WO2016086406A1

WO2016086406A1 - Network resource deployment method and device

Info

Publication number: WO2016086406A1
Application number: PCT/CN2014/093124
Authority: WO
Inventors: 刘敬全; 宁晋炜; 贾铭
Original assignee: 华为技术有限公司
Priority date: 2014-12-05
Filing date: 2014-12-05
Publication date: 2016-06-09
Also published as: CN105580407A; CN105580407B

Abstract

Disclosed are a network resource deployment method and device, comprising: respectively acquiring historical data generated by a network within at least one set time period; with regard to the acquired historical data within each set time period, fitting same to obtain a curvilinear function between the number of user terminals corresponding to the access type and information about network resources consumed by the user terminals; when a subsequent network resource deployment is performed, with regard to any access type, utilizing the curvilinear function corresponding to the access type obtained by fitting to predict information about network resources needing to be consumed under the number of user terminals accessing the network of the access type; and utilizing the predicted information about network resources needing to be consumed by the user terminals accessing the network of various access types to perform the network resource deployment, which achieves the early planning for a network deployment, avoids the problems that network capacity shortage hinders the development of a network and deceases the quality of service of the network, etc., thereby improving the network performance.

Description

Network resource deployment method and device

Technical field

The present invention relates to the field of wireless communication technologies, and in particular, to a network resource deployment method and device.

Background technique

With the rapid development of the global MBB (English: Mobile and Broad) network, the number of services and the number of users have grown rapidly. During the network deployment phase, it is necessary to predict future resource requirements based on network users and service development, and perform network planning based on the predicted results, which can effectively avoid the problem of low network performance caused by network capacity problems.

Currently, the way to predict the future resource requirements of the network includes but is not limited to:

The first way: through the extraction of historical network data, based on the growth trend of traffic volume in historical data and the increasing trend of the number of users, predict the growth of traffic and number of users in the network for a period of time, and according to Predict the results and obtain the distribution of future users and traffic.

Defects: The first method predicts the growth trend of traffic and number of users in the network, but cannot determine the consumption requirements of network resources, which is not conducive to guiding the deployment of network resources.

The second way: based on the first method, predict the consumption demand of network resources by introducing proportional parameters. For example, the current network resource is x. By extracting the historical data of the network and determining that the proportional parameter is increased by 5 times, the network resource demand of the predicted network in the future is 5x.

Defects: Although the second method predicts the consumption demand of network resources, it provides a reference for network deployment. However, the resource demand and the growth trend of traffic volume and the growth trend of the number of users are nonlinear, and the single utilization ratio The parameters predict the demand of future network resources, which makes the difference between the predicted result and the actual required result larger, which leads to the possibility of resource shortage or resource waste in the deployed network, which is not conducive to the improvement of network performance.

Summary of the invention

In view of this, the embodiments of the present invention provide a network resource deployment method and device, which are used to solve the problem that the resource shortage caused by the existing network resource deployment process leads to low network performance.

According to a first aspect of the present invention, a network resource deployment method is provided, including:

Collecting historical data generated by the network in at least one set time period, where the historical data includes an access type of the user terminal accessing the network and network resource information consumed by the user terminal;

The number of user terminals belonging to the same access type and the network consumed by the user terminal in the set time period are counted according to the access type included in the historical data for the historical data in each set time period. Resource information, establishing a correspondence between the access type, the number of user terminals, and network resource information consumed by the user terminal;

For each type of access, the access is obtained according to the correspondence between the number of user terminals corresponding to the access type established in each set time period and the network resource information consumed by the user terminal. a curve function between the number of user terminals corresponding to the type and the network resource information consumed by the user terminal;

The number of user terminals accessing the network in the access type is predicted for any type of access when the network resource is deployed;

And predicting, according to the obtained curve function between the number of user terminals corresponding to the access type and the network resource information consumed by the user terminal, and the predicted number of user terminals, predicting a user terminal accessing the network by using the access type The amount of network resource information that needs to be consumed;

The network resource deployment is performed by using the predicted network resource information that the user terminal accessing the network with various access types needs to consume.

With reference to the possible implementation manners of the first aspect of the present invention, in a first possible implementation, the user terminals belonging to the same access type in the set time period are counted according to the access type included in the historical data. The quantity and the network resource information consumed by the user terminal, and the correspondence between the access type, the number of user terminals, and the network resource information consumed by the user terminal, including:

If the access type included in the historical data is a generated service data type, the setting is counted. The number of user terminals that generate the service data type and the network resource information consumed by the user terminal in the time period, and establish a correspondence relationship between the generated service data type, the number of user terminals, and the network resource information consumed by the user terminal;

If the access type included in the historical data is an attachment activation type, the number of user terminals belonging to the attachment activation type and the network resource information consumed by the user terminal in the set time period are counted, and the attachment activation type and the user terminal are established. The correspondence between the quantity and the network resource information consumed by the user terminal;

If the access type included in the historical data is an online connection type, the number of user terminals belonging to the online connection type and the network resource information consumed by the user terminal in the set time period are counted, and the online connection type and the user terminal are established. The correspondence between the quantity and the network resource information consumed by the user terminal.

In conjunction with the possible implementation of the first aspect of the present invention, or the first possible implementation of the first aspect of the present invention, in a second possible implementation, the method further includes:

According to the access type included in the historical data, the number of user terminals belonging to the same access type in the set time period is statistically obtained according to the statistics of the historical data in each set time period. The number of user terminals corresponding to the service data type generated during the set time period, the number of user terminals corresponding to the activation type in the set time period, and the number of user terminals corresponding to the online connection type in the set time period Establishing a quantitative relationship between a user terminal that generates a service data type, a user terminal that attaches an activation type, and a user terminal that is an online connection type.

In conjunction with the second possible implementation of the first aspect of the present invention, in a third possible implementation, the method further includes:

A quantity relationship between a user terminal that generates a service data type, a user terminal that attaches an activation type, and a user terminal that is an online connection type that is established in each set time period is obtained, and the user terminal that generates the service data type is attached and attached. a quantity function between the activation type of user terminal and the online connection type of user terminal;

For any type of access, predict the number of user terminals accessing the network with this type of access Quantity, including:

When predicting the total number of user terminals accessing the network, the quantity function and the total number of user terminals predicted to obtain the access network are obtained according to the fitting, and the number of at least one type of user terminals is predicted:

The number of user terminals that generate the service data type, the number of user terminals to which the activation type is attached, and the number of user terminals of the online connection type.

In conjunction with the first possible embodiment of the first aspect of the invention, or in combination with the second possible embodiment of the first aspect of the invention, or in combination with the third possible embodiment of the first aspect of the invention, at the fourth In a possible implementation manner, the method further includes:

Obtaining network quality information and network traffic information in at least one set time period respectively;

Corresponding relationship between the generated service data type, the number of user terminals, and the network resource information consumed by the user terminal is established for the historical data in each set time period obtained, including:

The network quality information in the set time period, the network traffic information in the set time period, and the number of user terminals corresponding to the service data type generated during the set time period and the network consumed by the user terminal The resource information establishes a correspondence between the type of the generated service data, the number of user terminals, and the network resource information consumed by the user terminal.

With reference to the fourth possible implementation manner of the first aspect of the present invention, in a fifth possible implementation manner, the correspondence between the generated service data type, the number of user terminals, and the network resource information consumed by the user terminal is established, including :

Establishing a correspondence between the generated service data type, the number of the user terminals, and the physical resource block PRB resource utilization, wherein the physical resource block PRB resource utilization includes at least the uplink PRB resource utilization rate and the downlink PRB resource utilization ratio. a kind

and / or,

Establishing a mapping relationship between the type of the service data, the number of the user terminals, and the data transmission rate, where the physical resource block utilization includes at least one of an uplink data transmission rate and a downlink data transmission rate.

In conjunction with a possible embodiment of the first aspect of the invention, or in combination with the first aspect of the first aspect of the invention A possible embodiment, or a second possible embodiment incorporating the first aspect of the invention, or a third possible embodiment incorporating the first aspect of the invention, or a fourth possibility in combination with the first aspect of the invention In an implementation manner, or in combination with the fifth possible implementation manner of the first aspect of the present invention, in a sixth possible implementation manner, the number of user terminals corresponding to the access type and the network consumed by the user terminal are obtained. Curve functions between resource information, including:

Using the set data model, the curve function between the number of user terminals corresponding to the access type and the network resource information consumed by the user terminal is obtained, wherein the curve function obtained by the fitting includes function coefficients and function expressions. formula.

In conjunction with a possible embodiment of the first aspect of the invention, or a first possible embodiment of the first aspect of the invention, or a second possible embodiment of the first aspect of the invention, or in combination with the first aspect of the invention A third possible embodiment, or a fourth possible embodiment of the first aspect of the invention, or a fifth possible embodiment of the first aspect of the invention, or a combination of the first aspect of the invention In a seventh possible implementation manner, the network resource information that needs to be consumed in the number of user terminals that access the network by using the access type is included in the seventh possible implementation manner, including:

Using the predicted number of the user terminals, network resource information satisfying the condition of the number of user terminals accessing the network with the access type is determined from the curve function.

In conjunction with a possible embodiment of the first aspect of the invention, or a first possible embodiment of the first aspect of the invention, or a second possible embodiment of the first aspect of the invention, or in combination with the first aspect of the invention A third possible embodiment, or a fourth possible embodiment of the first aspect of the invention, or a fifth possible embodiment of the first aspect of the invention, or a combination of the first aspect of the invention Six possible implementation manners, or in combination with the seventh possible implementation manner of the first aspect of the present invention, in the eighth possible implementation manner, using the predicted user terminal accessing the network in various access types The network resource information consumed and network resource deployment, including:

If the network resource information that needs to be consumed by the user terminal that generates the service data type access network is predicted, the network resource information consumed by the user terminal that generates the service data type according to the prediction is Expand the target network resource information and determine the network resource expansion strategy;

The network resource is expanded and deployed according to the network resource expansion policy.

With reference to the eighth possible implementation manner of the first aspect of the present invention, in the ninth possible implementation manner, the network resource information includes a PRB resource utilization rate;

Determining a network resource expansion strategy according to the predicted network resource information consumed by the user terminal that generates the service data type and the expanded target network resource information, including:

Calculating a predicted quotient of the PRB resource utilization rate of the user terminal that generates the service data type and the target PRB resource utilization rate of the expanded capacity;

The product value is expanded with the expansion factor;

Calculate the difference between the product value and the set coefficient, and determine the calculated difference as the capacity expansion strategy of the PRB resource utilization.

With reference to the eighth possible implementation manner of the first aspect of the present invention, or the ninth possible implementation manner of the first aspect of the present invention, in the tenth possible implementation manner, the network resource information further includes Data transmission rate

Calculating a quotient of the predicted data transmission rate of the user terminal that generates the service data type and the target data transmission rate of the expanded capacity;

Calculating a difference between the quotient value and the set coefficient, and determining the calculated difference value as a capacity expansion strategy of the data transmission rate.

In conjunction with the eighth possible embodiment of the first aspect of the invention, or in combination with the ninth possible embodiment of the first aspect of the invention, or in combination with the tenth possible embodiment of the first aspect of the invention, In a possible implementation manner, the network resource information further includes a quantity of user terminals that generate a service data type;

Calculating the predicted number of user terminals that generate service data types and generating business data for capacity expansion The quotient of the number of target user terminals of the type;

Calculating a difference between the quotient value and the set coefficient, and determining the calculated difference value as a capacity expansion strategy for generating the number of user terminals of the service data type.

