[go: up one dir, main page]

CN119233270B - Method for selecting regional value center point of communication network - Google Patents

Method for selecting regional value center point of communication network Download PDF

Info

Publication number
CN119233270B
CN119233270B CN202411054352.5A CN202411054352A CN119233270B CN 119233270 B CN119233270 B CN 119233270B CN 202411054352 A CN202411054352 A CN 202411054352A CN 119233270 B CN119233270 B CN 119233270B
Authority
CN
China
Prior art keywords
point
points
base station
value
computer room
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202411054352.5A
Other languages
Chinese (zh)
Other versions
CN119233270A (en
Inventor
于新雁
王亭
袁华玉
邹悦
戴晓缔
黄文卫
胡焕明
吴旦
李中贤
肖松
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Chinacomm Design & Consulting Co ltd
Original Assignee
Chinacomm Design & Consulting Co ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Chinacomm Design & Consulting Co ltd filed Critical Chinacomm Design & Consulting Co ltd
Priority to CN202411054352.5A priority Critical patent/CN119233270B/en
Publication of CN119233270A publication Critical patent/CN119233270A/en
Application granted granted Critical
Publication of CN119233270B publication Critical patent/CN119233270B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/18—Network planning tools
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/22—Traffic simulation tools or models
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/02—Arrangements for optimising operational condition
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/06—Testing, supervising or monitoring using simulated traffic
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

本公开目的在于提供一种通信网络区域价值中心点的选择方法，包括以下步骤：S1获取基础信息：获取研究区域的基础信息，基础信息包括机房信息、基站信息、宽带信息；S2预处理基础信息：对S1获取的基础信息进行以下的预处理；S3：分别计算S2所获取的所有基准点的业务分值、结构分值，最终取得每一基准点对应的综合价值分值后排序；S4：根据S3所排序得到的各基准点及其对应的综合价值分值，逐一确定各价值中心点，直到确定的价值中心点的数量达到预估数量M；S5：依据S4所确定的各价值中心点与机房进行匹配，确定架构机房的方案，通过运营商架构机房规划方案中架构机房与价值中心点的匹配度，为运营商判定规划方案是否合理提供参考。

The present disclosure aims to provide a method for selecting a value center point of a communication network area, comprising the following steps: S1: obtaining basic information: obtaining basic information of a research area, the basic information including computer room information, base station information and broadband information; S2: preprocessing basic information: performing the following preprocessing on the basic information obtained by S1; S3: respectively calculating the business scores and structural scores of all benchmark points obtained by S2, and finally obtaining the comprehensive value score corresponding to each benchmark point and then sorting them; S4: determining each value center point one by one according to each benchmark point sorted by S3 and its corresponding comprehensive value score, until the number of determined value center points reaches an estimated number M; S5: matching each value center point determined by S4 with the computer room, determining a plan for constructing the computer room, and providing a reference for the operator to determine whether the planning plan is reasonable through the matching degree between the computer room and the value center point in the operator's computer room planning plan.

