value equal to the threshold value as the worst index value.
Optionally, the evaluating the network optimization quality of the target area according to the number of the worst cells includes:
Determining a first ratio of the number of the worst cells to the number of all cells in the target area, and evaluating the network optimization quality of the target area according to the first ratio, wherein the smaller the first ratio, the better the network optimization quality of the target area.
Optionally, the evaluating the network optimization quality of the target area according to the number of the worst cells includes:
determining a first ratio of the number of the worst cells to the number of all cells in the target area and determining a second ratio of the number of weak coverage cells in the target area to the number of all cells in the target area;
And evaluating the network optimization quality of the target area according to the ratio of the first ratio to the second ratio, wherein the larger the ratio of the first ratio to the second ratio is, the better the network optimization quality of the target area is.
The embodiment of the invention provides a network optimization quality evaluation device, which comprises:
the acquisition unit is used for acquiring an index value corresponding to the network quality index of each cell in the target area;
The counting unit is used for counting the number of the cells corresponding to each index value and taking the index value of the maximum value of the number of the cells corresponding to all the index values as the maximum number index value;
A determining unit, configured to determine a worst index value according to the maximum number index value and a threshold, and determine the number of worst cells in the target region according to the worst index value, where the worst cell is a cell in which an index value corresponding to a network quality index of the cell is smaller than the worst index value;
and the evaluation unit is used for evaluating the network optimization quality of the target area according to the number of the worst cells.
Optionally, the statistical unit is specifically configured to:
Establishing a two-dimensional bar graph according to an index value corresponding to the network quality index of each cell, wherein each value in an abscissa of the two-dimensional bar graph represents the index value, and each value in an ordinate represents the number of cells with the same index value;
And determining a maximum number index value according to the two-dimensional column diagram, wherein the maximum number index value is an index value corresponding to the maximum value of the number of the cells with the same index value.
Optionally, the determining unit is specifically configured to:
taking an index value which is smaller than the maximum number index value and has an absolute value of a difference value with the maximum number index value as the threshold value as the worst index value; or,
And taking the index value with the ratio to the maximum number index value equal to the threshold value as the worst index value.
Optionally, the evaluation unit is specifically configured to:
Determining a first ratio of the number of the worst cells to the number of all cells in the target area, and evaluating the network optimization quality of the target area according to the first ratio, wherein the smaller the first ratio, the better the network optimization quality of the target area.
Optionally, the evaluation unit is specifically configured to:
Determining a first ratio of the number of the worst cells to the number of all cells in the target area and determining a second ratio of the number of weak coverage cells in the target area to the number of all cells in the target area;
And evaluating the network optimization quality of the target area according to the ratio of the first ratio to the second ratio, wherein the larger the ratio of the first ratio to the second ratio is, the better the network optimization quality of the target area is.
according to the method and the device provided by the embodiment of the invention, the index value corresponding to the network quality index of each cell in the target area is counted, the index value corresponding to the maximum cell number in the counting result is used as the maximum number index value, and then the worst index value is determined according to the maximum number index value and the threshold value, so that the cell with the index value corresponding to the network quality index of the cell in the target area smaller than the worst index value can be determined according to the worst index value, and the network optimization quality of the target area can be evaluated according to the number of the worst cells in the target area. In the embodiment of the invention, the network optimization quality is not evaluated according to external factors such as equipment, areas and coverage, but a method based on class normal distribution is used for determining the worst index value according to the maximum number index value and the threshold value from the statistical result, so that the influence of the external factors such as the equipment, the areas and the coverage is eliminated, the method is used for evaluating the wireless network optimization quality of units such as regional branch companies and three-party optimization manufacturers, and the objective fairness of evaluation is improved.
Drawings
in order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is a schematic flow chart of a network optimization quality evaluation method according to an embodiment of the present invention;
FIG. 2 is a two-dimensional bar graph provided in accordance with an embodiment of the present invention;
FIG. 3 is a two-dimensional bar graph provided by an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a network optimization quality evaluation apparatus according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the present invention will be described in further detail with reference to the accompanying drawings, and it is apparent that the described embodiments are only a part of the embodiments of the present invention, not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
the embodiment of the invention can be applied to systems such as LTE (Long Term Evolution), GSM (Global System for Mobile Communications), WCDMA (Wideband code division Multiple Access) and the like.
