CN105163321B - A kind of data traffic localization method and device - Google Patents
A kind of data traffic localization method and device Download PDFInfo
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- CN105163321B CN105163321B CN201410242729.XA CN201410242729A CN105163321B CN 105163321 B CN105163321 B CN 105163321B CN 201410242729 A CN201410242729 A CN 201410242729A CN 105163321 B CN105163321 B CN 105163321B
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Abstract
The embodiment of the invention discloses a kind of data traffic localization methods, will be divided into more than one timeslice analysis time, obtain the user information that data traffic is generated in each timeslice；The data traffic that user generates in each timeslice is navigated in grid, and navigates to the confidence level of the data traffic in grid；Obtain data traffic and confidence level of each grid within analysis time.The embodiment of the present invention also accordingly discloses a kind of data traffic positioning device, comprising: division module, for more than one timeslice will to be divided into analysis time；First obtains module, for obtaining the user information for generating data traffic in each timeslice；Data traffic locating module, the data traffic for generating user in each timeslice navigate in grid, and navigate to the confidence level of the data traffic in grid；Second obtains module, for obtaining data traffic and confidence level of each grid within analysis time.
Description
Technical field
The present invention relates to wireless communication technique more particularly to a kind of data traffic localization methods and device.
Background technique
In global system for mobile communications (Global System for Mobile communication, GSM), 3G, nothing
Line local area network (Wireless Local Area Networks, WLAN), long term evolution (Long Term Evolution,
) etc. LTE in multi-network cooperatives, the shunting of 2G high flow capacity, high load capacity cell is one of target.By reasonably planning and building
WLAN, LTE website realize that effective shunting of 2G cell is important means and practical difficulties.Because WLAN, LTE website cover
Lid range is less than 2G cell, and when Bus stop planning needs to analyze the data service flow in region, and carries out grid accurate positioning,
Service traffics are being narrower than physical and chemical presentation in cell range, are assisting the high flow volume region and high value of operation maintenance personnel positioning network
Region, to instruct the construction addressing of WLAN, LTE website.
By acquiring the signaling of relevant interface (such as Gb, Gn), the cell information of service traffics generation can be obtained.To accurate
Position more fine-grained grid (such as 100mx100m), need by measurement report (Measurement Report, MR) or other
More accurate location information.With circuit switching (Circuit Switch, CS) business difference, the packet switch of 2G network
(Packet Switch, PS) service connection state does not report MR signaling, and it is no longer suitable to be usually used in the pinpoint MR positioning mode of CS business
With currently, the data traffic locating scheme for being used for PS business is not yet proposed, to be unfavorable for high flow volume region and high value region
Positioning, lead to not provide effective reference for the construction addressing of WLAN, LTE website.
Summary of the invention
In view of this, the embodiment of the present invention provides to solve existing technical problem:
A kind of data traffic localization method will be divided into more than one timeslice analysis time, this method comprises:
Obtain the user information that data traffic is generated in each timeslice；
Grid positioning is carried out based on the user for generating data traffic in each timeslice, user is generated in each timeslice
Data traffic navigates in grid, and navigates to the confidence level of the data traffic in grid；
Obtain data traffic and confidence level of each grid within analysis time.
Preferably, carrying out grid positioning based on the user for generating data traffic in timeslice, and navigate in grid
Data traffic confidence level, comprising:
Judge whether the user has occurred voice service in the timeslice, if so, according to the user in institute
The voice service monitoring report MR progress grid positioning for betiding same cell in timeslice is stated, and navigates to the number in grid
According to the confidence level of flow；Otherwise, the voice service history MR of same cell is betided before the timeslice according to the user
Grid positioning is carried out, and navigates to the confidence level of the data traffic in grid.
Determine preferably, the voice service MR for betiding same cell in the timeslice according to user carries out grid
Position, and navigate to the confidence level of the data traffic in grid, comprising:
According to the MR quantity in grid corresponding under cell, the user in the timeslice is generated in the cell
Data traffic be prorated under the cell in the corresponding grid of MR, the data traffic confidence being assigned in grid
Degree is set as the first confidence level.
Preferably, the voice service history MR for betiding same cell before the timeslice according to user carries out grid
Lattice positioning, and navigate to the confidence level of the data traffic in grid, comprising:
According to the historical act track of the user, the voice service that whether there is same cell before the timeslice is judged
Effectively substitution MR, if it does, being generated the user in the timeslice in the cell according to effective substitution MR quantity
Data traffic be prorated under the cell and effectively substitute in the corresponding grid of MR, the data being assigned in grid
Flow confidence level is set as the second confidence level；If it does not, the user in the timeslice is generated in the cell
Data traffic be evenly distributed in all grids under the cell, the data traffic confidence level being assigned in grid is set
It is set to third confidence level, wherein the third confidence level is not more than the second confidence level, and second confidence level is set no more than first
Reliability.