Description

Method for selecting regional value center point of communication network
Technical Field
The disclosure relates to the technical field of wireless communication, in particular to a method for selecting a value center point of a communication network area.
Background
With the rapid development of communication networks, operators face complex network environments and diversified user demands, 2/3/4/5G multiple network systems coexist, and home broadband and government private line double-sided service demands are overlapped, so that network construction cost and operation cost are increased increasingly. In such a background, operators are sequentially developing a series of network optimization works of frequency-reducing network-exiting and simple architecture. In the optimization and adjustment process, how to analyze the network coverage key area bearing a large number of users and services, find the value center point, build a very simple network architecture with optimal cost, and have important influence on reducing TCO cost, improving network quality and boosting service development for operators.
Disclosure of Invention
Aiming at the technical problems in the related art, the disclosure provides a method for selecting a value center point of a communication network area, which can overcome the defects in the prior art.
In order to achieve the technical purpose, the technical scheme of the present disclosure is realized as follows:
The disclosure aims to provide a method for selecting a value center point of a communication network area, which comprises the following steps:
S1, acquiring basic information of a research area, wherein the basic information comprises machine room information, base station information and broadband information,
The base station information comprises longitude and latitude information of the base station, and the daily average flow of the base station of the last 1 month;
The broadband information comprises latitude and longitude information of a home wide cell, latitude and longitude information of a private line government and enterprise building, and the number of users of the home wide cell on the network in the last 1 day and the number of users of the private line on the network in the government and enterprise;
The machine room information comprises machine room longitude and latitude information, machine room property attribution, machine room area, machine room electricity leading distance and maximum load, machine room transmission resources and whether dangerous sources exist around the machine room;
s2, preprocessing the basic information, namely preprocessing the basic information acquired in the step S1:
s2.1, determining a home scene of the research area, wherein the home scene represents specific area types (can be specifically urban areas, county areas, villages and towns, rural areas and the like) of the research area;
s2.2, setting a corresponding analysis radius r (which can be specifically shown as urban area-300 m, county-500 m, village-800 m and rural area-1500 m) for the study area according to the attribution scene of the study area;
S2.3 positioning, positioning and parameter calculation, wherein a certain point of the research area is optionally used as a datum point 0, then the datum point 0 is used as a circle center, and r, 2r, 3r, 4r and 5r are used as radiuses to respectively make 5 layers of circles, namely the radiation area of the datum point 0 is divided into 5 layers, and the number of base stations BS in each layer, the single-station average access distance D between the base stations and a machine room connected with the base stations, the sum F of daily average flow of the base stations and the sum B of broadband users are respectively counted;
Then, a plurality of points in a plurality of opposite directions of the datum point 0 are selected based on the datum point 0, the points are respectively taken as the datum points and numbered in sequence, then, each datum point is respectively taken as a circle center, each datum point 0 is referred to, each layer of circles are respectively made by taking r, 2r, 3r, 4r and 5r as radiuses, the number of base stations BS of each layer of each datum point, the single-station average access distance D between the base station and a machine room connected with the base station, the sum F of daily average flow of the base stations and the sum B of broadband users are respectively counted;
Repeatedly iterating the method until the new locating point exceeds the boundary of the research area, explaining that the locating point is located to reach the limit, and then obtaining all the locating points and the corresponding base station quantity BS, the single station average access distance D between the base station and the machine room connected with the base station, the sum F of the daily average flow of the base station and the sum B of the broadband users;
s2.4, preliminarily calculating the estimated quantity M of all value center points according to the research area, the belonging attribution scene and the area of the research area, wherein M=the area/(pi (5 r) 2) +1 of the research area;
s3, calculating service scores and structure scores of all the datum points acquired in the step S2 respectively, and finally acquiring comprehensive value scores corresponding to all the datum points and sequencing;
S4, determining all the value center points one by one according to the reference points obtained by the sequencing in the S3 and the corresponding comprehensive value scores thereof until the number of the determined value center points reaches the estimated number M;
And S5, according to the matching of the value center points determined in the S4 with the machine room, determining a scheme of the architecture machine room, and judging whether the planning scheme is reasonable or not by the operator through the matching degree of the architecture machine room and the value center points in the planning scheme of the operator architecture machine room. The step S5 may be implemented by using the prior art.
Preferably, the specific step of S2.3 is:
S2.3.1, optionally, taking a certain point of the research area as a datum point 0, taking the datum point 0 as a circle center, respectively making 5 layers of circles with r, 2r, 3r, 4r and 5r as radiuses, dividing the radiation area of the datum point 0 into 5 layers, respectively counting the number of base stations in each layer, namely, BS (i, j), the average access distance of a single station between the base station and a machine room connected with the base station, namely, D (i, j), the sum of daily average flow of the base stations, F (i, j) and the sum of broadband users, wherein i, j respectively correspond to the point number and the layer number, namely, i=0, 1 is smaller than or equal to j is smaller than 5;
S2.3.2, firstly, taking four points of distances r in the up, down, left and right directions of the datum point 0 as the basis of the datum point 0, respectively taking 4 datum points, and respectively marking point numbers as 1,2, 3 and 4, namely datum points 1,2, 3 and 4;
S2.3.3, respectively making 5 layers of circles by taking datum points 1, 2, 3 and 4 as circle centers and r, 2r, 3r, 4r and 5r as radiuses, dividing the radiation area of the datum points 1, 2, 3 and 4 into 5 layers, respectively counting the number of base stations in each layer, namely BS (i, j), the average access distance of a single station between the base station and an upper connected room, namely D (i, j), the sum of daily average flow of the base stations, namely F (i, j) and the sum of broadband users, namely B (i, j), aiming at the datum points 1, 2, 3 and 4, wherein i is the point number, j is the layer number, i is more than or equal to 1 and less than or equal to 4, and j is more than or equal to 1 and less than or equal to 5;
S2.3.4, respectively taking four points of distances r in the upper, lower, left and right directions of the datum points 1,2, 3 and 4 as the basis of the datum points 1,2, 3 and 4, respectively taking the four points as 4 datum points, simultaneously removing repeated points, and sequentially numbering the obtained points as 5, 6, 7 and 8.
S2.3.5, respectively taking datum points 5, 6, 7, 8 and..K as circle centers, respectively taking r, 2r, 3r, 4r and 5r as radiuses, respectively making 5 layers of circles, dividing the radiation areas of the datum points 5, 6, 7, 8 and..K into 5 layers, respectively counting the number of base stations in each layer, namely BS (i, j), the single-station average access distance between the base station and an upper online room, namely D (i, j), the sum of daily average flow of the base stations, namely F (i, j) and the sum of broadband users, namely B (i, j), wherein i is a point number, j is a layer number, and 5 is equal to or less than i is equal to K, and 1 is equal to or less than or equal to 5;
S2.3.6, finally, based on the point positions 5, 6, 7, 8 and..K, iteratively repeating with reference to S2.3.4-S2.3.5 until the newly-fetched point positions exceed the boundary of the research area, and marking the point position numbers of all fetched reference points as {0, 1, 2 and..N }, wherein N is the maximum point position number;
S2.3.7, respectively carrying out normalization processing on data of the datum points {0, 1,2 and..N } according to four dimensions of the number of the base stations BS, the average single station access distance D between the base stations and the machine room connected with the base stations, the sum F of daily average flow of the base stations and the sum B of broadband users to obtain a base station density score BSS (i, j), a base station access score DS (i, j), a base station service score FS (i, j) and a broadband service score BS (i, j) of each layer of each datum point, wherein i is a point number, j is a layer number, i is less than or equal to 0 and less than or equal to N, and 1 is less than or equal to j is less than or equal to 5.
Preferably, in S2.3.7, the data of the base station access score DS (i, j) is normalized after being inverted due to the difference between the data of the "single station average access distance D between the base station and the machine room connected thereto" and the data of other three dimensions.
Preferably, the specific step of S3 is:
S3.1, traversing all fiducial points 0,1, 2, 3..n, initializing i=0, i.e. selecting fiducial point 0, then continuing S3.2;
s3.2, calculating a service score YW (i), a structure score JG (i) and a comprehensive value score V (i) of the reference point i, wherein the service score YW (i), the structure score JG (i) and the comprehensive value score V (i) are calculated according to the following specific formulas;
