WO2015157954A1

WO2015157954A1 - Data processing method and apparatus

Info

Publication number: WO2015157954A1
Application number: PCT/CN2014/075559
Authority: WO
Inventors: 黄帆; 张洁涛; 庄宏成
Original assignee: 华为技术有限公司
Priority date: 2014-04-17
Filing date: 2014-04-17
Publication date: 2015-10-22
Also published as: CN106465324A; CN106465324B

Abstract

The present invention relates to the field of communications. Disclosed are a data processing method and apparatus, which can estimate a quantity of users in a preset area more accurately. A specific scheme comprises: obtaining a user distribution probability density of a preset quantity of users; calculating a region probability of each user according to the user distribution probability density of the preset quantity of users; and calculating a user estimated value, p(k) or a service estimated value according to the region probability of each user. The present invention is used for data processing.

Description

Data processing method and device

Technical field

The present invention relates to the field of communications, and in particular, to a data processing method and apparatus.

Background technique

The wireless network can locate the user, such as a cellular network or a WLAN (Wireless Local Area Networks). A user can be a terminal device. According to the positioning result of the user, the user's distribution map can be obtained, and then the preset is obtained. The number of users, traffic, throughput, or other statistics in the range is selected according to the obtained statistics, or the capacity and coverage of the base station are optimized according to the obtained statistical values.

However, there are errors in the positioning of the user in the prior art. For example, the positioning error range of the GPS (Global Positioning System) is about 10 meters, and the order of the cellular network positioning is about 100 meters. In addition, due to differences in environment, etc. Other errors will also occur. In the prior art, the center point of the user range that is located is used as the user location, so that the number of users, traffic, throughput, or other statistical values obtained within the preset range is inaccurate.

Summary of the invention

Embodiments of the present invention provide a data processing method and apparatus that can more accurately estimate the number of users within a preset range.

In order to achieve the above object, the embodiment of the present invention adopts the following technical solutions:

In a first aspect, a data processing apparatus includes:

An acquiring unit, configured to obtain a user distribution probability density of a preset number of users, where a user distribution probability density of each of the preset number of users is a probability of the user in a unit area;

a calculating unit, configured to calculate an area probability of each user according to a user distribution probability density of the preset number of users acquired by the acquiring unit, where an area probability of each user is that the user is in a preset area The probability;

The calculating unit is further configured to calculate a user estimated value, a corpse or a service estimated value according to the regional probability of each user, where the user estimated value is an estimated value of the number of users in the preset area, The corpse is a probability that a user exists in the preset area, and the service estimated value is an estimated value of the user traffic in the preset area. In combination with the first aspect, in a first possible implementation manner,

m

The calculating unit is further configured to calculate the user estimated value according to the first formula t=∑;

Where t/ is the estimated value of the user, which is the number of valid users, and the valid user is a user whose area probability is greater than 0, and is the area probability of the first valid user.

With reference to the first aspect, in a second possible implementation manner, the calculating unit is further configured to use the second formula p(^>= s

=1

Where t = C _m ^k is the number of valid combinations, and the effective combination is a combination of users in the preset area, which is the number of valid users, and the effective user is a user whose area probability is greater than 0, a probability that there are ^ users in the preset area in the first combination of the effective combinations.

In combination with the second possible implementation of the first aspect, in a third possible implementation manner,

The calculating unit is further configured to calculate the user estimated value according to a third formula [/=; _χ ^));

Where t/ is the estimated value of the user.

In combination with the second possible implementation of the first aspect, in a fourth possible implementation,

The calculating unit is further configured to calculate the y according to the fourth formula ⁼ Γ1 ΓΊΟ-

Wherein, the set of users in the first combination of the effective combinations is a user

The regional probability of _y, = {Λ. ₂ , ··· y _k } , y _x , = 2, ··· :) is the Xth user in the ^.

In combination with the first aspect, in a fifth possible implementation,

The obtaining unit is further configured to acquire a traffic volume of each valid user, where the effective user is a user whose area probability is greater than 0; the calculating unit is further configured to calculate the service according to a fifth formula=£(w _iX estimated value; The estimated value of the service, the number of the valid users, is the traffic volume of the first user in the effective user, and A is the regional probability of the first user in the effective user.

In conjunction with the first aspect or any one of the possible implementations of the first aspect, in a sixth possible implementation,

The calculating unit is further configured to calculate a regional probability of the user according to the sixth formula = i /W^;

Where Λ· is the regional probability of the user, /(X) is the user distribution probability density of the user, and X is the unit area, which is the preset area.

