Mobile network performance evaluation method and device, electronic equipment and storage medium

Abstract

The invention provides a mobile network performance evaluation method and device, electronic equipment and a storage medium, and relates to the field of wireless communication. The evaluation method comprises the following steps: acquiring network performance original data based on wireless call record trace data and application layer service OTT data under a target cell within a sampling period; performing corresponding data processing on the network performance original data based on the trace data and the OTT data to obtain network performance indexes based on the trace data and the OTT data; and fusing the network performance indexes based on the trace data and the OTT data to obtain a multi-dimensional network performance index system based on fused data, which is used for evaluating the mobile network performance of the target cell. The method and the device are used for at least solving the problem that wireless network quality evaluation in the prior art cannot truly reflect real perception and use experience when a user accessed to a network uses the network to carry out various applications. The method is suitable for scenes such as network evaluation and optimization.

Description

Technical Field

[0001] The present invention relates to the field of wireless communications, and in particular to a method, device, electronic device and computer-readable storage medium for evaluating mobile network performance. Background Art

[0002] With the coordinated deployment and development of 4 / 5G (the 4 / 5 Generation mobile communication technology) networks and the continuous updating of mobile phone applications, the usage habits of wireless network users are also changing, and the quality requirements for network services provided by operators are becoming more stringent. Therefore, the evaluation of network quality urgently needs to change from quality management based on the network itself to a quality assurance mechanism that focuses on customer perception.

[0003] With the development of science and technology in recent years, innovative applications of mobile terminals have emerged in an endless stream, and users' usage habits have also shifted from the previous simple voice, text and picture applications to various usage scenarios such as short videos, high-definition videos, online games, and mobile payments. The existing wireless network quality assessment data source mainly comes from northbound network management data. The data sampling time granularity is large (the minimum is hourly data) and can only objectively reflect whether the network performance indicators are good or not, but cannot truly reflect the actual perception and usage experience of users connected to the current network when using the network for various applications. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide a method, device, electronic device and computer-readable storage medium for evaluating mobile network performance in view of the above-mentioned deficiencies in the prior art. The method can truly reflect the actual perception and usage experience of users connected to the current network when using the network for various applications, and accurately evaluate the mobile network performance perceived by users from the user's perspective.

[0005] In a first aspect, the present invention provides a method for evaluating mobile network performance, the method comprising: obtaining original network performance data based on wireless call record trace data and application layer service OTT data in a target cell within a sampling period; performing corresponding data processing on the original network performance data based on trace data and OTT data respectively to obtain network performance indicators based on trace data and OTT data; fusing the network performance indicators based on trace data and OTT data to obtain a multi-dimensional network performance indicator system based on fused data, which is used to evaluate the mobile network performance of the target cell.

[0006] Preferably, the network performance original data based on trace data and OTT data are respectively processed accordingly to obtain network performance indicators based on trace data and OTT data, specifically including: calculating the access success rate, disconnection rate and switching success rate of the network performance original data based on trace data to obtain network performance indicators based on trace data, wherein the network performance indicators based on trace data include one or more of the following combinations: target cell identifier, start and end time, access success rate, disconnection rate, switching success rate; obtaining the average value of each performance indicator corresponding to the target APP under the target cell from the network performance original data based on OTT data, and performing weighted summation on the average value of each performance indicator corresponding to the target APP to obtain the network performance indicator based on OTT data, wherein the network performance indicators based on OTT data include one or more of the following combinations: target cell identifier, start and end time, reference signal received power, reference signal signal-to-interference ratio, downlink rate, uplink rate, browsing service delay, video service freeze number of times, and travel time between network packages PING service delay.

[0007] Preferably, the calculation of the access success rate, the disconnection rate and the switching success rate of the original network performance data based on the trace data specifically includes: calculating the access success rate, the disconnection rate and the switching success rate respectively according to the following formulas: Access success rate = number of successful wireless control RRC connection establishment times / number of RRC connection establishment requests; Disconnection rate = (number of abnormal wireless link releases + number of wireless link reconstructions) / (number of abnormal wireless link releases + number of positive wireless link releases + number of wireless link reconstructions); Switching success rate = number of successful switching times / number of switching requests.

[0008] Preferably, the method of obtaining the average value of each performance indicator corresponding to the target APP in the target cell from the original network performance data based on OTT data, and weighted summing the average values ​​of each performance indicator corresponding to the target APP to obtain the network performance indicator based on OTT data specifically includes: obtaining the average value of each performance indicator corresponding to the target APP in the target cell from the original network performance data based on OTT data, and weighted summing the average values ​​of each performance indicator corresponding to the target APP according to the APP list of the target cell and the following formula:

[0009]

[0010]

[0011]

[0012]

[0013]

[0014]

[0015]

[0016] Among them, A1, A2...An are the number of times the corresponding target APP in the APP list of the target cell appears in the sampling period, RSRP1, RSRP2,..., RSRPn are the average values ​​of the reference signal received power of the corresponding target APP in the APP list of the target cell in the sampling period, SINR1, SINR2,..., SINRn are the average values ​​of the reference signal signal-to-interference ratio of the corresponding target APP in the APP list of the target cell in the sampling period, DL_THROUGHOUT1, DL_THROUGHPUT2,..., DL_THROUGHPUTn are the average values ​​of the downlink rate of the corresponding target APP in the APP list of the target cell in the sampling period, UL_THROUGHPUT1, UL_THROUGHPUT2, UL_THROUGHPUTn are the average values ​​of the downlink rate of the corresponding target APP in the APP list of the target cell in the sampling period, UT2, …, UL_THROUGHPUTn are respectively the average uplink rates of the corresponding target APPs in the APP list of the target cell during the sampling period, HTTP_DELAY1, HTTP_DELAY2, …, HTTP_DELAYn are respectively the average browsing service delays of the corresponding target APPs in the APP list of the target cell during the sampling period, VIDEO_CATON1, VIDEO_CATON2, …, VIDEO_CATON are respectively the average number of video service freezes of the corresponding target APPs in the APP list of the target cell during the sampling period, PING1, PING2, …, PINGn are respectively the average PING service delays of the corresponding target APPs in the APP list of the target cell during the sampling period.

[0017] Preferably, before calculating the access success rate, the disconnection rate and the switching success rate of the network performance original data based on the trace data, it also includes: parsing the service quality classification identifier QCI in the network performance original data based on the trace data; filtering out the network performance original data based on the trace data corresponding to the target QCI, for calculating the access success rate, the disconnection rate and the switching success rate.

[0018] Preferably, the network performance indicators based on trace data and OTT data are integrated to obtain a multi-dimensional network performance indicator system based on the integrated data, specifically including: integrating the network performance indicators based on trace data and OTT data based on the target cell identifier and start and end time to obtain a multi-dimensional network performance indicator system based on the integrated data.

[0019] Preferably, after obtaining the multidimensional network performance indicator system based on fused data, it also includes: obtaining the geographical location, site information, and antenna performance in the target cell engineering parameter table based on the target cell identifier; associating the geographical location, site information, and antenna performance of the target cell with the multidimensional network performance indicator system based on fused data, and visually displaying the association results in a geographic information system. According to the International Mobile Subscriber Identity IMSI / International Mobile Equipment Identity IMEI, the multidimensional network performance indicator system corresponding to the target user is screened out from the multidimensional network performance indicator system based on fused data, and used to evaluate the mobile network performance perceived by the target user in the target cell.

[0020] In a second aspect, the present invention also provides a mobile network performance evaluation device, which includes: an acquisition module, used to obtain original network performance data based on wireless call record data trace and application service data OTT; a data processing module, connected to the collection and acquisition module, used to perform corresponding data processing on the original network performance data of trace and OTT respectively, to obtain network performance indicators of trace and OTT; an evaluation and analysis module, connected to the data processing module, used to fuse the network performance indicators of trace and OTT, to obtain a multi-dimensional network performance indicator system based on the fused data, for evaluating mobile network performance.

[0021] In a third aspect, the present invention further provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to implement the evaluation method provided in the first aspect.

[0022] In a fourth aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the evaluation method provided in the first aspect is implemented.

[0023] The present invention provides a method, device, electronic device and computer-readable storage medium for evaluating mobile network performance. The key indicators for evaluating the network wireless performance of the evaluation cell are constructed through the target key fields in the trace data, and then the relevant service experience indicators in the OTT data are associated with the evaluation cell, and finally the comprehensive evaluation indicator system of the network performance of the evaluation cell is obtained. Since the OTT data comes from the application service data of the smart terminal, the indicators based on the OTT data can reflect the user's perception of network performance. Therefore, the present invention introduces multi-source data such as trace data and OTT data, and constructs a network evaluation system based on multi-source data, so that the evaluation results based on the network evaluation system are closer to the user's real network usage experience, so that it can ultimately provide more accurate guidance on the operator's network optimization work and optimization focus. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 This is a flow chart of a method for evaluating mobile network performance according to Embodiment 1 of the present invention;

[0025] Figure 2 This is a schematic diagram of the structure of a mobile network performance evaluation device according to Embodiment 2 of the present invention;

[0026] Figure 3 This is a structural diagram of a data processing module in a mobile network performance evaluation device according to Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0027] In order to enable those skilled in the art to better understand the technical solution of the present invention, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0028] It should be understood that the specific embodiments and drawings described herein are only used to explain the present invention rather than to limit the present invention.

[0029] It can be understood that, in the absence of conflict, the various embodiments of the present invention and the various features in the embodiments can be combined with each other.

[0030] It can be understood that, for the convenience of description, the drawings of the present invention only show the parts related to the present invention, while the parts irrelevant to the present invention are not shown in the drawings.

[0031] It can be understood that each unit and module involved in the embodiments of the present invention may correspond to only one physical structure, or may be composed of multiple physical structures, or multiple units and modules may be integrated into one physical structure.

[0032] It can be understood that, without conflict, the functions and steps marked in the flowcharts and block diagrams of the present invention may occur in an order different from that marked in the drawings.

[0033] It is understood that the flowcharts and block diagrams of the present invention illustrate the possible architectures, functions, and operations of the systems, devices, equipment, and methods according to the various embodiments of the present invention. Each box in the flowchart or block diagram may represent a unit, module, program segment, or code, which contains executable instructions for implementing the specified functions. Moreover, each box or combination of boxes in the block diagram and flowchart may be implemented by a hardware-based system that implements the specified functions, or may be implemented by a combination of hardware and computer instructions.

[0034] It can be understood that the units and modules involved in the embodiments of the present invention can be implemented by software or hardware. For example, the units and modules can be located in a processor.

[0035] Embodiment 1:

[0036] This embodiment provides a method for evaluating the performance of a mobile network. As Figure 1 shown, the method for evaluating the performance of a mobile network includes:

[0037] Step S101, obtain the original network performance data based on wireless call record trace data and application layer service OTT data under the target cell within the sampling period.

[0038] In this embodiment, the sampling period generally refers to the sampling duration of the trace data. Generally, the sampling start time is set as T1, and the sampling end time (the sampling start time and the sampling end time are equivalent to the start time and the end time of the start and end times in the following text) is T2. The sampling duration (sampling period granularity) is denoted as ΔT = T2 - T1. The sampling duration of the trace data can be accurate to a 5-minute granularity, or can be customized according to different requirements for analyzing network problems, such as 15 minutes, 30 minutes, etc. It can also be flexibly set according to the sampling time T' of the subsequent OTT data and the time range requirements for network analysis. By screening the data with the same ECI (cell unique identifier) in the OTT data and the trace data, that is, ensuring that all data are the network performance data of the target cell (such as target cell A) in the network. Among the screened data, further extract the OTT data that satisfies the time range of T1 < T' < T2, and the original network performance data based on the trace and OTT under this cell within the sampling period ΔT can be obtained.

[0039] In this embodiment, the key fields of the trace data mainly include: cell information, start and end times (start time and end time, abbreviated as start and end times), RRC connection establishment type, RRC connection status, handover situation, etc., as shown in Table 1:

[0040] Table 1 Key fields of the trace data

[0041]

[0042] In this embodiment, the OTT data includes three major types of data: network collection information, user information (desensitized), and service experience information. In addition, the OTT data also contains other aspects of data. Limited by data security and user information protection, on the premise of protecting user privacy and strictly complying with data usage specifications, the OTT-related data is utilized to construct the network performance evaluation system to the minimum extent.

[0043] Among them, the OTT data is shown in Tables 2 - 4:

[0044] Table 2 OTT network collection information

[0045]

[0046] Table 3 User information

[0047] English name Chinese name IMSI International Mobile Subscriber Identity IMEI International Mobile Equipment Identity Number APP_LIST APP List

[0048] Table 4 Service experience information

[0049] English name Chinese name DL_THROUGHPUT Downlink rate UL_THROUGHPUT Uplink rate HTTP_DELAY Browsing service delay VIDEO_CATON Video service freeze times PING PING service delay

[0050] Step S102, performing corresponding data processing on the original network performance data based on the trace data and the OTT data, respectively, to obtain network performance indicators based on the trace data and the OTT data.

[0051] Specifically, step 102: performing corresponding data processing on the original network performance data based on the trace data and the OTT data, respectively, to obtain network performance indicators based on the trace data and the OTT data, including:

[0052] Step 1021, calculate the access success rate, disconnection rate and switching success rate of the original network performance data based on the trace data, and obtain the network performance indicators based on the trace data, wherein the network performance indicators based on the trace data include one or more combinations of the following: target cell identifier, start and end time (start time and end time, referred to as start and end time), access success rate, disconnection rate, and switching success rate.

[0053] In this embodiment, the network performance indicators based on trace data as shown in Table 5 include target cell identifier, start and end time, access success rate, disconnection rate, and switching success rate. Among them, the access success rate is used to characterize the access performance of the network, and the access success rate is evaluated based on the process of establishing the air interface RRC connection, which is defined as the ratio of the number of successful air interface RRC connection establishments to the number of RRC connection establishment requests within the statistical period. The disconnection rate is used to characterize the retention performance of the network, and the disconnection rate is evaluated based on the air interface wireless link release status and the wireless link reconstruction status, which is defined as the ratio of the total number of abnormal wireless link releases and reconstructions within the statistical period to the total number of wireless link releases and reconstructions. The switching success rate is used to characterize the mobility performance of the network, and the network switching success rate is evaluated based on the switching status within and between stations, which is defined as the ratio of the number of successful switching to the number of switching requests within the statistical period.

[0054] Table 5 Examples of network performance indicators based on trace data

[0055] English name Chinese name ECI Target cell ID STARTTIME Start time ENDTIME End time CONACSUC Access success rate CONDROP Drop rate HOSUC Switching success rate

[0056] Specifically, step 1021 includes: calculating the access success rate, the drop rate, and the switching success rate according to the following formulas:

[0057] Access success rate = number of successful RRC connection establishment by wireless control / number of RRC connection establishment requests;

[0058] Drop rate = (number of abnormal releases of the wireless link + number of wireless link reestablishments) / (number of abnormal releases of the wireless link + number of normal releases of the wireless link + number of wireless link reestablishments);

[0059] Switching success rate = number of successful switching / number of switching requests.

[0060] Step 1022, obtain the average value of each performance indicator corresponding to the target APP under the target cell from the original network performance data based on OTT data, and perform weighted summation on the average value of each performance indicator corresponding to the target APP to obtain the network performance indicator based on OTT data, wherein the network performance indicator based on OTT data includes one or more of the following combinations: target cell identifier, start and end time (start time and end time, referred to as start and end time), reference signal received power, reference signal signal-to-interference ratio, downlink rate, uplink rate, browsing service delay, video service freeze times, and travel time between network packages PING service delay. Table 6 shows an example of one combination of network performance indicators based on OTT data.

[0061] Table 6 Example of network performance indicators based on OTT data

[0062]

[0063]

[0064] In this embodiment, because OTT data is network data based on terminal application services, even in the same sampling time T' in the same cell (same ECI), there will be multiple OTT data generated by different users in the target cell using different terminal applications in the current sampling time T', so the processing of OTT data is relatively complicated. Therefore, it is necessary to further process the multiple OTT data. In this embodiment, the main focus is on network parameters such as RSRP, SINR, DL_THROUGHPUT, UL_THROUGHPUT, HTTP_DELAY, VIDEO_CATON and PING. The multiple OTT data are processed by weighted summation, and the APP list (APP_LIST) is used as the counting item of the weighted ratio to be calculated. The number of times the target APP1 appears is recorded as A1, the number of times the target APP2 appears is recorded as A2, and so on. It is assumed that there are n target APPs reporting relevant application data in this sampling period, that is, the number of times the last target APPn appears is recorded as An. The weighted ratios of (APP1, APP2...APPn) obtained in this way are respectively For the same ECI and the same target APP in the same sampling period, the same indicator will theoretically have different numerical results reported by different user terminals. In order to simplify the data calculation and processing process, it is first subjected to an averaging process. Taking RSRP as an example, the RSRP values ​​that meet the above screening conditions are averaged (avg) and recorded as RSRP1 as the network reference signal received power value corresponding to the target APP1. Following the above calculation method, the results of the average calculation of various indicators of different target APPs are respectively marked with numbers. For example, the performance indicators of target APP1 are marked as RSRP1, SINR1, DL_THROUGHPUT1, UL_THROUGHPUT1, HTTP_DELAY1, VIDEO_CATON1 and PING1, and so on until n.

[0065] Specifically, step 1022 includes: obtaining the average value of each performance indicator corresponding to the target APP in the target cell from the original network performance data based on the OTT data,

[0066] According to the APP list of the target cell and the following formula, the average values ​​of the performance indicators corresponding to the target APP are weighted and summed:

[0067]

[0068]

[0069]

[0070]

[0071]

[0072]

[0073]

[0074] Among them, A1, A2...An are the number of times the corresponding target APP in the APP list of the target cell appears in the sampling period, RSRP1, RSRP2,..., RSRPn are the average values ​​of the reference signal received power of the corresponding target APP in the APP list of the target cell in the sampling period, SINR1, SINR2,..., SINRn are the average values ​​of the reference signal signal-to-interference ratio of the corresponding target APP in the APP list of the target cell in the sampling period, DL_THROUGHPUT1, DL_THROUGHPUT2,..., DL_THROUGHPUTn are the average values ​​of the downlink rate of the corresponding target APP in the APP list of the target cell in the sampling period, UL_THROUGHPUT1, UL_THROUGHPUT2, UL_THROUGHPUTn are the average values ​​of the downlink rate of the corresponding target APP in the APP list of the target cell in the sampling period, UT2, ..., UL_THROUGHPUTn are respectively the average uplink rates of the corresponding target APPs in the APP list of the target cell during the sampling period, HTTP_DELAY1, HTTP_DELAY2, ..., HTTP_DELAYn are respectively the average browsing service delays of the corresponding target APPs in the APP list of the target cell during the sampling period, VIDEO_CATON1, VIDEO_CATON2, ..., VIDEO_CATONn are respectively the average video service freeze times of the corresponding target APPs in the APP list of the target cell during the sampling period, PING1, PING2, ..., PINGn are respectively the average PING service delays of the corresponding target APPs in the APP list of the target cell during the sampling period. In this embodiment, in a certain sampling period, 5 types of target APP information are collected in the APP_LIST data, among which target APP1 appears 300 times, target APP2 appears 1500 times, target APP3 appears 450 times, target APP4 appears 2100 times, and target APP5 appears 730 times. Then according to the calculation method of weighted proportion The weighted ratio of target APP1 is calculated as: 300 / (300+1500+450+2100+730)=0.059. Similarly, the weighted ratios of (APP1, APP2, APP3, APP4, APP5) are calculated as (0.059, 0.295, 0.089, 0.413, 0.144) respectively.

[0075] Assume that the relevant indicator values ​​of target APP1-target APP5 are shown in Table 7 below:

[0076] Table 7 Related index values ​​of target APP1-target APP5

[0077]

[0078]

[0079] According to the formula Calculate RSRP e =-88.546, and the formulas for other indicators are deduced in the same way. The weighted average values ​​of various performance indicators are calculated, as shown in Table 8. This simplifies the data calculation process and reduces the amount of subsequent calculations:

[0080] Table 8 Weighted average values ​​of performance indicators

[0081] Performance indicators Weighted mean RSRP_e -88.546 SINR_e 0.991 DL_THROUGHPUT_e 200.565 UL_THROUGHPUT_e 39.595 HTTP_DELAY_e 25.24 VIDEO_CATON_e 33.664 PING_e 117.917

[0082] Step 103, integrating the network performance indicators based on the trace data and the OTT data to obtain a multi-dimensional network performance indicator system based on the integrated data.

[0083] Optionally, step 103: integrating network performance indicators based on trace data and OTT data to obtain a multi-dimensional network performance indicator system based on the integrated data, specifically including: integrating network performance indicators based on trace data and OTT data based on target cell identifiers and start and end times to obtain a multi-dimensional network performance indicator system based on the integrated data.

[0084] In this embodiment, the multi-dimensional network performance indicator system based on fusion data is shown in Table 9. By correlating the network performance indicators of trace data and OTT data, a new network evaluation system is constructed, so that the evaluation results based on the new network evaluation system are closer to the user's real network usage experience, so that it can ultimately provide more accurate guidance on the operator's network optimization work and optimization focus:

[0085] Table 9 Multidimensional network performance index system based on fusion data

[0086] English name Chinese name ECI Target cell ID STARTTIME Start time ENDTIME End time CONACSUC Access success rate CONDROP Drop rate HOSUC Switching success rate RSRP_e Reference signal received power SINR_e Reference signal signal-to-interference ratio DL_THROUGHPUT_e Downlink rate UL_THROUGHPUT_e Uplink rate HTTP_DELAY_e Browsing service delay VIDEO_CATON_e Video service freeze times PING_e PING service delay

[0087] Optionally, in order to further distinguish between voice services, data services, etc., and to conduct more targeted evaluation and problem location on the network, before calculating the access success rate, disconnection rate, and switching success rate of the network performance raw data based on trace data, the evaluation method further includes: parsing the service quality classification identifier QCI in the network performance raw data based on trace data; screening out the network performance raw data based on trace data corresponding to the target QCI, for calculating the access success rate, disconnection rate, and switching success rate.

[0088] In this embodiment, QCI and corresponding service content are shown in Table 10:

[0089] Table 10 QCI and corresponding services

[0090]

[0091]

[0092] Optionally, in order to assist the analysis and optimization of the network more intuitively and in detail, after obtaining the multi-dimensional network performance indicator system based on the fused data, the evaluation method also includes: obtaining the geographical location, site information, and antenna performance in the target cell engineering parameter table based on the target cell identifier; associating the geographical location, site information, and antenna performance of the target cell with the multi-dimensional network performance indicator system based on the fused data, and visually displaying the association results in a geographic information system.

[0093] Optionally, in order to further analyze the network performance from the user / device perspective based on the above, after obtaining the multidimensional network performance indicator system based on fused data, the evaluation method also includes: according to the international mobile user identity code IMSI / international mobile equipment identity code IMEI, the multidimensional network performance indicator system corresponding to the target user is screened out from the multidimensional network performance indicator system based on fused data, which is used to evaluate the mobile network performance perceived by the target user in the target cell. The mobile network performance evaluation method provided in this embodiment constructs key indicators for network wireless performance evaluation through certain key fields in the trace data, and then associates the relevant service experience indicators in the OTT data with the cell described by the trace indicator, and finally obtains a comprehensive network performance evaluation indicator system at the cell level, so that the evaluation results are closer to the user's real network usage experience, so that it can ultimately provide more accurate guidance for the operator's network optimization work and optimization focus. In addition, based on the different values ​​of the QCI field in the trace data field, voice services, data services, etc. are further distinguished, and the network is evaluated and problems are located more specifically. By associating the target cell engineering parameter table and using the geographic information system for visualization, the network analysis and optimization are assisted in a more intuitive and detailed manner. By associating user information fields such as IMSI / IMEI, the obtained network performance evaluation indicators are counted and split in different dimensions, and the network performance is further analyzed from the user / device perspective.

[0094] Embodiment 2:

[0095] like Figure 2 As shown, this embodiment provides a mobile network performance evaluation device, including:

[0096] The acquisition module 21 is used to obtain original network performance data based on wireless call record data trace and application service data OTT.

[0097] The data processing module 22 is connected to the acquisition module and is used to perform corresponding data processing on the original network performance data of the trace and OTT respectively to obtain the network performance indicators of the trace and OTT.

[0098] The evaluation and analysis module 23 is connected to the data processing module and is used to integrate the network performance indicators of trace and OTT to obtain a multi-dimensional network performance indicator system based on the integrated data for evaluating the performance of the mobile network.

[0099] Alternatively, if Figure 3 As shown, the data processing module 22 includes a first data processing submodule 221 and a second data processing submodule 222, and the first data processing submodule 221 and the second data processing submodule 222 are both connected to the acquisition module 21. The first data processing submodule 221 is used to calculate the access success rate, the disconnection rate and the switching success rate of the original network performance data based on the trace data, and obtain the network performance indicators based on the trace data, wherein the network performance indicators based on the trace data include one or more of the following combinations: target cell identifier, start and end time, access success rate, disconnection rate, switching success rate; the second data processing submodule 222 is used to obtain the average value of each performance indicator corresponding to the target APP under the target cell from the original network performance data based on the OTT data, and perform weighted summation on the average value of each performance indicator corresponding to the target APP to obtain the network performance indicators based on the OTT data, wherein the network performance indicators based on the OTT data include one or more of the following combinations: target cell identifier, start and end time, reference signal received power, reference signal signal-to-interference ratio, downlink rate, uplink rate, browsing service delay, video service freeze number of times, and travel time between network packages PING service delay.

[0100] Specifically, the first data processing submodule 221 is used to calculate the access success rate, the disconnection rate and the switching success rate according to the following formulas: Access success rate = number of successful wireless control RRC connection establishment times / number of RRC connection establishment requests; Disconnection rate = (number of abnormal wireless link releases + number of wireless link reconstructions) / (number of abnormal wireless link releases + number of positive wireless link releases + number of wireless link reconstructions); Switching success rate = number of successful switching times / number of switching requests. The second data processing submodule 222 is used to obtain the average value of each performance indicator corresponding to the target APP under the target cell from the original network performance data based on OTT data, and perform weighted summation on the average value of each performance indicator corresponding to the target APP according to the APP list of the target cell and the following formula:

[0101]

[0102]

[0103]

[0104]

[0105]

[0106]

[0107]

[0108] Among them, A1, A2...An are the number of times the corresponding target APP in the APP list of the target cell appears in the sampling period, RSRP1, RSRP2,..., RSRPn are the average values ​​of the reference signal received power of the corresponding target APP in the APP list of the target cell in the sampling period, SINR1, SINR2,..., SINRn are the average values ​​of the reference signal signal-to-interference ratio of the corresponding target APP in the APP list of the target cell in the sampling period, DL_THROUGHPUT1, DL_THROUGHPUT2,..., DL_THROUGHPUTn are the average values ​​of the downlink rate of the corresponding target APP in the APP list of the target cell in the sampling period, UL_THROUGHPUT1, UL_THROUGHPUT2, UL_THROUGHPUTn are the average values ​​of the downlink rate of the corresponding target APP in the APP list of the target cell in the sampling period, UT2, …, UL_THROUGHPUTn are respectively the average uplink rates of the corresponding target APPs in the APP list of the target cell during the sampling period, HTTP_DELAY1, HTTP_DELAY2, …, HTTP_DELAYn are respectively the average browsing service delays of the corresponding target APPs in the APP list of the target cell during the sampling period, VIDEO_CATON1, VIDEO_CATON2, …, VIDEO_CATONn are respectively the average number of video service freezes of the corresponding target APPs in the APP list of the target cell during the sampling period, PING1, PING2, …, PINGn are respectively the average PING service delays of the corresponding target APPs in the APP list of the target cell during the sampling period.

[0109] Optionally, the first data processing submodule 221 is further used to parse the service quality classification identifier QCI in the network performance original data based on the trace data; filter out the network performance original data based on the trace data corresponding to the target QCI, and use it to calculate the access success rate, drop rate and switching success rate.

[0110] Specifically, the evaluation and analysis module 23 is used to fuse the network performance indicators based on the trace data and the OTT data based on the target cell identifier and the start and end time, and obtain a multi-dimensional network performance indicator system based on the fused data.

[0111] Optionally, the evaluation and analysis module 23 is further used to obtain the geographical location, site information, and antenna performance in the target cell engineering parameter table based on the target cell identifier after obtaining the multidimensional network performance indicator system based on the fused data; associate the geographical location, site information, and antenna performance of the target cell with the multidimensional network performance indicator system based on the fused data, and visualize the association results in a geographic information system; and further used to screen out the multidimensional network performance indicator system corresponding to the target user from the multidimensional network performance indicator system based on the fused data according to the International Mobile Subscriber Identity IMSI / International Mobile Equipment Identity IMEI, for evaluating the mobile network performance perceived by the target user in the target cell. It can be understood that the above-mentioned mobile network performance evaluation device is used to execute the method corresponding to the embodiment 1 provided above, so the beneficial effects that can be achieved can refer to the method of the embodiment 1 above and the beneficial effects of the corresponding scheme in the specific implementation method below, which will not be repeated here.

[0112] Embodiment 3:

[0113] This embodiment further provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to implement the method for evaluating mobile network performance in the above embodiment.

[0114] Embodiment 4:

[0115] This embodiment further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the method for evaluating the performance of a mobile network in the above embodiment is implemented.

[0116] It is to be understood that the above embodiments are merely exemplary embodiments used to illustrate the principles of the present invention, but the present invention is not limited thereto. For those of ordinary skill in the art, various modifications and improvements can be made without departing from the spirit and essence of the present invention, and these modifications and improvements are also considered to be within the scope of protection of the present invention.

Claims

1. A method for evaluating mobile network performance, characterized in that: include: Obtain the original network performance data based on wireless call record trace data and application layer service OTT data in the target cell within the sampling period; Perform corresponding data processing on the original network performance data based on trace data and OTT data respectively to obtain network performance indicators based on trace data and OTT data; The network performance indicators based on trace data and OTT data are integrated to obtain a multi-dimensional network performance indicator system based on integrated data, which is used to evaluate the mobile network performance of the target cell.

2. The method for evaluating mobile network performance according to claim 1, characterized in that: The network performance raw data based on trace data and OTT data are processed accordingly to obtain network performance indicators based on trace data and OTT data, specifically including: Calculate the access success rate, the disconnection rate and the switching success rate for the original network performance data based on the trace data to obtain the network performance index based on the trace data, wherein the network performance index based on the trace data includes one or more combinations of the following: target cell identifier, start and end time, access success rate, disconnection rate and switching success rate; The average value of each performance indicator corresponding to the target APP in the target cell is obtained from the original network performance data based on OTT data, and the average value of each performance indicator corresponding to the target APP is weighted and summed to obtain the network performance indicator based on OTT data, wherein the network performance indicator based on OTT data includes one or more of the following combinations: target cell identifier, start and end time, reference signal receiving power, reference signal signal-to-interference ratio, downlink rate, uplink rate, browsing service delay, video service freeze number, and travel time between network packages and PING service delay.

3. The method for evaluating mobile network performance according to claim 2, characterized in that: The calculation of the access success rate, the disconnection rate and the switching success rate based on the original network performance data of the trace data specifically includes: The access success rate, disconnection rate, and switching success rate are calculated using the following formulas: Access success rate = number of successful RRC connection establishment by wireless control / number of RRC connection establishment requests; Drop rate = (number of abnormal releases of the wireless link + number of wireless link reestablishments) / (number of abnormal releases of the wireless link + number of normal releases of the wireless link + number of wireless link reestablishments); Switching success rate = number of successful switching / number of switching requests.

4. The method for evaluating mobile network performance according to claim 2, characterized in that: The method of obtaining the average value of each performance indicator corresponding to the target APP in the target cell from the original network performance data based on the OTT data, and performing weighted summation on the average value of each performance indicator corresponding to the target APP to obtain the network performance indicator based on the OTT data, specifically includes: Obtain the average value of each performance indicator corresponding to the target APP in the target cell from the original network performance data based on OTT data. According to the APP list of the target cell and the following formula, the average values ​​of the performance indicators corresponding to the target APP are weighted and summed: Among them, A1, A2...An are the number of times the corresponding target APP in the APP list of the target cell appears in the sampling period, RSRP1, RSRP2,..., RSRPn are the average values ​​of the reference signal received power of the corresponding target APP in the APP list of the target cell in the sampling period, SINR1, SINR2,..., SINRn are the average values ​​of the reference signal signal-to-interference ratio of the corresponding target APP in the APP list of the target cell in the sampling period, DL_THROUGHPUT1, DL_THROUGHPUT2,..., DL_THROUGHPUTn are the average values ​​of the downlink rate of the corresponding target APP in the APP list of the target cell in the sampling period, UL_THROUGHPUT1, UL_THROUGHPUT2, UL_THROUGHPUTn are the average values ​​of the downlink rate of the corresponding target APP in the APP list of the target cell in the sampling period, UT2, …, UL_THROUGHPUTn are respectively the average uplink rates of the corresponding target APPs in the APP list of the target cell during the sampling period, HTTP_DELAY1, HTTP_DELAY2, …, HTTP_DELAYn are respectively the average browsing service delays of the corresponding target APPs in the APP list of the target cell during the sampling period, VIDEO_CATON1, VIDEO_CATON2, …, VIDEO_CATONn are respectively the average number of video service freezes of the corresponding target APPs in the APP list of the target cell during the sampling period, PING1, PING2, …, PINGn are respectively the average PING service delays of the corresponding target APPs in the APP list of the target cell during the sampling period.

5. The method for evaluating mobile network performance according to claim 2, characterized in that: Before calculating the access success rate, the disconnection rate, and the switching success rate based on the original network performance data based on the trace data, the method further includes: Parse the service quality classification identifier (QCI) in the original network performance data based on trace data; Filter out the original network performance data based on trace data corresponding to the target QCI to calculate the access success rate, drop rate and switching success rate.

6. The method for evaluating mobile network performance according to claim 2, characterized in that: The network performance indicators based on trace data and OTT data are integrated to obtain a multi-dimensional network performance indicator system based on integrated data, specifically including: Based on the target cell identifier and the start and end time, the network performance indicators based on trace data and OTT data are integrated to obtain a multi-dimensional network performance indicator system based on the integrated data.

7. The method for evaluating mobile network performance according to claim 2, characterized in that: After obtaining the multi-dimensional network performance indicator system based on fusion data, the method further includes: Based on the target cell identifier, the geographical location, site information, and antenna performance in the target cell engineering parameter table are obtained; the geographical location, site information, and antenna performance of the target cell are associated with a multi-dimensional network performance indicator system based on fusion data, and the associated results are visualized in a geographic information system; According to the International Mobile Subscriber Identity IMSI / International Mobile Equipment Identity IMEI, a multi-dimensional network performance indicator system corresponding to the target user is screened out from the multi-dimensional network performance indicator system based on fusion data, which is used to evaluate the mobile network performance perceived by the target user in the target cell.

8. A mobile network performance evaluation device, characterized in that: include: The acquisition module is used to obtain the original network performance data based on wireless call record data trace and application service data OTT. The data processing module is connected to the acquisition module and is used to process the original network performance data of trace and OTT to obtain the network performance indicators of trace and OTT. The evaluation and analysis module is connected to the data processing module and is used to integrate the network performance indicators of trace and OTT to obtain a multi-dimensional network performance indicator system based on the integrated data for evaluating the performance of the mobile network.

9. An electronic device, characterized in that: It comprises a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to implement a method for evaluating mobile network performance as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, a method for evaluating mobile network performance as described in any one of claims 1 to 7 is implemented.

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