CN113784376B - Communication system processing method, server and storage medium - Google Patents
Communication system processing method, server and storage medium Download PDFInfo
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Abstract
The application provides a communication system processing method, a server and a storage medium, wherein the method comprises the following steps: acquiring cell-level application layer data and bandwidth data corresponding to a communication system; calculating the application layer data to obtain an average data service flow ratio; calculating the bandwidth data to obtain a bandwidth factor; and according to the average data service flow ratio and the bandwidth factor, carrying out standard efficiency calculation to obtain the standard efficiency of the target cell, wherein the standard efficiency is used for evaluating the resource efficiency. The cell standard efficiency which is close to the actual condition of using the network resources of the communication system and has high accuracy is obtained by acquiring important parameters influencing the perception of the user and the evaluation of the network resource efficiency of the communication system and carrying out comprehensive calculation processing on the important parameters. The method and the device effectively solve the problem that the resource occupation amount data of the physical layer adopted in the prior art cannot accurately evaluate the resource utilization efficiency actually used by the user.
Description
Technical Field
The present disclosure relates to the field of communications technologies, and in particular, to a processing method, a server, and a storage medium for a communications system.
Background
The mobile communication system requires a large investment in constructing communication base stations to form a continuous coverage network, and provides seamless coverage voice and data service for users. Digital signals of mobile communication are propagated by means of radio waves, and frequency resources are very scarce resources. In order to fully utilize resources such as a base station and frequency, and improve the use efficiency and user perception of the resources, an operator is generally required to acquire the use condition of the resources at the cell level in the mobile communication system, so that the evaluation of the use efficiency of the resources is facilitated.
At present, a communication system processing method for acquiring cell-level resource usage conditions in a mobile communication system commonly used by 2G, 3G, 4G and 5G is to directly acquire resource occupation amount data of a physical layer from a base station, thereby acquiring resource occupation rate. And through the obtained resource occupancy rate, the evaluation of the resource utilization efficiency of the mobile communication system is realized.
The existing communication system processing method cannot obtain accurate and comprehensive resource utilization rate data of actual use of cell-level users in a mobile communication system, so that operators cannot accurately evaluate the resource utilization efficiency of actual use of the users.
Disclosure of Invention
The application provides a processing method of a communication system, a server and a storage medium, so as to obtain cell standard efficiency which directly influences user perception and characterizes network resource utilization rate of the communication system, and solve the problem that in the prior art, accurate evaluation cannot be carried out on the resource utilization rate actually used by a user.
In a first aspect, the present application provides a communication system processing method, including:
acquiring cell-level application layer data and bandwidth data corresponding to a communication system;
calculating the application layer data to obtain an average data service flow ratio;
calculating the bandwidth data to obtain a bandwidth factor;
and according to the average data service flow ratio and the bandwidth factor, carrying out standard efficiency calculation to obtain the standard efficiency of the target cell, wherein the standard efficiency is used for evaluating the resource efficiency.
Optionally, the application layer data includes: the data traffic c carried by the target cell, all data traffic F carried by the communication system to which the target cell belongs, the total number M of cells under the communication system to which the target cell belongs, and the cell service model correction coefficient epsilon of the target cell;
the calculating the application layer data to obtain an average data service flow ratio includes:
the average data traffic flow ratio mu of the target cell is determined using the formula mu=c (F/M)/(epsilon).
Optionally, the data service flow c carried by the target cell specifically includes: the sum of at least one class of data traffic carried by the target cell.
Optionally, the application layer data further includes: the number m of types of data traffic j, and the cell-level rate weight coefficient beta of the data traffic j in the target cell j Network level rate weighting coefficient alpha for data traffic j j User number y of data traffic j in target cell j ；
The cell service model correction coefficient epsilon of the target cell adopts a formula
And (5) determining.
Optionally, the network-level rate weight coefficient of the data service j is obtained through a whole network data grabbing mode.
Optionally, the cell-level rate weight coefficient of the data service j in the target cell and the number of users of the data service j in the target cell are obtained through a system grabbing mode.
Optionally, the bandwidth data includes: the method comprises the steps of co-configuring carrier wave type N of a mobile communication system under a communication system of a target cell, configuring carrier wave number k to be counted in the target cell, wherein k is {1,2,3 }. I..N., absolute value d of bandwidth configured by the target cell, absolute value b of bandwidth configured by a carrier wave with number i under the communication system of the target cell i The total number n of cells corresponding to the carrier with the number i under the communication system to which the target cell belongs i The duty ratio S of terminals supporting carrier wave with number k in all terminals in the network under the communication system to which the target cell belongs k The total number M of cells under a communication system to which the target cell belongs;
the calculating the bandwidth data to obtain a bandwidth factor includes:
using the formula
The bandwidth factor p of the target cell is determined.
Optionally, the calculating the standard efficiency according to the average data traffic flow ratio and the bandwidth factor to obtain the standard efficiency of the target cell includes:
the standard efficiency eta of the target cell is determined by the formula eta = mu +.rho according to the average data traffic flow ratio mu and the bandwidth factor rho.
In a second aspect, the present application provides a server comprising:
a processor and a memory;
the memory stores executable instructions executable by the processor;
wherein the processor executes the executable instructions stored by the memory, causing the processor to perform the communication system processing method as described above.
In a third aspect, the present application provides a storage medium having stored therein computer-executable instructions which, when executed by a processor, are adapted to carry out a communication system processing method as described above.
In a fourth aspect, the present application provides a program product comprising a computer program which, when executed by a processor, implements a method as described above.
The application provides a communication system processing method, a server and a storage medium. The cell standard efficiency which is close to the actual condition of using the network resources of the communication system and has high accuracy is obtained by acquiring important parameters influencing the perception of the user and the evaluation of the network resource efficiency of the communication system and carrying out comprehensive calculation processing on the important parameters. The method and the device effectively solve the problem that the resource occupation amount data of the physical layer adopted in the prior art contains the resource occupation amount data used by non-users, so that the actual use efficiency of the resources used by the users cannot be accurately evaluated.
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In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief description will be given below of the drawings that are needed in the embodiments or the prior art descriptions, it being obvious that the drawings in the following description are some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort to a person skilled in the art.
Fig. 1 is a schematic processing diagram of a communication system according to an embodiment of the present application;
fig. 2 is a schematic flow chart of a processing method of a communication system according to an embodiment of the present application;
fig. 3 is a schematic flow chart of a processing method of the communication system according to the embodiment of the present application;
fig. 4 is a schematic diagram of a process flow of cell data service preference standardization provided in an embodiment of the present application;
fig. 5 is a schematic structural diagram of a server according to an embodiment of the present application.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.
Fig. 1 is a schematic processing diagram of a communication system according to an embodiment of the present application. As shown in fig. 1, the communication system network includes a bottom physical layer and a top application layer. The data providing device 11 in the application layer is connected to a server 12. Further, the server 12 includes a processor and a memory. The data providing device 11 monitors, records and stores application layer data flowing into the user terminal and bandwidth data stored therein. Further, the application layer data and the bandwidth data stored by the data providing apparatus 11 may be stored in units of one cell. The server 12 acquires cell-level application layer data and bandwidth data from the data providing device 11. The server 12 performs standard performance calculation on the acquired application layer data and bandwidth data to obtain standard performance of the target cell. The staff member can evaluate the use condition of the communication system resources of each cell by using the standard efficiency obtained by the server 12, so as to optimize the communication system resources, and continuously improve the perception of users.
Alternatively, the data providing device 11 may be any one of a network management device, an end-to-end analysis device, or a billing system device, and the embodiment is not particularly limited.
In the prior art, operators generally adopt the resource occupancy rate of a physical layer in a communication system network to perform problem investigation or resource optimization on the communication system network resources. When resource optimization is performed on a 4G long term evolution (english: long Term Evolution, abbreviated: LTE) mobile communication system to improve user perception, the utilization rate of a common 4G physical resource block (english: physical Resource Block, abbreviated: PRB) is used to evaluate the resource utilization efficiency of the communication system. But sometimes there is a strong interference inside and outside the communication system. The internal interference of the communication system is formed by unreasonable network structure caused by factors such as network construction structure, level of network structural design, actual deployment position of base station and the like; communication system external interference, such as interference caused to the communication system by interfering signals in the environment external to the communication system. Interference existing inside and outside a communication system often causes that information of a user in an LTE system cannot be decoded correctly, and the information of the user cannot be transmitted effectively, so that the information of the user is retransmitted repeatedly in the system. The repeated retransmission of the user information in the system shows a phenomenon of virtual high in PRB utilization rate. The virtually high PRB utilization is not the result of the actual use of the service by the user. When staff utilizes the PRB utilization rate to evaluate the network resource utilization efficiency of the communication system, the virtual high of the resource occupation is easy to be misled, and the evaluation result is inaccurate. Inaccuracy in the assessment of the efficiency of the use of network resources of a communication system often results in the staff missing serious interference problems existing in the network and even affecting the effectiveness of the optimization of network resources of the communication system.
Compared with the prior art, the main improvement point of the embodiment is that the application layer service data and the bandwidth data which influence the resource use efficiency and the actual use of the user perceived by the user are directly obtained according to the network resource optimization requirement of the communication system. And then, based on the obtained application layer data and bandwidth data, standard efficiency calculation is carried out to obtain the standard efficiency of the target cell, and accurate evaluation of the network resource efficiency of the communication system is carried out.
Fig. 2 is a schematic flow chart of a processing method of a communication system according to an embodiment of the present application. The present embodiment describes the flow of the processing method of the communication system in detail on the basis of fig. 1. The execution body of this embodiment may be the server 12 in the embodiment shown in fig. 1, and the method includes:
s201, acquiring cell-level application layer data and bandwidth data corresponding to a communication system;
the communication modes of the current mainstream are 4G and 5G, and the application layer data of which the 4G and 5G mainly influence the perception of users and the efficiency of network resources is related data of the application layer data traffic.
Specifically, the data providing apparatus 11 monitors, records, and stores application layer data of the user terminal flowing into each cell and stores bandwidth data configured for each cell. When it is necessary to evaluate the resource efficiency of a target cell in a communication system, the server 12 reads the application layer data and the bandwidth data of the target cell from the data providing device 11 according to the communication number of the target cell.
The application layer data of the target cell comprises: the data traffic c carried by the target cell, all the data traffic F carried by the communication system to which the target cell belongs, and the total number M of cells under the communication system to which the target cell belongs. These application layer data are all important parameters that affect the accurate assessment of the data traffic usage of the target cell.
The bandwidth data of the target cell configuration includes: the method comprises the steps of co-configuring carrier wave type N of a mobile communication system under a communication system of a target cell, configuring carrier wave number k to be counted in the target cell, wherein k is {1,2,3 }. I..N., absolute value d of bandwidth configured by the target cell, absolute value b of bandwidth configured by a carrier wave with number i under the communication system of the target cell i The total number n of cells corresponding to the carrier with the number i under the communication system to which the target cell belongs i The duty ratio S of terminals supporting carrier wave with number k in all terminals in the network under the communication system to which the target cell belongs k The total number M of cells under the communication system to which the target cell belongs. These bandwidth data are all important parameters that affect accurate assessment of the bandwidth usage of the target cell. Specifically, carriers with the same center frequency point and bandwidth belong to the same carrier, and the same carrier is numbered by the same carrier.
Then, the server 12 performs comprehensive calculation processing on the application layer data and the bandwidth data affecting the accurate evaluation of the resource efficiency of the target cell according to the following steps to obtain accurate standard energy efficiency for evaluating the network resource efficiency of the communication system.
S202, calculating application layer data to obtain an average data service flow ratio;
in particular, users of different scenarios have different preferences for different categories of data traffic when using the data traffic. For example, user gaming APP for a college and university scenario is used more, while user email or video-like traffic for a business office scenario is more. A typical feature of gaming data services is frequent triggering but low traffic, and mail or video-like services are continuous high traffic. The data traffic c value carried by the cells in the college and university scene is smaller, and the c value of the cells in the business office scene is larger, so that the difference is not caused by the network occurrence problem. In order to avoid erroneous judgment when evaluating the cell data traffic, it is highly necessary to normalize the preference of the cell data traffic. Therefore, the server 12 first performs normalization processing on the preference of the data traffic of the target cell, and obtains the cell traffic model correction coefficient epsilon of the target cell.
Then, based on the data traffic c carried by the target cell, all data traffic F carried by the communication system to which the target cell belongs, the total number M of cells under the communication system to which the target cell belongs, and the cell service model correction coefficient epsilon of the target cell. The server 12 determines the average data traffic flow ratio μ of the target cell using the following formula:
μ＝c÷(F÷M)÷ε。
the average data traffic flow ratio mu of the target cells determined by the server 12 eliminates the preference of different cells for data traffic. Meanwhile, the server 12 obtains the ratio of the data traffic carried by the target cell to the average data traffic carried by all cells in the communication system to which the target cell belongs. The average data traffic ratio mu of the target cell determined by the server 12 greatly facilitates the accurate comparison analysis of the data traffic of the different cells by the staff.
S203, calculating bandwidth data to obtain bandwidth factors;
specifically, the server 12 determines the ratio of the bandwidth capability of the target cell to the bandwidth capability of all cells of the communication system, that is, the bandwidth factor ρ of the target cell, using the following formula:
wherein N is the carrier type commonly configured by the mobile communication system in the communication system to which the target cell belongs, k is the carrier number of the configuration to be counted in the target cell, wherein k is {1,2,3 }, i..N }, d is the absolute value of the bandwidth configured by the target cell, and b i Is the absolute value of the bandwidth configured by the carrier with the number i under the communication system to which the target cell belongs, n i Is the total number of cells corresponding to the carrier with the number i under the communication system to which the target cell belongs, S k The duty ratio of the terminals supporting the carrier wave with the number k in all the terminals in the network under the communication system to which the target cell belongs, and M is the total number of the cells under the communication system to which the target cell belongs. Specifically, carriers with the same center frequency point and bandwidth belong to the same carrier, and the same carrier is numbered by the same carrier.
The bandwidth factor ρ of the target cell determined by the server 12 is calculated by taking the bandwidth of a carrier and the total number of cells of the carrier into consideration, and taking into account the influence factors such as the terminal permeability of the carrier configured by the target cell. The bandwidth factor ρ of the target cell determined by the server 12 considers the own bandwidth factor of the cell bandwidth evaluation and the influencing factor of the terminal device used by the user, so as to ensure that the bandwidth factor is more fit for the actual use situation of the user.
S204, according to the average data traffic flow ratio and the bandwidth factor, standard efficiency calculation is carried out to obtain the standard efficiency of the target cell, and the standard efficiency is used for evaluating the resource efficiency;
specifically, the server 12 performs standard performance calculation according to the average data traffic flow ratio μ and the bandwidth factor ρ, to obtain the standard performance of the target cell. Specifically, the server 12 determines the standard performance η of the target cell using the formula η=μ++ρ.
The server 12 can calculate the standard performance of different cells according to the method provided by the present embodiment. Further, the server 12 compares the standard performance of the cell with a preset threshold value to obtain a judgment result of the resource efficiency of the cell. Specifically, the preset threshold includes an upper threshold limit delta high And a lower threshold delta low . When eta > delta high I.e. the standard cell performance is higher than delta high When the judgment result is that the cell bears too much traffic and has heavier load, the perception of the user is possibly deteriorated; when eta < delta low I.e. the standard cell performance is lower than delta low When the traffic carried by the cell is too small, the wireless resources are not fully utilized, and the related problems need to be processed and solved as soon as possible.
Optionally, the data traffic c carried by the target cell in step S202 may be the sum of all the data traffic carried by the target cell, or may be the sum of at least one type of data traffic carried by the target cell.
When the data traffic c carried by the target cell is the sum of all the data traffic carried by the target cell, the average data traffic ratio of the cells is the total data traffic ratio of the cells. The obtained cell standard efficiency can be used for staff to conduct the problem investigation and resource optimization of the cell communication system network resources. The staff can accurately and timely find out the problem cell with abnormal resource efficiency according to the standard efficiency and the judgment result of different cells calculated by the server 12. And a worker rapidly evaluates and analyzes the cell resource efficiency, so that the resource optimization response rate is improved, and the user perception is further improved. In addition, the method combines the standard efficiency of the cell and the PRB utilization rate of the cell, and can also effectively evaluate and analyze the internal and external interference of the system.
When the data traffic c carried by the target cell is the sum of one type of data traffic in multiple types of data traffic carried by the target cell, the average data traffic ratio of the cells is one type of data traffic ratio carried by the cells. The obtained cell standard efficiency can be used for analyzing specific data services by staff, and is beneficial to service optimization of the data services or development of new data services by taking the data services as design reference basis.
Further, when the server 12 performs calculation and determination on the cell standard performance, the time period of the application layer data and the bandwidth data acquired from the data providing device 11 may be a month period, or may be a quarter period or a year period, which is not particularly limited in this embodiment.
In this embodiment, the server 12 obtains important parameters that directly affect user perception and evaluation of network resource efficiency of the communication system, and performs comprehensive calculation processing on the important parameters to obtain accurate cell standard performance. In the process of obtaining the standard efficiency of the cells, the data service preference and the data service flow characteristics of different cells are standardized, and the obtained average data service flow ratio of the cells ensures the accuracy of the comparison analysis among the different cells. The bandwidth factor not only considers the bandwidth factor of the network, but also considers the influence of the terminal equipment used by the user on the use of the data service flow. Therefore, the standard efficiency of the cell obtained based on the comprehensive calculation of the average data traffic flow ratio of the cell and the bandwidth factor is relevant to the actual situation of using network resources by the user. The communication system processing method provided by the embodiment has high accuracy, and is greatly convenient for staff to accurately evaluate the network resource efficiency of the communication system. In addition, the obtained cell standard efficiency is beneficial to the data service developer to carry out service optimization on the existing data service or carry out new data service development by taking the service optimization as a reference basis.
Fig. 3 is a schematic flow chart of a processing method of the communication system according to the embodiment of the present application. FIG. 3 is a further detailed illustration of the embodiment of FIG. 2, as shown in FIG. 3, the method comprising:
s301, acquiring cell-level application layer data and bandwidth data corresponding to a communication system;
specifically, the implementation of step S301 is similar to that of step S201 in the embodiment shown in fig. 2, and this embodiment will not be described herein.
S302, calculating and determining a cell service model correction coefficient of a target cell according to application layer data;
specifically, a specific flow for determining the cell service model correction coefficient of the target cell according to the application layer data calculation is shown in fig. 4. Fig. 4 is a schematic diagram of a process flow for standardizing cell data service preference provided in the embodiment of the present application, where after the server 12 obtains the application layer data of the target cell according to step S301, the server performs standardization processing on preferences of different types of data services according to the process shown in fig. 4, to obtain a cell service model correction coefficient epsilon of the target cell. The method specifically comprises the following steps:
s401, obtaining a cell-level data service flow corresponding to a communication system;
specifically, the implementation of step S401 is similar to that of step S201 in the embodiment shown in fig. 2, and this embodiment will not be described herein.
S402, classifying the data service flow according to the data service type;
specifically, the server 12 classifies data traffic according to data traffic types, such as game types, web browsing types, instant messaging types, video types, etc., and configures a network-level rate weighting coefficient α for each type of data traffic j j And a cell-level rate weighting coefficient beta j 。
S403, obtaining a network-level rate weight coefficient and a cell-level rate weight coefficient in a data grabbing mode;
specifically, the network-level rate weighting coefficient α j And cell-level rate weight coefficient beta j Are obtained by the server 12 by means of data crawling.
Wherein the network level rate weighting coefficient alpha j Is available to the server 12 by way of a data capture over the network. Specifically, the server 12 captures the average rate of data traffic generated by all users continuously using the data traffic j in the communication system to which the target cell belongs. The server 12 then sets the absolute value of the average rate of data traffic generated by all users using data traffic j to alpha j . Alternatively, the server 12 may also store the target cellThe relative value of the average data service rate generated by different kinds of data service j under the communication system is set as alpha j 。
Cell-level rate weighting coefficient beta j Is available to the server 12 by way of system crawling. Specifically, the server 12 system captures the average rate of data traffic generated by all users of the target cell using data traffic j continuously. The server 12 then sets the absolute value of the average rate of data traffic generated by all users of the target cell using data traffic j to be beta j . Alternatively, the server 12 may set the magnitude relation of the average data traffic rates generated by different kinds of data traffic j of the target cell to be β j 。
S404, obtaining the number of users of each data service in a target cell in a data grabbing mode;
specifically, the server 12 captures the number of users of each data service j in the target cell in a system capturing manner, and obtains the number of users γ of each data service j in the target cell j 。
S405, obtaining the number of users of each data service in a target cell in a data grabbing mode;
specifically, the server 12 obtains the network-level rate weight coefficient α based on steps S403 to S404 j Cell-level rate weighting coefficient beta j User number gamma of each data service j of target cell j The cell service model correction coefficient epsilon of the target cell is determined by adopting the following formula:
where j=1, 2,3,..m.
The cell service model correction coefficient of the target cell comprehensively considers the preference factors of users of different scenes on the data service and the characteristics of different types of data service, and can obtain the average data service flow ratio with high accuracy when the average data service flow ratio of the cell is calculated subsequently. The cell service model correction coefficient of the target cell ensures the accuracy when the average data service flow ratio of different cells is compared and analyzed subsequently.
The specific manner in which the server 12 uses the cell traffic model correction coefficients of the target cell for calculating the average data traffic flow ratio of the cell is as follows in step S303.
S303, calculating the application layer data based on the cell service model correction coefficient of the target cell to obtain an average data service flow ratio;
s304, calculating bandwidth data to obtain bandwidth factors;
s305, according to the average data traffic flow ratio and the bandwidth factor, standard efficiency calculation is carried out to obtain the standard efficiency of the target cell, and the standard efficiency is used for evaluating the resource efficiency;
specifically, steps S303-S305 are similar to the specific implementation of steps S202-S204 in the embodiment shown in FIG. 2, and are not described here again.
The method provided by the embodiment can be used for rapidly identifying the cell with abnormal network resource use in the communication system, is convenient for a worker to rapidly and effectively solve the problem of cell level, and enhances the perception of users. The method provided in this embodiment will be further described using the following specific implementation cases.
The specific procedure for determining the standard performance at 8 months for cell a by the method provided by the present embodiment is as follows for the server 12. The server 12 acquires the application layer data and the bandwidth data related to the cell a from the data providing device 11. The application layer data and bandwidth data related to the cell a acquired by the server 12 are: the 4G network is respectively deployed on three frequency bands of 900MHz (L900 for short), 1800MHz (L1800 for short) and 2100MHz (L2100 for short) under the 4G communication system to which the cell A belongs, wherein the frequency band of the cell A is L900,
l900 has 100 cells in total, and the bandwidths configured by the 100 cells are all 10MHz;
l1800 has 200 cells in total, and the bandwidths configured by the 200 cells are all 20MHz;
l2100 has 100 cells, and the bandwidth configured by the 100 cells is 20MHz;
the 4G mobile phone has 90% of frequency bands supporting L900 under the 4G communication system to which the cell A belongs;
the total flow of the 4G network of 8 months under the 4G communication system of the cell A is 55000GB (English: gigabyte; short: GB);
the data traffic carried by cell a in 8 months is 35GB.
First, the procedure for calculating the cell a traffic model correction coefficient epsilon by the server 12 is as follows:
specifically, the server 12 first classifies 8 months of data traffic into 4 classes of data traffic including game class, web browsing class, instant messaging class, and video class.
The server 12 then obtains, through whole network data grabbing, the average rate of data traffic generated by the class 4 data traffic in the 4G network under the 4G communication system to which the cell a belongs, as follows: game class 100kbps, web browsing class 200kbps, instant messaging class 600kbps, video class 2000kbps. Thereby, the server 12 sets the network level rate weight coefficient α of the class 4 data traffic, respectively j The method comprises the following steps of: game class alpha 1 =100, web browsing class α 2 Instant messaging class α=200 3 =600, video class α 4 ＝2000。
Similarly, the average rate of data traffic generated in cell a by server 12 through system data crawling to obtain class 4 data traffic is: the game class is 90kbps, the web browsing class is 190kbps, the instant messaging class is 400kbps, and the video class is 1000kbps. The server 12 sets up cell-level rate weighting coefficients beta for class 4 data services, respectively j The method comprises the following steps of: game class beta 1 =90, web browsing class β 2 =190, instant messaging class β 3 =400, video class β 4 ＝1000。
Similarly, the server 12 obtains the user number gamma of the class 4 data service in the cell A through system data grabbing j The method comprises the following steps of: game gamma 1 =201, web browsing class γ 2 =301, instant messaging class γ 3 =401, video class γ 4 ＝202。
The server 12 calculates the network level rate weighting factor alpha according to the above-mentioned class 4 data traffic j Cell levelRate weight coefficient beta j User number gamma in cell a j The cell service model correction coefficient epsilon of the target cell of the cell A is calculated as follows:
Then, the server 12 calculates the average data traffic ratio μ of cell a as:
μ＝c÷(F÷M)÷ε
＝35÷[55000÷(100+200+100)]÷0.756
＝0.337；
next, the server 12 calculates the bandwidth factor ρ of the cell a as:
finally, the server 12 calculates the standard performance η of cell a:
η＝μ÷ρ＝0.337÷0.514＝0.656。
further, the server 12 presets an upper threshold δ high =0.8, lower threshold δ low =0.7. According to the standard performance η=0.656 of the cell a, the server 12 determines that: cell standard performance for cell a is below the lower threshold delta low Cell a fails to function sufficiently and has low use efficiency.
Then, based on the above-mentioned determination result of the server 12, the staff can analyze the network problem of the cell a, and see what factors are the factors of weak coverage, interference, improper carrier equalization configuration, etc. to the bottom, which cause the use efficiency to be low, and after the problem is solved, the cell a can more fully absorb the data traffic.
In this embodiment, the server 12 classifies the data traffic carried by the cell, and then obtains the network-level rate weight coefficient and the cell-level rate weight coefficient of each type of data traffic in a data grabbing manner. The network-level rate weight coefficient and the cell-level rate weight coefficient of each type of data service are adopted, so that the data service preference of different cells is standardized, and the cell service model correction coefficient of the target cell is obtained. And then, the cell average data service flow ratio obtained by calculating the cell service model correction coefficient of the target cell is a corrected numerical value, so that the accuracy of the comparison analysis of the cell average data service flow ratios among different cells is ensured. And finally, carrying out standard efficiency calculation by adopting the corrected cell average data service flow ratio and bandwidth factor to obtain accurate cell standard efficiency. And comparing the standard effectiveness of the cell with a preset threshold value to directly obtain a judging result of the network resource utilization efficiency of the cell communication system. The staff can quickly identify the cell with abnormal network resource usage in the communication system through the judging result, quickly and effectively solve the problem of cell level, optimize the network resource and greatly enhance the perception of users.
The embodiment of the application also provides a server. Fig. 5 is a schematic structural diagram of a server according to an embodiment of the present application. As shown in fig. 5, the server includes a processor 51 and a memory 52, where the memory 52 stores executable instructions executable by the processor 51, so that the processor 51 can be used to execute the technical solution of the above method embodiment, and the implementation principle and technical effect are similar, and the embodiment is not repeated here. It should be understood that the processor 51 may be a central processing unit (in english: central Processing Unit, abbreviated as CPU), or may be other general purpose processors, digital signal processors (in english: digital Signal Processor, abbreviated as DSP), application specific integrated circuits (in english: application Specific Integrated Circuit, abbreviated as ASIC), or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the present invention may be embodied directly in a hardware processor for execution, or in a combination of hardware and software modules in a processor for execution. The memory 52 may comprise a high-speed RAM memory, and may further comprise a nonvolatile memory NVM, such as at least one magnetic disk memory, and may also be a U-disk, a removable hard disk, a read-only memory, a magnetic disk or optical disk, etc.
The embodiment of the application also provides a storage medium, in which computer-executable instructions are stored, and when the computer-executable instructions are executed by a processor, the communication system processing method is realized.
The storage medium may be implemented by any type or combination of volatile or nonvolatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disk. A storage media may be any available media that can be accessed by a general purpose or special purpose computer.
An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an application specific integrated circuit (English: application Specific Integrated Circuits; ASIC). It is also possible that the processor and the storage medium reside as discrete components in an electronic device or a master device.
Embodiments of the present application also provide a program product, such as a computer program, which when executed by a processor implements a communication system processing method covered by the present application.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the method embodiments described above may be performed by hardware associated with program instructions. The foregoing program may be stored in a computer readable storage medium. The program, when executed, performs steps including the method embodiments described above; and the aforementioned storage medium includes: various media that can store program code, such as ROM, RAM, magnetic or optical disks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced with equivalents; such modifications and substitutions do not depart from the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention.
Claims (9)
1. A method of processing a communication system, comprising:
acquiring cell-level application layer data and bandwidth data corresponding to a communication system;
calculating the application layer data to obtain an average data service flow ratio;
calculating the bandwidth data to obtain a bandwidth factor;
according to the average data service flow ratio and the bandwidth factor, standard efficiency calculation is carried out to obtain standard efficiency of a target cell, and the standard efficiency is used for evaluating resource efficiency;
the application layer data comprises: the data traffic c carried by the target cell, all data traffic F carried by the communication system to which the target cell belongs, the total number M of cells under the communication system to which the target cell belongs, and the cell service model correction coefficient epsilon of the target cell;
the calculating the application layer data to obtain an average data service flow ratio includes:
the average data traffic flow ratio mu of the target cell is determined using the formula mu=c (F/M)/(epsilon).
2. The method according to claim 1, wherein the data traffic c carried by the target cell specifically comprises: the sum of at least one class of data traffic carried by the target cell.
3. The method of claim 1, wherein the application layer dataFurther comprises: the number m of types of data traffic j, and the cell-level rate weight coefficient beta of the data traffic j in the target cell j Network level rate weighting coefficient alpha for data traffic j j User number y of data traffic j in target cell j ；
The cell service model correction coefficient epsilon of the target cell adopts a formula
And (5) determining.
4. A method according to claim 3, wherein the network level rate weighting factor of the data traffic j is obtained by means of whole network data grabbing.
5. A method according to claim 3, characterized in that the cell-level rate weight coefficient of the data traffic j in the target cell and the number of users of the data traffic j in the target cell are obtained by means of system grabbing.
6. The method of any of claims 1-5, wherein the bandwidth data comprises: the method comprises the steps of co-configuring carrier wave type N of a mobile communication system under a communication system of a target cell, configuring carrier wave number k to be counted in the target cell, wherein k is {1,2,3 }. I..N., absolute value d of bandwidth configured by the target cell, absolute value b of bandwidth configured by a carrier wave with number i under the communication system of the target cell i The total number n of cells corresponding to the carrier with the number i under the communication system to which the target cell belongs i The duty ratio S of terminals supporting carrier wave with number k in all terminals in the network under the communication system to which the target cell belongs k The total number M of cells under a communication system to which the target cell belongs;
the calculating the bandwidth data to obtain a bandwidth factor includes:
using the formula
The bandwidth factor p of the target cell is determined.
7. The method according to any one of claims 1-5, wherein the performing standard performance calculation according to the average data traffic flow ratio and the bandwidth factor to obtain the standard performance of the target cell includes:
the standard efficiency eta of the target cell is determined by the formula eta = mu +.rho according to the average data traffic flow ratio mu and the bandwidth factor rho.
8. A server, comprising: a processor and a memory;
the memory stores executable instructions executable by the processor;
wherein execution of the executable instructions stored by the memory by the processor causes the processor to perform the method of any one of claims 1-7.
9. A storage medium having stored therein computer-executable instructions which, when executed by a processor, are adapted to carry out the method of any one of claims 1 to 7.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104780569A (en) * | 2015-04-02 | 2015-07-15 | 南京邮电大学 | Multilayered satellite network channel resource management method |
| CN109982385A (en) * | 2017-12-27 | 2019-07-05 | 中国移动通信集团公司 | Network intelligence equalization methods and device based on LTE type of service feature |
| CN110505105A (en) * | 2019-09-26 | 2019-11-26 | 中国联合网络通信集团有限公司 | Control method, device, equipment and the storage medium of network service quality |
| WO2020057261A1 (en) * | 2018-09-17 | 2020-03-26 | 华为技术有限公司 | Communication method and apparatus |
| CN111757403A (en) * | 2019-03-29 | 2020-10-09 | 华为技术有限公司 | Resource allocation method and communication device |
| CN112153702A (en) * | 2020-11-05 | 2020-12-29 | 广州竞远安全技术股份有限公司 | Local area network bandwidth resource allocation method, storage device and equipment |
| CN113015218A (en) * | 2021-04-29 | 2021-06-22 | 中国联合网络通信集团有限公司 | Method and device for processing mobile communication information |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10298279B2 (en) * | 2017-04-05 | 2019-05-21 | Isco International, Llc | Method and apparatus for increasing performance of communication paths for communication nodes |
-
2021
- 2021-09-28 CN CN202111144800.7A patent/CN113784376B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104780569A (en) * | 2015-04-02 | 2015-07-15 | 南京邮电大学 | Multilayered satellite network channel resource management method |
| CN109982385A (en) * | 2017-12-27 | 2019-07-05 | 中国移动通信集团公司 | Network intelligence equalization methods and device based on LTE type of service feature |
| WO2020057261A1 (en) * | 2018-09-17 | 2020-03-26 | 华为技术有限公司 | Communication method and apparatus |
| CN111757403A (en) * | 2019-03-29 | 2020-10-09 | 华为技术有限公司 | Resource allocation method and communication device |
| CN110505105A (en) * | 2019-09-26 | 2019-11-26 | 中国联合网络通信集团有限公司 | Control method, device, equipment and the storage medium of network service quality |
| CN112153702A (en) * | 2020-11-05 | 2020-12-29 | 广州竞远安全技术股份有限公司 | Local area network bandwidth resource allocation method, storage device and equipment |
| CN113015218A (en) * | 2021-04-29 | 2021-06-22 | 中国联合网络通信集团有限公司 | Method and device for processing mobile communication information |
Non-Patent Citations (2)
| Title |
|---|
| Supporting dynamic bandwidth adjustment based on virtual transport link in software-defined IP over optical networks;Yu Zhou; Byrav Ramamurthy; Bingli Guo; Shanguo Huang;《Journal of Optical Communications and Networking ( Volume: 10, Issue: 3, March 2018)》;全文 * |
| 基于可用带宽估计的拥塞控制算法研究;揭鸿;《中国优秀硕士学位论文全文数据库 信息科技辑 (月刊)》;全文 * |
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