CN102387260B - Method and system for determining dropped call rate - Google Patents

Method and system for determining dropped call rate Download PDF

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Publication number
CN102387260B
CN102387260B CN201110321050.6A CN201110321050A CN102387260B CN 102387260 B CN102387260 B CN 102387260B CN 201110321050 A CN201110321050 A CN 201110321050A CN 102387260 B CN102387260 B CN 102387260B
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users
counter
active user
user
sampling period
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CN102387260A (en
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王转莉
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ZTE Corp
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ZTE Corp
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Priority to PCT/CN2012/072848 priority patent/WO2013056530A1/en
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04M—TELEPHONIC COMMUNICATION
    • H04M3/00—Automatic or semi-automatic exchanges
    • H04M3/22—Arrangements for supervision, monitoring or testing
    • H04M3/36—Statistical metering, e.g. recording occasions when traffic exceeds capacity of trunks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04M—TELEPHONIC COMMUNICATION
    • H04M3/00—Automatic or semi-automatic exchanges
    • H04M3/08—Indicating faults in circuits or apparatus
    • H04M3/10—Providing fault- or trouble-signals
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/08—Testing, supervising or monitoring using real traffic

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  • Signal Processing (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

The invention discloses a method and system for determining a dropped call rate. The method comprises the following steps of: recording a user number which is abnormally released in a sampling period and a user number which is successfully established in the sampling period by adopting a summation and accumulation way through a foreground according to the increased user number and the decreased user number, and calculating a current user number in the sampling period; after the sampling period is reached, respectively writing the user number which is abnormally released in the sampling period and the user number which is successfully established in the sampling period into an abnormally-released user counter and a successfully-established user counter by adopting the summation and accumulation way through the foreground; writing the current user number of the sampling period into a current user counter by adopting a way of covering previous data; after a reporting period is reached, synchronizing the data on the abnormally-released user counter, the successfully-established user counter and the current user counter to a webmaster through the foreground; and determining the dropped call rate of the reporting period by the webmaster according to the user number which is abnormally released in the reporting period, the user number which is successfully established in the reporting period and the current user number of the last reporting period.

Description

Cutting off rate is determined method and system
Technical field
The present invention relates to field of mobile communication, particularly relate to a kind of cutting off rate and determine method and system.
Background technology
In the prior art, cutting off rate is the index of an important measurement systematic function of mobile communications network.As the 4th generation technique Long Term Evolution (Long Term Evolution, referred to as the LTE) system of mobile network's evolution, cutting off rate index is more important.
At present, the definition of cutting off rate index comprises two kinds of computational methods: method one, according to the number of users of abnormal release, divided by the total number of users discharging, determine cutting off rate; Method two, the number of users of setting up divided by success according to the number of users of abnormal release is determined cutting off rate.In LTE system, mainly according to method two, determine cutting off rate index.
In method two, molecule (the abnormal number of users discharging) and the denominator (number of users that success is set up) of determining cutting off rate index do not have interdependence, and the number of users that the abnormal number of users discharging and success are set up does not have interdependence in a granularity.In these cases, can cause the index of cutting off rate to occur being greater than 100% abnormal conditions.Densely distributed at number of users, add up in the situation that fineness ratio is larger, abnormal difficult exposure like this, but sparse in user distribution, statistics granularity is smaller, and successfully set up and extremely discharge in the situation across granularity, the abnormal occurrence probability of this statistics is very high, thereby has had a strong impact on the accuracy of index.
Summary of the invention
The invention provides a kind of cutting off rate and determine method and system, to solve in prior art cutting off rate under special circumstances, be greater than 100% and problem that the cutting off rate accuracy that causes reduces.
The invention provides a kind of cutting off rate and determine method, comprising:
The number of users of the increase that the foreground of base station reports according to the chain of command of base station and the number of users of minimizing, adopt the cumulative mode of summation to be recorded in the number of users of abnormal release in the sampling period and the number of users that success is set up, and calculate active user's number of real-time online within the sampling period;
The sampling period then after, foreground adopts the cumulative mode of summation that the number of users of the number of users of the abnormal release in this sampling period and success foundation is write respectively to abnormal releasing user counter and is successfully established subscriber's meter, and adopts the mode that covers former data that active user's number in this sampling period is write to active user's counter;
Report cycle then after, foreground is synchronized to webmaster by abnormal releasing user counter, the data that are successfully established on subscriber's meter and active user's counter;
Webmaster is determined the cutting off rate of this report cycle according to the number of users of the abnormal release of this report cycle, the number of users of success foundation and active user's number of a upper report cycle.
The present invention also provides a kind of cutting off rate to determine system, comprises base station foreground and webmaster, and wherein, base station foreground comprises:
Sampling module, for the number of users of increase and the number of users of minimizing reporting according to the chain of command of base station, adopt the cumulative mode of summation to be recorded in the number of users of abnormal release in the sampling period and the number of users that success is set up, and calculate active user's number of real-time online within the sampling period;
Processing module, for the sampling period then after, adopt the cumulative mode of summation that the number of users of the number of users of the abnormal release in this sampling period and success foundation is write respectively to abnormal releasing user counter and is successfully established subscriber's meter, and adopt the mode that covers former data that active user's number in this sampling period is write to active user's counter;
Reporting module, for report cycle then after, abnormal releasing user counter, the data that are successfully established on subscriber's meter and active user's counter are synchronized to webmaster;
Webmaster, for determining the cutting off rate of this report cycle according to the number of users of the abnormal release of this report cycle, the number of users of success foundation and active user's number of a upper report cycle.
Beneficial effect of the present invention is as follows:
By online active user's number at last granularity end being introduced to the cutting off rate index of next granularity, calculate, solve in prior art cutting off rate under special circumstances and be greater than 100% and problem that the cutting off rate accuracy that causes reduces, can under any circumstance guarantee the accuracy of cutting off rate.
Accompanying drawing explanation
Fig. 1 is the flow chart that the cutting off rate of the embodiment of the present invention is determined method;
Fig. 2 is the schematic diagram that the eNB of the embodiment of the present invention processes;
Fig. 3 is the process chart of the ENB performance sampling MOD of the embodiment of the present invention;
Fig. 4 is the process chart that the oldest value of OMC performance of the embodiment of the present invention gathers;
Fig. 5 is the structural representation that the cutting off rate of the embodiment of the present invention is determined system.
Embodiment
In order to solve in prior art cutting off rate under special circumstances, be greater than 100% and problem that the cutting off rate accuracy that causes reduces, the invention provides a kind of cutting off rate and determine method and system, particularly, first at (the Operations & Maintenance Center of operation maintenance center, referred to as OMC) a kind of new mode that gathers of webmaster introducing, be called the oldest value and gather mode.This mode supports the user data at last granularity end to introduce in this granularity.In addition, the foreground in base station, increases a kind of data processing method, is called sampling and revises (Modify, referred to as MOD) mode, completes the sampling of active user's number, replaces original sampled value all the time by the up-to-date sampled value of not zero clearing.By AM/BAM combination, final accurately definite cutting off rate.Below in conjunction with accompanying drawing and embodiment, the present invention is further elaborated.Should be appreciated that specific embodiment described herein, only in order to explain the present invention, does not limit the present invention.
Embodiment of the method
According to embodiments of the invention, provide a kind of cutting off rate to determine method, Fig. 1 is the flow chart that the cutting off rate of the embodiment of the present invention is determined method, before the flow process of carrying out as shown in Figure 1, the foreground of base station need to be handled as follows:
Number of users for abnormal release: all modes of gathering that need to abnormal releasing user counter are set to summing mode, and wherein, all modes of gathering comprise: foreground account form, the webmaster time is gathered mode, and mode is gathered in webmaster space;
The number of users of setting up for success: all modes of gathering that need to be successfully established subscriber's meter are set to summing mode, and wherein, all modes of gathering comprise: foreground account form, the webmaster time is gathered mode, and mode is gathered in webmaster space;
For current number of users: foreground account form that need to the active user's counter MOD mode that is set to sample, the webmaster time mode of gathering is set to ask the oldest value mode, and the webmaster space mode of gathering is set to summing mode.
Wherein, sampling MOD mode is specially: sampling refers to that the foreground (platform property statistical module) of base station periodically counts statistical phenomeon according to the chain of command of base station (business module) report of user, adds and subtracts calculating, obtains the value in sampling period.MOD refers to after each sample clock generator is overtime, and the value that this cycle is calculated writes in counter, as the value of this counter, covers original value all the time by up-to-date value.
Ask the oldest value mode to be: gathering of OMC be take granularity as unit, have 15 minutes granularities, 30 minutes granularities, 1 hour granularity, 1 day granularity, 1 week granularity, January granularity etc.When the definition of the oldest value is this Granular Computing index, the mode that gathers is got the value that last granularity is preserved for the counter of old value.As: calculate 2011-09-0711 point 15 minutes to 11: 30 cutting off rates during this period of time of 2011-09-07, the value of current number of users is got the counter that to be 2011-09-07 11: 00 report to 2011-09-07 for 15 minutes during this period of time at 11 o'clock.