According to a second aspect of the present invention, a network resource deployment device is provided, including:

An acquiring module, configured to separately acquire historical data generated by a network in at least one set time period, where the historical data includes an access type of a user terminal accessing the network and network resource information consumed by the user terminal;

And a module is configured to collect, according to the access type included in the historical data, the number of user terminals belonging to the same access type in the set time period, and the historical data in each set time period acquired The network resource information consumed by the user terminal establishes a correspondence between the access type, the number of user terminals, and network resource information consumed by the user terminal;

The modeling module is configured to: according to the correspondence between the number of user terminals corresponding to the access type established in each set time period and the network resource information consumed by the user terminal, for each access type, Obtaining a curve function between the number of user terminals corresponding to the access type and the network resource information consumed by the user terminal;

And a prediction module, configured to predict, according to any access type, the number of user terminals accessing the network by using the access type, and based on the obtained user terminal corresponding to the access type The curve function between the number and the network resource information consumed by the user terminal and the predicted number of user terminals, and predict the network resource information that needs to be consumed under the number of user terminals accessing the network with the access type; The network resource information that the user terminal accessing the network with various access types needs to consume, and the network resource is deployed.

With reference to a possible implementation manner of the second aspect of the present invention, in a first possible implementation, the establishing module is specifically configured to: if the access type included in the historical data is a service data type, The number of user terminals that generate the service data type and the network resource information consumed by the user terminal in a fixed time period, and establish a correspondence relationship between the generated service data type, the number of user terminals, and the network resource information consumed by the user terminal;

If the access type included in the historical data is an attachment activation type, the set time is counted. The number of user terminals belonging to the attachment activation type and the network resource information consumed by the user terminal, and the correspondence between the attachment activation type, the number of user terminals, and the network resource information consumed by the user terminal;

With reference to the possible implementation manner of the second aspect of the present invention, or the first possible implementation manner of the second aspect of the present invention, in the second possible implementation manner, the network resource deployment device further includes: a quantity relationship establishing module ,among them:

The quantity relationship establishing module is specifically configured to: according to the historical data in each set time period acquired, according to the access type included in the historical data, belong to the same access in the set time period After the number of types of user terminals, the number of user terminals corresponding to the service data type generated during the set time period according to the statistics, the number of user terminals corresponding to the activation type in the set time period, and the set time period The number of user terminals corresponding to the online connection type establishes a quantitative relationship between the user terminal that generates the service data type, the user terminal that attaches the activation type, and the user terminal that is of the online connection type.

With reference to the second possible implementation manner of the second aspect of the present invention, in a third possible implementation, the modeling module is further configured to generate a service data type that is established in each set time period. The quantity relationship between the user terminal, the user terminal of the attachment activation type, and the user terminal of the online connection type, and the number of user terminals that generate the service data type, the user terminal of the attachment activation type, and the user terminal of the online connection type are fitted. function;

The prediction module is specifically configured to: when the total number of user terminals accessing the network is predicted, obtain the quantity function and the total number of user terminals that are predicted to obtain the access network according to the fitting, and predict at least one of the following users: Number of terminals:

In conjunction with the first possible embodiment of the second aspect of the invention, or in combination with the second possible embodiment of the second aspect of the invention, or in combination with the third possible embodiment of the second aspect of the invention, at the fourth In a possible implementation, the acquiring module is further configured to separately obtain network quality information and network traffic information in at least one set time period;

The establishing module is configured to generate, according to the obtained network quality information in the set time period, the network traffic information in the set time period, and the statistically obtained user terminal corresponding to the service data type in the set time period. The number and the network resource information consumed by the user terminal establish a correspondence between the type of the generated service data, the number of user terminals, and the network resource information consumed by the user terminal.

With reference to the fourth possible implementation manner of the second aspect of the present invention, in a fifth possible implementation manner, the establishing module establishes between generating a service data type, a number of user terminals, and a physical resource block PRB resource utilization rate. Corresponding relationship, wherein the physical resource block PRB resource utilization rate includes at least one of an uplink PRB resource utilization rate and a downlink PRB resource utilization rate;

and / or,

In conjunction with a possible embodiment of the second aspect of the invention, or a first possible embodiment of the second aspect of the invention, or a second possible embodiment of the second aspect of the invention, or in combination with the second aspect of the invention a third possible implementation, or a fourth possible implementation of the second aspect of the invention, or a fifth possible implementation of the second aspect of the invention, in a sixth possible implementation The modeling module is specifically configured to use a set data model to fit a curve function between the number of user terminals corresponding to the access type and the network resource information consumed by the user terminal, where the fitting is obtained. The curve function contains function coefficients and function expressions.

In conjunction with a possible embodiment of the second aspect of the invention, or a first possible embodiment of the second aspect of the invention, or a second possible embodiment of the second aspect of the invention, or A third possible embodiment of the second aspect of the invention, or a fourth possible embodiment of the second aspect of the invention, or a fifth possible embodiment of the second aspect of the invention, or a combination A sixth possible implementation manner of the second aspect of the present invention, in the seventh possible implementation, the prediction module is specifically configured to determine, by using the predicted number of the user terminals, from the curve function The network resource information satisfying the condition of the number of user terminals accessing the network in the access type.

In conjunction with a possible embodiment of the second aspect of the invention, or a first possible embodiment of the second aspect of the invention, or a second possible embodiment of the second aspect of the invention, or in combination with the second aspect of the invention A third possible embodiment, or a fourth possible embodiment of the second aspect of the invention, or a fifth possible embodiment of the second aspect of the invention, or a combination of the second aspect of the invention The sixth possible implementation manner, or the seventh possible implementation manner of the second aspect of the present invention, in the eighth possible implementation manner, the prediction module is specifically used to generate a service data type if predicted The network resource expansion policy is determined according to the network resource information consumed by the user terminal that generates the service data type and the target network resource information that is expanded;

With reference to the eighth possible implementation manner of the second aspect of the present invention, in the ninth possible implementation manner, the network resource information includes a PRB resource utilization rate;

The prediction module is specifically configured to calculate a PRB resource utilization rate of the predicted user terminal that generates the service data type and a quotient of the target PRB resource utilization rate of the expanded capacity;

The product value is expanded with the expansion factor;

With reference to the eighth possible implementation manner of the second aspect of the present invention, or the ninth possible implementation manner of the second aspect of the present invention, in the tenth possible implementation manner, the network resource information further includes Data transmission rate

The prediction module is specifically configured to calculate a predicted number of user terminals that generate service data types The quotient of the transmission rate and the target data transmission rate of the expansion;

In conjunction with the eighth possible embodiment of the second aspect of the invention, or in combination with the ninth possible embodiment of the second aspect of the invention, or in combination with the tenth possible embodiment of the second aspect of the invention, In a possible implementation manner, the network resource information further includes a quantity of user terminals that generate a service data type;

The prediction module is specifically configured to calculate a predicted quotient of the number of user terminals that generate the service data type and the quotient of the number of target user terminals that generate the service data type.

According to a third aspect of the present invention, a network resource deployment device is provided, including:

Communication interface for communicating with other network devices;

a memory for storing program code;

a processor for executing program code stored in the memory, specifically executing:

In the subsequent deployment of network resources, for any type of access, it is predicted to access the network. The number of user terminals that access the network; and

With reference to a possible implementation manner of the third aspect of the present invention, in a first possible implementation, the processor is specifically configured to perform:

If the access type included in the historical data is a generated service data type, the number of user terminals that belong to the service data type and the network resource information consumed by the user terminal in the set time period are collected, and the service data type is generated. Correspondence between the number of user terminals and network resource information consumed by the user terminal;

In conjunction with a possible implementation of the third aspect of the present invention, or in conjunction with the first possible implementation of the third aspect of the present invention, in a second possible implementation, the processor is further configured to perform:

According to the access type included in the historical data, the number of user terminals belonging to the same access type in the set time period is statistically obtained according to the statistics of the historical data in each set time period. The number of user terminals corresponding to the service data type generated during the set time period, the number of user terminals corresponding to the activation type in the set time period, and the number of user terminals corresponding to the online connection type in the set time period , create business data A quantitative relationship between a type of user terminal, a user terminal of an attached activation type, and a user terminal of an online connection type.

With reference to the second possible implementation manner of the third aspect of the present invention, in a third possible implementation, the processor is further configured to:

In conjunction with the first possible embodiment of the third aspect of the invention, or in combination with the second possible embodiment of the third aspect of the invention, or in combination with the third possible embodiment of the third aspect of the invention, in the fourth In a possible implementation manner, the processor is further configured to:

With reference to the fourth possible implementation manner of the third aspect of the present invention, in a fifth possible implementation, the processor is specifically configured to perform:

and / or,

In conjunction with a possible embodiment of the third aspect of the invention, or a first possible embodiment of the third aspect of the invention, or a second possible embodiment of the third aspect of the invention, or in combination with the third aspect of the invention A third possible implementation manner, or a fourth possible implementation manner of the third aspect of the invention, or a fifth possible implementation manner of the third aspect of the invention, in the sixth possible implementation manner The processor is specifically configured to execute:

In conjunction with a possible embodiment of the third aspect of the invention, or a first possible embodiment of the third aspect of the invention, or a second possible embodiment of the third aspect of the invention, or in combination with the third aspect of the invention A third possible embodiment, or a fourth possible embodiment of the third aspect of the invention, or a fifth possible embodiment of the third aspect of the invention, or in combination with the third aspect of the invention In a seventh possible implementation manner, the processor is specifically configured to perform:

In conjunction with a possible embodiment of the third aspect of the invention, or a first possible embodiment of the third aspect of the invention, or a second possible embodiment of the third aspect of the invention, or in combination with the third aspect of the invention A third possible embodiment, or a fourth possible embodiment of the third aspect of the invention, or a fifth possible embodiment of the third aspect of the invention, or in combination with the third aspect of the invention The sixth possible implementation manner, or the seventh possible implementation manner of the third aspect of the present invention, in the eighth possible implementation manner, the processor is specifically configured to perform:

If it is predicted that the user terminal that needs to access the network to generate the service data type needs to consume the network resources The source information determines the network resource expansion strategy according to the predicted network resource information consumed by the user terminal that generates the service data type and the expanded target network resource information;

With reference to the eighth possible implementation manner of the third aspect of the present invention, in the ninth possible implementation manner, the network resource information includes a PRB resource utilization rate;

The processor is specifically configured to execute:

The product value is expanded with the expansion factor;

With reference to the eighth possible implementation manner of the third aspect of the present invention, or the ninth possible implementation manner of the third aspect of the present invention, in the tenth possible implementation manner, the network resource information further includes Data transmission rate

The processor is specifically configured to execute:

In conjunction with the eighth possible embodiment of the third aspect of the invention, or in combination with the ninth possible embodiment of the third aspect of the invention, or in combination with the tenth possible embodiment of the third aspect of the invention, In a possible implementation manner, the network resource information further includes a quantity of user terminals that generate a service data type;

The processor is specifically configured to execute:

Calculating a predicted quotient of the number of user terminals that generate the service data type and the quotient of the number of target user terminals that generate the service data type;

Calculating a difference between the quotient value and the set coefficient, and determining the calculated difference value to generate a service A capacity expansion policy for the number of user terminals of the data type.