The device executing the embodiment of the present invention may be a personal computer, a server, a standard ATCA (Advanced telecommunications Computing Architecture) blade server, or dedicated hardware, and the like, and the embodiment of the present invention is not limited thereto.
based on the above description, as shown in fig. 1, a schematic flow chart of a network optimization quality evaluation method provided by the embodiment of the present invention is shown.
referring to fig. 1, the method includes:
step 101: acquiring an index value corresponding to the network quality index of each cell in a target area;
Step 102: counting the number of cells corresponding to each index value, and taking the index value of the maximum value of the number of the cells corresponding to all the index values as the maximum number index value;
Step 103: determining a worst index value according to the maximum number index value and a threshold value, and determining the number of worst cells in the target region according to the worst index value, wherein the worst cells are cells of which the index values corresponding to the network quality indexes of the cells are smaller than the worst index value;
step 104: and evaluating the network optimization quality of the target area according to the number of the worst cells.
in step 101, the network quality indicator may refer to any network quality indicator used for evaluating network quality. For example, the network quality indicator is any one of the following:
The call completing rate; SINR (Signal to Interference plus Noise Ratio); RSRP (Reference Signal Received Power); an uplink and downlink rate; a Radio Resource Control (RRC) connection establishment success rate; a cell handover success rate; and the paging success rate.
Of course, the above is only a part of the network quality indicators, and may also be other types of network quality indicators, which is not limited in the embodiment of the present invention.
In step 102, the obtained index values corresponding to the network quality index of each cell are counted, and specifically, a two-dimensional histogram may be established according to the index values corresponding to the network quality index of each cell, so that the distribution state of the index value corresponding to each cell in the target area may be determined according to the established two-dimensional histogram.
it should be noted that, in the embodiment of the present invention, each value in the abscissa of the established two-dimensional bar chart represents an index value, and each value in the ordinate represents the number of cells having the same index value.
For example, as shown in fig. 2, a two-dimensional bar chart is provided according to an embodiment of the present invention. In fig. 2, each value in the abscissa represents a call completing rate, and each value in the ordinate represents the number of cells having the same call completing rate.
According to the established two-dimensional bar graph, the index value corresponding to the maximum value of the number of the cells with the same index value can be determined.
of course, the maximum number index value may also be determined by other methods, which is not limited in the embodiment of the present invention.
in step 103, after the maximum quantity index value is determined, the worst index value may be determined according to the maximum quantity index value and the threshold.
in the embodiment of the present invention, the threshold may be determined according to an actual situation, and the thresholds corresponding to different network quality indicators are also different, which is not described herein again. However, it should be noted that the threshold is smaller than the maximum number index value; or the threshold is greater than 0 and less than 1.
In the embodiment of the present invention, the worst index value may be determined in a plurality of ways, and one possible way to determine the worst index value is to use an index value that is smaller than the maximum number index value and whose absolute value of the difference from the maximum number index value is a threshold value as the worst index value, and at this time, may use the maximum number index value and a value after the threshold value is removed as the worst index value. For example, if the maximum quantity index value is A and the threshold value is σ, the worst index value is A- σ. Note that, in this case, the threshold value needs to be smaller than the maximum number index value.
For example, referring to fig. 2, as shown in fig. 3, a two-dimensional bar chart is provided according to an embodiment of the present invention. In fig. 3, each value in the abscissa represents a call completing rate, and each value in the ordinate represents the number of cells having the same call completing rate. The index value corresponding to the M point coordinates is the maximum number index value A, and the threshold value is sigma. And the index value corresponding to the S point coordinate is A-sigma. So that the cells with index values lower than a-sigma are all the worst cells.
in an embodiment of the present invention, another possible implementation manner of determining the worst index value is to use an index value whose ratio to the maximum number index value is equal to the threshold as the worst index value, and at this time, a product of the maximum number index value and the threshold may be determined as the worst index value. Note that, in this case, the threshold is greater than 0 and less than 1.
After the worst index value is determined, a cell with an index value of the network quality index smaller than the worst index value among all cells in the target area may be used as the worst cell, so that in step 104, the network optimization quality of the target area may be evaluated according to the number of the worst cells.
specifically, in step 104, determining the number of worst cells in the target area, then using a ratio of the number of the worst cells to the number of all cells in the target area as a first ratio, and evaluating the network optimization quality of the target area according to the first ratio, wherein the smaller the first ratio, the better the network optimization quality of the target area; the larger the first ratio is, the worse the network optimization quality of the target area is.
