Network status determination method, apparatus, device, and medium

Abstract

A network state determination method, device, equipment and medium are disclosed, the method comprising: obtaining user complaint data, the user complaint data at least including a complaint location name and a first longitude and latitude, and determining a complaint area corresponding to the user complaint data; obtaining network data of each cell in the complaint area, the network data at least including MDT data and engineering parameter data, the MDT data at least including a cell name, an evolved Node B, a base station cell number, a second longitude and latitude, and an RSRP value, and the engineering parameter data at least including a cell name, a third longitude and latitude, a signal frequency, and a scene; determining network state parameters according to the network data, the network state parameters at least including a cell name, an evolved Node B, a base station cell number, a sampling point ratio, an average RSRP value, an average distance, a minimum distance, a signal frequency, and / or a scene; and determining a network state in the complaint area according to the network state parameters of each cell. The application improves the network state determination accuracy.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and in particular to a method, apparatus, device, and medium for determining network status. Background Technology

[0002] With the development of mobile network technology, network optimization has shifted from performance improvement to user experience enhancement, with resolving user complaints being a crucial approach. However, in current network optimization practices, to identify the causes of user complaints, optimization personnel often need to conduct on-site testing and signaling indicator analysis in complex wireless environments to determine the network status in question. This process is costly in terms of manpower and resources, has lengthy complaint processing cycles, and suffers from low accuracy. Summary of the Invention

[0003] The main objective of this invention is to provide a method, apparatus, device, and medium for determining network status, aiming to solve the problem of how to improve the accuracy of network status determination.

[0004] To achieve the above objectives, the present invention provides a network state determination method, which includes the following steps:

[0005] Acquire user complaint data, which includes at least the complaint location name and a first latitude and longitude, and determine the complaint area corresponding to the user complaint data;

[0006] Obtain network data for each cell in the complaint area. The network data includes at least Minimum Drive Test (MDT) data and engineering parameter data. The MDT data includes at least the cell name, evolved Node B, base station cell number, second latitude and longitude, and Reference Received Power (RSRP) value. The engineering parameter data includes at least the cell name, third latitude and longitude, signal frequency, and scenario.

[0007] Network status parameters are determined based on the network data. The network status parameters include at least cell name, evolved Node B, base station cell number, sampling point ratio, average RSRP value, average spacing, minimum spacing, signal frequency and / or scenario.

[0008] The network status within the complaint area is determined based on the network status parameters of each community.

[0009] In one embodiment, the step of determining the complaint area corresponding to the user complaint data includes:

[0010] Based on the preset grid area and the first latitude and longitude, determine the midpoint latitude and longitude of each side of the complaint area;

[0011] The complaint area is determined based on the latitude and longitude of the midpoint of each side.

[0012] In one embodiment, the step of determining network state parameters based on the network data includes:

[0013] Determine the target number of sampling points for the MDT data in each cell, and the total number of sampling points for the MDT data;

[0014] The sampling point ratio of each cell is determined based on the ratio of the target sampling point number to the total sampling point number, and the network status parameters include the sampling point ratio.

[0015] In one embodiment, the step of determining network state parameters based on the network data includes:

[0016] The target spacing of each cell is determined based on the first latitude and longitude and the third latitude and longitude, wherein the target spacing is the distance between the complaint location and the base station;

[0017] The average and / or minimum spacing of all cells within the complaint area are determined based on the target spacing, and the network status parameters include the average spacing and / or the minimum spacing.

[0018] In one embodiment, the step of determining the network status within the complaint area based on the network status parameters of each cell includes:

[0019] If there are cells in the complaint area with an average RSRP value less than a preset first power value and a sampling point ratio greater than a preset first ratio, then it is determined that the network in the complaint area has weak coverage, and the network status includes weak coverage.

[0020] In one embodiment, after determining that the network status of the complaint area has weak coverage, the method further includes:

[0021] If the average spacing is greater than the preset first spacing, then the analysis result of the weak coverage is determined to be that there are coverage holes.

[0022] If the minimum spacing is greater than the preset second spacing, then the analysis result of the weak coverage is determined to be rural remote access;

[0023] If a pre-defined building exists within the complaint area, the analysis result of the weak coverage is determined to be obstruction by a tall building;

[0024] If a preset scenario exists within the complaint area, the analysis result of the weak coverage is determined to indicate the existence of a fast scenario.

[0025] In one embodiment, the step of determining the network status within the complaint area based on the network status parameters of each cell includes:

[0026] Based on the signal frequency, the evolved Node B, and the base station cell number, determine whether there are cells with the same frequency and coverage in the complaint area;

[0027] If the same frequency and coverage cell exists in the complaint area, and the sampling point ratio of the same frequency and coverage cell is greater than the preset second ratio, then the difference in the average RSRP value of each cell is determined.

[0028] If the scenario of the complaint area is a city, and the difference is less than a preset second power value, then it is determined that the network in the complaint area has overlapping coverage, and the network status includes overlapping coverage.

[0029] In one embodiment, the network status further includes the target distance between the complaint location and the base station, and the step of determining the network status within the complaint area based on the network status parameters of each cell includes:

[0030] If the scenario corresponding to the complaint area is a city, and there are cells in the complaint area with a target spacing exceeding a preset distance, and the proportion of sampling points corresponding to cells with a target spacing exceeding a preset distance is greater than a preset first proportion, then it is determined that the network in the complaint area has over-coverage, and the network status includes over-coverage.

[0031] In one embodiment, the step of determining the network status within the complaint area based on the network status parameters of each cell includes:

[0032] If there are cells in the complaint area with a sampling point ratio less than a preset first ratio, then it is determined that the network in the complaint area needs to be rectified or optimized by radio frequency. The network status includes needing rectification or optimization by radio frequency.

[0033] In one embodiment, the network data further includes performance indicator data, which includes at least fault alarm data, load data, and / or interference data; the step of determining network status parameters based on the network data further includes:

[0034] The network status parameters of the cell are determined based on the performance index data. The network status parameters also include the cell's fault warning, interference value, and load value.

[0035] The step of determining the network status within the complaint area based on the network status parameters of each cell includes:

[0036] If there are cells with fault alarms in the complaint area, and the proportion of sampling points of cells with fault alarms is greater than the preset first proportion, then it is determined that there is a network equipment fault in the complaint area.

[0037] And / or, if there are cells in the complaint area with interference values ​​greater than a preset first threshold, and the proportion of sampling points of cells with interference values ​​greater than the preset first threshold is greater than a preset first proportion, then it is determined that the network in the complaint area has high interference.

[0038] And / or, if there are cells in the complaint area with a load greater than a preset second threshold, and the proportion of sampling points of cells with a load greater than the preset second threshold is greater than a preset first proportion, then it is determined that the network in the complaint area has a high load, and the network status includes equipment failure, high interference and / or high load.

[0039] To achieve the above objectives, the present invention also provides a network state determination device, the network state determination device comprising:

[0040] The acquisition module is used to acquire user complaint data, which includes at least the complaint location name and a first latitude and longitude, and to determine the complaint area corresponding to the user complaint data.

[0041] The matching module is used to obtain network data of each cell in the complaint area. The network data includes at least Minimum Drive Test (MDT) data and engineering parameter data. The MDT data includes at least cell name, evolved Node B, base station cell number, second latitude and longitude, and Reference Signal Received Power (RSRP) value. The engineering parameter data includes at least cell name, third latitude and longitude, signal frequency, and scenario.

[0042] The calculation module is used to determine network status parameters based on the network data. The network status parameters include at least cell name, evolved Node B, base station cell number, sampling point ratio, average RSRP value, average spacing, minimum spacing, signal frequency and / or scenario.

[0043] The determination module is used to determine the network status within the complaint area based on the network status parameters of each cell.

[0044] To achieve the above objectives, the present invention also provides a network state determination device, the network state determination device including a memory, a processor, and a network state determination program stored in the memory and executable on the processor, wherein when the network state determination program is executed by the processor, it implements the various steps of the network state determination method as described above.

[0045] To achieve the above objectives, the present invention also provides a computer-readable storage medium storing a network state determination program, which, when executed by a processor, implements the various steps of the network state determination method as described above.

[0046] This invention provides a method, apparatus, device, and medium for determining network status. The method involves acquiring user complaint data, which includes at least the complaint location name and a first latitude and longitude coordinate, and determining the corresponding complaint area. It then acquires network data for each cell within the complaint area, including at least minimized drive test (MDT) data and engineering parameter data. Based on the network data, it determines network status parameters, including at least the cell name, evolved Node B, base station cell number, sampling point ratio, average RSRP value, average spacing, minimum spacing, signal frequency, and / or scenario. Finally, it determines the network status within the complaint area based on the network status parameters of each cell. By determining the network status parameters of cells using network data and then determining the network status of the complaint area based on these parameters, the accuracy and efficiency of determining the network status within the complaint area are improved. Attached Figure Description

[0047] Figure 1 This is a schematic diagram of the hardware structure of the network status determination device according to an embodiment of the present invention;

[0048] Figure 2 This is a flowchart illustrating the first embodiment of the network state determination method of the present invention;

[0049] Figure 3 This is a schematic diagram of the complaint area in the network status determination method of the present invention;

[0050] Figure 4 This is a schematic diagram of the complaint area in the network status determination method of the present invention;

[0051] Figure 5 This is a detailed flowchart of step S30 of the second embodiment of the network state determination method of the present invention;

[0052] Figure 6 This is a schematic diagram of the logic structure of the network state determination device of the present invention.

[0053] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0054] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0055] The main solution of this invention is as follows: First, acquire user complaint data, which includes at least the complaint location name and a first latitude and longitude, and determine the complaint area corresponding to the user complaint data. Second, acquire network data for each cell in the complaint area, which includes at least minimized drive test (MDT) data and engineering parameter data. Third, determine network status parameters based on the network data, which include at least the cell name, evolved Node B, base station cell number, sampling point ratio, average RSRP value, average spacing, minimum spacing, signal frequency, and / or scenario. Fourth, determine the network status within the complaint area based on the network status parameters of each cell.

[0056] By determining the network status parameters of a cell using network data, and then using these parameters to determine the network status of the complaint area, the accuracy and efficiency of determining the network status within the complaint area are improved.

[0057] As one implementation scheme, network state determination devices can, for example, Figure 1 As shown.

[0058] The embodiments of the present invention relate to a network status determination device, which includes: a processor 101, such as a CPU, a memory 102, and a communication bus 103. The communication bus 103 is used to implement communication between these components.