Advantageous effects of embodiments of the present invention:

The embodiment of the present invention obtains historical data generated by the network in at least one set time period, where the historical data includes an access type of the user terminal accessing the network and network resource information consumed by the user terminal; The historical data in the set time period is used to count the number of user terminals belonging to the same access type and the network resource information consumed by the user terminal in the set time period according to the access type included in the historical data. Establishing a correspondence between the access type, the number of user terminals, and the network resource information consumed by the user terminal; for each access type, according to the user corresponding to the access type established for each set time period Corresponding relationship between the number of terminals and the network resource information consumed by the user terminal, and fitting a curve function between the number of user terminals corresponding to the access type and the network resource information consumed by the user terminal; During deployment, for any type of access, it is predicted to access the network with this type of access. The number of user terminals; and based on the obtained curve function between the number of user terminals corresponding to the access type and the network resource information consumed by the user terminal and the predicted number of user terminals, the prediction is based on the access type The network resource information that needs to be consumed in the number of user terminals that enter the network; the network resource information that needs to be consumed by the user terminal that is predicted to access the network with various access types, and the network resource deployment, so that before the network resource is deployed, Based on the historical data generated by the network, the future network capacity and resource demand are predicted, and the network planning is planned in advance, effectively realizing the targeted expansion of the network capacity, avoiding the network development and the network due to the tight network capacity. Problems such as reduced service quality have improved network performance.

DRAWINGS

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly described below. It is obvious that the drawings in the following description are only some embodiments of the present invention, Those skilled in the art can also obtain other drawings based on these drawings without paying for inventive labor.

FIG. 1 is a schematic flowchart of a network resource deployment method according to Embodiment 1 of the present invention;

2 is a schematic flowchart of a network resource deployment method according to Embodiment 2 of the present invention;

2(1) is a function diagram showing a mapping relationship between the number of user terminals that generate the downlink service data type and the downlink PRB resource utilization corresponding to the user terminal that generates the downlink service data type;

2(2) is a function diagram showing a mapping relationship between the number of established user terminals that generate the downlink service data type and the downlink data transmission rate corresponding to the user terminal that generates the downlink service data type;

3 is a schematic flowchart of a network resource deployment method according to Embodiment 3 of the present invention;

4 is a schematic structural diagram of a network resource deployment device according to Embodiment 4 of the present invention;

FIG. 5 is a schematic structural diagram of a network resource deployment device according to Embodiment 5 of the present invention.

detailed description

In order to achieve the object of the present invention, an embodiment of the present invention provides a network resource deployment method and device, which predicts future network capacity and resource requirements based on historical data generated by the network before network resource deployment, and implements network deployment. The advance planning effectively achieves targeted capacity expansion of the network capacity, avoiding problems such as network capacity constraints hindering network development and degrading network service quality, and improving network performance.

The various embodiments of the present invention are described in detail below with reference to the accompanying drawings. It is apparent that the described embodiments are only a part of the embodiments of the 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.

Embodiment 1:

FIG. 1 is a schematic flowchart diagram of a network resource deployment method according to Embodiment 1 of the present invention. The method can be as follows.

Step 101: Acquire historical data generated by the network in at least one set time period.

The historical data includes an access type of a user terminal accessing the network and network resource information consumed by the user terminal.

It should be noted that the access type includes at least one of generating a service data type, an attachment activation type, and an online connection type.

In step 101, network capacity expansion needs to be predicted before network capacity expansion. The basis for predicting network expansion in the embodiment of the present invention is historical data generated by the network.

The historical data includes the access type of the user terminal accessing the network and the network resource information consumed by the user terminal.

It should be noted that the so-called attach activation type, the so-called online connection type, and the so-called generated service data type state describe the access status of the user terminal accessing the network.

The attachment activation type refers to that the user terminal is registered on the network side, and the network side allocates information such as an IP address for communication; the online connection type refers to establishing a communication connection with the network side, but has not generated service data, that is, Waiting state; generating the service data type means that the service data for communication is generated between the network side device and the network side device.

In order to improve the accuracy of the prediction, the set time period can be relatively long. It is recommended that the length of the set time period be at least one week, or not limited to one week, and can also be determined according to actual needs, and the length of the set time period can be According to the actual needs, it can also be determined according to the system requirements. The length of the set time period is not limited here.

For each historical data acquired in a set time period, the access type of each user terminal accessing the network and the network resource information consumed by the user terminal in each set time period are respectively determined.

Step 102: Count the number of user terminals belonging to the same access type and the user terminal in the set time period according to the access type included in the historical data for the historical data in each set time period acquired. The network resource information that is consumed is used to establish a correspondence between the access type, the number of user terminals, and the network resource information consumed by the user terminal.

In step 102, for the historical data in each set time period acquired, the number of user terminals belonging to the same access type in the set time period is counted according to the access type included in the historical data. Network resource information consumed by the user terminal.

Specifically, each set time period is acquired for each of the acquired time periods. The historical data in the historical data, according to the access type included in the historical data, the number of user terminals belonging to the same access type in the set time period is counted, for example, the number of user terminals attached to the activation type may be determined by the core network. According to the direct statistics of the traffic data, the number of user terminals of the online connection type and the number of user terminals that generate the service data type can be directly calculated by the access gateway according to the traffic data.

The user terminal that generates the service data type can be further divided into a user terminal that generates an uplink service data type and a user terminal that generates a downlink service data type. The number of user terminals that generate the uplink service data type can also be obtained by:

The first way:

The number of user terminals that are scheduled to transmit uplink service data in each transmission time interval (English: Transmission Time Interval; TTI) is counted by the base station, and the number of user terminals that are counted by multiple TTIs in the set time period is averaged. The value is the number of user terminals that generate the uplink service data type.

The second way:

Counting the duration of each user terminal transmitting the uplink service data, and counting the total duration of the effective transmission of the uplink service data of the entire network in the set time period; the duration of transmitting the uplink service data and the total duration of transmitting the uplink service data according to each user terminal Calculate the number of user terminals that generate the uplink service data type.

The third way:

During the set time period, the average number of user terminals that have cached data in the uplink data buffer queue of one cell in the coverage of the base station is counted, and the average number of statistics is multiplied by the total sampling point corresponding to the set time period, and then Dividing the product by the total length of time that the cell effectively transmits the uplink service data, the obtained quotient value may be the number of user terminals that generate the uplink service data type in the set time period.

The number of user terminals that generate the downlink service data type can also be calculated by using the foregoing three methods. The parameters used in the calculation are changed to: the number of user terminals transmitting downlink service data, the total duration of transmitting downlink service data, and the downlink service. The data has associated parameters.

Optionally, the method further includes:

For example, the historical data of the acquired network may determine that the number of user terminals that generate the service data type, the user terminal that attaches the activation type, and the user terminal that is of the online connection type are linear, for example, the user terminal with the attached activation type and The number of user terminals of the online connection type is about 30%; the ratio of the number of user terminals that generate the service data type to the user terminal of the online connection type is about 10%, which means that the user is based on the type of service data generated. The number relationship between the terminal, the user terminal of the attached activation type, and the user terminal of the online connection type can predict the number of user terminals of various access types in the future network.

For a user terminal that is in a different access type, the network side needs to allocate network resources to the network when accessing the network. When acquiring historical data, the user terminal of the different access types of the access network acquires the network resources consumed by the user terminal. .

It should be noted that the network resource includes at least one or more of an uplink physical resource block (English: Physical Resource Block; abbreviation: PRB) utilization rate, a downlink PRB resource utilization rate, an uplink data transmission rate, and a downlink data transmission rate. Kind.

In the historical data for each set time period acquired, the number of user terminals in each set time period and the network resource information consumed by the user terminal in the set time period may be counted, and the network resources consumed here are collected. The information may be an average value of network resource information consumed by multiple user terminals of the same access type in the set time period. The representation form of the network resource information is not limited herein.

The number of users and users of each access type in each set time period When the network resource information consumed by the terminal is used, the correspondence between the access type, the number of user terminals, and the network resource information consumed by the user terminal is established.

For example, if the access type included in the historical data is a generated service data type, the number of user terminals belonging to the service data type and the network resource information consumed by the user terminal in the set time period are counted, and the service data is generated. The correspondence between the type, the number of user terminals, and the network resource information consumed by the user terminal;

Optionally, since the number of user terminals of various access types needs to be considered when the network resources are quantized, other network factors such as the size of the network traffic and the network quality are further considered, and therefore, When the correspondence between the access type, the number of user terminals, and the network resource information consumed by the user terminal, the network quality information and the network traffic information in the at least one set time period are separately acquired.

It should be noted that, when the network quality information is obtained in each set time period, the network quality information in the set time period may be filtered to exclude information indicating poor network quality, thereby reducing network quality. The adverse impact of information on network resources, but may affect the accuracy of the modeling.

When the network traffic information is obtained in each set time period, the network traffic information in the set time period may be filtered to exclude information indicating that the network traffic is small, thereby reducing the information of the network traffic to the network resources. The adverse effects, but may affect the accuracy of the modeling.

Here to establish a network that generates the type of service data, the number of user terminals, and the consumption of the user terminal. The correspondence between resource information is described as an example.

Specifically, the network quality information in the set time period, the network traffic information in the set time period, and the number of user terminals corresponding to the service data type generated during the set time period and the user terminal are obtained according to statistics. The consumed network resource information establishes a correspondence between the generated service data type, the number of user terminals, and the network resource information consumed by the user terminal.

If the network resource information includes the PRB resource utilization rate, the service data type is generated according to the obtained network quality information in the set time period, the network traffic information in the set time period, and the statistically obtained set time period. A corresponding relationship between the number of the user terminals and the network resource information consumed by the user terminal is established, and the correspondence between the type of the service data, the number of the user terminals, and the PRB resource utilization rate is established.

The PRB resource utilization rate includes at least one of an uplink PRB resource utilization rate and a downlink PRB resource utilization rate.

It should be noted that the number of user terminals that generate the service data type and the PRB resource utilization rate corresponding to the user terminal that generates the service data type are satisfied: the more the number of user terminals that generate the service data type, the greater the PRB resource utilization rate. Conversely, the fewer the number of user terminals that generate the service data type, the smaller the PRB resource utilization.

If the network resource information includes the data transmission rate, the service data type corresponding to the network quality information in the set time period, the network traffic information in the set time period, and the statistically obtained set time period are generated. The number of user terminals and the network resource information consumed by the user terminal establish a mapping relationship between the type of the generated service data, the number of user terminals, and the data transmission rate.

The physical resource block utilization rate includes at least one of an uplink data transmission rate and a downlink data transmission rate.

It should be noted that the number of user terminals that generate the service data type is equal to the data transmission rate corresponding to the user terminal that generates the service data type: the more the number of user terminals that generate the service data type, the smaller the data transmission rate; The smaller the number of user terminals that generate the service data type, the larger the data transmission rate.

Step 103: For each type of access, according to the correspondence between the number of user terminals corresponding to the access type established in each set time period and the network resource information consumed by the user terminal, A curve function between the number of user terminals corresponding to the access type and the network resource information consumed by the user terminal.

