CN104244342B - A kind of user's mobile status method of estimation for LTE A heterogeneous networks - Google Patents
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Abstract
The invention provides a kind of user's mobile status method of estimation for LTE A heterogeneous networks.This method includes：A, according to current switching weight coefficient, weighting switching times of the user to be measured within the period of default first length are counted；B, estimate that user's to be measured estimates mobile status according to the weighting switching times of statistics；C, according to the current handover trigger time estimated mobile status and set user to be measured of user to be measured；D, handoff failure event of the user to be measured within the period of default second length is recorded, and calculates the handover failure rate of user to be measured；E, when the handover failure rate of user to be measured meets preparatory condition, step G is performed；Otherwise, step F is performed；F, the ratio according to all kinds of handoff failure events of the user to be measured recorded in total handoff failure event, the switching weight coefficient of user to be measured is adjusted, returns and perform step A；G, current is estimated into current moving state of the mobile status as user to be measured.The mobile status of user can be preferably estimated using the present invention, effectively improves performance of handoffs.
Description
Technical field
The present invention relates to mobile communication technology field, more particularly to a kind of user's mobile status for LTE-A heterogeneous networks
Method of estimation.
Background technology
In China, 3GPP Long Term Evolutions (LTE) licence plate is formally provided, and each operator has started to extensive commercialization.From 3G nets
The Experience in Development of network and the whole world have been disposed from the point of view of the national statistics result of LTE network, mobile data services still embody with
It is main traffic hotspots and network capacity and the spy of performance bottleneck the crowd massings such as business activity center, family and office buildings
Property.For this feature, currently the most important countermeasure of putting into practice is to provide wide covering by large-scale macro base station, is introduced in hot zones
Realize that the load of area business shunts with small-sized and microminiature base station is disposed, this network structure is exactly heterogeneous network.
Although the honeycomb heterogeneous network for introducing mini site has numerous advantages, the problem of very important is also faced.
Under heterogeneous network system environments, because low power nodes cell has the transmission power of oneself and corresponding coverage, therefore
Whole system environment becomes more complicated.Especially when user equipment is in mobile status, the standard configuration under homogenous networks
Many algorithms and parameter have all no longer been applicable.For example, the estimation algorithm of the user moving speed under homogenous networks, these schemes are set
Meter is all based on traditional homogeneous network model, and is poorly suitable for the scene of heterogeneous network.In heterogeneous network cell semidiameter not compared with
Greatly, even the UE at the uniform velocity moved, in the same time, the quantity of the picocell passed through and the quantity of macrocell may be poor
Different very big, the translational speed so estimated also can be widely different.
Have the mobile status algorithm for estimating of some heterogeneous networks at present, such as only count macro base station to the switching number of macro base station
Mesh；By switching times, all statistics is directly cumulative；Or the switching times of different switching types are pressed into fixed weight weighted sum
Deng still, these methods can not all well adapt to different network topology structures.
In summary, in order to solve the defects of prior art is present, lift user under heterogeneous networks topological structure and move shape
The accuracy that state is estimated, and the compatibility to existing protocol is kept, it must just propose that a kind of new heterogeneous networks topology that is applied to is tied
The speed estimation algorithms of structure.This problem also just turns into many scientific and technical personnel's focus of attention in the industry naturally
The content of the invention
In view of this, the invention provides a kind of user's mobile status method of estimation for LTE-A heterogeneous networks, so as to
Preferably to estimate the mobile status of user, effectively improve performance of handoffs.
What technical scheme was specifically realized in：
A kind of user's mobile status method of estimation for LTE-A heterogeneous networks, this method include：
A, according to current switching weight coefficient, count weighting of the user to be measured within the period of default first length and cut
Change number；
B, estimate that user's to be measured estimates mobile status according to the weighting switching times of statistics；
C, according to the current handover trigger time estimated mobile status and set user to be measured of user to be measured；
D, handoff failure event of the user to be measured within the period of default second length is recorded, and calculates user's to be measured
Handover failure rate；
E, when the handover failure rate of user to be measured meets preparatory condition, step G is performed；Otherwise, step F is performed；
F, the ratio according to all kinds of handoff failure events of the user to be measured recorded in total handoff failure event, adjust
The switching weight coefficient of whole user to be measured, return and perform step A；
G, current is estimated into current moving state of the mobile status as user to be measured.
