CN111818551A - VOLTE call drop reason determination method and device - Google Patents
VOLTE call drop reason determination method and device Download PDFInfo
- Publication number
- CN111818551A CN111818551A CN201910295889.3A CN201910295889A CN111818551A CN 111818551 A CN111818551 A CN 111818551A CN 201910295889 A CN201910295889 A CN 201910295889A CN 111818551 A CN111818551 A CN 111818551A
- Authority
- CN
- China
- Prior art keywords
- cell
- call drop
- cells
- call
- volte
- 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.)
- Granted
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/02—Arrangements for optimising operational condition
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/10—Scheduling measurement reports ; Arrangements for measurement reports
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Mobile Radio Communication Systems (AREA)
Abstract
The embodiment of the invention discloses a method for determining a dropped call reason of VOLTE, which comprises the following steps: acquiring a plurality of on-off records respectively corresponding to a plurality of VOLTE calls of a plurality of users according to a plurality of extensible detail interface XDR signaling data, wherein the plurality of VOLTE calls occur in a plurality of cells; determining a poor quality cell in a plurality of cells according to a plurality of on-off records and poor quality judgment indexes, wherein the poor quality judgment indexes comprise at least one of the total number of users in the cell, the occupation ratio of the poor quality users in the cell and the call drop rate of the cell; and determining the reason of the VOLTE call drop of the poor cell according to the call drop analysis index. By adopting the embodiment of the invention, the VOLTE call drop reason can be fully mined and accurately determined so as to effectively support network maintenance and optimization and improve the VOLTE voice call quality.
Description
Technical Field
The invention relates to the technical field of mobile communication, in particular to a method and a device for determining a VOLTE call drop reason.
Background
Currently, VOLTE (Voice over LTE (Long Term Evolution)) is a development trend of Mobile Voice Communication as a high-definition Voice service based on 4G Mobile Communication Technology (The 4Generation Mobile Communication Technology). With the development of the VOLTE voice service, the quality problem of the VOLTE voice service is more and more concerned, the VOLTE voice call quality is guaranteed, and the improvement of the user satisfaction is an urgent need of telecommunication operators.
The existing reason analysis for the abnormal call drop of the VOLTE voice service is developed based on the overall call drop rate index of the whole users, namely, the overall call drop rate of the VOLTE users is determined by calculating the ratio of the total call drop times and the total connection times which are counted. However, the quality difference reason obtained based on the analysis has great limitation, is not specific and accurate enough, and is not beneficial to improving the VOLTE voice call quality.
Disclosure of Invention
The embodiment of the invention provides an antenna engineering parameter measuring method, an antenna engineering parameter measuring device, equipment and a storage medium, which are used for solving the problem that the existing VOLTE call drop reason determining result is not accurate enough and improving VOLTE voice call quality.
In order to solve the technical problem, the invention is realized as follows:
in a first aspect, a method for determining a call drop reason of VOLTE is provided, where the method includes:
acquiring a plurality of on-off records respectively corresponding to a plurality of VOLTE calls of a plurality of users according to a plurality of extensible detail interface XDR signaling data, wherein the plurality of VOLTE calls are generated in a plurality of cells;
determining a poor cell in the plurality of cells according to the plurality of on-off records and the poor quality judgment indexes, wherein the poor quality judgment indexes comprise at least one of the total number of users in the cell, the percentage of poor quality users in the cell and the call drop rate of the cell;
and determining the reason of the VOLTE call drop of the poor cell according to the call drop analysis index.
In a second aspect, an apparatus for determining a call drop reason in VOLTE is provided, the apparatus includes:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring a plurality of on-off records respectively corresponding to a plurality of VOLTE calls of a plurality of users according to a plurality of extensible detail interface XDR signaling data, and the plurality of VOLTE calls are generated in a plurality of cells;
the first determining module is used for determining a poor cell in the plurality of cells according to the plurality of on-off records and the poor quality judging indexes, wherein the poor quality judging indexes comprise at least one of the total number of users in the cell, the occupation ratio of the poor quality users in the cell and the call drop rate of the cell;
and the second determining module is used for determining the reason of the VOLTE call drop of the poor cell according to the call drop analysis index.
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, a plurality of extensible detailed interface XDR signaling data at the bottom layer are fully mined and analyzed to obtain the on-off records of single VOLTE call of each single user in a plurality of cells, the analyzed on-off records are used as a bottom layer data source, and a quality difference cell is further screened from the plurality of cells by combining quality difference judgment indexes. Therefore, the quality difference cells are accurately judged by adopting the multiple quality difference judgment indexes, and the VOLTE call drop reason is determined based on the specific call drop analysis indexes, so that the VOLTE call drop reason is fully excavated and accurately determined, the network maintenance and optimization are effectively supported, and the VOLTE voice call quality is improved.
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 call drop reason of VOLTE in an embodiment of the present invention;
fig. 2 is a schematic diagram of a process of determining a call drop reason of VOLTE in the embodiment of the present invention;
fig. 3 is a schematic structural diagram of a VOLTE call drop reason determining apparatus in the embodiment of the present invention;
fig. 4 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 existing analysis scheme for analyzing the abnormal call drop reason of the VoLTE voice service based on the single call drop rate index stated in the background technology part, more effective information can not be provided for the network quality analysis in the big data era, and the technical requirements of intelligent operation and maintenance can not be met.
In addition, except for a mode of acquiring the overall call drop rate index of the VoLTE user, in the existing related technology, the call drop index condition of the local city user is acquired according to the difference of the statistical dimensionality of the call drop reasons. However, there are several problems:
(1) the abnormal call drop index of the VoLTE voice service with the city level granularity is suitable for examination and notification, and has great limitation when relating to more specific scenes of network abnormality monitoring and reason analysis.
(2) There are various reasons for the abnormal call drop of the VoLTE voice service, and a single call drop rate index cannot reflect more call drop reasons, so that deeper call drop reason analysis work cannot be carried out.
(3) From the networking level of the VoLTE network, a call drop abnormity analysis means from two dimensions of a core network element side and a wireless base station side is lacked.
Therefore, the existing analysis means for reasons of abnormal call drop of the VoLTE voice service is relatively stayed on the surface layer, so that the value of large data cannot be fully mined and utilized. Therefore, a scheme capable of accurately and deeply mining the reason of the VoLTE call drop is needed to be provided, so that the VoLTE voice call quality is guaranteed, and the user satisfaction is improved.
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 call drop reason of VOLTE. The method may specifically comprise:
step S101: and acquiring a plurality of on-off records respectively corresponding to a plurality of VOLTE calls of a plurality of users according to the XDR signaling data of the plurality of extensible detail interface interfaces, wherein the plurality of VOLTE calls are generated in a plurality of cells.
Step S103: and determining a poor quality cell in the plurality of cells according to the plurality of on-off records and the poor quality judgment indexes, wherein the poor quality judgment indexes comprise at least one of the total number of users in the cell, the occupation ratio of the poor quality users in the cell and the call drop rate of the cell.
Step S105: and determining the reason of the VOLTE call drop of the poor cell according to the call drop analysis index.
In the embodiment of the invention, a plurality of extensible detailed interface XDR signaling data at the bottom layer are fully mined and analyzed to obtain the on-off records of single VOLTE call of each single user in a plurality of cells, the analyzed on-off records are used as a bottom layer data source, and quality difference cells are further screened from the plurality of cells by combining quality difference judgment indexes, namely quality difference analysis is carried out on end-to-end call data based on a VOLTE network. Therefore, the quality difference cells are accurately judged by adopting the multiple quality difference judgment indexes, and the VOLTE call drop reason is determined based on the specific call drop analysis indexes, so that the VOLTE call drop reason is fully excavated and accurately determined, the network maintenance and optimization are effectively supported, and the VOLTE voice call quality is improved.
Optionally, for the method for determining a call drop reason of VOLTE in the embodiment of the present invention, in a case that the quality difference determination index includes a total number of users in a cell, a percentage of users with poor quality in the cell, and a call drop rate in the cell, the step S103 may be specifically executed as:
determining the call drop rate of each cell in the plurality of cells according to the plurality of on-off records;
and determining the cells with the call drop rate larger than the call drop rate threshold, the total number of users larger than the total number threshold and the poor user occupation ratio larger than the poor user occupation ratio threshold as the poor cells.
It can be understood that, according to the on-off records of single VOLTE calls of each single user in multiple cells, the drop call rate statistics of the cell granularity is performed, and then the poor quality cells are accurately screened by further combining the drop call rate, the total number of users and the poor quality user occupation ratio of each cell with the magnitude relations of the predetermined drop call rate threshold, the total number of users threshold and the poor quality user occupation ratio threshold.
The cell call drop rate can be hour granularity or minute granularity, and statistics is carried out according to actual requirements.
Further optionally, the percentage of the total number of the poor quality cells to the total number of the plurality of cells is a preset value, and the preset value is equal to the product of the first proportion, the second proportion and the third proportion;
wherein the first proportion is the ratio of the total number of the first cells with the call drop rate larger than the call drop rate threshold in the plurality of cells to the total number of the plurality of cells,
the second ratio is the ratio of the total number of the second cells to the total number of the first cells, wherein the total number of the users in the first cells is larger than the threshold of the total number of the users,
the third ratio is the ratio of the total number of the third cells with the poor quality user occupation ratio larger than the poor quality user occupation ratio threshold in the second cell to the total number of the second cells.
It is understood that, in order to ensure that the poor quality cells are accurately screened from the plurality of cells as the screening samples, the selection of the drop call rate threshold, the total number of users threshold and the poor quality user ratio threshold preferably needs to make the proportion of the poor quality cells screened based on the selection reach a certain preset value, such as 0.1%.
The process of determining the threshold may be described with reference to a specific example, specifically, a certain amount of sample space is screened out, a list of cells at about 200000 different times is obtained, a user-level drop call rate indicator condition is obtained, and a 0.1% cell meeting the quality difference threshold is obtained according to the daily maintenance experience and the indicator condition. Wherein, the threshold of the call drop rate is set as x%, the threshold of the total number of users is set as y, and the threshold of the proportion of poor quality users is set as z%, the related weight parameters are as follows:
xi: the percentage of the number of cells with the call drop rate of > x%;
v: the total number of users in the cell is larger than the number of cells in y;
ζ: the percentage of users with poor quality in the cell is greater than z% of the number of the cells;
it can be seen that the screening rule from the poor quality cell is: n is m × ξ × ν × ζ.
Specifically, when the number of cells whose call drop rate is larger than x% is 7824 in the overall sample space (i.e., m) of 200000, ξ is 3.9%, when the number of cells whose total number of users in the cells satisfying y in 7824 is 7015, ν is 90%, the number of cells whose percentage of users in the cells satisfying z% in 7015 is 231, and ν is 3.3%, ξ × ν × ζ is 0.001. I.e., the threshold values of x, y, and z, should be able to screen about 0.1% of the abnormal cell list from the full cell list and make the value xi x ν x ζ be 0.1%.
Optionally, the drop call analysis indicator includes: at least one of the evaluation indexes of abnormal call drop type of the cell, the call drop rate of county granularity, the call drop rate of core network element granularity, the call drop rate of wireless manufacturer granularity, the call drop rate of terminal type granularity, the user occupation ratio of poor quality in the cell and the time granularity of the cell;
the abnormal call drop type of the cell is determined based on a plurality of XDR signaling data, and the county granularity call drop rate, the core network element granularity call drop rate, the wireless manufacturer granularity call drop rate, the terminal type granularity call drop rate, the poor user occupation ratio in the cell and the cell time granularity evaluation index are determined based on a plurality of on-off records.
It can be understood that, besides being used as underlying data of a plurality of on-off records, a plurality of XDR signaling data may also determine specific types of abnormal call drops based on analysis of the plurality of XDR signaling data, and further may perform cell granularity summarization based on the specific abnormal call drops to determine the abnormal call drop type of the cell, for example, determine the specific call drop type with the highest frequency of occurrence in each cell as the abnormal call drop type of the cell corresponding to the cell. The call drop rate of the cell granularity can be determined in a summarizing mode based on the plurality of on-off records, and the call drop rate and the cell time granularity evaluation indexes of the district granularity, the core network element granularity, the wireless manufacturer granularity and the terminal type granularity can be further determined in a summarizing mode.
The call drop rate comprises a calling call drop rate and a called call drop rate.
Similarly, it may also be determined whether the user is a poor user based on the call drop condition of each user in the cell, for example, when the call drop ratio of the user reaches a certain value, the user may be regarded as a poor user, so that the poor user ratio may be determined.
Optionally, the abnormal call drop type of the cell includes: at least one of a long term evolution, LTE, tear down, an enhanced single radio voice call continuity, eSRVCC, failure, media flow disruption, and registration timeout.
It should be noted that, in the embodiment of the present invention, the abnormal call drop types of the cell, except for the four abnormal call drop types, may be collectively classified as other abnormal call drop types.
Optionally, the granularity call drop rate of the core network element includes: at least one of a proxy call session control function P-CSCF network element granularity drop rate, a serving call session control function S-CSCF network element granularity drop rate, and an enhanced mobile switching center eMSC network element granularity drop rate.
Optionally, the cell time granularity evaluation index includes: at least one of a cell day granularity call drop rate, a cell full-day poor quality duration, and a number of days in which a call drop anomaly exists in a cell within a preset period.