YW (i) = Σfs (i, j) k (j) +Σbs (i, j) k (j) (formula one);
JG (i) = Σbss (i, j) k (j) +Σds (i, j) k (j) (formula two);
v (i) =yw (i) +jg (i); (formula three);
in the formula, i is the point number of the current datum point, i is more than or equal to 0 and less than or equal to N, j is the layer number of the datum point, and j is more than or equal to 1 and less than or equal to 5;
YW (i) -business score for reference point i;
JG (i) -structural score of reference point i;
v (i) -the integrated value score for reference point i;
k (j) -weight adjustment coefficients represent the weight of each layer of 1-5 layers, and the values of the weight adjustment coefficients are 1, 0.8, 0.6, 0.4 and 0.2 respectively, and are used for calculating the service scores corresponding to each point bit;
S3.3, if i is not less than N, indicating that all the datum points are traversed, continuing to S3.4, otherwise, increasing the value of i by 1, namely selecting the next datum point in sequence, and returning to S3.2;
and S3.4, finally, sequencing all the datum points in the order of the comprehensive value scores from the big value score to the small value score.
Preferably, the specific step of S4 is:
s4.1, selecting a datum point with the largest comprehensive value score, and marking the datum point as a value center point 1;
s4.2, marking the value center point 1 as a current value center point T, wherein T is the point number of the current value center point, initializing T as 1, and representing iteration from the value center point 1;
S4.3, calculating the distance between the current value center point T and other reference points, and removing other reference points with the distance of less than 5r from the current value center point T;
s4.4, increasing the value of T by 1, selecting the value center point T with the largest comprehensive value score from the rest datum points, and indicating that the current value center point T has iterated;
S4.5, if T is not less than M, indicating that the number of the selected value center points reaches the estimated number M, ending the iteration, and entering S4.6, otherwise, indicating that the iteration should be continued, and returning to S4.3;
S4.6, saving the value center points 1 and 2.
Preferably, the specific step of S5 is:
s5.1, selecting a total amount of existing machine rooms in a research area as a framework machine room screening basis;
S5.2, comprehensively judging the dimensionalities of property rights, space, power matching, transmission resources and the like of the whole existing machine room, and directly overruling the existing machine room which does not meet the condition;
s5.3, performing distance matching on the existing machine room meeting the preliminary judgment condition and the value center points selected in the S4, and judging that the machine room is reasonable if the distance between the existing machine room and a certain value center point is smaller than r;
S5.4, presetting a threshold value according to the actual condition of the research area, wherein if the reasonable machine room occupation ratio in the planning scheme is higher than the threshold value, the planning scheme of the architecture machine room is reasonable, and if the occupation ratio is lower than the threshold value, the planning scheme of the architecture machine room is unreasonable, and the position of the existing machine room needs to be adjusted by referring to each value center point.
Preferably, the threshold value is greater than or equal to 60%. In practice, the threshold value may be up and down, depending on the situation, but not lower than 60%.
Preferably, in S2.1, the type of the home scene includes a urban area, a county, a village and a village.
Preferably, in the step S2.2, a corresponding analysis radius r is set for the study area according to the attribution scene of the study area, specifically, urban area-300 m, county-500 m, village-800 m and rural area-1500 m.
Compared with the prior art, the method has the beneficial effects that starting from two aspects of the fixed-moving service dimension and the structural dimension of the base station layout, the method establishes a quantifiable corresponding relation between data such as the base station scale, the base station traffic, the base station access distance, the broadband user quantity and the like and the regional value in a mode of outwards extending layer by taking the datum point as the center and taking the preset value as the radius, simultaneously can intuitively reflect the value aggregation degree of the point location, and performs comprehensive analysis and calculation on the basis of the data to accurately obtain the value center point of the communication network region. Compared with the traditional network value prediction method, the method has the advantages that a base station is abandoned as a single dimension, the structure dimension and the broadband service dimension are increased, data collection and analysis are carried out at any point in a target area, meanwhile, scene differentiation model presetting is carried out on the analysis method according to different scenes, the accuracy and the rationality of a prediction result are improved, and high value references are provided for operator network simplification.
Drawings
In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present disclosure, and other drawings may be obtained according to these drawings without inventive effort for a person of ordinary skill in the art.
Fig. 1 is a general flow chart of a method for selecting a value center point of a communication network area according to the present invention.
Fig. 2 is a schematic diagram of a point location epitaxial layering provided by the invention.
Fig. 3 is a schematic diagram of a determination flow of a machine room of an architecture according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure.
As shown in fig. 1 to 3, in order to facilitate understanding of the above technical solutions of the present disclosure, the following describes the above technical solutions of the present disclosure in detail by a specific usage manner.
The method for selecting the communication network regional value center point comprises the following steps:
S1, acquiring basic information of a research area, wherein the basic information comprises machine room information, base station information and broadband information,
The base station information comprises longitude and latitude information of the base station, and the daily average flow of the base station of the last 1 month;
The broadband information comprises latitude and longitude information of a home wide cell, latitude and longitude information of a private line government and enterprise building, and the number of users of the home wide cell on the network in the last 1 day and the number of users of the private line on the network in the government and enterprise;
The machine room information comprises machine room longitude and latitude information, machine room property attribution, machine room area, machine room electricity leading distance and maximum load, machine room transmission resources and whether dangerous sources exist around the machine room;
s2, preprocessing the basic information, namely preprocessing the basic information acquired in the step S1:
s2.1, determining a home scene of the research area, wherein the home scene represents specific area types (can be specifically urban areas, county areas, villages and towns, rural areas and the like) of the research area;
s2.2, setting a corresponding analysis radius r (which can be specifically shown as urban area-300 m, county-500 m, village-800 m and rural area-1500 m) for the study area according to the attribution scene of the study area;
S2.3 positioning, positioning and parameter calculation, wherein a certain point of the research area is optionally used as a datum point 0, then the datum point 0 is used as a circle center, and r, 2r, 3r, 4r and 5r are used as radiuses to respectively make 5 layers of circles, namely the radiation area of the datum point 0 is divided into 5 layers, and the number of base stations BS in each layer, the single-station average access distance D between the base stations and a machine room connected with the base stations, the sum F of daily average flow of the base stations and the sum B of broadband users are respectively counted;
Then, a plurality of points in a plurality of opposite directions of the datum point 0 are selected based on the datum point 0, the points are respectively taken as the datum points and numbered in sequence, then, each datum point is respectively taken as a circle center, each datum point 0 is referred to, each layer of circles are respectively made by taking r, 2r, 3r, 4r and 5r as radiuses, the number of base stations BS of each layer of each datum point, the single-station average access distance D between the base station and a machine room connected with the base station, the sum F of daily average flow of the base stations and the sum B of broadband users are respectively counted;
Repeatedly iterating the method until the new locating point exceeds the boundary of the research area, explaining that the locating point is located to reach the limit, and then obtaining all the locating points and the corresponding base station quantity BS, the single station average access distance D between the base station and the machine room connected with the base station, the sum F of the daily average flow of the base station and the sum B of the broadband users;
s2.4, preliminarily calculating the estimated quantity M of all value center points according to the research area, the belonging attribution scene and the area of the research area, wherein M=the area/(pi (5 r) 2) +1 of the research area;
s3, calculating service scores and structure scores of all the datum points acquired in the step S2 respectively, and finally acquiring comprehensive value scores corresponding to all the datum points and sequencing;
S4, determining all the value center points one by one according to the reference points obtained by the sequencing in the S3 and the corresponding comprehensive value scores thereof until the number of the determined value center points reaches the estimated number M;
And S5, according to the matching of the value center points determined in the S4 with the machine room, determining a scheme of the architecture machine room, and judging whether the planning scheme is reasonable or not by the operator through the matching degree of the architecture machine room and the value center points in the planning scheme of the operator architecture machine room. The step S5 may be implemented by using the prior art.
