CN103634807B - WIFI data hotspot cell data monitoring method and WLAN deployment ordering method and device - Google Patents
WIFI data hotspot cell data monitoring method and WLAN deployment ordering method and device Download PDFInfo
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Abstract
The invention discloses a WIFI data hotspot cell data monitoring method and a WLAN deployment ordering method and device. The WLAN deployment ordering method comprises obtaining network telephone traffic statistical data of a WLAN cell to be deployed and calculating and obtaining data hotspot cell data; obtaining PS signaling monitoring data of the WLAN cell to be deployed and calculating and obtaining WIFI data hotspot cell data; and grating the priority of the WIFI data hotspot cell data and obtaining the deployment priority sequence of the WIFI data hotspot cell. With the WIFI data hotspot cell data monitoring method and the WLAN deployment ordering method and device, the WIFI data hotspot cell can be accurately positioned, and thus the problem of rich configuration poor consumption of a WLAN network is greatly reduced.
Description
Technical Field
The invention relates to the technical field of mobile communication, in particular to a WIFI data hotspot cell data monitoring method, a WLAN deployment ordering method and a device.
Background
With the continuous increase of the voice service and the explosive increase of the data service of the GSM network of the mobile communication network, the wireless utilization rate has reached 70%, the GSM service dense area faces the bottleneck of point selection and the bottleneck of frequency resources, the TD network cannot effectively share the GSM traffic, and in order to effectively deal with the bottleneck problem encountered in the GSM network development, the data service which is explosively increased needs to be shared urgently, and the cooperative development among networks is promoted.
The WLAN hotspots can effectively absorb data services, but the current WLAN network deployment hotspot selection mode mainly determines multiple WLAN network deployment scenes according to site functions and service applications and determines the deployment priority of the WLAN network according to the importance of the sites to perform site deployment, so that the deployment cannot accurately analyze the WLAN service requirements of clients, the actual application requirements of the clients cannot be fully considered, analysis on WIFI support capability of client terminals and analysis on the requirements of client data services are lacked, the WLAN network deployment accuracy is about 80%, and the problem of hot-loading and cold-cooling in part of deployment areas occurs, thereby causing resource waste.
In addition, the priority level of the hotspot construction is simply divided according to the importance of the scene, and the WLAN hotspots are divided into four types according to the use frequency under the normal condition: the method is characterized in that A is colleges and universities, B comprises public areas such as airports, railway stations, bus stations, subway stations and large-scale exhibition centers, C comprises semi-closed places such as hotels, shopping malls, chain tea houses/coffee houses, hospitals, small and medium-sized enterprise gathering places, working parks, residential districts, business office buildings and villages and towns, and D is a group client with definite WLAN service requirements.
How to find a proper area to deploy the WLAN effectively absorbs data services of a hotspot area, and the problems of hot-loading and cold-use caused by inaccurate positioning of WIFI data hotspots and inaccurate priority of establishing the WIFI data hotspot area are difficult problems of planning and establishing the WLAN.
Disclosure of Invention
In order to solve the technical problem of hot-charging and cold-cooling caused by inaccurate positioning of WIFI data hotspots in the prior art, the invention provides a WIFI data hotspot cell data monitoring method and device and a WLAN deployment method and device, which can accurately position the WIFI data hotspot cell and remarkably reduce the problem of hot-charging and cold-cooling of a WLAN network.
One aspect of the present invention provides a WIFI data hotspot cell data monitoring method, which includes the following steps:
obtaining network telephone traffic statistical data of a WLAN cell to be deployed, and calculating to obtain data hotspot cell data; and obtaining PS signaling monitoring data of the WLAN cell to be deployed, and calculating to obtain WIFI data hotspot cell data.
By adopting the method, the WIFI data service hotspot cell can be accurately positioned.
In another aspect of the present invention, a WLAN deployment sequencing method is further provided, including the following steps:
obtaining network telephone traffic statistical data of a WLAN cell to be deployed, and calculating to obtain data hotspot cell data; obtaining PS signaling monitoring data of the WLAN cell to be deployed, and calculating to obtain WIFI data hotspot cell data; and carrying out priority grading on the WIFI data hotspot cell data to obtain a deployment priority sequence of the WIFI data hotspot cell.
By using the method, on the basis of accurately positioning the WIFI data service hotspot cell, the deployment priority sequence is obtained by grading the priority of the WIFI data service hotspot cell, so that the accuracy of WLAN network deployment can be obviously improved, the network resource utilization rate is improved, the data pressure of a GSM/TD network is shunted by the WLAN, and the problem of WLAN hot-loading and cold-using is avoided.