Further, the scheme of step S105 will be described with reference to fig. 2. Specifically, for a poor quality cell, a possible reason of the poor quality can be preliminarily obtained after transverse comparison according to a single variable principle, as shown in fig. 2, a general conclusion is finally obtained mainly by analyzing and judging the obtainable dimensions of the cell, county, time, wireless manufacturer, user, dropped call type and core network element.
For example, as can be seen from the hour call drop rate index of the cell in fig. 2, the cell is a poor quality cell with abnormal call drops, and the cell is abnormal all day long, it is possible to compare in the same direction whether other cells in the same county are abnormal or not in the hour, if the other cells are not abnormal, it indicates that the single cell is abnormal, and if the other cells are also abnormal, it indicates that the cells in the county are abnormal and general; for the index of the call drop rate of the hour granularity of the same wireless manufacturer in the same county, judging whether the call drop rates of the hour granularity of all the wireless manufacturers A in the county are abnormal in the hour, if so, indicating that the wireless manufacturers have problems, otherwise, judging whether the index of the call drop rate of the hour granularity of other wireless manufacturers in the county is abnormal, and judging whether the index is a problem of a district in the county; for other indexes, the process of transverse comparison is similar to that described above according to the principle of single variable.
For each index in fig. 2, where the hour index for the cell: judging the index of abnormal call drop rate of the cell; the main call drop types: counting the call drop type with the largest proportion, and assisting in judging whether a certain signaling flow is abnormal or not, so that the proportion of the signaling call drop of a certain type is obviously more than that of other types; the number of users with poor quality and the ratio: counting the number of users with poor call drop quality, and calculating the user proportion with poor quality so as to analyze whether the call drop abnormality is a common condition or an isolated abnormality of a certain user; user tracking analysis: screening users with abnormal call drop rate in the current cell, tracking the call drop rate index conditions of the users in other cells in the same time period, analyzing whether the reason of individual users exists or not to cause index degradation, and if some users have abnormal call drop conditions in a plurality of cells, the possibility of user side abnormality exists; meanwhile, the terminal brands and the models of the users are analyzed, and whether the quality of a certain brand of equipment is poor or not is judged in an auxiliary mode; the indexes of the cell all day are as follows: comparing the day granularity indexes to determine whether long-time abnormity exists; the total day difference hours of the cell: counting the abnormal conditions of the call drop rate in a plurality of periods within 24 hours all day, and determining whether long-time abnormality exists; hour indexes of the same wireless manufacturer in the same district and county are as follows: comparing the index conditions of the wireless manufacturers of the abnormal cells in the same county to analyze whether the problem of the wireless side equipment exists or not; hour indexes of other wireless manufacturers in the same county are as follows: comparing the index conditions of other wireless manufacturers in the same county to analyze whether the common abnormal problem exists on the wireless side; the cell was characterized by approximately 7 days of poor quality: counting the number of days with quality difference of the cell in the last 7 days, and determining whether the cell has a continuous call drop abnormal condition or only sporadic abnormality in the current day; the P-CSCF (Proxy Call Session Control Function) index of the city: comparing the drop call rate indexes of the core network element P-CSCF of the local city where the cell is located, and judging whether one or more P-CSCF network element indexes are abnormal; the city S-CSCF (Serving-Call Session Control Function) index: comparing the drop call rate index of the S-CSCF of the core network element of the local city where the cell is located, and judging whether one or more S-CSCF network element indexes are abnormal; the local market eMSC (enhanced Mobile Switching Center) index: and comparing the call drop rate indexes of the eMSC of the local city core network element where the cell is located, and judging whether one or more eMSC network element indexes are abnormal.
Based on the indexes, according to a single variable principle, possible quality difference reasons are preliminarily obtained after transverse comparison, namely a delimiting conclusion is as follows: the cell is abnormal, the call drop type is mainly LTE transfer type, the cell is initially judged to be caused by the abnormality of the wireless equipment, other cells and other counties are not involved, and the cell is unrelated to users, terminals and core network elements.
According to the indexes, logic analysis is carried out after the indexes are summarized, one reason of poor quality of the cell can be preliminarily obtained, namely comprehensive judgment can be carried out according to all dimension indexes obtained through processing and by combining preset analysis logic, initial judgment and summary conclusion of reasons of abnormal VOLTE call drop rate under the cell can be obtained, and the conclusion can support maintenance personnel to carry out auxiliary judgment.
Optionally, the method for determining a call drop reason of VOLTE in the embodiment of the present invention may further include the following steps:
determining a target poor cell with a target reason of the VOLTE call drop;
and generating a position distribution map of the target quality difference cell.
It can be understood that, specifically, the corresponding target poor quality cells can be respectively determined for different reasons of the VOLTE call drop, and the position distribution conditions of the poor quality cells of the corresponding parts are visually displayed, so that the call drop reasons can be more clearly and more vividly viewed.
Optionally, in the method for determining a call drop reason of VOLTE according to the embodiment of the present invention, the location distribution map includes at least one of a GIS geographic distribution map and a thermal distribution map.
It can be understood that the geographical distribution display can be implemented for the case that the specific VOLTE call drop reason exists in different geographical areas, such as different cities, counties, and the like. That is to say, according to the geographic location, the number of users, the abnormal frequency, the service scene and other comprehensive information of the abnormal cells, and by combining the GIS map, the thermodynamic diagram and other technical means, the abnormal cells possibly affected by association can be associated, so that the overall distribution condition of the cells with abnormal call drop rate and the number of affected users can be visually and clearly observed.
In summary, according to the method for determining the call drop reason of the VOLTE in the embodiment of the present invention, the abnormal reason of the cell can be preliminarily determined according to the problem delimiting conclusion of the single poor cell, and the reason may be located only in the cell, may be located in the user, and may also be located in the core network element; furthermore, deep mining can be performed based on the conclusion of a single cell, namely association can be performed through the position relation among the cells through the presentation mode of a GIS map and thermodynamic diagram, so that abnormal problem judgment can be performed more comprehensively and accurately.
Referring to fig. 3, an embodiment of the present invention further provides a device for determining a call drop reason of VOLTE, which may specifically include:
an obtaining module 301, configured to obtain, according to multiple XDR signaling data of an extensible detailed interface, multiple on-off records corresponding to multiple VOLTE calls of multiple users, where the multiple VOLTE calls occur in multiple cells;
a first determining module 303, configured to determine a poor cell in the multiple cells according to the multiple on-off records and the poor quality determination index, where the poor quality determination index includes at least one of a total number of users in the cell and a percentage of users in the cell, and a call drop rate of the cell;
the second determining module 305 determines a reason for the VOLTE call drop of the poor cell according to the call drop analysis indicator.
Preferably, in the device for determining a call drop reason in VOLTE according to the embodiment of the present invention, in a case where the poor quality determination indicator includes a total number of users in a cell, a ratio of poor quality users in the cell, and a call drop rate in the cell, the first determining module 303 may be specifically configured to:
determining the call drop rate of each cell in the plurality of cells according to the plurality of on-off records;
and determining the cells with the call drop rate larger than the call drop rate threshold, the total number of users larger than the total number threshold and the poor user occupation ratio larger than the poor user occupation ratio threshold as the poor cells.
Preferably, in the device for determining a call drop reason of VOLTE provided in the embodiment of the present invention, a percentage of the total number of the poor quality cells to the total number of the plurality of cells is a preset value, and the preset value is equal to a product of the first ratio, the second ratio, and the third ratio;
wherein the first proportion is the ratio of the total number of the first cells with the call drop rate larger than the call drop rate threshold in the plurality of cells to the total number of the plurality of cells,
the second ratio is the ratio of the total number of the second cells to the total number of the first cells, wherein the total number of the users in the first cells is larger than the threshold of the total number of the users,
the third ratio is the ratio of the total number of the third cells with the poor quality user occupation ratio larger than the poor quality user occupation ratio threshold in the second cell to the total number of the second cells.
Preferably, in the apparatus for determining a reason for a dropped call in VOLTE according to an embodiment of the present invention, the drop call analysis index includes: at least one of the evaluation indexes of abnormal call drop type of the cell, the call drop rate of county granularity, the call drop rate of core network element granularity, the call drop rate of wireless manufacturer granularity, the call drop rate of terminal type granularity, the user occupation ratio of poor quality in the cell and the time granularity of the cell;
the abnormal call drop type of the cell is determined based on a plurality of XDR signaling data, and the county granularity call drop rate, the core network element granularity call drop rate, the wireless manufacturer granularity call drop rate, the terminal type granularity call drop rate, the poor user occupation ratio in the cell and the cell time granularity evaluation index are determined based on a plurality of on-off records.
Preferably, in the apparatus for determining a call drop reason for VOLTE provided in the embodiment of the present invention,
the abnormal call drop type of the cell comprises the following steps: at least one of a long term evolution, LTE, tear down bearer, an enhanced single radio voice call continuity, eSRVCC, failure, media flow interruption, and registration timeout;
the above-mentioned core network element granularity call drop rate includes: at least one of a proxy call session control function P-CSCF network element granularity call drop rate, a serving call session control function S-CSCF network element granularity call drop rate and an enhanced mobile switching center eMSC network element granularity call drop rate;
the cell time granularity evaluation index includes: at least one of a cell day granularity call drop rate, a cell full-day poor quality duration, and a number of days in which a call drop anomaly exists in a cell within a preset period.
Preferably, the apparatus for determining a call drop reason for VOLTE provided in the embodiment of the present invention may further include:
a third determining module, configured to determine a target poor cell for which a reason for the VOLTE call drop is a target reason;
and the generating module is used for generating a position distribution map of the target quality difference cell.
Preferably, in the apparatus for determining a call drop reason for VOLTE according to an embodiment of the present invention, the location profile includes at least one of a GIS geographic profile and a thermal profile.
It can be understood that the apparatus for determining a reason for a dropped call of VOLTE according to the embodiment of the present invention can implement each process of the method for determining a reason for a dropped call of VOLTE, and the related descriptions about the method for determining a reason for a dropped call of VOLTE are applicable to the apparatus for determining a reason for a dropped call of VOLTE, and are not described herein again.
In the embodiment of the invention, a plurality of extensible detailed interface XDR signaling data at the bottom layer are fully mined and analyzed to obtain the on-off records of single VOLTE call of each single user in a plurality of cells, the analyzed on-off records are used as a bottom layer data source, and a quality difference cell is further screened from the plurality of cells by combining quality difference judgment indexes. Therefore, the quality difference cells are accurately judged by adopting the multiple quality difference judgment indexes, and the VOLTE call drop reason is determined based on the specific call drop analysis indexes, so that the VOLTE call drop reason is fully excavated and accurately determined, the network maintenance and optimization are effectively supported, and the VOLTE voice call quality is improved.
Fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present application. Referring to fig. 4, 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 or the like.
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. 4, but that 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.
And the processor reads a corresponding computer program from the nonvolatile memory into the memory and runs the computer program to form the VOLTE call drop reason determining device on a 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 on-off records respectively corresponding to a plurality of VOLTE calls of a plurality of users according to a plurality of extensible detail interface XDR signaling data, wherein the plurality of VOLTE calls occur in a plurality of cells;
determining a poor quality cell in a plurality of cells according to a plurality of on-off records and poor quality judgment indexes, wherein the poor quality judgment indexes comprise at least one of the total number of users in the cell, the occupation ratio of the poor quality users in the cell and the call drop rate of the cell;
and determining the reason of the VOLTE call drop of the poor cell according to the call drop analysis index.
In the embodiment of the invention, a plurality of extensible detailed interface XDR signaling data at the bottom layer are fully mined and analyzed to obtain the on-off records of single VOLTE call of each single user in a plurality of cells, the analyzed on-off records are used as a bottom layer data source, and a quality difference cell is further screened from the plurality of cells by combining quality difference judgment indexes. Therefore, the quality difference cells are accurately judged by adopting the multiple quality difference judgment indexes, and the VOLTE call drop reason is determined based on the specific call drop analysis indexes, so that the VOLTE call drop reason is fully excavated and accurately determined, the network maintenance and optimization are effectively supported, and the VOLTE voice call quality is improved.
The method executed by the VOLTE call drop reason determining apparatus according to the embodiment shown in fig. 1 of the present application may be applied to a processor, or implemented by the 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 Gate 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 apparatus for determining a call drop reason for VOLTE in fig. 1, and implement the function of the apparatus for determining a call drop reason for VOLTE in the embodiment shown in fig. 1, which is 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 the method performed by the VOLTE call drop reason determining apparatus in the embodiment shown in fig. 1, and are specifically configured to perform:
acquiring a plurality of on-off records respectively corresponding to a plurality of VOLTE calls of a plurality of users according to a plurality of extensible detail interface XDR signaling data, wherein the plurality of VOLTE calls occur in a plurality of cells;
determining a poor quality cell in a plurality of cells according to a plurality of on-off records and poor quality judgment indexes, wherein the poor quality judgment indexes comprise at least one of the total number of users in the cell, the occupation ratio of the poor quality users in the cell and the call drop rate of the cell;
and determining the reason of the VOLTE call drop of the poor cell according to the call drop analysis index.
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 call drop reason of VOLTE (Voice over Long term evolution), the method comprising:
acquiring a plurality of on-off records respectively corresponding to a plurality of VOLTE calls of a plurality of users according to a plurality of extensible detail interface XDR signaling data, wherein the plurality of VOLTE calls are generated in a plurality of cells;
determining a poor cell in the plurality of cells according to the plurality of on-off records and the poor quality judgment indexes, wherein the poor quality judgment indexes comprise at least one of the total number of users in the cell, the percentage of poor quality users in the cell and the call drop rate of the cell;
and determining the reason of the VOLTE call drop of the poor cell according to the call drop analysis index.
2. The method according to claim 1, wherein in a case that the quality-difference determination index includes the total number of users in the cell, the percentage of users with quality difference in the cell, and the call drop rate in the cell, the determining a quality-difference cell in the plurality of cells according to the plurality of on-off records and the quality-difference determination index comprises:
determining the call drop rate of each cell in the plurality of cells according to the plurality of on-off records;
and determining the cells with the call drop rate larger than the call drop rate threshold, the total number of users larger than the total number threshold and the poor user occupation ratio larger than the poor user occupation ratio threshold as the poor cells.
3. The method of claim 2,
the percentage of the total number of the poor quality cells to the total number of the plurality of cells is a preset value, and the preset value is equal to the product of a first proportion, a second proportion and a third proportion;
wherein the first proportion is a ratio of a total number of first cells with a dropped call rate greater than the dropped call rate threshold among the plurality of cells to the total number of the plurality of cells,
the second ratio is a ratio of the total number of the second cells in the first cell to the total number of the first cells, wherein the total number of the users in the first cell is greater than the total number threshold of the users,
the third ratio is a ratio of the total number of third cells in the second cell, in which the ratio of the poor quality users to the poor quality users is greater than the threshold of the ratio, to the total number of the second cells.
4. The method of claim 1,
the call drop analysis indexes comprise: at least one of the evaluation indexes of abnormal call drop type of the cell, the call drop rate of county granularity, the call drop rate of core network element granularity, the call drop rate of wireless manufacturer granularity, the call drop rate of terminal type granularity, the user occupation ratio of poor quality in the cell and the time granularity of the cell;
the abnormal cell drop type is determined based on the plurality of XDR signaling data, and the district-county granularity call drop rate, the core network element granularity call drop rate, the wireless manufacturer granularity call drop rate, the terminal type granularity call drop rate, the poor user occupation ratio in the cell and the cell time granularity evaluation index are determined based on the plurality of on-off records.
5. The method of claim 4,
the abnormal call drop type of the cell comprises the following steps: at least one of a long term evolution, LTE, tear down bearer, an enhanced single radio voice call continuity, eSRVCC, failure, media flow interruption, and registration timeout;
the granularity call drop rate of the core network element comprises the following steps: at least one of a proxy call session control function P-CSCF network element granularity call drop rate, a serving call session control function S-CSCF network element granularity call drop rate and an enhanced mobile switching center eMSC network element granularity call drop rate;
the cell time granularity evaluation index comprises: at least one of a cell day granularity call drop rate, a cell full-day poor quality duration, and a number of days in which a call drop anomaly exists in a cell within a preset period.
6. The method according to any one of claims 1 to 5, further comprising:
determining a target poor cell with the reason of the VOLTE call drop as a target reason;
and generating a position distribution map of the target quality difference cell.
7. The method of claim 6, wherein the location profile comprises at least one of a GIS geographic profile and a thermodynamic profile.
8. A VOLTE call drop cause determination apparatus, 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 on-off records respectively corresponding to a plurality of VOLTE calls of a plurality of users according to a plurality of extensible detail interface XDR signaling data, and the plurality of VOLTE calls are generated in a plurality of cells;
the first determining module is used for determining a poor cell in the plurality of cells according to the plurality of on-off records and the poor quality judging indexes, wherein the poor quality judging indexes comprise at least one of the total number of users in the cell, the occupation ratio of the poor quality users in the cell and the call drop rate of the cell;
and the second determining module is used for determining the reason of the VOLTE call drop of the poor cell according to the call drop analysis index.
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 |
---|---|---|---|
CN201910295889.3A CN111818551B (en) | 2019-04-12 | 2019-04-12 | VOLTE call drop reason determination method and device |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201910295889.3A CN111818551B (en) | 2019-04-12 | 2019-04-12 | VOLTE call drop reason determination method and device |
Publications (2)
Publication Number | Publication Date |
---|---|
CN111818551A true CN111818551A (en) | 2020-10-23 |
CN111818551B CN111818551B (en) | 2022-07-01 |
Family
ID=72843999
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201910295889.3A Active CN111818551B (en) | 2019-04-12 | 2019-04-12 | VOLTE call drop reason determination method and device |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN111818551B (en) |
Cited By (2)
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 |
CN114554534A (en) * | 2020-11-24 | 2022-05-27 | 中国移动通信集团北京有限公司 | Network factor determination method and device influencing voice perception and electronic equipment |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
KR20150129457A (en) * | 2014-05-12 | 2015-11-20 | 주식회사 네이블커뮤니케이션즈 | Apparatus and method for providing quality analysis of volte service using terminal agent |
US20160295439A1 (en) * | 2015-04-01 | 2016-10-06 | Qualcomm Incorporated | Measurement procedures during connected mode discontinuous reception cycle based on blocking low priority data activities |
CN106304180A (en) * | 2016-08-15 | 2017-01-04 | 中国联合网络通信集团有限公司 | A kind of method and device of the speech service quality determining user |
CN107548082A (en) * | 2016-06-28 | 2018-01-05 | 中兴通讯股份有限公司 | The method, apparatus and system of one germplasm difference regional analysis |
CN109379736A (en) * | 2018-10-26 | 2019-02-22 | 北京市天元网络技术股份有限公司 | The method of adjustment and device of subzone network quality |
-
2019
- 2019-04-12 CN CN201910295889.3A patent/CN111818551B/en active Active
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
KR20150129457A (en) * | 2014-05-12 | 2015-11-20 | 주식회사 네이블커뮤니케이션즈 | Apparatus and method for providing quality analysis of volte service using terminal agent |
US20160295439A1 (en) * | 2015-04-01 | 2016-10-06 | Qualcomm Incorporated | Measurement procedures during connected mode discontinuous reception cycle based on blocking low priority data activities |
CN107548082A (en) * | 2016-06-28 | 2018-01-05 | 中兴通讯股份有限公司 | The method, apparatus and system of one germplasm difference regional analysis |
CN106304180A (en) * | 2016-08-15 | 2017-01-04 | 中国联合网络通信集团有限公司 | A kind of method and device of the speech service quality determining user |
CN109379736A (en) * | 2018-10-26 | 2019-02-22 | 北京市天元网络技术股份有限公司 | The method of adjustment and device of subzone network quality |
Non-Patent Citations (1)
Title |
---|
杨帆: ""一种基于V网的RRC多目标重建功能优化方法"", 《长江信息通信》 * |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN114554534A (en) * | 2020-11-24 | 2022-05-27 | 中国移动通信集团北京有限公司 | Network factor determination method and device influencing voice perception and electronic equipment |
CN114554534B (en) * | 2020-11-24 | 2024-05-07 | 中国移动通信集团北京有限公司 | Network factor determination method and device for influencing voice perception and electronic equipment |
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 |
Also Published As
Publication number | Publication date |
---|---|
CN111818551B (en) | 2022-07-01 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN111817868B (en) | Method and device for positioning network quality abnormity | |
CN107026746B (en) | Network service quality evaluation method, system and network equipment | |
CN110121189B (en) | Network monitoring method and device | |
US20220006714A1 (en) | Method and apparatus for prediction of device failure | |
CN110149654B (en) | Method and device for determining faults of base station antenna feeder system | |
CN109005514B (en) | Backfill method and device of user position information, terminal equipment and storage medium | |
CN111818551B (en) | VOLTE call drop reason determination method and device | |
CN108668296B (en) | Method, device and equipment for determining circuit switched fallback perception difference cell | |
CN109150565B (en) | Network situation perception method, device and system | |
US11516100B1 (en) | Cloud-to-cloud integration of vendor device testing automation and carrier performance analytics | |
CN113365306B (en) | Network analysis method and device, storage medium and computer system | |
CN111818560A (en) | Method and device for determining poor quality cell | |
CN113301555A (en) | Resident cell determining method, resident cell determining device, resident cell determining equipment, resident cell determining medium and resident cell determining product | |
CN110865931B (en) | Simulation method, simulation device, electronic equipment and storage medium | |
CN112637770A (en) | Cell state judgment method and device based on minimization of drive tests and computing equipment | |
CN111935772A (en) | Method and device for determining value of service area | |
CN110213123A (en) | A kind of flux monitoring method, device and equipment | |
CN114630359B (en) | Method, device, electronic equipment and computer storage medium for determining network coverage | |
US20230217272A1 (en) | Radio device anomaly detection | |
CN109743762B (en) | Method and device for starting eSRVCC function | |
CN111292524B (en) | Congestion information determination method and device, electronic equipment and storage medium | |
CN113727382A (en) | Network quality determination method and device, network equipment and computer storage medium | |
CN116828509B (en) | Network blind area detection method and system | |
CN113381867A (en) | Communication delay reason determining method and device, electronic equipment and storage medium | |
CN112752252B (en) | Cell home location identification method and device |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |