CN105721247B - A method and system for analyzing user online behavior data - Google Patents

Abstract

The invention provides an analysis method and analysis system for user online behavior data. The analysis method includes: filtering out small-flow services in user or community online records; small-flow services are services with web browsing traffic less than or equal to 200KB, and video traffic less than or equal to 480KB; or, small-flow services are services with a transmission rate of less than or equal to 50Kbps . The analysis method of user online behavior data can provide network planning with data that is more in line with the actual network needs of users or communities, thereby improving network quality, improving the accuracy of network construction and the effectiveness of investment.

Description

A method and system for analyzing user online behavior data

technical field

The present invention relates to the field of communication technology, in particular to an analysis method and analysis system for user online behavior data.

Background technique

At present, telecom operators generally have an overall surplus of mobile network resources but a local shortage, and the network quality cannot meet the rapid development of mobile Internet services.

The traditional network planning and design of telecom operators is usually based on traffic forecasting. Traffic statistics can only obtain the traffic of a base station cell within a certain period of time, and cannot distinguish users or traffic types. This is different from actual mobile Internet users. The distribution characteristics of data traffic do not match, and the accuracy of network construction and investment effectiveness are very low.

Existing network planning technology uses the traffic data such as the data traffic of the base station cell as an important basis. The traffic data of the cell generally comes from the monitoring module of the equipment, and only the traffic volume of the cell in a certain period of time can be counted, and the traffic cannot be distinguished from users. , It is also impossible to distinguish the business type of traffic, so the statistical data obtained do not match the actual user experience, and cannot truly reflect the actual perception and needs of users when surfing the Internet.

Contents of the invention

The present invention aims at the above-mentioned technical problems existing in the prior art, and provides an analysis method and analysis system for user online behavior data. This analysis method can provide network planning with data that is more in line with the actual network needs of users or communities, thereby improving network quality, improving the accuracy of network construction and the effectiveness of investment.

The present invention provides a method for analyzing user online behavior data, comprising: filtering out small flow services in user or community online records; the small flow services are services with web page browsing traffic less than or equal to 200KB and video traffic less than or equal to 480KB; or , the small flow service is a service with a transmission rate less than or equal to 50Kbps.

Preferably, it also includes: when calculating the effective transmission time of a user or a cell using the same traffic type service, merging the overlapping time of multiple online records of the user or cell using the same traffic type service in the same time period into one and the overlapping time equal time period calculation;

Alternatively, when calculating the total effective transmission time of a user or a community surfing the Internet, the overlapping time of multiple Internet access records of the user or community surfing the Internet within the same time period is combined into a time period equal to the overlapping time period for calculation.

Preferably, the method further includes: correcting the traffic type of web browsing records in user or cell surfing records to stream media type.

Preferably, it also includes: calculating the perception rate of the user or cell using the same traffic type service;

Wherein, the perceived rate of the user using the same traffic type service=the traffic of the user using the same traffic type service/the effective transmission time of the user using the same traffic type service;

The perceived rate of the cell using the same traffic type service=the traffic of the cell using the same traffic type service/the effective transmission time of the cell using the same traffic type service.

Preferably, it also includes: calculating the total perceived rate of the user or the cell surfing the Internet;

Wherein, the total perceived rate of the user surfing the Internet=the total traffic used by the user surfing the Internet/the total effective transmission time of the user surfing the Internet;

The total perceived rate of the cell surfing the Internet=the total traffic used by the cell surfing the Internet/the total effective transmission time of the cell surfing the Internet.

The present invention also provides an analysis system for user online behavior data, including:

The filtering module is used to filter out small traffic services in user or community online records; the small traffic services are services with webpage browsing traffic less than or equal to 200KB and video traffic less than or equal to 480KB; or, the small traffic services are services with a transmission rate of less than Equal to 50Kbps business.

Preferably, it also includes:

The merging module is used for merging the overlapping time of multiple online records of the user or community using the same traffic type service in the same time period into one overlapping time period when calculating the effective transmission time of the user or community using the same traffic type service Equal time period calculation; or, when calculating the total effective transmission time of the user or community online, the overlapping time of multiple Internet access records of the user or community online in the same time period is combined into one that is equal to the overlapping time period time period calculation.

Preferably, it also includes: a correction module, which is used to correct the records whose traffic type is web browsing in the user or cell Internet access records to stream media types.

Preferably, it also includes:

The first calculation module is used to calculate the perception rate of the same traffic type service used by the user or the cell;

Wherein, the perceived rate of the user using the same traffic type service=the traffic of the user using the same traffic type service/the effective transmission time of the user using the same traffic type service;

The perceived rate of the cell using the same traffic type service=the traffic of the cell using the same traffic type service/the effective transmission time of the cell using the same traffic type service.

Preferably, it also includes: a second calculation module, configured to calculate the total perceived rate of the user or the cell surfing the Internet;

Wherein, the total perceived rate of the user surfing the Internet=the total traffic used by the user surfing the Internet/the total effective transmission time of the user surfing the Internet;

The total perceived rate of the cell surfing the Internet=the total traffic used by the cell surfing the Internet/the total effective transmission time of the cell surfing the Internet.

Beneficial effects of the present invention: the method for analyzing user online behavior data provided by the present invention, through in-depth analysis of user or community online behavior data, corrects the type of online traffic according to the actual network behavior of the user or community, and filters out small flow services , recalculate the effective transmission time of users using various types of traffic types, and can obtain the actual perception rate of users or communities actually using various types of traffic and overall Internet traffic, so as to provide network planning that is more in line with the actual network needs of users or communities Data, thereby improving the accuracy of network construction and the effectiveness of investment.

The analysis system of user online behavior data provided by the present invention can correct the type of online traffic according to the actual online behavior of users or communities by setting a correction module, and can filter out small traffic services by setting a filter module, and can filter out small flow services by setting a merging module , can recalculate the effective transmission duration of users using various traffic types of services, and by setting the first calculation module and the second calculation module, the actual perception rate of various service types of traffic used by the user or the community and the overall Internet traffic can be obtained, thereby Provide network planning with data that is more in line with the actual network needs of users or communities, thereby improving the accuracy of network construction and the effectiveness of investment.

Description of drawings

Fig. 1 is the flowchart of analytical method in the embodiment of the present invention 1;

Fig. 2 is a schematic diagram of calculating the effective transmission duration of multiple online records;

Fig. 3 is the flowchart of analytical method in the embodiment of the present invention 2;

Fig. 4 is the functional block diagram of analysis system in the embodiment 3 of the present invention;

Fig. 5 is a functional block diagram of the analysis system in Embodiment 4 of the present invention.

The reference signs therein explain:

1. Filter module; 2. Merge module; 3. Correction module; 4. The first computing module; 5. The second computing module; UFDR1. The first online record; UFDR2. The second online record; UFDR3. The third Online record; UFDR4. The fourth online record; UFDR5. The actual effective transmission time of the four online records.

Detailed ways

In order for those skilled in the art to better understand the technical solution of the present invention, a method and system for analyzing user online behavior data provided by the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

Example 1:

This embodiment provides a method for analyzing user online behavior data, as shown in FIG. 1 , including: Step 10: filtering out small traffic services in user or community online records.

Among them, the small traffic business is usually set as the service threshold when distinguishing the business threshold: web browsing traffic is less than or equal to 200KB, and video traffic is less than or equal to 480KB. When the business threshold is not distinguished, it is usually set as: the business whose transmission rate is less than or equal to 50Kbps. Because the unified processing of small traffic services (such as periodic heartbeat packets, etc.) and other services will affect and deviate the indicators of traffic calculation, the calculation of traffic is not accurate enough, resulting in inaccurate analysis results of user online behavior data, so In the analysis of users' online behavior data, filtering out small traffic services can eliminate the influence and deviation of small traffic services on traffic statistics, so that the traffic statistics of users' online traffic can truly reflect the actual traffic usage of users, and thus make users The analysis results of online behavior data are more accurate.

Step 11: When calculating the effective transmission time of a user or a community using the same traffic type service, combine the overlapping time of multiple online records of the user or community using the same traffic type service in the same time period into one equal to the overlapping time period time period calculation.

As shown in FIG. 2 , the calculation of the effective transmission time of multiple online records is illustrated by taking the calculation of the effective transmission time of four online records as an example. In Fig. 2, the X-axis represents the time axis, and the Y-axis represents the order of each online record. The first online record UFDR1, the second online record UFDR2, the third online record UFDR3 and the fourth online record UFDR4 are services of the same traffic type, and the time interval of the first online record UFDR1 is included in the second online record Within the time interval of UFDR2; the time interval of the second online record UFDR2 intersects with the time interval of the third online record UFDR3; the time of the first online record UFDR1, the second online record UFDR2 and the third online record UFDR3 The interval does not intersect with the time interval of the fourth online record UFDR4; the effective transmission time of these four online records combined by time length is the actual effective transmission time UFDR5 located below the X coordinate axis.