The invention also provides a device for realizing the method.
The utility model provides a WIFI data hotspot district data monitoring devices, includes data hotspot district acquisition module and WIFI data hotspot district acquisition module, wherein:
the data hotspot cell acquisition module is used for acquiring network telephone traffic statistical data of the WLAN cell to be deployed and calculating to acquire data of the data hotspot cell; and the WIFI data hotspot cell acquisition module is used for acquiring PS signaling monitoring data of the WLAN cell to be deployed and calculating to acquire WIFI data hotspot cell data.
A WLAN deployment sequencing device comprises a data hotspot cell acquisition module, a WIFI data hotspot cell acquisition module and a deployment priority sequencing module, wherein:
the data hotspot cell acquisition module is used for acquiring network telephone traffic statistical data of the WLAN cell to be deployed and calculating to acquire data of the data hotspot cell;
the WIFI data hotspot cell acquisition module is used for acquiring PS signaling monitoring data of the WLAN cell to be deployed and calculating to acquire WIFI data hotspot cell data;
the deployment priority ordering module is used for carrying out priority grading on the WIFI data hotspot cell data to obtain a deployment priority sequence of the WIFI data hotspot cell.
According to the WIFI data hotspot cell data monitoring method and device, data service hotspot cells are found by analyzing data services in the cells through a network management system, and the data such as the WIFI support capability of the data service hotspot cell terminals, the flow generated by the terminals, the number of the WIFI terminals are supported and the like are comprehensively analyzed by applying a PS signaling monitoring system, so that the accuracy of WLAN network deployment can be remarkably improved, and the WLAN hot-load and cold-use problem is reduced.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
Fig. 1 is a flowchart of a WIFI data hotspot cell data monitoring method in an embodiment of the present invention;
fig. 2 is a flowchart illustrating processing of network traffic statistics in a WIFI data hotspot cell data monitoring method in an embodiment of the present invention;
fig. 3 is a flowchart illustrating processing of PS signaling monitoring data in a WIFI data hotspot cell data monitoring method in an embodiment of the present invention;
fig. 4 is a flow chart of high-traffic WIFI terminal signaling analysis in the WIFI data hotspot cell data monitoring method of the present invention;
FIG. 5 is a flow chart of a WLAN deployment ordering method in an embodiment of the present invention;
fig. 6 is a schematic structural diagram of a WIFI data hotspot cell data monitoring device in an embodiment of the present invention;
fig. 7 is a schematic structural diagram of a WLAN deployment sequencing apparatus in an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
As shown in fig. 1, a specific embodiment of a WIFI data hotspot cell data monitoring method according to the present invention includes:
step 101, obtaining network telephone traffic statistical data of a WLAN cell to be deployed, and calculating to obtain data of a data hotspot cell;
and 102, obtaining PS signaling monitoring data of the WLAN cell to be deployed, and calculating to obtain WIFI data hotspot cell data.
As shown in fig. 2, in order to locate a data hotspot cell, a network manager (TD/GSM/WLAN) is mainly used to analyze data service in the cell, and the data of the data hotspot cell is obtained through the following steps:
step 201, extracting network traffic data of each to-be-deployed WLAN cell;
the selection principle of the WLAN cell to be deployed is that after a network construction engineering parameter table is obtained and network management telephone traffic statistical data of the latest month are analyzed, points with more than 27 concurrent users of a single AP are listed as a type of WLAN hot spot, and the WLAN hot spot is preferentially brought into expansion deployment; points with the WLAN bandwidth utilization rate of more than 70% are classified as WLAN hotspots, and are preferentially brought into capacity expansion deployment.
And taking the two types of cells as the cells to be deployed with the WLAN, and extracting network traffic data of the cells. In order to avoid the influence of a large data flow event generated by a user in an abrupt manner on the data analysis accuracy, the invention preferably can extract statistical data of 18 time periods (0 point-2 points and 8 points-24 points) and a total of 540 time periods of all cells of the whole network for 30 days continuously.
Step 202, performing mean calculation on the network traffic data, arranging according to the data traffic of the cells, and taking the cells with the data traffic higher than the average traffic of each cell as high-traffic cells.
Step 203, comparing the data flow of each cell in the preset time period with the average data flow of the cell in the continuous time period, and calculating the probability that the data flow of the cell occurring every day is greater than the average data flow, so as to obtain the non-accidental data hotspot cell data.
In order to avoid the cells with sporadic high data flow rate being counted, data needs to be screened, and sporadic data hot spot cells are eliminated. Specifically, the 18-time period data traffic of each cell may be compared with the average data traffic of the cell in 540 consecutive time periods, the probability that the data traffic of the cell occurring every day is greater than the average data traffic of 540 time periods is calculated, and the non-sporadic data hotspot cells of days, weeks, and months are further determined. Daily non-sporadic data hotspots: there are more than 6 periods of data traffic greater than the mean traffic of 540 periods (probability of occurrence greater than 1/3) of cells per day. Weekly non-sporadic data hotspots: and the traffic statistical data for 7 continuous days has cells which are not sporadic data hotspots for more than 3 days. Monthly non-sporadic data hotspots: and the traffic statistical data has more than 2 weeks of cells which are not sporadic data hot spots in 30 consecutive days.
The selection criteria in the above time period may be changed according to the specific situation of the network usage, and is not limited to the selection criteria given in this specific embodiment.
And carrying out PS signaling monitoring analysis on the located data service hotspot region result, counting information of all terminal types, affiliated cells, terminal data flow, total cell data flow and the like under the data hotspot cell, matching the counted terminal types with a WIFI terminal database, and finding out data such as the number of WIFI terminals, the WIFI terminal occupation ratio and high-flow WIFI terminals and the like distributed under each data service hotspot cell.
As shown in fig. 3, monitoring data through PS signaling comprises the following steps:
step 301, acquiring PS signaling monitoring data of all terminal users in a preset time period in the data hotspot cell;
and extracting PS signaling monitoring data of all terminal users in the data hotspot cell in 24 time periods every day. In order to avoid the influence of the large data flow events generated by the user in an abrupt manner on the data analysis accuracy, it is preferable to extract the statistical data of 168 time intervals in a continuous week.
Step 302, carrying out terminal information data duplication elimination processing on the PS signaling monitoring data to obtain user terminal information;
data statistics of 168 time periods of all user terminals in a data service hotspot cell are obtained through PS signaling monitoring data, but because one terminal has the problem of multiple repeated data, repeated user terminal information is removed, and finally information such as the type of the user terminal, the cell to which the user terminal belongs, terminal data flow, total cell data flow and the like is reserved, so that the next analysis and processing are facilitated.
Step 303, obtaining a WIFI terminal existing in a data hotspot cell according to the matching of the user terminal information and a WIFI terminal database;
step 304, calculating the distribution quantity and the terminal proportion of the WIFI terminals in the data hotspot cell;
and through the combination and analysis of the existing PS signaling monitoring data and the WIFI terminal information, the distribution quantity and the terminal proportion of the WIFI terminals under each data service hotspot cell are found, the distribution quantity of the WIFI terminals in the cells is sequenced, and the data hotspot cells with large distribution quantity of the WIFI terminals are screened out.
305, sequencing the distribution quantity of WIFI terminals of each cell, and screening out a data hotspot cell with the distribution quantity of the WIFI terminals larger than a preset value as a first WIFI data hotspot cell;
through 7 days multiplied by 24 hours per day signaling monitoring statistical data analysis, the hour data traffic of each WIFI terminal is subjected to average processing and then sequenced, and the WIFI terminal which carries 50% of the total WIFI data traffic of each cell according to descending sequence is defined as a high-traffic WIFI terminal under a data hotspot cell.
After the data processing, the WIFI terminals with large quantity distribution and high proportion of data hotspot cells and high flow can be obtained. And determining the data hotspot cells with large quantity distribution and high proportion of WIFI terminals as the first WIFI data hotspot cell deployed by the WLAN station.
According to the obtained high-data-flow WIFI terminal user, on one hand, PS signaling monitoring analysis is carried out on the high-data-flow WIFI terminal, and a data hotspot cell concentrated by the high-data-flow WIFI terminal is found (the high-data-flow WIFI terminal occupies a large proportion); and on the other hand, CS signaling monitoring analysis is carried out on the high-data-flow WIFI terminal, and a potential hotspot region (the flow direction of the high-flow WIFI terminal) of the data service is found.
As shown in fig. 4, the analysis process for monitoring the signaling of the high-traffic WIFI terminal includes:
step 401, acquiring PS signaling monitoring data of the high-traffic WIFI terminal in preset time periods of a PS domain and a CS domain;
and counting signaling monitoring data of 24 time periods each day of the WIFI terminal in the PS domain and the CS domain. In order to avoid the influence of the large data flow events generated by the user in an abrupt manner on the data analysis accuracy, preferably, the statistical data of a total of 168 time periods of 24 time periods per day can be extracted continuously for one week.
Step 402, performing mean value calculation on PS signaling monitoring data generated in a PS domain to obtain data traffic of each WIFI terminal generated in a relevant cell, and sequencing to obtain a hotspot cell with high data traffic generated by a WIFI terminal user as a second WIFI data hotspot cell;
step 403, performing mean value calculation on the PS signaling monitoring data generated in the CS domain to obtain a potential data hotspot cell generated by the high-traffic WIFI terminal user flowing, and screening the data hotspot cell to obtain a potential data hotspot cell generated by the high-traffic WIFI terminal user flowing in the network as a third WIFI data hotspot cell.
The extracted CS signaling data in 168 time periods are subjected to average processing, the influence of sudden voice large-traffic demand events in a small number of time periods on the accuracy of the analysis data result is eliminated, potential data hotspot cells generated by the flow of high-flow WIFI terminal users are found, and the accuracy of the data analysis result is improved.
And screening potential data hotspot cells generated by the WIFI terminal user. After average processing is carried out on the WIFI terminal with high data traffic, the voice telephone traffic generated by each user in the relevant cell is counted and sequenced, and a potential data hotspot cell generated by the flow of the high-traffic WIFI terminal users in the network is found and used as a third WIFI data hotspot cell.
As shown in fig. 5, an embodiment of the present invention further provides a method for ordering WLAN deployment, including the following steps:
501, obtaining network telephone traffic statistical data of a WLAN cell to be deployed, and calculating to obtain data of a data hotspot cell;
step 502, obtaining PS signaling monitoring data of the WLAN cell to be deployed, and calculating to obtain WIFI data hotspot cell data;
and 503, performing priority grading on the WIFI data hotspot cell data to obtain a deployment priority sequence of the WIFI data hotspot cell.
After the data processing in steps 501 and 502, three WIFI data hotspot cells are obtained, and in order to better perform WLAN site deployment, the priorities of the three WIFI data hotspot cells are ranked and ranked in step 503, so as to obtain a deployment priority sequence of the WIFI data hotspot cells.
Specifically, a community WIFI demand heat degree model is established according to PS signaling monitoring data of the current network and telephone traffic statistical data, and then PS signaling data of a WIFI hotspot community are input into the model to be scored. The software system automatically outputs the construction priority score, and the higher the score is, the higher the construction urgency is, so as to guide the accurate WLAN network planning and construction.
The cell WIFI demand heat degree model adopts an empirical formula to perform cubic processing on each index, the higher the score of a cell with a high occupancy ratio is, the lower the score of the cell with a low occupancy ratio is, the more the score of the cell with a low occupancy ratio is, the cell WIFI demand heat degree is fully distinguished, and meanwhile, the weight of the data traffic contribution ratio of the high-traffic WIFI terminal is strengthened by the algorithm and is higher than the weight score of the data traffic contribution ratio of the high-traffic WIFI terminal with a constant occupancy ratio value.
The heat model formula is as follows:
wherein,representing the data traffic contribution proportion of the high-traffic WIFI terminal;
representing the quantity proportion of the high-flow WIFI terminals;
representing the quantity proportion of the WIFI terminals;
representing the voice call duration proportion of the high-flow WIFI terminal;
CEILING (10 Mi/Max (M1.., Mn))/10 represents the number of stages of the step function, namely, the maximum value is 1, other values are distributed from 0 to 0.1 and 0.2.. to 1, and the total number of the short messages received and sent by the high-traffic WIFI terminal is divided into 11 equal parts and weighted by the step function;
w1, W2, W3 and W4 are weight coefficients, the priority W1 is the highest, W2 times is W3 and W4, and the four coefficients are obtained through modeling analysis of a large amount of local network data.
And calculating through a demand heat model to obtain WIFI demand heat scores of all the cells, and sequencing the scores to obtain priority data of the cells constructing the WIFI data hotspots.
The model can be based on various platforms including JAVA, and can effectively solve the problem that algorithm weight factors of different users and network scale areas are different through a graphical operation interface and a dynamic adjustment function of the algorithm weight factors aiming at GSM/TD network data. The model software realizes automatic mass data operation by reading the PS signaling database, automatically outputs the heat degree score of the WIFI data hotspot cell, and finally sorts the score result to obtain the deployment scheme of the WLAN.
According to the method for deploying the WLAN, the WLAN network is accurately deployed by adopting the outstanding technical means of speech integration, PS signaling positioning data hotspot, terminal capability analysis, cell WIFI demand heat modeling, hotspot establishment priority establishment established by applying model scoring and the like, the accuracy of the WLAN network deployment can reach 99%, and is improved by about 20% compared with the accuracy of the original deployment method. The hot-charging and cold-using phenomenon of WLAN network deployment is obviously reduced, the utilization rate of equipment resources is improved, and the investment is saved.
By mining PS signaling monitoring data and network management statistical data, a WIFI terminal concentrated area is accurately positioned, and meanwhile, the user flow direction is determined by analyzing CS signaling, so that a high-flow WIFI terminal concentrated area and a common data service hotspot area (potential data service area) are judged, the effectiveness of WLAN deployment is ensured, T/G data flow can be effectively shunted, and the cooperative development among networks is promoted.
The scoring of the hot spot area is realized by establishing a mathematical model, the irrationality of artificially and subjectively setting the hot spot area to establish the priority in the current WLAN deployment method is avoided, meanwhile, the scoring is automatically calculated for the hot spot data through model software, and the manpower is saved. The method is adopted to deploy the WLAN network, and the scientificity and the normativity of WLAN network deployment are improved.
The embodiment of the present invention further provides a device for implementing a WIFI data hotspot cell data monitoring method, as shown in fig. 6, the device includes a data hotspot cell acquisition module 601 and a WIFI data hotspot cell acquisition module 602, where:
the data hotspot cell acquiring module 601 is configured to acquire network traffic statistical data of a WLAN cell to be deployed, and calculate to acquire data of the data hotspot cell;
the WIFI data hotspot cell acquiring module 602 is configured to acquire PS signaling monitoring data of the WLAN cell to be deployed, and calculate to acquire WIFI data hotspot cell data.
The data hotspot cell acquisition module 601 is further configured to:
extracting network traffic data of each WLAN cell to be deployed;
carrying out average calculation on the network telephone traffic data, arranging according to cell data flow, and taking a cell with the data flow higher than the average flow of each cell as a high-flow cell;
and comparing the data flow of each cell in a preset time period with the average data flow of the cell in a continuous time period, and calculating the probability that the data flow of the cell appearing every day is greater than the average data flow to obtain the non-accidental data hotspot cell data.
The WIFI data hotspot cell acquisition module 602 is further configured to:
acquiring PS signaling monitoring data of all terminal users in a preset time period under the data hotspot cell;
carrying out terminal information data duplication elimination processing on the PS signaling monitoring data to obtain user terminal information;
matching the user terminal information with a WIFI terminal database to obtain a WIFI terminal existing under a data hotspot cell;
calculating the distribution quantity and the terminal proportion of the WIFI terminals in the data hotspot cell;
sequencing the distribution quantity of WIFI terminals in each cell, and screening out data hotspot cells with the distribution quantity of the WIFI terminals larger than a preset value as first WIFI data hotspot cells;
carrying out mean value calculation on data flow of each WIFI terminal in a preset time period, then sequencing, and defining the WIFI terminal which bears 50% of total WIFI data flow of each cell after descending the sequence as a high-flow WIFI terminal under a data hotspot cell;
acquiring PS signaling monitoring data of the high-traffic WIFI terminal in preset time periods of a PS domain and a CS domain;
performing mean value calculation on PS signaling monitoring data generated by a PS domain to obtain the data traffic of each WIFI terminal generated in a relevant cell, and sequencing to obtain a hotspot cell with high data traffic generated by a WIFI terminal user as a second WIFI data hotspot cell;
and carrying out mean value calculation on PS signaling monitoring data generated by the CS domain to obtain a potential data hotspot cell generated by the flow of the high-flow WIFI terminal user, screening the data hotspot cell to obtain a potential data hotspot cell generated by the flow of the high-flow WIFI terminal user in the network as a third WIFI data hotspot cell.
As shown in fig. 7, in order to implement accurate WLAN deployment, an embodiment of the present invention further provides a WLAN deployment ordering apparatus, where the apparatus includes a data hotspot cell acquiring module 701, a WIFI data hotspot cell acquiring module 702, and a deployment priority ranking module 703.
The priority ranking module 703 is configured to calculate the WIFI data hotspot cell demand heat score according to the following formula:
wherein,representing the data traffic contribution proportion of the high-traffic WIFI terminal;
representing the quantity proportion of the high-flow WIFI terminals;
representing the quantity proportion of the WIFI terminals;
representing the voice call duration proportion of the high-flow WIFI terminal;
CEILING (10 Mi/Max (M1.., Mn))/10 represents the number of stages of the step function;
w1, W2, W3, and W4 are weight coefficients.
The priority data of the hotspot cells for establishing the WIFI data are obtained by sequencing according to the obtained WIFI demand heat scores of the cells, unreasonable property of setting the priority of the hotspot regions by subjective human factors can be avoided, meanwhile, the hotspot data are automatically calculated and scored through model software, manpower is saved, and scientificity and normalization of WLAN network deployment are improved.
It should be noted that: the above embodiments are only used for illustrating the present invention and not for limiting, the present invention is not limited to the above examples, and all technical solutions and modifications thereof which do not depart from the spirit and scope of the present invention should be covered by the claims of the present invention.
Claims (16)
1. A WIFI data hotspot cell data monitoring method is characterized by comprising the following steps:
obtaining network telephone traffic statistical data of a WLAN cell to be deployed, and calculating to obtain data hotspot cell data;
obtaining PS signaling monitoring data of the WLAN cell to be deployed, and calculating to obtain WIFI data hotspot cell data;
the step of obtaining PS signaling monitoring data of the WLAN cell to be deployed and calculating WIFI data hotspot cell data further includes:
acquiring PS signaling monitoring data of all terminal users in a preset time period under the data hotspot cell;
carrying out terminal information data duplication elimination processing on the PS signaling monitoring data to obtain user terminal information;
matching the user terminal information with a WIFI terminal database to obtain a WIFI terminal existing under a data hotspot cell;
calculating the distribution quantity and the terminal proportion of the WIFI terminals in the data hotspot cell;
and sequencing the distribution quantity of the WIFI terminals in each cell, and screening out the data hotspot cells with the distribution quantity of the WIFI terminals larger than a preset value as first WIFI data hotspot cells.
2. The method of claim 1, wherein obtaining network traffic statistics for the WLAN cells to be deployed, and wherein calculating the obtained data hotspot cell data further comprises:
extracting network traffic data of each WLAN cell to be deployed;
and carrying out average calculation on the network telephone traffic data, arranging according to the data flow of the cells, and taking the cell with the data flow higher than the average flow of each cell as a high-flow cell.
3. The method of claim 2, wherein the step of averaging the network traffic data, ranking according to cell data traffic, and using a cell with a traffic higher than an average per cell traffic as a high traffic cell further comprises:
and comparing the data flow of each cell in a preset time period with the average data flow of the cell in a continuous time period, and calculating the probability that the data flow of the cell appearing every day is greater than the average data flow to obtain the non-accidental data hotspot cell data.
4. The method according to claim 1, wherein the step of sorting the distribution quantity of the WIFI terminals in each cell and screening out the data hotspot cells with the distribution quantity of the WIFI terminals larger than a preset value as the first WIFI data hotspot cells further comprises the following steps:
carrying out mean value calculation on data flow of each WIFI terminal at a preset time period, then sequencing, and defining the WIFI terminals which are loaded according to the descending sequence and have a preset proportion of total flow of WIFI data of each cell as high-flow WIFI terminals under the data hotspot cell;
acquiring PS signaling monitoring data of the high-traffic WIFI terminal in preset time periods of a PS domain and a CS domain;
performing mean value calculation on PS signaling monitoring data generated by a PS domain to obtain the data traffic of each WIFI terminal generated in a relevant cell, and sequencing to obtain a hotspot cell with high data traffic generated by a WIFI terminal user as a second WIFI data hotspot cell;
and carrying out mean value calculation on PS signaling monitoring data generated by the CS domain to obtain a potential data hotspot cell generated by the flow of the high-flow WIFI terminal user, screening the data hotspot cell to obtain a potential data hotspot cell generated by the flow of the high-flow WIFI terminal user in the network as a third WIFI data hotspot cell.
5. A WLAN deployment ordering method, comprising:
obtaining network telephone traffic statistical data of a WLAN cell to be deployed, and calculating to obtain data hotspot cell data;
obtaining PS signaling monitoring data of the WLAN cell to be deployed, and calculating to obtain WIFI data hotspot cell data;
carrying out priority grading on the WIFI data hotspot cell data to obtain a deployment priority sequence of the WIFI data hotspot cell;
the step of obtaining PS signaling monitoring data of the WLAN cell to be deployed and calculating WIFI data hotspot cell data further includes:
acquiring PS signaling monitoring data of all terminal users in a preset time period under the data hotspot cell;
carrying out terminal information data duplication elimination processing on the PS signaling monitoring data to obtain user terminal information;
matching the user terminal information with a WIFI terminal database to obtain a WIFI terminal existing under a data hotspot cell;
calculating the distribution quantity and the terminal proportion of the WIFI terminals in the data hotspot cell;
and sequencing the distribution quantity of the WIFI terminals in each cell, and screening out the data hotspot cells with the distribution quantity of the WIFI terminals larger than a preset value as first WIFI data hotspot cells.
6. The method of claim 5, wherein obtaining network traffic statistics for the WLAN cell to be deployed, and wherein calculating the obtained data hotspot cell data further comprises:
extracting network traffic data of each WLAN cell to be deployed;
and carrying out average calculation on the network telephone traffic data, arranging according to the data flow of the cells, and taking the cell with the data flow higher than the average flow of each cell as a high-flow cell.
7. The method of claim 6, wherein the step of averaging the network traffic data, ranking according to cell data traffic, and using a cell with a traffic higher than an average per cell traffic as a high traffic cell further comprises:
and comparing the data flow of each cell in a preset time period with the average data flow of the cell in a continuous time period, and calculating the probability that the data flow of the cell appearing every day is greater than the average data flow to obtain the non-accidental data hotspot cell data.
8. The method according to claim 5, wherein the step of sorting the distribution quantity of the WIFI terminals in each cell and screening out the data hotspot cells with the distribution quantity of the WIFI terminals larger than a preset value as the first WIFI data hotspot cells further comprises the following steps:
carrying out mean value calculation on data flow of each WIFI terminal at a preset time period, then sequencing, and defining the WIFI terminals which are loaded according to the descending sequence and have a preset proportion of total flow of WIFI data of each cell as high-flow WIFI terminals under the data hotspot cell;
acquiring PS signaling monitoring data of the high-traffic WIFI terminal in preset time periods of a PS domain and a CS domain;
performing mean value calculation on PS signaling monitoring data generated by a PS domain to obtain the data traffic of each WIFI terminal generated in a relevant cell, and sequencing to obtain a hotspot cell with high data traffic generated by a WIFI terminal user as a second WIFI data hotspot cell;
and carrying out mean value calculation on PS signaling monitoring data generated by the CS domain to obtain a potential data hotspot cell generated by the flow of the high-flow WIFI terminal user, screening the data hotspot cell to obtain a potential data hotspot cell generated by the flow of the high-flow WIFI terminal user in the network as a third WIFI data hotspot cell.
9. A WIFI data hotspot cell data monitoring device is characterized by comprising a data hotspot cell acquisition module and a WIFI data hotspot cell acquisition module, wherein,
the data hotspot cell acquisition module is used for acquiring network telephone traffic statistical data of the WLAN cell to be deployed and calculating to acquire data of the data hotspot cell;
the WIFI data hotspot cell acquisition module is used for acquiring PS signaling monitoring data of the WLAN cell to be deployed and calculating to acquire WIFI data hotspot cell data;
the WIFI data hotspot cell acquisition module is further configured to:
acquiring PS signaling monitoring data of all terminal users in a preset time period under the data hotspot cell;
carrying out terminal information data duplication elimination processing on the PS signaling monitoring data to obtain user terminal information;
matching the user terminal information with a WIFI terminal database to obtain a WIFI terminal existing under a data hotspot cell;
calculating the distribution quantity and the terminal proportion of the WIFI terminals in the data hotspot cell;
and sequencing the distribution quantity of the WIFI terminals in each cell, and screening out the data hotspot cells with the distribution quantity of the WIFI terminals larger than a preset value as first WIFI data hotspot cells.
10. The apparatus of claim 9, wherein the data hotspot cell acquisition module is further configured to:
extracting network traffic data of each WLAN cell to be deployed;
and carrying out average calculation on the network telephone traffic data, arranging according to the data flow of the cells, and taking the cell with the data flow higher than the average flow of each cell as a high-flow cell.
11. The apparatus of claim 10, wherein the data hotspot cell acquisition module is further configured to:
and comparing the data flow of each cell in a preset time period with the average data flow of the cell in a continuous time period, and calculating the probability that the data flow of the cell appearing every day is greater than the average data flow to obtain the non-accidental data hotspot cell data.
12. The apparatus of claim 9, wherein the WIFI data hotspot cell acquisition module is further configured to:
carrying out mean value calculation on data flow of each WIFI terminal at a preset time period, then sequencing, and defining the WIFI terminals which are loaded according to the descending sequence and have a preset proportion of total flow of WIFI data of each cell as high-flow WIFI terminals under the data hotspot cell;
acquiring PS signaling monitoring data of the high-traffic WIFI terminal in preset time periods of a PS domain and a CS domain;
performing mean value calculation on PS signaling monitoring data generated by a PS domain to obtain the data traffic of each WIFI terminal generated in a relevant cell, and sequencing to obtain a hotspot cell with high data traffic generated by a WIFI terminal user as a second WIFI data hotspot cell;
and carrying out mean value calculation on PS signaling monitoring data generated by the CS domain to obtain a potential data hotspot cell generated by the flow of the high-flow WIFI terminal user, screening the data hotspot cell to obtain a potential data hotspot cell generated by the flow of the high-flow WIFI terminal user in the network as a third WIFI data hotspot cell.
13. The utility model provides a WLAN deploys sequencing device, its characterized in that includes data hotspot district acquisition module, WIFI data hotspot district acquisition module and deploys priority sequencing module, wherein:
the data hotspot cell acquisition module is used for acquiring network telephone traffic statistical data of the WLAN cell to be deployed and calculating to acquire data of the data hotspot cell;
the WIFI data hotspot cell acquisition module is used for acquiring PS signaling monitoring data of the WLAN cell to be deployed and calculating to acquire WIFI data hotspot cell data;
the deployment priority ordering module is used for carrying out priority grading on the WIFI data hotspot cell data to obtain a deployment priority sequence of the WIFI data hotspot cell;
the WIFI data hotspot cell acquisition module is further configured to:
acquiring PS signaling monitoring data of all terminal users in a preset time period under the data hotspot cell;
carrying out terminal information data duplication elimination processing on the PS signaling monitoring data to obtain user terminal information;
matching the user terminal information with a WIFI terminal database to obtain a WIFI terminal existing under a data hotspot cell;
calculating the distribution quantity and the terminal proportion of the WIFI terminals in the data hotspot cell;
and sequencing the distribution quantity of the WIFI terminals in each cell, and screening out the data hotspot cells with the distribution quantity of the WIFI terminals larger than a preset value as first WIFI data hotspot cells.
14. The apparatus of claim 13, wherein the data hotspot cell acquisition module is further configured to:
extracting network traffic data of each WLAN cell to be deployed;
and carrying out average calculation on the network telephone traffic data, arranging according to the data flow of the cells, and taking the cell with the data flow higher than the average flow of each cell as a high-flow cell.
15. The apparatus of claim 14, wherein the data hotspot cell acquisition module is further configured to:
and comparing the data flow of each cell in a preset time period with the average data flow of the cell in a continuous time period, and calculating the probability that the data flow of the cell appearing every day is greater than the average data flow to obtain the non-accidental data hotspot cell data.
16. The apparatus of claim 13, wherein the WIFI data hotspot cell acquisition module is further configured to:
carrying out mean value calculation on data flow of each WIFI terminal at a preset time period, then sequencing, and defining the WIFI terminals which are loaded according to the descending sequence and have a preset proportion of total flow of WIFI data of each cell as high-flow WIFI terminals under the data hotspot cell;
acquiring PS signaling monitoring data of the high-traffic WIFI terminal in preset time periods of a PS domain and a CS domain;
performing mean value calculation on PS signaling monitoring data generated by a PS domain to obtain the data traffic of each WIFI terminal generated in a relevant cell, and sequencing to obtain a hotspot cell with high data traffic generated by a WIFI terminal user as a second WIFI data hotspot cell;
and carrying out mean value calculation on PS signaling monitoring data generated by the CS domain to obtain a potential data hotspot cell generated by the flow of the high-flow WIFI terminal user, screening the data hotspot cell to obtain a potential data hotspot cell generated by the flow of the high-flow WIFI terminal user in the network as a third WIFI data hotspot cell.
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