In step 103, for each type of access, according to the correspondence between the number of user terminals corresponding to the access type established in each set time period and the network resource information consumed by the user terminal, The fixed data model is fitted to obtain a curve function between the number of user terminals corresponding to the access type and the network resource information consumed by the user terminal, wherein the curve function obtained by the fitting includes function coefficients and function expressions.

Optionally, the method further includes:

A quantity relationship between a user terminal that generates a service data type, a user terminal that attaches an activation type, and a user terminal that is an online connection type that is established in each set time period is obtained, and the user terminal that generates the service data type is attached and attached. A quantitative function between the activation type of user terminal and the online connection type of user terminal.

Step 104: When the network resource deployment is required, predict the number of user terminals that access the network by using the access type for any type of access.

In step 104, when predicting the total number of user terminals accessing the network, the quantity function between the user terminal that generates the service data type, the user terminal that attaches the activation type, and the user terminal that is of the online connection type is obtained according to the fitting. The total number of user terminals accessing the network is predicted, and the number of at least one type of user terminals is predicted:

Step 105: Based on the obtained curve function between the number of user terminals corresponding to the access type and the network resource information consumed by the user terminal, and the predicted number of user terminals, predicting access to the network by using the access type. The network resource information that needs to be consumed under the number of user terminals.

In step 105, based on the obtained curve function between the number of user terminals corresponding to the access type and the network resource information consumed by the user terminal, and the predicted number of user terminals, The network resource information that satisfies the condition of the number of user terminals accessing the network with the access type is determined in the curve function.

For example, the number of user terminals that predict the network that generates the service data type access network is taken as an example for description.

If, in step 104, the number of user terminals of the network that generates the service data type access network is predicted, the curve function between the number of user terminals corresponding to the service data type and the network resource information consumed by the user terminal is searched for. The predicted number of user terminals is determined from the curve function to determine network resource information satisfying the condition of the number of user terminals of the network that generates the service data type access network.

Step 106: Perform network resource deployment by using the predicted network resource information that the user terminal accessing the network with various access types needs to consume.

In step 106, network resource deployment is performed by using the predicted network resource information that is generated by the user terminal that generates the service data type access network.

Here, the network resource deployment required by the user terminal of the network that generates the service data type access network may be used for network resource deployment as an example for description.

Specifically, the network resource expansion policy is determined according to the predicted network resource information consumed by the user terminal that generates the service data type and the expanded target network resource information; and the network resource expansion strategy is deployed according to the network resource expansion policy.

Specifically, if the network resource includes the PRB resource utilization, the network resource expansion strategy is determined according to the predicted network resource information consumed by the user terminal that generates the service data type and the expanded target network resource information, including:

The product value is expanded with the expansion factor;

Specifically, if the network resource includes a data transmission rate, the service is generated according to the prediction. The network resource information consumed by the user terminal of the data type and the target network resource information that is expanded to determine the network resource expansion strategy include:

Specifically, if the network resource information further includes the number of user terminals that generate the service data type, determining network resources according to the predicted network resource information consumed by the user terminal that generates the service data type and the expanded target network resource information. Capacity expansion strategy, including:

Based on the determined network expansion strategy, the network is expanded and the new network resources are deployed.

The historical data generated by the network in the at least one set time period is obtained by the solution of the first embodiment of the present invention, where the historical data includes the access type of the user terminal accessing the network and the network resource information consumed by the user terminal. Calculating the number of user terminals belonging to the same access type and the consumption of the user terminal in the set time period according to the access type included in the historical data for the historical data in each set time period obtained Network resource information, establishing a correspondence between the access type, the number of user terminals, and network resource information consumed by the user terminal; for each access type, according to the access established for each set time period Corresponding relationship between the number of user terminals corresponding to the type and the network resource information consumed by the user terminal, and fitting a curve function between the number of user terminals corresponding to the access type and the network resource information consumed by the user terminal; When performing network resource deployment in the future, for any type of access, predict the access class. The number of user terminals accessing the network; and based on the obtained curve function between the number of user terminals corresponding to the access type and the network resource information consumed by the user terminal, and the predicted number of user terminals, predicting the species Access type requires access to the number of user terminals on the network The network resource information is consumed; the network resource information that needs to be consumed by the predicted user terminal accessing the network with various access types is used to deploy the network resource, so that before the network resource is deployed, based on the historical data generated by the network, the future The network capacity and resource requirements are predicted, and the network planning is planned in advance, effectively realizing the targeted expansion of network capacity, avoiding problems such as network capacity shortage hindering network development and degrading network service quality, and improving the network. performance.

Embodiment 2:

FIG. 2 is a schematic flowchart diagram of a network resource deployment method according to Embodiment 2 of the present invention. The second embodiment of the present invention predicts network resources based on downlink service data on the basis of the first embodiment of the present invention. The method can be as follows.

Step 201: Acquire historical data generated by the network in at least one set time period.

It should be noted that the historical data involved in the second embodiment of the present invention is data associated with the downlink service.

The access type herein includes at least one of generating a downlink service data type, an attachment activation type, and an online connection type.

In step 201, network capacity expansion needs to be predicted before network capacity expansion. The basis for predicting network expansion in the embodiment of the present invention is historical data generated by the network.

Step 202: According to the historical data for each set time period acquired Generating a downlink service data type included in the data, and counting the number of user terminals that generate the downlink service data type and the network resource information consumed by the user terminal in the set time period, and establishing the downlink service data type, the number of user terminals, and the user. Correspondence between network resource information consumed by the terminal.

In step 202, for the historical data in each set time period acquired, according to the generated downlink service data type included in the historical data, the user terminal that belongs to the downlink service data type in the set time period is counted. The amount and network resource information consumed by the user terminal.

Specifically, in a set time period, for the historical data in each set time period acquired, according to the generated downlink service data type included in the historical data, the statistics are generated in the set time period. The number of user terminals of the business data type.

For example: the first way:

The number of user terminals that are scheduled to transmit downlink service data in each TTI is counted by the base station, and the number of user terminals that are counted by multiple TTIs in the set time period is averaged to obtain the number of user terminals that generate the downlink service data type. .

The second way:

Counting the duration of the downlink service data transmitted by each user terminal, and counting the total duration of the effective transmission of the downlink service data of the entire network in the set time period; the transmission duration of the downlink service data and the total duration of the downlink service data transmission according to each user terminal Calculate the number of user terminals that generate downlink service data.

The third way:

During the set time period, the average number of user terminals with buffered data in the downlink data buffer queue of one cell in the coverage of the base station is counted, and the average number of statistics is multiplied by the total sampling point corresponding to the set time period, and then Dividing the product by the total length of time that the cell transmits the downlink service data transmission effectively, and the obtained quotient may be the number of user terminals that generate the downlink service data type in the set time period.

Optionally, the method further includes:

For historical data acquired in each set time period, according to the historical data package After the number of user terminals belonging to the same access type is obtained in the set time period, the number of user terminals corresponding to the downlink service data type is generated according to the statistics, Establishing the number of user terminals corresponding to the activation type and the number of user terminals corresponding to the online connection type in the set time period, establishing a user terminal that generates a downlink service data type, a user terminal attached to the activation type, and online The quantitative relationship between user terminals of the connection type.

For example, the historical data of the acquired network may determine that the number of user terminals that generate the downlink service data type, the user terminal that attaches the activation type, and the user terminal that is of the online connection type are linear, for example, the user terminal of the attachment activation type. The ratio of the number of user terminals of the online connection type is about 30%; the ratio of the number of user terminals that generate the downlink service data type to the user terminal of the online connection type is about 10%, which means that downlink service data is generated according to The number relationship between the type of user terminal, the user terminal of the attached activation type, and the user terminal of the online connection type can predict the number of user terminals of various access types in the future network.

It should be noted that the network resource includes at least one of a downlink PRB resource utilization rate and a downlink data transmission rate.

Here, the correspondence between the generation of the downlink service data type, the number of user terminals, and the network resource information consumed by the user terminal is taken as an example.

Specifically, according to the obtained network quality information in the set time period, the network traffic information in the set time period, and the statistically obtained number of user terminals corresponding to the downlink service data type in the set time period, and the user The network resource information consumed by the terminal establishes a correspondence between the type of the downlink service data, the number of the user terminals, and the network resource information consumed by the user terminal.

If the network resource information includes the downlink PRB resource utilization rate, the downlink service is generated according to the obtained network quality information in the set time period, the network traffic information in the set time period, and the statistically obtained set time period. The number of user terminals corresponding to the data type and the network resource information consumed by the user terminal establish a correspondence between the downlink service data type, the number of user terminals, and the downlink PRB resource utilization.

It should be noted that the number of user terminals that generate the downlink service data type is the same as the downlink PRB resource usage corresponding to the user terminal that generates the downlink service data type: the more the number of user terminals that generate the downlink service data type, the downlink PRB The resource utilization ratio is larger. Conversely, the fewer the number of user terminals that generate the downlink service data type, the smaller the downlink PRB resource utilization rate.

As shown in FIG. 2(1), a function diagram of a mapping relationship between the number of user terminals that generate the downlink service data type and the downlink PRB resource utilization corresponding to the user terminal that generates the downlink service data type.

If the network resource information includes the downlink service data transmission rate, the downlink service is generated according to the obtained network quality information in the set time period, the network traffic information in the set time period, and the statistically obtained set time period. The number of user terminals corresponding to the data type and the network resource information consumed by the user terminal establish a mapping relationship between the downlink service data type, the number of user terminals, and the downlink service data transmission rate.

It should be noted that the number of user terminals that generate the downlink service data type and the downlink service data transmission rate corresponding to the user terminal that generates the downlink service data type are satisfied: the more the number of user terminals that generate the downlink service data type, the downlink service The smaller the data transmission rate is; on the contrary, the smaller the number of user terminals that generate the downlink service data type, the larger the downlink service data transmission rate.

As shown in FIG. 2(2), a function diagram of a mapping relationship between the number of established user terminals that generate the downlink service data type and the downlink service data transmission rate corresponding to the user terminal that generates the downlink service data type.

Step 203: For generating the downlink service data type, fitting the corresponding relationship between the number of user terminals corresponding to the generated downlink service data type established in each set time period and the network resource information consumed by the user terminal A curve function is generated between the number of user terminals corresponding to the downlink service data type and the network resource information consumed by the user terminal.

In step 203, according to the correspondence between the number of user terminals corresponding to the type of downlink service data generated in the respective set time period and the network resource information consumed by the user terminal, using the set data model, A curve function between the number of user terminals corresponding to the type of downlink service data generated and the network resource information consumed by the user terminal is obtained, wherein the curve function obtained by the fitting includes function coefficients and function expressions.

Optionally, the method further includes:

The quantity relationship between the user terminal that generates the downlink service data type, the user terminal that attaches the activation type, and the user terminal that is connected to the online connection type established in each set time period is obtained, and the user terminal that generates the downlink service data type is obtained by fitting. A quantitative function between the user terminal of the activation type and the user terminal of the online connection type.

Step 204: When the network resource deployment is required, the number of user terminals that generate the downlink service data type access network by using the type of downlink service data type is predicted.

