CN101203018B - Method for distributing business density time and business in a mobile communication - Google Patents

Abstract

The invention provides a method for distributing service and time of service density in mobile communication, wherein, the time distribution method includes: step one, the portfolio of 24 hours of a base station subdistrict is calculated, and whether the portfolio of a busy system is equal to the portfolio of a busy subdistrict is judged, if yes, step two is carried out, otherwise, step three is carried out; step two, 'one' is taken as a magnification factor of the portfolio as time fluctuates; step three, a non-uniform coefficient of the portfolio of all moments is calculated when the portfolio of the subdistrict surpasses the portfolio of the busy system; step four, based on a magnification factor calculated according to the non-uniform coefficient, the dimension of a non-uniform coefficient G is judged; step five, according to the magnification factor, the distribution of a voice service and a data service is programmed. The invention takes advantages of the existing service data and fully considers time fluctuation property and malconformation of the service, thus a telephone traffic distribution is closer to a real condition in details.

Description

Traffic density time and method for distributing business in a kind of mobile communication

Technical field

The present invention relates to the method for distributing business in a kind of mobile communication, traffic density time and method for distributing business in particularly a kind of mobile communication.

Background technology

In current traffic forecast process, traffic density figure adopts the thick spacious generating mode of a kind of comparison.At first on electronic chart, manually mark off dissimilar zones, as dense city, city, suburb, rural area, import the traffic carrying capacity under each type unit are then, and traffic carrying capacity is sprinkled into the various atural objects of planning region uniformly by certain weight in the zone of the type, on skyscraper, common building, greenery patches, river etc.

Business hours distributes unbalanced being meant to have very strong lack of uniformity professional the distribution in time, and promptly All Ranges can not reach maximum by interior at one time number of users.There is the extremely strong characteristic of migrating in the mobile subscriber, and reaches maximum as business district traffic carrying capacity in 8 hour operating time, and service areas such as food and drink are in lunch and date for dinner traffic carrying capacity maximum, and living area people's back traffic carrying capacity of going home between the lights reaches maximum etc.Tradition traffic density figure just with total professional maximum constantly serve as according to having done simple process, do not considered the time dependent wave characteristic of this business, make its actual conditions that predicted the outcome substantial deviation in the bigger zone of traffic fluctuations.

Lack of uniformity between the business is meant that business mainly is divided into speech business and data service two big classes, owing to there is bigger difference between the different business, also there is a great difference in the use habit of same its different business of user.Traditional approach is not considered two kinds of correlation properties between the business, and just two kinds of business are done simple addition obtains final traffic density figure, and this result and actual conditions exist than big difference obviously.

Traditional business density generation method comprises as shown in Figure 1:

(1), estimates the voice user's quantity in the planning region according to user's method of estimation;

(2) substance environment classification definitely with a planning region classification, is divided into dense city, common city, suburb, rural area etc.;

(3) according to different areas, be standard with voice user's number, specified data user and voice user's ratio, permeability just, thereby specified data service-user number;

(4) according to the different pieces of information business when the user traffic model, specified data user's throughput;

(5) according to single user throughput and number of users specified data service throughput.

Summary of the invention

In view of above-mentioned, the traffic density that the invention provides in a kind of new mobile communication is improved one's methods, so that determine the traffic assignments situation more accurately.

To achieve these objectives, the invention provides the traffic density time allocation method used therein in a kind of mobile communication, comprising:

Step 1,24 hours the traffic carrying capacity in calculation base station sub-district, whether the traffic carrying capacity when judging system busy during with busy cells is consistent, if consistent, changes step 2 over to, otherwise, change step 3 over to;

Step 2 gets 1 with the amplification coefficient that traffic carrying capacity fluctuates in time;

Step 3; The nonuniformity coefficient that surpasses all moment portfolios of system's busy-hour traffic in the calculation plot; Portfolio when surpassing system busy when at first obtaining busy cells and ordering; In order the computing service amount successively cumulative sum account for the percentage that the percentage of all portfolios and ordering number account for all sequences number; Portfolio percentage and percentage of time are carried out respectively linear fit and curve; Linear fit curve and curve curve are presented on take sequence number percentage to abscissa; In the chart take portfolio percentage as ordinate; Obtain nonuniformity coefficient G