In a second aspect, a data processing apparatus includes a processor, a memory, and a bus, wherein the processor and the memory are connected to each other through the bus;

The processor is configured to obtain a user distribution probability density of a preset number of users, where a user distribution probability density of each of the preset number of users is a probability that the user is in a unit area;

The processor is further configured to calculate an area probability of each user according to a user distribution probability density of the preset number of users, where an area probability of each user is a probability that the user is in a preset area;

The processor is further configured to calculate a user estimated value, a corpse or a service estimated value according to the regional probability of each user, where the user estimated value is an estimated value of the number of users in the preset area, The corpse is a probability that a user exists in the preset area, and the service estimated value is an estimated value of the user traffic in the preset area.

In combination with the second aspect, in a first possible implementation manner,

m

The processor is further configured to calculate the user estimate according to the first formula f/=∑^;

With reference to the second aspect, in a second possible implementation, the processor is further configured to calculate, according to the second formula, Ρ(Α) = θ Wherein, t = C _m ^k , which is the number of valid combinations, the effective combination is a combination of users in the preset area, and the number of valid users is the number of valid users, and the effective user is a user whose area probability is greater than 0, AO And a probability that there is a user in the preset area in the first combination of the effective combinations.

In combination with the second possible implementation of the second aspect, in a third possible implementation manner,

The processor is further configured to calculate the user estimate according to a third formula [/ = ; _x pt));

Where t/ is the estimated value of the user.

In conjunction with the second possible implementation of the second aspect, in a fourth possible implementation,

The processor is further configured to calculate according to the fourth formula (^ ⁼ Γ1 Γ1Ο ^_

The region probability of _y, ={Λ. y ₂ ■■■ _k } , y _XJ (x = 2, ··· ^:) is the Xth user in the ^.

In combination with the second aspect, in a fifth possible implementation manner,

The processor is further configured to acquire a traffic volume of each valid user, where the effective user is a user whose area probability is greater than 0; and the processor is further configured to calculate, according to a fifth formula, έ(^,· ^Χ Business estimate

The estimated value of the service, the number of the valid users, is the traffic volume of the first user in the effective user, and A is the regional probability of the first user in the effective user.

With reference to the second aspect or any one of the possible implementation manners of the second aspect, in a sixth possible implementation manner,

The processor is further configured to calculate a region probability of the user i according to the sixth formula = i/W^; Where Λ· is the regional probability of the user, /(X) is the user distribution probability density of the user, and X is the unit area, which is the preset area.

In a third aspect, a data processing method includes:

And obtaining a user distribution probability density of the preset number of users, where a user distribution probability density of each of the preset number of users is a probability that the user is in the unit area;

Calculating, according to the user distribution probability density of the preset number of users, an area probability of each user, where the area probability of each user is a probability that the user is in a preset area;

And calculating, according to the regional probability of each user, a user estimate, P(k or a service estimation value, where the user estimation value is an estimated value of the number of users in the preset area, where the corpse (A) is The probability that there is a user in the preset area, and the service estimated value is an estimated value of the user traffic in the preset area.

With reference to the third aspect, in a first possible implementation manner, the calculating the user estimation value according to the regional probability of each user includes:

m

Calculating the user estimate according to the first formula f/=∑^; wherein t/ is the user estimated value, which is the number of valid users, and the effective user is a user whose area probability is greater than 0, and is the first The area probability of a valid user.

With reference to the third aspect, in a second possible implementation, the calculating the corpse O) according to the regional probability of each user includes:

Calculate the corpse according to the second formula corpse = ∑ Pj (k) ( ;

=1

Where t = C _m ^k is the number of valid combinations, and the effective combination is a combination of users in the preset area, which is the number of valid users, and the effective user is a user whose area probability is greater than 0, And a probability that there is a user in the preset area in the first combination of the effective combinations.

With reference to the two possible implementation manners of the third aspect, in a third possible implementation, the calculating the user estimation value according to the regional probability of each user includes: The user estimate is calculated according to a third formula = ^ x P(A)); wherein t/ is the user estimate.

In combination with the two possible implementation manners of the third aspect, in a fourth possible implementation manner, the method includes:

According to the fourth formula ^p j (^) ⁼ Γ1 Γ 1 ( ^1_ calculate the AO); wherein, the set of users in the first combination of the effective combinations is a user

The regional probability of _y, = {Λ . y ₂ ■■■ y _k } , y _XJ (x = 2, ·· · ^:) is the Xth user in the ^.