In step 204, when predicting the total number of user terminals accessing the network, the quantity function between the user terminal generating the downlink service data type, the user terminal attaching the activation type, and the user terminal of the online connection type according to the fitting is obtained according to the fitting. And predicting the total number of user terminals accessing the network, and predicting the number of user terminals that generate the downlink service data type.

Step 205: Based on the obtained curve function between the number of user terminals corresponding to the downlink service data type and the network resource information consumed by the user terminal, and the predicted number of user terminals, predicting the type of downlink service data generated by the type The network resource information that needs to be consumed under the number of user terminals accessing the network.

In step 205, determining, according to the obtained curve function between the number of user terminals corresponding to the downlink service data type and the network resource information consumed by the user terminal, and the predicted number of user terminals, determining from the curve function The network resource information satisfying the condition of the number of user terminals that generate the downlink service data type access network in this kind is obtained.

In step 204, the number of user terminals of the network that generates the downlink service data type access network is predicted, and then the curve function between the number of user terminals corresponding to the downlink service data type and the network resource information consumed by the user terminal is searched. And the predicted number of user terminals, from which the network resource information satisfying the condition of the number of user terminals of the network that generates the downlink service data type access network is determined.

Step 206: Perform network resource deployment by using network resource information that is predicted to generate a downlink service data type access network user terminal.

In step 206, the network resource expansion policy is determined according to the predicted network resource information and the expanded target network resource information that are generated by the user terminal that generates the downlink service data type, and the network resource is expanded and deployed according to the network resource expansion policy.

Specifically, if the network resource includes the downlink PRB resource utilization, the network resource expansion policy is determined according to the predicted network resource information consumed by the user terminal that generates the downlink service data type and the expanded target network resource information, including:

Calculating a predicted quotient of the PRB resource utilization rate of the user terminal that generates the downlink service data type and the target downlink PRB resource utilization rate of the expanded capacity;

The product value is expanded with the expansion factor;

The difference between the calculated product value and the set coefficient is determined, and the calculated difference is determined as a capacity expansion strategy of the downlink PRB resource utilization.

Specifically, if the network resource includes a downlink service data transmission rate, according to the prediction The network resource information consumed by the user terminal of the downlink service data type and the target network resource information of the expanded network are determined, and the network resource expansion strategy is determined, including:

Calculating a quotient of the predicted downlink service data transmission rate of the user terminal that generates the downlink service data type and the target downlink service data transmission rate of the expanded capacity;

Calculating a difference between the quotient value and the set coefficient, and determining the calculated difference value as a capacity expansion strategy of the downlink service data transmission rate.

Specifically, if the network resource information further includes the number of user terminals that generate the downlink service data type, determining, according to the predicted network resource information consumed by the user terminal that generates the downlink service data type, and the expanded target network resource information, Network resource expansion strategy, including:

Calculating a predicted quotient of the number of user terminals that generate the downlink service data type and the quotient of the number of target user terminals that generate the downlink service data type;

Calculating a difference between the quotient value and the set coefficient, and determining the calculated difference value as a capacity expansion strategy for generating the number of user terminals of the downlink service data type.

For example, it is assumed that the current network total user terminal size of the operator A is 3 million. By using the modeling method of the second embodiment of the present invention, the downlink capacity modeling model of the network is obtained as shown in FIG. 2(1) and FIG. 2(2). .

That is, when the capacity expansion target is a downlink PRB resource utilization rate of 70%, according to the curve shown in FIG. 2(1), it can be determined that the average number of target user terminals that generate downlink service data is 70%, which is according to FIG. 2 (2) The curve shown, the downlink data transmission rate corresponding to the downlink PRB resource utilization rate is 5 Mbps.

If the trend forecast analysis based on historical data, the number of network user terminals will increase to about 6 million in the next three months.

Taking one of the cells 0 as an example, if the current downlink PRB utilization rate is 50%, the average number of target user terminals that generate downlink service data is 1.6, and the average downlink data transmission rate of the cell is 10 Mbps.

Through the modeling method of the second embodiment of the present invention, the downlink capacity modeling model of the network is obtained as shown in FIG. 2 . (1) and FIG. 2 (2), according to the correspondence between the number of activated user terminals, the number of online user terminals, and the number of user terminals that generate downlink service data, it can be determined that after the next three months, The average number of target user terminals for downlink service data will reach 3.2. The query of Figure 2(1) and Figure 2(2) predicts that the downlink PRB resource utilization rate is 85% and the downlink user rate is 4Mbps.

Finally, based on various factors, a capacity expansion strategy for expanding one carrier is obtained.

Embodiment 3:

FIG. 3 is a schematic flowchart diagram of a network resource deployment method according to Embodiment 3 of the present invention. The third embodiment of the present invention predicts network resources based on uplink service data based on the first embodiment of the present invention. The method can be as follows.

Step 301: Acquire historical data generated by the network in at least one set time period.

It should be noted that the historical data involved in the third embodiment of the present invention is data associated with the uplink service.

The access type herein includes at least one of generating an uplink service data type, an attachment activation type, and an online connection type.

In step 301, network capacity expansion needs to be predicted before network capacity expansion. The basis for predicting network expansion in the embodiment of the present invention is historical data generated by the network.

Step 302: According to the historical data generated in each set time period, according to the generated uplink service data type included in the historical data, the statistics belong to the generated uplink in the set time period. The number of user terminals of the service data type and the network resource information consumed by the user terminal establish a correspondence between the type of the uplink service data, the number of the user terminals, and the network resource information consumed by the user terminal.

In step 302, for the historical data in each set time period of the acquired, according to the generated uplink service data type included in the historical data, the user terminal that belongs to the uplink service data type in the set time period is counted. The amount and network resource information consumed by the user terminal.

Specifically, in a set time period, for the historical data in each set time period acquired, according to the generated uplink service data type included in the historical data, the statistics are generated in the set time period. The number of user terminals of the business data type.

For example: the first way:

The number of user terminals that are scheduled to transmit uplink service data in each TTI is counted by the base station, and the number of user terminals that are counted by multiple TTIs in the set time period is averaged to obtain the number of user terminals that generate the uplink service data type. .

The second way:

Counting the duration of each user terminal transmitting the uplink service data, and counting the total duration of the effective transmission of the uplink service data of the entire network in the set time period; the transmission duration of the uplink service data and the total duration of the uplink service data transmission according to each user terminal Calculate the number of user terminals that generate uplink service data.

The third way:

During the set time period, the average number of user terminals that have cached data in the uplink data buffer queue of one cell in the coverage of the base station is counted, and the average number of statistics is multiplied by the total sampling point corresponding to the set time period, and then Dividing the product by the total duration of the effective transmission of the uplink service data transmission by the cell, and obtaining the quotient value may be the number of user terminals that generate the uplink service data type in the set time period.

Optionally, the method further includes:

For the historical data in each set time period obtained, according to the access type included in the historical data, the user end of the same access type in the set time period is statistically obtained. After the number of terminals, the number of user terminals corresponding to the uplink service data type generated during the set time period, the number of user terminals corresponding to the activation type in the set time period, and the online connection within the set time period The number of user terminals corresponding to the type establishes a quantitative relationship between a user terminal that generates an uplink service data type, a user terminal that attaches an activation type, and a user terminal that is an online connection type.

For example, the historical data of the acquired network may determine that the number of user terminals that generate the uplink service data type, the user terminal that attaches the activation type, and the user terminal that is of the online connection type are linear, for example, the user terminal of the attachment activation type. The ratio of the number of user terminals of the online connection type is about 30%; the ratio of the number of user terminals that generate the uplink service data type to the user terminal of the online connection type is about 10%, which means that the uplink service data is generated according to The number relationship between the type of user terminal, the user terminal of the attached activation type, and the user terminal of the online connection type can predict the number of user terminals of various access types in the future network.

It should be noted that the network resource includes at least one of an uplink PRB resource utilization rate and an uplink data transmission rate.

The set time period can be obtained when the network traffic information is obtained in each set time period. The network traffic information is filtered to exclude information that represents less network traffic. This can reduce the adverse impact of less network traffic on network resources, but may affect the accuracy of modeling.

Here, the correspondence between the generation of the uplink service data type, the number of user terminals, and the network resource information consumed by the user terminal is taken as an example.

Specifically, according to the obtained network quality information in the set time period, the network traffic information in the set time period, and the statistically obtained number of user terminals corresponding to the uplink service data type and the user in the set time period. The network resource information consumed by the terminal establishes a correspondence between the type of the uplink service data, the number of the user terminals, and the network resource information consumed by the user terminal.

If the network resource information includes the uplink PRB resource utilization rate, the uplink service is generated according to the obtained network quality information in the set time period, the network traffic information in the set time period, and the statistically obtained set time period. The number of the user terminals corresponding to the data type and the network resource information consumed by the user terminal establish a correspondence between the type of the uplink service data, the number of the user terminals, and the uplink PRB resource utilization.

It should be noted that the number of user terminals that generate the uplink service data type and the uplink PRB resource usage that corresponds to the user terminal that generates the uplink service data type are satisfied: the more the number of user terminals that generate the uplink service data type, the uplink PRB The resource utilization ratio is larger; on the contrary, the smaller the number of user terminals that generate the uplink service data type, the smaller the uplink PRB resource utilization rate.

If the network resource information includes the uplink service data transmission rate, the uplink service is generated according to the obtained network quality information in the set time period, the network traffic information in the set time period, and the statistically obtained set time period. The number of user terminals corresponding to the data type and the network resource information consumed by the user terminal establish a mapping relationship between the type of the uplink service data, the number of the user terminals, and the downlink service data transmission rate.

It should be noted that the number of user terminals that generate the uplink service data type and the uplink service data transmission rate corresponding to the user terminal that generates the uplink service data type are satisfied: the more the number of user terminals that generate the uplink service data type, the uplink service The smaller the data transmission rate is; on the contrary, the smaller the number of user terminals that generate the uplink service data type, the larger the uplink service data transmission rate.

Step 303: For generating the uplink service data type, fitting the corresponding relationship between the number of user terminals corresponding to the generated uplink service data type established in each set time period and the network resource information consumed by the user terminal A curve function is generated between the number of user terminals corresponding to the uplink service data type and the network resource information consumed by the user terminal.

In step 303, according to the correspondence between the number of user terminals corresponding to the generated uplink service data type and the network resource information consumed by the user terminal, the set data model is used. A curve function is obtained between the number of user terminals corresponding to the type of the generated uplink service data and the network resource information consumed by the user terminal, wherein the curve function obtained by the fitting includes function coefficients and function expressions.

Optionally, the method further includes:

A quantity relationship between a user terminal that generates an uplink service data type, a user terminal that attaches an activation type, and a user terminal that is an online connection type that is established in each set time period is obtained, and a user terminal that generates an uplink service data type is obtained by fitting A quantitative function between the user terminal of the activation type and the user terminal of the online connection type.

Step 304: When the network resource deployment is required, the number of user terminals that generate the uplink service data type access network by using the type of the uplink service data type is predicted.

In step 304, when predicting the total number of user terminals accessing the network, the quantity function between the user terminal generating the uplink service data type, the user terminal attaching the activation type, and the user terminal of the online connection type is obtained according to the fitting. And predicting the total number of user terminals that access the network, and predicting the number of user terminals that generate the uplink service data type.