Description based on above-mentioned and processing, as shown in Figure 1, according to the cutting off rate of the embodiment of the present invention, determine that method comprises following processing:
Step 101, the number of users of the increase that the foreground of base station reports according to the chain of command of base station and the number of users of minimizing, adopt the cumulative mode of summation to be recorded in the number of users of abnormal release in the sampling period and the number of users that success is set up, and calculate active user's number of real-time online within the sampling period;
That is to say, in step 101, need to be accumulated in the sum of the abnormal number of users discharging in this sampling period and the sum of the number of users that success is set up, for example, UE1 extremely discharges after successful connection, and UE1 is not only after successful connection but also extremely discharge, now subsequently, the abnormal number of users discharging is 2, and the number of users that success is set up is also 2, and for active user's number, the active user's number that needs real-time online in the calculating sampling cycle, for example, within a sampling period, there is UE1, UE2, UE3, UE4, these 5 user's successful connections of UE5 are in line states, active user's number is 5, if within this sampling period, there are again 2 user UE2, UE3 discharges extremely, there is user UE6 successful connection to be in line states, active user's number is 5-2+1=4, within the next sampling period, if there is 1 user UE5 extremely to discharge, there are 2 user UE7, UE8 successful connection is in line states, active user's number is 4-1+2=5.
Step 102, the sampling period then after, foreground adopts the cumulative mode of summation that the number of users of the number of users of the abnormal release in this sampling period and success foundation is write respectively to abnormal releasing user counter and is successfully established subscriber's meter, and adopts the mode that covers former data that active user's number in this sampling period is write to active user's counter;
For example, before foreground writes the number of users of the number of users of the abnormal release in this sampling period and success foundation respectively in abnormal releasing user counter and is successfully established subscriber's meter, abnormal releasing user counter is respectively 4 and 5 with the counting that is successfully established subscriber's meter, the number of users that the number of users of the abnormal release in this sampling period and success are set up is respectively 2 and 1, foreground adopts the cumulative mode of summation that the number of users of the number of users of the abnormal release in this sampling period and success foundation is write respectively to abnormal releasing user counter and is successfully established after subscriber's meter, the value of abnormal releasing user counter is 4+2=6, the value that is successfully established subscriber's meter is 5+1=6.
For active user's counter, before active user's number in this sampling period is write, the value of active user's counter is 5, active user's number in this sampling period is 8, when active user's number in this sampling period is write to active user's counter, use 8 to replace 5, after active user's number in this sampling period is write to active user's counter, the value of active user's counter is 8.
Step 103, report cycle then after, foreground is synchronized to webmaster by abnormal releasing user counter, the data that are successfully established on subscriber's meter and active user's counter;
In step 103, measuring object can be take as unit in foreground, and abnormal releasing user counter, the data that are successfully established on subscriber's meter and active user's counter are synchronized to webmaster.Wherein, measurement unit comprises: community, network element etc.
Step 104, webmaster is determined the cutting off rate of this report cycle according to active user's number of the number of users of the abnormal release of this report cycle and the successful number of users of setting up and a upper report cycle.
Particularly, in step 104, the number of users of the abnormal release of cutting off rate=this report cycle of this report cycle/(number of users of the successful foundation of active user's number+this report cycle of a upper report cycle).
That is to say, if the number of users that the number of users of the abnormal release of this report cycle that foreground reports is 3, success is set up is 5, active user's number is 6, active user's number of a upper report cycle is 4, cutting off rate=3/ of this report cycle (4+5).When calculating the cutting off rate of next report cycle, need to call active user's number 6 of this report cycle.
Preferably, in embodiments of the present invention, base station is the evolved base station (evolved Node B, referred to as eNB) in LET system.
Fig. 2 is the schematic diagram that the eNB of the embodiment of the present invention processes, as shown in Figure 2, and platform property module and the OMC of the chain of command of eNB, eNB.
ENB take below as example, the technique scheme of the embodiment of the present invention is described.Fig. 3 is the process chart of the ENB performance sampling MOD of the embodiment of the present invention, as shown in Figure 3:
Step 1, the chain of command of eNB, when having number of users to increase, reports and adds 1 foreground (platform property module) to eNB, when having number of users to reduce, reports and subtracts the 1 platform property module to eNB.
Step 2, the platform property module of eNB is responsible for the periodic sampling of number of users.Chain of command reports the added-time, and the data in this sampling period are added to 1, reports while subtracting, and the data in sampling period are subtracted to 1.After sample clock generator is overtime, the value in this sampling period is write in active user's counter.
Step 3, when reporting the moment to arrive, measuring object be take as unit reports OMC by performance collection data in the foreground of eNB, if reported constantly, does not arrive, and performs step 2.
Fig. 4 is the process chart that the oldest value of OMC performance of the embodiment of the present invention gathers, as shown in Figure 4, measuring object be take after unit reports OMC by performance collection data in foreground at eNB, OMC puts performance collection data in storage, and according to granularity, the performance collection data in storehouse is gathered, if the mode that gathers for the oldest value mode, is got this granularity, the last value of granularity that reports finally gathers value as this counter.
Embodiment 1
With under the object of community, the realization flow situation of radio resource control (Radio Resource Control, referred to as RRC) cutting off rate is example, and technique scheme of the present invention is illustrated below.Suppose that the sampling MOD cycle is 30S.Between OMC and foreground, report cycle is 15 minutes.Concrete implementation step is as follows:
Step 1, has 5 user UE1 to UE5 at certain day 11 o'clock to 11: 15, to connect (Attach) success.
Wherein, UE1 is Attach success between 11 o'clock to 11: 30 seconds, and chain of command reports report of user number to add 1 event to platform property module.Platform property module is 1 in the sampled value of this sampling granularity.Sample clock generator is overtime, and sampled value 1 is write in active user's counter, and Counter Value is 1.
Between 11: 30 seconds to 11: 10, do not have user to access, sampling is always 1, and Counter Value is 1.
11: 10 assign between 11: 10: 30, UE2 to UE4 Attach success.Chain of command has reported 4 numbers of users to add 1 event to platform property module.Platform property module adds 4 times in this sampling granularity, so sampled value is 5.Sample clock generator is overtime, and sampled value is write in active user's counter, and Counter Value is 5.
Before 11: 15, then do not have user to access, the Counter Value of active user's number is always 5.
Step 2,11: 15, report constantly and arrive, foreground synchrodata is to OMC webmaster.Wherein the current RRC number of users counters count value of this granularity is 5, and it is 0 that this granularity discharges number of times statistical value extremely, and it is 5 that this granularity is successfully set up number statistical value.
According to cutting off rate Index Formula=abnormal number of users discharging/(number of users that current number of users+success is set up); The cutting off rate index of this granularity is 0/ (0+5)=0.(current RRC number of users is 0, is because this Granular Computing value is got the value of last granularity).
Step 3,11: 15 to 11: 30: UE1 and UE2 are because RLC ERROR IND causes extremely having gone offline.
Wherein, UE1 is because RLC ERROR IND causes extremely having gone offline between 11: 15 to 11: 15: 30, and chain of command reports report of user number to subtract 1 event to platform property module.Platform property module subtracts 1 in this sampling granularity, so sampled value is 4.Sample clock generator is overtime, and sampled value is write in active user's counter, and Counter Value is 4.
Between 11: 15 minutes 30 seconds 1, do not have user to change, sampling is always 4, and Counter Value is 4.
11: 20 assign between 11: 20: 30, and UE2 is because RLC ERROR IND causes extremely having gone offline.Chain of command reports report of user number to subtract 1 event to platform property module.Platform property module subtracts 1 in this sampling granularity, so sampled value is 3.Sample clock generator is overtime, and sampled value is write in active user's counter.Counter Value is 3.
Before 11: 30, then do not have user to access, the Counter Value of active user's number is always 3.
Step 4,11: 30, report constantly and arrive, foreground synchrodata is to OMC webmaster.Wherein the current RRC number of users counters count value of this granularity is 3, and it is 2 that this granularity discharges number of times statistical value extremely, and it is 0 that this granularity is successfully set up number statistical value.
According to cutting off rate Index Formula=abnormal number of users discharging/(number of users that current number of users+success is set up); The cutting off rate index of this granularity is 2/ (5+0)=40%.(current RRC number of users is 5, is because this Granular Computing value is got the value of last granularity).
Embodiment 2
Below with under the object of community, the general continental rise wireless access network RAB of evolution (Evolved Universal Terrestrial Radio Access Network Radio Access Bear, referred to as ERAB) the realization flow situation of cutting off rate is example, technical scheme to the embodiment of the present invention is elaborated, suppose that the sampling MOD cycle is 30S, between OMC and foreground, report cycle is 15 minutes, and concrete implementation step is as follows:
Step 1, has 5 user UE1 to UE5 successful at 11 o'clock to 11: 15 Attach of certain day, and each user sets up a default bearing.
Wherein, UE1 is Attach success between 11 and 11: 30 seconds, and chain of command reports ERAB number to add 1 event to platform property module.Platform property module is 1 in the sampled value of this sampling granularity.Sample clock generator is overtime, and sampled value 1 is write in current ERAB counter, and Counter Value is 1.
Between 11: 30 seconds to 11: 10, do not have user to access, sampling is always 1, and Counter Value is 1.
11: 10 assign between 11: 10: 30, UE2 to UE4 Attach success.Chain of command has reported 4 ERAB numbers to add 1 event to platform property module.Platform property module adds 4 times in this sampling granularity, so sampled value is 5.Sample clock generator is overtime, and sampled value is write in current ERAB counter, and Counter Value is 5.
Before 11: 15, then do not have user to access, the Counter Value of current ERAB number is always 5.
Step 2,11: 15, report constantly and arrive, foreground synchrodata is to OMC webmaster.Wherein the current ERAB number counters count value of this granularity is 5, and it is 0 that this granularity discharges ERAB several statistical values extremely, and this granularity is successfully set up ERAB, and to count statistical value be 5.
According to cutting off rate Index Formula=abnormal ERAB number discharging/(the ERAB number that current ERAB number+success is set up); The ERAB cutting off rate index of this granularity is 0/ (0+5)=0.(current ERAB number of users is 0, is because this Granular Computing value is got the value of last granularity).
Step 3,11: 15 to 11: 30: UE1 and UE2 are because RLC ERROR IND causes extremely having gone offline.
Wherein, UE1 11: 15 and 11: 15: 30 between because RLC ERROR IND causes extremely having gone offline, chain of command reports ERAB number to subtract 1 event to platform property module.Platform property module subtracts 1 in this sampling granularity, so sampled value is 4.Sample clock generator is overtime, and sampled value is write in current ERAB counter.Counter Value is 4.
Between 11: 15 minutes 30 seconds 1, do not have user to change, sampling is always 4.Counter Value is 4.
11: 20 assign between 11: 20: 30, and UE2 is because RLC ERROR IND causes extremely having gone offline.Chain of command reports ERAB number to subtract 1 event to platform property module.Platform property module subtracts 1 in this sampling granularity, so sampled value is 3.Sample clock generator is overtime, and sampled value is write in current ERAB counter, and Counter Value is 3.
Before 11: 30, then there is no ERAB access, the Counter Value of current ERAB number is always 3.
Step 4,11: 30, report constantly and arrive, foreground synchrodata is to OMC webmaster.Wherein the current ERAB counter statistical value of this granularity is 3, and it is 2 that this granularity discharges number of times statistical value extremely, and it is 0 that this granularity is successfully set up ERAB number statistical value.
According to cutting off rate Index Formula=abnormal ERAB number discharging/(the ERAB number that current ERAB number+success is set up); The cutting off rate index of this granularity is 2/ (5+0)=40% (current ERAB number is 5, is because this Granular Computing value is got the value of last granularity).
In sum, technical scheme by means of the embodiment of the present invention, by online active user's number at last granularity end being introduced to the cutting off rate index of next granularity, calculate, solve in prior art cutting off rate under special circumstances and be greater than 100% and problem that the cutting off rate accuracy that causes reduces, can under any circumstance guarantee the accuracy of cutting off rate.
Device embodiment
According to embodiments of the invention, provide a kind of cutting off rate to determine system, Fig. 5 is the structural representation that the cutting off rate of the embodiment of the present invention is determined system, as shown in Figure 5, according to the cutting off rate of the embodiment of the present invention, determine that system comprises base station foreground 50 and webmaster 52, wherein, base station foreground 50 comprises: sampling module 502, processing module 504, reporting module 506, below be described in detail the modules of the embodiment of the present invention.
First, the foreground 50 of base station need to be handled as follows:
Number of users for abnormal release: all modes of gathering that need to abnormal releasing user counter are set to summing mode, and wherein, all modes of gathering comprise: foreground 50 account forms, 52 times of webmaster are gathered mode, and mode is gathered in webmaster 52 spaces;
The number of users of setting up for success: all modes of gathering that need to be successfully established subscriber's meter are set to summing mode, and wherein, all modes of gathering comprise: foreground 50 account forms, 52 times of webmaster are gathered mode, and mode is gathered in webmaster 52 spaces;
For current number of users: foreground 50 account forms that need to the active user's counter MOD mode that is set to sample, 52 time of the webmaster mode of gathering is set to ask the oldest value mode, and the webmaster 52 space modes of gathering are set to summing mode.
Wherein, sampling MOD mode is specially: sampling refers to that the foreground 50 (platform property statistical module) of base station periodically counts statistical phenomeon according to the chain of command of base station (business module) report of user, adds and subtracts calculating, obtains the value in sampling period.MOD refers to after each sample clock generator is overtime, and the value that this cycle is calculated writes in counter, as the value of this counter, covers original value all the time by up-to-date value.
Ask the oldest value mode to be: gathering of OMC be take granularity as unit, have 15 minutes granularities, 30 minutes granularities, 1 hour granularity, 1 day granularity, 1 week granularity, January granularity etc.When the definition of the oldest value is this Granular Computing index, the mode that gathers is got the value that last granularity is preserved for the counter of old value.As: calculate 2011-09-07 11: 15 to 11: 30 cutting off rates during this period of time of 2011-09-07, the value of current number of users is got the counter that to be 2011-09-07 11: 00 report to 2011-09-07 for 15 minutes during this period of time at 11 o'clock.
Sampling module 502, for the number of users of increase and the number of users of minimizing reporting according to the chain of command of base station, adopt the cumulative mode of summation to be recorded in the number of users of abnormal release in the sampling period and the number of users that success is set up, and calculate active user's number of real-time online within the sampling period;
That is to say, sampling module 502 need to be accumulated in the sum of the abnormal number of users discharging in this sampling period and the sum of the number of users that success is set up, for example, UE1 extremely discharges after successful connection, UE1 is not only after successful connection but also extremely discharge subsequently, now, the abnormal number of users discharging is 2, and the number of users that success is set up is also 2, and for active user's number, the active user's number that needs real-time online in the calculating sampling cycle, for example, within a sampling period, there is UE1, UE2, UE3, UE4, these 5 user's successful connections of UE5 are in line states, active user's number is 5, if within this sampling period, there are again 2 user UE2, UE3 discharges extremely, there is user UE6 successful connection to be in line states, active user's number is 5-2+1=4, within the next sampling period, if there is 1 user UE5 extremely to discharge, there are 2 user UE7, UE8 successful connection is in line states, active user's number is 4-1+2=5.
Processing module 504, for the sampling period then after, adopt the cumulative mode of summation that the number of users of the number of users of the abnormal release in this sampling period and success foundation is write respectively to abnormal releasing user counter and is successfully established subscriber's meter, and adopt the mode that covers former data that active user's number in this sampling period is write to active user's counter;
For example, before processing module 504 writes the number of users of the number of users of the abnormal release in this sampling period and success foundation respectively in abnormal releasing user counter and is successfully established subscriber's meter, abnormal releasing user counter is respectively 4 and 5 with the counting that is successfully established subscriber's meter, the number of users that the number of users of the abnormal release in this sampling period and success are set up is respectively 2 and 1, foreground 50 adopts the cumulative mode of summation that the number of users of the number of users of the abnormal release in this sampling period and success foundation is write respectively to abnormal releasing user counter and is successfully established after subscriber's meter, the value of abnormal releasing user counter is 4+2=6, the value that is successfully established subscriber's meter is 5+1=6.
For active user's counter, before active user's number in this sampling period is write, the value of active user's counter is 5, active user's number in this sampling period is 8, when active user's number in this sampling period is write to active user's counter, use 8 to replace 5, after active user's number in this sampling period is write to active user's counter, the value of active user's counter is 8.
Reporting module 506, for report cycle then after, abnormal releasing user counter, the data that are successfully established on subscriber's meter and active user's counter are synchronized to webmaster 52;
Reporting module 506 can be take measuring object as unit, and abnormal releasing user counter, the data that are successfully established on subscriber's meter and active user's counter are synchronized to webmaster 52.Wherein, measurement unit comprises: community, network element etc.
Webmaster 52, for determining the cutting off rate of this report cycle according to active user's number of the number of users of the abnormal release of this report cycle and the successful number of users of setting up and a upper report cycle.
Particularly, the number of users of the abnormal release of cutting off rate=this report cycle of this report cycle/(number of users of the successful foundation of active user's number+this report cycle of a upper report cycle).
That is to say, if the number of users that the number of users of the abnormal release of this report cycle that foreground 50 reports is 3, success is set up is 5, active user's number is 6, active user's number of a upper report cycle is 4, cutting off rate=3/ of this report cycle (4+5).When calculating the cutting off rate of next report cycle, need to call active user's number 6 of this report cycle.
Preferably, in embodiments of the present invention, base station is the eNB in LET system.
Fig. 2 is the schematic diagram that the eNB of the embodiment of the present invention processes, as shown in Figure 2, and platform property module and the OMC of the chain of command of eNB, eNB.
ENB take below as example, the technique scheme of the embodiment of the present invention is described.Fig. 3 is the process chart of the ENB performance sampling MOD of the embodiment of the present invention, as shown in Figure 3:
Step 1, the chain of command of eNB, when having number of users to increase, reports and adds 1 foreground (platform property module) to eNB, when having number of users to reduce, reports and subtracts the 1 platform property module to eNB.
Step 2, the platform property module of eNB is responsible for the periodic sampling of number of users.Chain of command reports the added-time, and the data in this sampling period are added to 1, reports while subtracting, and the data in sampling period are subtracted to 1.After sample clock generator is overtime, the value in this sampling period is write in active user's counter.
Step 3, when reporting the moment to arrive, measuring object be take as unit reports OMC by performance collection data in the foreground of eNB, if reported constantly, does not arrive, and performs step 2.
Fig. 4 is the process chart that the oldest value of OMC performance of the embodiment of the present invention gathers, as shown in Figure 4, measuring object be take after unit reports OMC by performance collection data in foreground at eNB, OMC puts performance collection data in storage, and according to granularity, the performance collection data in storehouse is gathered, if the mode that gathers for the oldest value mode, is got this granularity, the last value of granularity that reports finally gathers value as this counter.
Embodiment 1
With under the object of community, the realization flow situation of radio resource control (Radio Resource Control, referred to as RRC) cutting off rate is example, and technique scheme of the present invention is illustrated below.Suppose that the sampling MOD cycle is 30S.Between OMC and foreground 50, report cycle is 15 minutes.Concrete implementation step is as follows:
Step 1, has 5 user UE1 to UE5 at certain day 11 o'clock to 11: 15, to connect (Attach) success.
Wherein, UE1 is Attach success between 11 o'clock to 11: 30 seconds, and chain of command reports report of user number to add 1 event to platform property module.Platform property module is 1 in the sampled value of this sampling granularity.Sample clock generator is overtime, and sampled value 1 is write in active user's counter, and Counter Value is 1.
Between 11: 30 seconds to 11: 10, do not have user to access, sampling is always 1, and Counter Value is 1.
11: 10 assign between 11: 10: 30, UE2 to UE4 Attach success.Chain of command has reported 4 numbers of users to add 1 event to platform property module.Platform property module adds 4 times in this sampling granularity, so sampled value is 5.Sample clock generator is overtime, and sampled value is write in active user's counter, and Counter Value is 5.
Before 11: 15, then do not have user to access, the Counter Value of active user's number is always 5.
Step 2,11: 15, report constantly and arrive, foreground 50 synchrodatas are to OMC webmaster 52.Wherein the current RRC number of users counters count value of this granularity is 5, and it is 0 that this granularity discharges number of times statistical value extremely, and it is 5 that this granularity is successfully set up number statistical value.
According to cutting off rate Index Formula=abnormal number of users discharging/(number of users that current number of users+success is set up); The cutting off rate index of this granularity is 0/ (0+5)=0.(current RRC number of users is 0, is because this Granular Computing value is got the value of last granularity).
Step 3,11: 15 to 11: 30: UE1 and UE2 are because RLC ERROR IND causes extremely having gone offline.
Wherein, UE1 is because RLC ERROR IND causes extremely having gone offline between 11: 15 to 11: 15: 30, and chain of command reports report of user number to subtract 1 event to platform property module.Platform property module subtracts 1 in this sampling granularity, so sampled value is 4.Sample clock generator is overtime, and sampled value is write in active user's counter, and Counter Value is 4.
Between 11: 15 minutes 30 seconds 1, do not have user to change, sampling is always 4, and Counter Value is 4.
11: 20 assign between 11: 20: 30, and UE2 is because RLC ERROR IND causes extremely having gone offline.Chain of command reports report of user number to subtract 1 event to platform property module.Platform property module subtracts 1 in this sampling granularity, so sampled value is 3.Sample clock generator is overtime, and sampled value is write in active user's counter.Counter Value is 3.
Before 11: 30, then do not have user to access, the Counter Value of active user's number is always 3.
Step 4,11: 30, report constantly and arrive, foreground 50 synchrodatas are to OMC webmaster 52.Wherein the current RRC number of users counters count value of this granularity is 3, and it is 2 that this granularity discharges number of times statistical value extremely, and it is 0 that this granularity is successfully set up number statistical value.
According to cutting off rate Index Formula=abnormal number of users discharging/(number of users that current number of users+success is set up); The cutting off rate index of this granularity is 2/ (5+0)=40%.(current RRC number of users is 5, is because this Granular Computing value is got the value of last granularity).
Embodiment 2
With under the object of community, the realization flow situation of ERAB cutting off rate is example, and the technical scheme of the embodiment of the present invention is elaborated below, supposes that the sampling MOD cycle is 30S, and between OMC and foreground 50, report cycle is 15 minutes, and concrete implementation step is as follows:
Step 1, has 5 user UE1 to UE5 successful at 11 o'clock to 11: 15 Attach of certain day, and each user sets up a default bearing.
Wherein, UE1 is Attach success between 11 and 11: 30 seconds, and chain of command reports ERAB number to add 1 event to platform property module.Platform property module is 1 in the sampled value of this sampling granularity.Sample clock generator is overtime, and sampled value 1 is write in current ERAB counter, and Counter Value is 1.
Between 11: 30 seconds to 11: 10, do not have user to access, sampling is always 1, and Counter Value is 1.
11: 10 assign between 11: 10: 30, UE2 to UE4 Attach success.Chain of command has reported 4 ERAB numbers to add 1 event to platform property module.Platform property module adds 4 times in this sampling granularity, so sampled value is 5.Sample clock generator is overtime, and sampled value is write in current ERAB counter, and Counter Value is 5.
Before 11: 15, then do not have user to access, the Counter Value of current ERAB number is always 5.
Step 2,11: 15, report constantly and arrive, foreground 50 synchrodatas are to OMC webmaster 52.Wherein the current ERAB number counters count value of this granularity is 5, and it is 0 that this granularity discharges ERAB several statistical values extremely, and this granularity is successfully set up ERAB, and to count statistical value be 5.
According to cutting off rate Index Formula=abnormal ERAB number discharging/(the ERAB number that current ERAB number+success is set up); The ERAB cutting off rate index of this granularity is 0/ (0+5)=0.(current ERAB number of users is 0, is because this Granular Computing value is got the value of last granularity).
Step 3,11: 15 to 11: 30: UE1 and UE2 are because RLC ERROR IND causes extremely having gone offline.
Wherein, UE1 11: 15 and 11: 15: 30 between because RLC ERROR IND causes extremely having gone offline, chain of command reports ERAB number to subtract 1 event to platform property module.Platform property module subtracts 1 in this sampling granularity, so sampled value is 4.Sample clock generator is overtime, and sampled value is write in current ERAB counter.Counter Value is 4.
Between 11: 15 minutes 30 seconds 1, do not have user to change, sampling is always 4.Counter Value is 4.
11: 20 assign between 11: 20: 30, and UE2 is because RLC ERROR IND causes extremely having gone offline.Chain of command reports ERAB number to subtract 1 event to platform property module.Platform property module subtracts 1 in this sampling granularity, so sampled value is 3.Sample clock generator is overtime, and sampled value is write in current ERAB counter, and Counter Value is 3.
Before 11: 30, then there is no ERAB access, the Counter Value of current ERAB number is always 3.
Step 4,11: 30, report constantly and arrive, foreground 50 synchrodatas are to OMC webmaster 52.Wherein the current ERAB counter statistical value of this granularity is 3, and it is 2 that this granularity discharges number of times statistical value extremely, and it is 0 that this granularity is successfully set up ERAB number statistical value.
According to cutting off rate Index Formula=abnormal ERAB number discharging/(the ERAB number that current ERAB number+success is set up); The cutting off rate index of this granularity is 2/ (5+0)=40% (current ERAB number is 5, is because this Granular Computing value is got the value of last granularity).
In sum, technical scheme by means of the embodiment of the present invention, by online active user's number at last granularity end being introduced to the cutting off rate index of next granularity, calculate, solve in prior art cutting off rate under special circumstances and be greater than 100% and problem that the cutting off rate accuracy that causes reduces, can under any circumstance guarantee the accuracy of cutting off rate.
Although be example object, the preferred embodiments of the present invention are disclosed, it is also possible those skilled in the art will recognize various improvement, increase and replacement, therefore, scope of the present invention should be not limited to above-described embodiment.

Claims (8)

1. cutting off rate is determined a method, it is characterized in that, comprising:
The number of users of the increase that the foreground of base station reports according to the chain of command of described base station and the number of users of minimizing, adopt the cumulative mode of summation to be recorded in the number of users of abnormal release in the sampling period and the number of users that success is set up, and calculate active user's number of real-time online within the described sampling period;
The described sampling period then after, described foreground adopts the cumulative mode of summation that the number of users of the number of users of the described abnormal release in this sampling period and described success foundation is write respectively to abnormal releasing user counter and is successfully established subscriber's meter, and adopts the mode that covers former data that described active user's number in this sampling period is write to active user's counter;
Report cycle then after, described foreground by described abnormal releasing user counter, described in the data that are successfully established on subscriber's meter and described active user's counter be synchronized to webmaster;
Described webmaster is determined the cutting off rate of this report cycle according to the number of users of the abnormal release of this report cycle, the number of users of success foundation and active user's number of a upper report cycle, wherein, the number of users of the abnormal release of cutting off rate=this report cycle of this report cycle/(number of users of the successful foundation of active user's number+this report cycle of a upper report cycle).
2. the method for claim 1, is characterized in that, described foreground by described abnormal releasing user counter, described in be successfully established data on subscriber's meter and described active user's counter and be synchronized to webmaster and specifically comprise:
Measuring object be take as unit in described foreground, by described abnormal releasing user counter, described in the data that are successfully established on subscriber's meter and described active user's counter be synchronized to webmaster.
3. method as claimed in claim 2, is characterized in that, described measurement unit comprises: community, network element.
4. the method for claim 1, is characterized in that, described base station is the evolved base station in long evolving system.
5. cutting off rate is determined a system, it is characterized in that, comprises base station foreground and webmaster, and wherein, base station foreground comprises:
Sampling module, for the number of users of increase and the number of users of minimizing reporting according to the chain of command of described base station, adopt the cumulative mode of summation to be recorded in the number of users of abnormal release in the sampling period and the number of users that success is set up, and calculate active user's number of real-time online within the described sampling period;
Processing module, for the described sampling period then after, adopt the cumulative mode of summation that the number of users of the number of users of the described abnormal release in this sampling period and described success foundation is write respectively to abnormal releasing user counter and is successfully established subscriber's meter, and adopt the mode that covers former data that described active user's number in this sampling period is write to active user's counter;
Reporting module, for report cycle then after, by described abnormal releasing user counter, described in the data that are successfully established on subscriber's meter and described active user's counter be synchronized to webmaster;
Described webmaster, for determining the cutting off rate of this report cycle according to the number of users of the abnormal release of this report cycle, the number of users of success foundation and active user's number of a upper report cycle;
Described webmaster is specifically for the cutting off rate of determining this report cycle by following formula:
The number of users of the abnormal release of cutting off rate=this report cycle of this report cycle/(number of users of the successful foundation of active user's number+this report cycle of a upper report cycle).
6. device as claimed in claim 5, is characterized in that, reporting module specifically for:
Take measuring object as unit, by described abnormal releasing user counter, described in the data that are successfully established on subscriber's meter and described active user's counter be synchronized to webmaster.
7. device as claimed in claim 6, is characterized in that, described measurement unit comprises: community, network element.
8. device as claimed in claim 5, is characterized in that, described base station is the evolved base station in long evolving system.
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