Preferably, the weighting switching times are：
N=Nm+w*Np
Wherein, N is to weight switching times, NmFor user to be measured within the period of default first length in different grand bases
The total degree switched between standing, NpCut for user to be measured is related to picocell within the period of default first length
Number is changed, w is current switching weight coefficient.
Preferably, the initial value of the switching weight coefficient w is 0.
Preferably, default first length is 100 seconds.
Preferably, the step B includes：
Pre-set a fast state threshold value and middling speed state threshold；
When the weighting switching times of statistics are more than or equal to fast state threshold value, that estimates the user to be measured estimates movement
State is fast state；
When the weighting switching times of statistics are less than fast state threshold value but are more than or equal to middling speed state threshold, estimation should
The mobile status of estimating of user to be measured is middling speed state；
When the weighting switching times of statistics are less than middling speed state threshold, the mobile status of estimating for estimating the user to be measured is
Lower-speed state.
Preferably, the fast state threshold value is 6, the middling speed state threshold is 3.
Preferably, the step C includes：
Zoom factor is set, and the current handover trigger time is used as using the product of handover trigger time and zoom factor；
When user to be measured is when to estimate mobile status be fast state, the zoom factor is high speed zoom factor；
When user to be measured is when to estimate mobile status be middling speed state, the zoom factor is middling speed zoom factor；
And when user to be measured is when to estimate mobile status be lower-speed state, the zoom factor is low speed zoom factor.
Preferably, the high speed zoom factor is 0.25, the middling speed zoom factor is 0.5, the low speed zoom factor
For 1.
Preferably, the step E includes：
Pre-set first threshold and Second Threshold；
When the too early handover failure rate in the handover failure rate of user to be measured is less than first threshold and too late handover failure rate
During less than Second Threshold, step G is performed；Otherwise, step F is performed.
Preferably, the first threshold is 0.55%, the Second Threshold is 10%.
Preferably, the step F includes：
According to all kinds of handoff failure events of the user to be measured recorded, count the user to be measured and too early handoff failure occurs
The number of handoff failure too late；
When the number of too early handoff failure is more than the number switched too late, then by the value of current switching weight coefficient
Subtract default step-length；When the number of handoff failure too late is more than the number switched too early, then by current switching weight coefficient
Value add default step-length；
Return and perform step A.
Preferably, the value of the default step-length is 0.1.
As seen from the above technical solution, in the inventive solutions, due to both considering picocell and macrocell
The difference of covering radius, it is contemplated that in macrocell heterogeneous networks topological structure influence, and make use of SON technologies to be fitted
The optimal switching weight coefficient of heterogeneous networks topological structure is closed, so can preferably estimate the mobile status of user, but also
Performance of handoffs can effectively be improved.In addition, low power nodes not necessarily derive from same operator, and it is possibly even to use
What family oneself was laid, uncertain and polytropy may be presented in the change similar to Home eNodeB, therefore network topology.And pass through
Using user's mobile status method of estimation of the present invention, after network topology changes, adjustment that can also be adaptive is related
Parameter, it is adapted to following heterogeneous network deployment feature complicated and changeable.Further, since the inventive method does not require to change existing LTE-
A communication protocols, also do not increase signaling consumption, and computation complexity is not also high, to user terminal also without any change, only needs
Base station side is partially improved, you can implement this method, therefore the present invention has good popularizing application prospect.
Brief description of the drawings
Fig. 1 is the schematic flow sheet of user's mobile status method of estimation for LTE-A heterogeneous networks of the present invention.
Fig. 2 is the effect diagram one of user's mobile status method of estimation for LTE-A heterogeneous networks of the present invention.
Fig. 3 is the effect diagram two of user's mobile status method of estimation for LTE-A heterogeneous networks of the present invention.
Embodiment
For technical scheme and advantage is more clearly understood, below in conjunction with drawings and the specific embodiments, to this
Invention is described in further detail.