$G=\frac{\mathrm{SA}}{\mathrm{SA}+\mathrm{SB}}$

Wherein SA is the area between linear fit curve and the curve fit curve, and SB is that the curve fit curve is to the area between the transverse axis;

Step 4, judge the size of nonuniformity coefficient G, if G＜0.2, the amplification coefficient that fluctuates in time of traffic carrying capacity all ratios of traffic carrying capacity mean values and system's busy-hour traffic constantly of equaling to surpass in the sub-district system's busy-hour traffic then, if 0.2＜G＜0.35, then the amplification coefficient that fluctuates in time of traffic carrying capacity equals 0.4+0.6X sub-district busy-hour traffic/system's busy-hour traffic, if 0.35＜G＜0.45, then the amplification coefficient that fluctuates in time of traffic carrying capacity equals 0.3+0.7X sub-district busy-hour traffic/system's busy-hour traffic, if G＞0.45, then the amplification coefficient that fluctuates in time of traffic carrying capacity equals 0.2+0.8X sub-district busy-hour traffic/system's busy-hour traffic;

Step 5 is according to the distribution of amplification coefficient planning speech business and data service.

As preferably, be that the traffic carrying capacity of inscribing all base station cells during with difference is sued for peace the moment of summed result maximum during system busy.

As preferably, it during busy cells each maximum moment in traffic carrying capacity constantly in each sub-district.

As preferably, above-mentioned traffic carrying capacity is voice services volume or data business volume.

The present invention also provides the method for distributing business of the traffic density in a kind of mobile communication, comprising:

Step 1,24 hours voice services volume A in calculation base station sub-district and data business volume B;

Step 2, the amplification coefficient that fluctuates in time of computing voice traffic carrying capacity A and data business volume B respectively in accordance with the method for claim 1;

Step 3 is calculated correlation coefficient r,

$r=\frac{\mathrm{Cov}(A,B)}{\sqrt{\mathrm{Cov}(A,A)\mathrm{Cov}(B,B)}}$

Wherein, Cov (A, B) covariance of expression A and B;

Step 4, the size of judgement r, if | r|≤0.404, then adopt the amplification coefficient of voice services volume A to amplify traffic density, if | r|＞0.404, then adopt the amplification coefficient of data business volume B to amplify traffic density.

Beneficial effect of the present invention is to utilize existing business datum, and the distribution of traffic carrying capacity is refine to base station cell, makes traffic distribution in detail more near actual conditions.。

Utilization of the present invention is carried out a certain proportion of amplification than the traffic carrying capacity of the sub-district of big-difference and is solved unbalanced and professional unbalanced problem of time by sub-district time fluctuation characteristic and system time wave characteristic are existed, utilize existing business datum, taken into full account professional time fluctuation characteristic and professional lack of uniformity, made traffic distribution more near actual conditions

Below in conjunction with accompanying drawing, the specific embodiment of the present invention is described in further detail.For the person of ordinary skill in the field, from detailed description of the invention, above-mentioned and other purposes of the present invention, feature and advantage will be apparent.

Description of drawings

Fig. 1 is the flow chart of traffic density time allocation method used therein of the prior art.

Fig. 2 is the flow chart of the traffic density time allocation method used therein of a preferred embodiment of the present invention.

Fig. 3 is the product process figure of the nonuniformity coefficient of a preferred embodiment of the present invention.

Fig. 4 is the lorenz curve figure of a preferred embodiment of the present invention.

Fig. 5 is the data service amplification coefficient product process figure of a preferred embodiment of the present invention.

Below in conjunction with the drawings and specific embodiments traffic density time and space allocation method in a kind of mobile communication of the present invention are described in further detail.

Embodiment

The traffic density time allocation method used therein of a preferred embodiment of the present invention may further comprise the steps as shown in Figure 2:

Step 21,24 hours traffic carrying capacity of accounting base-station sub-district, this traffic carrying capacity can be voice services volume or data business volume.Present embodiment selects the data in a week to average, with the input as next step of the average data that obtains.

Step 22 relatively and the traffic carrying capacity of statistical system when busy and the traffic carrying capacity during busy cells, is inscribed the traffic carrying capacity of all base station cells and is sued for peace the moment of summed result maximum when wherein being meant difference during system busy; It during busy cells each maximum moment in traffic carrying capacity constantly in each sub-district.If the traffic carrying capacity of the traffic carrying capacity during system busy during with busy cells equates, then change step 23 over to, otherwise, change step 24 over to.

Step 23 gets 1 with amplification coefficient.

Step 24 calculates amplification coefficient according to the traffic carrying capacity nonuniformity coefficient.

Step 25, professional according to amplification coefficient planning, comprise speech business and data service.

The method of calculating amplification coefficient according to the traffic carrying capacity nonuniformity coefficient in the step 24 may further comprise the steps as shown in Figure 3:

Step 31, the traffic carrying capacity when traffic carrying capacity when obtaining busy cells and busy cells, the traffic carrying capacity when the selecting system busy big moment of traffic carrying capacity during than busy cells, and these traffic carrying capacitys constantly.

Step 32, with the traffic carrying capacity ordering of selecting, according to sequence arrangement from small to large, the traffic carrying capacity after the ordering is converted to the form of percentage, and the computing service amount sum that adds up successively accounts for the percentage that the percentage of all traffic carrying capacitys and ordering number account for all sequences number in order.

Step 33 as shown in Figure 4, is carried out linear fit to the percentage and the percentage of time of traffic carrying capacity, forms equilibrium line.

Step 34 carries out curve fitting to the percentage and the percentage of time of traffic carrying capacity, forms lorenz curve.

Step 35 is calculated nonuniformity coefficient G according to fitting result,

$G=\frac{\mathrm{SA}}{\mathrm{SA}+\mathrm{SB}}$

Wherein SA is the area between linear fit curve and the curve fit curve, SB is that the curve fit curve is to the area between the transverse axis, the result of nonuniformity coefficient G is between 0-1, G＜0.1 expression is highly average, 0.1＜G＜0.2 expression is average, 0.2＜G＜0.35 expression traffic is unbalanced, 0.35＜G＜unbalanced degree of 0.45 expression traffic is bigger, and G＞0.45 expression traffic is quite unbalanced;

Then utilize nonuniformity coefficient G to calculate amplification coefficient, if G＜0.2, the amplification coefficient that fluctuates in time of traffic carrying capacity all ratios of traffic carrying capacity mean values and system's busy-hour traffic constantly of equaling to surpass in the sub-district system's busy-hour traffic then,

If 0.2＜G≤0.35, amplification coefficient=0.4+0.6X sub-district busy-hour traffic/system's busy-hour traffic of fluctuating in time of traffic carrying capacity then,

If 0.35＜G≤0.45, amplification coefficient=0.3+0.7X sub-district busy-hour traffic/system's busy-hour traffic of fluctuating in time of traffic carrying capacity then,

If G＞0.45, then amplification coefficient=0.2+0.8X sub-district busy-hour traffic/system's busy-hour traffic of fluctuating in time of traffic carrying capacity.

The data service amplification coefficient generation method of a preferred embodiment of the present invention may further comprise the steps as shown in Figure 5:

Step 51,24 hours voice services volume A in calculation base station sub-district and data business volume B;

Step 52 is according to the preceding method amplification coefficient that fluctuates in time of computing voice traffic carrying capacity A and data business volume B respectively;

Step 53 is calculated correlation coefficient r,

$r=\frac{\mathrm{Cov}(A,B)}{\sqrt{\mathrm{Cov}(A,A)\mathrm{Cov}(B,B)}}$

Wherein, Cov (A, B) covariance of expression A and B; Computational methods are

E is a mathematic expectaion;

Step 54, the size of judgement r, if | r|≤0.404, then adopt the amplification coefficient of voice services volume A to amplify traffic density, if | r|＞0.404, then adopt the amplification coefficient of data business volume B to amplify traffic density.

From the mobile network management system, extract the information relevant with above-mentioned base station cell, comprise latitude and longitude of base station, the base station cell antenna is hung high, continuous 7 days voice services volume of base station cell antenna directional angle, base station cell antenna elevation angle, base station cell transmitting power, base station cell, the continuous 7 day data flows of base station cell etc.

The above is preferred embodiment of the present invention only, is not to be used for limiting practical range of the present invention; If do not break away from the spirit and scope of the present invention, the present invention is made amendment or is equal to replacement, the guarantor that all should be encompassed in claim of the present invention expands in the middle of the scope.

Claims (3)

1. the traffic density time allocation method used therein in the mobile communication is characterized in that comprising:

Step 1,24 hours the traffic carrying capacity in calculation base station sub-district, whether the traffic carrying capacity when judging system busy during with busy cells is consistent, if consistent, changes step 2 over to, otherwise, change step 3 over to;

Step 2 gets 1 with the amplification coefficient that traffic carrying capacity fluctuates in time;

Step 3, the nonuniformity coefficient that surpasses all moment traffic carrying capacitys of system's busy-hour traffic in the calculation plot, all traffic carrying capacitys when surpassing system busy when at first obtaining busy cells and ordering, the computing service amount sum that adds up successively accounts for the percentage that the percentage of all traffic carrying capacitys and ordering number account for all sequences number in order, traffic carrying capacity percentage and sequence number percentage are carried out linear fit and curve fit respectively, being presented on linear fit curve and curve fit curve with sequence number percentage is abscissa, with traffic carrying capacity percentage is in the chart of ordinate, obtain nonuniformity coefficient G

$G=\frac{\mathrm{SA}}{\mathrm{SA}+\mathrm{SB}}$

Wherein SA is the area between linear fit curve and the curve fit curve, and SB is that the curve fit curve is to the area between the transverse axis;

Be that the traffic carrying capacity of inscribing all base station cells during with difference is sued for peace the moment of summed result maximum during described system busy; It during described busy cells each maximum moment in traffic carrying capacity constantly in each sub-district;

Step 4, judge the size of nonuniformity coefficient G, if G＜0.2, the amplification coefficient that fluctuates in time of traffic carrying capacity all ratios of traffic carrying capacity mean values and system's busy-hour traffic constantly of equaling to surpass in the sub-district system's busy-hour traffic then, if 0.2＜G＜0.35, then the amplification coefficient that fluctuates in time of traffic carrying capacity equals 0.4+0.6 * sub-district busy-hour traffic/system's busy-hour traffic, if 0.35＜G＜0.45, then the amplification coefficient that fluctuates in time of traffic carrying capacity equals 0.3+0.7 * sub-district busy-hour traffic/system's busy-hour traffic, if G＞0.45, then the amplification coefficient that fluctuates in time of traffic carrying capacity equals 0.2+0.8 * sub-district busy-hour traffic/system's busy-hour traffic;

Step 5 is according to the distribution of amplification coefficient planning speech business and data service.

2. the traffic density time allocation method used therein in the mobile communication according to claim 1 is characterized in that: above-mentioned traffic carrying capacity is voice services volume or data business volume.

3. the traffic density method for distributing business in the mobile communication is characterized in that comprising:

Step 1,24 hours voice services volume A in calculation base station sub-district and data business volume B;

Step 2, the amplification coefficient that fluctuates in time of computing voice traffic carrying capacity A and data business volume B respectively in accordance with the method for claim 1;

Step 3 is calculated correlation coefficient r,

$r=\frac{\mathrm{Cov}(A,B)}{\sqrt{\mathrm{Cov}(A,A)\mathrm{Cov}(B,B)}}$

Wherein, Cov (A, B) covariance of expression A and B;

Step 4, the size of judgement r, if | r|≤0.404, then adopt the amplification coefficient of voice services volume A to amplify traffic density, if | r|＞0.404, then adopt the amplification coefficient of data business volume B to amplify traffic density.

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