CN111818551B - VOLTE call drop reason determination method and device - Google Patents

Abstract

The embodiment of the present invention discloses a method for determining the cause of a VOLTE call drop. The method includes: acquiring a plurality of on-off calls corresponding to a plurality of VOLTE calls of a plurality of users according to XDR signaling data of a plurality of scalable detailed single interfaces. Records, among which, multiple VOLTE calls occurred in multiple cells; according to multiple on-off records and quality poor judgment indicators, determine the poor quality cells in multiple cells, and the quality poor judgment indicators include the total number of users in the cell and the poor quality users in the cell At least one of the ratios, and the call drop rate of the cell; according to the call drop analysis index, determine the cause of the VOLTE call drop in the cell with poor quality. The embodiment of the present invention can fully excavate and accurately determine the cause of VOLTE call drop, so as to effectively support network maintenance and optimization, and improve the quality of VOLTE voice calls.

Description

VOLTE call drop cause determination method and device

technical field

The invention relates to the technical field of mobile communication, and in particular, to a method and device for determining the cause of a VOLTE call drop.

Background technique

At present, VOLTE (Voice over LTE (Long Term Evolution, Long Term Evolution)), as a high-definition voice service based on 4G mobile communication technology (The 4Generation Mobile Communication Technology), is a development trend of mobile voice communication. With the development of VOLTE voice services, the quality of VOLTE voice services has attracted more and more attention. It is an urgent need for telecom operators to ensure the quality of VOLTE voice calls and improve user satisfaction.

The existing reason analysis for abnormal call drop of VOLTE voice service is carried out based on the overall call drop rate index of all users, that is, the overall call drop rate of VOLTE users is determined by calculating the ratio of the total number of dropped calls to the total number of connections. . However, the reasons for the poor quality obtained based on this analysis have great limitations and are not specific and accurate enough, which is not conducive to improving the quality of VOLTE voice calls.

SUMMARY OF THE INVENTION

Embodiments of the present invention provide an antenna engineering parameter measurement method, device, and storage medium, so as to solve the problem that the existing VOLTE call drop cause determination result is not accurate enough, so as to improve the VOLTE voice call quality.

In order to solve the above-mentioned technical problems, the present invention is achieved in this way:

In a first aspect, a method for determining the cause of a VOLTE call drop is provided, the method comprising:

Obtain multiple on-off records corresponding to multiple VOLTE calls of multiple users according to the XDR signaling data of multiple scalable detailed single interfaces, wherein the multiple VOLTE calls occur in multiple cells;

Determine a cell with poor quality among the plurality of cells according to the plurality of on-off records and the poor quality judgment index, the poor quality judgment index comprising at least one of the total number of users in the cell and the proportion of users with poor quality in the cell, and cell drop rate;

According to the call drop analysis index, determine the cause of the VOLTE call drop in the poor-quality cell.

In a second aspect, a VOLTE call drop cause determination device is provided, and the device includes:

The acquisition module is used to acquire multiple on-off records corresponding to multiple VOLTE calls of multiple users according to the XDR signaling data of multiple scalable detailed single interfaces, wherein the multiple VOLTE calls occurred in multiple cells ;

The first determination module determines the cells with poor quality in the plurality of cells according to the plurality of on-off records and the poor quality judgment indicators, and the poor quality judgment indicators include the total number of users in the cells and the proportion of users with poor quality in the cells. at least one of , and the call drop rate of the cell;

The second determining module determines the cause of the VOLTE call drop in the poor-quality cell according to the call drop analysis index.

In a third aspect, an electronic device is provided, the electronic device includes a processor, a memory, and a computer program stored on the memory and executable on the processor, when the computer program is executed by the processor The steps of implementing the method as described in the first aspect.

In a fourth aspect, a computer-readable storage medium is provided, wherein a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method according to the first aspect are implemented .

