CN107493579B

CN107493579B - Method and device for wireless network pre-construction planning in colleges and universities

Info

Publication number: CN107493579B
Application number: CN201710693535.5A
Authority: CN
Inventors: 蔡子龙; 傅俊锋; 王题; 韦广林; 王一
Original assignee: China United Network Communications Group Co Ltd; China Information Technology Designing and Consulting Institute Co Ltd
Current assignee: China United Network Communications Group Co Ltd; China Information Technology Designing and Consulting Institute Co Ltd
Priority date: 2017-08-14
Filing date: 2017-08-14
Publication date: 2020-11-10
Anticipated expiration: 2037-08-14
Also published as: CN107493579A

Abstract

The embodiment of the invention provides a wireless network planning method and device for colleges and universities, which can better guarantee the service use of valuable college users. The planning method comprises the following steps: acquiring real-time position information of a user and service use conditions of the user; determining the client type of the user according to the real-time position information of the user or the service use condition of the user; determining a designated user according to the service condition of the user; classifying the colleges according to the number of college users in the designated users in the colleges and the category of the colleges; determining the service use condition of the business of the college user in the designated users in any grid outside the college in a preset investigation period according to the service use condition of the users; marking any grid outside the colleges according to the service condition of the college users in the predetermined investigation period in any grid outside the colleges and the area of any grid outside the colleges; and displaying the grading situation of each college and the marking situation of any grid outside the colleges.

Description

Method and device for wireless network pre-construction planning in colleges and universities

Technical Field

The invention relates to the field of communication, in particular to a method and a device for planning wireless networks of colleges and universities before construction.

Background

At present, when an operator plans and constructs a wireless network, the operator divides a local network into grids and defines the scenes of the grid affiliation. And then, evaluating the necessity and priority of site construction according to information such as scenes, traffic, the number of users, investment and the like. The scenes comprise houses, shopping malls, office buildings, counties, towns, administrative villages and the like, and the scenes of colleges and universities are also included. College campuses are a very important market for communications carriers. On one hand, college students are young people, most of the students use mobile internet services very frequently, and ARPU (Average income Per User) and DOU (Average monthly internet traffic Per User) are relatively high and are relatively good users for operators. On the other hand, students in colleges and universities become a group with high and medium income after graduation, and still stay in the network of the operator due to the viscosity of numbers, so that high income return is brought to the operator. The new colleges and universities enter the study in 9 months every year, and three operators all put into a large amount of marketing resources and compete very strongly. In order to maintain the inventory market and strive for larger market share, operators also invest considerable manpower and material resources. A college scenario is an important scenario in wireless network coverage. Operators need to make specific planning and construction schemes after analyzing the value of each college scene.

The conventional planning and construction method can only evaluate and screen the user number and the service volume of the whole college grid, and the analysis of the user structure is lacked, so that the use experience of a high-value user cannot be accurately guaranteed. In addition, the current method mainly determines the priority of the construction of the colleges and universities according to indexes such as income, business volume and the like, only focuses on the college area, and cannot ensure the activity area of college users outside the colleges and universities, so that the perception fall of the users is caused.

Disclosure of Invention

The embodiment of the invention provides a method and a device for planning wireless networks of colleges and universities before construction, which can better guarantee the service use of valuable college users.

In order to achieve the above purpose, the embodiment of the invention adopts the following technical scheme:

in a first aspect, a pre-construction planning method for a wireless network of a college is provided, which includes: acquiring real-time position information of a user and service use conditions of the user, wherein the services comprise voice services and data services; determining the client type of the user according to the real-time position information of the user or the service use condition of the user, wherein the client type comprises college users; determining a designated user according to the service use condition of the user, wherein the designated user comprises the following steps: heavy traffic users with DOU (direction of arrival) more than or equal to that of threshold users and high-value users with ARPU (autonomous Underwater Power Unit) exceeding a preset value in a local network; determining colleges to which college users belong according to the real-time position information of the users or the service conditions of the users; determining the grade of each college according to the number of college users in the designated users and/or college conditions of the college users and/or the types of the colleges; determining the service use condition of the business of the college user in the designated users in any grid outside the college in a preset investigation period according to the real-time position information of the users or the service use condition of the users; marking any grid outside the colleges according to the service condition of the college users in the predetermined investigation period in any grid outside the colleges and the area of any grid outside the colleges; and displaying the grading situation of each college and the marking situation of any grid outside the colleges.

The pre-construction planning method for the wireless network of the colleges and universities, provided by the embodiment of the invention, comprises the steps of firstly determining college users according to the service use conditions of users in the whole network, and then determining heavy-flow users and high-value users according to the service use conditions of the users; then, classifying the colleges according to college conditions of high-value users and heavy-flow users in college users; marking any grid outside the colleges according to the service use condition of high-value users and heavy-flow users outside the colleges in a preset investigation period; and finally, displaying the grading condition of each college and the marking condition of any grid outside the college so that a wireless network planner can correspondingly plan and construct any grid outside each college and the college according to the grading condition of each college and the marking condition of any grid outside the college. The method provided by the embodiment of the invention can be used for grading each college according to the high-value college user and the heavy-flow college user and marking any grid outside the college differently, so that construction planning with different priorities can be carried out on each college according to different grading conditions during later planning and construction, and meanwhile, a specific planning and construction can be carried out on other grids according to the grading conditions of the college and the marking conditions of any grid outside the college, thereby ensuring the service use of the high-value college users more effectively.

Preferably, the determining the client type of the user according to the real-time location information of the user or the service usage of the user, the client type including a college user, includes: determining users using the campus package and campus customer collector as college users according to the service conditions of the users; or determining the users who use the service in colleges and universities for more than the preset number of days every month as college users according to the real-time position information of the users.

Preferably, the designated user is determined according to the service usage of the user, and the designated user includes: heavy traffic users with average per-household per-month internet traffic DOU greater than or equal to DOU of threshold users and high-value users with average income ARPU exceeding a preset value in a local network comprise: determining users with the ARPU exceeding a preset value as high-value users according to the service conditions of the users; determining the user with DOU greater than or equal to threshold user in the local network as heavy flow user according to the service condition of user; each local network corresponds to a threshold user; the ratio of the sum of the DOUs of all the users with the DOUs larger than or equal to the DOU of the threshold user in the local network and the DOU of the threshold user to the total data traffic of the local network is a first preset percentage.