[0059] Memory 102 can be high-speed RAM or stable memory (non-volatile memory), such as disk storage. Figure 1 As shown, the memory 102, which is a computer-readable storage medium, may include a network status determination program; and the processor 101 may be used to call the network status determination program stored in the memory 102 and perform the following operations:

[0060] Acquire user complaint data, which includes at least the complaint location name and a first latitude and longitude, and determine the complaint area corresponding to the user complaint data;

[0061] Obtain network data for each cell in the complaint area. The network data includes at least Minimum Drive Test (MDT) data and engineering parameter data. The MDT data includes at least the cell name, evolved Node B, base station cell number, second latitude and longitude, and Reference Received Power (RSRP) value. The engineering parameter data includes at least the cell name, third latitude and longitude, signal frequency, and scenario.

[0062] Network status parameters are determined based on the network data. The network status parameters include at least cell name, evolved Node B, base station cell number, sampling point ratio, average RSRP value, average spacing, minimum spacing, signal frequency and / or scenario.

[0063] The network status within the complaint area is determined based on the network status parameters of each community.

[0064] In one embodiment, the processor 101 can be used to invoke a network state determination program stored in the memory 102 and perform the following operations:

[0065] Based on the preset grid area and the first latitude and longitude, determine the midpoint latitude and longitude of each side of the complaint area;

[0066] The complaint area is determined based on the latitude and longitude of the midpoint of each side.

[0067] In one embodiment, the processor 101 can be used to invoke a network state determination program stored in the memory 102 and perform the following operations:

[0068] Determine the target number of sampling points for the MDT data in each cell, and the total number of sampling points for the MDT data;

[0069] The sampling point ratio of each cell is determined based on the ratio of the target sampling point number to the total sampling point number, and the network status parameters include the sampling point ratio.

[0070] In one embodiment, the processor 101 can be used to invoke a network state determination program stored in the memory 102 and perform the following operations:

[0071] The target spacing of each cell is determined based on the first latitude and longitude and the third latitude and longitude, wherein the target spacing is the distance between the complaint location and the base station;

[0072] The average and / or minimum spacing of all cells within the complaint area are determined based on the target spacing, and the network status parameters include the average spacing and / or the minimum spacing.

[0073] In one embodiment, the processor 101 can be used to invoke a network state determination program stored in the memory 102 and perform the following operations:

[0074] If there are cells in the complaint area with an average RSRP value less than a preset first power value and a sampling point ratio greater than a preset first ratio, then it is determined that the network in the complaint area has weak coverage, and the network status includes weak coverage.

[0075] In one embodiment, the processor 101 can be used to invoke a network state determination program stored in the memory 102 and perform the following operations:

[0076] If the average spacing is greater than the preset first spacing, then the analysis result of the weak coverage is determined to be that there are coverage holes.

[0077] If the minimum spacing is greater than the preset second spacing, then the analysis result of the weak coverage is determined to be rural remote access;

[0078] If a pre-defined building exists within the complaint area, the analysis result of the weak coverage is determined to be obstruction by a tall building;

[0079] If a preset scenario exists within the complaint area, the analysis result of the weak coverage is determined to indicate the existence of a fast scenario.

[0080] In one embodiment, the processor 101 can be used to invoke a network state determination program stored in the memory 102 and perform the following operations:

[0081] Based on the signal frequency, the evolved Node B, and the base station cell number, determine whether there are cells with the same frequency and coverage in the complaint area;

[0082] If the same frequency and coverage cell exists in the complaint area, and the sampling point ratio of the same frequency and coverage cell is greater than the preset second ratio, then the difference in the average RSRP value of each cell is determined.

[0083] If the scenario of the complaint area is a city, and the difference is less than a preset second power value, then it is determined that the network in the complaint area has overlapping coverage, and the network status includes overlapping coverage.

[0084] In one embodiment, the processor 101 can be used to invoke a network state determination program stored in the memory 102 and perform the following operations:

[0085] If the scenario corresponding to the complaint area is a city, and there are cells in the complaint area with a target spacing exceeding a preset distance, and the proportion of sampling points corresponding to cells with a target spacing exceeding a preset distance is greater than a preset first proportion, then it is determined that the network in the complaint area has over-coverage, and the network status includes over-coverage.

[0086] In one embodiment, the processor 101 can be used to invoke a network state determination program stored in the memory 102 and perform the following operations:

[0087] If there are cells in the complaint area with a sampling point ratio less than a preset first ratio, then it is determined that the network in the complaint area needs to be rectified or optimized by radio frequency. The network status includes needing rectification or optimization by radio frequency.

[0088] In one embodiment, the processor 101 can be used to invoke a network state determination program stored in the memory 102 and perform the following operations:

[0089] The network status parameters of the cell are determined based on the performance index data. The network status parameters also include the cell's fault warning, interference value, and load value.

[0090] If there are cells with fault alarms in the complaint area, and the proportion of sampling points of cells with fault alarms is greater than the preset first proportion, then it is determined that there is a network equipment fault in the complaint area.

[0091] And / or, if there are cells in the complaint area with interference values ​​greater than a preset first threshold, and the proportion of sampling points of cells with interference values ​​greater than the preset first threshold is greater than a preset first proportion, then it is determined that the network in the complaint area has high interference.

[0092] And / or, if there are cells in the complaint area with a load greater than a preset second threshold, and the proportion of sampling points of cells with a load greater than the preset second threshold is greater than a preset first proportion, then it is determined that the network in the complaint area has a high load, and the network status includes equipment failure, high interference and / or high load.

[0093] Based on the hardware architecture of the network state determination device described above, an embodiment of the network state determination method of the present invention is proposed.

[0094] Reference Figure 2 , Figure 2 This is a first embodiment of the network state determination method of the present invention, the network state determination method includes the following steps:

[0095] Step S10: Obtain user complaint data, which includes at least the complaint location name and a first latitude and longitude, and determine the complaint area corresponding to the user complaint data.

[0096] Specifically, user complaint data is obtained. This data includes at least the location name of the complaint, the first latitude and longitude, and the scene. The scene can be urban or rural, and cities can be further divided into county-level cities and city-level cities, as shown in the table below:

[0097] Complaint location longitude latitude Scene Complaint Location Name 125.336082 43.90718 City

[0098] To determine the complaint area corresponding to user complaint data, a preset range within the location of the complaint data can be used. Optionally, the preset range can be a circular area centered on the first latitude and longitude of the complaint location with a preset radius. Alternatively, the preset range can be a square area centered on the first latitude and longitude of the complaint location with a preset grid size, such as... Figure 3 As shown.

[0099] Step S20: Obtain the network data of each cell in the complaint area. The network data includes at least Minimization of Drivetests (MDT) data and engineering parameter data. The MDT data includes at least cell name, Evolved Node B, base station cell number, second longitude and latitude, and Reference Signal Receiving Power (RSRP) value. The engineering parameter data includes at least cell name, third longitude and latitude, signal frequency, and scenario.

[0100] Specifically, the network data of each cell in the complaint area may include MDT (Minimization of drivetests) data and engineering parameter data. Optionally, the network data may include MDT data, engineering parameter data, and performance metric data.

[0101] The MDT data includes cell name, ENB (Evolved Node B), CI (Cell Identity), second longitude and latitude, RSRP (Reference Signal Receiving Power) value, RSRQ (Reference Signal Receiving Quality) value, etc. Obtain the MDT data of each cell in the complaint area, and compare the second longitude and latitude in the MDT data with the longitude and latitude of the midpoints of the four sides of the complaint area to obtain the MDT data within the complaint area. Exemplarily, as Figure 4 shown, the complaint location is O(x, y). When the longitude and latitude of the midpoint of the upper side of the complaint area is A(x1, y1), the longitude and latitude of the midpoint of the lower side of the complaint area is B(x2, y2), the longitude and latitude of the midpoint of the left side of the complaint area is C(x3, y3), and the longitude and latitude of the midpoint of the right side of the complaint area is D(x4, y4), obtain the MDT data of each cell in the complaint area, that is, obtain the MDT data of the second longitude and latitude (j, w) where x3 < j < x4 and y2 < w < y1.

[0102] Optionally, when the network data includes MDT data and engineering parameter data, obtain the network data of each cell in the complaint area, and obtain the MDT data within the complaint area. The MDT data includes Evolved Node B, base station cell number, second longitude and latitude, RSRP value, RSRQ value, etc. Exemplarily, the user complaint data and MDT data are shown in the following table:

[0103]

[0104]

[0105] The MDT data table is obtained by deduplicating the complaint location name and cell name fields. The table includes the complaint location name, cell name, ENB, CI, sampling point ratio, and average RSRP value of the cell. The MDT data table can be matched with the engineering parameter data table using the cell name field to update the MDT data table content, adding fields such as third latitude and longitude, azimuth, frequency, station type, region, and scenario.

[0106] The technical parameter data, or NRM data, includes cell name, third latitude and longitude, evolved NodeB, base station cell number, azimuth, signal frequency, region and / or scenario, etc. For example, the technical parameter data is shown in the table below:

[0107]

[0108]

[0109] Optionally, when network data can include MDT data, engineering parameter data, and performance indicator data, performance indicator data, i.e., PM data, can also be matched with MDT data and engineering parameter data using the cell name field. Performance indicator data includes data such as important alarms, high load, and high interference. For example, the performance indicator data is shown in the table below:

[0110]

[0111]

[0112] Step S30: Determine network status parameters based on the network data. The network status parameters include at least the cell name, evolved Node B, base station cell number, sampling point ratio, average RSRP value, average spacing, minimum spacing, signal frequency, and / or scenario.

[0113] Specifically, network status parameters include cell name, evolved Node B, base station cell number (CI), sampling point ratio, average RSRP value, average spacing, minimum spacing, target spacing, signal frequency, and scenario. The average spacing is the average of the target spacing of each cell, the minimum spacing is the minimum of the target spacing of each cell, and the target spacing is the distance between the first latitude and longitude of the user complaint data and the third latitude and longitude of the MDT data in the cell.

[0114] Optionally, the average RSRP value in the network state parameters is shown in the following formula:

[0115]

[0116] Where RSRP′ is the average RSRP value of each cell in the complaint area, R iLet i = 1, ..., n be the RSRP values ​​of each cell in the network data, and n be the total number of RSRP values ​​within the complaint area. An example is shown in the table below:

[0117]

[0118] Optionally, obtain MDT data for each cell in the complaint area. The MDT data includes the sampling point ratio. Based on the sampling points at the second latitude and longitude of each MDT data point, the target sampling point number and the total sampling point number of the MDT data in each cell can be determined. Based on the ratio of the target sampling point number 'a' to the total sampling point number 'b', the sampling point ratio 'c' of each cell is determined, as shown in the following formula:

[0119]

[0120] For example, as shown in the table below:

[0121]

[0122] Optionally, obtain MDT data for each cell in the complaint area. The MDT data includes the average spacing and / or minimum spacing. Determine the target spacing for each cell based on the first latitude and longitude and the third latitude and longitude. The target spacing is the distance between the complaint location and the base station, as shown in the following formula:

[0123]

[0124] The average and / or minimum spacing of all communities within the complaint area is determined based on the target spacing, as shown in the following formula:

[0125]

[0126] in, d represents the average spacing between all residential areas within the complaint area. i ,i=1,......,n are the target spacing, and n is the number of cells;

[0127] d m =min(d i )=min(d1,d2,......,d n );

[0128] Where, d m d represents the minimum spacing among all residential areas within the complaint area. i ,i=1,......,n is the target spacing, and n is the number of cells.

[0129] Step S40: Determine the network status within the complaint area based on the network status parameters of each cell.

[0130] Specifically, the network status within the complaint area is determined based on the network status parameters of each cell. The network status includes normal status, overlapping coverage, weak coverage, fault alarm, high interference, high load, over-coverage, pending rectification, and / or pending radio frequency optimization.

[0131] Optionally, if there are cells within the complaint area with an average RSRP value lower than a preset first power value and a sampling point ratio greater than a preset first ratio, then the network in the complaint area is determined to have weak coverage. For example, the preset first power value is -105dBm, and the preset first ratio is 10%. Optionally, after determining that the network in the complaint area has weak coverage, the analysis results for the reasons for the weak coverage in the complaint area can include coverage holes, rural remote access, building obstruction, and high-speed scenarios. Specifically, when the average spacing is greater than a preset first spacing, the analysis result for weak coverage is the presence of coverage holes; for example, the first spacing is 300 meters. When the minimum spacing is greater than a preset second spacing, the analysis result for weak coverage is the presence of rural remote access; for example, the preset second spacing is 2000 meters. When there are preset buildings within the complaint area, where the preset buildings can be high-rise buildings such as residential buildings, schools, or shopping malls, the analysis result for weak coverage is the presence of high-rise building obstruction. When there are preset scenarios within the complaint area, where the preset scenarios can be scenarios such as high-speed rail, the analysis result for weak coverage is the presence of high-speed scenarios.

[0132] Optionally, the network status within the complaint area is determined based on the network status parameters of each cell, and the presence of co-frequency and co-covered cells in the complaint area is determined based on the signal frequency, evolved Node B, and base station cell number. If co-frequency and co-covered cells exist in the complaint area, and the proportion of sampling points of co-frequency and co-covered cells is greater than a preset second proportion, the difference in the average RSRP values ​​of each cell is determined. For example, the preset second proportion is 30%. If the scenario of the complaint area is urban, and the difference is less than a preset second power value, it is determined that the network in the complaint area has overlapping coverage. For example, the preset second power value is 6dB.

[0133] Optionally, the network data also includes performance indicator data, which includes at least fault alarm data, load data, and / or interference data; step S30 includes: determining the network status parameters of the cell based on the performance indicator data, which also includes the cell's fault warning, interference value, and load value; step S40 includes: if there are cells with fault alarms in the complaint area, and the proportion of sampling points of cells with fault alarms is greater than a preset first proportion, then it is determined that there is a device fault in the network of the complaint area; and / or, if there are cells with interference values ​​greater than a preset first threshold in the complaint area, and the proportion of sampling points of cells with interference values ​​greater than the preset first threshold is greater than a preset first proportion, then it is determined that there is high interference in the network of the complaint area; and / or, if there are cells with loads greater than a preset second threshold in the complaint area, and the proportion of sampling points of cells with loads greater than the preset second threshold is greater than a preset first proportion, then it is determined that there is high load in the network of the complaint area, where the network status includes device fault, high interference, and / or high load, and optionally, the preset first proportion is 10%.

[0134] Optionally, if the scenario corresponding to the complaint area is a city, and there are communities in the complaint area with target spacing exceeding a preset distance, and the proportion of sampling points corresponding to communities with target spacing exceeding a preset distance is greater than a preset first proportion, then it is determined that the network in the complaint area has over-coverage, and the network status includes over-coverage. For example, the preset first proportion is 10%.

[0135] Optionally, if there are cells in the complaint area with a sampling point ratio less than a preset first ratio, then it is determined that the network in the complaint area needs to be rectified or optimized by radio frequency. The network status includes needing rectification or optimization by radio frequency.

[0136] Based on the network status parameters of each community, the network status within the complaint area can be determined. An optimization plan can then be determined based on the network status, as shown in the table below:

[0137]

[0138] In this embodiment, the technical solution involves acquiring user complaint data, which includes at least the complaint location name and a first latitude and longitude, to determine the complaint area corresponding to the user complaint data; acquiring network data for each cell within the complaint area, which includes at least minimized drive test (MDT) data and engineering parameter data; determining network status parameters based on the network data, which include at least the cell name, evolved Node B, base station cell number, sampling point ratio, average RSRP value, average spacing, minimum spacing, signal frequency, and / or scenario; and determining the network status within the complaint area based on the network status parameters of each cell. By determining the network status parameters of cells using network data and then determining the network status of the complaint area based on these parameters, the accuracy and efficiency of determining the network status within the complaint area are improved.

[0139] Reference Figure 5 , Figure 5 This is a second embodiment of the network state determination method of the present invention. Based on the first embodiment, step S20 includes:

[0140] Step S21: Determine the midpoint latitude and longitude of each side of the complaint area based on the preset grid area and the first latitude and longitude.

[0141] Step S22: Determine the complaint area based on the latitude and longitude of the midpoint of each side.

[0142] Specifically, based on the preset grid area and the first latitude and longitude coordinates, the midpoint latitude and longitude coordinates of each side of the complaint area are determined. Optionally, the side length of the preset grid area is l, and the first latitude and longitude coordinates are (x, y). The latitude and longitude coordinates of the midpoints of the four sides within the complaint area are determined using the preset grid area and the first latitude and longitude coordinates, such as... Figure 4 As shown, the latitude and longitude of the midpoint of the upper edge of the complaint area is A(x1,y1), as shown in the following formula:

[0143] x1 = x;

[0144]

[0145] The latitude and longitude of the midpoint at the bottom edge of the complaint area is B(x2,y2), as shown in the following formula:

[0146] x² = x;

[0147]

[0148] The latitude and longitude of the midpoint on the left side of the complaint area is C(x3,y3), as shown in the following formula:

[0149]

[0150] y3 = y;

[0151] The latitude and longitude of the midpoint on the right side of the complaint area is D(x4,y4), as shown in the formula below.

[0152]

[0153] y4 = y;

[0154] Where 2πr represents the Earth's circumference, d(x, y) is the first latitude and longitude in the user complaint data, and l is the side length of the preset grid area. For example, given the user complaint location latitude and longitude (125.336082, 43.90718) and the grid size of the complaint area l = 400m, calculate the latitude and longitude of the midpoints of the four sides of the complaint area: the midpoint of the top side is A (125.336082, 45.710698), the midpoint of the bottom side is B (125.336082, 42.103661), the midpoint of the left side is C (123.719182, 43.90718), and the midpoint of the right side is D (126.952981, 43.90718).

[0155] After determining the latitude and longitude of the midpoint of each side of the grid area, the complaint area is determined based on the latitude and longitude of the midpoint of each side, such as... Figure 4 As shown.

[0156] In the technical solution of this embodiment, the midpoint latitude and longitude of each side of the complaint area are determined according to the preset grid area and the first latitude and longitude; the complaint area is determined according to the midpoint latitude and longitude of each side, thereby determining the complaint area corresponding to the user complaint data, which facilitates accurate acquisition of network data within the complaint area and makes the determination of the network status of the complaint area more accurate.

[0157] Reference Figure 6 The present invention also provides a network state determination device, the network state determination device comprising:

[0158] The acquisition module 100 is used to acquire user complaint data, which includes at least the complaint location name and a first latitude and longitude, and to determine the complaint area corresponding to the user complaint data.

[0159] The matching module 200 is used to acquire network data of each cell in the complaint area. The network data includes at least Minimum Drive Test (MDT) data and engineering parameter data. The MDT data includes at least cell name, evolved Node B, base station cell number, second latitude and longitude, and reference signal received power (RSRP) value. The engineering parameter data includes at least cell name, third latitude and longitude, signal frequency, and scene.

[0160] Calculation module 300 is used to determine network status parameters based on the network data. The network status parameters include at least cell name, evolved Node B, base station cell number, sampling point ratio, average RSRP value, average spacing, minimum spacing, signal frequency and / or scenario.

[0161] The determination module 400 is used to determine the network status within the complaint area based on the network status parameters of each cell.

[0162] In one embodiment, the acquisition module 100 is specifically used to: determine the complaint area corresponding to the user complaint data.

[0163] Based on the preset grid area and the first latitude and longitude, determine the midpoint latitude and longitude of each side of the complaint area;

[0164] The complaint area is determined based on the latitude and longitude of the midpoint of each side.

[0165] In one embodiment, the calculation module 300 is specifically used for determining network state parameters based on the network data as follows:

[0166] Determine the target number of sampling points for the MDT data in each cell, and the total number of sampling points for the MDT data;

[0167] The sampling point ratio of each cell is determined based on the ratio of the target sampling point number to the total sampling point number, and the network status parameters include the sampling point ratio.

[0168] In one embodiment, the calculation module 300 is specifically used for determining network state parameters based on the network data as follows:

[0169] The target spacing of each cell is determined based on the first latitude and longitude and the third latitude and longitude, wherein the target spacing is the distance between the complaint location and the base station;

[0170] The average and / or minimum spacing of all cells within the complaint area are determined based on the target spacing, and the network status parameters include the average spacing and / or the minimum spacing.

[0171] In one embodiment, in determining the network status within the complaint area based on the network status parameters of each cell, the determining module 400 is specifically configured to:

[0172] If there are cells in the complaint area with an average RSRP value less than a preset first power value and a sampling point ratio greater than a preset first ratio, then it is determined that the network in the complaint area has weak coverage, and the network status includes weak coverage.

[0173] In one embodiment, after determining that the network status of the complaint area has weak coverage, the determining module 400 is specifically used to:

[0174] If the average spacing is greater than the preset first spacing, then the analysis result of the weak coverage is determined to be that there are coverage holes.

[0175] If the minimum spacing is greater than the preset second spacing, then the analysis result of the weak coverage is determined to be rural remote access;

[0176] If a pre-defined building exists within the complaint area, the analysis result of the weak coverage is determined to be obstruction by a tall building;

[0177] If a preset scenario exists within the complaint area, the analysis result of the weak coverage is determined to indicate the existence of a fast scenario.

[0178] In one embodiment, in determining the network status within the complaint area based on the network status parameters of each cell, the determining module 400 is specifically configured to:

[0179] Based on the signal frequency, the evolved Node B, and the base station cell number, determine whether there are cells with the same frequency and coverage in the complaint area;

[0180] If the same frequency and coverage cell exists in the complaint area, and the sampling point ratio of the same frequency and coverage cell is greater than the preset second ratio, then the difference in the average RSRP value of each cell is determined.

[0181] If the scenario of the complaint area is a city, and the difference is less than a preset second power value, then it is determined that the network in the complaint area has overlapping coverage, and the network status includes overlapping coverage.

[0182] In one embodiment, in determining the network status within the complaint area based on the network status parameters of each cell, the determining module 400 is specifically configured to:

[0183] If the scenario corresponding to the complaint area is a city, and there are cells in the complaint area with a target spacing exceeding a preset distance, and the proportion of sampling points corresponding to cells with a target spacing exceeding a preset distance is greater than a preset first proportion, then it is determined that the network in the complaint area has over-coverage, and the network status includes over-coverage.

[0184] In one embodiment, in determining the network status within the complaint area based on the network status parameters of each cell, the determining module 400 is specifically configured to:

[0185] If there are cells in the complaint area with a sampling point ratio less than a preset first ratio, then it is determined that the network in the complaint area needs to be rectified or optimized by radio frequency. The network status includes needing rectification or optimization by radio frequency.

[0186] In one embodiment, the calculation module 300 is specifically used for determining network state parameters based on the network data as follows:

[0187] The network status parameters of the cell are determined based on the performance index data. The network status parameters also include the cell's fault warning, interference value, and load value.

[0188] In determining the network status within the complaint area based on the network status parameters of each cell, the determining module 400 is specifically used for:

[0189] If there are cells with fault alarms in the complaint area, and the proportion of sampling points of cells with fault alarms is greater than the preset first proportion, then it is determined that there is a network equipment fault in the complaint area.

[0190] And / or, if there are cells in the complaint area with interference values ​​greater than a preset first threshold, and the proportion of sampling points of cells with interference values ​​greater than the preset first threshold is greater than a preset first proportion, then it is determined that the network in the complaint area has high interference.

[0191] And / or, if there are cells in the complaint area with a load greater than a preset second threshold, and the proportion of sampling points of cells with a load greater than the preset second threshold is greater than a preset first proportion, then it is determined that the network in the complaint area has a high load, and the network status includes equipment failure, high interference and / or high load.

[0192] The present invention also provides a network state determination device, the network state determination device including a memory, a processor, and a network state determination program stored in the memory and executable on the processor, wherein when the network state determination program is executed by the processor, it implements the various steps of the network state determination method as described in the above embodiments.

[0193] The present invention also provides a computer-readable storage medium storing a network state determination program, which, when executed by a processor, implements the various steps of the network state determination method as described in the above embodiments.

[0194] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0195] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, system, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, system, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, system, article, or apparatus that includes that element.

[0196] Through the above description of the embodiments, those skilled in the art can clearly understand that the systems described in the embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a computer-readable storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device (which may be a mobile phone, computer, parking management device, air conditioner, or network device, etc.) to execute the systems described in the various embodiments of the present invention.

[0197] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A method for determining network state, characterized in that, The network state determination method includes: Acquire user complaint data, which includes at least the complaint location name and a first latitude and longitude, and determine the complaint area corresponding to the user complaint data; Obtain network data for each cell in the complaint area. The network data includes at least Minimum Drive Test (MDT) data and engineering parameter data. The MDT data includes at least cell name, evolved NodeB, base station cell number, second latitude and longitude, and Reference Received Power (RSRP) value. The engineering parameter data includes at least cell name, third latitude and longitude, signal frequency, and scenario. Network status parameters are determined based on the network data. The network status parameters include at least cell name, evolved NodeB, base station cell number, sampling point ratio, average RSRP value, average spacing, minimum spacing, signal frequency and / or scenario. The network status within the complaint area is determined based on the network status parameters of each community. The step of determining the network status within the complaint area based on the network status parameters of each cell includes: Based on the signal frequency, the evolved NodeB, and the base station cell number, determine whether there are cells with the same frequency and coverage in the complaint area; If there is a cell with the same frequency and coverage in the complaint area, and the proportion of sampling points of the cell with the same frequency and coverage is greater than the preset second proportion, then the difference between the average RSRP values ​​of each cell with the same frequency and coverage is determined. If the scenario of the complaint area is a city, and the difference is less than a preset second power value, then it is determined that the network in the complaint area has overlapping coverage, and the network status includes overlapping coverage.

2. The network state determination method as described in claim 1, characterized in that, The step of determining the complaint area corresponding to the user complaint data includes: Based on the preset grid area and the first latitude and longitude, determine the midpoint latitude and longitude of each side of the complaint area; The complaint area is determined based on the latitude and longitude of the midpoint of each side.

3. The network state determination method as described in claim 1, characterized in that, The step of determining network state parameters based on the network data includes: Determine the target number of sampling points for the MDT data in each cell, and the total number of sampling points for the MDT data; The sampling point ratio of each cell is determined based on the ratio of the target sampling point number to the total sampling point number, and the network status parameters include the sampling point ratio.

4. The network state determination method as described in claim 1, characterized in that, The step of determining network state parameters based on the network data includes: The target spacing of each cell is determined based on the first latitude and longitude and the third latitude and longitude, wherein the target spacing is the distance between the complaint location and the base station; The average and / or minimum spacing of all cells within the complaint area are determined based on the target spacing, and the network status parameters include the average spacing and / or the minimum spacing.

5. The network state determination method as described in claim 1, characterized in that, The step of determining the network status within the complaint area based on the network status parameters of each cell further includes: If there are cells in the complaint area with an average RSRP value less than a preset first power value and a sampling point ratio greater than a preset first ratio, then it is determined that the network in the complaint area has weak coverage, and the network status includes weak coverage.

6. The network state determination method as described in claim 5, characterized in that, After determining that the network status of the complaint area has weak coverage, the method further includes: If the average spacing is greater than the preset first spacing, then the analysis result of the weak coverage is determined to be that there are coverage holes. If the minimum spacing is greater than the preset second spacing, then the analysis result of the weak coverage is determined to be rural remote access; If a pre-defined building exists within the complaint area, the analysis result of the weak coverage is determined to be obstruction by a tall building; If a preset scenario exists within the complaint area, the analysis result of the weak coverage is determined to indicate the existence of a fast scenario.

7. The network state determination method as described in claim 1, characterized in that, The network status also includes the target distance between the complaint location and the base station, and the step of determining the network status within the complaint area based on the network status parameters of each cell further includes: If the scenario corresponding to the complaint area is a city, and there are cells in the complaint area with a target spacing exceeding a preset distance, and the proportion of sampling points corresponding to cells with a target spacing exceeding a preset distance is greater than a preset first proportion, then it is determined that the network in the complaint area has over-coverage, and the network status includes over-coverage.

8. The network state determination method as described in claim 1, characterized in that, The step of determining the network status within the complaint area based on the network status parameters of each cell further includes: If there are cells in the complaint area with a sampling point ratio less than a preset first ratio, then it is determined that the network in the complaint area needs to be rectified or optimized by radio frequency. The network status includes needing rectification or optimization by radio frequency.

9. The network state determination method as described in claim 1, characterized in that, The network data also includes performance indicator data, which at least includes fault alarm data, load data, and / or interference data; the step of determining network status parameters based on the network data further includes: The network status parameters of the cell are determined based on the performance index data. The network status parameters also include the cell's fault warning, interference value, and load value. The step of determining the network status within the complaint area based on the network status parameters of each cell further includes: If there are cells with fault alarms in the complaint area, and the proportion of sampling points of cells with fault alarms is greater than the preset first proportion, then it is determined that there is a network equipment fault in the complaint area. And / or, if there are cells in the complaint area with interference values ​​greater than a preset first threshold, and the proportion of sampling points of cells with interference values ​​greater than the preset first threshold is greater than a preset first proportion, then it is determined that the network in the complaint area has high interference. And / or, if there are cells in the complaint area with a load greater than a preset second threshold, and the proportion of sampling points of cells with a load greater than the preset second threshold is greater than a preset first proportion, then it is determined that the network in the complaint area has a high load, and the network status includes equipment failure, high interference and / or high load.

10. A network state determination device, characterized in that, The network status determination device includes: The acquisition module is used to acquire user complaint data, which includes at least the complaint location name and a first latitude and longitude, and to determine the complaint area corresponding to the user complaint data. The matching module is used to obtain network data of each cell in the complaint area. The network data includes at least Minimum Drive Test (MDT) data and engineering parameter data. The MDT data includes at least cell name, evolved NodeB, base station cell number, second latitude and longitude, and Reference Signal Received Power (RSRP) value. The engineering parameter data includes at least cell name, third latitude and longitude, signal frequency, and scenario. The calculation module is used to determine network status parameters based on the network data. The network status parameters include at least cell name, evolved NodeB, base station cell number, sampling point ratio, average RSRP value, average spacing, minimum spacing, signal frequency and / or scenario. The determination module is used to determine whether there are co-frequency and co-coverage cells in the complaint area based on the signal frequency, the evolved NodeB, and the base station cell number; if there are co-frequency and co-coverage cells in the complaint area, and the sampling point ratio of the co-frequency and co-coverage cells is greater than a preset second ratio, then the difference between the average RSRP values ​​of each co-frequency and co-coverage cell is determined; if the scenario of the complaint area is a city, and the difference is less than a preset second power value, then it is determined that the network in the complaint area has overlapping coverage, and the network status includes overlapping coverage.

11. A network state determination device, characterized in that, The network state determination device includes a memory, a processor, and a network state determination program stored in the memory and executable on the processor, wherein the network state determination program, when executed by the processor, implements the various steps of the network state determination method as described in any one of claims 1-9.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a network state determination program, which, when executed by a processor, implements the steps of the network state determination method as described in any one of claims 1-9.

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