Fig. 1 is the schematic flow sheet of user's mobile status method of estimation for LTE-A heterogeneous networks of the present invention.
As shown in figure 1, user's mobile status method of estimation for LTE-A heterogeneous networks in the embodiment of the present invention is mainly wrapped
Include step as described below：
Step 11, according to current switching weight coefficient, user to be measured is counted within the period of default first length
Weight switching times.
In this step, it is necessary to according to current switching weight coefficient, in (the time of i.e. default first length a period of time
Section) in statistics user to be measured weighting switching times.
In the inventive solutions, above-mentioned weighting switching times can be counted using various ways.For example, at this
In one preferred embodiment of invention, the weighting switching times can be：
N=Nm+w*Np (1)
Wherein, N is to weight switching times, NmFor user to be measured within the period of default first length in different grand bases
The total degree switched between standing, NpCut for user to be measured is related to picocell within the period of default first length
Number is changed, w is current switching weight coefficient.
In the inventive solutions, it is not to immobilize to switch weight coefficient w, but can be dynamically over time
Change, therefore in this step, it is necessary to according to current switching weight coefficient, user to be measured is counted in default first length
Period in weighting switching times.
In addition, in the preferred embodiment, switching weight coefficient w initial value could be arranged to 0, certainly,
Other suitable preset values can also be arranged to.
In addition, in the preferred embodiment, default first length can be 100 seconds or other
The value pre-set.
Step 12, estimate that user's to be measured estimates mobile status according to the weighting switching times of statistics.
After statistics obtains weighting switching times, you can estimate that user's to be measured estimates shifting according to the weighting switching times
Dynamic state.
For example, in the preferred embodiment, a fast state threshold value N can be pre-setHO_HWith middling speed shape
State threshold value NHO_M；Then, user to be measured is estimated according to the weighting switching times of statistics, fast state threshold value and middling speed state threshold
Estimate mobile status.
For example, when the weighting switching times of statistics are more than or equal to fast state threshold value, estimate that the user's to be measured is pre-
It is fast state to estimate mobile status；
When the weighting switching times of statistics are less than fast state threshold value but are more than or equal to middling speed state threshold, estimation should
The mobile status of estimating of user to be measured is middling speed state；
When the weighting switching times of statistics are less than middling speed state threshold, the mobile status of estimating for estimating the user to be measured is
Lower-speed state.
In addition, in the preferred embodiment, the fast state threshold value N can be presetHO_HWith middling speed state threshold
Value NHO_MValue.For example, the preferably, fast state threshold value NHO_HFor 6, the middling speed state threshold NHO_MFor 3.
Pre-estimated user to be measured estimate mobile status after, can be accurate in order to ensure that this estimates mobile status
Ground reflects the mobile status of user, it is also necessary to continues executing with the judgement that following step carries out next step.
Step 13, according to the current handover trigger time estimated mobile status and set user to be measured of user to be measured.
When user is moved in each minizone, handover trigger time TTT length will directly influence switching
Effect.If handover trigger overlong time, easily occur to switch too late；And if the handover trigger time is too short, easily occur
Switching too early.
In order to more really reflection practical situations, in the preferred embodiment, can set scaling because
Sub- sf, and the current handover trigger time is used as using TTT and sf product.Wherein, the value of zoom factor can be according to the pre- of user
Mobile status is estimated to determine.
For example, when user to be measured is when to estimate mobile status be fast state, the zoom factor is high speed zoom factor
sf_high；
When user to be measured is when to estimate mobile status be middling speed state, the zoom factor is middling speed zoom factor sf_
medium；
And when user to be measured is when to estimate mobile status be lower-speed state, the zoom factor is low speed zoom factor sf_
low。
Preferably, in a particular embodiment of the present invention, can preset above-mentioned high speed zoom factor, middling speed scaling because
The value of son and low speed zoom factor.For example, high speed zoom factor is 0.25, middling speed zoom factor is 0.5, low speed zoom factor
For 1 (equivalent to without using zoom factor).
Therefore, in this step, can be according to the current switching estimated mobile status and set user to be measured of user to be measured
Triggered time.
Step 14, handoff failure event of the user to be measured within the period of default second length is recorded, and is calculated to be measured
The handover failure rate of user.
