CN108966238B - Network capacity expansion method and device - Google Patents
Network capacity expansion method and device Download PDFInfo
- Publication number
- CN108966238B CN108966238B CN201710354128.1A CN201710354128A CN108966238B CN 108966238 B CN108966238 B CN 108966238B CN 201710354128 A CN201710354128 A CN 201710354128A CN 108966238 B CN108966238 B CN 108966238B
- Authority
- CN
- China
- Prior art keywords
- cell
- capacity
- designated area
- cells
- coefficient
- 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
Links
Images
Classifications
-
- 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
- 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
- H04W16/24—Cell structures
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Mobile Radio Communication Systems (AREA)
- Data Exchanges In Wide-Area Networks (AREA)
Abstract
The embodiment of the application provides a network capacity expansion method and a device, wherein the method comprises the following steps: acquiring the average required capacity of each user in a designated area and the bearable capacity of each corresponding cell; calculating the number of users which can be borne by each cell according to the average required capacity and the bearable capacity of each cell; determining the number of cells required for meeting the total required capacity of the 4G online user number according to the 4G online user number in the designated area and the number of users which can be borne by each cell; and determining whether to expand each cell corresponding to the specified area or not according to the required cell number and the total number of the cells corresponding to the specified area. The invention solves the problems that the prior scheme lacks VoLTE prediction analysis, lacks research on various service perception rates and lacks analysis on the cell-level service occupation ratio.
Description
Technical Field
The present application relates to the field of communications technologies, and in particular, to a network capacity expansion method and a network capacity expansion device.
Background
With the maturity of the 4G network, the number of 4G users and data flow are increased explosively, which brings huge impact to network capacity, and network capacity expansion is urgent according to user perception.
At present, the industry does not have a unified method for 4G network expansion, operators and equipment manufacturers respectively provide own expansion judgment standards, and the expansion standard thresholds are different.
Generally, the capacity expansion standard of each manufacturer for a 4G network is mainly to evaluate dimensions such as an effective RRC (Radio Resource Control) connection number, an uplink and downlink PRB (Physical Resource Block) utilization rate, and an uplink and downlink traffic of a cell to determine whether a capacity expansion threshold is reached.
The main stream capacity expansion standard is generally determined according to the cell classification of large, medium and small packets, and when the cell reaches a threshold during busy hour, the carrier frequency capacity expansion is implemented. The cell classification standard and the capacity expansion threshold are shown as the following table:
when the cell meets any one of the following standards, the cell is defined as a cell needing capacity expansion:
1) "the number of valid RRC users reaches a threshold" and "the uplink utilization reaches a threshold" and "the uplink traffic reaches a threshold";
2) the "number of valid RRC users" reaches the threshold, "the" downlink utilization rate reaches the threshold (PDSCH or PDCCH), "and the" downlink traffic reaches the threshold.
Therefore, the capacity expansion scheme generally adopted in the prior art is lack of VoLTE prediction analysis, various service perception rate researches and cell-level service proportion analysis, and cell scenes are divided according to service types; although different thresholds can be set according to different scenes, the thresholds of various scenes are still fixed, the rolling effect is not strong, and a capacity prediction and early warning mechanism is lacked.
Disclosure of Invention
In view of the above, embodiments of the present application are proposed to provide a network capacity expansion method and a corresponding network capacity expansion apparatus, which overcome or at least partially solve the above problems.
In order to solve the above problem, an embodiment of the present application discloses a network capacity expansion method, including:
acquiring the average required capacity of each user in a designated area and the bearable capacity of each corresponding cell;
calculating the number of users which can be borne by each cell according to the average required capacity and the bearable capacity of each cell;
determining the number of cells required by the total required capacity for meeting the 4G online user number according to the 4G online user number in the designated area and the number of users which can be borne by each cell;
and determining whether to expand each cell corresponding to the designated area or not according to the required cell number and the total number of the cells corresponding to the designated area.
Preferably, the obtaining of the average required capacity of each user of the designated area comprises:
and acquiring the average required capacity of each user in the specified area according to the data service model.
Preferably, the method further comprises the following steps:
and extracting the total number of users in the designated area, the session duration, the session times, the uplink and downlink flow and the number of users of each service type in the large platform data to obtain a data service model.
Preferably, the data traffic model includes data traffic and voice traffic.
Preferably, the acquiring the bearable capacity of each cell corresponding to the designated area includes:
calculating the bearable capacity of each cell according to the configuration parameters of each cell;
the configuration parameter includes at least one of bandwidth, frequency band, subframe configuration, power, cell load, and signal-to-interference-plus-noise ratio.
Preferably, the step of determining whether to expand the capacity of each cell corresponding to the designated area according to the required number of the cells and the total number of the cells corresponding to the designated area includes:
and when the required number of the cells reaches the threshold value of the total number of the cells corresponding to the designated area, expanding the capacity of each cell corresponding to the designated area.
Preferably, the method further comprises the following steps:
collecting voice total traffic and data total traffic of the 2G network in a specified time period closest to the current time in a specified area, and acquiring a corresponding 2G network switching coefficient;
acquiring the average number of RRC links, the maximum number of RRC links, downlink flow and uplink flow of the 4G network in the specified time period in a specified area, and acquiring a corresponding increasing coefficient of the average number of RRC links, a corresponding increasing coefficient of the maximum number of RRC links and an increasing coefficient of the uplink and downlink flow;
and acquiring a corresponding 4G pre-expansion growth coefficient according to the RRC link average number growth coefficient, the RRC link maximum number growth coefficient, the uplink and downlink flow growth coefficient and the 2G network switching coefficient, and judging the number of 4G users in the next time period in the specified area, wherein the time period is the same as the specified time period.
Preferably, when determining that the cell corresponding to the designated area needs capacity expansion, sending out a capacity expansion early warning; wherein, the dilatation early warning includes: emergency capacity expansion early warning, important capacity expansion early warning and common capacity expansion early warning.
On the other hand, the embodiment of the present invention further discloses a network capacity expansion device, including:
the acquisition module is used for acquiring the average required capacity of each user in the designated area and the bearable capacity of each corresponding cell;
the bearing user number calculation module is used for calculating the number of users which can be borne by each cell according to the average required capacity and the bearable capacity of each cell;
the cell number calculation module is used for determining the number of cells required by the total demand capacity meeting the 4G online user number according to the 4G online user number in the designated area and the user number capable of being borne by each cell;
and the capacity expansion determining module is used for determining whether to expand the capacity of each cell corresponding to the specified area according to the required cell number and the total number of the cells corresponding to the specified area.
Preferably, the acquisition module comprises:
and the average required capacity obtaining submodule is used for obtaining the average required capacity of each user in the specified area according to the data service model.
Preferably, the method further comprises the following steps:
and the data service model acquisition module is used for extracting the total number of users in the specified area, the session duration, the session times, the uplink and downlink flow and the number of users of each service type in the large platform data to obtain a data service model.
Preferably, the data traffic model includes data traffic and voice traffic.
Preferably, the acquisition module comprises:
the bearable capacity calculation submodule is used for calculating the bearable capacity of each cell according to the configuration parameters of each cell;
the configuration parameter includes at least one of bandwidth, frequency band, subframe configuration, power, cell load, and signal-to-interference-plus-noise ratio.
Preferably, the step of determining whether to expand the capacity of each cell corresponding to the designated area according to the required number of the cells and the total number of the cells corresponding to the designated area includes:
and when the required number of the cells reaches the threshold value of the total number of the cells corresponding to the specified area, expanding the capacity of each cell corresponding to the specified area.
Preferably, the method further comprises the following steps:
the 2G network switching coefficient acquisition module is used for acquiring the total voice traffic and the total data traffic of the 2G network in a specified time period in a specified area and acquiring a corresponding 2G network switching coefficient;
the coefficient acquisition module is used for acquiring the RRC link average number, the RRC link maximum number, the downlink flow and the uplink flow of the 4G network in the specified time period in a specified area and acquiring a corresponding RRC link average number increase coefficient, a corresponding RRC link maximum number increase coefficient and a corresponding uplink and downlink flow increase coefficient;
and the capacity expansion determining module is used for acquiring a corresponding 4G pre-capacity expansion increasing coefficient according to the RRC link average number increasing coefficient, the RRC link maximum number increasing coefficient, the uplink and downlink flow increasing coefficient and the 2G network switching coefficient, and judging the number of 4G users in the next time period in the specified area, wherein the time period is the same as the specified time period.
Preferably, when determining that the cell corresponding to the designated area needs capacity expansion, sending out a capacity expansion early warning; wherein, the dilatation early warning includes: emergency capacity expansion early warning, important capacity expansion early warning and common capacity expansion early warning.
Compared with the prior art, the embodiment of the application has the following advantages:
firstly, the embodiment of the invention calculates the number of users which can be borne by each cell according to the obtained average demand capacity of each user in the specified area and the bearable capacity of each corresponding cell, determines the number of cells required by the total demand capacity which meets the 4G online user number according to the 4G online user number in the specified area and the number of users which can be borne by each cell, and determines whether to expand the capacity of each cell corresponding to the specified area according to the required cell number and the total number of the cells corresponding to the specified area. Compared with the prior art, the commonly adopted capacity expansion scheme lacks VoLTE prediction analysis, lacks research on various service perception rates, lacks analysis on cell-level service proportion, and divides cell scenes according to service types; although different thresholds can be set according to different scenes, the thresholds of various scenes are still fixed and the rolling effect is not strong. According to the embodiment of the invention, DPI data can be dynamically acquired according to a big data platform, and the business model analysis of user perception is carried out to obtain the uplink and downlink perception rate of a single user; and calculating the evaluation standard of the single cell based on the user perception bearing capacity by combining the subframe and transmission bandwidth configuration of the single cell according to the analysis result of the data service model.
