A multipath propagation area identification method, device, equipment and storage medium

Abstract

The application discloses a multipath propagation area identification method, which is used to solve the problem of the existing identification scheme needing to rely on artificial way to audit and determine, and having the problem of insufficient identification accuracy. The method comprises the following steps: acquiring MTD data, MR data and engineering parameters uploaded by each user terminal; calculating the angle of arrival (AOA) of each UE according to the MTD data and the engineering parameters; calculating the proportion of the number of each angle of arrival (AOA) in each cell according to the ECI carried in the MTD data and the AOA; generating a low-proportion angle of arrival (AOA) list according to the angle of arrival (AOA) whose proportion is less than a preset proportion threshold; matching the angle of arrival (MR-AOA) data carried in the MR data uploaded by each UE with the low-proportion angle of arrival (AOA) list to determine a multipath propagation UE; determining the area characteristics corresponding to the multipath propagation UE according to the MR data, and determining the multipath propagation area according to the area characteristics.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of wireless communication, and in particular to a multi-path propagation area identification method and device, equipment and a storage medium. BACKGROUND

[0002] In the field of wireless communication, multi-path propagation refers to the propagation phenomenon that a radio signal reaches a receiving antenna through multiple paths from a transmitting antenna.

[0003] Radio waves are electromagnetic waves, and the main mode of propagation is space wave, i.e. direct wave, reflected wave, refracted wave, diffracted wave and their combined waves. When radio waves encounter objects, reflection, refraction and scattering occur, and different objects will be encountered in the process of wave propagation, thus causing different reflection, refraction and scattering. For example, the scattering of the atmosphere, the reflection and refraction of the ionosphere, and the reflection of mountains, buildings and other surface objects, all of which will cause multi-path propagation.

[0004] Due to multi-path propagation, the receiving antenna will receive direct signals and delayed signals reflected, which may cause signal attenuation or distortion and other problems. Therefore, in the process of daily wireless network optimization, it is urgent to identify the high multi-path propagation area, and then guide the optimization of the antenna feeder system parameters according to the identification of the high multi-path propagation area, to realize the optimization of the wireless network.

[0005] In the prior art, the actual position information of the user and the wireless coverage environment in which the user is located are obtained to determine the user scenario, and then the multi-path propagation is identified according to the user scenario.

[0006] The existing classification method of user coverage scenarios generally has the following methods:

[0007] 1. According to the actual topography, building features, traffic flow and other scene attributes of the problem area, combined with artificial judgment, the user scenario is determined by electronic map or field survey method;

[0008] 2. Based on the measurement report (MR) data, combined with the timing advance (TA) and reference signal receiving power (RSRP) information in the MR data, the user scenario is simulated and determined;

[0009] 3. Based on the minimization drive test (MDT) data, combined with the latitude and longitude information reported by the user APP, the user area is determined.

[0010] However, the prior art has problems in that, since the scene recognition of the traditional user needs to rely on artificial way of auditing and determining, which is strongly related to the optimization experience and technical level of the personnel, and is not sensitive to the changes of the network, lacking automatic updating mechanism, there is a deficiency in accuracy; on the other hand, the user position information (AOA) of the MR data collection is relatively rough, and cannot accurately reflect the user distribution, while the MDT data is relatively less in sample size and collection field, and the evaluation comprehensiveness is slightly insufficient.

[0011] Therefore, there is an urgent need for a scheme that can accurately determine the scene where the user is located, and then realize accurate multi-path propagation area recognition. SUMMARY

[0012] The embodiment of the present application provides a multi-path propagation area recognition method, to solve the problem that the existing recognition scheme needs to rely on artificial way of auditing and determining, which is strongly related to the optimization experience and technical level of the personnel, and is not sensitive to the changes of the network, lacking automatic updating mechanism, and is deficient in recognition accuracy.

[0013] The embodiment of the present application also provides a multi-path propagation area recognition device, to solve the problem that the existing recognition scheme needs to rely on artificial way of auditing and determining, which is strongly related to the optimization experience and technical level of the personnel, and is not sensitive to the changes of the network, lacking automatic updating mechanism, and is deficient in recognition accuracy.

[0014] The embodiment of the present application also provides a multi-path propagation area recognition electronic device, to solve the problem that the existing recognition scheme needs to rely on artificial way of auditing and determining, which is strongly related to the optimization experience and technical level of the personnel, and is not sensitive to the changes of the network, lacking automatic updating mechanism, and is deficient in recognition accuracy.

[0015] The embodiment of the present application also provides a computer readable storage medium, to solve the problem that the existing recognition scheme needs to rely on artificial way of auditing and determining, which is strongly related to the optimization experience and technical level of the personnel, and is not sensitive to the changes of the network, lacking automatic updating mechanism, and is deficient in recognition accuracy.

[0016] The embodiment of the present application adopts the following technical scheme:

[0017] A method for identifying a multipath propagation area, comprising: obtaining minimization of drive test (MDT) data, measurement report (MR) data and engineering parameter data uploaded by user equipment (UE) in a to-be-identified area; calculating an angle of arrival (AOA) of each UE according to the MDT data and the engineering parameter data uploaded by each UE; calculating a proportion of the number of UEs corresponding to each AOA in each cell according to a cell unique identity (ECI) carried in the MDT data and the AOA; generating a low-proportion AOA list according to the AOA whose proportion is less than a preset proportion threshold; matching AOA-MR data carried in the MR data uploaded by each UE with the low-proportion AOA list, and determining a multipath propagation UE according to a matching result; determining an area feature corresponding to the multipath propagation UE according to MR data corresponding to the multipath propagation UE, and determining a multipath propagation area according to the area feature.