After the current handover trigger time there is provided user to be measured, you can (i.e. default second length within a period of time
In the period of degree) the handoff failure event of user to be measured is recorded, and use to be measured is calculated according to the handoff failure event recorded
The handover failure rate at family.
Step 15, judge whether the handover failure rate of user to be measured meets preparatory condition, if it is, performing step 17；It is no
Then, step 16 is performed.
At step 14, can be by the way that the handover failure rate of user be calculated.When handover failure rate is higher, illustrate
Estimated in step 12 to estimate mobile status and the deviation of actual conditions is larger, accuracy is relatively low；And when handover failure rate compared with
When low, then illustrate that the accuracy for estimating mobile status estimated in step 12 is higher.
Therefore, after handover failure rate by the way that user to be measured is calculated at step 14, you can in this step
Judge whether the handover failure rate of user to be measured meets preparatory condition.If meeting preparatory condition, illustrate institute in step 12
The accuracy for estimating mobile status of estimation is higher, therefore can perform step 17；And if being unsatisfactory for preparatory condition, then illustrate
The estimated accuracy for estimating mobile status is not high, it is necessary to continue further to optimize in step 12.
In the inventive solutions, above-mentioned steps 15 can have a variety of implementations, below will be with one kind therein
Exemplified by be illustrated.
Preferably, in a particular embodiment of the present invention, the step 15 can include step as described below：
Step 150, first threshold and Second Threshold are pre-set；
Step 151, when the too early handover failure rate in the handover failure rate of user to be measured is less than first threshold and cuts too late
When changing mortality and being less than Second Threshold, step 17 is performed；Otherwise, step 16 is performed.
Preferably, in a particular embodiment of the present invention, the first threshold is 0.55%, the Second Threshold is
10%.
That is, in this step, it is necessary to which the handover failure rate of user to be measured is controlled in an acceptable threshold value
In the range of.If within the range, then it represents that the accuracy for estimating mobile status is higher；And if not within the range, then table
Show that the accuracy for estimating mobile status is relatively low.
Step 16, the ratio according to all kinds of handoff failure events of the user to be measured recorded in total handoff failure event
Example, the switching weight coefficient of user to be measured is adjusted, return and perform step 11.
In the inventive solutions, above-mentioned steps 16 can have a variety of implementations, below will be with one kind therein
Exemplified by be illustrated.
Preferably, in a particular embodiment of the present invention, the step 16 can include：
Step 160, according to all kinds of handoff failure events of the user to be measured recorded, count the user to be measured and occur too early
The number of handoff failure and too late handoff failure；
Step 161, when the number of too early handoff failure is more than the number that switches too late, (i.e. too early handoff failure event is in
Leading position) when, then the value of current switching weight coefficient is subtracted into default step-length；And ought handoff failure too late number it is big
When number (i.e. handoff failure event is in leading position too late) switched too early, then taking current switching weight coefficient
Value is plus default step-length.
Step 162, return and perform step 11.
Wherein, in the preferred embodiment, the value of the default step-length can be pre-set.It is for example, described
The value of default step-length is 0.1.
Step 17, current is estimated into current moving state of the mobile status as user to be measured.
In this step, you can current is estimated into current moving state of the mobile status as user to be measured, terminated whole
Individual flow.
From the foregoing, it will be observed that pass through above-mentioned step 11~17, you can complete the assessment to user to be measured, obtain user's to be measured
Current moving state.
In addition, implementing testing and evaluation by multiple Multi simulation running, estimate using above-mentioned user's mobile status
It after meter method, can effectively improve the performance of handoffs of user, greatly improve the estimation of mobile status to user to be measured
Accuracy.
For example, inventor establishes outdoor wireless propagation environment model, and imitate using outdoor system level according to 3GPP agreements
True method, the mobile status estimation to user in LTE-A heterogeneous networks have carried out emulation experiment, and according to experimental result by the present invention
Proposed in method compared with conventional method of the prior art.
Fig. 2 is the effect diagram one of user's mobile status method of estimation for LTE-A heterogeneous networks of the present invention.
As shown in Fig. 2 switching of the user to be measured from macro base station to macro base station time is only counted in existing method 1 in Fig. 2
Number；Therefore, estimation accuracy rate of this method to low speed user is higher, but the estimation accuracy rate for highspeed user is but very
It is low.And if using the present invention method, then can keep good accuracy, that is to say, that for different speed steps,
The method of the present invention is respectively provided with good robustness.
In existing method 2 shown in Fig. 2, although it is contemplated that being cut using different weights to count to different switching types
Number is changed, still, in the method, handoff factor weight of the user to be measured from macro base station to macro base station is 1, and macro base station is to slightly
The switching times weight of base station is 0.45, and the switching times weight of femto base station to macro base station is 0.25, and femto base station is to slightly
The switching times weight of base station is 0.1.It follows that fixed weight is provided with this method for various switching types, should
Dynamic does not change weight, therefore does not necessarily adapt to different network topology structures, and its mobile status is estimated accurate
The fluctuation of rate is very big.And if using method of the invention, then there is more preferable accuracy in the mobile status estimation of high speed, from
And higher handover failure rate can be effectively prevented from.
In existing method 3 shown in Fig. 2, it is contemplated that whole switching types are counted, but all types of weights is equal
1 is arranged to, therefore its weight can not dynamically change, and can not naturally also adapt to different network topology structures, it is moved
The fluctuation of the accuracy rate of state estimation is very big, and larger mistake be present to the accuracy of the mobile status of low speed and middling speed estimation
Difference.And if using method of the invention, then the estimated result of low speed and user's mobile status of middling speed can be made substantially
Improve.Compared to existing method 3, use the present invention method can cause the mobile status of low speed user estimate accuracy from
31% lifting is to 80%, and the mobile status of middling speed user estimation accuracy mentions 54% from 37%, and improvement is fairly obvious.
Fig. 3 is the effect diagram two of user's mobile status method of estimation for LTE-A heterogeneous networks of the present invention.Such as figure
Shown in 3, the ordinate in Fig. 3 represents total switching rate change, and abscissa then represents to optimize using the method for the present invention
Process, that is, optimize number.Two curves in Fig. 3 respectively show unit macrocell and include 4 picocells
(picos) scene and handover failure rate situation of change in the optimization process under 10 picocell scenes is included.As shown in Figure 3 may be used
Know, when using the method for the present invention, the handover failure rate in optimization process, which has, to be decreased obviously.
In summary, in the inventive solutions, due to both considering picocell and macrocell covering radius
Difference, it is contemplated that in macrocell heterogeneous networks topological structure influence, and make use of SON technologies come obtain be adapted to heterogeneous networks
The optimal switching weight coefficient of topological structure, so can preferably estimate the mobile status of user, and can also effectively it change
Kind performance of handoffs.In addition, low power nodes not necessarily derive from same operator, and it is possibly even that user oneself lays
, uncertain and polytropy may be presented in the change similar to Home eNodeB, therefore network topology.And by using the present invention
User's mobile status method of estimation, after network topology changes, can also adaptive adjustment relevant parameter, be adapted to not
Carry out heterogeneous network deployment feature complicated and changeable.Further, since the inventive method does not require to change existing LTE-A communication protocols,
Also signaling consumption is not increased, and computation complexity is not also high, and to user terminal also without any change, only base station side need to be entered
Row is partially improved, you can implements this method, therefore the present invention has good popularizing application prospect.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all essences in the present invention
God any modification, equivalent substitution and improvements done etc., should be included within the scope of protection of the invention with principle.
Claims (10)
1. a kind of user's mobile status method of estimation for LTE-A heterogeneous networks, it is characterised in that this method includes：
A, according to current switching weight coefficient, weighting switching time of the user to be measured within the period of default first length is counted
Number；
B, estimate that user's to be measured estimates mobile status according to the weighting switching times of statistics；
C, according to the current handover trigger time estimated mobile status and set user to be measured of user to be measured；
D, handoff failure event of the user to be measured within the period of default second length is recorded, and calculates the switching of user to be measured
Mortality；
E, when the handover failure rate of user to be measured meets preparatory condition, step G is performed；Otherwise, step F is performed；
F, according to all kinds of handoff failure events of the user to be measured recorded, count the user to be measured occur too early handoff failure and
The number of handoff failure too late；
When the number of too early handoff failure is more than the number switched too late, then the value of current switching weight coefficient is subtracted
Default step-length；When the number of handoff failure too late is more than the number switched too early, then taking current switching weight coefficient
Value returns plus default step-length and performs step A；
G, current is estimated into current moving state of the mobile status as user to be measured；
Wherein, the weighting switching times are：
N=Nm+w*Np
Wherein, N is to weight switching times, NmFor user to be measured within the period of default first length different macro base stations it
Between the total degree that switches over, NpFor user to be measured switching time related to picocell within the period of default first length
Number, w is current switching weight coefficient.
2. according to the method for claim 1, it is characterised in that：
The initial value of the switching weight coefficient w is 0.
3. according to the method for claim 1, it is characterised in that：
Default first length is 100 seconds.
4. according to the method for claim 1, it is characterised in that the step B includes：
Pre-set a fast state threshold value and middling speed state threshold；
When the weighting switching times of statistics are more than or equal to fast state threshold value, that estimates the user to be measured estimates mobile status
For fast state；
When the weighting switching times of statistics are less than fast state threshold value but are more than or equal to middling speed state threshold, estimate that this is to be measured
The mobile status of estimating of user is middling speed state；
When the weighting switching times of statistics are less than middling speed state threshold, the mobile status of estimating for estimating the user to be measured is low speed
State.
5. according to the method for claim 4, it is characterised in that：
The fast state threshold value is 6, and the middling speed state threshold is 3.
6. according to the method for claim 1, it is characterised in that the step C includes：
Zoom factor is set, and the current handover trigger time is used as using the product of handover trigger time and zoom factor；
When user to be measured is when to estimate mobile status be fast state, the zoom factor is high speed zoom factor；
When user to be measured is when to estimate mobile status be middling speed state, the zoom factor is middling speed zoom factor；
And when user to be measured is when to estimate mobile status be lower-speed state, the zoom factor is low speed zoom factor.
7. according to the method for claim 6, it is characterised in that：
The high speed zoom factor is 0.25, and the middling speed zoom factor is 0.5, and the low speed zoom factor is 1.
8. according to the method for claim 1, it is characterised in that the step E includes：
Pre-set first threshold and Second Threshold；
When the too early handover failure rate in the handover failure rate of user to be measured is less than first threshold and handover failure rate is less than too late
During Second Threshold, step G is performed；Otherwise, step F is performed.
9. according to the method for claim 8, it is characterised in that：
The first threshold is 0.55%, and the Second Threshold is 10%.
10. according to the method for claim 1, it is characterised in that：
The value of the default step-length is 0.1.
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| CN109121154B (en) * | 2017-06-22 | 2021-01-19 | 北京大学 | User moving speed estimation method in ultra-dense heterogeneous cellular network |
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| CN101841835A (en) * | 2009-03-17 | 2010-09-22 | 大唐移动通信设备有限公司 | Switching optimization method, equipment and system |
| CN101848476A (en) * | 2009-03-27 | 2010-09-29 | 大唐移动通信设备有限公司 | Method, device and system for realizing self-optimization of switching parameter |
| CN102098712A (en) * | 2011-03-24 | 2011-06-15 | 东南大学 | Handoff parameter self-optimization method in mobile communication system |
| CN103283279A (en) * | 2011-08-11 | 2013-09-04 | 联发科技股份有限公司 | Method of heterogeneous network mobility |
| CN102958093A (en) * | 2011-08-27 | 2013-03-06 | 华为技术有限公司 | Method and device for detecting mobile state |
| CN103907377A (en) * | 2011-09-30 | 2014-07-02 | 诺基亚公司 | Mobility enhancement for fast moving user equipment in a heterogenous network environment |
| CN103918326A (en) * | 2011-10-03 | 2014-07-09 | 阿尔卡特朗讯 | Method of estimating mobility of user equipment and wireless device |
| CN103220694A (en) * | 2012-01-18 | 2013-07-24 | 华为技术有限公司 | Estimation method of motion state of user equipment and user equipment |
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