In an embodiment, the specific steps of S2.3 are as follows:
S2.3.1, optionally, taking a certain point of the research area as a datum point 0, taking the datum point 0 as a circle center, respectively making 5 layers of circles with r, 2r, 3r, 4r and 5r as radiuses, dividing the radiation area of the datum point 0 into 5 layers, respectively counting the number of base stations in each layer, namely, BS (i, j), the average access distance of a single station between the base station and a machine room connected with the base station, namely, D (i, j), the sum of daily average flow of the base stations, F (i, j) and the sum of broadband users, wherein i, j respectively correspond to the point number and the layer number, namely, i=0, 1 is smaller than or equal to j is smaller than 5;
S2.3.2, firstly, taking four points of distances r in the up, down, left and right directions of the datum point 0 as the basis of the datum point 0, respectively taking 4 datum points, and respectively marking point numbers as 1,2, 3 and 4, namely datum points 1,2, 3 and 4;
S2.3.3, respectively making 5 layers of circles by taking datum points 1, 2, 3 and 4 as circle centers and r, 2r, 3r, 4r and 5r as radiuses, dividing the radiation area of the datum points 1, 2, 3 and 4 into 5 layers, respectively counting the number of base stations in each layer, namely BS (i, j), the average access distance of a single station between the base station and an upper connected room, namely D (i, j), the sum of daily average flow of the base stations, namely F (i, j) and the sum of broadband users, namely B (i, j), aiming at the datum points 1, 2, 3 and 4, wherein i is the point number, j is the layer number, i is more than or equal to 1 and less than or equal to 4, and j is more than or equal to 1 and less than or equal to 5;
S2.3.4, respectively taking four points of distances r in the upper, lower, left and right directions of the datum points 1,2, 3 and 4 as the basis of the datum points 1,2, 3 and 4, respectively taking the four points as 4 datum points, simultaneously removing repeated points, and sequentially numbering the obtained points as 5, 6, 7 and 8.
S2.3.5, respectively taking datum points 5, 6, 7, 8 and..K as circle centers, respectively taking r, 2r, 3r, 4r and 5r as radiuses, respectively making 5 layers of circles, dividing the radiation areas of the datum points 5, 6, 7, 8 and..K into 5 layers, respectively counting the number of base stations in each layer, namely BS (i, j), the single-station average access distance between the base station and an upper online room, namely D (i, j), the sum of daily average flow of the base stations, namely F (i, j) and the sum of broadband users, namely B (i, j), wherein i is a point number, j is a layer number, and 5 is equal to or less than i is equal to K, and 1 is equal to or less than or equal to 5;
S2.3.6, finally, based on the point positions 5, 6, 7, 8 and..K, iteratively repeating with reference to S2.3.4-S2.3.5 until the newly-fetched point positions exceed the boundary of the research area, and marking the point position numbers of all fetched reference points as {0, 1, 2 and..N }, wherein N is the maximum point position number;
S2.3.7, respectively carrying out normalization processing on data of the datum points {0, 1,2 and..N } according to four dimensions of the number of the base stations BS, the average single station access distance D between the base stations and the machine room connected with the base stations, the sum F of daily average flow of the base stations and the sum B of broadband users to obtain a base station density score BSS (i, j), a base station access score DS (i, j), a base station service score FS (i, j) and a broadband service score BS (i, j) of each layer of each datum point, wherein i is a point number, j is a layer number, i is less than or equal to 0 and less than or equal to N, and 1 is less than or equal to j is less than or equal to 5.
In an embodiment, in S2.3.7, for the data of the base station access score DS (i, j), the data of the base station and the data of the single station average access distance D between the machine room connected with the base station are normalized after being inverted due to the difference between the data and other three-dimensional data.
In an embodiment, the specific step of S3 is:
S3.1, traversing all fiducial points 0,1, 2, 3..n, initializing i=0, i.e. selecting fiducial point 0, then continuing S3.2;
s3.2, calculating a service score YW (i), a structure score JG (i) and a comprehensive value score V (i) of the reference point i, wherein the service score YW (i), the structure score JG (i) and the comprehensive value score V (i) are calculated according to the following specific formulas;
YW (i) = Σfs (i, j) k (j) +Σbs (i, j) k (j) (formula one);
JG (i) = Σbss (i, j) k (j) +Σds (i, j) k (j) (formula two);
v (i) =yw (i) +jg (i); (formula three);
in the formula, i is the point number of the current datum point, i is more than or equal to 0 and less than or equal to N, j is the layer number of the datum point, and j is more than or equal to 1 and less than or equal to 5;
YW (i) -business score for reference point i;
JG (i) -structural score of reference point i;
v (i) -the integrated value score for reference point i;
k (j) -weight adjustment coefficients represent the weight of each layer of 1-5 layers, and the values of the weight adjustment coefficients are 1, 0.8, 0.6, 0.4 and 0.2 respectively, and are used for calculating the service scores corresponding to each point bit;
S3.3, if i is not less than N, indicating that all the datum points are traversed, continuing to S3.4, otherwise, increasing the value of i by 1, namely selecting the next datum point in sequence, and returning to S3.2;
and S3.4, finally, sequencing all the datum points in the order of the comprehensive value scores from the big value score to the small value score.
In an embodiment, the specific step of S4 is:
s4.1, selecting a datum point with the largest comprehensive value score, and marking the datum point as a value center point 1;
s4.2, marking the value center point 1 as a current value center point T, wherein T is the point number of the current value center point, initializing T as 1, and representing iteration from the value center point 1;
S4.3, calculating the distance between the current value center point T and other reference points, and removing other reference points with the distance of less than 5r from the current value center point T;
s4.4, increasing the value of T by 1, selecting the value center point T with the largest comprehensive value score from the rest datum points, and indicating that the current value center point T has iterated;
S4.5, if T is not less than M, indicating that the number of the selected value center points reaches the estimated number M, ending the iteration, and entering S4.6, otherwise, indicating that the iteration should be continued, and returning to S4.3;
S4.6, saving the value center points 1 and 2.
In an embodiment, the specific step of S5 is:
s5.1, selecting a total amount of existing machine rooms in a research area as a framework machine room screening basis;
S5.2, comprehensively judging the dimensionalities of property rights, space, power matching, transmission resources and the like of the whole existing machine room, and directly overruling the existing machine room which does not meet the condition;
s5.3, performing distance matching on the existing machine room meeting the preliminary judgment condition and the value center points selected in the S4, and judging that the machine room is reasonable if the distance between the existing machine room and a certain value center point is smaller than r;
S5.4, presetting a threshold value according to the actual condition of the research area, wherein if the reasonable machine room occupation ratio in the planning scheme is higher than the threshold value, the planning scheme of the architecture machine room is reasonable, and if the occupation ratio is lower than the threshold value, the planning scheme of the architecture machine room is unreasonable, and the position of the existing machine room needs to be adjusted by referring to each value center point.
In one embodiment, the threshold is greater than or equal to 60%. In practice, the threshold value may be up and down, depending on the situation, but not lower than 60%.
In an embodiment, in S2.1, the type of the home scene includes a city, a county, a village, and a village.
In an embodiment, in the step S2.2, a corresponding analysis radius r is set for the study area according to the home scene of the study area, specifically, the analysis radius r is from urban area to 300m, from county to 500m, from village to 800m, and from rural area to 1500m.
In summary, through the unique design of the present disclosure, compared with the prior art, the present disclosure starts from two aspects of the service dimension of fixed movement and the structural dimension of the base station layout, and establishes a quantifiable corresponding relationship between the data such as the base station scale, the base station traffic, the base station access distance, the broadband user quantity and the regional value in a mode of outwards extending layer by layer with the preset value as a radius by taking the reference point as the center, and meanwhile, the value aggregation degree of the point location can be intuitively reflected, and on the basis, the big data comprehensive analysis and calculation are performed, so that the value center point of the communication network region is accurately obtained. Compared with the traditional network value prediction method, the method has the advantages that a base station is abandoned as a single dimension, the structure dimension and the broadband service dimension are increased, data collection and analysis are carried out at any point in a target area, meanwhile, scene differentiation model presetting is carried out on the analysis method according to different scenes, the accuracy and the rationality of a prediction result are improved, and high value references are provided for operator network simplification.
The foregoing description of the preferred embodiments of the present disclosure is not intended to limit the disclosure, but rather to cover all modifications, equivalents, improvements and alternatives falling within the spirit and principles of the present disclosure.