With reference to the third aspect, in a fifth possible implementation, the calculating the service estimation value according to the regional probability of each user includes:

Obtaining a traffic volume of each valid user, where the effective user is a user whose area probability is greater than 0; calculating the service estimation value according to a fifth formula = 3⁄4 ( ν,· ><;

The estimated value of the service, the number of the valid users, is the traffic volume of the first user in the effective user, and the corpse is the regional probability of the first user in the effective user.

With reference to the third aspect or any one of the possible implementation manners of the third aspect, in a sixth possible implementation manner, the determining, according to the user distribution probability density of the preset number of users, an area probability of each user, including :

Calculating the regional probability of the user according to the sixth formula = where Λ· is the regional probability of the user, /(X) is the user distribution probability density of the user, and X is the unit area, and the preset area is .

The data processing method and device provided by the embodiment of the present invention calculates the user distribution probability density of a preset number of users, and calculates the regional probability of each user according to the user distribution probability density of the preset number of users, according to each user's The regional probability calculation user estimate, corpse or business estimate can more accurately estimate the number of users in the preset range.

DRAWINGS

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following will BRIEF DESCRIPTION OF THE DRAWINGS The drawings used in the description of the embodiments are briefly described. It is obvious that the drawings in the following description are only some embodiments of the present invention, and those skilled in the art, without any creative work, Other drawings may also be obtained from these drawings.

1 is a schematic structural diagram of a data processing apparatus according to an embodiment of the present invention; FIG. 2 is a schematic structural diagram of a data processing apparatus according to another embodiment of the present invention; FIG. 3 is a schematic diagram of a data processing apparatus according to an embodiment of the present invention; Schematic diagram of the data processing method flow.

detailed description

The technical solutions in the embodiments of the present invention are clearly and completely described in the following with reference to the drawings in the embodiments of the present invention. It is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments of the present invention without creative efforts are within the scope of the present invention.

The embodiment of the present invention provides a data processing apparatus for use in a wireless network. Referring to FIG. 1, the data processing apparatus 101 includes an obtaining unit 101 1 and a computing unit 1012.

The obtaining unit 101 1 is configured to obtain a user distribution probability density of a preset number of users, where a user distribution probability density of each of the preset number of users is a probability of the user in the unit area.

The calculating unit 1012 is configured to calculate an area probability of each user according to a user distribution probability density of a preset number of users acquired by the obtaining unit 101 1 , wherein the area probability of each user is a probability that the user is in the preset area.

The calculating unit 1012 is further configured to calculate a user estimated value, a corpse (or a service estimated value, according to an area probability of each user, where the user estimated value is an estimated value of the number of users in the preset area, and the corpse is a preset area. The probability of the user, the estimated value of the service is an estimate of the amount of user traffic in the preset area.

The data processing apparatus provided by the embodiment of the present invention calculates the user distribution probability density of a preset number of users, calculates the regional probability of each user according to the user distribution probability density of the preset number of users, and calculates the user according to the regional probability of each user. Estimates, corpses (A), or business estimates provide a more accurate estimate of the number of users in the preset range.

Optionally, in the first application scenario, the calculating unit 1012 is further configured to perform according to the first The formula f/ = ^ calculates the user estimate.

Where '-t/ is the user's estimated value, m is the number of valid users, and the effective user is the user whose area probability is greater than 0, which is the area probability of the first valid user.

Optionally, in the second application scenario, the calculating unit 1012 is further configured to calculate P according to the second formula corpse ( )= ο.

=1

Where t = c _m ^k , which is the number of valid combinations, the effective combination is the combination of users in the preset area, the number of valid users, the effective user is the user whose area probability is greater than 0, and O) is the effective combination The probability that there are users in the preset area in the combination.

The calculating unit 1012 is further configured to calculate a user estimated value according to the third formula [/ = ; ( P t)).

Where t/ is the user's estimated value, which is the number of valid users, and the effective user is the user whose area 4 is greater than 0.

Further optionally, the calculating unit 1012 is further configured to calculate ^) according to the fourth formula ^S^d.

Where ^ is the set of users in the first combination of valid combinations, the area probability of user _y, . = {Λ. yi ■■■ Λ , y _XJ (x = 2, ··· ^:) is ^ Dijon: Users.

Optionally, in the third application scenario, the obtaining unit 1011 is further configured to obtain a service volume of each valid user, where the effective user is a user whose area probability is greater than 0. The calculating unit 1012 is further configured to calculate a service estimated value according to the fifth formula = £(w _iX .