In the embodiment of the present invention, by fully mining and analyzing the XDR signaling data of multiple extensible detailed single interfaces at the bottom layer, the on-off records of each single user's single VOLTE call in multiple cells are obtained, and the analysis results are obtained. The multiple on-off records are used as the underlying data source, and the poor-quality cells are further screened from the multiple cells based on the poor-quality judgment indicators. Specifically, when judging the poor-quality cells, in addition to considering the call drop rate of the cell, it is also necessary to combine the total number of users in the cell. At least one of the two poor quality judgment indicators, and the proportion of poor quality users in the cell, in order to improve the accuracy of the poor quality cell judgment, and then according to the specific call drop analysis indicators, the reasons for the VOLTE call drop of each poor quality cell can be analyzed. Analysis confirmed. In this way, by using a variety of poor quality judgment indicators to accurately determine the poor quality cells, and based on the specific call drop analysis indicators to determine the cause of VOLTE call drop, to fully excavate and accurately determine the cause of VOLTE call drop, so as to effectively support the network. Maintenance and optimization to improve the quality of VOLTE voice calls.

Description of drawings

The accompanying drawings described herein are used to provide further understanding of the present invention and constitute a part of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the attached image:

1 is a schematic flowchart of a method for determining the cause of VOLTE call drop in the embodiment of the present invention;

Fig. 2 is the process schematic diagram of determining the cause of VOLTE call drop in the embodiment of the present invention;

Fig. 3 is the structural representation of the device for determining the cause of VOLTE call drop 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 ways

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

For the existing analysis solution based on a single call drop rate indicator to analyze the cause of abnormal call drop of VoLTE voice service stated in the background art, it cannot provide more effective information for network quality analysis in the era of big data, nor can it meet the requirements of intelligent operation and maintenance technical requirements.

In addition, in addition to the method of obtaining the overall call drop rate index of VoLTE users, in the related art, the call drop index situation of users in different cities is obtained according to different statistical dimensions of call drop reasons. But there are the following problems:

(1) The city-level granularity of VoLTE voice service abnormal call drop indicators is suitable for assessment and notification. When it comes to more specific network abnormal monitoring and cause analysis scenarios, there are great limitations.

(2) There are many reasons for the abnormal call drop of the VoLTE voice service. A single call drop rate indicator cannot reflect more call drop reasons, so it is impossible to carry out more in-depth call drop cause analysis work.

(3) From the perspective of VoLTE network networking, there is a lack of abnormal call drop analysis methods from the core network element side and the wireless base station side.

It can be seen that the existing analysis methods for abnormal dropped calls of VoLTE voice services are relatively superficial, resulting in the inability to fully exploit and utilize the value of big data. Therefore, it is necessary to provide a solution that can accurately and deeply mine the cause of VoLTE call drop, so as to ensure the quality of VoLTE voice calls and improve user satisfaction.

The technical solutions provided by the embodiments of the present invention will be 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 the cause of a VOLTE call drop. The method may specifically include:

Step S101 : Acquire multiple on-off records corresponding to multiple VOLTE calls of multiple users according to the XDR signaling data of multiple scalable detailed single interfaces, wherein multiple VOLTE calls occur in multiple cells.

Step S103: According to the multiple on-off records and the poor quality judgment indicators, determine the poor quality cells in the plurality of cells, and the quality poor judgment indicators include at least one of the total number of users in the cells and the proportion of users with poor quality in the cells, and the dropped calls in the cells. Rate.

Step S105: According to the call drop analysis index, determine the cause of the VOLTE call drop in the cell with poor quality.

In the embodiment of the present invention, by fully mining and analyzing the XDR signaling data of multiple extensible detailed single interfaces at the bottom layer, the on-off records of each single user's single VOLTE call in multiple cells are obtained, and the analysis results are obtained. The multiple on-off records of the VOLTE network are used as the underlying data source, and the poor-quality cells are further screened from the multiple cells in combination with the poor-quality judgment indicators, that is, the poor-quality cells are analyzed based on the end-to-end call data of the VOLTE network. In addition to considering the call drop rate of the cell, it is also necessary to combine at least one of the two poor quality judgment indicators, the total number of users in the cell and the proportion of users with poor quality in the cell, to improve the accuracy of the judgment of poor quality cells. The call drop analysis index analyzes and determines the cause of the VOLTE call drop in each cell with poor quality. In this way, by using a variety of poor quality judgment indicators to accurately determine the poor quality cells, and based on the specific call drop analysis indicators to determine the cause of VOLTE call drop, to fully excavate and accurately determine the cause of VOLTE call drop, so as to effectively support the network. Maintenance and optimization to improve the quality of VOLTE voice calls.

