Data detection method and apparatus, device, and computer-readable storage medium

Abstract

The application discloses a kind of data detection method, device, equipment and computer readable storage medium, the method includes: obtaining minimization drive test target data, the minimization drive test target data includes the reference signal received power RSRP data of user equipment receiving main cell radio signal corresponding main cell and maximum time advance TA value;The RSRP data of main cell is input into preset data detection model, and the first distance of user equipment to main cell is obtained, and reference distance is determined according to the TA value;If the first distance and the reference distance are not consistent, then determine that the minimization drive test target data is abnormal.The application improves the accuracy and efficiency of the identification of abnormal minimization drive test target data.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and in particular to a data detection method, apparatus, device, and computer-readable storage medium. Background Technology

[0002] Tamper-proofing is one of the most common testing methods for wireless data in the telecommunications industry. Tampered wireless data is abnormal, and abnormal wireless data often has adverse consequences for wireless communication performance metrics. For example, abnormal wireless data may lead to a poor user experience and prevent effective improvement in wireless network optimization. Abnormal wireless data also increases the complexity and time of wireless network optimization, affects the accuracy of result analysis, and is detrimental to network quality assessment and wireless network optimization. Therefore, it is necessary to identify abnormal data in wireless data. Summary of the Invention

[0003] The main objective of this invention is to provide a data detection method, apparatus, device, and computer-readable storage medium, which aims to solve the problem of how to identify abnormal data in wireless data.

[0004] To achieve the above objectives, the present invention provides a data detection method, which includes the following steps:

[0005] Obtain the minimum drive test target data, which includes the reference signal received power (RSRP) data of the main cell corresponding to the user equipment receiving the main cell radio signal and the maximum time advance (TA) value;

[0006] The RSRP data of the main cell is input into a preset data detection model to obtain the first distance from the user equipment to the main cell, and the reference distance is determined based on the TA value;

[0007] If the first distance is inconsistent with the reference distance, the minimized road test target data is determined to be abnormal.

[0008] In one embodiment, after the step of determining the reference distance based on the TA value, the method further includes:

[0009] If the first distance is consistent with the reference distance, the RSRP data of the neighboring cell is input into a preset data detection model to obtain the second distance from the user equipment to the neighboring cell;

[0010] The third distance between the main cell and the neighboring cells is determined based on the preset location information of the main cell and the preset location information of the neighboring cells;

[0011] If the sum of the first distance and the second distance is less than the third distance, then the minimized road test target data is determined to be abnormal.

[0012] In one embodiment, before the step of inputting the RSRP data of the primary cell into a preset data detection model, the method further includes:

[0013] Obtain minimum road test training data, which includes user equipment location training information, RSRP training data, and TA training values;

[0014] A pre-defined neural network model is trained based on the minimized road test training data to obtain a data detection model.

[0015] In one embodiment, prior to the step of obtaining the minimized road test training data, the method further includes:

[0016] Obtain the minimum initial road test data, which includes the initial location information of the user equipment, the initial RSRP data, and the initial TA value;

[0017] The fourth distance between the user equipment and the main cell is determined based on the initial location information of the user equipment and the preset location information of the main cell;

[0018] If the fourth distance is inconsistent with the reference distance, then the minimized initial road test data is determined to be abnormal;

[0019] If the fourth distance is consistent with the reference distance, then the minimized road test training data is determined based on the minimized initial road test data.

[0020] In one embodiment, the step of determining the minimum road test training data based on the minimum road test initial data if the fourth distance is consistent with the reference distance includes:

[0021] If the fourth distance is consistent with the reference distance, the initial RSRP data of the main cell is input into the preset prediction model to obtain the fifth distance of the user equipment to the location information of the main cell.

[0022] If the fifth distance is inconsistent with the reference distance, then the minimized initial road test data is determined to be abnormal;

[0023] If the fifth distance is consistent with the reference distance, then the minimized initial road test data will be used as the minimized road test training data.

[0024] In one embodiment, after the step of determining the fourth distance between the user equipment and the main cell based on the initial location information of the user equipment and the preset location information of the main cell, the method further includes:

[0025] If the fourth distance is greater than or equal to the preset distance, then the minimized initial road test data is determined to be abnormal.

[0026] If the fourth distance is less than the preset distance, then the step of determining that the initial data of minimizing the road test is abnormal is executed if the fourth distance is inconsistent with the reference distance.

[0027] In one embodiment, the step of determining the fourth distance between the user equipment and the main cell based on the initial location information of the user equipment and the preset location information of the main cell includes:

[0028] The latitude and longitude of the user equipment are determined based on the initial location information of the user equipment.

[0029] The latitude and longitude of the main cell are determined based on the location information of the main cell;

[0030] The fourth distance between the user equipment and the main cell is determined based on the latitude and longitude of the user equipment and the main cell.

[0031] To achieve the above objectives, the present invention also provides a data detection device, the data detection device comprising:

[0032] The acquisition module is used to acquire the minimized drive test target data, which includes the reference signal received power (RSRP) data of the main cell corresponding to the user equipment receiving the main cell radio signal and the maximum time advance (TA) value.

[0033] The determination module is used to input the RSRP data of the main cell into a preset data detection model to obtain the first distance from the user equipment to the main cell, and determine the reference distance based on the TA value;

[0034] The detection module is used to determine that the minimized road test target data is abnormal if the first distance is inconsistent with the reference distance.

[0035] To achieve the above objectives, the present invention also provides a data detection device, the data detection device including a memory, a processor, and a data detection program stored in the memory and executable on the processor, wherein the data detection program, when executed by the processor, implements the various steps of the data detection method described above.

[0036] To achieve the above objectives, the present invention also provides a computer-readable storage medium storing a data detection program, which, when executed by a processor, implements the various steps of the data detection method described above.

[0037] This invention provides a data detection method, apparatus, device, and computer-readable storage medium to acquire minimized drive test target data. The minimized drive test target data includes the RSRP data and TA value of the primary cell. The RSRP data of the primary cell is input into a preset data detection model to obtain a first distance from the user equipment to the primary cell, and a reference distance is determined based on the TA value. If the first distance and the reference distance are inconsistent, the minimized drive test target data is determined to be abnormal. By comparing the first distance corresponding to the RSRP data and the reference distance corresponding to the TA value, abnormal minimized drive test target data is identified, improving the accuracy and efficiency of identifying abnormal minimized drive test target data. Attached Figure Description

[0038] Figure 1 This is a schematic diagram of the hardware structure of the data detection device according to an embodiment of the present invention;

[0039] Figure 2 This is a flowchart illustrating the first embodiment of the data detection method of the present invention;

[0040] Figure 3 This is a flowchart illustrating the second embodiment of the data detection method of the present invention;

[0041] Figure 4 This is a schematic diagram illustrating the distances from the user equipment to the main cell and neighboring cells in the data detection method of the present invention;

[0042] Figure 5 This is a schematic diagram illustrating the distances from the user equipment to the main cell and neighboring cells in the data detection method of the present invention;

[0043] Figure 6 This is a flowchart illustrating the third embodiment of the data detection method of the present invention;

[0044] Figure 7 This is a flowchart illustrating the fourth embodiment of the data detection method of the present invention;

[0045] Figure 8 This is a detailed flowchart of step S120 in the fifth embodiment of the data detection method of the present invention;

[0046] Figure 9 This is a logical structure diagram of the data detection device of the present invention.

[0047] 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

[0048] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0049] The main solution of this invention is to obtain the minimized drive test target data, which includes the RSRP data and TA value of the main cell. The RSRP data of the main cell is input into a preset data detection model to obtain the first distance from the user equipment to the main cell, and the reference distance is determined according to the TA value. If the first distance is inconsistent with the reference distance, the minimized drive test target data is determined to be abnormal.

[0050] By comparing the first distance corresponding to RSRP data with the reference distance corresponding to TA value, the abnormal minimum road test target data is determined, which improves the accuracy and efficiency of identifying abnormal minimum road test target data.

[0051] As one implementation solution, data inspection equipment can be like Figure 1 As shown.

[0052] The present invention relates to a data detection 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 enable communication between these components.

[0053] 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 data detection program; and the processor 101 may be used to call the data detection program stored in the memory 102 and perform the following operations:

[0054] Obtain the minimum drive test target data, which includes the reference signal received power (RSRP) data of the main cell corresponding to the user equipment receiving the main cell radio signal and the maximum time advance (TA) value;

[0055] The RSRP data of the main cell is input into a preset data detection model to obtain the first distance from the user equipment to the main cell, and the reference distance is determined based on the TA value;

[0056] If the first distance is inconsistent with the reference distance, the minimized road test target data is determined to be abnormal.

[0057] In one embodiment, the processor 101 can be used to invoke a data detection program stored in the memory 102 and perform the following operations:

[0058] If the first distance is consistent with the reference distance, the RSRP data of the neighboring cell is input into a preset data detection model to obtain the second distance from the user equipment to the neighboring cell;

[0059] The third distance between the main cell and the neighboring cells is determined based on the preset location information of the main cell and the preset location information of the neighboring cells;

[0060] If the sum of the first distance and the second distance is less than the third distance, then the minimized road test target data is determined to be abnormal.

[0061] In one embodiment, the processor 101 can be used to invoke a data detection program stored in the memory 102 and perform the following operations:

[0062] Obtain minimum road test training data, which includes user equipment location training information, RSRP training data, and TA training values;

[0063] A pre-defined neural network model is trained based on the minimized road test training data to obtain a data detection model.

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

[0065] Obtain the minimum initial road test data, which includes the initial location information of the user equipment, the initial RSRP data, and the initial TA value;

[0066] The fourth distance between the user equipment and the preset main cell is determined based on the location information of the user equipment and the location information of the main cell.

[0067] If the fourth distance is inconsistent with the reference distance, then the minimized initial road test data is determined to be abnormal;

[0068] If the fourth distance is consistent with the reference distance, then the minimized road test training data is determined based on the minimized initial road test data.

[0069] In one embodiment, the processor 101 can be used to invoke a data detection program stored in the memory 102 and perform the following operations:

[0070] If the fourth distance is consistent with the reference distance, the initial RSRP data of the main cell is input into the preset prediction model to obtain the fifth distance of the user equipment to the location information of the main cell.

[0071] If the fifth distance is inconsistent with the reference distance, then the minimized initial road test data is determined to be abnormal;

[0072] If the fifth distance is consistent with the reference distance, then the minimized initial road test data will be used as the minimized road test training data.

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

[0074] If the fourth distance is greater than or equal to the preset distance, then the minimized initial road test data is determined to be abnormal.

[0075] If the fourth distance is less than the preset distance, then the step of determining that the initial data of minimizing the road test is abnormal is executed if the fourth distance is inconsistent with the reference distance.

[0076] In one embodiment, the processor 101 can be used to invoke a data detection program stored in the memory 102 and perform the following operations:

[0077] The latitude and longitude of the user equipment are determined based on the initial location information of the user equipment.

[0078] The latitude and longitude of the main cell are determined based on the location information of the main cell;

[0079] The fourth distance between the user equipment and the main cell is determined based on the latitude and longitude of the user equipment and the main cell.

[0080] Based on the hardware architecture of the aforementioned data detection equipment, embodiments of the data detection method of the present invention are proposed.

[0081] Reference Figure 2 , Figure 2 This is a first embodiment of the data detection method of the present invention, the data detection method comprising the following steps:

[0082] Step S10: Obtain the minimized drive test target data, which includes the reference signal received power (RSRP) data of the main cell corresponding to the user equipment receiving the main cell radio signal and the maximum time advance (TA) value.

[0083] Specifically, the minimum drive test target data is the MDT (Minimization Drive Test) data of the wireless network. The minimum drive test target data includes the RSRP (Reference Signal Receiving Power) data and TA (Time Advanced) value of the primary cell corresponding to the user equipment receiving the primary cell's wireless signal.

[0084] Step S20: Input the RSRP data of the main cell into a preset data detection model to obtain the first distance from the user equipment to the main cell, and determine the reference distance based on the TA value;

[0085] Specifically, the RSRP data of the main cell is input into a preset data detection model to obtain the first distance from the user equipment to the main cell. The data detection model can be the SPM standard propagation model, which can be expressed by the following formula:

[0086]

[0087] Where d represents the distance between the user equipment and the base station; L(Ploss) represents the path loss, assuming a transmit power of 1 dB, a distance loss of 1 km of 101 dB, and a receive power of -100 dB; K1 represents the offset constant; K2 represents the distance attenuation factor; K3 represents the correlation factor of the base station antenna height; K4 represents the correction factor for diffraction calculation; K5 represents the correction factor for the effective height and distance of the transmit antenna; K6 represents the correction factor for the effective height of the base station; K7 represents the terrain-averaged weighted loss; hms represents the height of the user equipment relative to the ground; heff represents the effective height of the base station antenna; Diffraction represents the diffraction loss calculated by the equivalent blade diffraction method; and Clutter represents the terrain correction factor.

[0088] The formula for calculating the reference signal received power RSRP and the path loss L (Ploss) is as follows:

[0089] RSRP = P TX -L(Ploss);

[0090] Among them, P TX This refers to the transmit power of the base station antenna, which can be divided into the transmit power of the uplink reference signal for user devices and the transmit power of the downlink reference signal for the base station, depending on whether it is uplink or downlink.

[0091] During random access, the TA value ranges from 0 to 1282. The user equipment adjusts its uplink transmission time based on the TA value, which is Nta = TA × 16. The reference distance is determined based on the TA value. For example, when TA = 1, the uplink transmission time Nta = 1 × 16Ts, and the reference distance corresponding to TA is 16 × 4.89 = 78.12m.

[0092] Step S30: If the first distance is inconsistent with the reference distance, then the minimized road test target data is determined to be abnormal.

[0093] Specifically, when the first distance and the reference distance are inconsistent, the minimized drive test target data is determined to be abnormal. When the first distance and the reference distance are consistent, the minimized drive test target data can be determined to be normal data, and further judgment can be made on the minimized drive test target data. Removing abnormal minimized drive test target data facilitates the analysis of wireless network optimization data and improves the accuracy and efficiency of wireless communication data analysis.

[0094] In this embodiment, the minimized drive test target data is acquired. This minimized drive test target data includes the RSRP data and TA value of the primary cell. The RSRP data of the primary cell is input into a preset data detection model to obtain a first distance from the user equipment to the primary cell, and a reference distance is determined based on the TA value. If the first distance and the reference distance are inconsistent, the minimized drive test target data is determined to be abnormal. By comparing the first distance corresponding to the RSRP data and the reference distance corresponding to the TA value, abnormal minimized drive test target data is identified, improving the accuracy and efficiency of identifying abnormal minimized drive test target data.

[0095] Reference Figure 3 , Figure 3 This is a second embodiment of the data detection method of the present invention. Based on the first embodiment, after step S20, it further includes:

[0096] Step S40: If the first distance is consistent with the reference distance, the RSRP data of the neighboring cell is input into a preset data detection model to obtain the second distance from the user equipment to the neighboring cell.

[0097] Step S50: Determine the third distance between the main cell and the neighboring cell based on the preset location information of the main cell and the preset location information of the neighboring cells;

[0098] Step S60: If the sum of the first distance and the second distance is less than the third distance, then the minimized road test target data is determined to be abnormal.

[0099] Specifically, the minimized drive test target data also includes RSRP data of the neighboring cell corresponding to the wireless signal received by the user equipment. When the first distance is consistent with the reference distance, the RSRP data of the neighboring cell is input into the preset data detection model to obtain the second distance from the user equipment to the neighboring cell.

[0100] The third distance between the main cell and neighboring cells is determined based on the preset location information of the main cell and the preset location information of neighboring cells. The location information may include latitude, longitude, and altitude. The latitude and longitude of the main cell are determined based on its location information; the latitude and longitude of the neighboring cells are determined based on their location information; and the third distance between the main cell and neighboring cells is determined based on their latitude and longitude.

[0101] When the sum of the first distance and the second distance is greater than the third distance, such as Figure 4As shown, a represents the user equipment, b represents the primary cell, c represents the neighboring cell, d1 represents the first distance from the user equipment to the primary cell, d2 represents the second distance from the user equipment to the neighboring cell, and D represents the third distance from the primary cell to the neighboring cell. The sum of the first and second distances is greater than the third distance, indicating that the minimized drive test target data is normal. When the sum of the first and second distances equals the third distance, as shown... Figure 5 As shown, a represents the user equipment, b represents the primary cell, c represents the neighboring cell, d1 represents the first distance from the user equipment to the primary cell, d2 represents the second distance from the user equipment to the neighboring cell, and D represents the third distance from the primary cell to the neighboring cell. If the sum of the first and second distances equals the third distance, the minimized drive test target data is considered normal. If the sum of the first and second distances is less than the third distance, the minimized drive test target data is considered abnormal.

[0102] In this embodiment, when the first distance matches the reference distance, the RSRP data of the neighboring cell is input into a preset data detection model to obtain the second distance from the user equipment to the neighboring cell. A third distance between the main cell and the neighboring cell is determined based on preset location information of the main cell and preset location information of the neighboring cells. If the sum of the first distance and the second distance is less than the third distance, the minimized drive test target data is determined to be abnormal. Further detection of minimized drive test target data where the first distance and the reference distance match identifies abnormal minimized drive test target data, thus improving the accuracy of identifying abnormal minimized drive test target data.

[0103] Reference Figure 6 , Figure 6 In a third embodiment of the data detection method of the present invention, based on the first or second embodiment, before step S20, the method further includes:

[0104] Step S70: Obtain the minimum road test training data, which includes the user equipment location training information, RSRP training data, and TA training value;

[0105] Step S80: Train a preset neural network model based on the minimized road test training data to obtain a data detection model.

[0106] Specifically, the minimized drive test training data is the MDT data of the wireless network. This data is used to train a pre-defined neural network model and includes user equipment location training information, RSRP training data, and TA training values. The RSRP training data can be the RSRP data of the primary cell corresponding to the user equipment receiving the primary cell's wireless signal and / or the RSRP data of the neighboring cells corresponding to the user equipment receiving the neighboring cell's wireless signal. The pre-defined neural network model is trained using the minimized drive test training data to obtain a data detection model. This model is used to generate the distance from the user equipment to the primary cell based on the primary cell's RSRP data, and / or to the distance from the user equipment to the neighboring cells based on the neighboring cells' RSRP data.

[0107] In this embodiment, minimal road test training data is acquired, and a preset neural network model is trained based on the minimal road test training data to obtain a data detection model. The data detection model, trained based on the minimal road test training data, identifies abnormal minimal road test target data, thereby improving the accuracy and efficiency of identifying abnormal minimal road test target data.

[0108] Reference Figure 7 , Figure 7 This is a fourth embodiment of the data detection method of the present invention. Based on the third embodiment, before step S70, it further includes:

[0109] Step S90: Obtain the minimum initial road test data, which includes the initial location information of the user equipment, the initial RSRP data, and the initial TA value;

[0110] Step S100: Determine the fourth distance between the user equipment and the main cell based on the initial location information of the user equipment and the preset location information of the main cell;

[0111] Step S110: If the fourth distance is inconsistent with the reference distance, then the minimized initial road test data is determined to be abnormal.

[0112] Step S120: If the fourth distance is consistent with the reference distance, then determine the minimized road test training data based on the minimized initial road test data.

[0113] Specifically, before obtaining the minimum drive test training data, data filtering is required. The initial minimum drive test data is obtained, which is the unfiltered MDT data of the wireless network. This initial minimum drive test data includes initial location information of user equipment, initial RSRP data, and initial TA values.

[0114] The fourth distance between the user equipment and the main cell is determined based on the initial location information of the user equipment and the preset location information of the main cell. For example, the latitude and longitude of the user equipment are determined based on the initial location information of the user equipment, the latitude and longitude of the main cell are determined based on the location information of the main cell, and the fourth distance between the user equipment and the main cell is determined based on the latitude and longitude of the user equipment and the main cell.

[0115] After determining the fourth distance, it can be determined whether the fourth distance is greater than the preset distance. If the fourth distance is greater than or equal to the preset distance, it is determined that the initial data of the minimization road test is abnormal; if the fourth distance is less than the preset distance, step S110 or step S120 is executed.

[0116] After determining the fourth distance, it can be determined whether the fourth distance is consistent with the reference distance. If the fourth distance is inconsistent with the reference distance, the minimum road test initial data is determined to be abnormal; if the fourth distance is consistent with the reference distance, the minimum road test training data is determined based on the minimum road test initial data.

[0117] In this embodiment, the technical solution involves acquiring minimal initial drive test data; determining a fourth distance between the user equipment and the main cell based on the user equipment's initial location information and the preset main cell's location information; if the fourth distance is inconsistent with the reference distance, the minimal initial drive test data is deemed abnormal; if the fourth distance is consistent with the reference distance, minimal drive test training data is determined based on the minimal initial drive test data. By filtering the minimal initial drive test data and identifying abnormal minimal initial drive test data, the determined minimal drive test training data is deemed non-abnormal, thereby improving the accuracy of the trained data detection model.

[0118] Reference Figure 8 , Figure 8 This is the fifth embodiment of the data detection method of the present invention. Based on the fourth embodiment, step S120 includes:

[0119] Step S121: If the fourth distance is consistent with the reference distance, the initial RSRP data of the main cell is input into the preset prediction model to obtain the fifth distance of the user equipment to the location information of the main cell.

[0120] Step S122: If the fifth distance is inconsistent with the reference distance, then the minimized initial road test data is determined to be abnormal.

[0121] Step S123: If the fifth distance is consistent with the reference distance, then the minimized initial road test data is used as the minimized road test training data.

[0122] Specifically, the preset prediction model is used to determine the fifth distance from the user equipment to the main cell's location information based on the main cell's RSRP data. The preset prediction model is the General model, i.e., the standard macro cell propagation model. The applicable range of the prediction model is: frequency 0.5GHz~2GHz; base station antenna height 30m~200m; user equipment antenna height 1m~10m; communication distance: 1Km~35Km. The prediction model can be expressed by the following formula:

[0123] RSRP RX =P TX +K1+K2×log(d)+K3×log(H eff )+K4×Diffraction

[0124] +K5×log(H eff )×log(d)+K6(H meff )+K clutter

[0125] Among them, RSRP RX P represents the received power of the reference signal. TX H represents the transmit power of the base station antenna; meff Indicates the height of the user equipment; H eff K represents the effective antenna height of the base station above the ground; Diffraction represents diffraction loss; k3 represents the effective antenna height gain; k5 represents the Okumura-Hata multiplicative correction factor; k6 represents the base station antenna height correction factor; K clutter This indicates the ground damage at the location of the base station.

[0126] The values ​​of K1, K2, K3, K4, K5, and K6 obtained from training the data detection model vary in different regions. For example, in densely populated urban areas, K1 = 0.02, K2 = 56.5, K3 = 0, K4 = 0, K5 = -13.82, and K6 = -6.55; in general urban areas, K1 = 8.45, K2 = 52.05, K3 = 0, K4 = 0, K5 = -13.82, and K6 = -6.55; in suburban areas, K1 = 26.08, K2 = 45.69, K3 = 0, K4 = 0, K5 = -13.82, and K6 = -6.55; and in rural areas, K1 = 6.06, K2 = 50.01, K3 = 0, K4 = 0, K5 = -13.82, and K6 = -6.55.

[0127] After determining the fifth distance from the user equipment to the main cell, if the fifth distance is inconsistent with the reference distance, the minimized drive test initial data is determined to be abnormal; if the fifth distance is consistent with the reference distance, the minimized drive test initial data is used as the minimized drive test training data.

[0128] In this embodiment, if the fourth distance matches the reference distance, the initial RSRP data of the main cell is input into a preset prediction model to obtain the fifth distance from the user equipment to the main cell. If the fifth distance does not match the reference distance, the minimized drive test initial data is determined to be abnormal. If the fifth distance matches the reference distance, the minimized drive test initial data is used as minimized drive test training data. Further filtering of the minimized drive test initial data where the fourth distance matches the reference distance improves the accuracy of identifying abnormal minimized drive test initial data, ensuring that the determined minimized drive test training data is non-abnormal, and improving the accuracy of the trained data detection model.

[0129] Reference Figure 9 The present invention also provides a data detection device, the data detection device comprising:

[0130] The acquisition module 100 is used to acquire the minimized drive test target data, which includes the reference signal received power (RSRP) data of the main cell corresponding to the user equipment receiving the main cell radio signal and the maximum time advance (TA) value.

[0131] The determination module 200 is used to input the RSRP data of the main cell into a preset data detection model to obtain the first distance from the user equipment to the main cell, and determine the reference distance based on the TA value;

[0132] The detection module 300 is used to determine that the minimized road test target data is abnormal if the first distance is inconsistent with the reference distance.

[0133] In one embodiment, after determining the reference distance based on the TA value, the determining module 200 is specifically used for:

[0134] If the first distance is consistent with the reference distance, the RSRP data of the neighboring cell is input into a preset data detection model to obtain the second distance from the user equipment to the neighboring cell;

[0135] The third distance between the main cell and the neighboring cells is determined based on the preset location information of the main cell and the preset location information of the neighboring cells;

[0136] If the sum of the first distance and the second distance is less than the third distance, then the minimized road test target data is determined to be abnormal.

[0137] In one embodiment, before inputting the RSRP data of the primary cell into a preset data detection model, the determining module 200 is specifically used for:

[0138] Obtain minimum road test training data, which includes user equipment location training information, RSRP training data, and TA training values;

[0139] A pre-defined neural network model is trained based on the minimized road test training data to obtain a data detection model.

[0140] In one embodiment, before acquiring the minimum road test training data, the determining module 200 is specifically used for:

[0141] Obtain the minimum initial road test data, which includes the initial location information of the user equipment, the initial RSRP data, and the initial TA value;

[0142] The fourth distance between the user equipment and the main cell is determined based on the initial location information of the user equipment and the preset location information of the main cell;

[0143] If the fourth distance is inconsistent with the reference distance, then the minimized initial road test data is determined to be abnormal;

[0144] If the fourth distance is consistent with the reference distance, then the minimized road test training data is determined based on the minimized initial road test data.

[0145] In one embodiment, regarding determining the minimum road test training data based on the minimum road test initial data if the fourth distance is consistent with the reference distance, the determining module 200 is specifically used for:

[0146] If the fourth distance is consistent with the reference distance, the initial RSRP data of the main cell is input into the preset prediction model to obtain the fifth distance of the user equipment to the location information of the main cell.

[0147] If the fifth distance is inconsistent with the reference distance, then the minimized initial road test data is determined to be abnormal;

[0148] If the fifth distance is consistent with the reference distance, then the minimized initial road test data will be used as the minimized road test training data.

[0149] In one embodiment, after determining the fourth distance between the user equipment and the main cell based on the initial location information of the user equipment and the preset location information of the main cell, the determining module 200 is specifically used for:

[0150] If the fourth distance is greater than or equal to the preset distance, then the minimized initial road test data is determined to be abnormal.

[0151] If the fourth distance is less than the preset distance, then the step of determining that the initial data of minimizing the road test is abnormal is executed if the fourth distance is inconsistent with the reference distance.

[0152] In one embodiment, in determining the fourth distance between the user equipment and the main cell based on the initial location information of the user equipment and the location information of the preset main cell, the determining module 200 is specifically used for:

[0153] The latitude and longitude of the user equipment are determined based on the initial location information of the user equipment.

[0154] The latitude and longitude of the main cell are determined based on the location information of the main cell;

[0155] The fourth distance between the user equipment and the main cell is determined based on the latitude and longitude of the user equipment and the main cell.

[0156] The present invention also provides a data detection device, the data detection device including a memory, a processor, and a data detection program stored in the memory and executable on the processor, wherein when the data detection program is executed by the processor, it implements the various steps of the data detection method as described in the above embodiments.

[0157] The present invention also provides a computer-readable storage medium storing a data detection program, which, when executed by a processor, implements the various steps of the data detection method described in the above embodiments.

[0158] 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.

[0159] 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.

[0160] 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.

[0161] 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 data detection method, characterized in that, The data detection method includes: Obtain the minimum drive test target data, which includes the reference signal received power (RSRP) data of the main cell corresponding to the user equipment receiving the main cell radio signal and the maximum time advance (TA) value; The RSRP data of the main cell is input into a preset data detection model to obtain the first distance from the user equipment to the main cell, and the reference distance is determined based on the TA value; If the first distance is inconsistent with the reference distance, the minimized road test target data is determined to be abnormal; The minimized drive test target data includes RSRP data of neighboring cells corresponding to the wireless signals received by the user equipment from neighboring cells. After the step of determining the reference distance based on the TA value, the method further includes: If the first distance is consistent with the reference distance, the RSRP data of the neighboring cell is input into a preset data detection model to obtain the second distance from the user equipment to the neighboring cell; The third distance between the main cell and the neighboring cells is determined based on the preset location information of the main cell and the preset location information of the neighboring cells; If the sum of the first distance and the second distance is less than the third distance, then the minimized road test target data is determined to be abnormal. Before the step of inputting the RSRP data of the main cell into the preset data detection model, the method further includes: Obtain minimum drive test training data, which includes user equipment location training information, RSRP training data, and TA training value; RSRP training data is the RSRP data of the main cell corresponding to the user equipment receiving the main cell radio signal and / or the RSRP data of the neighboring cell corresponding to the user equipment receiving the neighboring cell radio signal. A pre-set neural network model is trained based on the minimized road test training data to obtain a data detection model; Before the step of obtaining the minimized road test training data, the method further includes: Obtain the minimum initial road test data, which includes the initial location information of the user equipment, the initial RSRP data, and the initial TA value; The fourth distance between the user equipment and the main cell is determined based on the initial location information of the user equipment and the preset location information of the main cell; If the fourth distance is inconsistent with the reference distance, then the minimized initial road test data is determined to be abnormal; If the fourth distance is consistent with the reference distance, the initial RSRP data of the main cell is input into the preset prediction model to obtain the fifth distance of the user equipment to the location information of the main cell. If the fifth distance is inconsistent with the reference distance, then the minimized initial road test data is determined to be abnormal; If the fifth distance is consistent with the reference distance, then the minimized initial road test data will be used as the minimized road test training data.

2. The data detection method as described in claim 1, characterized in that, After the step of determining the fourth distance between the user equipment and the main cell based on the initial location information of the user equipment and the preset location information of the main cell, the method further includes: If the fourth distance is greater than or equal to the preset distance, then the minimized initial road test data is determined to be abnormal. If the fourth distance is less than the preset distance, then the step of determining that the initial data of minimizing the road test is abnormal is executed if the fourth distance is inconsistent with the reference distance.

3. The data detection method as described in claim 1, characterized in that, The step of determining the fourth distance between the user equipment and the main cell based on the initial location information of the user equipment and the preset location information of the main cell includes: The latitude and longitude of the user equipment are determined based on the initial location information of the user equipment. The latitude and longitude of the main cell are determined based on the location information of the main cell; The fourth distance between the user equipment and the main cell is determined based on the latitude and longitude of the user equipment and the main cell.

4. A data detection device, characterized in that, The data detection device includes: The acquisition module is used to acquire the minimum drive test target data, which includes the reference signal received power (RSRP) data and the maximum timing advance (TA) value of the main cell corresponding to the user equipment receiving the main cell radio signal; the minimum drive test target data also includes the RSRP data of the neighboring cell corresponding to the user equipment receiving the neighboring cell radio signal. The determination module is used to input the RSRP data of the main cell into a preset data detection model to obtain the first distance from the user equipment to the main cell, and determine the reference distance based on the TA value; The detection module is used to determine that the minimized road test target data is abnormal if the first distance is inconsistent with the reference distance. The detection module is also used for: If the first distance is consistent with the reference distance, the RSRP data of the neighboring cell is input into a preset data detection model to obtain the second distance from the user equipment to the neighboring cell; The third distance between the main cell and the neighboring cells is determined based on the preset location information of the main cell and the preset location information of the neighboring cells; If the sum of the first distance and the second distance is less than the third distance, then the minimized road test target data is determined to be abnormal. The determining module is used for: Obtain minimum drive test training data, which includes user equipment location training information, RSRP training data, and TA training value; RSRP training data is the RSRP data of the main cell corresponding to the user equipment receiving the main cell radio signal and / or the RSRP data of the neighboring cell corresponding to the user equipment receiving the neighboring cell radio signal. A pre-set neural network model is trained based on the minimized road test training data to obtain a data detection model; Before the step of obtaining the minimized road test training data, the method further includes: Obtain the minimum initial road test data, which includes the initial location information of the user equipment, the initial RSRP data, and the initial TA value; The fourth distance between the user equipment and the main cell is determined based on the initial location information of the user equipment and the preset location information of the main cell; If the fourth distance is inconsistent with the reference distance, then the minimized initial road test data is determined to be abnormal; If the fourth distance is consistent with the reference distance, the initial RSRP data of the main cell is input into the preset prediction model to obtain the fifth distance of the user equipment to the location information of the main cell. If the fifth distance is inconsistent with the reference distance, then the minimized initial road test data is determined to be abnormal; If the fifth distance is consistent with the reference distance, then the minimized initial road test data will be used as the minimized road test training data.

5. A data detection device, characterized in that, The data detection device includes a memory, a processor, and a data detection program stored in the memory and executable on the processor. When the data detection program is executed by the processor, it implements the steps of the data detection method as described in any one of claims 1-3.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a data detection program, which, when executed by a processor, implements the steps of the data detection method as described in any one of claims 1-3.

Images