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CN106507378B - A kind of management method and device of cell coverage area - Google Patents

A kind of management method and device of cell coverage area Download PDF

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Publication number
CN106507378B
CN106507378B CN201611027414.9A CN201611027414A CN106507378B CN 106507378 B CN106507378 B CN 106507378B CN 201611027414 A CN201611027414 A CN 201611027414A CN 106507378 B CN106507378 B CN 106507378B
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cell
coverage
clusters
radius
cluster
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CN106507378A (en
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高洁
程新洲
晁昆
任鹏飞
曹丽娟
徐乐西
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China United Network Communications Group Co Ltd
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China United Network Communications Group Co Ltd
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    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W16/00Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/18Network planning tools

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

Abstract

The embodiment of the present invention provides the management method and device of a kind of cell coverage area, is related to wireless communication technology field, can find MPS process problem early, provides guidance for optimizing cells work.Concrete scheme includes: the target data for obtaining cell in preset range;The reasonable coverage area of cell, practical coverage area and cutting off rate in the preset range are determined according to the target data of cell;The description vectors of cell in the preset range are divided into K cluster by k-means algorithm;Wherein, the description vectors of a cell include the cutting off rate and covering ratio of the cell, cover the ratio than practical coverage area and reasonable coverage area for the cell;The K cluster includes at least normal covering cluster, excessively covering cluster and weak covering cluster.The present invention is for determining that there are the cells of covering problem.

Description

Method and device for managing cell coverage
Technical Field
The embodiment of the invention relates to the technical field of wireless communication, in particular to a method and a device for managing a cell coverage area.
Background
Cell coverage problems in 3G networks include both over-coverage and weak-coverage situations.
The over-coverage refers to the phenomenon that the coverage is too large and too far in the network. The over-coverage is represented as that the signal of the main control sector is too strong, and exceeds the reasonable coverage range of the sector, so that no main pilot frequency or cross-zone signals in the coverage range of other cells are caused to be the main control signal instead of the main pilot frequency, serious interference is brought to the sector, the internal interference of a network is unevenly distributed, and then, the wireless signals are disordered, the problems of poor connection performance, poor call quality, call drop and the like are caused, and the service quality of a user is influenced.
The weak coverage refers to the phenomenon that the signal strength of a coverage area is insufficient due to unreasonable antenna feeder or equipment parameter setting. Weak coverage may cause the primary coverage cell to have insufficient control power in the primary control coverage area, and a planned coverage area cannot be achieved.
In the prior art, in order to identify a cell with a coverage problem, a common method is to manually read LOG (english: LOG) information, and combine with drive test data analysis to find that there are abnormal events caused by over coverage or weak coverage of a cell with a longer distance, where the abnormal events are generally service quality problems that seriously affect user experience, such as poor pilot channel quality index Ec/Io, continuous call drop, low data service download rate, and the like.
However, the problematic cell can be found through LOG information only after the coverage problem has occurred, and can be found generally when the problem is serious, so that the prior art solution cannot find the cell coverage problem early.
Disclosure of Invention
The embodiment of the invention provides a management method of a cell coverage area, which can find the cell coverage problem as soon as possible and provide guidance for cell optimization work.
In order to achieve the above purpose, the embodiments of the present application adopt the following technical solutions:
in a first aspect, a method for managing a cell coverage is provided, including:
acquiring target data of cells within a preset range, wherein the target data of one cell comprises the following steps: the position information of the cell, a common-frequency neighbor cell list, the normal release times, the abnormal release times and the propagation delay data of the radio access bearer RAB of the cell in the historical time of the preset length, and the switching success times of the cell in the historical time of the preset length and each common-frequency neighbor interval in the preset range;
determining a reasonable coverage area, an actual coverage area and a call drop rate of the cell in the preset range according to target data of the cell;
dividing the description vectors of the cells in the preset range into K clusters through a K-means algorithm;
the description vector of one cell comprises the call drop rate and the coverage ratio of the cell, wherein the coverage ratio is the ratio of the actual coverage range to the reasonable coverage range of the cell; the K clusters at least comprise normal coverage clusters, excessive coverage clusters and weak coverage clusters.
In a second aspect, an apparatus for managing cell coverage is provided, which is configured to perform the method provided in the first aspect.
The method and the device for managing the cell coverage area provided by the embodiment of the invention analyze target data through a means algorithm, and divide description vectors of cells in a preset range into K clusters, wherein the K clusters at least comprise a normal coverage cluster, an excessive coverage cluster and a weak coverage cluster, and are respectively used for indicating the cells with normal coverage, excessive coverage and weak coverage.