Step 205: Based on the obtained curve function between the number of user terminals corresponding to the uplink service data type and the network resource information consumed by the user terminal, and the predicted number of user terminals, predicting the type of uplink service data generated by the type The network resource information that needs to be consumed under the number of user terminals accessing the network.

In step 305, based on the obtained curve function between the number of user terminals corresponding to the uplink service data type and the network resource information consumed by the user terminal, and the predicted number of user terminals, determining from the curve function Outgoing to generate an uplink service data type access network The network resource information of the number of user terminals.

In step 304, the number of user terminals of the network that generates the uplink service data type access network is predicted, and then the curve function between the number of user terminals corresponding to the type of the uplink service data type and the network resource information consumed by the user terminal is searched. And the predicted number of user terminals, from which the network resource information satisfying the condition of the number of user terminals of the network that generates the uplink service data type access network is determined.

Step 306: Perform network resource deployment by using network resource information that is predicted to generate an uplink service data type access network user terminal.

In step 306, the network resource expansion policy is determined according to the predicted network resource information and the expanded target network resource information that are generated by the user terminal that generates the uplink service data type, and the network resource is expanded and deployed according to the network resource expansion policy.

Specifically, if the network resource includes the uplink PRB resource utilization, the network resource expansion policy is determined according to the predicted network resource information consumed by the user terminal that generates the uplink service data type and the expanded target network resource information, including:

Calculating a predicted quotient of the PRB resource utilization rate of the user terminal that generates the uplink service data type and the target uplink PRB resource utilization rate of the expanded capacity;

The product value is expanded with the expansion factor;

The difference between the calculated product value and the set coefficient is determined, and the calculated difference is determined as a capacity expansion strategy of the uplink PRB resource utilization.

Specifically, if the network resource includes the uplink service data transmission rate, determining the network resource expansion strategy according to the predicted network resource information consumed by the user terminal that generates the uplink service data type and the expanded target network resource information, including:

Calculating a quotient of the predicted uplink service data transmission rate of the user terminal that generates the uplink service data type and the target uplink service data transmission rate of the expanded capacity;

Specifically, if the network resource information further includes a user that generates an uplink service data type. The number of the terminals determines the network resource expansion strategy according to the predicted network resource information consumed by the user terminal that generates the uplink service data type and the expanded target network resource information, including:

Calculating a predicted quotient of the number of user terminals that generate the uplink service data type and the number of the target user terminals that generate the uplink service data type;

Calculating a difference between the quotient value and the set coefficient, and determining the calculated difference value as a capacity expansion strategy for generating the number of user terminals of the uplink service data type.

Embodiment 4:

FIG. 4 is a schematic structural diagram of a network resource deployment device according to Embodiment 4 of the present invention. The network resource deployment device includes: an obtaining module 41, an establishing module 42, a modeling module 43, and a prediction module 44, where :

The obtaining module 41 is configured to separately acquire historical data generated by the network in the at least one set time period, where the historical data includes an access type of the user terminal accessing the network and network resource information consumed by the user terminal;

The establishing module 42 is configured to collect, according to the access data included in the historical data, the number of user terminals belonging to the same access type in the set time period, for the historical data in each set time period acquired. Establishing a correspondence between the access type, the number of user terminals, and the network resource information consumed by the user terminal, and the network resource information consumed by the user terminal;

The modeling module 43 is configured to: according to each access type, a correspondence between the number of user terminals corresponding to the access type established in each set time period and the network resource information consumed by the user terminal, Fitting a curve function between the number of user terminals corresponding to the access type and the network resource information consumed by the user terminal;

The prediction module 44 is configured to predict, according to any access type, the number of user terminals accessing the network by using the access type, and based on the obtained user corresponding to the access type. The curve function between the number of terminals and the network resource information consumed by the user terminal and the predicted number of user terminals, and predict the network resource information that needs to be consumed under the number of user terminals accessing the network with the access type; Users who access the network with various access types The network resource information that the terminal needs to consume to deploy network resources.

Specifically, the establishing module 41 is specifically configured to: if the access type included in the historical data is a generated service data type, count the number of user terminals that belong to the generated service data type and the user terminal in the set time period. The network resource information that is consumed, and the correspondence between the type of the generated service data, the number of the user terminals, and the network resource information consumed by the user terminal is established;

Optionally, the network resource deployment device further includes: a quantity relationship establishing module 45, where:

The quantity relationship establishing module 45 is configured to: according to the historical data in each set time period acquired, according to the access type included in the historical data, belong to the same connection in the statistically obtained set time period. After the number of user terminals of the type is entered, the number of user terminals corresponding to the service data type generated during the set time period according to the statistics, the number of user terminals corresponding to the activation type in the set time period, and the set time The number of user terminals corresponding to the online connection type in the period establishes a quantitative relationship between the user terminal that generates the service data type, the user terminal that attaches the activation type, and the user terminal that is of the online connection type.

Specifically, the modeling module 44 is further configured to obtain a quantity relationship between a user terminal that generates a service data type, a user terminal that attaches an activation type, and a user terminal that is an online connection type established in each set time period. The fitting is obtained by a quantity function between a user terminal that generates a service data type, a user terminal that attaches an activation type, and a user terminal that is an online connection type.

Specifically, the acquiring module 41 is further configured to separately acquire network quality information and network traffic information in at least one set time period;

The establishing module 42 is configured to generate, according to the obtained network quality information in the set time period, the network traffic information in the set time period, and the statistically generated user corresponding to the service data type in the set time period. The number of the terminals and the network resource information consumed by the user terminal establish a correspondence between the type of the generated service data, the number of the user terminals, and the network resource information consumed by the user terminal.

Specifically, the establishing module 42 is specifically configured to generate a service data type according to the obtained network quality information in the set time period, network traffic information in the set time period, and the statistically obtained set time period. Corresponding relationship between the number of the user terminals and the network resource information consumed by the user terminal, and the correspondence between the number of the generated service data, the number of the user terminals, and the physical resource block PRB resource utilization, wherein the physical resource block PRB resource utilization rate is established. It includes at least one of uplink PRB resource utilization and downlink PRB resource utilization.

Specifically, the establishing module 42 is specifically configured to generate service data according to the obtained network quality information in the set time period, network traffic information in the set time period, and the statistically obtained set time period. The number of the user terminals corresponding to the type and the network resource information consumed by the user terminal establish a mapping relationship between the type of the service data, the number of the user terminals, and the data transmission rate, where the physical resource block utilization includes at least the uplink data. One of a transmission rate and a downlink data transmission rate.

Specifically, the modeling module 43 is specifically configured to, according to each access type, the network resource information consumed by the user terminal according to the number of user terminals corresponding to the access type established in each set time period. Corresponding relationship, using the set data model, fitting a curve function between the number of user terminals corresponding to the access type and the network resource information consumed by the user terminal, wherein the curve function obtained by the fitting includes Function coefficients and function expressions.

Specifically, the prediction module 44 is specifically configured to: based on the obtained curve function between the number of user terminals corresponding to the access type and the network resource information consumed by the user terminal, and the predicted number of user terminals, The network resource information that satisfies the condition of the number of user terminals accessing the network with the access type is determined in the curve function.

The prediction module 44 is specifically configured to: when predicting the total number of user terminals accessing the network, According to the fitting, the quantity function between the user terminal that generates the service data type, the user terminal that attaches the activation type, and the user terminal that is connected to the online connection type, and the total number of user terminals that are predicted to obtain the access network, the following at least one user is predicted. Number of terminals:

The prediction module 44 is specifically configured to: when predicting network resource information that needs to be consumed by a user terminal that generates a service data type access network, the network resource information and the capacity expansion target consumed by the user terminal that generates the service data type according to the prediction Network resource information to determine a network resource expansion strategy;

Specifically, the network resource information includes a PRB resource utilization rate;

The prediction module 44 is specifically configured to calculate a PRB resource utilization rate of the predicted user terminal of the service data type and a quotient of the target PRB resource utilization rate of the expanded capacity;

The product value is expanded with the expansion factor;

Specifically, the network resource information further includes a data transmission rate;

The prediction module 44 is specifically configured to calculate a quotient of a predicted data transmission rate of the user terminal that generates the service data type and a target data transmission rate of the expanded capacity;

Specifically, the network resource information further includes the number of the user terminals that generate the service data type. The prediction module 44 is specifically configured to calculate the predicted number of user terminals that generate the service data type and the generated service data type of the expanded capacity. The quotient of the number of target user terminals;

The network resource deployment device provided by the fourth embodiment of the present invention is based on the network before the network resource is deployed. The historical data generated by the network predicts the future network capacity and resource requirements, realizes the advance planning of network deployment, effectively realizes the targeted expansion of network capacity, and avoids network development due to network capacity constraints and network services. Problems such as reduced quality have improved network performance.

Embodiment 5:

FIG. 5 is a schematic structural diagram of a network resource deployment device according to Embodiment 5 of the present invention. The deployment device has the functions of performing the first embodiment of the present invention to the third embodiment of the present invention. The deployment device may adopt a general computer system structure, and the computer system may be a processor-based computer. The deployment processing entity includes at least one processor 51, a communication bus 52, a memory 53, and at least one communication interface 54.

The processor 51 can be a general purpose central processing unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits for controlling the execution of the program of the present invention.

The communication bus 52 can include a path for communicating information between the components. The communication interface 54 uses devices such as any transceiver for communicating with other devices or communication networks, such as Ethernet, Radio Access Network (RAN), Wireless Local Area Networks (WLAN), and the like.

The computer system includes one or more memories 53, which may be read-only memory (ROM) or other types of static storage devices that can store static information and instructions, random access memory (RAM) or Other types of dynamic storage devices that can store information and instructions, or can be electrically erasable programmable read-only memory (EEPROM), CD-ROM (Compact Disc Read-Only Memory, CD-ROM) ) or other 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 capable of carrying or storing in the form of instructions or data structures. The desired program code and any other medium that can be accessed by the computer, but is not limited thereto. These memories are connected to the processor via a bus.

The memory 53 is configured to store an application code for executing the solution of the present invention. The application code of the inventive solution is stored in a memory and is controlled by the processor 51 for execution. The processor 51 is configured to execute an application stored in the memory 53.

In a possible implementation manner, when the application is executed by the processor 51, the following functions are implemented:

In a possible implementation, the processor 51 is specifically configured to perform:

In a possible implementation, the processor 51 is further configured to:

The network quality information in the set time period, the network traffic information in the set time period, and the number of user terminals corresponding to the service data type generated during the set time period and the network consumed by the user terminal The resource information is used to establish a correspondence between the type of the service data, the number of the user terminals, and the resource resource block PRB resource utilization, wherein the physical resource block PRB resource utilization includes at least the uplink PRB resource utilization rate and the downlink PRB resource. One of the utilization rates.

The network quality information in the set time period, the network traffic information in the set time period, and the number of user terminals corresponding to the service data type generated during the set time period and the network consumed by the user terminal The resource information is used to establish a mapping relationship between the type of the service data, the number of the user terminals, and the data transmission rate, where the physical resource block utilization includes at least one of an uplink data transmission rate and a downlink data transmission rate.

For each type of access, according to the correspondence between the number of user terminals corresponding to the access type established in each set time period and the network resource information consumed by the user terminal, using the set data model, The curve function between the number of user terminals corresponding to the access type and the network resource information consumed by the user terminal is obtained, wherein the curve function obtained by the fitting includes a function coefficient and a function expression.

Determining that the access is satisfied by the curve function based on the obtained curve function between the number of user terminals corresponding to the access type and the network resource information consumed by the user terminal and the predicted number of user terminals. Type of network resource information for the number of user terminals accessing the network.

When predicting the total number of user terminals accessing the network, the number function between the user terminal that generates the service data type, the user terminal that attaches the activation type, and the user terminal that is of the online connection type is obtained according to the fitting, and the access network is predicted. The total number of user terminals is predicted to get the following The number of fewer user terminals:

If the network resource information that needs to be consumed by the user terminal that accesses the network to generate the service data type is predicted, the network resource expansion strategy is determined according to the predicted network resource information consumed by the user terminal that generates the service data type and the expanded target network resource information. ;

In a possible implementation manner, the network resource information includes a PRB resource utilization rate;

The processor 51 is specifically configured to perform:

The product value is expanded with the expansion factor;

In a possible implementation manner, the network resource information further includes a data transmission rate;

The processor 51 is specifically configured to perform:

In a possible implementation manner, the network resource information further includes a quantity of user terminals that generate a service data type;

The processor 51 is specifically configured to perform:

The network resource deployment device provided in Embodiment 5 of the present invention predicts future network capacity and resource requirements based on historical data generated by the network before network resource deployment, and implements advanced planning of network deployment, and effectively implements targeted The network capacity is expanded to avoid problems such as network capacity shortages hindering network development and degrading network service quality, and improving network performance.

Those skilled in the art will appreciate that embodiments of the present invention can be provided as a method, apparatus (device), or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or a combination of software and hardware. Moreover, the invention can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) including computer usable program code.

The present invention has been described with reference to flowchart illustrations and/or block diagrams of methods, apparatus, and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or FIG. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing device to produce a machine for the execution of instructions for execution by a processor of a computer or other programmable data processing device. Means for implementing the functions specified in one or more of the flow or in a block or blocks of the flow chart.

The computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture comprising the instruction device. The apparatus implements the functions specified in one or more blocks of a flow or a flow and/or block diagram of the flowchart.

These computer program instructions can also be loaded onto a computer or other programmable data processing device such that a series of operational steps are performed on a computer or other programmable device to produce computer-implemented processing for execution on a computer or other programmable device. The instructions provide steps for implementing the functions specified in one or more of the flow or in a block or blocks of a flow diagram.

While the preferred embodiment of the invention has been described, it will be understood that Therefore, the right to attach All changes and modifications are intended to be included within the scope of the invention.

It will be apparent to those skilled in the art that various modifications and changes can be made in the present invention without departing from the scope of the invention. Thus, it is intended that the present invention cover the modifications and modifications of the invention

Claims

A method for deploying a network resource, comprising:

Collecting historical data generated by the network in at least one set time period, where the historical data includes an access type of the user terminal accessing the network and network resource information consumed by the user terminal;

The number of user terminals belonging to the same access type and the network consumed by the user terminal in the set time period are counted according to the access type included in the historical data for the historical data in each set time period. Resource information, establishing a correspondence between the access type, the number of user terminals, and network resource information consumed by the user terminal;

For each type of access, the access is obtained according to the correspondence between the number of user terminals corresponding to the access type established in each set time period and the network resource information consumed by the user terminal. a curve function between the number of user terminals corresponding to the type and the network resource information consumed by the user terminal;

The number of user terminals accessing the network in the access type is predicted for any type of access when the network resource is deployed;

And predicting, according to the obtained curve function between the number of user terminals corresponding to the access type and the network resource information consumed by the user terminal, and the predicted number of user terminals, predicting a user terminal accessing the network by using the access type The amount of network resource information that needs to be consumed;

The network resource deployment is performed by using the predicted network resource information that the user terminal accessing the network with various access types needs to consume.
The network resource deployment method according to claim 1, wherein the number of user terminals belonging to the same access type and the consumption of the user terminal in the set time period are counted according to the access type included in the historical data. The network resource information, the correspondence between the access type, the number of user terminals, and the network resource information consumed by the user terminal, including:

If the access type included in the historical data is a generated service data type, the number of user terminals belonging to the service data type and the network consumed by the user terminal in the set time period are counted. Resource information, establishing a correspondence relationship between the generated service data type, the number of user terminals, and the network resource information consumed by the user terminal;

If the access type included in the historical data is an attachment activation type, the number of user terminals belonging to the attachment activation type and the network resource information consumed by the user terminal in the set time period are counted, and the attachment activation type and the user terminal are established. The correspondence between the quantity and the network resource information consumed by the user terminal;

If the access type included in the historical data is an online connection type, the number of user terminals belonging to the online connection type and the network resource information consumed by the user terminal in the set time period are counted, and the online connection type and the user terminal are established. The correspondence between the quantity and the network resource information consumed by the user terminal.
The method for deploying a network resource according to claim 1 or 2, wherein the method further comprises:

According to the access type included in the historical data, the number of user terminals belonging to the same access type in the set time period is statistically obtained according to the statistics of the historical data in each set time period. The number of user terminals corresponding to the service data type generated during the set time period, the number of user terminals corresponding to the activation type in the set time period, and the number of user terminals corresponding to the online connection type in the set time period Establishing a quantitative relationship between a user terminal that generates a service data type, a user terminal that attaches an activation type, and a user terminal that is an online connection type.
The method for deploying a network resource according to claim 3, wherein the method further comprises:

A quantity relationship between a user terminal that generates a service data type, a user terminal that attaches an activation type, and a user terminal that is an online connection type that is established in each set time period is obtained, and the user terminal that generates the service data type is attached and attached. a quantity function between the activation type of user terminal and the online connection type of user terminal;

For any type of access, the number of user terminals that access the network by using the access type is predicted, including:

When predicting the total number of user terminals accessing the network, the quantity function and the total number of user terminals predicted to obtain the access network are obtained according to the fitting, and the number of at least one type of user terminals is predicted:

The number of user terminals that generate the service data type, the number of user terminals to which the activation type is attached, and the number of user terminals of the online connection type.
The method for deploying a network resource according to any one of claims 2 to 4, wherein the method further comprises:

Obtaining network quality information and network traffic information in at least one set time period respectively;

Corresponding relationship between the generated service data type, the number of user terminals, and the network resource information consumed by the user terminal is established for the historical data in each set time period obtained, including:

The network quality information in the set time period, the network traffic information in the set time period, and the number of user terminals corresponding to the service data type generated during the set time period and the network consumed by the user terminal The resource information establishes a correspondence between the type of the generated service data, the number of user terminals, and the network resource information consumed by the user terminal.
The network resource deployment method according to claim 5, wherein the correspondence between the generation of the service data type, the number of user terminals, and the network resource information consumed by the user terminal is established, including:

Establishing a correspondence between the generated service data type, the number of the user terminals, and the physical resource block PRB resource utilization, wherein the physical resource block PRB resource utilization includes at least the uplink PRB resource utilization rate and the downlink PRB resource utilization ratio. a kind

and / or,

Establishing a mapping relationship between the type of the service data, the number of the user terminals, and the data transmission rate, where the physical resource block utilization includes at least one of an uplink data transmission rate and a downlink data transmission rate.
The network resource deployment method according to any one of claims 1 to 6, wherein the curve function between the number of user terminals corresponding to the access type and the network resource information consumed by the user terminal is obtained, including:

Using the set data model, the curve function between the number of user terminals corresponding to the access type and the network resource information consumed by the user terminal is obtained, wherein the curve function obtained by the fitting includes function coefficients and function expressions. formula.
The network resource deployment method according to any one of claims 1 to 7, wherein the network resource information that needs to be consumed in the number of user terminals that access the network in the access type is predicted, including:

Using the predicted number of the user terminals, network resource information satisfying the condition of the number of user terminals accessing the network with the access type is determined from the curve function.
The method for deploying a network resource according to any one of claims 1 to 8, wherein the network resource deployment is performed by using the predicted network resource information that is consumed by the user terminal that accesses the network by using various access types, including:

If the network resource information that needs to be consumed by the user terminal that accesses the network to generate the service data type is predicted, the network resource expansion strategy is determined according to the predicted network resource information consumed by the user terminal that generates the service data type and the target network resource information that is expanded. ;

The network resource is expanded and deployed according to the network resource expansion policy.
The network resource deployment method according to claim 9, wherein the network resource information includes PRB resource utilization rate;

Determining a network resource expansion strategy according to the predicted network resource information consumed by the user terminal that generates the service data type and the expanded target network resource information, including:

Calculating a predicted quotient of the PRB resource utilization rate of the user terminal that generates the service data type and the target PRB resource utilization rate of the expanded capacity;

The product value is expanded with the expansion factor;

Calculate the difference between the product value and the set coefficient, and determine the calculated difference as the capacity expansion strategy of the PRB resource utilization.
The network resource deployment method according to any one of claims 9 to 10, wherein the network resource information further includes a data transmission rate;

According to the predicted network resource information and capacity expansion of the user terminal that generates the service data type Target network resource information, and determine network resource expansion strategies, including:

Calculating a quotient of the predicted data transmission rate of the user terminal that generates the service data type and the target data transmission rate of the expanded capacity;

Calculating a difference between the quotient value and the set coefficient, and determining the calculated difference value as a capacity expansion strategy of the data transmission rate.
The network resource deployment method according to any one of claims 9 to 11, wherein the network resource information further includes a quantity of user terminals that generate a service data type;

Determining a network resource expansion strategy according to the predicted network resource information consumed by the user terminal that generates the service data type and the expanded target network resource information, including:

Calculating a predicted quotient of the number of user terminals that generate the service data type and the quotient of the number of target user terminals that generate the service data type;

Calculating a difference between the quotient value and the set coefficient, and determining the calculated difference value as a capacity expansion strategy for generating the number of user terminals of the service data type.
A network resource deployment device, comprising:

An acquiring module, configured to separately acquire historical data generated by a network in at least one set time period, where the historical data includes an access type of a user terminal accessing the network and network resource information consumed by the user terminal;

And a module is configured to collect, according to the access type included in the historical data, the number of user terminals belonging to the same access type in the set time period, and the historical data in each set time period acquired The network resource information consumed by the user terminal establishes a correspondence between the access type, the number of user terminals, and network resource information consumed by the user terminal;

The modeling module is configured to: according to the correspondence between the number of user terminals corresponding to the access type established in each set time period and the network resource information consumed by the user terminal, for each access type, Obtaining a curve function between the number of user terminals corresponding to the access type and the network resource information consumed by the user terminal;

a prediction module, configured to predict, according to any access type, the number of user terminals accessing the network by using the access type in the subsequent deployment of the network resource; and based on the obtained access class The curve function between the number of user terminals corresponding to the type and the network resource information consumed by the user terminal and the predicted number of user terminals, and predict the network resources that need to be consumed under the number of user terminals accessing the network with the access type. Information; use the predicted network resource information that the user terminal accessing the network with various access types needs to consume, and perform network resource deployment.
The network resource deployment device according to claim 13, wherein

And the establishing module is configured to: if the access type included in the historical data is a generated service data type, collect statistics on the number of user terminals that belong to the service data type and the network resources consumed by the user terminal in the set time period. Information, establishing a correspondence relationship between the type of the generated service data, the number of user terminals, and the network resource information consumed by the user terminal;

If the access type included in the historical data is an attachment activation type, the number of user terminals belonging to the attachment activation type and the network resource information consumed by the user terminal in the set time period are counted, and the attachment activation type and the user terminal are established. The correspondence between the quantity and the network resource information consumed by the user terminal;

If the access type included in the historical data is an online connection type, the number of user terminals belonging to the online connection type and the network resource information consumed by the user terminal in the set time period are counted, and the online connection type and the user terminal are established. The correspondence between the quantity and the network resource information consumed by the user terminal.
The network resource deployment device according to claim 13 or 14, wherein the network resource deployment device further comprises: a quantity relationship establishing module, wherein:

The quantity relationship establishing module is specifically configured to: according to the historical data in each set time period acquired, according to the access type included in the historical data, belong to the same access in the set time period After the number of types of user terminals, the number of user terminals corresponding to the service data type generated during the set time period according to the statistics, the number of user terminals corresponding to the activation type in the set time period, and the set time period The number of user terminals corresponding to the online connection type establishes a quantitative relationship between the user terminal that generates the service data type, the user terminal that attaches the activation type, and the user terminal that is of the online connection type.
The network resource deployment device according to claim 15, wherein

The modeling module is further configured to obtain a quantity relationship between a user terminal that generates a service data type, a user terminal that attaches an activation type, and a user terminal that is an online connection type established in each set time period, and the fitting is obtained. a quantity function between a user terminal that generates a service data type, a user terminal that attaches an activation type, and a user terminal that is an online connection type;

The prediction module is specifically configured to: when the total number of user terminals accessing the network is predicted, obtain the quantity function and the total number of user terminals that are predicted to obtain the access network according to the fitting, and predict at least one of the following users: Number of terminals:

The number of user terminals that generate the service data type, the number of user terminals to which the activation type is attached, and the number of user terminals of the online connection type.
The network resource deployment device according to any one of claims 14 to 16, wherein

The acquiring module is further configured to separately acquire network quality information and network traffic information in at least one set time period;

The establishing module is configured to generate, according to the obtained network quality information in the set time period, the network traffic information in the set time period, and the statistically obtained user terminal corresponding to the service data type in the set time period. The number and the network resource information consumed by the user terminal establish a correspondence between the type of the generated service data, the number of user terminals, and the network resource information consumed by the user terminal.
The network resource deployment device according to claim 17, wherein

The establishing module is specifically configured to establish a correspondence between the generated service data type, the number of the user terminals, and the physical resource block PRB resource utilization, wherein the physical resource block PRB resource utilization includes at least the uplink PRB resource utilization. One of the rate and downlink PRB resource utilization;

and / or,

Establishing a mapping relationship between the type of the service data, the number of the user terminals, and the data transmission rate, where the physical resource block utilization includes at least one of an uplink data transmission rate and a downlink data transmission rate.
The network resource deployment device method according to any one of claims 13 to 18, characterized in that

The modeling module is specifically configured to use the set data model to fit the access type A curve function between the number of corresponding user terminals and network resource information consumed by the user terminal, wherein the curve function obtained by the fitting includes function coefficients and function expressions.
A network resource deployment device according to any one of claims 13 to 19, characterized in that

The prediction module is specifically configured to determine network resource information that satisfies the number of user terminals accessing the network by the access type from the curve function by using the predicted number of the user terminals.
A network resource deployment device according to any one of claims 13 to 20, characterized in that

The prediction module is specifically configured to: if the network resource information that needs to be consumed by the user terminal that generates the service data type access network is predicted, the network resource information consumed by the user terminal that generates the service data type according to the prediction and the target network that is expanded Resource information to determine the network resource expansion strategy;

The network resource is expanded and deployed according to the network resource expansion policy.
The network resource deployment device according to claim 21, wherein the network resource information includes a PRB resource utilization rate;

The prediction module is specifically configured to calculate a PRB resource utilization rate of the predicted user terminal that generates the service data type and a quotient of the target PRB resource utilization rate of the expanded capacity;

The product value is expanded with the expansion factor;

Calculate the difference between the product value and the set coefficient, and determine the calculated difference as the capacity expansion strategy of the PRB resource utilization.
The network resource deployment device according to any one of claims 21 to 22, wherein the network resource information further includes a data transmission rate;

The prediction module is specifically configured to calculate a quotient of a predicted data transmission rate of the user terminal that generates the service data type and a target data transmission rate of the expanded capacity;

Calculating a difference between the quotient value and the set coefficient, and determining the calculated difference value as a capacity expansion strategy of the data transmission rate.
The network resource deployment device according to any one of claims 21 to 23, wherein the network resource information further includes a quantity of user terminals that generate a service data type;

The prediction module is specifically configured to calculate a predicted number of user terminals that generate service data types And the quotient of the number of target user terminals that generate the type of service data;

Calculating a difference between the quotient value and the set coefficient, and determining the calculated difference value as a capacity expansion strategy for generating the number of user terminals of the service data type.
A network resource deployment device, comprising:

Communication interface for communicating with other network devices;

a memory for storing program code;

a processor for executing program code stored in the memory, specifically executing:

Collecting historical data generated by the network in at least one set time period, where the historical data includes an access type of the user terminal accessing the network and network resource information consumed by the user terminal;

The number of user terminals belonging to the same access type and the network consumed by the user terminal in the set time period are counted according to the access type included in the historical data for the historical data in each set time period. Resource information, establishing a correspondence between the access type, the number of user terminals, and network resource information consumed by the user terminal;

For each type of access, the access is obtained according to the correspondence between the number of user terminals corresponding to the access type established in each set time period and the network resource information consumed by the user terminal. a curve function between the number of user terminals corresponding to the type and the network resource information consumed by the user terminal;

The number of user terminals accessing the network in the access type is predicted for any type of access when the network resource is deployed;

And predicting, according to the obtained curve function between the number of user terminals corresponding to the access type and the network resource information consumed by the user terminal, and the predicted number of user terminals, predicting a user terminal accessing the network by using the access type The amount of network resource information that needs to be consumed;

The network resource deployment is performed by using the predicted network resource information that the user terminal accessing the network with various access types needs to consume.
The network resource deployment device according to claim 25, wherein the processor is specifically configured to execute:

If the access type included in the historical data is a generated service data type, the number of user terminals that belong to the service data type and the network resource information consumed by the user terminal in the set time period are collected, and the service data type is generated. Correspondence between the number of user terminals and network resource information consumed by the user terminal;

If the access type included in the historical data is an attachment activation type, the number of user terminals belonging to the attachment activation type and the network resource information consumed by the user terminal in the set time period are counted, and the attachment activation type and the user terminal are established. The correspondence between the quantity and the network resource information consumed by the user terminal;

If the access type included in the historical data is an online connection type, the number of user terminals belonging to the online connection type and the network resource information consumed by the user terminal in the set time period are counted, and the online connection type and the user terminal are established. The correspondence between the quantity and the network resource information consumed by the user terminal.
The network resource deployment device according to claim 25 or 26, wherein the processor is further configured to:

According to the access type included in the historical data, the number of user terminals belonging to the same access type in the set time period is statistically obtained according to the statistics of the historical data in each set time period. The number of user terminals corresponding to the service data type generated during the set time period, the number of user terminals corresponding to the activation type in the set time period, and the number of user terminals corresponding to the online connection type in the set time period Establishing a quantitative relationship between a user terminal that generates a service data type, a user terminal that attaches an activation type, and a user terminal that is an online connection type.
The network resource deployment device according to claim 27, wherein the processor is further configured to:

A quantity relationship between a user terminal that generates a service data type, a user terminal that attaches an activation type, and a user terminal that is an online connection type that is established in each set time period is obtained, and the user terminal that generates the service data type is attached and attached. a quantity function between the activation type of user terminal and the online connection type of user terminal;

When predicting the total number of user terminals accessing the network, the quantity function and the total number of user terminals predicted to obtain the access network are obtained according to the fitting, and the number of at least one type of user terminals is predicted:

The number of user terminals that generate the service data type, the number of user terminals to which the activation type is attached, and the number of user terminals of the online connection type.
The network resource deployment device according to any one of claims 26 to 28, wherein the processor is further configured to:

Obtaining network quality information and network traffic information in at least one set time period respectively;

The network quality information in the set time period, the network traffic information in the set time period, and the number of user terminals corresponding to the service data type generated during the set time period and the network consumed by the user terminal The resource information establishes a correspondence between the type of the generated service data, the number of user terminals, and the network resource information consumed by the user terminal.
The network resource deployment device according to claim 29, wherein the processor is specifically configured to execute:

Establishing a correspondence between the generated service data type, the number of the user terminals, and the physical resource block PRB resource utilization, wherein the physical resource block PRB resource utilization includes at least the uplink PRB resource utilization rate and the downlink PRB resource utilization ratio. a kind

and / or,

Establishing a mapping relationship between the type of the service data, the number of the user terminals, and the data transmission rate, where the physical resource block utilization includes at least one of an uplink data transmission rate and a downlink data transmission rate.
The network resource deployment device according to any one of claims 25 to 30, wherein the processor is specifically configured to execute:

Using the set data model, the curve function between the number of user terminals corresponding to the access type and the network resource information consumed by the user terminal is obtained, wherein the curve function obtained by the fitting includes function coefficients and function expressions. formula.
A network resource deployment device according to any one of claims 25 to 31, characterized in that The processor is specifically configured to execute:

Using the predicted number of the user terminals, network resource information satisfying the condition of the number of user terminals accessing the network with the access type is determined from the curve function.
The network resource deployment device according to any one of claims 25 to 32, wherein the processor is specifically configured to execute:

If the network resource information that needs to be consumed by the user terminal that accesses the network to generate the service data type is predicted, the network resource expansion strategy is determined according to the predicted network resource information consumed by the user terminal that generates the service data type and the target network resource information that is expanded. ;

The network resource is expanded and deployed according to the network resource expansion policy.
The network resource deployment device according to claim 33, wherein the network resource information includes a PRB resource utilization rate;

The processor is specifically configured to execute:

Calculating a predicted quotient of the PRB resource utilization rate of the user terminal that generates the service data type and the target PRB resource utilization rate of the expanded capacity;

The product value is expanded with the expansion factor;

Calculate the difference between the product value and the set coefficient, and determine the calculated difference as the capacity expansion strategy of the PRB resource utilization.
The network resource deployment device according to any one of claims 33 to 34, wherein the network resource information further includes a data transmission rate;

The processor is specifically configured to execute:

Calculating a quotient of the predicted data transmission rate of the user terminal that generates the service data type and the target data transmission rate of the expanded capacity;

Calculating a difference between the quotient value and the set coefficient, and determining the calculated difference value as a capacity expansion strategy of the data transmission rate.
The network resource deployment device according to any one of claims 33 to 35, wherein the network resource information further includes a quantity of user terminals that generate a service data type;

The processor is specifically configured to execute:

Calculating a predicted quotient of the number of user terminals that generate the service data type and the quotient of the number of target user terminals that generate the service data type;

Calculating a difference between the quotient value and the set coefficient, and determining the calculated difference value as a capacity expansion strategy for generating the number of user terminals of the service data type.