Preferably, the ranking of the colleges according to the number of college users among the designated users in the colleges and the category of the colleges comprises:

the category of each college comprises a first class college and a second class college; the grade of each college comprises A grade, B grade and C grade;

determining the colleges of the number of college heavy traffic users in the local network, wherein the number of college heavy traffic users is more than or equal to a first threshold college, and the colleges are A-level colleges; determining the colleges of the number of high-value users of the colleges and universities in the local network as A-level colleges and universities, wherein the number of the high-value users of the colleges and universities is greater than or equal to a second threshold college and university; each first threshold height correction corresponds to one local network, and each second threshold height correction corresponds to one local network; the college heavy traffic users are heavy traffic users in college users; the high-value users of the colleges and universities are high-value users in the college users;

determining a level B college and a level C college in colleges and universities except the level A college in a local network; the level B colleges comprise first-class colleges and second-class colleges, and the first-class colleges comprise colleges with education resource priority; the second class of colleges and universities comprises colleges and universities of which the number of users exceeds a preset number; the C-level colleges and universities are colleges and universities in the local network except the A-level colleges and the B-level colleges;

in the local network, the number of all college heavy traffic users is greater than or equal to the first threshold college heavy traffic user number, and the ratio of the sum of the college heavy traffic user numbers of the threshold colleges to the total number of the college heavy traffic users of the local network is a second preset percentage;

in the local network, the number of all the high-value users in the colleges is greater than or equal to the second threshold number of the high-value users in the colleges, and the ratio of the sum of the number of the high-value users in the colleges in the threshold colleges to the number of the high-value users in the local network is a second preset percentage.

Preferably, the marking of any grid outside the colleges and universities according to the service usage of the college users in any grid outside the colleges and universities in the predetermined investigation period and the area of any grid outside the colleges and universities comprises: the predetermined investigation time period comprises a first preset time period and a second preset time period; calculating a first preset time period income density index, a first preset time period people number density index, a second preset time period income density index and a second preset time period people number density index of any grid outside the colleges according to the service condition of business in any grid outside the colleges and universities of the designated users in a preset investigation time period and the area of any grid outside the colleges and universities;

marking grids with a first preset time interval income density index which is greater than or equal to a first preset time interval income density index of a first threshold grid in any grids outside a high school of the local network as first high correlation grids; marking grids with the first preset time interval people number density index being greater than or equal to the first preset time interval people number density index of the second threshold grid in any grid outside the local network height school as second high correlation grids; marking grids with a second preset time interval income density index which is greater than or equal to a second preset time interval income density index of a third threshold grid in any grid outside the school of the local network height as third-height related grids; marking grids with the second preset time interval people number density index being greater than or equal to a second preset time interval people number density index of a fourth threshold grid in any grid outside the local network height school as fourth high correlation grids; each first threshold grid corresponds to a local network; each second threshold grid corresponds to a local network; each third threshold grid corresponds to a local network; each fourth threshold grid corresponds to a local network;

in any grid outside colleges and universities of the local network, the income of the first preset time interval of the grid with all the first preset time interval income density indexes being more than or equal to the first preset time interval income density index of the first threshold grid, and the ratio of the sum of the income of the first preset time interval of the first threshold grid and the total income of the first preset time interval of any grid outside colleges and universities of the local network is a third preset percentage;

in any grid outside the colleges of the local network, the ratio of the number of people in the first preset time period of the grid with the first preset time period people number density index being greater than or equal to the first preset time period people number density index of the second threshold grid to the number of people in the first preset time period of the second threshold grid to the total number of people in the first preset time period of any grid outside the colleges of the local network is a third preset percentage;

in any grid outside the colleges of the local network, the income of all grids with the income density index of the second preset time interval being greater than or equal to the income density index of the second preset time interval of the third threshold grid, and the ratio of the sum of the income of the second preset time interval of the third threshold grid and the total income of the second preset time interval of any grid outside the colleges of the local network is a third preset percentage;

in any grid outside the colleges and universities of the local network, the ratio of the number of people in the second preset time period of the grid with the second preset time period people number density index being greater than or equal to the second preset time period people number density index of the fourth threshold grid to the number of people in the second preset time period of the fourth threshold grid to the total number of people in the second preset time period of any grid outside the colleges and universities of the local network is a third preset percentage.

In a second aspect, a pre-construction planning apparatus for wireless network in colleges and universities is provided, which includes:

the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring real-time position information of a user and service use conditions of the user, and services comprise voice services and data services;

the first judgment module is used for determining the client type of the user according to the real-time position information of the user or the service use condition of the user, which is acquired by the acquisition module, wherein the client type comprises college users;

the second judging module is used for determining the appointed user according to the service condition of the user service acquired by the acquiring module, and the appointed user comprises: heavy traffic users with DOU (direction of arrival) more than or equal to that of threshold users and high-value users with ARPU (autonomous Underwater Power Unit) exceeding a preset value in a local network;

the third judgment module is used for determining the colleges to which the college users belong according to the real-time position information of the users or the service conditions of the users, which are acquired by the acquisition module;

the grading module is used for determining the grade of each college according to the number of college users in the designated users in each college judged by the first judging module and the second judging module and/or the college condition of the college users determined by the third judging module and/or the category of each college;

the fourth judging module is used for determining the service use condition of the service of the college user in the designated users in any grid outside the colleges in the preset investigation period according to the real-time position information of the user or the service use condition of the user acquired by the acquiring module and the judgment results of the first judging module and the second judging module;

the marking module is used for marking any grid outside the colleges according to the service condition of the college users in the designated users outside the colleges in the preset investigation period and the area of the any grid outside the colleges determined by the fourth judging module;

and the display module is used for displaying the grading condition of each university by the grading module and the marking condition of any grid outside the university by the marking module.

Preferably, the first determining module is specifically configured to: determining users using the campus package and campus customer collector as college users according to the service conditions of the users acquired by the acquisition module; or determining the users who use the service in the colleges and universities for more than the preset number of days every month as college users according to the real-time position information of the users acquired by the acquisition module.

Optionally, the second determining module includes an ARPU subunit and a DOU subunit; the ARPU subunit is used for determining the users with the ARPU exceeding the preset value as high-value users according to the service conditions of the users acquired by the acquisition module; the DOU subunit is used for determining the user with the DOU greater than or equal to the DOU of the threshold user in the local network as the heavy traffic user according to the service condition of the user obtained by the obtaining module; each local network corresponds to a threshold user; in the local network, the ratio of the sum of the DOUs of all the users with the DOUs larger than or equal to the DOU of the threshold user and the DOU of the threshold user to the total data traffic of the local network is a first preset percentage.