For a cell, the target data comprises two types of information, one type is the working parameter data of the cell, and specifically comprises the position information of the cell and a same-frequency neighbor list; the other type is historical data about the working state of the cell, and specifically includes RAB normal release times, RAB abnormal release times and propagation delay data of the cell in the historical time of a preset length, and the switching success times of the cell in each same-frequency adjacent interval in the historical time of the preset length and the preset range. For an operator, target data are known and changed in real time, description vectors of cells are divided into different clusters by analyzing the data, the cells covered normally are indicated by normal covering clusters, and the cells with coverage problems are indicated by over covering clusters and weak covering clusters. Before an abnormal event caused by a coverage problem occurs, whether the cell coverage problem exists can be determined through the technical scheme of the application.
In the prior art, a coverage problem is found and corresponding measures are taken after an abnormal event occurs, and the method is a solution mode of 'post remedy'. The technical scheme provided by the embodiment of the application can find the coverage problem before the abnormal event occurs so as to guide the cell optimization work, and is a solution mode of 'prevention in advance'.
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 will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained based on these drawings without creative efforts.
Fig. 1 is an explanatory diagram of cell radius and inter-station distance;
fig. 2 is a flowchart illustrating a method for managing a cell coverage according to an embodiment of the present invention;
FIG. 3 is a diagram illustrating dynamic coverage radius of a serving cell according to an embodiment of the present invention;
fig. 4 is an explanatory diagram of a case where a cell is divided into 3 clusters in the embodiment of the present invention;
fig. 5 is a schematic structural diagram of a device for managing cell coverage 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.
The embodiment of the invention provides a method and a device for managing a cell coverage area, aiming at determining which cells have cell coverage problems by analyzing the existing data before an abnormal event caused by the coverage problems occurs, thereby providing guidance for cell optimization work.
The method for managing the cell coverage provided by the embodiment of the invention can be briefly summarized into two parts:
the first part, cell classification. By analyzing the target data of the cells within the preset range, the cells are divided into at least 3 types: normal coverage, excessive coverage, and weak coverage cells.
The target data can be obtained from an Operation Support System (OSS), and the first part can be executed for multiple times due to real-time change of the target data, so that real-time classification of cells is realized.
And the second part, cell optimization. The second part is optional, and the cell is automatically optimized on the basis of the first part. After the first part is executed each time, the second part can be executed, and automatic and real-time optimization of the cell is realized.
The following is a description of the relevant concepts present in the embodiments of the invention:
A. longitude and latitude distance formula
The longitude and latitude distance formula is used for calculating the distance between two points according to the longitude and latitude of the two points. Referring to fig. 1, D represents the distance between two points, and includes:
D=1000*6371.004*ACOS(COS(PI()/2-Lat1*PI()/180)*COS(PI()/2-Lat2*PI()/180)+COS(Lon1*PI()/180-Lon2*PI()/180)*SIN(PI()/2-Lat1*PI()/180)*SIN(PI()/2-Lat2*PI()/180))
wherein the unit of D is meter. Lat1 is the latitude of point a, Lat2 is the latitude of point B, Lon1 is the longitude of point a, and Lon2 is the longitude of point B.
B. Propagation delay
The base station device itself can receive the lead code (English: preamble) sent by the terminal before the call, and measure the propagation delay according to the known lead code at the base station side, then calculate the distance between the terminal and the base station by using the wireless signal in the free space propagation model, and store the statistical result in the device Counter: pmpropatitiondelay.
Taking the ericsson product as an example: the counter will measure the coverage distance of the transmitting cell, and measure propagation delay (i.e. cell distance parameter) from Random Access Channel (RACH) through correct Cyclic Redundancy Check (CRC).
Unlike peg counters, the counter is a pdf counter, i.e., a counter with a range property. The recorded values, occurring within a certain distance range ([ n%, (n + 1)% ]. CellRange), the counter is increased by 1, for a total of 41 non-equivalent value ranges as shown below:
pmPropagationDelay[0]:Maximum delay in number of chips,0..2562 chips
pmPropagationDelay[1]:Number of samples in range[0%..1%[
pmPropagationDelay[2]:Number of samples in range[1%..2%[
pmPropagationDelay[10]:Number of samples in range[9%..10%[
pmPropagationDelay[11]:Number of samples in range[10%..12%[
pmPropagationDelay[12]:Number of samples in range[12%..14%[
pmPropagationDelay[20]:Number of samples in range[28%..30%[
pmPropagationDelay[21]:Number of samples in range[30%..33%[
pmPropagationDelay[22]:Number of samples in range[33%..36%[
pmPropagationDelay[30]:Number of samples in range[57%..60%[
pmPropagationDelay[31]:Number of samples in range[60%..64%[
pmPropagationDelay[32]:Number of samples in range[64%..68%[
pmPropagationDelay[40]:Number of samples in range[96%..100%[
the maximum access range (English: CellRange) is the maximum propagation distance of the cell which can be set manually, and the default setting value is 35000 meters. Network management personnel can control the statistical step length by setting CellRange, and meanwhile, the parameter can control the starting and the closing of feature, when the parameter is larger than or equal to 35000, the feature is started, otherwise, the feature is closed.
C. Neighbor list
The neighbor list is static data configured at a Radio Network Controller (RNC) side and is used for indicating a User Equipment (UE) to perform static parameters for inter-cell handover. The neighboring cells of a cell are generally classified into three categories: the same-frequency adjacent cell, the different-frequency adjacent cell and the different-system adjacent cell. In the embodiment of the invention, only the adjacent regions with the same frequency are needed.
D.k-means clustering algorithm
The K-means algorithm is a typical clustering algorithm based on distance, and the distance is used as an evaluation index of similarity, that is, the closer the distance between two objects is, the greater the similarity of the two objects is. The algorithm considers clusters to be composed of closely spaced objects, and therefore targets the resulting compact and independent clusters as final targets. The specific algorithm is as follows:
(1) randomly selecting k objects from n data objects as initial clustering centers;
(2) calculating the distance between each object and the central objects according to the mean value (central object) of each clustering object, and dividing the corresponding objects again according to the minimum distance;
(3) re-computing the mean (center object) of each (changed) cluster;
(4) loop (2) through (3) until each cluster no longer changes.
E.E criterion decision
In the k-means algorithm, in the first step, any k objects are randomly selected as the centers of initial clusters, and the initial clusters represent one cluster. The algorithm reassigns each object remaining in the data set to the nearest cluster based on its distance from the center of the respective cluster in each iteration. After all data objects are examined, one iteration operation is completed, and a new clustering center is calculated. If the value of E does not change before and after an iteration, the algorithm is converged, and the function of the E criterion is determined.
With reference to the above description, the following describes the procedures of cell classification and cell optimization in detail through specific embodiments.
Examples
An embodiment of the present invention provides a method for managing a cell coverage, which is shown in fig. 2 and includes the following steps:
201. and acquiring target data of the cell within a preset range.
The preset range may be a city, and the cell in the preset range specifically refers to a cell in the city range. The preset range may also be a government district in a city, or other geographical range, and the specific size of the preset range is not limited in this embodiment.
The target data may be obtained from the OSS. For a cell, the target data for the cell includes: the position information of the cell, the list of the same-frequency adjacent cells, the normal release times of the Radio Access Bearer (RAB), the abnormal release times of the RAB and the propagation delay data of the cell within the history time of the preset length, and the switching success times of each same-frequency adjacent cell within the history time of the preset length and the preset range.
The location information may specifically be static parameter data of the cell, including longitude and latitude information.
202. Determining a reasonable coverage area, an actual coverage area and a call drop rate of a cell in a preset range according to target data of the cell;
in connection with fig. 1, the coverage of a cell is specifically indicated by the radius d of the cell. The cell radius may specifically refer to any one of a static coverage radius, a dynamic coverage radius, a reasonable coverage radius, and an actual coverage radius that appear later, and is used to indicate a static coverage range, a dynamic coverage range, a reasonable coverage range, and an actual coverage range of the cell, respectively.
In this embodiment, the static coverage radius and the dynamic coverage radius of the cell are first calculated according to the target data of the cell, and then the reasonable coverage radius of the cell is calculated according to the static coverage radius and the dynamic coverage radius of the cell, where the reasonable coverage radius of the cell is used to indicate the reasonable coverage area of the cell. The specific calculation process will be explained as follows:
radius of static coverage
Calculating to obtain the static coverage radius of the cell according to a first formula, wherein the first formula is as follows:
wherein d isn1Is the static coverage radius, R, of the cellnqIs the static spacing between the cell n and the qth co-frequency adjacent region, and q is the number of co-frequency adjacent regions of the cell n.
Dynamic radius of coverage
Fig. 3 is a schematic diagram illustrating the determination of the dynamic coverage radius of the serving cell according to the static distance between neighboring cells and the number of successful handovers between neighboring cells. In this embodiment, the dynamic coverage radius of the cell is calculated according to a second formula, where the second formula is:
wherein d isn2Is the dynamic coverage radius, R, of a cellnqIs the static spacing between the N and the q-th co-frequency adjacent interval, NnqThe successful times of switching between the cell n and the q-th co-frequency adjacent region are shown, and q is the number of the co-frequency adjacent regions of the cell n.
Reasonable radius of coverage
And calculating to obtain the dynamic coverage radius of the cell according to a third formula, wherein the third formula is as follows:
dn=(α*dn1+β*dn2)/(α+β)
wherein d isnIs a reasonable coverage radius of the cell, dn1Is the static coverage radius of the cell, dn2For the dynamic coverage radius of a cell, α and β are weighting factors of the static coverage radius and the dynamic coverage radius, respectively, and α + β is 1.
Actual radius of coverage
Calculating to obtain an actual coverage radius of the cell according to a fourth formula, wherein the actual coverage radius is used for indicating an actual coverage range, and the fourth formula is as follows:
wherein r isnIs the actual coverage radius of the cell, NiIs propagation delay data PD [ i ]]CellRange is the maximum coverage distance configured for the system.
Dropped call rate in a cell
In order to be closer to user perception, the embodiment introduces the performance index of the service in the data analysis process, the call drop rate can visually reflect the service perception of the user, and meanwhile, the high call drop rate is generally caused by the network coverage. The CDR represents the cell drop rate, and includes:
the CDR ═ RAB abnormal release times/(RAB abnormal release times + RAB normal release times) × 100%
203. Dividing description vectors of cells in a preset range into K clusters through a K-means algorithm;
the description vector of a cell comprises the call drop rate and the coverage ratio of the cell, wherein the coverage ratio is the ratio of the actual coverage range to the reasonable coverage range of the cell;
when the K-means clustering algorithm is initialized, the number K of clusters needs to be determined, and the central point C of each clusterk. The K clusters include at least a normal coverage cluster, an over coverage cluster, and a weak coverage cluster.
In this embodiment, as shown in fig. 4, the number K of clusters is initialized to 3, and the center point of each cluster is determined corresponding to the normal coverage cluster, the excessive coverage cluster, and the weak coverage cluster. The center points of these 3 clusters are determined according to a fifth formula:
wherein,is the average over-coverage rate of the cells within the preset range,is the average dropped call rate of the cell in the preset range, P is the self-optimization efficiency coefficient, C1Clusters represent over-coverage clusters, C2Clusters represent normal coverage clusters, C3Clusters represent weakly covering clusters.
After the central point of each cluster is determined, the distances between the cell and the central points of the K clusters are calculated according to the description vectors of the cell and the central points of the clusters, and all the cells in a preset range are divided into the clusters closest to the central points of the clusters.
Specifically, polling the whole network cells and C within the preset range1、C2、C3Distance of (2), cell and cluster CkThe distance of (d) is calculated as follows:
calculating to obtain a cell and C1、C2、C3After the distance of (2), the cell is divided into the cluster closest to the cluster center point. For example, if the cell is associated with C1The distance between the center point is smaller than the cell and C2The distance between the center point and the cell is smaller than that between the cell and C3Distance of center point, then the cell is divided into C1In clusters.
204. And optimizing the antenna feeder downtilt of the cell according to the division result.
The K clusters include a normal coverage cluster, an over coverage cluster, and a weak coverage cluster. The cells partitioned into the normal coverage cluster do not need to be optimized. Cells classified into either an over-coverage cluster or a weak-coverage cluster may be optimized. Optionally, in this embodiment, the number K of clusters includes, but is not limited to, 3, and the value of K may be greater than 3, for example, the over-coverage cluster is further subdivided into a light over-coverage cluster and a heavy over-coverage cluster, and all or part of cells in the heavy over-coverage cluster are selected for optimization.
For a cell to be optimized, the downtilt angle of the antenna feeder of the cell may be adjusted, and the specific adjustment manner in this embodiment is not limited. Illustratively, the cell antenna feeder downtilt angles in the normal coverage cluster, the excessive coverage cluster and the weak coverage cluster are adjusted according to a sixth formula:
wherein, thetat+1For adjusted antenna feed down-tilt angle, thetatFor the antenna feed downtilt before adjustment, e + ω is 1, MnDescription vectors for n cells within a predetermined range, C1Clusters represent over-coverage clusters, C2Clusters represent normal coverage clusters, C3Clusters represent weakly covering clusters.
205. And circularly dividing and optimizing the cells.
If the downtilt of the antenna feeder of the cell in the normal coverage cluster, the excessive coverage cluster or the weak coverage cluster is changed, the cell in the preset range can be divided again. For example, the division is performed periodically, or a certain trigger condition is set, and the division is performed when the condition is satisfied. After each division, optimization can be carried out according to the division result.
In a specific implementation manner, after the adjustment of the downtilt of the cell antenna feeder is completed, whether the central point of at least one cluster in the K clusters is changed is judged, and if yes, the description vectors of the cells in the preset range are re-divided into the K clusters through a K-means algorithm. And then optimizing according to the division result.
And after optimization, judging whether the central point of at least one cluster is changed again, and if so, dividing again. The loop is executed until the center point of each cluster no longer changes.
The method and the device for managing the cell coverage area provided by the embodiment of the invention analyze target data through a means algorithm, and divide description vectors of cells in a preset range into K clusters, wherein the K clusters at least comprise a normal coverage cluster, an excessive coverage cluster and a weak coverage cluster, and are respectively used for indicating the cells with normal coverage, excessive coverage and weak coverage. Before an abnormal event caused by a coverage problem occurs, whether the cell coverage problem exists can be determined through the technical scheme of the application, and the purpose of preventing the abnormal event in advance is achieved.
The embodiment of the invention also provides a device for managing the cell coverage. For performing the cell coverage management method described in the above embodiments.
The management device can be used as an independent computer device to acquire target data from the OSS, process the data and output a division result of the cell and a proposal scheme for optimizing the cell. Further, the computer device may also be used as a controller for the antenna feeder downtilt of the cell, and after the cell division is completed, the antenna feeder downtilt is automatically adjusted according to a preset antenna feeder downtilt control function (for example, a sixth formula).
The management device can be directly integrated in the OSS and connected with the OSS and the base station through the interface circuit, and target data acquired from the OSS sends an instruction to the base station after cell division is completed to instruct the cell to adjust the antenna feeder downtilt angle.
The management device may include a processor and a memory, and program code for executing aspects of the present invention is stored in the memory and controlled to be executed by the processor.
The memory may include volatile memory (e.g., random-access memory (RAM)). The memory may also include a non-volatile memory (e.g., a read-only memory (ROM)), a flash memory (e.g., a flash memory), a hard disk (e.g., a Hard Disk Drive (HDD)), or a solid-state drive (e.g., a SSD). The memory may also comprise a combination of memories of the kind described above.
The processor may be a Central Processing Unit (CPU), or a combination of a CPU and a hardware chip. The hardware chip may be a Network Processor (NP), an application-specific integrated circuit (ASIC), a Programmable Logic Device (PLD), or any combination thereof. The PLD may be a Complex Programmable Logic Device (CPLD), a Field Programmable Gate Array (FPGA), a General Array Logic (GAL), or any combination thereof.
As shown in fig. 5, in a specific embodiment, the management apparatus includes:
a data obtaining unit 501, configured to obtain target data of cells within a preset range, where the target data of one cell includes: the position information of the cell, a common-frequency neighbor list, the normal release times, the abnormal release times and the propagation delay data of the radio access bearer RAB of the cell in the historical time of the preset length, and the switching success times of the cell in the historical time of the preset length and each common-frequency neighbor interval in the preset range;
the data processing unit 502 is configured to determine a reasonable coverage area, an actual coverage area, and a call drop rate of a cell within a preset range according to the target data of the cell acquired by the data acquisition unit 501;
the algorithm executing unit 503 is further configured to divide the description vectors of the cells within the preset range into K clusters through a K-means algorithm;
the description vector of one cell comprises the call drop rate and the coverage ratio of the cell, wherein the coverage ratio is the ratio of the actual coverage range to the reasonable coverage range of the cell; the K clusters include at least a normal coverage cluster, an over coverage cluster, and a weak coverage cluster.
Optionally, the data processing unit 502 is specifically configured to calculate a static coverage radius and a dynamic coverage radius of the cell according to the target data of the cell; and calculating to obtain a reasonable coverage radius of the cell according to the static coverage radius and the dynamic coverage radius of the cell, wherein the reasonable coverage radius of the cell is used for indicating the reasonable coverage range of the cell.
Optionally, the data processing unit 502 is configured to calculate a static coverage radius of the cell according to a first formula, where the first formula is:
wherein d isn1Is the static coverage radius, R, of the cellnqIs the static spacing between the cell n and the qth co-frequency adjacent region, and q is the number of co-frequency adjacent regions of the cell n.
Optionally, the data processing unit 502 is specifically configured to calculate the dynamic coverage radius of the cell according to a second formula, where the second formula is:
wherein d isn2Is the dynamic coverage radius, R, of a cellnqIs the static spacing between the N and the q-th co-frequency adjacent interval, NnqThe successful times of switching between the cell n and the q-th co-frequency adjacent region are shown, and q is the number of the co-frequency adjacent regions of the cell n.
Optionally, the data processing unit 502 is specifically configured to calculate a dynamic coverage radius of the cell according to a third formula, where the third formula is:
dn=(α*dn1+β*dn2)/(α+β);
wherein d isnIs a reasonable coverage radius of the cell, dn1Is the static coverage radius of the cell, dn2For the dynamic coverage radius of a cell, α and β are weighting factors of the static coverage radius and the dynamic coverage radius, respectively, and α + β is 1.
Optionally, the data processing unit 502 is specifically configured to calculate an actual coverage radius of the cell according to a fourth formula, where the actual coverage radius is used to indicate an actual coverage range, and the fourth formula is as follows:
wherein r isnIs the actual coverage radius of the cell, NiIs propagation delay data PD [ i ]]CellRange is the maximum coverage distance configured for the system.
Optionally, the algorithm executing unit 503 is configured to initialize the number K of the clusters to 3, and determine a center point of each cluster corresponding to the normal coverage cluster, the excessive coverage cluster, and the weak coverage cluster; and calculating the distances between the cell and the center points of the K clusters according to the description vectors of the cell and the center points of the clusters, and dividing all the cells in a preset range into the clusters closest to the center points of the clusters.
Optionally, the algorithm executing unit 503 is specifically configured to determine a central point of each of the K clusters according to a fifth formula, where K is 3, and the fifth formula is:
wherein,is the average over-coverage rate of the cells within the preset range,is the average dropped call rate of the cell in the preset range, P is the self-optimization efficiency coefficient, C1Clusters represent over-coverage clusters, C2Clusters represent normal coverage clusters, C3Clusters represent weakly covering clusters.
Optionally, if the downtilt of the cell antenna feeder in the normal coverage cluster, the excessive coverage cluster or the weak coverage cluster changes, the algorithm execution unit 503 is further configured to determine whether the central point of at least one cluster in the K clusters changes after the adjustment of the downtilt of the cell antenna feeder is completed; and if so, re-dividing the description vectors of the cells in the preset range into K clusters through a K-means algorithm.
Optionally, the management apparatus further includes an optimization control unit 504, configured to adjust a cell antenna feeder downtilt angle in the normal coverage cluster, the excessive coverage cluster, and the weak coverage cluster according to a sixth formula, where the sixth formula is:
wherein, thetat+1To adjust forRear antenna feeder down tilt angle thetatFor the antenna feed downtilt before adjustment, e + ω is 1, MnDescription vectors for n cells within a predetermined range, C1Clusters represent over-coverage clusters, C2Clusters represent normal coverage clusters, C3Clusters represent weakly covering clusters.
The method and the device for managing the cell coverage area provided by the embodiment of the invention analyze target data through a means algorithm, and divide description vectors of cells in a preset range into K clusters, wherein the K clusters at least comprise a normal coverage cluster, an excessive coverage cluster and a weak coverage cluster, and are respectively used for indicating the cells with normal coverage, excessive coverage and weak coverage.
For a cell, the target data comprises two types of information, one type is the working parameter data of the cell, and specifically comprises the position information of the cell and a same-frequency neighbor list; the other type is historical data about the working state of the cell, and specifically includes RAB normal release times, RAB abnormal release times and propagation delay data of the cell in the historical time of the preset length, and the handover success times of each same-frequency adjacent interval of the cell in the historical time of the preset length and the preset range. For an operator, target data is known and changed in real time, description vectors of cells are divided into different clusters by analyzing the data, the normally covered clusters are used for indicating the cells covered normally, and the over-covered clusters and the weak covered clusters are used for indicating the cells with problems. Before an abnormal event caused by a coverage problem occurs, whether the cell coverage problem exists can be determined through the technical scheme of the application.
In the prior art, a coverage problem is found and corresponding measures are taken after an abnormal event occurs, and the method is a solution mode of 'post remedy'. The technical scheme provided by the embodiment of the application can find the coverage problem before the abnormal event occurs so as to guide the cell optimization work, and is a solution mode of 'prevention in advance'.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and the changes or substitutions should be covered within 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 (18)

1. A method for managing cell coverage, comprising:
acquiring target data of cells within a preset range, wherein the target data of one cell comprises the following steps: the position information of the cell, a common-frequency neighbor cell list, the normal release times, the abnormal release times and the propagation delay data of the radio access bearer RAB of the cell in the historical time of the preset length, and the switching success times of the cell in the historical time of the preset length and each common-frequency neighbor interval in the preset range;
determining a reasonable coverage area, an actual coverage area and a call drop rate of the cell in the preset range according to target data of the cell;
dividing the description vectors of the cells in the preset range into K clusters through a K-means algorithm;
the description vector of one cell comprises the call drop rate and the coverage ratio of the cell, wherein the coverage ratio is the ratio of the actual coverage range to the reasonable coverage range of the cell; the K clusters at least comprise normal coverage clusters, excessive coverage clusters and weak coverage clusters.
2. The method for managing cell coverage according to claim 1, wherein determining the reasonable coverage of the cell within the preset range according to the target data of the cell comprises:
calculating to obtain the static coverage radius and the dynamic coverage radius of the cell according to the target data of the cell;
and calculating to obtain a reasonable coverage radius of the cell according to the static coverage radius and the dynamic coverage radius of the cell, wherein the reasonable coverage radius of the cell is used for indicating the reasonable coverage range of the cell.
3. The method for managing cell coverage according to claim 2, wherein calculating the static coverage radius of the cell according to the target data of the cell comprises:
calculating to obtain the static coverage radius of the cell according to a first formula, wherein the first formula is as follows:
wherein d isn1Is the static coverage radius, R, of cell nnqIs the static spacing between the cell n and the qth co-frequency adjacent region, and q is the number of co-frequency adjacent regions of the cell n.
4. The method for managing cell coverage according to claim 2, wherein calculating the dynamic coverage radius of the cell according to the target data of the cell comprises:
and calculating to obtain the dynamic coverage radius of the cell according to a second formula, wherein the second formula is as follows:
wherein d isn2Is the dynamic coverage radius, R, of cell nnqIs the static spacing between the N and the q-th co-frequency adjacent interval, NnqThe successful times of switching between the cell n and the q-th co-frequency adjacent region are shown, and q is the number of the co-frequency adjacent regions of the cell n.
5. The method for managing cell coverage according to claim 2, wherein the calculating a reasonable coverage radius of the cell according to the static coverage radius and the dynamic coverage radius of the cell comprises:
and calculating to obtain the dynamic coverage radius of the cell according to a third formula, wherein the third formula is as follows:
dn=(α*dn1+β*dn2)/(α+β);
wherein d isnIs a reasonable coverage radius of the cell, dn1Is the static coverage radius of the cell, dn2Is the dynamic coverage radius of a cell, and alpha and beta are respectively staticCoverage radius and dynamic coverage radius, and α + β ═ 1.
6. The method for managing cell coverage according to claim 1, wherein determining the actual coverage of the cell within the preset range according to the target data of the cell comprises:
calculating to obtain an actual coverage radius of the cell according to a fourth formula, wherein the actual coverage radius is used for indicating an actual coverage range, and the fourth formula is as follows:
wherein r isnIs the actual coverage radius of the cell, NiIs propagation delay data PD [ i ]]CellRange is the maximum coverage distance configured for the system.
7. The method for managing cell coverage according to claim 1, wherein dividing the description vector of the cell within the preset range into K clusters by a K-means algorithm comprises:
initializing the number K of clusters to 3, and determining the central point of each cluster corresponding to a normal coverage cluster, an excessive coverage cluster and a weak coverage cluster;
and calculating the distances between the cell and the center points of the K clusters according to the description vectors of the cell and the center points of the clusters, and dividing all the cells in the preset range into the clusters closest to the center points of the clusters.
8. The method for managing cell coverage according to claim 7, wherein initializing the number of clusters K to 3 and determining the center point of each cluster comprises:
determining a center point of each of the K clusters according to a fifth formula, where K is 3, and the fifth formula is:
wherein,the average over-coverage rate of the cells in the preset range is,is the average dropped call rate of the cell in the preset range, P is a self-optimization efficiency coefficient, C1Clusters represent over-coverage clusters, C2Clusters represent normal coverage clusters, C3Clusters represent weakly covering clusters.
9. The method for managing cell coverage according to any one of claims 1 to 8, wherein if a cell antenna feed downtilt angle in a normal coverage cluster, an excessive coverage cluster, or a weak coverage cluster changes, the dividing the description vector of the cell in the preset range into K clusters by a K-means algorithm further includes:
after the adjustment of the downtilt of the cell antenna feeder is finished, judging whether the central point of at least one cluster in the K clusters changes;
and if so, re-dividing the description vectors of the cells in the preset range into the K clusters through a K-means algorithm.
10. An apparatus for managing a cell coverage area, comprising:
a data obtaining unit, configured to obtain target data of cells within a preset range, where the target data of one cell includes: the position information of the cell, a common-frequency neighbor cell list, the normal release times, the abnormal release times and the propagation delay data of the radio access bearer RAB of the cell in the historical time of the preset length, and the switching success times of the cell in the historical time of the preset length and each common-frequency neighbor interval in the preset range;
the data processing unit is used for determining the reasonable coverage area, the actual coverage area and the call drop rate of the cell in the preset range according to the target data of the cell acquired by the data acquisition unit;
the algorithm execution unit is also used for dividing the description vectors of the cells in the preset range into K clusters through a K-means algorithm;
the description vector of one cell comprises the call drop rate and the coverage ratio of the cell, wherein the coverage ratio is the ratio of the actual coverage range to the reasonable coverage range of the cell; the K clusters at least comprise normal coverage clusters, excessive coverage clusters and weak coverage clusters.
11. The apparatus for managing cell coverage according to claim 10,
the data processing unit is specifically used for calculating the static coverage radius and the dynamic coverage radius of the cell according to the target data of the cell; and calculating to obtain a reasonable coverage radius of the cell according to the static coverage radius and the dynamic coverage radius of the cell, wherein the reasonable coverage radius of the cell is used for indicating the reasonable coverage range of the cell.
12. The apparatus for managing cell coverage of claim 11,
the data processing unit is configured to calculate a static coverage radius of the cell according to a first formula, where the first formula is:
wherein d isn1Is the static coverage radius, R, of the cellnqIs the static spacing between the cell n and the qth co-frequency adjacent region, and q is the number of co-frequency adjacent regions of the cell n.
13. The apparatus for managing cell coverage of claim 11,
the data processing unit is specifically configured to calculate a dynamic coverage radius of the cell according to a second formula, where the second formula is:
wherein d isn2Is the dynamic coverage radius, R, of a cellnqIs the static spacing between the N and the q-th co-frequency adjacent interval, NnqThe successful times of switching between the cell n and the q-th co-frequency adjacent region are shown, and q is the number of the co-frequency adjacent regions of the cell n.
14. The apparatus for managing cell coverage of claim 11,
the data processing unit is specifically configured to calculate a dynamic coverage radius of the cell according to a third formula, where the third formula is:
dn=(α*dn1+β*dn2)/(α+β);
wherein d isnIs a reasonable coverage radius of the cell, dn1Is the static coverage radius of the cell, dn2For the dynamic coverage radius of a cell, α and β are weighting factors of the static coverage radius and the dynamic coverage radius, respectively, and α + β is 1.
15. The apparatus for managing cell coverage according to claim 10,
the data processing unit is specifically configured to calculate an actual coverage radius of the cell according to a fourth formula, where the actual coverage radius is used to indicate an actual coverage range, and the fourth formula is:
wherein r isnIs the actual coverage radius of the cell, NiIs propagation delay data PD [ i ]]CellRange is the maximum coverage distance configured for the system.
16. The apparatus for managing cell coverage according to claim 10,
the algorithm execution unit is used for initializing the number K of the clusters to 3, respectively corresponding to the normal coverage cluster, the excessive coverage cluster and the weak coverage cluster, and determining the central point of each cluster; and calculating the distances between the cell and the center points of the K clusters according to the description vectors of the cell and the center points of the clusters, and dividing all the cells in the preset range into the clusters closest to the center points of the clusters.
17. The apparatus for managing cell coverage of claim 16,
the algorithm execution unit is specifically configured to determine a center point of each of the K clusters according to a fifth formula, where K is 3, and the fifth formula is:
wherein,the average over-coverage rate of the cells in the preset range is,is the average dropped call rate of the cell in the preset range, P is a self-optimization efficiency coefficient, C1Clusters represent over-coverage clusters, C2Clusters represent normal coverage clusters, C3Clusters represent weakly covering clusters.
18. The apparatus for managing cell coverage according to any of claims 10-17, wherein if the cell antenna feed downtilt in the normal coverage cluster, the excessive coverage cluster or the weak coverage cluster changes,
the algorithm execution unit is further configured to determine whether a central point of at least one cluster in the K clusters changes after adjusting the downtilt of the cell antenna feeder is completed; and if so, re-dividing the description vectors of the cells in the preset range into the K clusters through a K-means algorithm.
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