Preferably, the data traffic and confidence level for obtaining each grid within analysis time, comprising:
Grid K grid K in data traffic+timeslice 2 of grid K in data traffic=timeslice 1 within analysis time
Data traffic+... the data traffic of grid K in+timeslice n；
Confidence level of the grid K within analysis time=(confidence level × timeslice 1 of the data traffic of grid K in timeslice 1
In data traffic+timeslice 2 of interior grid K in confidence level × timeslice 2 of the data traffic of grid K grid K data traffic
+ ... in+timeslice n in the confidence level of the data traffic of grid K × timeslice n grid K data traffic)/grid K analyzing
Data traffic in time, wherein n is the number for analysis time being divided into timeslice, and K=1,2 ... ..., N, N is selected stream
Measure the grid sum of analyzed area.
Preferably, the data traffic confidence level being assigned in grid is set as the second confidence level, comprising:
According to the mobility of the user, the data traffic confidence level that is assigned to described in setting in grid.
Preferably, this method further include: the mobility of user is determined based on the history active cell of user, specific:
User's history active cell is analyzed, if the time that user occupies same cell in the first preset time is more than the
Two preset times, it is determined that the user is first kind user；
If user occupies the time of two or three cells more than the 4th preset time in third preset time, and
The distance between described cell is greater than pre-determined distance, it is determined that the user is the second class user；
If user occupies three or more cells in the 5th preset time, and the time for occupying same cell is no more than
6th preset time, it is determined that the user is third class user,
The mobility according to the user, the data traffic confidence level being assigned to described in setting in grid, comprising:
The data traffic confidence level of the first kind user of setting is not less than the data traffic confidence level of the second class user, setting
The second class user data traffic confidence level be not less than third class user data traffic confidence level.
Preferably, the historical act track according to the user, judges to whether there is before the timeslice with small
The voice service in area effectively substitutes MR, comprising:
According to the mobility of the user and the historical act track of the user, judge before the timeslice whether
Voice service in the presence of same cell effectively substitutes MR, specifically:
For first kind user, it is effective that voice service is found in current time the piece forward period of the 7th preset time
MR is substituted, when finding first timeslice existed with cell voice service MR, determines the same cell voice in the timeslice
Business MR is that voice service effectively substitutes MR；
For the second class user, before 24 hours before period corresponding with current time piece and the period and/
Or the period of the 8th preset time covering later, it finds voice service and effectively substitutes MR；
For third class user, it is effective that voice service is found in current time the piece forward period of the 9th preset time
MR is substituted, when finding first timeslice existed with cell voice service MR, determines the same cell voice in the timeslice
Business MR is that voice service effectively substitutes MR.
A kind of data traffic positioning device, comprising: division module, first obtain module, data traffic locating module, second
Obtain module；Wherein,
The division module, for more than one timeslice will to be divided into analysis time；
Described first obtains module, for obtaining the user information for generating data traffic in each timeslice；
The data traffic locating module, it is fixed for carrying out grid based on the user for generating data traffic in each timeslice
Position, the data traffic that user generates in each timeslice is navigated in grid, and navigate to the data traffic in grid
Confidence level；
Described second obtains module, for obtaining data traffic and confidence level of each grid within analysis time.
Preferably, the data traffic locating module, is specifically used for:
Judge whether the user has occurred voice service in the timeslice, if so, according to the user in institute
The voice service monitoring report MR progress grid positioning for betiding same cell in timeslice is stated, and navigates to the number in grid
According to the confidence level of flow；Otherwise, the voice service history MR of same cell is betided before the timeslice according to the user
Grid positioning is carried out, and navigates to the confidence level of the data traffic in grid.
Preferably, the data traffic locating module, specifically for inciting somebody to action according to the MR quantity in grid corresponding under cell
It is corresponding that the data traffic that the user generates in the cell in the timeslice is prorated to MR under the cell
In grid, the data traffic confidence level being assigned in grid is set as the first confidence level.
Preferably, the data traffic locating module judges institute specifically for the historical act track according to the user
The voice service that whether there is same cell before stating timeslice effectively substitutes MR, if it does, according to effective substitution MR quantity, it will
The data traffic that the user generates in the cell in the timeslice is prorated under the cell and effectively substitutes
In the corresponding grid of MR, the data traffic confidence level being assigned in grid is set as the second confidence level；If it does not, will
The data traffic that the user generates in the cell in the timeslice is evenly distributed to all grids under the cell
In, the data traffic confidence level being assigned in grid is set as third confidence level, wherein the third confidence level is not more than
Second confidence level, second confidence level are not more than the first confidence level.
Preferably, described second obtains module, it is specifically used for calculating:
Grid K grid K in data traffic+timeslice 2 of grid K in data traffic=timeslice 1 within analysis time
Data traffic+... the data traffic of grid K in+timeslice n；
Confidence level of the grid K within analysis time=(confidence level × timeslice 1 of the data traffic of grid K in timeslice 1
In data traffic+timeslice 2 of interior grid K in confidence level × timeslice 2 of the data traffic of grid K grid K data traffic
+ ... in+timeslice n in the confidence level of the data traffic of grid K × timeslice n grid K data traffic)/grid K analyzing
Data traffic in time, wherein n is the number for analysis time being divided into timeslice, and K=1,2 ... ..., N, N is selected stream
Measure the grid sum of analyzed area.
Preferably, the distribution is arranged specifically for the mobility according to the user in the data traffic locating module
Data traffic confidence level into grid.