Preferably, the classification module is specifically configured to:

according to the judgment results of the first judgment module, the second judgment module and the third module, determining the colleges of the number of college heavy traffic users in the local network, wherein the number of college heavy traffic users is greater than or equal to a first threshold college, and the colleges are A-level colleges; determining the colleges of the number of high-value users of the colleges and universities in the local network as A-level colleges and universities, wherein the number of the high-value users of the colleges and universities is greater than or equal to a second threshold college and university; each first threshold height correction corresponds to one local network, and each second threshold height correction corresponds to one local network; the college heavy traffic users are heavy traffic users in college users; the high-value users of the colleges and universities are high-value users in the college users;

Optionally, the marking module includes: a calculation subunit and a labeling subunit; the predetermined investigation time period comprises a first preset time period and a second preset time period;

the calculating subunit is configured to calculate, according to the service conditions of the business in any grid outside the colleges and universities of the college users in the predetermined investigation period and the area of any grid outside the college and determined by the fourth determining module, a first preset period income density index, a first preset period popularity density index, a second preset period income density index and a second preset period popularity density index of any grid outside the college and outside the college;

the marking subunit is used for marking the grids with the income density index of the first preset time interval in any grid outside colleges and universities of the local network as first high-association grids according to the calculation result of the calculating subunit, wherein the income density index of the first preset time interval in any grid outside colleges and universities of the local network is greater than or equal to the income density index of the first preset time interval of the first threshold grid; marking grids with the first preset time interval people number density index being more than or equal to the first preset time interval people number density index of the second threshold grid in any grids outside the high school of the local network as second high correlation grids; marking the grids with the second preset time interval income density index being more than or equal to the second preset time interval income density index of the third threshold grid in any grid outside the high school of the local network as third high correlation grids; marking grids with the second preset time interval people number density index being more than or equal to the second preset time interval people number density index of a fourth threshold grid in any grids outside the high school of the local network as fourth high correlation grids;

each first threshold grid corresponds to a local network; each second threshold grid corresponds to a local network; each third threshold grid corresponds to a local network; each fourth threshold grid corresponds to a local network;

The embodiment of the invention provides a method and a device for planning wireless networks of colleges and universities before construction, wherein the method comprises the following steps: acquiring real-time position information of a user and service use conditions of the user, wherein the services comprise voice services and data services; determining the client type of the user according to the real-time position information of the user or the service use condition of the user, wherein the client type comprises college users; determining a designated user according to the service use condition of the user, wherein the designated user comprises the following steps: heavy traffic users with DOU (direction of arrival) more than or equal to that of threshold users and high-value users with ARPU (autonomous Underwater Power Unit) exceeding a preset value in a local network; determining colleges to which college users belong according to the real-time position information of the users or the service conditions of the users; determining the grade of each college according to the number of college users in the designated users and/or college users belonging to the college and/or the category of each college; determining the service use condition of the business of the college user in the designated users in any grid outside the college in a preset investigation period according to the real-time position information of the users or the service use condition of the users; marking any grid outside the colleges according to the service condition of the college users in the predetermined investigation period in any grid outside the colleges and the area of any grid outside the colleges; and displaying the grading situation of each college and the marking situation of any grid outside the colleges. The pre-construction planning scheme of the wireless network of the colleges and universities provided by the embodiment of the invention firstly determines college users through the service use conditions of the users in the whole network, and then determines heavy-flow users and high-value users according to the service use conditions of the users; then, classifying the colleges according to college conditions of high-value users and heavy-flow users in college users; marking any grid outside the colleges according to the service use condition of high-value users and heavy-flow users outside the colleges in a preset investigation period; and finally, displaying the grading condition of each college and the marking condition of any grid outside the college so that a wireless network planner can correspondingly plan and construct any grid outside each college and the college according to the grading condition of each college and the marking condition of any grid outside the college. The method provided by the embodiment of the invention can be used for grading each college according to the high-value college user and the heavy-flow college user and marking any grid outside the college differently, so that construction planning with different priorities can be carried out on each college according to different grading conditions during later planning and construction, and meanwhile, a specific planning and construction can be carried out on other grids according to the grading conditions of the college and the marking conditions of any grid outside the college, thereby ensuring the service use of the high-value college users more effectively.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.

Fig. 1 is a schematic flow chart of a pre-construction planning method for wireless networks in colleges and universities according to an embodiment of the present invention;

FIG. 2 is a schematic flow chart of a college classification method according to an embodiment of the present invention;

FIG. 3 is a schematic flow chart of a method for marking a grid outside a college according to an embodiment of the present invention;

fig. 4 is a schematic structural diagram of a pre-construction planning apparatus for wireless networks in colleges and universities according to an embodiment of the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

It should be noted that, in the embodiments of the present invention, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "exemplary" or "e.g.," an embodiment of the present invention is not necessarily to be construed as preferred or advantageous over other embodiments or designs. Rather, use of the word "exemplary" or "such as" is intended to present concepts related in a concrete fashion.

It should be noted that, in the embodiments of the present invention, "of", "corresponding" and "corresponding" may be sometimes used in combination, and it should be noted that, when the difference is not emphasized, the intended meaning is consistent.

At present, operators only evaluate and screen the wireless network planning of each college according to the number of users and the service volume of the college grid as a whole, and the analysis of the user structure is lacked, so that the use experience of high-value users cannot be accurately guaranteed; and the priority of the construction of the colleges and universities is determined only according to indexes such as income, business volume and the like, and only the college area is concerned, so that the activity area of college users outside the colleges and universities cannot be guaranteed, and the perception fall of the users can be caused.

In order to solve the above problem, referring to fig. 1, an embodiment of the present invention provides a method for wireless network pre-construction planning in colleges and universities, including:

101. and acquiring real-time position information of a user and service use conditions of the user, wherein the services comprise voice services and data services.

For example, the network end may report the location of the cell covered by the base station used by the user when using the service to determine the grid to which the user belongs at the moment, or may determine the grid where the user is located by the user real-time location reported by the GPS of the user terminal.

Specifically, the service use condition of the user is recorded by the network cloud in real time, and includes information such as a package use condition of the user, a data service use condition, a voice service use condition and a user age name.

102. And determining the client type of the user according to the real-time position information of the user or the service use condition of the user, wherein the client type comprises the college users.

Specifically, the method for determining the college users in step 102 includes:

determining users using campus packages or campus customers as college users according to the service conditions of the users; screening out users using campus packages and campus customers according to the obtained service use condition of the users, and determining the users as colleges and universities;

or determining the users who use the service in colleges and universities for more than the preset number of days every month as college users according to the real-time position information of the users; for example, through analysis of users counted in some base stations of the colleges and universities in the field, it is found that in 23 working days of a month, a user using a service for more than 10 days in the colleges and universities can be determined to be a college user, i.e. the preset number of days is 10 days.