Among them, the estimated value for the service, the number of valid users, the traffic volume of the first user in the effective user, the corpse, is the regional probability of the first user in the effective user. Optionally, the calculating unit 1012 is further configured to calculate a region probability of the user i according to the sixth formula = ί.

Where Λ· is the regional probability of the user, /(X) is the user's distribution probability density, and X is the unit area, which is the preset area. The data processing apparatus provided by the embodiment of the present invention calculates the user distribution probability density of a preset number of users, calculates the regional probability of each user according to the user distribution probability density of the preset number of users, and calculates the user according to the regional probability of each user. Estimates, corpses (A), or business estimates provide a more accurate estimate of the number of users in the preset range.

Another embodiment of the present invention provides a data processing apparatus 2001. Referring to FIG. 2, the apparatus may be embedded or itself a microprocessor computer, such as a general-purpose computer, a custom machine, a mobile terminal, or a tablet device. The data processing apparatus 2001 comprises: at least one processor 201 1 , a memory 2012 and a bus 2013, and the at least one processor 201 1 and the memory 2012 are connected by a bus 2013 and complete communication with each other.

The bus 2013 can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component) bus, or an EISA (Extended Industry Standard Architecture) bus. The bus 2013 can be divided into an address bus, a data bus, a control bus, and the like. For ease of representation, only one thick line is shown in Figure 2, but it does not mean that there is only one bus or one type of bus. among them:

The memory 2012 is used to execute the application code of the inventive scheme, and the application code for executing the inventive scheme is stored in a memory and controlled by the processor 201 1 for execution.

The memory can be a read only memory ROM or other type of static storage device that can store static information and instructions, a random access memory RAM or other type of dynamic storage device that can store information and instructions, or can be electrically erasable or programmable. Read-only memory EEPROM, CD-ROM or other optical disc storage, optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), disk storage media or other magnetic storage devices, or can be used for Any other medium that carries or stores the desired program code in the form of an instruction or data structure and that can be accessed by a computer, but is not limited thereto. These memories are connected to the processor via a bus.

The processor 201 1 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one configured to implement the embodiment of the present invention. Or multiple integrated circuits.

The processor 201 1 is configured to call the program code in the memory 2012, in a possible real In the implementation manner, when the above application is executed by the processor 2011, the following functions are implemented. The processor 2011 is configured to obtain a user distribution probability density of a preset number of users, where a user distribution probability density of each of the preset number of users is a probability that the user is in the unit area.

The processor 2011 is further configured to calculate an area probability of each user according to a user distribution probability density of the preset number of users, where the area probability of each user is a probability that the user is within the preset area.

The processor 2011 is further configured to calculate a user estimated value, a corpse or a service estimated value according to an area probability of each user, where the user estimated value is an estimated value of the number of users in the preset area, and the corpse is a user in the preset area. Probability, the service estimate is an estimate of the amount of user traffic in the preset area.

Optionally, in the first application scenario, the processor 2011 is further used according to the first

m

The formula f/ = ^ calculates the user estimate. Where t/ is the user's estimated value, which is the number of valid users, and the effective user is the user whose area probability is greater than 0, and is the area probability of the first valid user.

Optionally, in the second application scenario, the processor 2011 is further configured to calculate the corpse according to the second formula corpse = W 0).

=1

Processor 2011 is also used to calculate user estimates based on the third formula [/ = ;( P t)).

Where t/ is the user's estimated value, which is the number of valid users, and the effective user is the area. 4 users with a rate greater than 0.

Further optional, processor 2011, is also used according to the fourth formula

Corpse).

Where ^ is the set of users in the first combination of valid combinations, the area probability of user _y, . = {Λ. ... _k } ' y _x A ^x = ¹ ^ ² , ... is the xth user in ^ .

Optionally, in the third application scenario, the processor 2011 is further configured to obtain the traffic volume of each valid user, and the effective user is a user whose area probability is greater than 0. The processor 2011 is further configured to calculate a service estimation value according to a fifth formula = £( ν,·><, where, for the service estimation value, the number of valid users, the traffic of the first user in the effective user, the corpse, The area probability of the first user in the active user.

Optionally, the processor 2011 is further configured to calculate a region probability of the user i according to the sixth formula = i W^.

Among them, Λ· is the regional probability of the user, /(X) is the user's distribution probability density, and X is the unit area, which is the preset area.

Based on the embodiment corresponding to FIG. 1 above, an embodiment of the present invention provides a data processing method, which is applied to the data processing apparatus described in the embodiment corresponding to FIG. 1, and is shown in FIG.

301. Obtain a user distribution probability density of a preset number of users.

Among them, the user distribution probability density of a user is the probability of the user in the unit area.

Optionally, the user distribution probability density of the user within a certain range may be a constant, that is, the probability that the user appears in each position within a certain range is equal, and the user is evenly distributed within a certain range. Alternatively, the center position of the preset area is used as a reference point, and the distribution probability density of the user is h(x), which represents the probability that the user appears at a position X from the reference point, so that the user and the user can be calculated. The probability that the reference point distance is within "is

Η ) - h x)dx. Alternatively, the user's distribution probability density is a function / (X), /(X) represents the probability that the user appears at the location JC, and JC is a unit area. /(X) can be a discrete function or a continuous function.

Of course, there are many cases in which the user's user distribution probability density is not limited to the three forms listed in the embodiment, and is merely exemplified herein, and does not mean that the present invention is limited to the user probability density of the three forms.

302. Calculate an area probability of each user according to a user distribution probability density of a preset number of users.

The area probability of a user is the probability that the user is within the preset area.

In combination with the description in step 301, optionally, when the user distribution probability density of the user is constant in the preset area, the user distribution probability density of the user is multiplied by the area of the user within the preset area. The regional probability of the user, that is, XS, where Λ is the user's regional probability, α is the user's user distribution probability density, and S is the user's distribution range within the preset area.

Alternatively, the center position of the preset area is used as a reference point, and the distribution probability density of the user is h (x), and ζ θ) represents the probability that the user appears at a position of X from the reference point, and the user The regional probability is = [ h{x)dx , where Λ· is the user's regional probability, “the farthest distance between the location where the user may appear in the preset area and the reference point.

Alternatively, the distribution probability density of the user is a function / (X), /(X) represents the probability that the user appears at position X, and X is a unit area. According to the sixth formula

= ί ^^)^ Calculates the user's area probability. Among them, the corpse, the regional probability of the user, is the preset area.

Of course, there are many methods for calculating the regional probability of the user, and the present invention is only an example. The calculation of several regional probabilities does not mean that the invention is limited to these methods.

303. Calculate a user estimate, a corpse (A), or a business estimate based on the regional probability of each user.

The estimated value of the user is an estimated value of the number of users in the preset area, and the probability that the user is a user in the preset area, and the estimated value of the service is an estimated value of the user traffic in the preset area.

Specifically, in the first application scenario.

m

The user estimate is calculated according to the first formula f/=∑^, where t/ is the user estimate, m is the number of valid users, and the effective user is the user with the region probability greater than 0, and the corpse is the region probability of the first user. For example, there are a total of four users in the preset area with an area probability greater than 0, namely, users A, B, C, and D, and the regional probabilities of the four users in the preset area are respectively 0.1, 0.2, 0.3, 0.4 , then the user estimate in the preset area is

0. 1 +0.2+0.3+0.4= 1.

Optionally, in the second application scenario.

Calculate the corpse according to the second formula =( = ), t = C _m ^k , which is a valid combination

=1

The number of effective combinations is the combination of users in the preset area, which is the probability that there is a user in the preset area in the first combination of the effective combination. Further optionally, the user estimate is calculated according to the third formula = ; _χ ^)), where t/ is the user estimate, m is the number of valid users, and the effective user is the user whose region probability is greater than 0. Further, if each user is independent of each other in the preset area, according to the fourth formula s^n no-, wherein ^ is a set of users in the first combination of the effective combination, and is the area of the user_y Probability, = ^ _w y ₂ ■■■ y _k } , y _X (x = 2, ... is the JC user in the middle, here, it should be noted that when k is the number of valid users, the effective combination There is only one combination, that is, all valid m

The collection of households, at this time, the corpse (w) = f, corpse, is the regional probability of the first user.

=1

For example, there are four users in the preset area whose area probability is greater than 0, which are respectively users A, B, C, D, and whether 4 users are independent of each other in the preset area, and 4 The area probability of the user in the preset area is 0.1, 0.2, 0.3, and 0.4, respectively.

(1) There are four valid combinations of one user in the preset area, which are A, B, C, and D respectively.

The probability that only A exists in the preset area, that is, the probability of the first combination is corpse O.l X (1-0.2) (1-0.3) X (1-0.4)=0.0336;

There is only a probability of B in the preset area, that is, the probability of the second combination is corpse ₂ (1) two 0.2 X (1-0.1) (1-0.3) X (1-0.4) = 0.0756;

There is only a probability of C in the preset area, that is, the probability of the third combination is corpse ₃ (1) = 0.3 X (1-0.1) (1-0.2) X (1-0.4) = 0.1296;

There is only a probability of D in the preset area, that is, the probability of the fourth combination is corpse ₄ (1) = 0.4 X (1-0.1) (1-0.2) X (1-0.3) = 0. 2016.

Then there is a probability of 1 user in the preset area (1) = ^(1) + corpse ₂ (1) + corpse ₃ (1) + corpse ₄ (1) = 0.4404.

(2) There are 6 valid combinations of 2 users in the preset area, which are AB, AC, AD, BC, BD, CD.

The probability that only AB exists in the preset area, that is, the probability of the first combination is two 0.1 0.2 (1-0.3) (1-0.4)=0.0084;

There is only the probability of AC in the preset area, that is, the probability of the second combination is corpse ₂ (2) = 0.1 X 0.3 (1-0.2) X (1-0.4) = 0.0144;

The probability that only AD exists in the preset area, that is, the probability of the third combination is Ρ ₃ (2)=0.1

X 0.4 (1-0.2) X (1-0.3)=0.0224;

The probability that only BC exists in the preset area, that is, the probability of the fourth combination is

X 0.3 (1-0.1) X (1-0.4)=0.0324;

The probability that only BD exists in the preset area, that is, the probability of the fifth combination is corpse ₅ (2) two 0.2 X 0.4 (1-0.1) X (1-0.3)=0.0504;

The probability that only CD exists in the preset area, that is, the probability of the sixth combination is corpse ₆ (2) = 0.3 0.4 (1-0.1) (1-0.2) = 0.0864;

There is a probability of 2 users in the preset area (2) = Ρχ {2) + corpse ₂ (2) + corpse ₃ (2) + 4 (2) + Ρ ₅ (2) + corpse ₆ (2) = 0.2144. (3) There are 4 valid combinations of 3 users in the preset area, which are: ABC, ABD, ACD, BCD.

The probability that only ABC exists in the preset area, that is, the probability of the first combination is

?ι(3)=0.1 X 0.2 0.3 X (1-0.4)=0.0036;

The probability that only ABD exists in the preset area, that is, the probability of the second combination is corpse ₂ (3) = 0.1 X 0.2 0.4 (1-0.3) = 0.0056;

There is only the probability of ACD in the preset area, that is, the probability of the third combination is corpse ₃ (3) = 0.1 X 0.3 X 0.4 (1-0.2) = 0.0096;

There is only a probability of BCD in the preset area, that is, the probability of the fourth combination is corpse 4(3)=0.2 0.3 0.4 (1-0.1)= 0.0216.

There are 3 probabilities in the default area (3) = Λ (3) + corpse ₂ (3) + corpse ₃ (3) + corpse 4 (3) = 0.0404.

(4) There is one ABCD in the effective combination of 4 users.

(4) = 0.1 0.2 0.3 0.4 = 0.0024.

According to the third formula, the user estimate in the preset area can be calculated. 1/=1 X P(l)+ 2 X P(2)+ 3 corpse (3)+ 4 corpse (4)=1.

Optionally, in the third application scenario.

Obtain the traffic of each valid user. The effective user is the user whose area probability is greater than 0. According to the fifth formula = £ (w _iX calculates the service estimation value, where is the service estimation value, the number of valid users, the traffic volume of the first user in the effective user, the corpse, the regional probability of the first user in the effective user .

For example, there are four users in the preset area whose area probability is greater than 0, which are users A, B, C, and D, respectively, whether the four users are independent of each other in the preset area, and four users are in the preset area. The regional probabilities are 0.1, 0.2, 0.3, and 0.4, respectively, and the traffic volume of the four users in the preset area is 10, 20, 30, and 40, respectively. Then, according to the fifth formula, the estimated value of the service in the preset area can be calculated as W=0.1 X 10+0.2 20, 0.3 χ 30, 0.4 x 40=30.

Usually, a preset area can be used as a grid to divide a geographical location within a certain range into multiple grids, and the user estimate in each grid is calculated by the area probability. Value, corpse ( ) or business estimate, taking into account the probability of each user in the grid, based on these calculations, you can more accurately estimate the number of users or traffic in different grids, and choose to add new base stations accordingly. Location or optimize the capacity and coverage of the base station.

The data processing method provided by the embodiment of the present invention calculates the user distribution probability density of a preset number of users, calculates the regional probability of each user according to the user distribution probability density of the preset number of users, and calculates the user according to the regional probability of each user. Estimates, corpses (A), or business estimates provide a more accurate estimate of the number of users in the preset range.

From the description of the above embodiments, those skilled in the art can clearly understand that the present invention can be implemented in hardware, firmware implementation, or a combination thereof. When implemented in software, the functions described above may be stored in or transmitted as one or more instructions or code on a computer readable medium. Computer readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one location to another. A storage medium may be any available media that can be accessed by a computer. For example, but not limited to: the computer readable medium may include RAM (Random Access Memory), ROM (Read Only Memory), and EEPROM (Electrically Erasable Programmable Read Only Memory). Read memory), CD-ROM (Compact Disc Read Only Memory) or other optical disc storage, disk storage media or other magnetic storage device, or can be used to carry or store desired programs in the form of instructions or data structures. Code and any other medium that can be accessed by a computer. Also. Any connection may suitably be a computer readable medium. For example, if the software is transmitted from a website, server, or other remote source using coaxial cable, fiber optic cable, twisted pair, DSL (Digital Subscriber Line), or wireless technologies such as infrared, radio, and microwave, Then coaxial cable, fiber optic cable, twisted pair, DSL or wireless technologies such as infrared, wireless and microwave are included in the fixing of the associated medium. As used in the present invention, the disc and the disc include a CD (Compact Disc), a laser disc, a disc, a DVD disc (Digital Versatile Disc), a floppy disc, and a Blu-ray disc, wherein the disc is usually magnetically copied, The disc uses a laser to optically replicate the data. Combinations of the above should also be included within the scope of the computer readable media.

The above description is only a specific embodiment of the present invention, but the scope of protection of the present invention is not It is to be understood that those skilled in the art are susceptible to variations and substitutions within the scope of the present invention. Therefore, the scope of the invention should be determined by the scope of the claims.

Claims

claims

1. A data processing device, characterized in that it includes:

The acquisition unit is used to obtain the user distribution probability density of a preset number of users, wherein the user distribution probability density of each user in the preset number of users is the probability of the user in the unit area;

The calculation unit is configured to calculate the area probability of each user according to the user distribution probability density of the preset number of users obtained by the acquisition unit, wherein the area probability of each user is when the user is within the preset area. The probability;

The calculation unit is also configured to calculate a user estimate, a service estimate, or a service estimate based on the regional probability of each user, where the user estimate is an estimate of the number of users in the preset area, so Said body is the probability that a user exists in the preset area, and the business estimate value is an estimate value of the user's traffic volume in the preset area.

2. The device according to claim 1, characterized in that,

m

The calculation unit is also used to calculate the user estimated value according to the first formula =∑;

Wherein, t/ is the estimated user value, is the number of effective users, the effective users are users whose regional probability is greater than 0, and Λ is the regional probability of the th effective user.

3. The device according to claim 1, characterized in that the calculation unit is also used to calculate the P(J&,

=1

Among them, t = C _m ^k , is the number of valid combinations, the valid combination is a combination of users existing in the preset area, is the number of valid users, and the valid users are users with a regional probability greater than 0, AO ) is the probability that users exist in the preset area in the th combination of the effective combinations.

4. The device according to claim 3, characterized in that,

The calculation unit is also used to calculate the user estimated value according to the third formula [/ =; (^));

Among them, t/ is the user estimated value.

5. The device according to claim 3, characterized in that, The calculation unit is also used to calculate the above according to the fourth formula (ΓΊ ΓΊΟ—);

Among them, is the set of users in the th combination of the effective combinations, is the user

_y's regional probability, = {Λ . y ₂ ■■■ y _k } , y _XJ (x = 2, ··· ^:) is the Xth user in ^.

6. The device according to claim 1, characterized in that,

The acquisition unit is also used to obtain the traffic volume of each effective user, and the effective user is a user with a regional probability greater than 0; the calculation unit is also used to calculate the result according to the fifth formula = £(ν,·χ estimated business value;

Where, is the business estimate value, is the number of the effective users, is the traffic volume of the th user among the effective users, and A is the regional probability of the th user among the effective users.

7. The device according to any one of claims 1-6, characterized in that,

The calculation unit is also used to calculate the user's regional probability according to the sixth formula =i/W^;

Wherein, Λ· is the area probability of the user, /(X) is the user distribution probability density of the user, X is the unit area, and is the preset area.

8. A data processing device, characterized in that it includes a processor, a memory and a bus, and the processor and the memory are connected to each other through the bus;

Wherein, the processor is configured to obtain the user distribution probability density of a preset number of users, wherein the user distribution probability density of each user in the preset number of users is the probability of the user within the unit area;

The processor is further configured to calculate the area probability of each user according to the user distribution probability density of the preset number of users, wherein the area probability of each user is the probability of the user being in the preset area;

The processor is also configured to calculate a user estimate, a user estimate, or a service estimate based on the regional probability of each user, wherein the user estimate is an estimate of the number of users in the preset area, and Corpse (is the concept of a user in the preset area rate, and the estimated traffic value is an estimated value of user traffic volume in the preset area.

9. The device according to claim 8, characterized in that,

m

The processor is also configured to calculate the user estimate value according to the first formula f/ =∑; wherein, t/ is the user estimate value, is the number of effective users, and the effective users are those with regional probability greater than 0 User, is the regional probability of the th effective user.

10. The device according to claim 8, characterized in that the processor is also used to calculate the

=1

Wherein, t = C _m ^k , is the number of valid combinations, the valid combination is a combination of users existing in the preset area, is the number of valid users, and the valid users are users whose regional probability is greater than 0, is The probability that users exist in the preset area in the th combination of the effective combinations.

11. The device according to claim 10, characterized in that,

The processor is also used to calculate the user estimated value according to the third formula [/ = ; _x P t));

Among them, t/ is the user estimated value.

12. The device according to claim 10, characterized in that,

The processor ^is also configured to calculate ^the

Among them, is the set of users in the th combination of the effective combinations, is the regional probability of user_y, ={ y ₂ ■■■ y _k ) , y _XJ (x = 2, ··· ^:) is the The Xth user in the above list.

13. The device according to claim 8, characterized in that,

The processor is also used to obtain the traffic volume of each effective user, and the effective user is a user with a regional probability greater than 0; the processor is also used to calculate all the traffic according to the fifth formula =έ(^,· ^χ estimated business value;

Among them, is the estimated service value, is the number of effective users, is the is the traffic volume of the th user among the effective users, and A is the area probability of the th user among the effective users.

14. The device according to any one of claims 8 to 13, characterized in that the processor is also used to calculate the user's area probability according to the sixth formula =ί;

15. A data processing method, characterized by including:

Obtain the user distribution probability density of a preset number of users, where the user distribution probability density of each user in the preset number of users is the probability of the user in the unit area;

Calculate the area probability of each user according to the user distribution probability density of the preset number of users, where the area probability of each user is the probability of the user within the preset area;

Calculate user estimation value, P(k or service estimation value according to the regional probability of each user, wherein the user estimation value is an estimation value of the number of users in the preset area, and P(A) is the The probability that a user exists in the preset area, and the business estimate value is an estimate of the user traffic volume in the preset area.

16. The method according to claim 15, characterized in that: calculating the user estimate based on the regional probability of each user includes:

m

Calculate the user estimate value according to the first formula f/ =∑; where, t/ is the user estimate value, is the number of effective users, the effective users are users with regional probability greater than 0, Λ is the th Regional probability of effective users.

17. The method according to claim 15, characterized in that the calculation of the regional probability according to each user includes:

Calculate the body according to the second formula = W; where, _tcm ^k , is the number of valid combinations, the valid combination is a combination of users existing in the preset area, is the number of valid users, and the valid users for the district The user whose domain probability is greater than 0 is the probability that there are users in the preset area in the th combination of the effective combinations.

18. The method according to claim 17, characterized in that: calculating the user estimate value according to the regional probability of each user includes:

The user estimated value is calculated according to the third formula =; _Xj P t)); where t/ is the user estimated value.

19. The method according to claim 17, characterized in that it includes:

Calculate the P according to the fourth formula ^P j (^) ⁼ Γ1 Γ1( ^1_ , where is the set of users in the J'th combination of the effective combinations, and is the user

_y's regional probability, ={Λ. y ₂ ■■■ y _k } , y _XJ (x = 2, ··· ^:) is the Xth user in ^.

20. The method according to claim 15, characterized in that: calculating the service estimate value according to the regional probability of each user includes:

Obtain the business volume of each effective user, and the effective user is a user with a regional probability greater than 0; Calculate the business estimate value according to the fifth formula = £(ν,· _Χ ;

21. The method according to any one of claims 15 to 20, wherein calculating the regional probability of each user based on the user distribution probability density of the preset number of users includes:

Calculate the user's area probability according to the sixth formula = i/W^; where, Λ· is the area probability of the user, /(X) is the user distribution probability density of the user, X is the unit area, and Describe the default area.