CN117998451A - Quality difference cell identification method, electronic equipment and storage medium - Google Patents
Quality difference cell identification method, electronic equipment and storage medium Download PDFInfo
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- H—ELECTRICITY
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- H04W—WIRELESS COMMUNICATION NETWORKS
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- H04W28/08—Load balancing or load distribution
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Abstract
The application discloses a method for identifying a quality difference cell, electronic equipment and a storage medium, and belongs to the field of wireless communication stroking, wherein the method for identifying the quality difference cell comprises the following steps: acquiring service times of the target cell in each time slice and times of occurrence of service quality differences of the target type service, wherein each time slice is divided according to preset time granularity; determining the business quality difference proportion of the target cell in each time slice according to the business times and business quality difference times in each time slice; acquiring the capacity proportion of a target cell in each time slice; and identifying the quality difference type of the target cell based on the service quality difference proportion of the target cell in each time slice and the capacity proportion of the target cell in each time slice.
Description
Technical Field
The application belongs to the technical field of wireless communication, and particularly relates to a method for identifying a poor quality cell, electronic equipment and a storage medium.
Background
With the popularization of wireless internet, demands of users for networks are continuously increasing. In order to improve user perception, an operator changes an original network optimization method guided by network key performance indicators (Key Performance Indicator, KPIs) into a network optimization method guided by user perception, hopes to find the quality difference in a positioning network through data analysis before receiving user complaints, and continuously improves the network and improves user experience.
The movement of a user in the wireless internet cannot be controlled, the service demands of the user are varied, and the wireless spectrum resources are scarce, so that the air interface resources of the wireless internet can be limited, and the data transmission quality is affected.
The current user perception analysis method generally adopts precursor difference aggregation to find out cells with perception differences, then surveys the most likely quality difference reasons, and the method can lead the screened wireless quality difference cells to not find out abnormality, so that the accuracy rate of identifying the wireless quality difference cells is lower.
Disclosure of Invention
The embodiment of the application provides a method for identifying a poor quality cell, electronic equipment and a storage medium, which can solve the problem of low accuracy in identifying a wireless poor quality cell.
In a first aspect, a method for identifying a bad cell is provided, including: acquiring service times of the target cell in each time slice and times of occurrence of service quality differences of the target type service, wherein each time slice is divided according to preset time granularity; determining the business quality difference proportion of the target cell in each time slice according to the business times and the business quality difference times in each time slice; acquiring the capacity proportion of the target cell in each time slice; and identifying the quality difference type of the target cell based on the service quality difference proportion of the target cell in each time slice and the capacity proportion of the target cell in each time slice.
In a second aspect, there is provided an electronic device comprising a processor and a memory storing a program or instructions executable on the processor, which when executed by the processor, implement the steps of the method as described in the first aspect.
In a third aspect, there is provided a readable storage medium having stored thereon a program or instructions which when executed by a processor implement the steps of the method according to the first aspect.
In a fourth aspect, a chip is provided, the chip comprising a processor and a communication interface, the communication interface and the processor being coupled, the processor being configured to execute programs or instructions for implementing the steps of the method according to the first aspect.
In a fifth aspect, there is provided a computer program/program product stored in a storage medium, the computer program/program product being executed by at least one processor to carry out the steps of the method according to the first aspect.
In the embodiment of the application, the quality difference type of the target cell is identified according to the service quality difference time slice of the target cell in the preset time period and the duty ratio of the time slice with larger capacity load, thereby improving the accuracy of quality difference cell identification and accelerating the positioning speed of the quality difference of the subsequent network.
Drawings
Fig. 1 shows a block diagram of a wireless communication system to which embodiments of the present application are applicable;
fig. 2 is a flow chart illustrating a method for identifying a bad cell according to an embodiment of the present application;
Fig. 3 is a schematic flow chart of another method for identifying a bad cell according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of an apparatus for identifying a bad cell according to an embodiment of the present application;
fig. 5 shows a schematic structural diagram of a communication device according to an embodiment of the present application.
Detailed Description
The technical solutions of the embodiments of the present application will be clearly described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which are derived by a person skilled in the art based on the embodiments of the application, fall within the scope of protection of the application.
The terms first, second and the like in the description and in the claims, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the terms so used are interchangeable under appropriate circumstances such that the embodiments of the application are capable of operation in sequences other than those illustrated or otherwise described herein, and that the "first" and "second" distinguishing between objects generally are not limited in number to the extent that the first object may, for example, be one or more. Furthermore, in the description and claims, "and/or" means at least one of the connected objects, and the character "/" generally means a relationship in which the associated object is an "or" before and after.
It should be noted that the techniques described in the embodiments of the present application are not limited to long term evolution (Long Term Evolution, LTE)/LTE evolution (LTE-Advanced, LTE-a) systems, but may also be used in other wireless communication systems, such as code division multiple access (Code Division Multiple Access, CDMA), time division multiple access (Time Division Multiple Access, TDMA), frequency division multiple access (Frequency Division Multiple Access, FDMA), orthogonal frequency division multiple access (Orthogonal Frequency Division Multiple Access, OFDMA), single carrier frequency division multiple access (Single-carrier Frequency Division Multiple Access, SC-FDMA), and other systems. The terms "system" and "network" in embodiments of the application are often used interchangeably, and the techniques described may be used for both the above-mentioned systems and radio technologies, as well as other systems and radio technologies. The following description describes a New Radio (NR) system for exemplary purposes and NR terminology is used in much of the following description, but these techniques may also be applied to applications other than NR system applications, such as 6 th Generation (6G) communication systems.
Fig. 1 shows a block diagram of a wireless communication system to which an embodiment of the present application is applicable. The wireless communication system includes a terminal 11 and a network device 12. The terminal 11 may be a Mobile phone, a tablet Computer (Tablet Personal Computer), a Laptop (Laptop Computer) or a terminal-side device called a notebook, a Personal digital assistant (Personal DIGITAL ASSISTANT, PDA), a palm Computer, a netbook, an ultra-Mobile Personal Computer (ultra-Mobile Personal Computer, UMPC), a Mobile internet appliance (Mobile INTERNET DEVICE, MID), an augmented reality (augmented reality, AR)/Virtual Reality (VR) device, a robot, a wearable device (Wearable Device), a vehicle-mounted device (VUE), a pedestrian terminal (PUE), a smart home (home device with a wireless communication function, such as a refrigerator, a television, a washing machine, a furniture, etc.), a game machine, a Personal Computer (Personal Computer, a PC), a teller machine, or a self-service machine, etc., and the wearable device includes: intelligent wrist-watch, intelligent bracelet, intelligent earphone, intelligent glasses, intelligent ornament (intelligent bracelet, intelligent ring, intelligent necklace, intelligent anklet, intelligent foot chain etc.), intelligent wrist strap, intelligent clothing etc.. It should be noted that the specific type of the terminal 11 is not limited in the embodiment of the present application. The network-side device 12 may include an access network device and/or a core network device, where the access network device 12 may also be referred to as a radio access network device, a radio access network (Radio Access Network, RAN), a radio access network function, or a radio access network element. Access network device 12 may include a base station, a WLAN access Point, a WiFi node, or the like, which may be referred to as a node B, an evolved node B (eNB), an access Point, a base transceiver station (Base Transceiver Station, BTS), a radio base station, a radio transceiver, a Basic service set (Basic SERVICE SET, BSS), an Extended service set (Extended SERVICE SET, ESS), a home node B, a home evolved node B, a transmission and reception Point (TRANSMITTING RECEIVING Point, TRP), or some other suitable terminology in the art, and the base station is not limited to a particular technical vocabulary so long as the same technical effect is achieved, and it should be noted that in the embodiment of the present application, only a base station in an NR system is described as an example, and the specific type of the base station is not limited.
The following describes in detail, with reference to the attached drawings, the identification schemes of the bad cells provided by the embodiments of the present application through some embodiments and application scenarios thereof.
The wireless part with the greatest influence on the perception of the user in the wireless internet, but the capacity limitation of the cell in the wireless internet frequently happens because the capacity of the wireless cell cannot be increased limitlessly due to the lack of wireless spectrum resources and the capacity of a specific cell cannot be predicted accurately due to the strong mobility of the user. In a cell with limited capacity, if a large number of users suddenly appear or the service suddenly increases at a certain time, the perception of a large number of users under the cell is deteriorated. It follows that capacity limitation and user perceived difference are strongly correlated and user perceived and cell load are time-varying. Therefore, the embodiment of the application provides a method for identifying a poor quality cell, which evaluates the user perception and load conditions of the cell from small time granularity (such as 15 minutes or 1 hour, which is called a time slice in the embodiment of the application), judges that the cell is mainly due to poor user perception if the number of time slices in which the user perception difference and the load are high exceeds a certain threshold value, and judges that other poor quality reasons possibly exist in the cell and needs to be checked in a key way if the number of time slices in which the user perception difference and the medium and low load are simultaneously exceeds a certain threshold value.
Fig. 2 is a flow chart of a method for identifying a bad cell in an embodiment of the application, and the method 200 may be performed by an electronic device. In other words, the method may be performed by software or hardware installed on an electronic device. As shown in fig. 2, the method may include the following steps.
S210, obtaining service times of the target cell in each time slice and times of occurrence of service quality differences of the target type service, wherein each time slice is divided according to preset time granularity.
In the embodiment of the present application, the time slices may be divided according to a preset time granularity, and one time slice may include one time granularity, for example, the time granularity may be 1 hour, one time slice may include one hour, or the time granularity may be 15 minutes, and one time slice may include 15 minutes.
The selection of the time slice size may be determined according to the variability of the sensing and the capacity and the computing load, which is not limited in the embodiment of the present application.
In the embodiment of the application, the target type service used for evaluation can be a predetermined type service or a service provided by a server with stable service quality. For example, the target type service may be some typical service, such as a common service using web browsing, video, games, and the like. Or a part of services provided by the server with stable service quality can be selected.
In one possible implementation, the obtaining the number of times of occurrence of the service quality difference in each time slice may include the following steps:
Step 1, obtaining media surface user service data of the target cell in each time slice;
and step 2, performing user perception evaluation based on the media surface user service data in each time slice, and obtaining the times of occurrence of service quality differences in each time slice.
In the above possible implementation manner, media plane data of a target cell in the wireless communication system may be acquired, key transmission parameters may be extracted, and whether there is a service quality difference is determined according to a predefined model, so as to determine the number of times of occurrence of the service quality difference in each time slice.
For example, the media plane data of the target cell may be acquired through a media plane probe, for example, the media plane data is copied to the media plane probe by a beam-splitting manner at an S1-U interface of a base station and a service gateway (SERVING GATEWAY, SGW) of long term evolution (Long Term Evolution, LTE), or the media plane data is copied to the media plane probe by a beam-splitting manner at an N3 interface of a base station and a user plane function (User Plane Function, UPF) of a New air interface (New Radio, NR). The media plane probe is responsible for extracting critical traffic data, such as transmission control protocol (Transmission Control Protocol, TCP) link setup delay, download rate, etc., from the media plane message. And judging whether the user requirement is met or not based on the key service data output by the media surface probe, whether the downloading rate is qualified or not, whether the video is stuck or not and the like, thereby determining whether the service quality is poor or not. And further, the times of occurrence of service quality difference in each time slice can be obtained.
It should be noted that, in the embodiment of the present application, the specific manner of evaluating the key service data and service awareness extracted by the media plane probe is not limited.
S212, determining the business quality difference proportion of the target cell in each time slice according to the business times and the business quality difference times in each time slice.
In the embodiment of the present application, for each time slice, the service quality difference ratio in the time slice may be obtained according to the number of times of occurrence of the target type service and the number of times of occurrence of the service quality difference in the time slice. For example, assuming that the number of times of occurrence of the target type service in a certain time slice is N and the number of times of occurrence of the service quality difference is N, the service quality difference ratio of the target cell in the time slice is N/N.
And S214, acquiring the capacity proportion of the target cell in each time slice.
In a specific application, because different cells have different bandwidths, different uplink and downlink proportions, different antennas and the like, the throughput of the different cells may be different, and therefore, in the embodiment of the application, different expected capacity values can be set for different types of cells.
In the embodiment of the application, the capacity proportion of the target cell in each time slice can be obtained according to the capacity load of the target cell in each time slice and the expected capacity value of the target cell.
The capacity load of the target cell may be obtained in various ways, for example, key performance index (Key Performance Indicator, KPI) data directly output by the base station may be used, or throughput obtained by statistics of the media plane probe may also be directly used.
Thus, in one possible implementation, obtaining the capacity fraction of the target cell within each time slice may comprise the steps of:
Step 1, obtaining throughput of the target cell in each time slice; for example, the throughput of the target cell in each time slice is counted using the media plane probe.
And 2, calculating the ratio of the throughput in each time slice to the expected capacity of the target cell to obtain the capacity ratio in each time slice.
In a specific application, the throughput of a cell generally includes two groups of uplink throughput and downlink throughput, the ratio of the throughput to the expected capacity can be calculated respectively, and the one with the highest ratio is selected as the total cell load. Thus, in one possible implementation, in the above step 2, for any time slice, the capacity ratio in that time slice in the target cell may be obtained by:
Step 21, calculating a first ratio of the downlink throughput of the target cell in the time slice to the expected capacity.
Step 22, calculating a second ratio of the uplink throughput of the target cell in the time slice to the expected capacity;
And step 23, taking the maximum value of the first ratio and the second ratio as the capacity proportion of the target cell in the time slice.
For example, if the ratio of the downlink throughput to the expected capacity of the target cell in a certain time slice is 90% and the ratio of the uplink throughput to the expected capacity is 20%, the ratio of the downlink throughput to the expected capacity is 90% as the load ratio, i.e., the capacity ratio, of the target cell in the time slice.
In one possible implementation, the traffic quality difference proportion of each time slice and the capacity proportion of each time slice in the preset time period can be summarized according to the time slices. In this possible implementation manner, the traffic quality difference proportion and the capacity proportion of each time slice in the target cell may be summarized, so as to obtain the traffic quality difference proportion and the capacity proportion of each time slice.
In the above possible implementation manner, the preset time period may be a longer time range including a plurality of time slices, for example, the preset time period may be 1 day, or 12 hours, or 1 week, etc.
In one possible implementation manner, to ensure statistical stability, only time slices in which the number of service times exceeds a certain threshold may be used, for example, when summarizing, time slices in which the number of service times exceeds a first threshold in the preset time period may be selected, and time slices in which the number of service times is less than the first threshold in the preset time period may not be summarized.
And S216, identifying the quality difference type of the target cell based on the service quality difference proportion of the target cell in each time slice and the capacity proportion of the target cell in each time slice.
In one possible implementation, S216 may include: and determining the target cell as a capacity-limited bad quality cell under the condition that the number of first target time slices in a preset time period exceeds a first threshold value and the number of second target time slices in a plurality of first target time slices exceeds a second threshold value, wherein the preset time period comprises a plurality of time slices, the first target time slices are time slices in which the business bad quality ratio in the time slices meets a preset condition, and the second target time slices are time slices in which the capacity ratio exceeds a fourth threshold value.
In the embodiment of the present application, the first target time slice may be defined as a bad traffic time slice, that is, a time slice satisfying the predetermined condition is a bad traffic time slice.
Wherein the predetermined condition may include one of:
(1) The traffic quality difference ratio exceeds a third threshold. For example, the third threshold may be predefined, and when the quality of service difference ratio in one time slice exceeds the third threshold, the time slice is considered as a quality of service difference time slice.
(2) Belonging to N time slices with highest service quality difference proportion in a preset time period, wherein N is an integer greater than or equal to 1. The N time slices with the highest service quality difference proportion in the preset time period are defined as service quality difference time slices. The specific value of N may be set according to practical situations, which is not limited in the embodiment of the present application.
In the embodiment of the present application, if the capacity ratio of a certain time slice exceeds a fourth threshold, the time slice may be defined as a high load time slice (i.e., a second target time slice), and if the number of poor service time slices exceeds a first threshold and the number of high load times in the poor service time slices exceeds a second threshold within a certain preset time period, it may be determined that the target cell is a capacity limited poor service cell.
In one possible implementation, S216 may further include: and determining the target cell as a wireless quality difference cell under the condition that the number of the first target time slices of the target cell in a preset time period exceeds a fifth threshold value and the number ratio of the second target time slices in a plurality of first target time slices does not exceed a sixth threshold value.
In the embodiment of the present application, if the capacity ratio of a certain time slice exceeds a fifth threshold, the time slice may be defined as a high load time slice (i.e., a second target time slice), and if the number of poor quality of service time slices exceeds a first threshold and the number of high load times in the poor quality of service time slices does not exceed a sixth threshold in a certain preset time period, it may be determined that the target cell is a poor quality of radio cell.
The fifth threshold may be the same as the first threshold, but is not limited to this, and the fifth threshold may be different from the first threshold, that is, the same number of quality of service slots may be set for the capacity-limited quality difference cell and the radio quality difference cell, and different number of quality of service slots may be set.
In addition, the sixth threshold may be the same as the second threshold or may be different from the second threshold, that is, the same high-load time slice number ratio threshold may be set for the capacity-limited bad cell and the radio bad cell, or different high-load time slice number ratio thresholds may be set, which may be specifically determined according to practical applications.
By the technical scheme provided by the embodiment of the application, whether the target cell is the capacity-limited bad cell can be determined according to the service bad time slice of the target cell in the preset time period and the duty ratio of the time slice with larger capacity load, so that the accuracy of identifying the bad cell is improved, and the positioning speed of the subsequent network bad cell can be accelerated.
In particular, in the application, the quality difference cells may be identified for the plurality of cells to be processed according to the processing manner of the target cell.
Fig. 3 is a schematic flow chart of another method for identifying a bad cell according to an embodiment of the present application, and as shown in fig. 3, the method 300 mainly includes the following steps.
S310, acquiring media surface data of a cell to be processed in the wireless communication system, extracting key transmission parameters, and judging whether the service quality is poor according to a predefined model.
For example, media plane data of a cell to be processed is acquired through a media plane probe, for example, the media plane data is copied to the media plane probe in a beam-splitting manner at an S1-U interface of a base station and a service gateway (SERVING GATEWAY, SGW) of long term evolution (Long Term Evolution, LTE), or the media plane data is copied to the media plane probe in a beam-splitting manner at an N3 interface of a base station and a user plane function (User Plane Function, UPF) of a New air interface (New Radio, NR). The media plane probe is responsible for extracting critical traffic data, such as transmission control protocol (Transmission Control Protocol, TCP) link setup delay, download rate, etc., from the media plane message. And judging whether the user requirement is met or not based on the key service data output by the media surface probe, whether the downloading rate is qualified or not, whether the video is blocked or not, and the like.
The method for evaluating the key service data and service perception extracted by the media surface probe is not particularly limited in the application.
S312, calculating the business quality difference proportion of each cell according to the time slices.
In the embodiment of the application, a time slice with a proper size can be selected, the size of the time slice can be determined according to the variability of perception and capacity and the calculation load, and the time slice is generally selected to be 15 minutes or 1 hour. And calculating the frequency of occurrence business and the frequency of quality difference of each cell in the time slice, and calculating the business quality difference proportion.
Alternatively, some of the services may be used, for example, some of the typical services may be selected, such as common services using web browsing, video, games, etc. Only a portion of the servers with stable quality of service may be selected for evaluation.
S314, the load ratio (i.e., the capacity ratio) of each cell is calculated in time slices.
In the embodiment of the application, the obtained cell throughput is different in consideration of different bandwidths, different uplink and downlink proportions, different antennas and the like of different cells. Thus, different desired capacity values may be set for different types of cells.
The cell capacity load can be obtained through various ways, for example, KPI data directly output by a base station can be used, and throughput obtained through statistics by a media plane probe can be directly used. The present invention is not particularly limited.
Alternatively, the cell-to-cell time slice statistics may be calculated to obtain the ratio of the throughput of the cell to the expected capacity as the cell load ratio.
The cell throughput generally comprises two groups of uplink throughput and downlink throughput, the ratio of the uplink throughput to the expected capacity of the cell and the ratio of the downlink throughput to the expected capacity of the cell can be calculated for one cell, and the cell load ratio with the highest ratio is selected as the cell load ratio of the cell. The desired capacity ratio of the downlink throughput is 90%, and the desired capacity ratio of the uplink throughput is 20%, and the desired capacity ratio of the downlink throughput is 90% is selected as the cell load ratio.
S316, summarizing the business quality difference proportion and the load proportion of each time slice of each cell.
The traffic quality difference ratio obtained in S312 and the load ratio obtained in S314 are summarized based on the cell and the time slice.
And S318, outputting a capacity limited cell list and a wireless quality difference cell list according to the service quality difference proportion and the load proportion of each cell in each time slice in a long time range.
Wherein the long time range may comprise a plurality of time slices, such as selected in days/week.
Alternatively, to ensure statistical stability, only time slices with traffic times exceeding a certain threshold may be used in S318.
In the embodiment of the application, the time slices with the service quality difference can be defined as time slices with the service quality difference ratio exceeding a threshold value, and N time slices with the highest service quality difference ratio can be selected as the time slices with the service quality difference.
In the embodiment of the application, the time slices with the load proportion exceeding the threshold value can be defined as high-load time slices.
In S318, a cell whose number of bad traffic time slices exceeds a threshold and whose number of high load time slices is a ratio of the number of bad traffic time slices to the ratio of the number of high load time slices exceeds a specific threshold may be selected as a capacity-limited cell according to time slices within a long time granularity of cell aggregation.
And selecting the cells with the number of the service quality difference time slices exceeding the threshold value and the number of the service quality difference time slices which are not high-load time slices and the ratio of which exceeds the threshold value as the wireless quality difference cells according to the time slices within the long-time granularity of the cell aggregation.
The service quality difference time slice number thresholds of the capacity limited cell and the wireless quality difference cell can be different or the same. The duty ratio threshold of the high load time slices in the poor service time slices can be the same or different.
By adopting the method provided by the embodiment of the application, the user perception and the cell capacity load are combined and considered in time slices, and the quality difference cell possibly having wireless problems due to capacity reasons are separated from the perception difference cell based on the high and low levels of the cell capacity load in the quality difference time slices, so that the subsequent differential treatment is convenient, the accuracy of a quality difference list is improved, and the quality difference positioning speed of a subsequent network is accelerated.
Based on the same technical conception, the embodiment of the application also provides a device for identifying the quality difference cell.
Fig. 4 is a schematic structural diagram of an apparatus for identifying a bad cell according to an embodiment of the present application, and as shown in fig. 4, the apparatus 400 mainly includes: a user service data acquisition module 401, a service perception evaluation module 402, a cell-level service quality difference proportion calculation module 403, a cell-level capacity proportion calculation module 404 and a quality difference cell screening module 405.
In the embodiment of the present application, a user service data acquisition module 401 is configured to acquire media plane user data; the service perception evaluation module 402 is configured to evaluate user perception based on the user data collected by the user service data collection module 401, and distinguish whether a quality difference exists; a cell-level service quality difference ratio calculating module 403, configured to calculate a service quality difference ratio of each cell in each time slice; a cell-level capacity ratio calculation module 404, configured to calculate a capacity ratio of each cell in each time slice; the quality difference cell screening module 405 is configured to screen the capacity limited cell list and the radio quality difference cell list according to a predetermined threshold based on the service quality difference ratio of each cell in each time slice calculated by the cell-level service quality difference ratio calculation module 403 and the capacity ratio of each cell in each time slice calculated by the cell-level capacity ratio calculation module 404.
The specific implementation manner of the bad cell screening module 405 for screening the capacity limited cell list and the radio bad cell list may be referred to the related description in the above method 300, and will not be described herein.
Optionally, as shown in fig. 5, the embodiment of the present application further provides an electronic device 500, including a processor 501 and a memory 502, where the memory 502 stores a program or an instruction that can be executed on the processor 501, and the program or the instruction implements the steps of the above-mentioned embodiment of the quality difference cell identification method when executed by the processor 501, and can achieve the same technical effects.
The embodiment of the application also provides a readable storage medium, on which a program or an instruction is stored, which when executed by a processor, implements each process of the above-mentioned embodiment of the method for identifying a bad cell, and can achieve the same technical effects, so that repetition is avoided, and no further description is given here.
Wherein the processor is a processor in the terminal described in the above embodiment. The readable storage medium includes computer readable storage medium such as computer readable memory ROM, random access memory RAM, magnetic or optical disk, etc.
The embodiment of the application further provides a chip, the chip comprises a processor and a communication interface, the communication interface is coupled with the processor, the processor is used for running a program or instructions, the processes of the above-mentioned quality difference cell identification method embodiment can be realized, the same technical effects can be achieved, and the repetition is avoided, and the description is omitted here.
It should be understood that the chips referred to in the embodiments of the present application may also be referred to as system-on-chip chips, or the like.
The embodiment of the present application further provides a computer program/program product, where the computer program/program product is stored in a storage medium, and the computer program/program product is executed by at least one processor to implement each process of the above-mentioned embodiment of the method for identifying a bad cell, and the same technical effects can be achieved, so that repetition is avoided, and details are not repeated here.
It should be noted that, in this document, 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 one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element. Furthermore, it should be noted that the scope of the methods and apparatus in the embodiments of the present application is not limited to performing the functions in the order shown or discussed, but may also include performing the functions in a substantially simultaneous manner or in an opposite order depending on the functions involved, e.g., the described methods may be performed in an order different from that described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a computer software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) comprising instructions for causing a terminal (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the method according to the embodiments of the present application.
The embodiments of the present application have been described above with reference to the accompanying drawings, but the present application is not limited to the above-described embodiments, which are merely illustrative and not restrictive, and many forms may be made by those having ordinary skill in the art without departing from the spirit of the present application and the scope of the claims, which are to be protected by the present application.
Claims (12)
1. The method for identifying the quality difference cell is characterized by comprising the following steps of:
Acquiring service times of the target cell in each time slice and times of occurrence of service quality differences of the target type service, wherein each time slice is divided according to preset time granularity;
Determining the business quality difference proportion of the target cell in each time slice according to the business times and the business quality difference times in each time slice;
acquiring the capacity proportion of the target cell in each time slice;
And identifying the quality difference type of the target cell based on the service quality difference proportion of the target cell in each time slice and the capacity proportion of the target cell in each time slice.
2. The method of claim 1, wherein identifying the quality of coverage type of the target cell based on the quality of service ratio of the target cell within each of the time slices and the capacity ratio of the target cell within each of the time slices comprises:
And determining the target cell as a capacity-limited bad quality cell under the condition that the number of first target time slices in a preset time period exceeds a first threshold value and the number of second target time slices in a plurality of first target time slices exceeds a second threshold value, wherein the preset time period comprises a plurality of time slices, the first target time slices are time slices in which the business bad quality ratio in the time slices meets a preset condition, and the second target time slices are time slices in which the capacity ratio exceeds a fourth threshold value.
3. The method of claim 2, wherein identifying the quality of coverage type of the target cell based on the quality of service ratio of the target cell within each of the time slices and the capacity ratio of the target cell within each of the time slices further comprises:
And determining the target cell as a wireless quality difference cell under the condition that the number of the first target time slices of the target cell in a preset time period exceeds a fifth threshold value and the number ratio of the second target time slices in a plurality of first target time slices does not exceed a sixth threshold value.
4. A method according to claim 2 or 3, wherein the predetermined condition comprises: and the business quality difference ratio exceeds a third threshold value, or N time slices with the highest business quality difference ratio in the preset time period belong to, wherein N is an integer greater than or equal to 1.
5. A method according to claim 2 or 3, wherein the predetermined period of time comprises a number of traffic times within each of the plurality of time slices exceeding a first threshold.
6. A method according to claim 2 or 3, wherein obtaining the number of times the target cell has a poor quality of service in each time slice comprises:
Acquiring media surface user service data of the target cell in each time slice;
And carrying out user perception evaluation based on the media surface user service data in each time slice, and obtaining the times of occurrence of service quality difference in each time slice.
7. A method according to claim 2 or 3, wherein obtaining the proportion of capacity of the target cell within each of the time slices comprises:
acquiring throughput of the target cell in each time slice;
And calculating the ratio of the throughput in each time slice to the expected capacity of the target cell to obtain the capacity ratio in each time slice.
8. The method of claim 7, wherein the throughput comprises a downstream throughput and an upstream throughput;
For a time slice, calculating a ratio of the throughput to the expected capacity of the target cell, to obtain a capacity ratio in the time slice, including:
Calculating a first ratio of the downlink throughput of the target cell in the time slice to the expected capacity;
calculating a second ratio of the uplink throughput of the target cell in the time slice to the expected capacity;
And taking the maximum value of the first ratio and the second ratio as the capacity proportion of the target cell in the time slice.
9. A method according to claim 2 or 3, characterized in that the method further comprises:
and summarizing the service quality difference proportion of each time slice and the capacity proportion of each time slice in the preset time period according to the time slices.
10. The method according to claim 1 or 2, wherein the target type of traffic comprises: the service of the preset service type or the service processed by the preset server.
11. An electronic device comprising a processor and a memory storing a program or instructions executable on the processor, which when executed by the processor, performs the steps of the method of identifying a bad cell according to any of claims 1 to 10.
12. A readable storage medium, wherein a program or instructions is stored on the readable storage medium, which when executed by a processor, implements the steps of the method for identifying a bad cell according to any of claims 1 to 10.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211348383.2A CN117998451A (en) | 2022-10-31 | 2022-10-31 | Quality difference cell identification method, electronic equipment and storage medium |
| PCT/CN2023/108052 WO2024093364A1 (en) | 2022-10-31 | 2023-07-19 | Recognition method for poor-quality cell, and electronic device and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211348383.2A CN117998451A (en) | 2022-10-31 | 2022-10-31 | Quality difference cell identification method, electronic equipment and storage medium |
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| CN117998451A true CN117998451A (en) | 2024-05-07 |
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| CN202211348383.2A Pending CN117998451A (en) | 2022-10-31 | 2022-10-31 | Quality difference cell identification method, electronic equipment and storage medium |
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| CN (1) | CN117998451A (en) |
| WO (1) | WO2024093364A1 (en) |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9307428B2 (en) * | 2014-01-07 | 2016-04-05 | Alcatel Lucent | Estimating available cell capacity based on monitored network data |
| CN110796366A (en) * | 2019-10-28 | 2020-02-14 | 中国联合网络通信集团有限公司 | Quality difference cell identification method and device |
| CN113068213B (en) * | 2020-01-02 | 2023-01-10 | 中国移动通信集团设计院有限公司 | Network capacity evaluation processing method and device, electronic equipment and storage medium |
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- 2022-10-31 CN CN202211348383.2A patent/CN117998451A/en active Pending
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| WO2024093364A1 (en) | 2024-05-10 |
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