Further, in the embodiment of the present invention, the network optimization quality of the target area may also be evaluated according to the number of weak coverage cells in the target area. The number of the weak coverage cells may be determined according to methods such as a network measurement report of the target area, which is not limited in the embodiment of the present invention.
Specifically, a first ratio of the number of the worst cells to the number of all cells in the target area is determined, and then a second ratio of the number of the weak coverage cells in the target area to the number of all cells in the target area is determined; finally, evaluating the network optimization quality of the target area according to the ratio of the first ratio to the second ratio, wherein the larger the ratio of the first ratio to the second ratio is, the better the network optimization quality of the target area is; the smaller the ratio of the first ratio to the second ratio is, the worse the network optimization quality of the target area is.
based on the same technical concept, the embodiment of the invention also provides a network optimization quality evaluation device which can execute the method embodiment.
as shown in fig. 4, a network optimization quality evaluation apparatus is provided for an embodiment of the present invention, and the apparatus includes:
an obtaining unit 401, configured to obtain an index value corresponding to a network quality index of each cell in a target area;
a counting unit 402, configured to count the number of cells corresponding to each index value, and use an index value with a maximum value of the number of cells corresponding to all index values as a maximum number index value;
A determining unit 403, configured to determine a worst index value according to the maximum number index value and a threshold, and determine the number of worst cells in the target area according to the worst index value, where the worst cell is a cell whose index value corresponding to the network quality index of the cell is smaller than the worst index value;
An evaluating unit 404, configured to evaluate the network optimization quality of the target area according to the number of the worst cells.
optionally, the statistical unit 402 is specifically configured to:
Establishing a two-dimensional bar graph according to an index value corresponding to the network quality index of each cell, wherein each value in an abscissa of the two-dimensional bar graph represents the index value, and each value in an ordinate represents the number of cells with the same index value;
And determining a maximum number index value according to the two-dimensional column diagram, wherein the maximum number index value is an index value corresponding to the maximum value of the number of the cells with the same index value.
optionally, the determining unit 403 is specifically configured to:
taking an index value which is smaller than the maximum number index value and has an absolute value of a difference value with the maximum number index value as the threshold value as the worst index value; or,
And taking the index value with the ratio to the maximum number index value equal to the threshold value as the worst index value.
optionally, the evaluation unit 404 is specifically configured to:
Determining a first ratio of the number of the worst cells to the number of all cells in the target area, and evaluating the network optimization quality of the target area according to the first ratio, wherein the smaller the first ratio, the better the network optimization quality of the target area.
optionally, the evaluation unit 404 is specifically configured to:
Determining a first ratio of the number of the worst cells to the number of all cells in the target area and determining a second ratio of the number of weak coverage cells in the target area to the number of all cells in the target area;
And evaluating the network optimization quality of the target area according to the ratio of the first ratio to the second ratio, wherein the larger the ratio of the first ratio to the second ratio is, the better the network optimization quality of the target area is.
in summary, according to the method and the apparatus provided by the embodiments of the present invention, by performing statistics on the obtained index values corresponding to the network quality indexes of each cell in the target area, the index value corresponding to the maximum value of the number of cells in the statistical result is used as the maximum number index value, and then the worst index value is determined according to the maximum number index value and the threshold, so that the cell with the index value corresponding to the network quality index of the cell in the target area smaller than the worst index value can be determined according to the worst index value, and the network optimization quality of the target area can be evaluated according to the number of the worst cells in the target area. In the embodiment of the invention, the network optimization quality is not evaluated according to external factors such as equipment, areas and coverage, but a method based on class normal distribution is used for determining the worst index value according to the maximum number index value and the threshold value from the statistical result, so that the influence of the external factors such as the equipment, the areas and the coverage is eliminated, the method is used for evaluating the wireless network optimization quality of units such as regional branch companies and three-party optimization manufacturers, and the objective fairness of evaluation is improved.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the scope of the invention. Thus, it is intended that the present invention cover the modifications and variations of this invention provided they come within the scope of the appended claims.
Claims (8)
1. A network optimization quality evaluation method is characterized by comprising the following steps:
Acquiring an index value corresponding to the network quality index of each cell in a target area;
counting the number of cells corresponding to each index value, and taking the index value of the maximum value of the number of the cells corresponding to all the index values as the maximum number index value;
taking an index value which is smaller than the maximum number index value and has a first threshold value as a worst index value; the first threshold value is less than the maximum quantity index value; or, the index value with the ratio to the maximum number index value equal to a second threshold value is taken as the worst index value; the second threshold is greater than 0 and less than 1;
Determining the number of worst cells in the target area according to the worst index value, wherein the worst cells are cells of which the index values corresponding to the network quality indexes of the cells are smaller than the worst index value;
and evaluating the network optimization quality of the target area according to the number of the worst cells.