Claims (7)

1.一种通信网络区域价值中心点的选择方法，其特征在于，包括以下步骤：1. A method for selecting a value center point of a communication network region, characterized by comprising the following steps: S1获取基础信息：获取研究区域的基础信息，基础信息包括机房信息、基站信息、宽带信息；其中，S1 Obtain basic information: Obtain basic information of the study area, including computer room information, base station information, and broadband information; 基站信息包括：基站经纬度信息，最近1月基站的日均流量；Base station information includes: base station latitude and longitude information, and the average daily traffic of the base station in the past month; 宽带信息包括：家宽小区经纬度信息、专线政企楼宇经纬度信息，最近1天的家宽小区在网用户数、政企专线在网用户数；Broadband information includes: longitude and latitude information of home broadband communities, longitude and latitude information of government and enterprise buildings with dedicated lines, the number of online users of home broadband communities and the number of online users of government and enterprise dedicated lines in the last day; 机房信息包括：机房经纬度信息、机房产权归属、机房面积、机房引电距离及最大负荷、机房传输资源、机房周边是否存在危险源；The information of the computer room includes: the longitude and latitude of the computer room, the ownership of the computer room, the area of the computer room, the distance and maximum load of the power supply to the computer room, the transmission resources of the computer room, and whether there are any dangerous sources around the computer room; S2预处理基础信息：对S1获取的基础信息进行以下的预处理：S2 preprocesses basic information: The basic information obtained in S1 is preprocessed as follows: S2.1:确定研究区域的归属场景，归属场景表示研究区域的具体区域类型；S2.1: Determine the attribution scenario of the study area, where the attribution scenario represents the specific area type of the study area; S2.2：根据研究区域的归属场景，为其设定对应的分析半径r；S2.2: According to the belonging scenario of the study area, set the corresponding analysis radius r for it; S2.3定位取定及参数计算：任选所述研究区域的某一点位作为基准点0，然后以基准点0为圆心，且以r、2r、3r、4r、5r为半径分别做5层圆，即将基准点0的辐射区域划分为5层，分别统计每一层内的基站数量BS、基站与其上联的机房之间的单站平均接入距离D、基站日均流量之和F、宽带用户之和B；S2.3 Positioning and parameter calculation: A point in the study area is selected as the reference point 0, and then 5 circles are made with the reference point 0 as the center and r, 2r, 3r, 4r, and 5r as the radius, that is, the radiation area of the reference point 0 is divided into 5 layers, and the number of base stations BS in each layer, the average single-station access distance D between the base station and the computer room connected to it, the sum of the average daily traffic of the base station F, and the sum of broadband users B are counted respectively; 然后再以基准点0为基础，选定基准点0的若干个相对方向上的若干个点位，分别取定为基准点并按顺序编号，然后分别将取定的各基准点作为圆心，参照基准点0且分别以r、2r、3r、4r、5r为半径分别做5层圆，并分别统计各基准点的每一层的基站数量BS、基站与其上联的机房之间的单站平均接入距离D、基站日均流量之和F、宽带用户之和B；Then, based on the reference point 0, several points in several relative directions of the reference point 0 are selected as reference points and numbered in sequence. Then, with each of the selected reference points as the center of the circle, five circles are made with reference to the reference point 0 and with the radii of r, 2r, 3r, 4r, and 5r, respectively. The number of base stations BS, the average single-station access distance D between the base station and the computer room connected to it, the sum of the average daily traffic of the base station F, and the sum of broadband users B are counted for each layer of each reference point. 参照上述方法反复迭代，直到新取定点位超出研究区域的边界，说明基准点取定已达极限，然后由此得到所有基准点及其对应的基站数量BS、基站与其上联的机房之间的单站平均接入距离D、基站日均流量之和F、宽带用户之和B；Repeat the above method until the new point exceeds the boundary of the study area, indicating that the benchmark point has reached the limit. Then, all benchmark points and their corresponding base station numbers BS, the average single-station access distance D between the base station and the computer room connected to it, the sum of the average daily traffic of the base station F, and the sum of broadband users B are obtained. 所述S2.3的具体步骤为：The specific steps of S2.3 are: S2.3.1：任选所述研究区域的某一点位作为基准点0，其点位编号为0，以基准点0为圆心，且以r、2r、3r、4r、5r为半径分别做5层圆，将基准点0的辐射区域划分为5层；分别统计每一层内的基站数量:BS（i，j）、基站与其上联的机房之间的单站平均接入距离:D（i，j）、基站日均流量之和:F（i，j）、宽带用户之和:B（i，j）；其中，i，j分别对应点位编号及层数，即i=0，1≦j≦5；S2.3.1: Select any point in the study area as reference point 0, whose point number is 0. Take reference point 0 as the center and make 5 circles with radius r, 2r, 3r, 4r, and 5r respectively, and divide the radiation area of reference point 0 into 5 layers; count the number of base stations in each layer: BS (i, j), the average single-station access distance between the base station and the computer room connected to it: D (i, j), the sum of the average daily traffic of the base station: F (i, j), and the sum of broadband users: B (i, j); where i and j correspond to the point number and the number of layers respectively, that is, i=0, 1≦j≦5; S2.3.2：首先，以基准点0为基础，将基准点0的上、下、左、右方向上距离r的四个点位，分别取定为4个基准点，点位编号分别记为1、2、3、4，即基准点1、2、3、4；S2.3.2: First, taking reference point 0 as the basis, four points at a distance r above, below, left, and right of reference point 0 are respectively selected as four reference points, and the point numbers are recorded as 1, 2, 3, and 4, i.e., reference points 1, 2, 3, and 