Preferably, the device further includes mobility determination module,
The mobility determination module, for analyzing user's history active cell, when user accounts in the first preset time
When being more than the second preset time with the time of same cell, determine that the user is first kind user；When user is default in third
The time of two or three cells is occupied in time more than the 4th preset time, and the distance between described cell is greater than default
Apart from when, determine the user be the second class user；When user occupies three or more cells, and occupancy in the 5th preset time
When the time of same cell is no more than six preset times, determine that the user is third class user,
The data traffic locating module is assigned to grid described in setting specifically for the mobility according to the user
In data traffic confidence level, wherein the data traffic confidence level of the first kind user of setting be not less than the second class user number
According to flow confidence level, the data traffic confidence level of the second class user of setting is not less than the data traffic confidence of third class user
Degree.
Preferably, the data traffic locating module, specifically for according to the user mobility and the user
Historical act track, judge that the voice service that whether there is same cell before the timeslice effectively substitutes MR, specifically: it is right
In first kind user, voice service is found in current time the piece forward period of the 7th preset time and effectively substitutes MR, is looked for
When to first timeslice existed with cell voice service MR, determine that same cell voice service MR in the timeslice is language
Sound business effectively substitutes MR；For the second class user, period corresponding with current time piece and the time before 24 hours
The period that the 8th preset time covers before or after section finds voice service and effectively substitutes MR；Third class is used
Family finds voice service in current time the piece forward period of the 9th preset time and effectively substitutes MR, finds first and deposit
In the timeslice of same cell voice service MR, determine that the same cell voice service MR in the timeslice is that voice service is effective
Substitute MR.
Data traffic localization method and device described in the embodiment of the present invention will be divided into more than one time analysis time
Piece obtains the user information that data traffic is generated in each timeslice；It is carried out based on the user for generating data traffic in each timeslice
Grid positioning, the data traffic that user generates in each timeslice is navigated in grid, and navigate to the number in grid
According to the confidence level of flow；Obtain data traffic and confidence level of each grid within analysis time.It is described according to embodiments of the present invention
Data traffic localization method and device, can be realized PS business datum flow based on grid positioning, to be conducive to improve
Bus station position accuracy.
Detailed description of the invention
Fig. 1 is a kind of data traffic localization method flow diagram of the embodiment of the present invention 1；
Fig. 2 is a kind of structural schematic diagram of the data traffic positioning device of the embodiment of the present invention 2；
Fig. 3 is the structural schematic diagram of another the data traffic positioning device of the embodiment of the present invention 2；
Fig. 4 is a kind of data traffic localization method flow diagram of the embodiment of the present invention 3.
Specific embodiment
For PS business without MR or without the location requirement under precise position information, the prior art there is no complete solution,
Can the approximate technology solved be mostly to analyze high flow capacity cell or high flow capacity user, further to the voice industry of such cell or user
The MR that business generates carries out grid positioning, and MR falls into most grids and then regards as high flow capacity grid.
Prior art based on premise are as follows: (such as 1 day) in a long time, PS and the CS business of high flow capacity user
Distribution trend is consistent, and voice service MR most grids is high flow capacity grid, and CS hot spot is PS hot spot.In fact, user
Different from the habit of data service using voice, the place often conversed is not necessarily the place for being suitble to online, only concurrently
Business or stationary user.On the other hand, prior art can only approximate location high flow capacity grid, can not know the stream in grid
Information is measured, because voice duration (i.e. MR quantity * MR measurement period) is not equal to PS service traffics, for example, high flow capacity is used
1 MR of family A concurrent flow may be much larger than the flow of 10 MR of user B.
The embodiment of the present invention considers in the case where PS business is without MR or other precise location informations, how by user data
Flow is pin-pointed in the grid actually occurred, and the data traffic information of energy computation grid, reduces voice-and-data business
The position error of the inconsistent introducing of behavioural habits.
The resolving ideas of the embodiment of the present invention are as follows: the data traffic in selection area is multiple by the division of business time of origin
Sufficiently small timeslice (such as 15 minutes) extracts the user information that data traffic is generated in each timeslice；In each timeslice
It is interior, to each user, positioned based on the CS business MR occurred the PS business same time with user and data flux statistics；If same
Period user does not initiate CS business, then analyzes user mobility according to cell motion track, finds for it and sends out in historical track
It is born in the MR of same cell, as most probable geographical location.
Below by specific embodiment, technical solution of the present invention is described in further detail.
Embodiment 1
Fig. 1 is a kind of data traffic localization method flow diagram of the embodiment of the present invention, as shown in Figure 1, this method comprises:
Step 101: obtaining the user information that data traffic is generated in each timeslice；
Here, need for be divided into analysis time more than one timeslice, the timeslice of division answers sufficiently small, guarantee user
The time granularity of larger displacement is not generated.
Step 102: grid positioning being carried out based on the user for generating data traffic in each timeslice, by user in each timeslice
The data traffic of interior generation navigates in grid, and navigates to the confidence level of the data traffic in grid；
Here it is possible to carry out grid positioning to all or part of user for generating data traffic in each timeslice.For example,
The ratio for only analyzing data total flow in the data traffic and the timeslice generated in timeslice is greater than the user of a preset value
Grid positioning is carried out, for generating the seldom user of data traffic, the data traffic that can be generated is evenly distributed to cell
Under grid in.
Step 103: obtaining data traffic and confidence level of each grid within analysis time.
Optionally, grid positioning is carried out based on the user for generating data traffic in timeslice described in step 102, and determines and determines
The confidence level of data traffic of the position into grid, comprising:
Judge whether the user has occurred voice service in the timeslice, if so, according to the user in institute
The voice service monitoring report MR progress grid positioning for betiding same cell in timeslice is stated, and navigates to the number in grid
According to the confidence level of flow；Otherwise, the voice service history MR of same cell is betided before the timeslice according to the user
Grid positioning is carried out, and navigates to the confidence level of the data traffic in grid.
Optionally, the MR for betiding same cell in the timeslice according to user carries out grid positioning, and determines
Navigate to the confidence level of the data traffic in grid, comprising:
According to the MR quantity in grid corresponding under cell, the user in the timeslice is generated in the cell
Data traffic be prorated under the cell in the corresponding grid of MR, the data traffic confidence being assigned in grid
Degree is set as the first confidence level.
Here, according to the MR quantity in grid corresponding under cell, the data that the user is generated in the cell
Flow is prorated to corresponding grid under the cell, it may be assumed that according to the ratio of the MR corresponded in grid under cell, by institute
It states the data traffic generated in cell to be assigned in the grid under the cell, MR is more in grid, and the data traffic of distribution is got over
It is more.
Optionally, the voice service history MR for betiding same cell before the timeslice according to user carries out grid
Lattice positioning, and navigate to the confidence level of the data traffic in grid, comprising:
According to the historical act track of the user, the voice service that whether there is same cell before the timeslice is judged
Effectively substitution MR, if it does, being generated the user in the timeslice in the cell according to effective substitution MR quantity
Data traffic be prorated under the cell and effectively substitute in the corresponding grid of MR, the data being assigned in grid
Flow confidence level is set as the second confidence level；If it does not, the user in the timeslice is generated in the cell
Data traffic be evenly distributed in all grids under the cell, the data traffic confidence level being assigned in grid is set
It is set to third confidence level, wherein the third confidence level is not more than the second confidence level, and second confidence level is set no more than first
Reliability.
It should be noted that confidence level value interval is 0~1.
Optionally, data traffic and confidence level of each grid of acquisition within analysis time described in step 103, comprising:
Grid K grid K in data traffic+timeslice 2 of grid K in data traffic=timeslice 1 within analysis time
Data traffic+... the data traffic of grid K in+timeslice n；
Confidence level of the grid K within analysis time=(confidence level × timeslice 1 of the data traffic of grid K in timeslice 1
In data traffic+timeslice 2 of interior grid K in confidence level × timeslice 2 of the data traffic of grid K grid K data traffic
+ ... in+timeslice n in the confidence level of the data traffic of grid K × timeslice n grid K data traffic)/grid K analyzing
Data traffic in time, wherein n is the number for analysis time being divided into timeslice, and K=1,2 ... ..., N, N is selected stream
Measure the grid sum of analyzed area.
Optionally, the data traffic confidence level being assigned in grid is set as the second confidence level, comprising:
According to the mobility of the user, the data traffic confidence level that is assigned to described in setting in grid.
Optionally, this method further include: the mobility of user is determined based on the history active cell of user, specific:
User's history active cell is analyzed, if the time that user occupies same cell in the first preset time is more than the
Two preset times, it is determined that the user is first kind user；
If user occupies the time of two or three cells more than the 4th preset time in third preset time, and
The distance between described cell is greater than pre-determined distance, it is determined that the user is the second class user；
If user occupies three or more cells in the 5th preset time, and the time for occupying same cell is no more than
6th preset time, it is determined that the user is third class user,
Correspondingly, the data traffic confidence level of the first kind user of setting is not less than the data traffic confidence of the second class user
Degree, the data traffic confidence level of the second class user of setting are not less than the data traffic confidence level of third class user.
Correspondingly, the historical act track according to the user, judges to whether there is before the timeslice with small
The voice service in area effectively substitutes MR, comprising:
According to the mobility of the user and the historical act track of the user, judge before the timeslice whether
Voice service in the presence of same cell effectively substitutes MR, specifically:
For first kind user, it is effective that voice service is found in current time the piece forward period of the 7th preset time
MR is substituted, when finding first timeslice existed with cell voice service MR, determines the same cell voice in the timeslice
Business MR is that voice service effectively substitutes MR；
For the second class user, before 24 hours before period corresponding with current time piece and the period and/
Or the period of the 8th preset time covering later, it finds voice service and effectively substitutes MR；
For third class user, it is effective that voice service is found in current time the piece forward period of the 9th preset time
MR is substituted, when finding first timeslice existed with cell voice service MR, determines the same cell voice in the timeslice
Business MR is that voice service effectively substitutes MR.
Embodiment 2
Fig. 2 is a kind of structural schematic diagram of the data traffic positioning device of the embodiment of the present invention 2, the device and 1 institute of embodiment
The data traffic localization method stated is corresponding, as shown in Fig. 2, the device includes: that division module 21, first obtains module 22, data
Flow locating module 23, second obtains module 24；Wherein,
Division module 21, for more than one timeslice will to be divided into analysis time；
First obtains module 22, for obtaining the user information for generating data traffic in each timeslice；
Data traffic locating module 23, for carrying out grid positioning based on the user for generating data traffic in each timeslice,
The data traffic that the data traffic that user generates in each timeslice is navigated in grid, and is navigated in grid is set
Reliability；
Second obtains module 24, for obtaining data traffic and confidence level of each grid within analysis time.
Optionally, data traffic locating module 23, is specifically used for:
Judge whether the user has occurred voice service in the timeslice, if so, according to the user in institute
The voice service monitoring report MR progress grid positioning for betiding same cell in timeslice is stated, and navigates to the number in grid
According to the confidence level of flow；Otherwise, the voice service history MR of same cell is betided before the timeslice according to the user
Grid positioning is carried out, and navigates to the confidence level of the data traffic in grid.
Optionally, data traffic locating module 23, specifically for according to the MR quantity in grid corresponding under cell, by institute
It states the data traffic that the user generates in the cell in timeslice and is prorated to the corresponding grid of MR under the cell
In lattice, the data traffic confidence level being assigned in grid is set as the first confidence level.
Optionally, data traffic locating module 23, specifically for the historical act track according to the user, described in judgement
The voice service that whether there is same cell before timeslice effectively substitutes MR, if it does, according to effective substitution MR quantity, by institute
It states the data traffic that the user generates in the cell in timeslice and is prorated under the cell and effectively substitute MR
In corresponding grid, the data traffic confidence level being assigned in grid is set as the second confidence level；If it does not, by institute
It states in all grids that the data traffic that the user generates in the cell in timeslice is evenly distributed under the cell,
The data traffic confidence level being assigned in grid is set as third confidence level, wherein the third confidence level is no more than the
Two confidence levels, second confidence level are not more than the first confidence level.
Optionally, second module 24 is obtained, is specifically used for calculating:
Grid K grid K in data traffic+timeslice 2 of grid K in data traffic=timeslice 1 within analysis time
Data traffic+... the data traffic of grid K in+timeslice n；
Confidence level of the grid K within analysis time=(confidence level × timeslice 1 of the data traffic of grid K in timeslice 1
In data traffic+timeslice 2 of interior grid K in confidence level × timeslice 2 of the data traffic of grid K grid K data traffic
+ ... in+timeslice n in the confidence level of the data traffic of grid K × timeslice n grid K data traffic)/grid K analyzing
Data traffic in time, wherein n is the number for analysis time being divided into timeslice, and K=1,2 ... ..., N, N is selected stream
Measure the grid sum of analyzed area.
Optionally, data traffic locating module 23 is assigned to described in setting specifically for the mobility according to the user
Data traffic confidence level in grid.
Optionally, as shown in figure 3, the device further includes mobility determination module 25,
Mobility determination module 25, for analyzing user's history active cell, when user occupies in the first preset time
When the time of same cell is more than the second preset time, determine that the user is first kind user；When user is when third is preset
The interior time for occupying two or three cells more than the 4th preset time, and the distance between described cell be greater than it is default away from
From when, determine the user be the second class user；When user occupies three or more cells in the 5th preset time, and occupy same
When the time of one cell is no more than six preset times, determine that the user is third class user,
Data traffic locating module 23 is assigned in grid described in setting specifically for the mobility according to the user
Data traffic confidence level, wherein the data traffic confidence level of the first kind user of setting be not less than the second class user data
Flow confidence level, the data traffic confidence level of the second class user of setting are not less than the data traffic confidence level of third class user.
Optionally, data traffic locating module 23, specifically for according to the mobility of the user and the user
Historical act track judges that the voice service that whether there is same cell before the timeslice effectively substitutes MR, specifically: for
First kind user finds voice service in current time the piece forward period of the 7th preset time and effectively substitutes MR, finds
First exist with cell voice service MR timeslice when, determine that same cell voice service MR in the timeslice is voice
Business effectively substitutes MR；For the second class user, period corresponding with current time piece and the period before 24 hours
Before or after the 8th preset time cover period, find voice service effectively substitute MR；For third class user,
Voice service is found in current time the piece forward period of the 9th preset time and effectively substitutes MR, finds first and exists together
When the timeslice of cell voice service MR, determine that the same cell voice service MR in the timeslice is that voice service effectively substitutes
MR。
Embodiment 3
Fig. 4 is data traffic localization method flow diagram described in the embodiment of the present invention 3, as shown in figure 4, the process packet
It includes:
Step 401: obtaining specified region and the data service total flow of analysis time, multiple foots will be divided into analysis time
Enough small timeslices.
Here, that is, the total data flow in selected range and acquisition time is acquired.
Step 402: the user information of the generation flow in extraction time piece, cell information.
Step 403: the user of selected k-th of generation flow judges whether the user has occurred voice in the timeslice
Business, if so, executing step 404；Otherwise, step 405 is executed.
Step 404: obtaining the MR that betides same cell of the user in the timeslice, carry out grid positioning, go to
Step 406.
Step 405: can judgement search the substitution MR occurred in same cell from the user's history track, and it is fixed to carry out grid
Position, if so, executing step 407；Otherwise, step 408 is executed.
Step 406: the flow that user's same time occurs being navigated in the grid, partial discharge positioning confidence level is
100%, go to step 409.
Step 407: the flow that user's same time occurs is navigated in the grid, it, should according to user mobility difference
Partial discharge positioning confidence level takes 100%/N~100% etc., goes to step 409.
Step 408: user's same time flow is evenly distributed in N number of grid of same cell, confidence level 100%/N,
Go to step 409.
Step 409: judging whether to complete all customer analysis in this timeslice, if so, going to step 410；Otherwise, right
Next user analyzes in this timeslice, return step 403.
Step 410: judging whether to complete all timeslice analyses, if so, going to step 411；Otherwise, to it is next when
Between piece analyzed, return step 402.
Step 411: counting flow of each grid within analysis time, and be based on the average weighted confidence level of flow.
Here, by multiple period data flow summations, and according to data traffic weighted calculation average confidence, owned
The total data flow of grid whole day and comprehensive confidence level.So far, the grid for completing all data traffics is accurately positioned, number in grid
More according to flow, comprehensive confidence level is higher, is more possible to as data service hot spot.
In the present embodiment, acquisition time is divided into multiple lesser timeslices (such as 15 minutes), obtains each timeslice
The place cell information of data traffic occurs for the user information and user that produce data traffic.Wherein, compared with minor time slice
Definition met within the same period, and the voice and business of user, which is believed that, only occurs in the same cell, i.e., no mobility.If
It is room subsystem that PS business, which occupies cell, directly divides cell as a grid room, and by user data traffic and the grid
Association, confidence level 100%.
In the present embodiment, if it is that macrocell judges that user is in the period for each user that PS business, which occupies cell,
It is no that voice service has occurred, thus extract with cell MR, it is specific to carry out the positioning of the grid in macrocell:
If the CS business of same cell has occurred in same time user, grid positioning is carried out with the MR of period to user, by this
The data traffic of user is prorated in the correspondence grid under macrocell, and set confidence level to according to MR quantity
100%.Wherein, the grid location technology based on MR, is not belonging to the scope of this patent, using prior art.
If not collecting concurrent CS MR with the period, having with cell is found from the user's history activity trajectory
Effect substitution MR.If substitution MR can be found, grid positioning is carried out to substitute MR, the data traffic of this period of user is projected
In the grid, confidence level can use 100%~100%/N and differ, and N represents the sum of the grid in the cell coverage area；
If still can not find the substitution MR of same cell in user's history track, data traffic is evenly distributed in cell
N number of grid, confidence level (100/N) %.
In the present embodiment, the method for effectively substituting MR is determined based on user's history track are as follows:
Firstly, acquiring any active ues list for initiating n times voice or data service in selected range in advance, first analysis is each
User's long-term action track, determines user mobility, stamps corresponding mobility label to all users.User mobility is divided into
Three classes:
A: fixed user, the main room that occupies divide cell or same macrocell, occupy adjacent area in cell cluster once in a while；
B: one line user of two o'clock, it is main to occupy apart from farther away 2 or 3 cell clusters；
C: frequent mobile subscriber, the main cell that occupies is unobvious, 4 or 5 or more the cell clusters not closed on；
Wherein, user mobility specific algorithm are as follows: when the cell and each business that each business of record user occupies continue
Long, the quantity and distance relation of 70% cell before analysis business duration accounting are adjusted the distance relatively close (within such as 300 meters) or are existed
Multiple cells of neighboring BS relationship are calculated by cell cluster.Cell cluster quantity based on the analysis results is stamped all users corresponding
Mobility label.
Under the premise of above, there are two ways to substituting MR is determined:
1, universal method:
A period (until before 24 hours) finds effective substitution MR of user generation and same cell forward, if can find
It is consistent valid with current PS business occupancy cell, in this, as this data service spot, confidence level optional 50%.
This scheme is less suitable for existing historical data, is not enough to the case where analyzing user mobility；Also it can be used as simplified processing side
Case can skip user mobility analysis, obtain approximate data traffic grid positioning result.
2, exact method:
Further, effective substitution MR for user's history track determines method, can also be then according to user mobility point
Analysis, the grid ownership of more acurrate judgement data traffic, specifically:
A class user: a period, which is found, forward effectively substitutes MR (until same period before 24 hours), until the substitution found
It is that same cell is valid that cell where MR, which occupies cell with current data service, using the grid of this period MR as this number
According to business spot, confidence level can be set between 80%~100%；
B class user: finding substitution MR with (until 12 hours) before and after the period before toward 24 hours, until the substitution MR institute found
Occupying cell with current data service in cell is that same cell is valid, using the grid of this period MR as this data industry
It is engaged in spot, between confidence level 50%~80%；
C class user: a period, which is found, forward effectively substitutes MR (until same period before 24 hours), until the substitution found
It is that same cell is valid that cell where MR, which occupies cell with current data service, using the grid of this period MR as this number
According to business spot, confidence level 30%~50%.
The method according to embodiments of the present invention, the case where MR or other precise location informations are not present in PS business
Under, the user class PS business and CS business occurred in each timeslice of association analysis solves user speech and data business conduct
It is accustomed to the error of inconsistent introducing, user data traffic is pin-pointed in the grid actually occurred, and grid can be obtained
Data traffic information, to be conducive to improve bus station position accuracy.
The foregoing is only a preferred embodiment of the present invention, is not intended to limit the scope of the present invention.
Claims (14)
1. a kind of data traffic localization method, which is characterized in that more than one timeslice, this method packet will be divided into analysis time
It includes:
Obtain the user information that data traffic is generated in each timeslice；
Grid positioning, the data that user is generated in each timeslice are carried out based on the user for generating data traffic in each timeslice
Flow navigates in grid, and navigates to the confidence level of the data traffic in grid；
Obtain data traffic and confidence level of each grid within analysis time；
Wherein, grid positioning is carried out based on the user for generating data traffic in timeslice, comprising:
Judge whether the user has occurred voice service in the timeslice, if so, according to the user when described
Between betide the voice service monitoring report MR of same cell in piece and carry out grid positioning, otherwise, according to the user when described
Between betide the voice service history MR of same cell before piece and carry out grid positioning.
2. the method according to claim 1, wherein betiding same cell in the timeslice according to user
Voice service MR carries out grid positioning, comprising:
According to the MR quantity in grid corresponding under cell, the number that the user in the timeslice is generated in the cell
It is prorated under the cell in the corresponding grid of MR according to flow；
The data traffic confidence level being assigned in grid is set as the first confidence level.
3. according to the method described in claim 2, it is characterized in that, described betide before the timeslice together according to user
The voice service history MR of cell carries out grid positioning, comprising:
According to the historical act track of the user, judge that the voice service that whether there is same cell before the timeslice is effective
MR is substituted, if it does, according to effective substitution MR quantity, the number that the user in the timeslice is generated in the cell
It is prorated under the cell and is effectively substituted in the corresponding grid of MR according to flow；The data traffic being assigned in grid
Confidence level is set as the second confidence level；
If it does not, the data traffic that the user in the timeslice generates in the cell is evenly distributed to described
In all grids under cell；The data traffic confidence level being assigned in grid is set as third confidence level, wherein described
Third confidence level is not more than the second confidence level, and second confidence level is not more than the first confidence level.
4. method according to any one of claims 1 to 3, which is characterized in that described to obtain each grid within analysis time
Data traffic and confidence level, comprising:
The number of grid K grid K in data traffic+timeslice 2 of grid K in data traffic=timeslice 1 within analysis time
According to flow+... the data traffic of grid K in+timeslice n；
Confidence level of the grid K within analysis time=(grid in confidence level × timeslice 1 of the data traffic of grid K in timeslice 1
In data traffic+timeslice 2 of lattice K in confidence level × timeslice 2 of the data traffic of grid K grid K data traffic+...
In+timeslice n in the confidence level of the data traffic of grid K × timeslice n grid K data traffic)/grid K is in analysis time
Interior data traffic, wherein n is the number for analysis time being divided into timeslice, and K=1,2 ... ..., N, N is selected flow point
Analyse the grid sum in region.
5. according to the method described in claim 3, it is characterized in that, the data traffic confidence level setting being assigned in grid
For the second confidence level, comprising:
According to the mobility of the user, the data traffic confidence level that is assigned to described in setting in grid.
6. according to the method described in claim 5, it is characterized in that, this method further include: the history active cell based on user
Determine the mobility of user, specific:
User's history active cell is analyzed, if the time that user occupies same cell in the first preset time is more than second pre-
If the time, it is determined that the user is first kind user；
If user occupies time of two or three cells more than the 4th preset time in third preset time, and described
The distance between cell is greater than pre-determined distance, it is determined that the user is the second class user；
If user occupies three or more cells in the 5th preset time, and the time for occupying same cell is no more than the 6th
Preset time, it is determined that the user is third class user,
The mobility according to the user, the data traffic confidence level being assigned to described in setting in grid, comprising:
The data traffic confidence level of the first kind user of setting is not less than the data traffic confidence level of the second class user, and the of setting
The data traffic confidence level of two class users is not less than the data traffic confidence level of third class user.
7. according to the method described in claim 6, it is characterized in that, the historical act track according to the user, judgement
The voice service that whether there is same cell before the timeslice effectively substitutes MR, comprising:
According to the mobility of the user and the historical act track of the user, judge to whether there is before the timeslice
Voice service with cell effectively substitutes MR, specifically:
For first kind user, voice service is found in current time the piece forward period of the 7th preset time and is effectively substituted
MR determines the same cell voice service in the timeslice when finding first timeslice existed with cell voice service MR
MR is that voice service effectively substitutes MR；
For the second class user, before 24 hours before period corresponding with current time piece and the period and/or it
The period of 8th preset time covering afterwards finds voice service and effectively substitutes MR；
For third class user, voice service is found in current time the piece forward period of the 9th preset time and is effectively substituted
MR determines the same cell voice service in the timeslice when finding first timeslice existed with cell voice service MR
MR is that voice service effectively substitutes MR.
8. a kind of data traffic positioning device, which is characterized in that the device includes: division module, the first acquisition module, data flow
Measure locating module, the second acquisition module；Wherein,
The division module, for more than one timeslice will to be divided into analysis time；
Described first obtains module, for obtaining the user information for generating data traffic in each timeslice；
The data traffic locating module will for carrying out grid positioning based on the user for generating data traffic in each timeslice
The data traffic that user generates in each timeslice navigates in grid, and navigates to the confidence of the data traffic in grid
Degree；
Described second obtains module, for obtaining data traffic and confidence level of each grid within analysis time；
Wherein, the data traffic locating module, is specifically used for:
Judge whether the user has occurred voice service in the timeslice, if so, according to the user when described
Between betide the voice service monitoring report MR of same cell in piece and carry out grid positioning, otherwise, according to the user when described
Between betide the voice service history MR of same cell before piece and carry out grid positioning.
9. device according to claim 8, which is characterized in that
The data traffic locating module, specifically for according to the MR quantity in grid corresponding under cell, by the timeslice
The data traffic that the interior user generates in the cell is prorated under the cell in the corresponding grid of MR；It is described
The data traffic confidence level being assigned in grid is set as the first confidence level.
10. device according to claim 9, which is characterized in that
The data traffic locating module, specifically for the historical act track according to the user, judge the timeslice it
The preceding voice service with the presence or absence of with cell effectively substitutes MR, if it does, according to effective substitution MR quantity, by the timeslice
The data traffic that the interior user generates in the cell, which is prorated under the cell, effectively substitutes the corresponding grid of MR
In lattice；The data traffic confidence level being assigned in grid is set as the second confidence level；If it does not, by the timeslice
The data traffic that the interior user generates in the cell is evenly distributed in all grids under the cell；The distribution
Data traffic confidence level into grid is set as third confidence level, wherein and the third confidence level is not more than the second confidence level,
Second confidence level is not more than the first confidence level.
11. according to the described in any item devices of claim 8 to 10, which is characterized in that
Described second obtains module, is specifically used for calculating:
The number of grid K grid K in data traffic+timeslice 2 of grid K in data traffic=timeslice 1 within analysis time
According to flow+... the data traffic of grid K in+timeslice n；
Confidence level of the grid K within analysis time=(grid in confidence level × timeslice 1 of the data traffic of grid K in timeslice 1
In data traffic+timeslice 2 of lattice K in confidence level × timeslice 2 of the data traffic of grid K grid K data traffic+...
In+timeslice n in the confidence level of the data traffic of grid K × timeslice n grid K data traffic)/grid K is in analysis time
Interior data traffic, wherein n is the number for analysis time being divided into timeslice, and K=1,2 ... ..., N, N is selected flow point
Analyse the grid sum in region.
12. device according to claim 10, which is characterized in that
The data traffic locating module is assigned in grid described in setting specifically for the mobility according to the user
Data traffic confidence level.
13. device according to claim 12, which is characterized in that the device further includes mobility determination module,
The mobility determination module, for analyzing user's history active cell, when user occupies together in the first preset time
When the time of one cell is more than the second preset time, determine that the user is first kind user；When user is in third preset time
The interior time for occupying two or three cells is more than the 4th preset time, and the distance between described cell is greater than pre-determined distance
When, determine that the user is the second class user；When user occupies three or more cells in the 5th preset time, and occupy same
When the time of cell is no more than six preset times, determine that the user is third class user,
The data traffic locating module is assigned in grid described in setting specifically for the mobility according to the user
Data traffic confidence level, wherein the data traffic confidence level of the first kind user of setting is not less than the data flow of the second class user
Confidence level is measured, the data traffic confidence level of the second class user of setting is not less than the data traffic confidence level of third class user.
14. device according to claim 13, which is characterized in that
The data traffic locating module, specifically for according to the mobility of the user and the historical act rail of the user
Mark judges that the voice service that whether there is same cell before the timeslice effectively substitutes MR, specifically: the first kind is used
Family finds voice service in current time the piece forward period of the 7th preset time and effectively substitutes MR, finds first and deposit
In the timeslice of same cell voice service MR, determine that the same cell voice service MR in the timeslice is that voice service is effective
Substitute MR；For the second class user, before 24 hours before period corresponding with current time piece and the period and/
Or the period of the 8th preset time covering later, it finds voice service and effectively substitutes MR；For third class user, when current
Between piece the 9th preset time forward period in find voice service and effectively substitute MR, find first and exist with cell voice
When the timeslice of business MR, determine that the same cell voice service MR in the timeslice is that voice service effectively substitutes MR.
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| CN110049501B (en) * | 2018-01-15 | 2022-04-15 | 中兴通讯股份有限公司 | Data acquisition method, data acquisition device and computer-readable storage medium |
| CN109344729B (en) * | 2018-09-07 | 2021-10-26 | 福建诺恒科技有限公司 | Method for identifying movement of people on road |
| CN113573236B (en) * | 2020-04-29 | 2024-04-05 | 亚信科技（中国）有限公司 | Method and device for evaluating confidence of positioning result |
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