Secondly, the embodiment of the invention defines the cell attributes (such as shopping malls, universities, streets and the like) according to the wireless environment and the service object of the cell, and establishes the judgment standard of the perception bearing capacity of the cell users according to the classification of the cell attributes
Thirdly, according to the total voice traffic, the total data traffic, the number of users of the 4G network, the flow and the 4G network market operation mechanism of the 2G network, the embodiment of the invention analyzes the trend of the number of users, calculates the growth trend of the 4G users, predicts the growth condition of the number of users in a cell, and establishes a capacity expansion early warning mechanism according to the times of reaching the capacity expansion threshold of the cell.
Drawings
FIG. 1 is a flowchart illustrating steps of a method for expanding a network capacity according to an embodiment of the present invention;
fig. 2 is a block diagram of a network capacity expansion apparatus according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a packet size of a VOLTE service high definition voice transient according to an embodiment of the present invention.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present application more comprehensible, the present application is described in further detail with reference to the accompanying drawings and the detailed description.
In order to make those skilled in the art further understand the embodiments of the present invention, the following describes the embodiments of the present invention with reference to a specific flow of network capacity expansion.
Example one
Referring to fig. 1, a flowchart illustrating steps of a network capacity expansion method according to an embodiment of the present invention is shown, which may specifically include:
step S101, obtaining the average required capacity of each user in the designated area and the bearable capacity of each corresponding cell.
In the embodiment of the invention, the designated area can be a shopping mall, a college and a street
Preferably, the method further comprises the following steps: and extracting the total number of users in the specified area, the session duration, the session times, the uplink and downlink flow and the number of users of each service type in the large platform data to obtain the data service model.
In the embodiment of the present invention, through the big data platform, according to the requirements of different areas, different scenes, different periods, etc., corresponding data may be extracted to perform analysis on the service model of the area or the scene, for example, data such as the total number of users in a period of time of a certain area or a certain scene, the session duration, the session times, the uplink and downlink flows, and the number of users of each service type may be extracted to perform analysis on the user service model, as shown in table 1 below.
Table 1:
as shown in table 1 above, data information such as the number of users, uplink traffic, downlink traffic, service duration, session times, and the like corresponding to different service types can be extracted from a large data platform configured for an existing network corresponding to a certain area, for example, the number of users corresponding to the instant messaging service in table 1 above: 298229, upstream flow: 46425.43MB, downstream traffic: 347723.5MB, service duration: 109874741.4S, number of sessions: 60893784 times; or acquiring the number of users with the service type corresponding to the game: 108644, upstream flow: 3511.325MB, downstream traffic: 63158.66MB, service duration: 2092667.859S, number of sessions: 4656622 times, etc.
The user activation ratio can be obtained by the number of users of each service type in the area/the total number of users in the area, the service activation ratio can be obtained by the service duration/the total service duration of each service type, the activation ratio of the corresponding service type of the user can be obtained by normalizing the service activation ratio and the user activation ratio, and the typical bearing rate of each service type can be obtained by the uplink and downlink flow/the service duration, as shown in the following table 2:
table 2:
according to the data service model in table 2, the single-user uplink (downlink) rate is calculated.
For example, analysis of DPI data by the above method can result in single-user uplink and downlink rate requirements of 36kbps and 550kbps, respectively. Due to different habits of users in different areas or scenes and the difference of networks in different areas or scenes, the analysis results are different, and the expansion guidance should be performed by adopting the analysis data aiming at the areas or scenes.
Preferably, the data traffic model may include data traffic and voice traffic.
Voice traffic (VoLTE) exists in three states: transients, active periods, quiet periods. By adopting AMR coding, the VoLTE service frame composition model in the following figure can know that a voice frame can be transmitted only after a RTP/UDP/IP/PDCP/RLC/MAC layer packet header is added, an AMR mechanism allows the packet header of the RTP/UDP/IP layer to be compressed, called ROHC, the overhead of the RTP/UDP/IP header of about 40Bytes is compressed into 4Bytes, and the capacity of a channel user is improved.
Referring to fig. 3, a schematic diagram of a size of a data packet of a VOLTE service in a high-definition voice transient period provided by an embodiment of the present invention is shown, for the VOLTE service, a size of the data packet sent in the high-definition voice transient period is the largest, the size of the data packet in the MAC layer is about 850 bits, a single-user rate is converted by a 20ms period to be about 42.5kbps, a certain bandwidth redundancy is considered, and meanwhile, a GBR guaranteed value of the VOLTE service in reference to a current fuzhou core network is taken as 48 kbps.
Considering that the existing network actually carries data service and VOLTE service at the same time, the VOLTE service priority is higher than the data service priority, the comprehensive service model needs to perform weighted average on the two service models, and the rate requirement of the comprehensive service model is calculated by weighted conversion on the VOLTE service (for example, 20%) and the data service (for example, 80%).
The aggregate traffic rate.
Taking the above model as an example, the calculation result is: uplink traffic rate 48kbps 20% +36kbps 80% ═ 38.4 kbps; downlink traffic rate 48kbps 20% +550kbps 80% + 450kbps
In the embodiment of the present invention, the required capacity of each user in the designated area may be counted, that is, the required capacity of each user for each service type is obtained, and further, the average required capacity of each user is obtained, and correspondingly, the capacity that can be carried by each cell corresponding to the designated area may also be obtained.
Preferably, the acquiring the bearable capacity of each cell corresponding to the designated area includes:
sub-step S1012: calculating the bearable capacity of each cell according to the configuration parameters of each cell;
wherein the configuration parameter includes at least one of bandwidth, frequency band, subframe configuration, power, cell load, and signal to interference plus noise ratio.
In the embodiment of the present invention, the capacity carrying capability of each cell is related to the parameter configuration of each cell, such as bandwidth, frequency band, subframe configuration, power, cell load, SINR (Signal to Interference plus Noise Ratio), etc.,
taking 20M bandwidth and subframe configuration 3D1U as an example, the single cell capacity is about uplink 5M and downlink 35M as an example:
the number of VOLTE users that a single cell can carry is 5Mbps 1024/48kbps 106.
The number of data services that can be carried by a single cell is Min (5Mbps 1024/36kbps, 35Mbps 1024/550 kbps)/60%: 108.
The single cell can support the number of the integrated service users ═ Min (5Mbps 1024/uplink service rate, 35Mbps 1024/downlink service rate)/60%.
Taking the model in table 2 as an example, the calculation results are: the number of users of the integrated service that can be carried by a single cell is Min (5Mbps 1024/38kbps, 35Mbps 1024/450 kbps)/60%: 132.
And step S102, calculating the number of users which can be borne by each cell according to the average required capacity and the bearable capacity of each cell.
In the embodiment of the invention, the number of users which can be borne by each cell corresponding to the designated area is further calculated according to the average required capacity of each user in the designated area and the bearable capacity of each corresponding cell.
And step S103, determining the number of the cells required by the total required capacity meeting the 4G online user number according to the 4G online user number in the designated area and the user number capable of being borne by each cell.
In the embodiment of the present invention, the number of cells required to satisfy the total capacity of the 4G online users in the designated area, that is, the minimum number of cells required to satisfy the total capacity of the 4G online users in the designated area, is determined according to the total number of users online by the 4G in the designated area and the number of users that can be carried by each cell corresponding to the designated area.
And step S104, determining whether to expand each cell corresponding to the specified area according to the required cell number and the total number of the cells corresponding to the specified area.
And determining whether to expand the designated area or not according to the minimum number of the cells of the designated area meeting the 4G online user number and the total number of the cells corresponding to the designated area.
Preferably, the step S104 may include:
substep S1042: and when the required number of the cells reaches a threshold value of the total number of the cells corresponding to the specified area, expanding the capacity of each cell corresponding to the specified area.
In the embodiment of the present invention, the threshold value refers to the minimum number of cells corresponding to the area capable of carrying the user capacity,
in practical applications, the threshold value may be set according to actual needs, for example, 2, 3, 5, and the like, which is not limited in this embodiment of the present invention.
And when the number of the cells meeting the requirement of the number of the users 4G on-line users in the specified area reaches the threshold value corresponding to the specified area, expanding the capacity of each cell corresponding to the specified area.
Preferably, the method may further comprise:
step S105: collecting the total voice traffic and the total data traffic of the 2G network in a specified time period closest to the current time in the specified area, and acquiring a corresponding 2G network switching coefficient;
step S106: acquiring the average number of RRC links, the maximum number of RRC links, downlink traffic and uplink traffic of the 4G network in the specified time period in the specified area, and acquiring a corresponding increase coefficient of the average number of RRC links, an increase coefficient of the maximum number of RRC links and an increase coefficient of the uplink traffic and the downlink traffic;
step S107: and acquiring a corresponding 4G pre-expansion growth coefficient according to the RRC link average number growth coefficient, the RRC link maximum number growth coefficient, the uplink and downlink flow growth coefficient and the 2G network switching coefficient, and judging the number of 4G users in the next time period in the specified area, wherein the time period is the same as the specified time period.
In the embodiment of the invention, the voice total traffic and the data total traffic of the 2G network of all cells in the area needing capacity expansion, the RRC link average number and the RRC link maximum number of the 4G network, the downlink traffic and the uplink traffic are collected to carry out user number trend analysis.
And analyzing the 2G user variation trend according to the total voice traffic and the total data traffic collected from the 2G network, and further acquiring the 4G user number trend analysis in the designated area.
Analyzing the average number of RRC links, the maximum number of RRC links, the downlink flow and the increase amplitude of the uplink flow in the month above:
the 4G pre-expansion increase coefficient is (RRC link average increase coefficient, RRC link maximum increase coefficient, uplink (downlink) traffic increase coefficient) +2G user network switching coefficient.
In the embodiment of the present invention, according to the analysis of the user number trend, it may be predicted that the number of users in the 4G network in the specified area after a specified time period (e.g., one month) is reached, the average number of RRC links at the cell level is collected and multiplied by the pre-expansion growth coefficient, and the cell to be expanded is analyzed, that is:
namely:
the pre-expansion 4G user quantity is equal to the RRC connection average number 4G pre-expansion increase coefficient.
The pre-expansion VOLTE user number is equal to RRC connection average number 4G pre-expansion increase coefficient is equal to VOLTE user ratio.
Preferably, when it is determined that the cell corresponding to the designated area needs capacity expansion, a capacity expansion early warning is sent out; wherein, the dilatation early warning includes: emergency capacity expansion early warning, important capacity expansion early warning and common capacity expansion early warning.
In the embodiment of the present invention, the emergency capacity expansion warning may be: when the same cell has 10 expansion in one month and the pre-expansion 4G user number is greater than the number of the comprehensive service users which can be borne by a single cell; the important capacity expansion early warning can be as follows: when the same cell has 20 expansion in one month and the pre-expansion 4G user number is greater than the number of the comprehensive service users which can be borne by a single cell; the ordinary dilatation early warning can be as follows: and the same cell has 30 expansion in one month, and the pre-expansion 4G user number is larger than the number of the comprehensive service users which can be borne by a single cell.
Firstly, the embodiment of the invention calculates the number of users which can be borne by each cell according to the obtained average demand capacity of each user in the specified area and the bearable capacity of each corresponding cell, determines the number of cells required by the total demand capacity which meets the 4G online user number according to the 4G online user number in the specified area and the number of users which can be borne by each cell, and determines whether to expand the capacity of each cell corresponding to the specified area according to the required cell number and the total number of the cells corresponding to the specified area. Compared with the prior art, the commonly adopted capacity expansion scheme lacks VoLTE prediction analysis, lacks research on various service perception rates, lacks analysis on cell-level service proportion, and divides cell scenes according to service types; although different thresholds can be set according to different scenes, the thresholds of various scenes are still fixed and the rolling effect is not strong. According to the embodiment of the invention, DPI data can be dynamically acquired according to a big data platform, and the business model analysis of user perception is carried out to obtain the uplink and downlink perception rate of a single user; and calculating the evaluation standard of the single cell based on the user perception bearing capacity by combining the subframe and transmission bandwidth configuration of the single cell according to the analysis result of the data service model.
Secondly, the embodiment of the invention defines the cell attributes (such as shopping malls, universities, streets and the like) according to the wireless environment and the service object of the cell, and establishes the judgment standard of the perception bearing capacity of the cell users according to the classification of the cell attributes
Thirdly, according to the total voice traffic, the total data traffic, the number of users of the 4G network, the flow and the 4G network market operation mechanism of the 2G network, the embodiment of the invention analyzes the trend of the number of users, calculates the growth trend of the 4G users, predicts the growth condition of the number of users in a cell, and establishes a capacity expansion early warning mechanism according to the times of reaching the capacity expansion threshold of the cell.
Example two
Referring to fig. 2, a block diagram of a structure of a network capacity expansion apparatus according to an embodiment of the present invention is shown, which may specifically include the following modules:
an obtaining module 201, configured to obtain an average required capacity of each user in a specified area and a bearable capacity of each corresponding cell;
preferably, the obtaining module 201 may include:
and the average required capacity obtaining submodule is used for obtaining the average required capacity of each user in the specified area according to the data service model.
Preferably, the method further comprises the following steps:
and the data service model acquisition module is used for extracting the total number of users in the specified area, the session duration, the session times, the uplink and downlink flow and the number of users of each service type in the large platform data to obtain the data service model.
Preferably, the data traffic model includes data traffic and voice traffic.
Preferably, the obtaining module 201 may include:
the bearable capacity calculation submodule is used for calculating the bearable capacity of each cell according to the configuration parameters of each cell;
wherein the configuration parameter includes at least one of bandwidth, frequency band, subframe configuration, power, cell load, and signal to interference plus noise ratio.
Preferably, the step of determining whether to expand the capacity of each cell corresponding to the designated area according to the required number of cells and the total number of cells corresponding to the designated area includes:
and when the required number of the cells reaches a threshold value of the total number of the cells corresponding to the specified area, expanding the capacity of each cell corresponding to the specified area.
A carrying user number calculating module 202, configured to calculate, according to the average required capacity and the bearable capacity of each cell, a number of users that can be carried by each cell;
the cell number calculation module 203 is configured to determine the number of cells required for meeting the total required capacity of the number of 4G online users according to the number of 4G online users in the designated area and the number of users that can be borne by each cell;
an expansion determining module 204, configured to determine whether to expand the cells corresponding to the designated area according to the required number of the cells and the total number of the cells corresponding to the designated area.
Preferably, the method further comprises the following steps:
the 2G network switching coefficient acquisition module is used for acquiring the total voice traffic and the total data traffic of the 2G network in a specified time period in the specified area and acquiring a corresponding 2G network switching coefficient;
the coefficient acquisition module is used for acquiring the RRC link average number, the RRC link maximum number, the downlink flow and the uplink flow of the 4G network in the specified time period in the specified area and acquiring the corresponding RRC link average number growth coefficient, the RRC link maximum number growth coefficient and the uplink and downlink flow growth coefficient;
and the capacity expansion determining module is used for acquiring a corresponding 4G pre-capacity expansion increasing coefficient according to the RRC link average number increasing coefficient, the RRC link maximum number increasing coefficient, the uplink and downlink flow increasing coefficient and the 2G network switching coefficient, and judging the number of 4G users in the next time period in the specified area, wherein the time period is the same as the specified time period.
Preferably, when it is determined that the cell corresponding to the designated area needs capacity expansion, a capacity expansion early warning is sent out; wherein, the dilatation early warning includes: emergency capacity expansion early warning, important capacity expansion early warning and common capacity expansion early warning.
For the device embodiment, since it is basically similar to the method embodiment, the description is simple, and for the relevant points, refer to the partial description of the method embodiment.
The embodiments in the present specification are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
As will be appreciated by one of skill in the art, embodiments of the present application may be provided as a method, apparatus, or computer program product. Accordingly, embodiments of the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
Embodiments of the present application are described with reference to flowchart illustrations and/or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing terminal to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing terminal to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing terminal to cause a series of operational steps to be performed on the computer or other programmable terminal to produce a computer implemented process such that the instructions which execute on the computer or other programmable terminal provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present application have been described, additional variations and modifications of these embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including the preferred embodiment and all such alterations and modifications as fall within the true scope of the embodiments of the application.
Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or terminal. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or terminal that comprises the element.
The above detailed description is given to a network capacity expansion method and a network capacity expansion device provided by the present application, and a specific example is applied in the present application to explain the principle and the implementation of the present application, and the description of the above embodiment is only used to help understand the method and the core idea of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.
Claims (10)
1. A method for expanding a network, comprising:
extracting the total number of users in a designated area, the session duration, the session times, the uplink and downlink flow and the number of users of each service type in the large platform data to obtain a data service model;
acquiring the average required capacity of each user in the specified area and the bearable capacity of each corresponding cell according to the data service model;
calculating the number of users which can be borne by each cell according to the average required capacity and the bearable capacity of each cell;
determining the number of cells required for meeting the total required capacity of the 4G online user number according to the 4G online user number in the designated area and the number of users which can be borne by each cell;
determining whether to expand each cell corresponding to the designated area according to the required cell number and the total number of the cells corresponding to the designated area;
wherein the determining whether to expand the capacity of each cell corresponding to the designated area according to the required number of cells and the total number of cells corresponding to the designated area comprises:
collecting the total voice traffic and the total data traffic of the 2G network in a specified time period closest to the current time in the specified area, and acquiring a corresponding 2G network switching coefficient;
acquiring the average number of RRC links, the maximum number of RRC links, downlink traffic and uplink traffic of the 4G network in the specified time period in the specified area, and acquiring a corresponding increase coefficient of the average number of RRC links, an increase coefficient of the maximum number of RRC links and an increase coefficient of the uplink traffic and the downlink traffic;
and acquiring a corresponding 4G pre-expansion growth coefficient according to the RRC link average number growth coefficient, the RRC link maximum number growth coefficient, the uplink and downlink flow growth coefficient and the 2G network switching coefficient, and judging the number of 4G users in the next time period in the specified area, wherein the time period is the same as the specified time period.
2. The method of claim 1, wherein the data traffic model comprises data traffic and voice traffic.
3. The method of claim 1, wherein obtaining the bearable capacity of each cell corresponding to the designated area comprises:
calculating the bearable capacity of each cell according to the configuration parameters of each cell;
wherein the configuration parameter includes at least one of bandwidth, frequency band, subframe configuration, power, cell load, and signal to interference plus noise ratio.
4. The method according to claim 1, wherein the step of determining whether to expand the capacity of each cell corresponding to the designated area according to the required number of cells and the total number of cells corresponding to the designated area comprises:
and when the required number of the cells reaches a threshold value of the total number of the cells corresponding to the specified area, expanding the capacity of each cell corresponding to the specified area.
5. The method according to claim 1, wherein when it is determined that the cell corresponding to the designated area needs capacity expansion, a capacity expansion early warning is issued; wherein, the dilatation early warning includes: emergency capacity expansion early warning, important capacity expansion early warning and common capacity expansion early warning.
6. A network capacity expansion device, comprising:
the extraction module is used for extracting the total number of users in a specified area in the large platform data, the session duration, the session times, the uplink and downlink flow and the number of users of each service type to obtain a data service model;
an obtaining module, configured to obtain, according to the data service model, an average required capacity of each user in the designated area and a bearable capacity of each corresponding cell;
a load-bearing user number calculating module, configured to calculate, according to the average required capacity and the bearable capacity of each cell, a number of users that can be borne by each cell;
the cell number calculation module is used for determining the number of cells required by the total demand capacity meeting the 4G online user number according to the 4G online user number in the designated area and the user number capable of being borne by each cell;
an expansion determining module, configured to determine whether to expand the capacity of each cell corresponding to the designated area according to the required number of cells and the total number of cells corresponding to the designated area;
a 2G network switching coefficient obtaining module, configured to determine whether to expand each cell corresponding to the designated area according to the required number of cells and the total number of cells corresponding to the designated area, where the determining includes: collecting the total voice traffic and the total data traffic of the 2G network in a specified time period in the specified area, and acquiring a corresponding 2G network switching coefficient;
the coefficient acquisition module is used for acquiring the RRC link average number, the RRC link maximum number, the downlink flow and the uplink flow of the 4G network in the specified time period in the specified area and acquiring the corresponding RRC link average number growth coefficient, the RRC link maximum number growth coefficient and the uplink and downlink flow growth coefficient;
and the capacity expansion determining module is used for acquiring a corresponding 4G pre-capacity expansion increasing coefficient according to the RRC link average number increasing coefficient, the RRC link maximum number increasing coefficient, the uplink and downlink flow increasing coefficient and the 2G network switching coefficient, and judging the number of 4G users in the next time period in the specified area, wherein the time period is the same as the specified time period.
7. The apparatus of claim 6, wherein the data traffic model comprises data traffic and voice traffic.
8. The apparatus of claim 6, wherein the obtaining module comprises:
the bearable capacity calculation submodule is used for calculating the bearable capacity of each cell according to the configuration parameters of each cell;
wherein the configuration parameter includes at least one of bandwidth, frequency band, subframe configuration, power, cell load, and signal to interference plus noise ratio.
9. The apparatus according to claim 6, wherein the step of determining whether to expand the capacity of each cell corresponding to the designated area according to the required number of cells and the total number of cells corresponding to the designated area includes:
and when the required number of the cells reaches a threshold value of the total number of the cells corresponding to the specified area, expanding the capacity of each cell corresponding to the specified area.
10. The apparatus of claim 6, wherein when it is determined that the cell corresponding to the designated area needs capacity expansion, a capacity expansion warning is issued; wherein, the dilatation early warning includes: emergency capacity expansion early warning, important capacity expansion early warning and common capacity expansion early warning.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710354128.1A CN108966238B (en) | 2017-05-18 | 2017-05-18 | Network capacity expansion method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710354128.1A CN108966238B (en) | 2017-05-18 | 2017-05-18 | Network capacity expansion method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108966238A CN108966238A (en) | 2018-12-07 |
| CN108966238B true CN108966238B (en) | 2021-12-28 |
Family
ID=64462625
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710354128.1A Active CN108966238B (en) | 2017-05-18 | 2017-05-18 | Network capacity expansion method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108966238B (en) |
Families Citing this family (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111294812B (en) * | 2018-12-10 | 2022-12-13 | 中兴通讯股份有限公司 | Resource capacity-expansion planning method and system |
| CN111385821B (en) * | 2018-12-29 | 2024-03-22 | 北京亿阳信通科技有限公司 | LTE carrier demand quantity prediction method and device |
| CN111490889B (en) * | 2019-01-28 | 2023-01-20 | 上海大唐移动通信设备有限公司 | Method and device for estimating wireless service growth |
| CN110166280B (en) * | 2019-04-10 | 2021-12-07 | 中国联合网络通信集团有限公司 | Network capacity expansion method and device |
| CN112203287B (en) * | 2019-07-08 | 2022-11-22 | 中国移动通信集团浙江有限公司 | Cell capacity adjusting method, device, equipment and storage medium |
| CN110740450B (en) * | 2019-10-14 | 2022-09-02 | 中国联合网络通信集团有限公司 | Network cell capacity expansion method and device |
| CN110768850A (en) * | 2019-11-12 | 2020-02-07 | 国家电网有限公司 | Communication capacity expansion processing method and device based on power system |
| CN110972150B (en) * | 2019-12-12 | 2023-04-07 | 中国移动通信集团内蒙古有限公司 | Network capacity expansion method and device, electronic equipment and computer storage medium |
| CN112291796B (en) * | 2020-11-17 | 2022-09-13 | 中国联合网络通信集团有限公司 | Cell network capacity expansion method, device, equipment and storage medium |
| CN115250486B (en) * | 2021-04-28 | 2024-06-11 | 中国移动通信集团四川有限公司 | Network capacity expansion method and device and electronic equipment |
| CN114650556B (en) * | 2022-05-05 | 2024-04-30 | 中国联合网络通信集团有限公司 | Method, device and equipment for detecting service bearing capacity of wireless network |
| CN114828050B (en) * | 2022-05-10 | 2024-04-30 | 中国联合网络通信集团有限公司 | Method, device, equipment and medium for determining service capacity |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2865209A1 (en) * | 2012-06-26 | 2015-04-29 | Huawei Technologies Co., Ltd. | Method and system for dynamic cell configuration |
| CN105323770A (en) * | 2014-07-31 | 2016-02-10 | 中国移动通信集团公司 | Expansion estimation method and expansion estimation device of wireless communication system |
| CN105992233A (en) * | 2015-02-13 | 2016-10-05 | 中国移动通信集团浙江有限公司 | Method and device for calculating capacity baseline of network service |
| CN106412917A (en) * | 2015-07-29 | 2017-02-15 | 中国移动通信集团公司 | Network expansion method and device |
-
2017
- 2017-05-18 CN CN201710354128.1A patent/CN108966238B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2865209A1 (en) * | 2012-06-26 | 2015-04-29 | Huawei Technologies Co., Ltd. | Method and system for dynamic cell configuration |
| CN105323770A (en) * | 2014-07-31 | 2016-02-10 | 中国移动通信集团公司 | Expansion estimation method and expansion estimation device of wireless communication system |
| CN105992233A (en) * | 2015-02-13 | 2016-10-05 | 中国移动通信集团浙江有限公司 | Method and device for calculating capacity baseline of network service |
| CN106412917A (en) * | 2015-07-29 | 2017-02-15 | 中国移动通信集团公司 | Network expansion method and device |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108966238A (en) | 2018-12-07 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108966238B (en) | Network capacity expansion method and device | |
| Lee et al. | PERCEIVE: Deep learning-based cellular uplink prediction using real-time scheduling patterns | |
| US8611825B2 (en) | Method and apparatus for providing a dynamic inactivity timer in a wireless communications network | |
| CN1853383B (en) | Information flow admission control for wireless systems | |
| CN104980934B (en) | Multi-service resource dispatching method and device | |
| US9565697B2 (en) | Method and a system for scheduling the downlink in long term evolution (LTE) networks based on quality of service (QoS) | |
| CN107708178B (en) | Information retransmission method and base station | |
| CN102137438A (en) | Method and device for allocating internet protocol (IP) network resources | |
| US20140226477A1 (en) | Method, Apparatus, and System for Improving user Experience of Small Flow User | |
| CN101600231A (en) | In packet scheduling, determine the method and system of the priority of subscriber equipment | |
| EP2822347B1 (en) | Packet forwarding device and packet forwarding method, and computer program | |
| CN107210852B (en) | System and method for controlling operation of an application by predicting a smoothed transport block size | |
| CN105830415A (en) | Methods, radio communication device and base station device for managing a media stream | |
| CN104581970B (en) | A kind of self-adapting dispatching method and equipment | |
| CN107302802B (en) | Data transmission method and device | |
| US20140185441A1 (en) | Transmission Timing Interval Adjusting Method and Communication System | |
| WO2012147499A1 (en) | Base station in mobile communication system and resource allocation method | |
| CN107155192B (en) | User experience quality assessment method and device | |
| CN103222297A (en) | Data acquisition and processing application method, system and corresponding equipment thereof | |
| Fowler et al. | LTE-advanced DRX mechanism for power saving | |
| CN109429352B (en) | Method and device for scheduling packet service data of base station | |
| Sayeed et al. | Cloud analytics for wireless metric prediction-framework and performance | |
| Szabó et al. | Service aware adaptive DRX scheme | |
| Alkhawlani | MCDM based joint admission control for heterogeneous wireless networks | |
| Nguyen et al. | Performance evaluation of E-MQS scheduler with Mobility in LTE heterogeneous network |
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 |