4; S2.3.3：分别以基准点1、2、3、4为圆心，且以r、2r、3r、4r、5r为半径分别做5层圆，将基准点1、2、3、4的辐射区域划分为5层；针对基准点1、2、3、4，分别统计各自每一层内的基站数量:BS（i，j）、基站与上联机房之间的单站平均接入距离:D（i，j）、基站日均流量之和:F（i，j）、宽带用户之和:B（i，j）；其中，i为点位编号、j为层数编号，1≦i≦4，1≦j≦5；S2.3.3: Take reference points 1, 2, 3, and 4 as the center of the circle and r, 2r, 3r, 4r, and 5r as the radius to make 5 circles respectively, and divide the radiation area of reference points 1, 2, 3, and 4 into 5 layers; for reference points 1, 2, 3, and 4, respectively count the number of base stations in each layer: BS (i, j), the average access distance between the base station and the uplink room: D (i, j), the sum of the average daily traffic of the base station: F (i, j), and the sum of broadband users: B (i, j); where i is the point number, j is the layer number, 1≦i≦4, 1≦j≦5; S2.3.4：然后，再分别以基准点1、2、3、4为基础，将基准点1、2、3、4各自的上、下、左、右方向上距离r的四个点位，分别各取定为4个基准点，同时剔除掉重复点位，将所得点位依次按顺序编号为5、6、7、8、…K，即基准点5、6、7、8、…K；S2.3.4: Then, based on reference points 1, 2, 3, and 4, four points at a distance r from each other in the upper, lower, left, and right directions of reference points 1, 2, 3, and 4 are respectively selected as four reference points, and duplicate points are eliminated. The obtained points are numbered in sequence as 5, 6, 7, 8, ...K, i.e., reference points 5, 6, 7, 8, ...K; S2.3.5：分别以基准点5、6、7、8、…K为圆心，且以r、2r、3r、4r、5r为半径分别做5层圆，将基准点5、6、7、8、…K的辐射区域划分为5层；针对基准点5、6、7、8、…K，分别统计每一层内的基站数量:BS（i，j）、基站与上联机房之间的单站平均接入距离:D（i，j）、基站日均流量之和:F（i，j）、宽带用户之和:B（i，j）；其中，i为点位编号、j为层数编号，5≦i≦K，1≦j≦5；S2.3.5: Take reference points 5, 6, 7, 8, ...K as the center of the circle and r, 2r, 3r, 4r, 5r as the radius to make 5 circles respectively, and divide the radiation area of reference points 5, 6, 7, 8, ...K into 5 layers; for reference points 5, 6, 7, 8, ...K, count the number of base stations in each layer: BS (i, j), the average access distance between the base station and the uplink room: D (i, j), the sum of the average daily traffic of the base station: F (i, j), and the sum of broadband users: B (i, j); where i is the point number, j is the layer number, 5≦i≦K, 1≦j≦5; S2.3.6：最后再以点位5、6、7、8、…K为基础，参照S2.3.4~S2.3.5迭代重复，直到新取定的点位超出所述研究区域的边界，将所有取定的基准点的点位编号记作{0、1、2、…N}，N为最大的点位编号；S2.3.6: Finally, based on points 5, 6, 7, 8, ...K, refer to S2.3.4~S2.3.5 for iteration until the newly determined points exceed the boundary of the study area. The point numbers of all the determined benchmark points are recorded as {0, 1, 2, ...N}, where N is the largest point number; S2.3.7：按照基站数量BS、基站与其上联的机房之间的单站平均接入距离D、基站日均流量之和F、宽带用户之和B四个维度，将基准点{0、1、2、…N}的数据分别进行归一化处理，得出每一基准点的每一层的基站密度得分BSS（i,j）、基站接入得分DS（i,j）、基站业务得分FS（i,j）、宽带业务得分BS（i,j）；其中，i为点位编号、j为层数编号，0≦i≦N，1≦j≦5；S2.3.7: According to the four dimensions of the number of base stations BS, the average single-station access distance D between the base station and the computer room connected to it, the sum of the average daily traffic of the base station F, and the sum of the broadband users B, the data of the benchmark points {0, 1, 2, ... N} are normalized respectively to obtain the base station density score BSS (i, j), base station access score DS (i, j), base station service score FS (i, j), and broadband service score BS (i, j) of each layer of each benchmark point; where i is the point number, j is the layer number, 0≦i≦N, 1≦j≦5; S2.4：根据研究区域、所属的归属场景及研究区域面积，初步计算所有价值中心点的预估数量M，M=研究区域的面积/（π*（5r）2）+1；S2.4: Based on the research area, the belonging scenario and the area of the research area, preliminarily calculate the estimated number M of all value centers, M = the area of the research area / (π*(5r) 2 ) + 1; S3：分别计算S2所获取的所有基准点的业务分值、结构分值，最终取得每一基准点对应的综合价值分值后排序；S3: Calculate the business scores and structural scores of all benchmarks obtained in S2 respectively, and finally obtain the comprehensive value score corresponding to each benchmark and sort them; 所述S3的具体步骤为：The specific steps of S3 are: S3.1：遍历所有基准点0、1、2、3...N，初始化i=0，即选中基准点0，然后继续S3.2；S3.1: traverse all reference points 0, 1, 2, 3...N, initialize i=0, that is, select reference point 0, and then continue S3.2; S3.2：计算基准点i的业务分值YW（i）、结构分值JG（i）、综合价值分值V（i），具体按下列公式计算；S3.2: Calculate the business score YW(i), structure score JG(i), and comprehensive value score V(i) of benchmark point i, specifically according to the following formula; YW（i）=∑FS（i，j）*k(j)+ ∑BS（i，j）*k(j)； （公式一）；YW(i)=∑FS(i,j)*k(j)+∑BS(i,j)*k(j); (Formula 1); JG（i）= ∑BSS（i，j）*k(j)+ ∑DS（i，j）* k(j)； （公式二）；JG(i) = ∑BSS(i, j)*k(j)+ ∑DS(i, j)*k(j); (Formula 2); V（i）= YW（i）+ JG（i）； （公式三）；V(i) = YW(i) + JG(i); (Formula 3); 上述公式中：i：当前基准点的点位编号，0≦i≦N；j为基准点的层数编号，1≦j≦5；In the above formula: i is the point number of the current reference point, 0≦i≦N; j is the layer number of the reference point, 1≦j≦5; YW（i）--基准点i的业务分值；YW(i)--business score of benchmark point i; JG（i）--基准点i的结构分值；JG(i) - structural score of benchmark point i; V（i）--基准点i的综合价值分值；V(i) – the comprehensive value score of benchmark point i; k(j)--权重调整系数，代表1~5层每一层的权重，分别取值为1、0.8、0.6、0.4、0.2，用于计算每一点位对应的业务分值；k(j)--weight adjustment coefficient, representing the weight of each layer from 1 to 5, with values of 1, 0.8, 0.6, 0.4, and 0.2 respectively, used to calculate the business score corresponding to each point; S3.3：若i≧N，表明所有基准点已经遍历结束，则继续S3.4；否则，让i数值增加1,即按顺序选定下一个基准点，回到S3.2；S3.3: If i≧N, it means that all reference points have been traversed, and then continue to S3.4; otherwise, increase the value of i by 1, that is, select the next reference point in order, and return to S3.2; S3.4：最后，以综合价值分值从大到小顺序，对所有基准点排序；S3.4: Finally, sort all benchmarks in descending order of their comprehensive value scores; S4：根据S3所排序得到的各基准点及其对应的综合价值分值，逐一确定各价值中心点，直到确定的价值中心点的数量达到预估数量M；S4: According to the benchmark points sorted in S3 and their corresponding comprehensive value scores, determine the value center points one by one until the number of determined value center points reaches the estimated number M; S5：依据S4所确定的各价值中心点与机房进行匹配，确定架构机房的方案，通过运营商架构机房规划方案中架构机房与价值中心点的匹配度，为运营商判定规划方案是否合理提供参考。S5: According to the matching of each value center point determined in S4 with the computer room, determine the plan for the computer room structure, and provide a reference for the operator to determine whether the planning plan is reasonable through the matching degree between the computer room structure and the value center point in the operator's computer room structure planning plan. 2.根据权利要求1所述的选择方法，其特征在于，所述S2.3.7中，针对基站接入得分DS（i,j）的数据，将其的数据求倒数后，再归一化处理。2. The selection method according to claim 1 is characterized in that, in S2.3.7, the data of the base station access score DS (i, j) is inversely calculated and then normalized. 3.根据权利要求1所述的选择方法，其特征在于，所述S4的具体步骤为：3. The selection method according to claim 1, characterized in that the specific steps of S4 are: S4.1：选取综合价值分值最大的基准点，将其记为价值中心点1；S4.1: Select the benchmark point with the largest comprehensive value score and record it as value center point 1; S4.2：将价值中心点1记作当前价值中心点T，T为当前价值中心点的点位编号，将T初始化为1，代表迭代从价值中心点1开始；S4.2: Value center point 1 is recorded as the current value center point T, where T is the point number of the current value center point. T is initialized to 1, indicating that the iteration starts from value center point 1; S4.3：计算当前价值中心点T与其他基准点的距离，并剔除掉与当前价值中心点T距离小于5r的其它基准点；S4.3: Calculate the distance between the current value center point T and other reference points, and remove other reference points whose distance from the current value center point T is less than 5r; S4.4：让T的数值增加1，并在剩余基准点中，选取综合价值分值最大的记为价值中心点T，且表示当前价值中心点T也已经发生迭代；S4.4: Increase the value of T by 1, and select the one with the largest comprehensive value score from the remaining benchmark points as the value center point T, and indicate that the current value center point T has also been iterated; S4.5：若T≧M，说明已经选取的价值中心点的数量已达到预估数量M，迭代应当结束，进入S4.6；否则，表明迭代应当继续，返回S4.3；S4.5: If T≧M, it means that the number of selected value centers has reached the estimated number M, and the iteration should end and go to S4.6; otherwise, it means that the iteration should continue and return to S4.3; S4.6：保存记录所选取的价值中心点1、2...T。S4.6: Save and record the selected value center points 1, 2...T. 4.根据权利要求3所述的选择方法，其特征在于，所述S5的具体步骤为：4. The selection method according to claim 3, characterized in that the specific steps of S5 are: S5.1：选择研究区域内全量现有机房，作为架构机房筛选基础；S5.1: Select all existing computer rooms in the study area as the basis for selecting architecture computer rooms; S5.2：对全量现有机房进行产权、空间、动力配套、传输资源进行综合判定，对于不符合条件的现有机房直接否决；S5.2: Comprehensively assess the property rights, space, power support, and transmission resources of all existing equipment rooms, and directly reject those that do not meet the requirements; S5.3：对符合初步判定条件的现有机房与S4所选取的各价值中心点进行距离匹配，若现有机房与某个价值中心点距离小于r，则判定合理；S5.3: Match the distance between the existing computer room that meets the preliminary judgment conditions and each value center point selected in S4. If the distance between the existing computer room and a value center point is less than r, the judgment is reasonable; S5.4：依据研究区域实际情况预设门限值，规划方案中合理机房占比若高于门限值，则该架构机房规划方案合理；若占比低于门限值，则该架构机房规划方案不合理，需参考各价值中心点来对现有机房位置进行调整。S5.4: Preset a threshold value based on the actual situation of the study area. If the proportion of reasonable computer rooms in the planning scheme is higher than the threshold value, then the planning scheme of the computer room architecture is reasonable; if the proportion is lower than the threshold value, then the planning scheme of the computer room architecture is unreasonable, and it is necessary to refer to the value center points to adjust the location of the existing computer room. 5.根据权利要求4所述的选择方法，其特征在于，所述门限值≥60%。The selection method according to claim 4 , wherein the threshold value is ≥ 60%. 6.根据权利要求1所述的选择方法，其特征在于，所述S2.1中，所述归属场景的类型包括市区、县城、乡镇、农村。6. The selection method according to claim 1 is characterized in that, in S2.1, the types of the belonging scenes include urban areas, county towns, towns, and rural areas. 7.根据权利要求6所述的选择方法，其特征在于，所述S2.2中，根据研究区域的归属场景，为其设定对应的分析半径r，具体为：市区-300m，县城-500m，乡镇-800m，农村-1500m。7. The selection method according to claim 6 is characterized in that, in S2.2, a corresponding analysis radius r is set for the study area according to the belonging scenario, specifically: urban area - 300m, county town - 500m, township - 800m, rural area - 1500m.
CN202411054352.5A 2024-08-02 2024-08-02 Method for selecting regional value center point of communication network Active CN119233270B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202411054352.5A CN119233270B (en) 2024-08-02 2024-08-02 Method for selecting regional value center point of communication network

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202411054352.5A CN119233270B (en) 2024-08-02 2024-08-02 Method for selecting regional value center point of communication network

Publications (2)

Publication Number Publication Date
CN119233270A CN119233270A (en) 2024-12-31
CN119233270B true CN119233270B (en) 2025-05-02

Family

ID=93946084

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202411054352.5A Active CN119233270B (en) 2024-08-02 2024-08-02 Method for selecting regional value center point of communication network

Country Status (1)

Country Link
CN (1) CN119233270B (en)

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109840611A (en) * 2017-11-28 2019-06-04 中国移动通信集团浙江有限公司 A kind of Integrated services access area constant volume addressing processing method and processing device
CN109996245A (en) * 2017-12-31 2019-07-09 中国移动通信集团四川有限公司 The communication resource launches appraisal procedure, device, electronic equipment and storage medium

Family Cites Families (15)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20010064747A (en) * 1999-12-18 2001-07-11 이계철 Method of estimation node-selection and investment cost in broadband subscriber line
US20070225008A1 (en) * 2006-03-23 2007-09-27 First Broadcasting Investment Partners, Llc Systems and methods for determining replacement communication facility
KR100918786B1 (en) * 2007-03-14 2009-09-23 주식회사 셀리지온 Network based terminal location method
KR101578390B1 (en) * 2013-08-07 2015-12-17 에스케이텔레콤 주식회사 Method and apparatus for locating base station
CN106304178A (en) * 2016-07-21 2017-01-04 国网信息通信产业集团有限公司 The QoS assurance of a kind of electrically-based heterogeneous wireless network and system
KR102189610B1 (en) * 2016-10-07 2020-12-11 가부시끼가이샤 디디에스 Information processing program and information processing device
CN107911817A (en) * 2017-11-15 2018-04-13 夏江 Mobile intelligent terminal scanning Wi-Fi hotspot completes roll-call method
CN111356148B (en) * 2018-12-21 2023-03-24 中兴通讯股份有限公司 Method and related equipment for realizing network optimization
CN111010665B (en) * 2019-12-18 2021-03-16 广东海格怡创科技有限公司 Hotspot range positioning method and device, computer equipment and storage medium
CN112217675B (en) * 2020-10-12 2023-03-24 北京电信规划设计院有限公司 Combined analysis method for big data of fixed and mobile communication network
CN114584183A (en) * 2020-11-30 2022-06-03 北京三星通信技术研究有限公司 Collaborative scheduling method and related equipment
KR102614912B1 (en) * 2021-02-10 2023-12-19 주식회사 페어랩스 Apparatus for evaluating latent value of patent based on deep learning and method thereof
CN115062816B (en) * 2022-05-07 2024-09-24 安徽电信规划设计有限责任公司 Service demand prediction method based on network construction data model
CN117132161A (en) * 2023-08-29 2023-11-28 中国移动通信集团内蒙古有限公司 Network resource data value analysis methods, devices, equipment and storage media
CN117726369A (en) * 2023-12-22 2024-03-19 北京工商大学 Commercial area address selection method and system based on mobile phone signaling data

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109840611A (en) * 2017-11-28 2019-06-04 中国移动通信集团浙江有限公司 A kind of Integrated services access area constant volume addressing processing method and processing device
CN109996245A (en) * 2017-12-31 2019-07-09 中国移动通信集团四川有限公司 The communication resource launches appraisal procedure, device, electronic equipment and storage medium

Also Published As

Publication number Publication date
CN119233270A (en) 2024-12-31

Similar Documents

Publication Publication Date Title
CN109327841B (en) Multi-dimensional evaluation and accurate construction evaluation method based on coverage and value association
WO2022089031A1 (en) Network optimization method based on big data and artificial intelligence
CN108495254B (en) Traffic cell population characteristic estimation method based on signaling data
CN114926098B (en) Method and system for quickly delineating urban and rural living circles based on mobile positioning data
CN111510957B (en) Mobile edge server coordinate positioning method based on multi-target constraint optimization
CN112653991A (en) WLAN indoor positioning method of TebNet neural network model based on deep learning
CN110688958A (en) Intersection Recognition Method Based on GoogLeNet Neural Network
CN103336894A (en) Automatic dividing method of city plot ratio
CN107506872A (en) A kind of residential block part throttle characteristics and the Categorical research method of model prediction
CN110852547B (en) Public service facility grading method based on position data and clustering algorithm
CN110232421B (en) Step-by-step combined OD flow direction space-time combined clustering method
CN105873119A (en) Method for classifying flow use behaviors of mobile network user groups
CN120069213A (en) Station planning optimization method and system based on charging station data analysis
CN119233270B (en) Method for selecting regional value center point of communication network
CN110288125A (en) A method for establishing a commuting model based on mobile phone signaling data and its application
CN118608354A (en) Urban comprehensive data analysis platform based on intelligent analysis algorithm model
CN118429164A (en) Communication base station service population distribution calculation method and system based on Thiessen polygon
CN107231635A (en) The analysis method and device of a kind of network coverage
CN116245299A (en) Electric vehicle charging station reachability analysis method based on LEVCD-2SFCA model
CN119294958B (en) Intelligent object genre method and system based on electronic map
CN114007230A (en) Base station network access data processing method and device, electronic equipment and storage medium
CN114037271A (en) Police resource allocation method and device
CN119831294B (en) Space utilization layout optimization method and system based on artificial intelligence
CN115087098B (en) Method, system and readable storage medium for identifying attribution of base station sector of communication base station
CN119151270B (en) Charging station address selection method, charging station address selection device, computer equipment and readable storage medium

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant