CN111818560A - Method and device for determining poor quality cell - Google Patents
Method and device for determining poor quality cell Download PDFInfo
- Publication number
- CN111818560A CN111818560A CN201910289792.1A CN201910289792A CN111818560A CN 111818560 A CN111818560 A CN 111818560A CN 201910289792 A CN201910289792 A CN 201910289792A CN 111818560 A CN111818560 A CN 111818560A
- Authority
- CN
- China
- Prior art keywords
- xdr
- target cell
- quality difference
- time
- determining
- 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.)
- Pending
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/08—Testing, supervising or monitoring using real traffic
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Data Exchanges In Wide-Area Networks (AREA)
Abstract
The embodiment of the invention discloses a method for determining a poor cell, which comprises the following steps: acquiring a plurality of extensible detailed list interfaces (XDR) call tickets of a full-network full-volume user within a preset time length, wherein the plurality of XDR call tickets correspond to a target cell; performing quality difference accumulation statistics on the target cell according to a quality difference judgment rule and time information carried in time fields of a plurality of XDR call tickets; and determining whether the target cell is a poor cell or not according to the result of the quality difference accumulation statistics. By adopting the embodiment of the invention, the cell with the data service quality problem can be efficiently and accurately positioned.
Description
Technical Field
The present invention relates to the field of mobile communications technologies, and in particular, to a method and an apparatus for determining a quality difference cell.
Background
With The development of 4G Mobile Communication Technology (The 4Generation Mobile Communication Technology), 4G Mobile Communication networks (4G networks for short) are continuously constructed, modified and upgraded, so that Mobile data services based on 4G networks are rapidly developed. With such development, users have increasingly demanded mobile internet services, and thus have made higher demands on mobile communication networks. Because the 4G network is an all-IP (Internet Protocol) data switching network with a flat structure, some conventional schemes for testing, evaluating and monitoring the 4G data services are no longer applicable, and the conventional schemes require a large amount of manpower and material resources, are time-consuming and labor-consuming, have low efficiency and are not high in accuracy.
Therefore, it is desirable to provide a solution for determining poor cells to efficiently and accurately locate cells with data quality problems.
Disclosure of Invention
The embodiment of the invention provides a method and a device for determining a poor cell, which are used for solving the problems of time and labor consumption, low efficiency and low accuracy of positioning of a poor cell of a data service.
In order to solve the technical problem, the invention is realized as follows:
in a first aspect, a method for determining a quality difference cell is provided, the method including:
acquiring a plurality of extensible detailed list interfaces (XDR) call tickets of a full-network full-volume user within a preset time length, wherein the plurality of XDR call tickets correspond to a target cell;
performing quality difference accumulation statistics on the target cell according to a quality difference judgment rule and time information carried in the time fields of the plurality of XDR call tickets;
and determining whether the target cell is a quality difference cell or not according to the result of the quality difference accumulation statistics.
In a second aspect, an apparatus for determining a quality difference cell is provided, the apparatus comprising:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring a plurality of extensible detailed list interfaces (XDR) call tickets of a full-network full-volume user within a preset time length, and the XDR call tickets correspond to a target cell;
the statistical module is used for carrying out quality difference accumulation statistics on the target cell according to a quality difference judgment rule and the time information carried in the time fields of the plurality of XDR call tickets;
and the determining module is used for determining whether the target cell is the poor cell according to the result of the poor accumulation statistics.
In a third aspect, an electronic device is provided, comprising a processor, a memory and a computer program stored on the memory and executable on the processor, the computer program, when executed by the processor, implementing the steps of the method according to the first aspect.
In a fourth aspect, a computer-readable storage medium is provided, on which a computer program is stored, which computer program, when being executed by a processor, carries out the steps of the method according to the first aspect.
In the embodiment of the invention, after a plurality of XDR call tickets corresponding to a target cell in a preset time length of a whole network user are obtained, quality difference accumulation statistics is carried out on the target cell according to a quality difference judgment rule and time information carried in time fields of the plurality of XDR call tickets, and whether the target cell is the quality difference cell is further determined according to a quality difference accumulation statistical result. Therefore, by carrying out big data summarization on XDR (X data reduction) call tickets for all users in the whole network and summarizing the cells where the users are located, the obtained XDR call tickets can cover all the users and the cells, omission is avoided, and further for each target cell, the quality difference accumulation statistics on the target cells in the time granularity is realized by combining the corresponding quality difference judgment rule and the time information corresponding to a plurality of XDR call tickets of multiple users in a certain time granularity, the user perception of using data services by the cell users can be truly embodied, namely whether the quality problem of the data services exists in the cell can be accurately embodied, a large amount of manpower and material resources do not need to be input, the analysis efficiency is improved, and whether the cell is the quality difference cell is accurately and efficiently evaluated.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention and not to limit the invention. In the drawings:
fig. 1 is a flowchart illustrating a method for determining a poor cell according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a device for determining a poor cell in an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an electronic device in an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
For the problem that the conventional service testing, evaluating and monitoring scheme stated in the background section is not suitable for 4G data services, at present, the problem of poor perception of 4G data services is generally found through three ways, including:
(1) and filtering out the cells with unqualified indexes by using day as granularity or week as granularity through index analysis and monitoring. The method is mainly characterized in that the matching degree of the analysis indexes is matched, and problem cells need to be filtered out through manual summary indexes according to rules. However, at present, a one-to-one determination rule cannot be obtained according to the indexes and the perception problem, that is, a simple corresponding relationship cannot be obtained, and meanwhile, the root cause of the perception problem cannot be determined according to limited index missing.
(2) And directly positioning the cell with poor user perception of the 4G data service through an electronic map by combining the drive test data with an HTTP (Hyper Text Transport Protocol) table. The method can accurately find the problem cell, and is the most commonly adopted problem finding means at present. However, the drive test mainly focuses on the test of the key roads, cells and other cells in a small range, and cannot cover all the cells, so that omission is inevitably caused, and particularly, test data cannot be collected at indoor sites. And if the test analysis of all cells is to be realized, the investment of large labor and material cost is needed, and the efficiency is low.
(3) And analyzing the complaint worksheet table directly fed back by the user, specifically extracting key information in the complaint worksheet table, summarizing the key information to obtain a perception problem table, and counting problem users and cells perceiving the 4G data service according to the perception problem table. However, in this manner, the information contained in the complaint work order table of a single user may not only be limited to the 4G data service, but also include a voice service, and the like, and the critical information in the complaint work order table is used to judge the 4G data service, so that the information is excessively redundant and is not beneficial to quickly sensing the problem, and in addition, background monitoring data and drive test data are required to be provided for assistance during the judgment, which may consume more manpower and material resources.
Therefore, it is desirable to provide a solution for determining poor cells to efficiently and accurately locate cells with data quality problems.
The technical solutions provided by the embodiments of the present invention are described in detail below with reference to the accompanying drawings.
Referring to fig. 1, an embodiment of the present invention provides a method for determining a poor cell. The method may specifically comprise:
step S101: and acquiring a plurality of extensible detailed list interfaces (XDR) call tickets of the whole network full users within a preset time length, wherein the plurality of XDR call tickets correspond to the target cell.
Alternatively, the preset time period may be a value less than or equal to 60 minutes, such as 30 minutes, 15 minutes, 10 minutes, 5 minutes, or 3 minutes; in the embodiment of the present invention, the granularity of the preset duration may be appropriately selected to be smaller when the conditions such as the computing capability allow.
Optionally, the expandable single-ported XDR ticket is a ticket based on the hypertext transfer protocol HTTP.
Step S103: and performing quality difference accumulation statistics on the target cell according to the quality difference judgment rule and the time information carried in the time fields of the plurality of XDR call tickets.
Step S105: and determining whether the target cell is a poor cell or not according to the result of the quality difference accumulation statistics.
In the embodiment of the invention, after a plurality of XDR call tickets corresponding to a target cell in a preset time length of a whole network user are obtained, quality difference accumulation statistics is carried out on the target cell according to a quality difference judgment rule and time information carried in time fields of the plurality of XDR call tickets, and whether the target cell is the quality difference cell is further determined according to a quality difference accumulation statistical result. Therefore, by carrying out big data summarization on XDR (X data reduction) call tickets for all users in the whole network and summarizing the cells where the users are located, the obtained XDR call tickets can cover all the users and the cells, omission is avoided, and further for each target cell, the quality difference accumulation statistics on the target cells in the time granularity is realized by combining the corresponding quality difference judgment rule and the time information corresponding to a plurality of XDR call tickets of multiple users in a certain time granularity, the user perception of using data services by the cell users can be truly embodied, namely whether the quality problem of the data services exists in the cell can be accurately embodied, a large amount of manpower and material resources do not need to be input, the analysis efficiency is improved, and whether the cell is the quality difference cell is accurately and efficiently evaluated.
The XDR ticket is a session level detailed record of a signaling process and a service transmission process generated after the XDR ticket is processed based on the internet full data, all internet access information of a user is contained, and the ticket content is rich and wide, so that the ticket contains very rich data analysis and mining values. Therefore, the XDR ticket of the whole network full quantity user is used as a data basis for evaluating whether the cell is a poor cell, which is beneficial to realizing deep analysis and mining of the cell data service quality, thereby ensuring the accuracy of analysis.
Optionally, in the method for determining a poor cell according to the embodiment of the present invention, step S103 may be specifically executed as:
determining a first XDR call ticket and a second XDR call ticket which access the same website and have the same user identification in a plurality of XDR call tickets;
if the first time information carried in the time field of the first XDR ticket and the second time information carried in the time field of the second XDR ticket meet the quality difference judgment rule, adding 1 to the count of the quality difference accumulation statistics;
and repeating the process until a plurality of XDR call tickets are traversed so as to complete the quality difference accumulation statistics of the target cell.
It can be understood that, when the quality difference accumulation statistics is performed on the target cell, the multiple XDR tickets corresponding to the target cell of the full-network full-quantity user within the preset time duration are traversed, specifically, for any two first XDR tickets and second XDR tickets which access the same website and correspond to the same user, an operation of judging whether the first time information and the second time information respectively carried by the respective time fields meet the quality difference judgment rule is performed, and when it is determined that a pair of the first time information and the second time information meet the quality difference judgment rule, the count of the quality difference accumulation statistics is increased by 1. Therefore, the condition that the same user visits the same website for multiple times in a short time in the whole network of users can be counted first, and then the condition is summarized to the target cell so as to complete the quality difference accumulation statistics of the target cell, and further the accurate quality difference cell judgment can be carried out on the behavior that the user visits the same website for multiple times in the target cell.
When the user identification corresponding to the first XDR ticket and the second XDR ticket is obtained, the user identification can be obtained based on the user number field of the first XDR ticket and the user identification corresponding to the second XDR ticket; specifically, the Subscriber Identification information carried by the Subscriber Number field may include an MSISDN (Mobile Subscriber International ISDN (Integrated services digital Network, Integrated services digital Network) Number, a Mobile station International Subscriber Identity), an IMSI (International Mobile Subscriber Identity), or an IMEI (International Mobile Equipment Identity). In addition, based on the respective cell fields of the users of the first XDR ticket and the second XDR ticket, the XDR tickets corresponding to the same target cell can be gathered together.
Optionally, in specific implementation, the obtained multiple XDR tickets of the whole network user may be collected according to the user identifier, and then all the XDR tickets of each user are arranged according to the starting time sequence of the tickets, so as to determine in sequence whether the time information corresponding to two XDR tickets accessing the same website respectively meets the quality difference determination rule, thereby facilitating to improve the efficiency of quality difference accumulation statistics on the target cell.
Optionally, when the time information carried in the time field of the XDR ticket includes an access start time and an access end time for a website, specifically for a first XDR ticket and a second XDR ticket that access the same website and have the same user identifier, that is, a first time information carried in the time field of the first XDR ticket includes a first access start time and a first access end time, and a second time information carried in the time field of the second XDR ticket includes a second access start time and a second access end time, the method for determining a quality difference cell according to the embodiment of the present invention further includes a step of determining whether the first time information and the second time information satisfy a quality difference determination rule, and may specifically perform:
determining a first interval duration between a first access ending time and a first access starting time and a second interval duration between a second access ending time and a second access starting time;
determining a third interval duration between the first XDR call ticket and the second XDR call ticket according to the first time information and the second time information;
and if the first interval duration and the second interval duration are both greater than the first duration threshold and the third interval duration is less than the second duration threshold, determining that the first time information and the second time information meet the quality difference judgment rule.
It can be understood that if the interval duration of two XDR tickets for the same website by the same user is less than the second duration threshold, that is, the user frequently accesses the same website in a short time, and the duration used by the two XDR tickets when accessing the same website is greater than the first duration threshold, that is, the elapsed time is too long from the moment of initiating access to the website (i.e., the access start moment) to the moment of receiving a response to the website (i.e., the access end moment), it may be said that data service perception is not good, that is, the first time information and the second time information corresponding to the first XDR ticket and the second XDR ticket respectively satisfy the quality difference determination rule, and further, the count of the quality difference accumulation statistics of the target cell may be increased by 1.
Optionally, the third interval duration may be an interval duration between the second access start time and the first access start time, or an interval duration between the second access start time and the first access end time.
Optionally, values of the first duration threshold and the second duration threshold may be adjusted according to actual needs; specifically, the application type field of each XDR ticket carries the service type information accessed by the user, such as video service, instant messaging service, and general web browsing service, and different first and second duration thresholds can be used based on different service types.
Optionally, in the method for determining a poor cell according to the embodiment of the present invention, for step S105, based on the result of different accumulated statistics of the poor cell, the scheme for determining whether the target cell is the poor cell may be implemented as different specific embodiments, so as to ensure the diversity and accuracy of the scheme for determining the poor cell.
In an embodiment, the step S105 may be specifically executed as:
determining the proportion of the user perception problem of the target cell according to the result of the quality difference accumulation statistics and the total amount of the call tickets of the target cell within the preset time;
and under the condition that the user perception problem proportion is greater than a first preset proportion, determining the target cell as a poor quality cell.
It can be understood that the user perception problem proportion of the target cell is determined based on the counting result of the quality difference accumulation statistics of the target cell by the plurality of XDR telephone bills of the whole network full-volume user and the ratio of the total telephone bills corresponding to the target cell in the preset time length, so that the target cell can be determined as the quality difference cell when the user perception problem proportion exceeds the corresponding proportion threshold value, that is, when the user perception of the plurality of telephone bills of the target cell is not good. Therefore, the user perception quantitative evaluation is realized by setting the preset proportion for evaluating the user perception in the quality difference cell, and the accuracy of determining the quality difference cell is improved.
In another specific embodiment, in a case that the count of the quality difference accumulation statistics includes a first count of the accumulation statistics on the data service awareness problem and a second count of the accumulation statistics on the network coverage awareness problem, if the first time information carried in the time field of the first XDR ticket and the second time information carried in the time field of the second XDR ticket satisfy the quality difference determination rule, the step of adding 1 to the count of the quality difference accumulation statistics may be specifically performed as:
if the first time information and the second time information meet the quality difference judgment rule and the first network type of the first XDR ticket is the same as the second network type of the second XDR ticket, adding 1 to the first count;
and if the first time information and the second time information meet the quality difference judgment rule and the first network type is different from the second network type, adding 1 to the second count.
It can be understood that, when performing the quality difference accumulation statistics on the target cell, in order to further improve the accuracy of the user perception problem evaluation on the data service of the target network type, the quality difference accumulation statistics may be respectively implemented for different network types, specifically, the statistical counting of the data service perception problem corresponding to the first network type and the statistical counting of the network coverage perception problem corresponding to the second network type may be implemented.
Optionally, the first network type includes a 4G network, and the second network type includes at least one of a 2G network and a 3G network.
It should be noted that, in the embodiment of the present invention, the statistical counting of the user perception problems of different network types is implemented, and the statistical counting of the user perception problems of other network types is also applicable to the scheme of the embodiment of the present invention, so as to finally realize the judgment whether the cell is the poor cell.
Further, step S105 may specifically be implemented as: and determining whether the target cell is a poor cell according to the result of the first counting or the result of the second counting.
Optionally, the step of determining whether the target cell is the poor cell according to the result of the first counting or the result of the second counting may be specifically performed as:
determining the proportion of the data service perception problem of the target cell according to the result of the first counting and the total call bill amount of the target cell within a preset time length;
determining the proportion of the network coverage perception problem of the target cell according to the second counting result and the total call ticket amount of the target cell within the preset time length;
and under the condition that the data service perception problem proportion is larger than a second preset proportion or the network coverage perception problem proportion is larger than a third preset proportion, determining the target cell as a poor cell.
It can be understood that, the counting result of the accumulated statistics of the data service perception problem and the network coverage perception problem of the target cell based on the multiple XDR tickets of the whole network user can be respectively determined according to the ratio of the total amount of the tickets of the target cell within the preset time, and the data service perception problem proportion and the network coverage perception problem proportion of the target cell can be respectively determined, so that the target cell can be determined as a poor cell when the data service perception problem proportion or the network coverage perception problem proportion exceeds the corresponding proportion threshold, that is, when the data service user perception or the network coverage user perception of the multiple tickets of the target cell is not good. Therefore, by setting the preset proportion for evaluating data service perception or network coverage perception in the poor quality cell, quantitative evaluation of the data service perception or the network coverage perception is realized, and the accuracy of determining the poor quality cell is improved.
It should be noted that, in any of the above embodiments, the number of samples collected in the target cell may be required, for example, to be greater than a certain number threshold, even if the sampling rate reaches a certain value, the number of sampling points is guaranteed, so as to achieve large data evaluation.
Optionally, in a case that the target cell is determined to be the poor quality cell, the method for determining the poor quality cell according to the embodiment of the present invention may further include:
and monitoring the change condition of the key performance index of the target cell.
It can be understood that, after determining the poor quality cell according to the above-mentioned scheme, the change conditions of various network indexes such as key performance indexes of the target cell, such as a call completing rate, a call dropping rate, an average network download rate, an uplink packet loss rate, a downlink packet loss rate, and the like, can be monitored by comprehensively using an index monitoring mode, so that the target cell determined as the poor quality cell is certified at a cell granularity level by different poor quality cell evaluation modes, thereby avoiding misjudgment of an error cell and further improving the accuracy of determination of the poor quality cell.
To sum up, the method for determining a poor cell according to the embodiment of the present invention starts with analysis of customer behavior, and is closer to the user perception situation through big data statistics, specifically, first extracts a full-network user hour granularity HTTP table, and establishes a perception data table containing necessary information, such as website access start time, website access end time, user identifier, application type, cell where the user is located, network type, user agent, and the like.
Then, the same website which is accessed by the same user for multiple times in a short time is found according to a corresponding rule, the behavior that the user accesses the same website for multiple times in the short time is probably caused by poor perception of data service (such as 4G data service), and the corresponding cell can be used as a suspected data service poor cell by converging the user problem to the corresponding cell granularity, namely, the interference is eliminated by counting the short-term repeated website access behavior of the user, and a judgment result is output after the rule processing; the quality difference cell is judged to have higher misjudgment rate through a single HTTP table, the total number of suspected data service perception problems of each cell is obtained by collecting big data of all users in the whole network, screening according to a set rule and overlapping perception data tables according to the cells, and the cell is judged to be a 4G data service quality difference cell when the number of suspected data service perception problems exceeds a set threshold; in addition, if the network type to which the secondary access website of the user belongs is a non-4G network in the sensing data table, it indicates that the problem of 4G signal coverage is a main cause, so the sensing data table needs to be classified more finely, and finally, after summary analysis, the output result is divided into two categories, namely poor quality of network coverage cause (such as redirection to 2G/3G) and poor quality of 4G data service. Therefore, some hidden faults existing in the current network can be found, for example, all indexes of a cell reach the standard but 4G data service perception is poor, and a feasible method is provided for problem location of the 4G network.
Referring to fig. 2, an embodiment of the present invention further provides a device for determining a poor cell, which may specifically include:
an obtaining module 201, configured to obtain multiple XDR tickets of a full-network full-volume user within a preset duration, where the multiple XDR tickets correspond to a target cell;
the statistical module 203 is used for performing quality difference accumulation statistics on the target cell according to the quality difference judgment rule and the time information carried in the time fields of the plurality of XDR call tickets;
the determining module 205 is configured to determine whether the target cell is a poor cell according to a result of the poor accumulation statistics.
Preferably, in the apparatus for determining a poor cell according to the embodiment of the present invention, the statistical module 203 may be specifically configured to:
determining a first XDR call ticket and a second XDR call ticket which access the same website and have the same user identification in a plurality of XDR call tickets;
if the first time information carried in the time field of the first XDR ticket and the second time information carried in the time field of the second XDR ticket meet the quality difference judgment rule, adding 1 to the count of the quality difference accumulation statistics;
and repeating the process until a plurality of XDR call tickets are traversed so as to complete the quality difference accumulation statistics of the target cell.
Preferably, in the apparatus for determining a poor cell according to the embodiment of the present invention, the first time information includes a first access start time and a first access end time, and the second time information includes a second access start time and a second access end time;
the apparatus for determining a poor cell may further include a determining module, where the determining module may be specifically configured to:
determining a first interval duration between a first access ending time and a first access starting time and a second interval duration between a second access ending time and a second access starting time;
determining a third interval duration between the first XDR call ticket and the second XDR call ticket according to the first time information and the second time information;
and if the first interval duration and the second interval duration are both greater than the first duration threshold and the third interval duration is less than the second duration threshold, determining that the first time information and the second time information meet the quality difference judgment rule.
Preferably, in the apparatus for determining a poor cell according to the embodiment of the present invention, the determining module 205 may be specifically configured to:
determining the proportion of the user perception problem of the target cell according to the result of the quality difference accumulation statistics and the total amount of the call tickets of the target cell within the preset time;
and under the condition that the user perception problem proportion is greater than a first preset proportion, determining the target cell as a poor quality cell.
Preferably, in the apparatus for determining a poor quality cell provided in the embodiment of the present invention, the count of the poor quality cumulative statistics includes a first count of performing cumulative statistics on a data service awareness problem and a second count of performing cumulative statistics on a network coverage awareness problem;
wherein, the judging module may be further specifically configured to:
if the first time information and the second time information meet the quality difference judgment rule and the first network type of the first XDR ticket is the same as the second network type of the second XDR ticket, adding 1 to the first count;
if the first time information and the second time information meet the quality difference judgment rule and the first network type is different from the second network type, adding 1 to the second count; and
the determining module 205 may be further specifically configured to:
and determining whether the target cell is a poor cell according to the result of the first counting or the result of the second counting.
Preferably, in the apparatus for determining a poor cell according to the embodiment of the present invention, the determining module 205 may further be specifically configured to:
determining the proportion of the data service perception problem of the target cell according to the result of the first counting and the total call bill amount of the target cell within a preset time length;
determining the proportion of the network coverage perception problem of the target cell according to the second counting result and the total call ticket amount of the target cell within the preset time length;
and under the condition that the data service perception problem proportion is larger than a second preset proportion or the network coverage perception problem proportion is larger than a third preset proportion, determining the target cell as a poor cell.
Preferably, in the apparatus for determining a poor cell according to the embodiment of the present invention, the first network type includes a 4G network, and the second network type includes at least one of a 2G network and a 3G network.
It can be understood that the determining apparatus for a poor quality cell provided in the embodiment of the present invention can implement each process of the foregoing determining method for a poor quality cell, and the related explanations regarding the determining method for a poor quality cell are all applicable to the determining apparatus for a poor quality cell, and are not described herein again.
In the embodiment of the invention, after a plurality of XDR call tickets corresponding to a target cell in a preset time length of a whole network user are obtained, quality difference accumulation statistics is carried out on the target cell according to a quality difference judgment rule and time information carried in time fields of the plurality of XDR call tickets, and whether the target cell is the quality difference cell is further determined according to a quality difference accumulation statistical result. Therefore, by carrying out big data summarization on XDR (X data reduction) call tickets for all users in the whole network and summarizing the cells where the users are located, the obtained XDR call tickets can cover all the users and the cells, omission is avoided, and further for each target cell, the quality difference accumulation statistics on the target cells in the time granularity is realized by combining the corresponding quality difference judgment rule and the time information corresponding to a plurality of XDR call tickets of multiple users in a certain time granularity, the user perception of using data services by the cell users can be truly embodied, namely whether the quality problem of the data services exists in the cell can be accurately embodied, a large amount of manpower and material resources do not need to be input, the analysis efficiency is improved, and whether the cell is the quality difference cell is accurately and efficiently evaluated.
Fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application. Referring to fig. 3, at a hardware level, the electronic device includes a processor, and optionally further includes an internal bus, a network interface, and a memory. The Memory may include a Memory, such as a Random-Access Memory (RAM), and may further include a non-volatile Memory, such as at least 1 disk Memory. Of course, the electronic device may also include hardware required for other services.
Optionally, the electronic device may be a server.
The processor, the network interface, and the memory may be connected to each other via an internal bus, which may be an ISA (Industry Standard Architecture) bus, a PCI (peripheral component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 3, but this does not indicate only one bus or one type of bus.
And the memory is used for storing programs. In particular, the program may include program code comprising computer operating instructions. The memory may include both memory and non-volatile storage and provides instructions and data to the processor.
The processor reads the corresponding computer program from the nonvolatile memory into the memory and then runs the computer program to form the determining device of the quality difference cell on the logic level. The processor is used for executing the program stored in the memory and is specifically used for executing the following operations:
acquiring a plurality of extensible detailed list interfaces (XDR) call tickets of a full-network full-volume user within a preset time length, wherein the plurality of XDR call tickets correspond to a target cell;
performing quality difference accumulation statistics on the target cell according to a quality difference judgment rule and time information carried in time fields of a plurality of XDR call tickets;
and determining whether the target cell is a poor cell or not according to the result of the quality difference accumulation statistics.
In the embodiment of the invention, after a plurality of XDR call tickets corresponding to a target cell in a preset time length of a whole network user are obtained, quality difference accumulation statistics is carried out on the target cell according to a quality difference judgment rule and time information carried in time fields of the plurality of XDR call tickets, and whether the target cell is the quality difference cell is further determined according to a quality difference accumulation statistical result. Therefore, by carrying out big data summarization on XDR (X data reduction) call tickets for all users in the whole network and summarizing the cells where the users are located, the obtained XDR call tickets can cover all the users and the cells, omission is avoided, and further for each target cell, the quality difference accumulation statistics on the target cells in the time granularity is realized by combining the corresponding quality difference judgment rule and the time information corresponding to a plurality of XDR call tickets of multiple users in a certain time granularity, the user perception of using data services by the cell users can be truly embodied, namely whether the quality problem of the data services exists in the cell can be accurately embodied, a large amount of manpower and material resources do not need to be input, the analysis efficiency is improved, and whether the cell is the quality difference cell is accurately and efficiently evaluated.
The method performed by the determining apparatus for poor quality cells as disclosed in the embodiment of fig. 1 of the present application may be applied to or implemented by a processor. The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The various methods, steps, and logic blocks disclosed in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor.
The electronic device may further execute the method executed by the device for determining a poor quality cell in fig. 1, and implement the functions of the device for determining a poor quality cell in the embodiment shown in fig. 1, which are not described herein again.
An embodiment of the present application further provides a computer-readable storage medium storing one or more programs, where the one or more programs include instructions, which, when executed by an electronic device including multiple application programs, enable the electronic device to perform a method performed by the determining device for the poor quality cell in the embodiment shown in fig. 1, and are specifically configured to perform:
acquiring a plurality of extensible detailed list interfaces (XDR) call tickets of a full-network full-volume user within a preset time length, wherein the plurality of XDR call tickets correspond to a target cell;
performing quality difference accumulation statistics on the target cell according to a quality difference judgment rule and time information carried in time fields of a plurality of XDR call tickets;
and determining whether the target cell is a poor cell or not according to the result of the quality difference accumulation statistics.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention 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.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. 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 apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, 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 apparatus 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 apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus 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 apparatus. 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 apparatus that comprises the element.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, 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, 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.
The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (10)
1. A method for determining a poor cell, the method comprising:
acquiring a plurality of extensible detailed list interfaces (XDR) call tickets of a full-network full-volume user within a preset time length, wherein the plurality of XDR call tickets correspond to a target cell;
performing quality difference accumulation statistics on the target cell according to a quality difference judgment rule and time information carried in the time fields of the plurality of XDR call tickets;
and determining whether the target cell is a quality difference cell or not according to the result of the quality difference accumulation statistics.
2. The method of claim 1, wherein the performing quality difference accumulation statistics on the target cell according to the quality difference determination rule and the time information carried in the time fields of the plurality of XDR tickets comprises:
determining a first XDR ticket and a second XDR ticket which access the same website and have the same user identification in the plurality of XDR tickets;
if the first time information carried in the time field of the first XDR ticket and the second time information carried in the time field of the second XDR ticket meet the quality difference judgment rule, adding 1 to the count of the quality difference accumulation statistics;
and repeating the process until the plurality of XDR call tickets are traversed so as to complete the quality difference accumulation statistics of the target cell.
3. The method of claim 2, wherein the first time information comprises a first visit start time and a first visit end time, and wherein the second time information comprises a second visit start time and a second visit end time;
wherein the method further comprises:
determining a first interval duration between the first access ending time and the first access starting time and a second interval duration between the second access ending time and the second access starting time;
determining a third interval duration between the first XDR call ticket and the second XDR call ticket according to the first time information and the second time information;
and if the first interval duration and the second interval duration are both greater than a first duration threshold and the third interval duration is less than a second duration threshold, determining that the first time information and the second time information meet the quality difference determination rule.
4. The method of claim 3, wherein the determining whether the target cell is a poor cell according to the result of the poor accumulation statistics comprises:
determining the proportion of the user perception problems of the target cell according to the result of the quality difference accumulation statistics and the total amount of the call tickets of the target cell in the preset time;
and determining the target cell as a poor cell under the condition that the user perception problem proportion is greater than a first preset proportion.
5. The method of claim 3, wherein the count of the quality difference accumulation statistics comprises a first count of the accumulation statistics of data traffic awareness issues and a second count of the accumulation statistics of network coverage awareness issues;
wherein, if the first time information carried in the time field of the first XDR ticket and the second time information carried in the time field of the second XDR ticket satisfy the quality difference determination rule, adding 1 to the count of the quality difference accumulation statistics, including:
if the first time information and the second time information meet a quality difference judgment rule, and a first network type of the first XDR ticket is the same as a second network type of the second XDR ticket, adding 1 to the first count;
if the first time information and the second time information meet a quality difference judgment rule and the first network type is different from the second network type, adding 1 to the second count;
wherein, the determining whether the target cell is a poor cell according to the counting result of the poor accumulation statistics includes:
and determining whether the target cell is a poor cell according to the result of the first counting or the result of the second counting.
6. The method of claim 5, wherein determining whether the target cell is a poor cell according to the result of the first count or the result of the second count comprises:
determining the proportion of the data service perception problem of the target cell according to the result of the first counting and the total call bill amount of the target cell in the preset time;
determining the proportion of the network coverage perception problem of the target cell according to the second counting result and the total call bill amount of the target cell within the preset time length;
and determining the target cell as a poor cell under the condition that the data service perception problem proportion is greater than a second preset proportion or the network coverage perception problem proportion is greater than a third preset proportion.
7. The method according to claim 5 or 6,
the first network type includes a 4G network and the second network type includes at least one of a 2G network and a 3G network.
8. An apparatus for determining a quality difference cell, the apparatus comprising:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring a plurality of extensible detailed list interfaces (XDR) call tickets of a full-network full-volume user within a preset time length, and the XDR call tickets correspond to a target cell;
the statistical module is used for carrying out quality difference accumulation statistics on the target cell according to a quality difference judgment rule and the time information carried in the time fields of the plurality of XDR call tickets;
and the determining module is used for determining whether the target cell is the poor cell according to the result of the poor accumulation statistics.
9. An electronic device, comprising: memory, processor and computer program stored on the memory and executable on the processor, which computer program, when executed by the processor, carries out the steps of the method according to any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, which computer program, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910289792.1A CN111818560A (en) | 2019-04-11 | 2019-04-11 | Method and device for determining poor quality cell |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910289792.1A CN111818560A (en) | 2019-04-11 | 2019-04-11 | Method and device for determining poor quality cell |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111818560A true CN111818560A (en) | 2020-10-23 |
Family
ID=72844472
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910289792.1A Pending CN111818560A (en) | 2019-04-11 | 2019-04-11 | Method and device for determining poor quality cell |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111818560A (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113365306A (en) * | 2021-06-30 | 2021-09-07 | 中国电信股份有限公司 | Network analysis method and device, storage medium and computer system |
| CN113453261A (en) * | 2021-06-25 | 2021-09-28 | 维沃移动通信有限公司 | Abnormal cell identification method and device and electronic equipment |
| CN114363194A (en) * | 2021-12-28 | 2022-04-15 | 中国电信股份有限公司 | Hidden danger analysis method and device for network equipment, electronic equipment and storage medium |
| CN114449564A (en) * | 2022-03-30 | 2022-05-06 | 中国联合网络通信集团有限公司 | Method, device and equipment for detecting performance failure cell |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150098352A1 (en) * | 2013-10-08 | 2015-04-09 | Tektronix, Inc. | Determining quality of experience confidence level for mobile subscribers |
| CN106878946A (en) * | 2017-02-16 | 2017-06-20 | 山东浪潮商用系统有限公司 | High ferro user identification method based on movement locus |
| CN107094301A (en) * | 2016-02-18 | 2017-08-25 | 中国移动通信集团福建有限公司 | Determine the method and apparatus that community user is perceived |
| CN108391223A (en) * | 2018-02-12 | 2018-08-10 | 中国联合网络通信集团有限公司 | A kind of method and device of determining lost contact user |
| CN108513313A (en) * | 2017-02-27 | 2018-09-07 | 中国移动通信集团北京有限公司 | One germplasm difference cell determining method and equipment |
| CN109005556A (en) * | 2018-07-24 | 2018-12-14 | 武汉虹信技术服务有限责任公司 | A kind of 4G network quality optimization method and system based on user bill |
-
2019
- 2019-04-11 CN CN201910289792.1A patent/CN111818560A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150098352A1 (en) * | 2013-10-08 | 2015-04-09 | Tektronix, Inc. | Determining quality of experience confidence level for mobile subscribers |
| CN107094301A (en) * | 2016-02-18 | 2017-08-25 | 中国移动通信集团福建有限公司 | Determine the method and apparatus that community user is perceived |
| CN106878946A (en) * | 2017-02-16 | 2017-06-20 | 山东浪潮商用系统有限公司 | High ferro user identification method based on movement locus |
| CN108513313A (en) * | 2017-02-27 | 2018-09-07 | 中国移动通信集团北京有限公司 | One germplasm difference cell determining method and equipment |
| CN108391223A (en) * | 2018-02-12 | 2018-08-10 | 中国联合网络通信集团有限公司 | A kind of method and device of determining lost contact user |
| CN109005556A (en) * | 2018-07-24 | 2018-12-14 | 武汉虹信技术服务有限责任公司 | A kind of 4G network quality optimization method and system based on user bill |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113453261A (en) * | 2021-06-25 | 2021-09-28 | 维沃移动通信有限公司 | Abnormal cell identification method and device and electronic equipment |
| CN113365306A (en) * | 2021-06-30 | 2021-09-07 | 中国电信股份有限公司 | Network analysis method and device, storage medium and computer system |
| CN114363194A (en) * | 2021-12-28 | 2022-04-15 | 中国电信股份有限公司 | Hidden danger analysis method and device for network equipment, electronic equipment and storage medium |
| CN114363194B (en) * | 2021-12-28 | 2024-04-30 | 中国电信股份有限公司 | Hidden danger analysis method and device for network equipment, electronic equipment and storage medium |
| CN114449564A (en) * | 2022-03-30 | 2022-05-06 | 中国联合网络通信集团有限公司 | Method, device and equipment for detecting performance failure cell |
| CN114449564B (en) * | 2022-03-30 | 2024-02-13 | 中国联合网络通信集团有限公司 | Method, device and equipment for detecting performance failure cell |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111818560A (en) | Method and device for determining poor quality cell | |
| CN102143507B (en) | Method and system for monitoring service quality, and analytical method and system therefor | |
| CN109327353B (en) | Service flow determination method and device and electronic equipment | |
| CN111783052B (en) | Account detection method and device | |
| CN111522711B (en) | Data monitoring processing system, method, execution end, monitoring end and electronic equipment | |
| CN101764720B (en) | Method and system for testing filtration performance | |
| CN109271453B (en) | Method and device for determining database capacity | |
| CN113411825B (en) | 5G cell positioning method and device, electronic equipment and storage medium | |
| CN111343647B (en) | Method, apparatus, device and medium for user perception evaluation | |
| CN104883705A (en) | Problem positioning method for data service complaints and device thereof | |
| CN108900339B (en) | Method and device for measuring service quality and electronic equipment | |
| CN113225218A (en) | Method and device for checking call ticket quality | |
| CN111818551A (en) | VOLTE call drop reason determination method and device | |
| CN112929238B (en) | Network information acquisition method, device and equipment and readable storage medium | |
| CN108235368B (en) | Method and device for determining wireless resources occupied by service | |
| CN113381867B (en) | Communication delay cause determining method and device, electronic equipment and storage medium | |
| CN113452533B (en) | Charging self-inspection and self-healing method and device, computer equipment and storage medium | |
| CN113727382A (en) | Network quality determination method and device, network equipment and computer storage medium | |
| CN106851604B (en) | A kind of Traffic prediction method and device of mobile communications network | |
| CN105630503A (en) | Selecting method for mobile device application and development based on operating records of user | |
| CN112752252B (en) | Cell home location identification method and device | |
| CN115696444B (en) | Time delay detection method, device, data analysis platform and readable storage medium | |
| CN105515896B (en) | A kind of judgment method and device of mobile terminal network obstruction | |
| CN111274118B (en) | Application optimization processing method, device and system | |
| CN115225936B (en) | Method, device, equipment and medium for determining definition index of video resource |
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 | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20201023 |