Optionally, for the method for determining the cause of VOLTE call drop according to the embodiment of the present invention, in the case that the above-mentioned poor quality judgment indicators include the total number of users in the cell, the proportion of users with poor quality in the cell, and the call drop rate of the cell, the above step S103 may be specific. Execute as:

Determine the call drop rate of each cell in multiple cells according to multiple on-off records;

A cell in which the call drop rate is greater than the call drop rate threshold, the total number of users is greater than the total number of users threshold, and the proportion of poor quality users is greater than the threshold of poor quality users in multiple cells is determined as a poor quality cell.

It can be understood that according to the on-off records of each single user's single VOLTE call in multiple cells, the call drop rate statistics of the cell granularity are carried out. Determine the relationship between the call drop rate threshold, the total number of users threshold and the threshold for the proportion of poor quality users, and accurately screen out the poor quality cells.

Among them, the call drop rate of the cell may be in hour granularity or minute granularity, and statistics are made according to actual needs.

Further optionally, the percentage of the total number of cells with poor quality to the total number of multiple cells is a preset value, and the preset value is equal to the product of the first ratio, the second ratio and the third ratio;

Wherein, the first ratio is the ratio of the total number of the first cells with the call drop rate greater than the call drop rate threshold in the multiple cells to the total number of the multiple cells,

The second ratio is the ratio of the total number of second cells in which the total number of users is greater than the threshold of the total number of users to the total number of first cells in the first cell,

The third ratio is the ratio of the total number of third cells in which the proportion of poor quality users is greater than the threshold of the proportion of poor quality users to the total number of second cells in the second cell.

It can be understood that, in order to ensure that poor-quality cells are accurately screened from multiple cells used as screening samples, the call drop rate threshold, the total number of users threshold, and the threshold for the proportion of poor-quality users are preferably selected based on The proportion of cells with poor quality reaches a certain preset value, such as 0.1%.

The above threshold determination process can be described below with specific examples. Specifically, by screening a certain amount of sample space and about 200,000 cell lists at different times, the user-level call drop rate indicators are obtained, and based on daily maintenance experience and The index situation yields cells that meet 0.1% of the quality difference threshold. Among them, the call drop rate threshold is set to x%, the total number of users threshold is set to y, and the threshold for the proportion of poor quality users is set to z%, and the weight parameters involved are as follows:

ξ: the proportion of the number of cells with call drop rate > x%;

ν: the proportion of the total number of users in the cell > the number of cells in y;

ζ: The proportion of the number of cells with poor quality users in the cell > z%;

It can be seen that the screening rule for poor quality cells is: n=m×ξ×ν×ζ.

Specifically, if the number of cells whose call drop rate is greater than x% is screened from the overall sample space of 200,000 (ie m) is 7824, ξ is 3.9%, and the total number of users in the 7824 cells that satisfy the cell is greater than y When the number of cells in 7015 is 7015, ν is 90%. Further, among the 7015 cells, the number of cells that satisfy the ratio of users with poor quality within the cell is greater than z% is 231, and ν is 3.3%, then ξ×ν×ζ=0.001. That is, the threshold values of x, y and z should be able to filter out about 0.1% of the abnormal cell list from the full cell list, and make the value of ξ×ν×ζ 0.1%.

Optionally, the above-mentioned call drop analysis indicators include: abnormal call drop type in the cell, call drop rate at district/county granularity, call drop rate at core network element granularity, call drop rate at wireless manufacturer granularity, call drop rate at terminal type granularity, and poor quality in the cell At least one of the user ratio and the cell time granularity evaluation index;

Among them, the abnormal call drop type of the cell is determined based on multiple XDR signaling data, the call drop rate of district and 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, and the poor quality users in the cell. The proportion and cell time granularity evaluation indicators are determined based on multiple on-off records.

It can be understood that, in addition to being the underlying data of multiple on-off records, multiple XDR signaling data can also be used to determine the specific type of each abnormal call drop based on the analysis of multiple XDR signaling data, and then can be based on each specific abnormal call drop. Summarize the cell granularity by the call type to determine the abnormal call drop type of the cell, for example, determine the specific call drop type with the highest frequency in each cell as the abnormal call drop type of the cell corresponding to the cell. Based on multiple on-off records, in addition to summarizing and determining the call drop rate of cell granularity, it can further aggregate and determine the call drop rate and cell time granularity evaluation indicators of district granularity, core network element granularity, wireless manufacturer granularity and terminal type granularity.

Among them, the call drop rate includes the call drop rate of the calling party and the call drop rate of the called party.

Similarly, it is also possible to determine whether a user is a poor quality user based on the call drop situation of each user in the cell. For example, when the user's call drop rate reaches a certain value, the user can be regarded as a poor quality user, so that the proportion of poor quality users can be determined. .

Optionally, the abnormal call drop type of the cell includes: at least one of long-term evolution LTE decommissioning, enhanced single wireless voice call continuity eSRVCC failure, media stream interruption and registration timeout.

It should be noted that the abnormal call drop types of the cell in the embodiment of the present invention, except for the abnormal call drop cases except the above four types of abnormal call drop types, may be uniformly classified into other abnormal call drop types.

Optionally, the above-mentioned core network element granularity call drop rate includes: proxy call session control function P-CSCF network element granularity call drop rate, serving call session control function S-CSCF network element granularity call drop rate and enhanced mobile switching center eMSC At least one of the network element granularity call drop rates.

Optionally, the above cell time granularity evaluation index includes: at least one of the cell day granularity call drop rate, the duration of poor quality of the cell throughout the day, and the number of days in which the cell has abnormal call drops within a preset period.

Further, the solution of the above step S105 will be described with reference to FIG. 2 . Specifically for the poor quality cells, according to the single variable principle, the possible reasons for the poor quality can be preliminarily obtained after horizontal comparison, as shown in Figure 2. The user dimension, the dropped call type dimension, and the core network element dimension are analyzed and judged, and a general conclusion is finally drawn.

For example, according to the hourly call drop rate index of the cell in Figure 2, it can be seen that the cell is a low-quality cell with abnormal call drops, and the cell is abnormal throughout the day, so it is possible to compare whether other cells in the same district or county are abnormal in the same direction within the hour. , if there is no abnormality in other cells, it means that the single cell is abnormal; if other cells are abnormal, it means that the cells in the district or county are abnormally common; for the hourly granularity call drop rate index of the same district and county and the same wireless manufacturer, it can be judged whether In this hour, the hourly granularity call drop rate of all wireless manufacturers A in the district and county is abnormal. If so, it means that there is a problem with the wireless manufacturer; Judging whether it is a district or county problem; for other indicators, according to the single variable principle, the process of horizontal comparison is similar to the above.

For each indicator in Figure 2, the hour indicator of the cell: an indicator to determine the abnormal call drop rate of the cell; main call drop types: the type of call drop with the largest proportion of statistics, to assist in judging whether there is a certain signaling process abnormality , resulting in a significantly higher proportion of dropped calls for certain types of signaling than for other types; the number and proportion of users with poor quality: Count the total number of users with poor quality of dropped calls, and calculate the proportion of users with poor quality to analyze abnormal dropped calls Whether it is a common situation or an isolated abnormality of a certain user; user tracking analysis: screen out users with abnormal call drop rates in this hour, and track the call drop rate indicators of these users in other cells during the same period, and analyze Whether there are individual user reasons that lead to the deterioration of indicators, such as some users have abnormal call drops in multiple cells, there is the possibility of abnormal user side; Judging whether there is poor quality of a certain brand of equipment; all-day indicators of the community: compare the granularity indicators of the day to confirm whether there is a long-term abnormality; the number of hours of poor quality of the community throughout the day: count the total number of time periods in 24 hours a day If there is an abnormal call drop rate, confirm whether there is an abnormality for a long time; the hour indicator of the same wireless manufacturer in the same district and county: compare the wireless manufacturer to which the abnormal cell belongs, and the indicators in the same district and county to analyze whether there is a problem with the wireless side equipment. Question: Hourly indicators of other wireless manufacturers in the same district and county: Compare the indicators of other wireless manufacturers in the same district and county to analyze whether there is a general abnormal problem on the wireless side; the number of days with poor quality in the past 7 days: count the number of days of poor quality in the community in the last 7 days The number of days with a qualitative difference in 7 days is to confirm whether there is an abnormal situation of persistent call drop in the cell, or it is only an occasional abnormality that occurs on the same day; the city's P-CSCF (Proxy-Call Session Control Function, proxy call session control function) Index: Compare the call drop rate index of the core network element P-CSCF in the city where the cell is located, and determine whether one or more P-CSCF network elements are abnormal; the S-CSCF (Serving-Call Session Control Function, service Call session control function) index: Compare the call drop rate index of the core network element S-CSCF in the city where the cell is located, to determine whether there is an abnormality in one or more S-CSCF network element indicators; the city's eMSC (enhanced Mobile Switching Center) , Enhanced mobile switching center) index: compare the call drop rate index of the core network element eMSC of the city where the cell is located, and determine whether there is an abnormality in one or more eMSC network element indexes.

Based on the above indicators, according to the principle of single variable, the possible reasons for the poor quality are initially obtained after horizontal comparison, that is, the demarcation conclusion is: the cell is abnormal, and the type of dropped calls is mainly LTE retransmission. , does not involve other cells, other districts and counties, and has nothing to do with users, terminals, and core network elements.

According to the summary of the above indicators and logical analysis, a reason for the poor quality of the cell can be initially obtained, that is, a comprehensive evaluation can be carried out according to the various dimensional indicators obtained by processing, combined with the preset analysis logic, and the reason for the abnormal VOLTE call drop rate in the cell can be obtained. Preliminary judgment and summary conclusion, which can support maintenance personnel to assist judgment.

Optionally, in the method for determining the cause of a VOLTE call drop according to the embodiment of the present invention, the following process steps may also be included:

Determine the cause of the VOLTE call drop as the target cause of the target poor quality cell;

Generate the location distribution map of the target poor quality cells.

It can be understood that the corresponding target poor-quality cells can be determined according to the reasons for different VOLTE call drops, and the location distribution of the corresponding part of the poor-quality cells can be visually displayed, so as to check the reasons for the dropped calls more clearly and vividly. .

Optionally, in the method for determining the cause of a VOLTE call drop according to the embodiment of the present invention, the above-mentioned 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 cases with specific VOLTE call drop reasons within specific geographic ranges such as different cities, districts and counties. That is to say, according to the comprehensive information such as the geographic location, number of users, abnormal frequency, and business scenarios of abnormal cells, combined with technical means such as GIS maps and heat maps, abnormal cells that may have associated effects can be linked. Clearly view the overall distribution of cells with abnormal call drop rates and the number of affected users.

To sum up, through the method for determining the cause of VOLTE call drop according to the embodiment of the present invention, according to the problem demarcation conclusion of a single poor quality cell, the abnormal cause of the cell can be preliminarily determined. It may be located in the core network element; further, in-depth mining can be carried out based on the conclusion of a single cell, that is, through the presentation of GIS maps and heat maps, and the location relationship between cells can be correlated to more comprehensively and accurately judge abnormal problems.

Referring to FIG. 3 , an embodiment of the present invention further provides a device for determining the cause of a VOLTE call drop, which may specifically include:

The obtaining module 301 is configured to obtain a plurality of on-off records corresponding to multiple VOLTE calls of multiple users according to the XDR signaling data of multiple scalable detailed single interfaces, wherein multiple VOLTE calls occur in multiple cells;

The first determination module 303 determines, according to a plurality of on-off records and a poor quality judgment index, a poor quality cell in the plurality of cells, and the quality poor judgment index includes at least one of the total number of users in the cell and the proportion of poor quality users in the cell, and cell drop rate;

The second determination module 305, according to the call drop analysis index, determines the cause of the VOLTE call drop in the cell with poor quality.

Preferably, in the device for determining the cause of VOLTE call drop provided by the embodiment of the present invention, in the case that the above-mentioned poor quality judgment indicators include the total number of users in the cell, the proportion of users with poor quality in the cell, and the call drop rate of the cell, the above-mentioned first determining module 303 , which can be used specifically for:

Determine the call drop rate of each cell in multiple cells according to multiple on-off records;

A cell in which the call drop rate is greater than the call drop rate threshold, the total number of users is greater than the total number of users threshold, and the proportion of poor quality users is greater than the threshold of poor quality users in multiple cells is determined as a poor quality cell.

Preferably, in the device for determining the cause of VOLTE call drop provided by the embodiment of the present invention, the percentage of the total number of cells with poor quality to the total number of multiple cells is a preset value, and the preset value is equal to the first ratio, the second ratio and the first ratio product of three proportions;

Wherein, the first ratio is the ratio of the total number of the first cells with the call drop rate greater than the call drop rate threshold in the multiple cells to the total number of the multiple cells,

The second ratio is the ratio of the total number of second cells in which the total number of users is greater than the threshold of the total number of users to the total number of first cells in the first cell,

The third ratio is the ratio of the total number of third cells in which the proportion of poor quality users is greater than the threshold of the proportion of poor quality users to the total number of second cells in the second cell.

Preferably, in the device for determining the cause of VOLTE call drop provided by the embodiment of the present invention, the above call drop analysis indicators include: abnormal call drop type in the cell, call drop rate at district/county granularity, call drop rate at core network element granularity, and call drop at wireless manufacturer granularity at least one of the call drop rate, the terminal type granularity call drop rate, the proportion of users with poor quality in the cell, and the cell time granularity evaluation index;

Among them, the abnormal drop type of the cell is determined based on multiple XDR signaling data, the call drop rate at district/county granularity, the call drop rate at core network element granularity, the call drop rate at wireless manufacturer granularity, the call drop rate at terminal type granularity, and the percentage of users with poor quality in the cell. The ratio and cell time granularity evaluation index are determined based on multiple on-off records.

Preferably, in the device for determining the cause of a VOLTE call drop provided by the embodiment of the present invention,

The abnormal call drop types of the above-mentioned cells include: at least one of long-term evolution LTE decommissioning, enhanced single wireless voice call continuity eSRVCC failure, media stream interruption and registration timeout;

The above-mentioned core network element granularity call drop rate includes: proxy call session control function P-CSCF network element granularity call drop rate, serving call session control function S-CSCF network element granularity call drop rate and enhanced mobile switching center eMSC network element granularity drop rate at least one of the call rates;

The above cell time granularity evaluation index includes: at least one of the cell day granularity call drop rate, the duration of poor quality of the cell throughout the day, and the number of days in which the cell has abnormal call drops within a preset period.

Preferably, the device for determining the cause of a VOLTE call drop provided by the embodiment of the present invention may further include:

The third determination module is used for determining the reason for the VOLTE call drop as the target poor quality cell of the target reason;

The generating module is used to generate the location distribution map of the target poor quality cells.

Preferably, in the device for determining the cause of a VOLTE call drop provided by 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 device for determining the cause of a VOLTE call drop provided by the embodiment of the present invention can realize the various processes of the aforementioned method for determining the cause of a VOLTE call drop. It is not repeated here.

In the embodiment of the present invention, by fully mining and analyzing the XDR signaling data of multiple extensible detailed single interfaces at the bottom layer, the on-off records of each single user's single VOLTE call in multiple cells are obtained, and the analysis results are obtained. The multiple on-off records are used as the underlying data source, and the poor-quality cells are further screened from the multiple cells based on the poor-quality judgment indicators. Specifically, when judging the poor-quality cells, in addition to considering the call drop rate of the cell, it is also necessary to combine the total number of users in the cell. At least one of the two poor quality judgment indicators, and the proportion of poor quality users in the cell, in order to improve the accuracy of the poor quality cell judgment, and then according to the specific call drop analysis indicators, the reasons for the VOLTE call drop of each poor quality cell can be analyzed. Analysis confirmed. In this way, by using a variety of poor quality judgment indicators to accurately determine the poor quality cells, and based on the specific call drop analysis indicators to determine the cause of VOLTE call drop, to fully excavate and accurately determine the cause of VOLTE call drop, so as to effectively support the network. Maintenance and optimization to improve the quality of VOLTE voice calls.

FIG. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present application. Referring to FIG. 4 , at the hardware level, the electronic device includes a processor, and optionally an internal bus, a network interface, and a memory. The memory may include memory, such as high-speed random-access memory (Random-Access Memory, RAM), or may also include non-volatile memory (non-volatile memory), such as at least one disk memory. Of course, the electronic equipment may also include hardware required for other services.

Optionally, the above electronic device may be a server or other device.

The processor, the network interface, and the memory can be connected to each other through an internal bus, which can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect, peripheral component interconnect standard) bus, or an EISA (Extended Industry) bus. StandardArchitecture, extended industry standard structure) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, and the like. For ease of presentation, only one bidirectional arrow is used in FIG. 4, but it does not mean that there is only one bus or one type of bus.

memory for storing programs. Specifically, the program may include program code, and the program code includes computer operation instructions. The memory may include memory and non-volatile memory and provide instructions and data to the processor.

The processor reads the corresponding computer program from the non-volatile memory into the memory and runs it, forming a VOLTE call drop cause determination device on a logical level. The processor executes the program stored in the memory, and is specifically used to perform the following operations:

Obtain multiple on-off records corresponding to multiple VOLTE calls of multiple users according to the XDR signaling data of multiple scalable detailed single interfaces, wherein multiple VOLTE calls occur in multiple cells;

Determine the poor-quality cells in the multiple cells according to the multiple on-off records and the poor-quality judgment indicators, and the poor-quality judgment indicators include at least one of the total number of users in the cell, the proportion of users with poor quality in the cell, and the call drop rate of the cell;

According to the call drop analysis index, determine the cause of the VOLTE call drop in the poor quality cell.

In the embodiment of the present invention, by fully mining and analyzing the XDR signaling data of multiple extensible detailed single interfaces at the bottom layer, the on-off records of each single user's single VOLTE call in multiple cells are obtained, and the analysis results are obtained. The multiple on-off records are used as the underlying data source, and the poor-quality cells are further screened from the multiple cells based on the poor-quality judgment indicators. Specifically, when judging the poor-quality cells, in addition to considering the call drop rate of the cell, it is also necessary to combine the total number of users in the cell. At least one of the two poor quality judgment indicators, and the proportion of poor quality users in the cell, in order to improve the accuracy of the poor quality cell judgment, and then according to the specific call drop analysis indicators, the reasons for the VOLTE call drop of each poor quality cell can be analyzed. Analysis confirmed. In this way, by using a variety of poor quality judgment indicators to accurately determine the poor quality cells, and based on the specific call drop analysis indicators to determine the cause of VOLTE call drop, to fully excavate and accurately determine the cause of VOLTE call drop, so as to effectively support the network. Maintenance and optimization to improve the quality of VOLTE voice calls.

The above-mentioned method performed by the apparatus for determining the cause of a VOLTE call dropped as disclosed in the embodiment shown in FIG. 1 of the present application may be applied to a processor, or implemented by a processor. A processor may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above-mentioned method can be completed by a hardware integrated logic circuit in a processor or an instruction in the form of software. The above-mentioned processor may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU), a network processor (Network Processor, NP), etc.; it may also be a digital signal processor (Digital Signal Processor, DSP), an application-specific integrated circuit ( Application Specific Integrated Circuit, ASIC), field programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The methods, steps, and logic block diagrams disclosed in the embodiments of this application can be implemented or executed. 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 conjunction with the embodiments of the present application may be directly embodied as executed by a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules may be located in random access memory, flash memory, read-only memory, programmable read-only memory or electrically erasable programmable memory, registers and other storage media mature in the art. The storage medium is located in the memory, and the processor reads the information in the memory, and completes the steps of the above method in combination with its hardware.

The electronic device can also execute the method performed by the apparatus for determining the cause of a VOLTE call drop in FIG. 1 , and implement the functions of the apparatus for determining the cause of a VOLTE call drop in the embodiment shown in FIG. 1 .

The embodiments of the present application also provide a computer-readable storage medium, where the computer-readable storage medium stores one or more programs, and the one or more programs include instructions, and the instructions are executed by an electronic device including multiple application programs. , the electronic device can be made to execute the method performed by the VOLTE call drop cause determination device in the embodiment shown in FIG. 1, and is specifically used to execute:

Obtain multiple on-off records corresponding to multiple VOLTE calls of multiple users according to the XDR signaling data of multiple scalable detailed single interfaces, wherein multiple VOLTE calls occur in multiple cells;

Determine the poor-quality cells in the multiple cells according to the multiple on-off records and the poor-quality judgment indicators, and the poor-quality judgment indicators include at least one of the total number of users in the cell, the proportion of users with poor quality in the cell, and the call drop rate of the cell;

According to the call drop analysis index, determine the cause of the VOLTE call drop in the poor quality cell.

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, etc.) 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 in the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to the processor of a general purpose computer, special purpose computer, embedded processor or other programmable data processing device to produce a machine such that the instructions executed by the processor of the computer or other programmable data processing device produce Means for implementing the functions specified in a flow or flow of a flowchart and/or a block or blocks of a block diagram.

These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory result in an article of manufacture comprising instruction means, the instructions The apparatus implements the functions specified in the flow or flow of the flowcharts and/or the block or blocks of the block diagrams.

These computer program instructions can also be loaded on a computer or other programmable data processing device to cause a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process such that The instructions provide steps for implementing the functions specified in the flow or blocks of the flowcharts and/or the block or blocks of the block diagrams.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

Memory may include non-persistent memory in computer readable media, random access memory (RAM) and/or non-volatile memory in the form of, for example, read only memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

Computer-readable media includes both persistent and non-permanent, removable and non-removable media, and storage of information may be implemented by any method or technology. Information may be computer readable instructions, data structures, modules of programs, 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 Disc (DVD) or other optical storage, Magnetic tape 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. Computer-readable media, as defined herein, excludes transitory computer-readable media, such as modulated data signals and carrier waves.

It should also be noted that the terms "comprising", "comprising" or any other variation thereof are intended to encompass a non-exclusive inclusion such that a process, method, article or device comprising a series of elements includes not only those elements, but also Other elements not expressly listed, or which are inherent to such a process, method, article of manufacture, or apparatus are also included. Without further limitation, an element qualified by the phrase "comprising a..." does not preclude the presence of additional identical elements in the process, method, article of manufacture, or device that includes the element.

It will be appreciated by those skilled in the art that the embodiments of the present application may be provided as a method, a system or a 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, etc.) having computer-usable program code embodied therein.

The above descriptions are merely examples of the present application, and are not intended to limit the present application. Various modifications and variations of this application are possible for those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of this application shall be included within the scope of the claims of this application.

Claims (8)

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; determining a poor quality cell in the plurality of cells according to the plurality of on-off records and the poor quality determination index under the condition that the poor quality determination index includes the total number of the users in the cell, the percentage of the poor quality users in the cell and the drop call rate of the cell, and the determining includes: determining the call drop rate of each cell in the plurality of cells according to the plurality of on-off records; 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;

determining the reason of the VOLTE call drop of the poor cell according to the call drop analysis index;

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 extensible detailed interface 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 quality user occupation ratio in the cell and the cell time granularity evaluation index are determined based on the on-off records.

2. The method of claim 1,

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.

3. The method of claim 1,

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.

4. A method according to any one of claims 1 to 3, 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.

5. The method of claim 4, wherein the location profile comprises at least one of a GIS geographic profile and a thermodynamic profile.

6. 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; determining a poor quality cell in the plurality of cells according to the plurality of on-off records and the poor quality determination index under the condition that the poor quality determination index includes the total number of the users in the cell, the percentage of the poor quality users in the cell and the drop call rate of the cell, and the determining includes: determining the call drop rate of each cell in the plurality of cells according to the plurality of on-off records; 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;

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;

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 extensible detailed interface 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 quality user occupation ratio in the cell and the cell time granularity evaluation index are determined based on the on-off records.

7. 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 5.

8. 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 5.

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