The effective transmission time calculated after combining the time lengths can make the actual transmission time statistics of Internet traffic more reasonable and accurate, thereby making the analysis results of user Internet behavior data more accurate.

Step 12: Correct the traffic type of web browsing records in user or community Internet access records to stream media type.

During the process of users or communities surfing the Internet, there are more records marked as web browsing type in traffic statistics calculation than streaming media type traffic statistics, and web browsing type actually belongs to streaming media type, so the actual traffic There are deviations in statistics. Therefore, when performing traffic statistics of web browsing type and streaming media type, it is necessary to correct the web browsing type of business into streaming media type of business, and then perform traffic statistics. In this way, the business flow statistics of web browsing type and streaming media type can be more accurate, so that the analysis results of user online behavior data can be more accurate.

In this embodiment, by using the user or the community to record data online, it can truly reflect the actual traffic usage of the user or the community. The online record data includes information such as the user (such as the user's mobile phone number), the size of the traffic, and the type of traffic business, as shown in the following table:

Each line of online record data represents a user's online record, including the user's mobile phone number, online start time, online end time, the traffic size of this record, the traffic business type of this record and other information, and the details of each record The information is as follows:

The analysis of user online behavior data is based on multiple records in the above table, but using these data directly will cause deviations in the analysis. Therefore, during the analysis process, it is necessary to process the multiple records in steps 10-12. In order to finally obtain the actual perception rate of users or cells using various services.

Among them, in practical applications, when the traffic type code ID of the Internet record is detected, it is 200 (for WAP1x, WAP2x (get) web browsing record), 201 (for WAP1x, WAP2x (post) web browsing record), 204 (for http (get) web page browsing record) and 205 (for http (post) web page browsing record), and when the data type (ContentType) of the online record is detected as: MP2T, application/zip, application/rar, audio/mp3, audio /mp4, audio/midi, video/3gp, video/flv, video/mp4, video/mpeg audio or video data type, modify the traffic type of Internet records that meet the above conditions from web browsing type to streaming media type ( Because the type of surfing records meeting the above conditions is usually web browsing type).

In addition, the traffic types recorded online also include MMS, instant messaging, email, VOIP, file transfer, and P2P, etc. When these traffic types are involved in the online records, the traffic statistics can be calculated according to the actual traffic, and there is no need to modify the traffic type.

Step 13: Calculate the perception rate of the user or cell using the same traffic type service.

Wherein, the perceived rate of the user using the same traffic type service=the user's traffic using the same traffic type service/the effective transmission time of the user using the same traffic type service. The perception rate of the cell using the same traffic type service = the traffic of the cell using the same traffic type service/the effective transmission time of the cell using the same traffic type service.

It should be noted that the traffic of the user (or community) using the web browsing type service and the streaming media type service is the actual traffic statistics after the traffic type correction and the small traffic service filtering; The traffic of traffic types other than streaming media services is the actual traffic statistics after filtering by small traffic services; and the effective transmission time of the user (or cell) using the same traffic type business is the effective transmission calculated after overlapping time duration. The perceived rate of the user or cell using the same traffic type service calculated in this way is more accurate, so that the network can plan mobile network data that is more in line with the actual needs of the user according to the perceived rate, thereby improving the quality of the mobile network.

The method for analyzing user online behavior data provided in this embodiment can correct the individual traffic types that can cause deviations in traffic statistics, filter out small traffic services, and recalculate the effective transmission time of users using various traffic types. Obtain the actual perception rate of various services used by users or cells, so as to provide network planning with closer to the user's actual experience and more accurate statistical data, thereby improving the accuracy of network construction and the effectiveness of network investment.

Example 2:

This embodiment provides a method for analyzing user online behavior data, as shown in FIG. 3 , including: Step 10: filtering out small traffic services in user or community online records.

Among them, the small traffic business is usually set as the service threshold when distinguishing the business threshold: web browsing traffic is less than or equal to 200KB, and video traffic is less than or equal to 480KB. When the business threshold is not distinguished, it is usually set as: the business whose transmission rate is less than or equal to 50Kbps. In the analysis of users' online behavior data, small traffic services are filtered out, which can eliminate the impact and deviation of small traffic services on traffic statistics, so that the user's online traffic statistics can truly reflect the user's actual traffic usage, and then enable users to surf the Internet The analysis results of behavioral data are more accurate.

Step 11': When calculating the total effective transmission time of a user or a community online, combine the overlapping time of multiple online records of the user or community in the same time period into a time period equal to the overlapping time period for calculation.

As shown in FIG. 2 , the calculation of the effective transmission time of multiple online records is illustrated by taking the calculation of the effective transmission time of four online records as an example. In Fig. 2, the X-axis represents the time axis, and the Y-axis represents the order of each online record. The first online record UFDR1, the second online record UFDR2, the third online record UFDR3, and the fourth online record UFDR4 are services of different traffic types. The time interval of the first online record UFDR1 is included in the second online record Within the time interval of UFDR2; the time interval of the second online record UFDR2 intersects with the time interval of the third online record UFDR3; the time of the first online record UFDR1, the second online record UFDR2 and the third online record UFDR3 The interval does not intersect with the time interval of the fourth online record UFDR4; the effective transmission time of these four online records combined by time length is the actual effective transmission time UFDR5 located below the X coordinate axis.

The effective transmission time calculated after combining the time lengths can make the actual transmission time statistics of Internet traffic more reasonable and accurate, thereby making the analysis results of user Internet behavior data more accurate.

Step 12': Calculate the total perceived rate of the user or cell surfing the Internet.

Wherein, the total perceived rate of the user surfing the Internet = the total traffic used by the user surfing the Internet / the total effective transmission time of the user surfing the Internet. The total perception rate of the community's Internet access = the total traffic used by the community's Internet access / the total effective transmission time of the community's Internet access.

It should be noted that the total traffic used by the user (or community) online is the actual total traffic statistics after filtering by small traffic services, and the total effective transmission time of the user (or community) online is the total calculated after overlapping time. effective transmission time. The calculated total perception rate of the user or cell is more accurate, so that the network can plan mobile network data that better meets the actual needs of the user or cell according to the total perception rate, thereby improving the quality of the mobile network.

In this embodiment, in the analysis method of the user's online behavior data, because the total perception rate of the user or the community is analyzed and calculated, that is, in the process of analyzing and calculating the total perception rate, it is only necessary to count the number of users or the community's Internet usage. Total traffic, the total traffic used by a user or community to access the Internet is the sum of the traffic of various types of traffic used by the user or community to access the Internet. Compared with the streaming media type, there are more traffic statistics, and the streaming media type records are less in the traffic statistics calculation than the web browsing type traffic statistics, so when counting the total Internet traffic of users or communities, the calculation The traffic of the web browsing type and the traffic of the streaming media type of the total incoming Internet traffic are exactly complementary, so there is no need to correct the records whose traffic type is the web browsing type. Therefore, in the method for analyzing user online behavior data in this embodiment, there is no step of correcting the traffic type of the web browsing type business.

The analysis method of user online behavior data provided in this embodiment can obtain the actual perceived rate of the user or community online by filtering out small flow services and recalculating the effective transmission time of the user's online traffic, thereby providing network planning that is closer to the user. The actual experience and more accurate statistical data will improve the accuracy of network construction and the effectiveness of network investment.

Beneficial effects of embodiment 1-2: the analysis method of user's online behavior data provided in embodiment 1-2, through in-depth analysis of user or community's online behavior data, according to the actual network behavior of user or community, the Internet traffic type is analyzed Correction, filtering out small traffic services, recalculating the effective transmission time of users using various types of traffic types, and being able to obtain the actual perception rate of various types of traffic used by users or communities and the overall Internet traffic, thereby providing a more suitable network planning Data on the actual network requirements of users or communities improves the accuracy of network construction and the effectiveness of investment.

Example 3:

This embodiment provides a system for analyzing user online behavior data, as shown in FIG. 4 , including: a filtering module 1 for filtering out small traffic services in user or community online records. Among them, the small flow service is a service with a web browsing traffic of less than or equal to 200KB, and a video flow of less than or equal to 480KB; or, the small flow service is a service with a transmission rate of less than or equal to 50Kbps.

The setting of the filtering module 1 can eliminate the impact and deviation of small traffic services on traffic statistics, so that the traffic statistics of users online can truly reflect the actual traffic usage of users, and then make the analysis results of user online behavior data more accurate.

In this embodiment, the analysis system further includes: a merging module 2, which is used for calculating the effective transmission duration of a user or a cell using the same traffic type service, and combining multiple online data of the user or cell using the same traffic type service within the same time period Recorded overlapping times are combined into a single time period calculation equal to the overlapping period. The effective transmission duration calculated by the merging module 2 can make the statistics of the actual transmission duration of the Internet traffic more reasonable and accurate, thereby making the analysis result of the user's Internet behavior data more accurate.

In this embodiment, the analysis system further includes a correction module 3, which is used to correct the traffic type of web browsing records in user or community Internet access records to stream media type. The setting of the modification module 3 can make the business flow statistics of the web browsing type and the streaming media type more accurate, thereby making the analysis results of the user's online behavior data more accurate.

In this embodiment, the analysis system further includes a first calculation module 4, configured to calculate the perception rate of a user or a cell using a service of the same traffic type. Among them, the user's perception rate of using the same traffic type service = the user's traffic of the same traffic type service / the effective transmission time of the user's use of the same traffic type service; the cell's perception rate of using the same traffic type service = the cell's use of the same traffic type of service traffic / The effective transmission time of the same traffic type service used by the cell.

Wherein, user (or community) uses the traffic of webpage browsing type service and stream media type business all to be the actual traffic statistics after the traffic type correction of correction module 3 and filtering module 1 small traffic service filtering; The traffic of other traffic type services other than the browsing type business and the streaming media type business is the actual traffic statistics after filtering by the filtering module 1 small traffic business; 2 The effective transmission duration calculated by combining overlapping time. This makes the perception rate calculated by the first calculation module 4 for users or cells using the same traffic type service more accurate, so that the network can plan mobile network data that is more in line with the actual needs of users according to the perception rate, thereby improving the quality of the mobile network .

In the analysis system of user online behavior data in this embodiment, the individual flow types that can cause deviations in flow statistics are corrected by the correction module, the small flow services are filtered out by the filter module, and the various flow types of services used by users are recalculated by the merge module The effective transmission duration can be obtained through the first calculation module to obtain the actual perception rate of various services used by users or cells, so as to provide network planning with closer to the user's actual experience and more accurate statistical data, thereby improving the accuracy of network construction and network investment effectiveness.

Example 4:

This embodiment provides an analysis system for user online behavior data, as shown in FIG. 5 , which includes a filtering module 1 for filtering out small traffic services in user or community online records. Among them, the small flow service is a service with a web browsing traffic of less than or equal to 200KB, and a video flow of less than or equal to 480KB; or, the small flow service is a service with a transmission rate of less than or equal to 50Kbps.

The setting of the filtering module 1 can eliminate the impact and deviation of small traffic services on traffic statistics, so that the traffic statistics of users online can truly reflect the actual traffic usage of users, and then make the analysis results of user online behavior data more accurate.

In this embodiment, the analysis system also includes: a merging module 2, which is used to merge the overlapping time of multiple online records of the user or the community in the same time period when calculating the total effective transmission time of the user or the community online into A period equal to the overlapping period is calculated. The effective transmission duration calculated by the merging module 2 can make the statistics of the actual transmission duration of the Internet traffic more reasonable and accurate, thereby making the analysis result of the user's Internet behavior data more accurate.

In this embodiment, the analysis system further includes a second calculation module 5, which is used to calculate the total perceived rate of the user or the cell surfing the Internet. Among them, the total perceived rate of the user's Internet access = the total traffic used by the user to access the Internet / the total effective transmission time of the user's Internet access; the total perceived rate of the community's Internet access = the total traffic used by the community to access the Internet / the total effective transmission time of the community's Internet access.

Among them, the total traffic used by the user (or community) online is the actual total traffic statistics after filtering the small traffic services by the filtering module 1, and the total effective transmission time of the user (or community) online is the overlapping time of the combined module 2 The total effective transmission duration calculated after the combination. This makes the total perception rate of the user or cell online calculated by the second calculation module 5 more accurate, so that the network can plan mobile network data that is more in line with the actual needs of the user or the cell according to the total perception rate, thereby improving the quality of the mobile network .

The analysis system of the user's online behavior data in this embodiment filters out small flow services through the filter module, recalculates the effective transmission time of the user's use of various flow types of services through the merging module, and can obtain the user or community online through the second calculation module. Actual perception rate, so as to provide network planning closer to the user's actual experience and more accurate statistical data, thereby improving the accuracy of network construction and the effectiveness of network investment.

Beneficial effects of embodiment 3-4: the analysis system of user's online behavior data provided in embodiment 3-4, by setting the correction module, can correct the type of Internet traffic according to the actual network behavior of the user or the community, and filter by setting module, which can filter out small traffic services. By setting the merging module, it can recalculate the effective transmission time of users using various types of traffic types. The actual perception rate of business type traffic and overall Internet traffic provides network planning with data that is more in line with the actual network needs of users or communities, thereby improving the accuracy of network construction and the effectiveness of investment.

It can be understood that, the above embodiments are only exemplary embodiments adopted for illustrating the principle of the present invention, but the present invention is not limited thereto. For those skilled in the art, various modifications and improvements can be made without departing from the spirit and essence of the present invention, and these modifications and improvements are also regarded as the protection scope of the present invention.

Claims (6)

1. a kind of analysis method of user's internet behavior data uses various different service types streams for obtaining user or cell The actual perceived rate of amount characterized by comprising filter out the small-flow service in user or cell internet records；It is described small Flow business is the business that web page browsing flow is less than or equal to 200KB, video flow is less than or equal to 480KB；Alternatively, the small stream Amount business is the business that transmission rate is less than or equal to 50Kbps；

It calculates user or cell and uses effective transmission duration of same flow type service or total effective transmission duration of online； Wherein, the overlapping time by user or cell within the same period using a plurality of internet records of same flow type service closes And user or cell are calculated for a period equal with overlapping time section and uses effective transmission of same flow type service Duration, alternatively, by the overlapping time for a plurality of internet records that user or cell surf the Internet within the same period merge into one with The overlapping time section equal period calculates total effective transmission duration of user or cell online；

The record that discharge pattern in user or cell internet records is web page browsing is modified to Streaming Media type；

User or cell are calculated using the perception rate of same flow type service or always perceives rate.

2. analysis method according to claim 1, which is characterized in that

The user uses the stream of same flow type service using perception rate=user of same flow type service Amount/user uses effective transmission duration of same flow type service；

The cell uses the stream of same flow type service using perception rate=cell of same flow type service Amount/cell uses effective transmission duration of same flow type service.

3. analysis method according to claim 1, which is characterized in that

Total effective of the total flow that total perception rate of user online uses/user online Transmit duration；

Total effective of the total flow that total perception rate of cell online uses/cell online Transmit duration.

4. a kind of analysis system of user's internet behavior data uses various different service types streams for obtaining user or cell The actual perceived rate of amount characterized by comprising

Filtering module, for filtering out the small-flow service in user or cell internet records；The small-flow service is that webpage is clear Flow of looking at is less than or equal to 200KB, video flow is less than or equal to the business of 480KB；Alternatively, the small-flow service is transmission rate Business less than or equal to 50Kbps；

Merging module, for when calculating user or cell and using effective transmission duration of same flow type service, by user Or cell within the same period using the overlapping time of a plurality of internet records of same flow type service merge into one with The overlapping time section equal period calculates；Alternatively, for when calculating total effective transmission duration of user or cell online, The overlapping time for a plurality of internet records that user or cell surf the Internet within the same period is merged into one and overlapping time section The equal period calculates；

Correction module, for the record that discharge pattern in user or cell internet records is web page browsing to be modified to Streaming Media class Type；

First computing module uses the perception rate of same flow type service for calculating user or cell；

Second computing module, for calculating total perception rate of user or cell online.

5. analysis system according to claim 4, which is characterized in that

The user uses the stream of same flow type service using perception rate=user of same flow type service Amount/user uses effective transmission duration of same flow type service；

The cell uses the stream of same flow type service using perception rate=cell of same flow type service Amount/cell uses effective transmission duration of same flow type service.

6. analysis system according to claim 4, which is characterized in that total perception rate=use of user's online The total effective transmission duration of the total flow that family online uses/user online；

Total effective of the total flow that total perception rate of cell online uses/cell online Transmit duration.