Further, if better guarantee needs to be provided for college students (the family member, the research student and the doctor student) in college users in planning and constructing a college wireless network, the college users can be divided into two categories, namely students and teaching workers according to the age information of the users, because the age interval from the family member to the doctor student is generally 19-26 years old, 27 years old is taken as a demarcation point of the students and the teaching workers, college users less than or equal to 27 years old are college student users, and college users more than 27 years old are college teaching worker users.

103. Determining a designated user according to the service use condition of the user, wherein the designated user comprises the following steps: heavy traffic users with DOU larger than or equal to threshold users and high-value users with ARPU exceeding a preset value in the local network.

Specifically, the step 103 includes: determining users with ARPU (Average revenue Peruser, Average income per user: income obtained by an operator from the users in a unit time period) exceeding a preset value as high-value users according to the service conditions of the users; determining a user with a DOU (data flow of use, average monthly internet traffic) in a local network being greater than or equal to a threshold user as a heavy traffic user according to the service condition of the user; each local network corresponds to a threshold user; all DOUs in the local network are larger than or equal to DOUs of users of the DOU of the threshold user, and the ratio of the sum of the DOUs of the threshold users to the total data traffic of the local network is a first preset percentage.

Illustratively, the preset value is 100 yuan; heavy traffic user: the method comprises the steps that a first preset percentage of local network users accumulated from high to low to the total amount in a DOU descending order is used as a threshold, users higher than the DOU threshold are heavy traffic users, and the first preset percentage is 80%; in order to more clearly indicate the selection of the heavy traffic users, threshold users are set in the heavy traffic user screening method.

The re-flow user definition and the threshold user definition are explained by taking a certain municipal network as an example: if the total number of the users in the whole market is 10, the average total flow per month is 10G; the DOU value of each user is respectively as follows:

user 1: 0.5G; user 2: 0.2G; user 3: 1.7G; user 4: 0.3G; user 5: 1.6G; user 6: 1.9G; user 7: 1.5G; user 8: 1.3G; user 9: 0.7G; user 10: 0.3G;

sorting 10 users according to the DOU value of each user from high to low: user 6-user 3-user 5-user 7-user 8-user 9-user 1-user 10-user 4-user 2;

and then accumulating the DOU values of all the users from high to low in sequence to obtain that the sum of the DOU values of the previous five users, namely the user 6, the user 3, the user 5, the user 7 and the user 8, reaches 80 percent of the total flow value, namely 8G, and the five users are defined as heavy flow users and the user 8 is defined as a threshold user.

Certainly, in the actual calculation, it is not necessary that the DOU of a certain user and the DOU of the user are just 80% of the total flow of the local network after being accumulated, and the sum is only approximate to a proportion, so the value close to 80% may be selected according to the actual situation for the first preset percentage.

104. And determining the colleges to which the college users belong according to the real-time position information of the users or the service use conditions of the users.

Specifically, the colleges and universities to which the college users belong can be determined by determining the colleges and universities in which the college users belong according to the real-time position information of the users, and the colleges and universities to which the users using the campus packages belong can also be determined according to the package contract situation of each college and the operator.

105. And determining the grade of each college according to the number of college users in the designated users and/or the college situation of the college users and/or the category of each college.

The designated college users, namely the college heavy traffic users and the college high-value users, are part of the college users who provide higher income for the operator, so that the part of user groups are the groups of the operator which need to be heavily protected during the construction of the wireless network of the college, and when planning and constructing the wireless network of the college, the priority of the construction of the wireless network of each college needs to be determined and the construction resources need to be allocated according to the number of the part of the groups owned by each college, so 105 steps are needed.

Wherein the classes of the colleges comprise a first class college and a second class college; the grade of each college comprises A grade, B grade and C grade; referring to fig. 2, the step 105 includes:

1051. determining the colleges of the number of college heavy traffic users in the local network, wherein the number of college heavy traffic users is more than or equal to a first threshold college, and the colleges are A-level colleges; determining the colleges of the number of high-value users of the colleges and universities in the local network as A-level colleges and universities, wherein the number of the high-value users of the colleges and universities is greater than or equal to a second threshold college and university; each first threshold height correction corresponds to one local network, and each second threshold height correction corresponds to one local network; the college heavy traffic users are heavy traffic users in college users; the high-value users in the colleges and universities are high-value users in the colleges and universities.

1052. And determining a level B college and a level C college in colleges and universities except the level A college in the local network.

The class-B colleges comprise class-I colleges and class-II colleges, and the class-I colleges comprise colleges with education resource priority, such as colleges 211 and 985; the second class of colleges and universities comprises colleges and universities with the number of college users exceeding a preset number of people, and the preset number of people is 5000 people; the C-level colleges and universities are colleges and universities in the local network except the A-level colleges and the B-level colleges;

in the local network, the number of all college heavy traffic users is greater than or equal to the first threshold college heavy traffic user number, and the ratio of the sum of the college heavy traffic user numbers of the threshold colleges to the total number of the college heavy traffic users of the local network is a second preset percentage; in the local network, the number of all the high-value users in the colleges is greater than or equal to the second threshold number of the high-value users in the colleges, and the ratio of the sum of the number of the high-value users in the colleges in the threshold colleges to the number of the high-value users in the local network is a second preset percentage.

Specifically, the second preset percentage is 80%, and the number of the high-value college users and the number of the heavy-traffic college users in each college can be determined according to the number of the users in the designated final college and the situation of the college of each college user.

The first threshold height correction and the second threshold height correction are explained by taking a certain local network as an example: if the total number of the universities is 10, the number of the high-value users of the universities is 6 thousands of people, and the number of the heavy-flow users of the universities is 5 thousands of people; the number of college users, the number of college high-value users and the number of college heavy-traffic users in each college are shown in table 1:

TABLE 1

All colleges and universities in the local network of the city are sorted according to the high-value user number of the colleges and universities from high to low: 7 colleges and universities, 3 colleges and universities, 1 colleges and universities, 6 colleges and universities, 4 colleges and universities, 9 colleges and universities, 10 colleges and universities, 8 colleges and universities, 2 colleges and universities, 5 colleges and universities;

then accumulating the number of high-value users of colleges and universities from high to low in sequence to obtain that the accumulated value of the number of high-value users of colleges and universities 7, 3, 1, 6, 4 and 9 is about 80 percent of the number of high-value users of the total colleges and universities, wherein the accumulated value is 76.6 percent of the number of high-value users of the total colleges and universities, so the six colleges and universities are A-level colleges, and the first threshold colleges and universities are 9;

all colleges and universities in the local network of the city are sorted according to the college heavy flow user number from high to low: 3 colleges and universities, 1 colleges and universities, 7 colleges and universities, 9 colleges and universities, 2 colleges and universities, 6 colleges and universities, 4 colleges and universities, 8 colleges and universities, 10 colleges and universities, 5 colleges and universities;

then accumulating the number of college heavy flow users of each college from high to low in sequence to obtain that the accumulated value of the number of college heavy flow users of college 3, college 1, college 7, college 9, college 2 and college 6 is about 80 percent of the total number of college heavy flow users, so that the six colleges are A-level colleges, and the second threshold height of the college 6 is at the moment;

in summary, level a colleges and universities include 3, 1, 7, 9, 2, 4 and 6, level B colleges and universities include 8 and 10, and level C colleges and universities include 5.

In addition, according to practical investigation, it can be understood that the grade a school not only contributes to most high-value and heavy-traffic users in high school, but also covers other important users, such as: a golden diamond five star user, a 4G user, and the like.

106. And determining the service use condition of the college user in the designated users in any grid outside the college in a preset investigation period according to the real-time position information of the users and the service use condition of the users.

Illustratively, the predetermined expedition periods include in particular a first preset period-weekday evening (six hours after 18:00 to the next day) and a second preset period-weekend full day.

107. Marking any grid outside the colleges according to the service use condition of the college users in the predetermined investigation period in any grid outside the colleges and the area of any grid outside the colleges.

According to actual examination conditions, college users can move outside the campus at weekday evening and weekend all day, and about half of income provided by the college users to operators is generated outside the college in the two periods, so that the service guarantee of the college users outside the college is also necessary when planning the wireless network of the college.

Specifically, referring to fig. 3, step 107 includes:

1071. and calculating a first preset time period income density index, a first preset time period people number density index, a second preset time period income density index and a second preset time period people number density index of any grid outside the high school according to the service condition of business in any grid outside the high school of the college users in the preset investigation time period and the area of any grid outside the high school.

1072. Marking grids with a first preset time interval income density index which is greater than or equal to a first preset time interval income density index of a first threshold grid in any grids outside a high school of the local network as first high correlation grids; marking grids with the first preset time interval people number density index being greater than or equal to the first preset time interval people number density index of the second threshold grid in any grid outside the local network height school as second high correlation grids; marking grids with a second preset time interval income density index which is greater than or equal to a second preset time interval income density index of a third threshold grid in any grid outside the school of the local network height as third-height related grids; and marking the grids with the second preset time interval people number density index being more than or equal to the second preset time interval people number density index of the fourth threshold grid in any grid outside the local network height school as fourth high correlation grids.

Illustratively, the arbitrary grids outside the high school include old multi-storey houses, shopping malls, hotels and entertainment places around the campus, and shopping malls and parks in the city center farther away from the school campus, etc.; the third predetermined percentage is 20%; the density index of the income of the extra-school grids at weekdays is the quotient of the income of the extra-school grids at weekdays and the area of the extra-school grids, the density index of the people number of the extra-school grids at weekdays is the quotient of the number of the people at weekdays and the area of the extra-school grids, the density index of the people number of the extra-school grids at weekends is the quotient of the number of the people number of the extra-school grids at weekends and the area of the extra-school grids, and the density index of the income of the extra-school grids at weekends is the quotient of the income of the.

Taking a certain municipal network as an example, the first high-association grid and the first threshold grid, the second high-association grid and the second threshold grid, the third high-association grid and the third threshold grid, and the fourth high-association grid and the fourth threshold grid are explained as follows: if the total number of 15 extra-school grids in the city is as follows: the total income of the weekday night is 5 ten thousand yuan, the total income of the weekend is 10 ten thousand yuan, and the total number of people in the weekday night is 5000; the total number of people at weekends is 1 ten thousand; sorting the five high school external grids according to the income density index of the working day and the evening: grid 2-grid 3-grid 1-grid 5-grid 4-grid 7-grid 10-grid 9-grid 8-grid 6-grid 15-grid 13-grid 11-grid 14-grid 12; the sum of the night income of the grid 2 and the grid 3 in the working day is 1 ten thousand yuan, which accounts for 20% of the total night income of the 15 grids in colleges and universities, so that the grid 2 and the grid 3 are first high-correlation grids, and the grid 3 is a first threshold grid; the same applies to the case of the remaining three sets of highly correlated grids and threshold grids.

108. And displaying the grading situation of each college and the marking situation of any grid outside the colleges.

Specifically, after the step 108, the construction planner performs corresponding planning construction on each college and any grid outside the college according to the classification condition of each college and the marking condition of any grid outside the college, for example, according to the classification condition of each college, a first planning construction resource is allocated to a level a college, a second planning construction resource is allocated to a level B college, and a third planning construction resource is allocated to a level C college; the resource amount of the first part of planning and construction resources is larger than that of the second part of planning and construction resources, and the resource amount of the second part of planning and construction resources is larger than that of the third part of planning and construction resources; in addition, because many high-association grids aimed at by a single index are protected, and the cost performance is low, a general planner can construct and optimize the grids which are the first high-association grid, the second high-association grid, the third high-association grid and the fourth high-association grid according to the marking condition of any grid outside the high school.

The pre-construction planning method for the wireless network of the colleges and universities, provided by the embodiment of the invention, comprises the following steps: acquiring real-time position information of a user and service use conditions of the user, wherein the services comprise voice services and data services; determining the client type of the user according to the real-time position information of the user or the service use condition of the user, wherein the client type comprises college users; determining a designated user according to the service use condition of the user, wherein the designated user comprises the following steps: heavy traffic users with DOU (direction of arrival) more than or equal to that of threshold users and high-value users with ARPU (autonomous Underwater Power Unit) exceeding a preset value in a local network; determining colleges to which college users belong according to the real-time position information of the users or the service conditions of the users; determining the grade of each college according to the number of college users in the designated users and/or college users belonging to the college and/or the category of each college; determining the service use condition of the business of the college user in the designated users in any grid outside the college in a preset investigation period according to the real-time position information of the users or the service use condition of the users; marking any grid outside the colleges according to the service condition of the college users in the predetermined investigation period in any grid outside the colleges and the area of any grid outside the colleges; and displaying the grading situation of each college and the marking situation of any grid outside the colleges. The pre-construction planning scheme of the wireless network of the colleges and universities provided by the embodiment of the invention firstly determines college users through the service use conditions of the users in the whole network, and then determines heavy-flow users and high-value users according to the service use conditions of the users; then, classifying the colleges according to college conditions of high-value users and heavy-flow users in college users; marking any grid outside the colleges according to the service use condition of high-value users and heavy-flow users outside the colleges in a preset investigation period; and finally, displaying the grading condition of each college and the marking condition of any grid outside the college so that a wireless network planner can correspondingly plan and construct any grid outside each college and the college according to the grading condition of each college and the marking condition of any grid outside the college. The method provided by the embodiment of the invention can be used for grading each college according to the high-value college user and the heavy-flow college user and marking any grid outside the college differently, so that construction planning with different priorities can be carried out on each college according to different grading conditions during later planning and construction, and meanwhile, a specific planning and construction can be carried out on other grids according to the grading conditions of the college and the marking conditions of any grid outside the college, thereby ensuring the service use of the high-value college users more effectively.

Referring to fig. 4, an embodiment of the present invention further provides a pre-construction planning apparatus for wireless networks in colleges and universities, where the apparatus includes:

an obtaining module 41, configured to obtain real-time location information of a user and service usage of the user, where the service includes a voice service and a data service;

a first determining module 42, configured to determine a client type of the user according to the real-time location information of the user or the service usage of the user, where the client type includes a college user;

a second determining module 43, configured to determine a designated user according to the service usage of the user acquired by the acquiring module 41, where the designated user includes: heavy traffic users with DOU (direction of arrival) more than or equal to that of threshold users and high-value users with ARPU (autonomous Underwater Power Unit) exceeding a preset value in a local network;

a third determining module 44, configured to determine a college to which the college user belongs according to the real-time location information of the user or the service usage of the user, which is acquired by the acquiring module 41;

the grading module 45 is used for determining the grade of each college according to the number of the college users in the designated users in each college determined by the first determination module 42 and the second determination module 43 and/or the college situation of the college user determined by the third determination module 44 and/or the category of each college;

a fourth determining module 46, configured to determine, according to the real-time location information of the user or the service usage of the user acquired by the acquiring module 41 and the determination results of the first determining module 42 and the second determining module 43, the service usage of the service in any grid outside the colleges and universities of the designated college users in the predetermined investigation period;

a marking module 47, configured to mark any grid outside the colleges according to the service usage of the college users in any grid outside the colleges during the predetermined investigation period and the area of any grid outside the colleges, which are determined by the fourth determining module 46;

and the display module 48 is used for displaying the grading condition of each university by the grading module 45 and the marking condition of any grid outside the university by the marking module 47.

Preferably, the first determination module 42 is specifically configured to: determining users who use the campus package and campus tenant as college users according to the service conditions of the users acquired by the acquisition module 41; or, according to the user real-time location information acquired by the acquisition module 41, determining the user who uses the service in the colleges and universities for more than the preset number of days every month as the college user.

Optionally, the second determining module 43 includes an ARPU sub-unit 431 and a DOU sub-unit 432; the ARPU subunit 431 is configured to determine, according to the service usage of the user acquired by the acquisition module 41, a user whose ARPU exceeds a preset value as a high-value user; the DOU subunit 432 is configured to determine, according to the service usage of the user obtained by the obtaining module 41, a user whose DOU in the local network is greater than or equal to the DOU of the threshold user as a heavy traffic user; each local network corresponds to a threshold user; in the local network, the ratio of the sum of the DOUs of all the users with the DOUs larger than or equal to the DOU of the threshold user and the DOU of the threshold user to the total data traffic of the local network is a first preset percentage.

Specifically, the first predetermined percentage is 80%.

Preferably, the classification module 45 is specifically configured to: the category of each college comprises a first class college and a second class college; the grade of each college comprises A grade, B grade and C grade; according to the judgment results of the first judgment module 42, the second judgment module 43 and the third module, determining the colleges of the number of college heavy traffic users in the local network, wherein the number of college heavy traffic users is more than or equal to a first threshold college, and the colleges are A-level colleges; determining the colleges of the number of high-value users of the colleges and universities in the local network as A-level colleges and universities, wherein the number of the high-value users of the colleges and universities is greater than or equal to a second threshold college and university; each first threshold height correction corresponds to one local network, and each second threshold height correction corresponds to one local network; the college heavy traffic users are heavy traffic users in college users; the high-value users of the colleges and universities are high-value users in the college users;

Wherein the second predetermined percentage is 80%.

Optionally, the marking module 47 includes: a calculation subunit 471 and a marking subunit 472; the predetermined investigation time period comprises a first preset time period and a second preset time period; illustratively, the first predetermined period is weekday evenings (18:00 to 6:00 on the next day), and the second predetermined period is the weekend whole day;

the calculating subunit 471 is configured to calculate, according to the service condition of the business in any grid outside the college and university of the college user in the predetermined investigation period and the area of any grid outside the college, determined by the fourth determining module 46, a first preset period income density index, a first preset period popularity density index, a second preset period income density index, and a second preset period popularity density index of any grid outside the college;

a marking subunit 472, configured to mark, according to the calculation result of the calculating subunit 471, a grid with a first preset period income density index that is greater than or equal to the first preset period income density index of the first threshold grid in any grid outside the colleges and universities of the local network as a first high-association grid; marking grids with the first preset time interval people number density index being more than or equal to the first preset time interval people number density index of the second threshold grid in any grids outside the high school of the local network as second high correlation grids; marking the grids with the second preset time interval income density index being more than or equal to the second preset time interval income density index of the third threshold grid in any grid outside the high school of the local network as third high correlation grids; marking grids with the second preset time interval people number density index being more than or equal to the second preset time interval people number density index of a fourth threshold grid in any grids outside the high school of the local network as fourth high correlation grids;

Specifically, the third predetermined percentage is 20%.

The pre-construction planning device for the wireless network of the colleges and universities provided by the embodiment of the invention comprises: the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring real-time position information of a user and service use conditions of the user, and services comprise voice services and data services; the first judgment module is used for determining the client type of the user according to the real-time position information of the user or the service use condition of the user, which is acquired by the acquisition module, wherein the client type comprises college users; the second judging module is used for determining the appointed user according to the service condition of the user service acquired by the acquiring module, and the appointed user comprises: heavy traffic users with DOU (direction of arrival) more than or equal to that of threshold users and high-value users with ARPU (autonomous Underwater Power Unit) exceeding a preset value in a local network; the third judgment module is used for determining the colleges to which the college users belong according to the real-time position information of the users or the service conditions of the users, which are acquired by the acquisition module; the grading module is used for determining the grade of each college according to the number of college users in the designated users in each college judged by the first judging module and the second judging module and/or the college condition of the college users determined by the third judging module and/or the category of each college; the fourth judging module is used for determining the service use condition of the service of the college user in the designated users in any grid outside the colleges in the preset investigation period according to the real-time position information of the user or the service use condition of the user acquired by the acquiring module and the judgment results of the first judging module and the second judging module; the marking module is used for marking any grid outside the colleges according to the service condition of the college users in the designated users outside the colleges in the preset investigation period and the area of the any grid outside the colleges determined by the fourth judging module; and the display module is used for displaying the grading condition of each university by the grading module and the marking condition of any grid outside the university by the marking module. Therefore, the pre-construction planning device for the wireless network of the colleges and universities, provided by the embodiment of the invention, can determine the college users through the service use conditions of the users in the whole network, and then determine the heavy traffic users and the high-value users according to the service use conditions of the users; then, classifying the colleges according to college conditions of high-value users and heavy-flow users in college users; marking any grid outside the colleges according to the service use condition of high-value users and heavy-flow users outside the colleges in a preset investigation period; and finally, displaying the grading condition of each college and the marking condition of any grid outside the college so that a wireless network planner can correspondingly plan and construct any grid outside each college and the college according to the grading condition of each college and the marking condition of any grid outside the college. The method provided by the embodiment of the invention can be used for grading each college according to the high-value college user and the heavy-flow college user and marking any grid outside the college differently, so that construction planning with different priorities can be carried out on each college according to different grading conditions during later planning and construction, and meanwhile, a specific planning and construction can be carried out on other grids according to the grading conditions of the college and the marking conditions of any grid outside the college, thereby ensuring the service use of the high-value college users more effectively.

The steps of a method or algorithm described in connection with the disclosure herein may be embodied in hardware or in software instructions executed by a processor. Embodiments of the present invention further provide a storage medium, which may include a memory for storing computer software instructions for a pre-construction planning apparatus for wireless networks of colleges and universities, the storage medium including program codes designed to execute the pre-construction planning method for wireless networks of colleges and universities. Specifically, the software instructions may be composed of corresponding software modules, and the software modules may be stored in a Random Access Memory (RAM), a flash Memory, a Read Only Memory (ROM), an Erasable Programmable Read Only Memory (EPROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a register, a hard disk, a removable hard disk, a compact disc Read Only Memory (CD-ROM), or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. Of course, the storage medium may also be integral to the processor. The processor and the storage medium may reside in an ASIC. Additionally, the ASIC may reside in a core network interface device. Of course, the processor and the storage medium may reside as discrete components in a core network interface device.

The embodiment of the invention also provides a computer program, which can be directly loaded into the memory and contains software codes, and the computer program can realize the pre-construction planning method of the wireless network in colleges and universities after being loaded and executed by a computer.

Those skilled in the art will recognize that, in one or more of the examples described above, the functions described in this invention may be implemented in hardware, software, firmware, or any combination thereof. When implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a general purpose or special purpose computer.

The above description is only for the specific embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A pre-construction planning method for wireless networks in colleges and universities is characterized by comprising the following steps:

acquiring real-time position information of a user and service use conditions of the user, wherein the services comprise voice services and data services;

determining the client type of the user according to the real-time position information of the user or the service use condition of the user, wherein the client type comprises college users;

determining a designated user according to the service condition of the user service, wherein the designated user comprises: heavy traffic users with average per-household per-month internet traffic DOU greater than or equal to DOU of threshold users and high-value users with average income ARPU exceeding a preset value in a local network;

determining colleges to which the college users belong according to the real-time position information of the users or the service conditions of the users;

determining the grade of each college according to the number of college users in the designated users and/or college conditions to which the college users belong and/or the category of each college;

determining the service use condition of the college user in the designated users in any grid outside colleges in a preset investigation period according to the real-time position information of the users and the service use condition of the users;

marking any grid outside the high school according to the service condition of the business in any grid outside the high school of the college users in the preset investigation period and the area of the any grid outside the high school;

and displaying the grading condition of each college and the marking condition of any grid outside the colleges.

2. The method of claim 1, wherein determining the customer type of the user according to the real-time location information of the user or the service usage of the user, the customer type comprising a college user, comprises:

determining users using campus packages or campus customers as college users according to the service conditions of the users;

or determining the users who use the service in colleges and universities for more than the preset number of days every month as college users according to the real-time user position information.

3. The method according to claim 1, wherein the determining of the designated user according to the service usage of the user comprises: heavy traffic users with DOU greater than or equal to threshold users and high-value users with ARPU exceeding a preset value in a local network comprise:

determining the users with the ARPU exceeding a preset value as high-value users according to the service conditions of the users;

determining the user with DOU greater than or equal to threshold user in the local network as heavy traffic user according to the service condition of the user; each local network corresponds to a threshold user;

and the ratio of the sum of the DOUs of all the users with the DOUs larger than or equal to the DOU of the threshold user in the local network to the total data traffic of the local network is a first preset percentage.

4. The method of claim 1, wherein the determining the level of each college according to the number of college users in the designated users and/or the college situation of the college users and/or the category of each college comprises:

the categories of the colleges comprise a first class college and a second class college; the levels of the colleges comprise A level, B level and C level;

determining the colleges of the number of college heavy traffic users in the local network, wherein the number of college heavy traffic users is more than or equal to a first threshold college, and the colleges are A-level colleges; determining the colleges of the number of high-value users of the colleges and universities in the local network as A-level colleges and universities, wherein the number of the high-value users of the colleges and universities is greater than or equal to a second threshold college and university; each first threshold height correction corresponds to a local network, and each second threshold height correction corresponds to a local network; the college heavy traffic users are heavy traffic users in college users; the high-value users of the colleges and universities are high-value users of the colleges and universities;

determining a level B college and a level C college in colleges and universities except the level A college in a local network;

the class-B colleges comprise class-I colleges and class-II colleges, and the class-I colleges comprise colleges with educational resource priority; the second class of colleges comprises colleges of which the number of the college users exceeds a preset number;

the class C colleges and universities are colleges and universities in the local network except the class A colleges and the class B colleges and universities;

in the local network, the ratio of the number of all the college heavy traffic users to the sum of the number of the college heavy traffic users of the threshold colleges to the number of the college heavy traffic users of the first threshold colleges to the total number of the college heavy traffic users of the local network is a second preset percentage;

in the local network, the ratio of the number of the college high-value users in the colleges to the sum of the number of the college high-value users in the threshold colleges to the number of the total college high-value users in the local network is a second preset percentage.

5. The method of claim 1, wherein the marking any grid outside the high school according to the service usage of the business in any grid outside the high school and the area of any grid outside the high school for a predetermined period of investigation by the college users of the designated users comprises:

the predetermined investigation time period comprises a first preset time period and a second preset time period;

calculating a first preset time period income density index, a first preset time period number density index, a second preset time period income density index and a second preset time period number density index of any grid outside the high school according to the service condition of business in any grid outside the high school of the college users in the preset investigation time period and the area of any grid outside the high school;

marking grids of which the first preset time period income density index is greater than or equal to a first threshold grid in any grids outside the high school of the local network as first high-association grids; marking grids of the first preset time period people number density index in any grid outside the local network height school, wherein the first preset time period people number density index is greater than or equal to a second threshold grid, as second high-association grids; marking grids with the second preset time interval income density index being more than or equal to a third threshold grid in any grid outside the local network height school as third-height related grids; marking grids of the second preset time period people number density index in any grid outside the local network height school, wherein the second preset time period people number density index is greater than or equal to a fourth threshold grid, as fourth high correlation grids;

in any grid outside the high school of the local network, the ratio of the income of the first preset time period of the grid of which all the first preset time period income density indexes are greater than or equal to the first preset time period income density index of a first threshold grid to the income of the first preset time period of the first threshold grid to the total income of the first preset time period of any grid outside the high school of the local network is a third preset percentage;

in any grid outside the high school of the local network, the ratio of the number of people in the first preset time period of the grid with the first preset time period people number density index being greater than or equal to the first preset time period people number density index of the second threshold grid to the sum of the number of people in the first preset time period of the second threshold grid to the total number of people in the first preset time period of any grid outside the high school of the local network is a third preset percentage;

in any grid outside the high school of the local network, the ratio of the income of the second preset time period of the grid of which all the second preset time period income density indexes are greater than or equal to the second preset time period income density index of a third threshold grid to the sum of the income of the second preset time period of the third threshold grid and the total income of the second preset time period of any grid outside the high school of the local network is a third preset percentage;

in any grid outside the high school of the local network, the ratio of the number of people in the second preset time period of the grid with the second preset time period people number density index of all the second preset time period people number density indexes being more than or equal to that of the fourth threshold grid to the sum of the number of people in the second preset time period of the fourth threshold grid to the total number of people in the second preset time period of any grid outside the high school of the local network is a third preset percentage.

6. A pre-construction planning device for wireless networks in colleges and universities, comprising:

the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring real-time position information of a user and service use conditions of the user, and the services comprise voice services and data services;

the first judging module is used for determining the client type of the user according to the real-time position information of the user or the service use condition of the user, which is acquired by the acquiring module, wherein the client type comprises a college user;

a second determining module, configured to determine a designated user according to the service usage of the user obtained by the obtaining module, where the designated user includes: heavy traffic users with DOU (direction of arrival) more than or equal to that of threshold users and high-value users with ARPU (autonomous Underwater Power Unit) exceeding a preset value in a local network;

the third judging module is used for determining the colleges to which the college users belong according to the real-time position information of the users or the service use conditions of the users acquired by the acquiring module;

the grading module is used for determining the grade of each college according to the number of college users in the designated users in each college judged by the first judging module and the second judging module and/or the college situation of the college users determined by the third judging module and/or the category of each college;

the fourth judging module is used for determining the service use condition of the college users in the designated users in any grid outside colleges in a preset investigation period according to the real-time position information of the users and the service use condition of the users acquired by the acquiring module and the judgment results of the first judging module and the second judging module;

the marking module is used for marking any grid outside the colleges according to the service condition of the college users in the designated users outside the colleges in the preset investigation period and the area of the any grid outside the colleges, wherein the service condition is determined by the fourth judging module;

and the display module is used for displaying the grading condition of the grading module on each college and the marking condition of the marking module on any grid outside the college.

7. The apparatus of claim 6, wherein the first determining module is specifically configured to:

determining users using the campus package and campus customer collector as college users according to the service conditions of the users acquired by the acquisition module;

or determining the users who use the service in the colleges and universities for more than the preset number of days every month as college users according to the real-time user position information acquired by the acquisition module.

8. The apparatus of claim 6, wherein the second determination module comprises an ARPU subunit and a DOU subunit;

the ARPU subunit is used for determining the users with the ARPU exceeding the preset value as high-value users according to the service conditions of the users acquired by the acquisition module;

the DOU subunit is used for determining the user with the DOU greater than or equal to the DOU of the threshold user in the local network as the heavy traffic user according to the service condition of the user obtained by the obtaining module; each local network corresponds to a threshold user;

in the local network, the ratio of the sum of the DOUs of all the users with the DOUs larger than or equal to the DOU of the threshold user and the DOU of the threshold user to the total data traffic of the local network is a first preset percentage.

9. The apparatus of claim 6, wherein the ranking module is specifically configured to:

according to the judgment results of the first judgment module, the second judgment module and the third judgment module, determining the colleges of the number of college heavy traffic users in the local network, wherein the number of college heavy traffic users is greater than or equal to a first threshold college, and the colleges are A-level colleges; determining the colleges of the number of high-value users of the colleges and universities in the local network as A-level colleges and universities, wherein the number of the high-value users of the colleges and universities is greater than or equal to a second threshold college and university; each first threshold height correction corresponds to a local network, and each second threshold height correction corresponds to a local network; the college heavy traffic users are heavy traffic users in college users; the high-value users of the colleges and universities are high-value users of the colleges and universities;

10. The apparatus of claim 6, wherein the tagging module comprises: a calculation subunit and a labeling subunit;

the calculating subunit is configured to calculate, according to the service conditions of the business in any grid outside the university of the college users in the predetermined investigation period and the area of any grid outside the college, which are determined by the fourth determining module, a first preset period income density index, a first preset period popularity density index, a second preset period income density index, and a second preset period popularity density index of any grid outside the college;

the marking subunit is configured to mark, according to the calculation result of the calculating subunit, a grid with a first preset period income density index greater than or equal to a first preset period income density index of a first threshold grid in any grid outside the high school of the local network as a first high association grid; marking grids with the first preset time interval people number density index being more than or equal to the first preset time interval people number density index of a second threshold grid in any grids outside the high school of the local network as second high correlation grids; marking the grids with the second preset time interval income density index being more than or equal to the second preset time interval income density index of a third threshold grid in any grid outside the high school of the local network as third high correlation grids; marking grids with the second preset time interval people number density index being more than or equal to that of a fourth threshold grid in any grids outside the high school of the local network as fourth high correlation grids; each first threshold grid corresponds to a local network; each second threshold grid corresponds to a local network; each third threshold grid corresponds to a local network; each fourth threshold grid corresponds to a local network;

in any grid outside the high school of the local network, the ratio of the income of all grids with the second preset time interval income density index being greater than or equal to the second preset time interval income density index of a third threshold grid to the income of the second preset time interval of the third threshold grid to the total income of any grid outside the high school of the local network in the second preset time interval is a third preset percentage;