2. The method of claim 1, wherein the counting the number of cells corresponding to each index value and taking the index value with the maximum value of the number of cells corresponding to all the index values as the maximum value index value comprises:
Establishing a two-dimensional bar graph according to an index value corresponding to the network quality index of each cell, wherein each value in an abscissa of the two-dimensional bar graph represents the index value, and each value in an ordinate represents the number of cells with the same index value;
and determining a maximum number index value according to the two-dimensional column diagram, wherein the maximum number index value is an index value corresponding to the maximum value of the number of the cells with the same index value.
3. the method of claim 1, wherein the evaluating the quality of network optimization for the target area based on the number of worst cells comprises:
Determining a first ratio of the number of the worst cells to the number of all cells in the target area, and evaluating the network optimization quality of the target area according to the first ratio, wherein the smaller the first ratio, the better the network optimization quality of the target area.
4. the method of claim 1, wherein the evaluating the quality of network optimization for the target area based on the number of worst cells comprises:
Determining a first ratio of the number of the worst cells to the number of all cells in the target area and determining a second ratio of the number of weak coverage cells in the target area to the number of all cells in the target area;
and evaluating the network optimization quality of the target area according to the ratio of the first ratio to the second ratio, wherein the larger the ratio of the first ratio to the second ratio is, the better the network optimization quality of the target area is.
5. A network optimization quality assessment apparatus, comprising:
the acquisition unit is used for acquiring an index value corresponding to the network quality index of each cell in the target area;
the counting unit is used for counting the number of the cells corresponding to each index value and taking the index value of the maximum value of the number of the cells corresponding to all the index values as the maximum number index value;
a determination unit configured to determine, as a worst index value, an index value that is smaller than the maximum number index value and whose absolute value of a difference from the maximum number index value is a first threshold value; the first threshold value is less than the maximum quantity index value; or, the index value with the ratio to the maximum number index value equal to a second threshold value is taken as the worst index value; the second threshold is greater than 0 and less than 1;
Determining the number of worst cells in the target area according to the worst index value, wherein the worst cells are cells of which the index values corresponding to the network quality indexes of the cells are smaller than the worst index value;
And the evaluation unit is used for evaluating the network optimization quality of the target area according to the number of the worst cells.
6. the apparatus of claim 5, wherein the statistics unit is specifically configured to:
Establishing a two-dimensional bar graph according to an index value corresponding to the network quality index of each cell, wherein each value in an abscissa of the two-dimensional bar graph represents the index value, and each value in an ordinate represents the number of cells with the same index value;
And determining a maximum number index value according to the two-dimensional column diagram, wherein the maximum number index value is an index value corresponding to the maximum value of the number of the cells with the same index value.
7. the apparatus of claim 5, wherein the evaluation unit is specifically configured to:
determining a first ratio of the number of the worst cells to the number of all cells in the target area, and evaluating the network optimization quality of the target area according to the first ratio, wherein the smaller the first ratio, the better the network optimization quality of the target area.
8. The apparatus of claim 5, wherein the evaluation unit is specifically configured to:
determining a first ratio of the number of the worst cells to the number of all cells in the target area and determining a second ratio of the number of weak coverage cells in the target area to the number of all cells in the target area;
and evaluating the network optimization quality of the target area according to the ratio of the first ratio to the second ratio, wherein the larger the ratio of the first ratio to the second ratio is, the better the network optimization quality of the target area is.
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| CN103179625A (en) * | 2011-12-20 | 2013-06-26 | 华为技术有限公司 | Cell optimization method, device in mobile communication system and system |
| CN102905291A (en) * | 2012-09-06 | 2013-01-30 | 大唐移动通信设备有限公司 | Method for prompting network optimization and network optimization server |
| CN103596214A (en) * | 2013-11-28 | 2014-02-19 | 中国联合网络通信集团有限公司 | Method and device for analyzing data |
| CN103619034A (en) * | 2013-12-06 | 2014-03-05 | 中国联合网络通信集团有限公司 | Method and device for evaluating structural rationality of WCDMA wireless network |
| CN104853379A (en) * | 2014-02-18 | 2015-08-19 | 中国移动通信集团公司 | Wireless network quality assessment method and device |
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