[0018] An apparatus for identifying a multipath propagation area, comprising: a data obtaining unit configured to obtain minimization of drive test (MDT) data, measurement report (MR) data and engineering parameter data uploaded by user equipment (UE) in a to-be-identified area; an angle of arrival (AOA) calculating unit configured to calculate an AOA of each UE according to the MDT data and the engineering parameter data uploaded by each UE; an AOA proportion determining unit configured to calculate a proportion of the number of UEs corresponding to each AOA in each cell according to a cell unique identity (ECI) carried in the MDT data and the AOA; a low-proportion AOA list generating unit configured to generate a low-proportion AOA list according to the AOA whose proportion is less than a preset proportion threshold; a multipath propagation identifying unit configured to match AOA-MR data carried in the MR data uploaded by each UE with the low-proportion AOA list, and determine a multipath propagation UE according to a matching result; and a multipath propagation area determining unit configured to determine an area feature corresponding to the multipath propagation UE according to MR data corresponding to the multipath propagation UE, and determine a multipath propagation area according to the area feature.

[0019] An electronic device for identifying a multipath propagation area, comprising: a processor; and a memory arranged to store computer-executable instructions that, when executed, cause the processor to perform the following operations:

[0020] Obtain the minimization of drive test (MTD) data, measurement report (MR) data and engineering parameter data uploaded by each user equipment (UE) in a region to be identified; calculate the angle of arrival (AOA) of each UE according to the MTD data and the engineering parameter data uploaded by each UE; calculate the proportion of the number of UEs corresponding to each AOA in each cell according to the cell unique identity (ECI) carried in the MTD data and the AOA; generate a low-proportion AOA list according to the AOA whose proportion is less than a preset proportion threshold; match the angle of arrival MR-AOA data carried in the MR data uploaded by each UE with the low-proportion AOA list, and determine a multipath propagation UE according to the matching result; determine the region feature corresponding to the multipath propagation UE according to the MR data corresponding to the multipath propagation UE, and determine a multipath propagation region according to the region feature.

[0021] A computer-readable storage medium stores one or more programs, which when executed by an electronic device including multiple applications, cause the electronic device to perform the following operations: obtaining minimization of drive test (MTD) data, measurement report (MR) data and engineering parameter data uploaded by each user equipment (UE) in a region to be identified; calculating the angle of arrival (AOA) of each UE according to the MTD data and the engineering parameter data uploaded by each UE; calculating the proportion of the number of UEs corresponding to each AOA in each cell according to the cell unique identity (ECI) carried in the MTD data and the AOA; generating a low-proportion AOA list according to the AOA whose proportion is less than a preset proportion threshold; matching the angle of arrival MR-AOA data carried in the MR data uploaded by each UE with the low-proportion AOA list, and determining a multipath propagation UE according to the matching result; determining the region feature corresponding to the multipath propagation UE according to the MR data corresponding to the multipath propagation UE, and determining a multipath propagation region according to the region feature.

[0022] The above at least one technical solution adopted by the embodiments of the present application can achieve the following beneficial effects:

[0023] The method provided in the embodiment of the application can be used for identifying a multipath propagation area. The server can obtain the minimization drive test (MDT) data, the measurement report (MR) data and the engineering parameter data uploaded by each user equipment (UE) in the area to be identified, and then calculate the angle of arrival (AOA) of each UE according to the MDT data and the engineering parameter data uploaded by each UE, so as to realize the simulation of AOA calculation based on the MDT data. Then, the proportion of the number of UEs corresponding to each AOA in each cell is determined according to the cell unique identifier (ECI) carried in the MDT data and the AOA, and a low-proportion AOA list is generated according to the AOA whose proportion of the number is less than a preset proportion threshold. The multipath propagation UE is determined by matching the angle of arrival MR-AOA data carried in the MR data uploaded by each UE with the low-proportion AOA list. The area feature corresponding to the multipath propagation UE is determined according to the MR data corresponding to the multipath propagation UE, and finally the multipath propagation area can be determined according to the area feature. The method provided in the embodiment of the application can be used for identifying a multipath propagation area. The method is based on the differential comparison of AOA data of MDT and MR data, and the high-proportion multipath signal proportion and the sampling feature number of high-proportion multipath are output by matching the strong correlation MR sampling points, so as to identify the uplink multipath coverage scene information of the cell and solve the problem of insufficient accuracy of the traditional checking method. BRIEF DESCRIPTION OF DRAWINGS

[0024] The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and serve to explain the principles of the application, and do not limit the application. In the drawings:

[0025] Figure 1 A specific flowchart of a multipath propagation area identification method provided in the embodiment of the application is shown in the figure.

[0026] Figure 2 A schematic diagram of a grid map provided in the embodiment of the application is shown in the figure.

[0027] Figure 3 A specific structure diagram of a multipath propagation area identification device provided in the embodiment of the application is shown in the figure.

[0028] Figure 4 A specific structure diagram of a multipath propagation area identification electronic device provided in the embodiment of the application is shown in the figure. DETAILED DESCRIPTION

[0029] In order to make the purposes, technical solutions and advantages of the present application clearer, the technical solutions of the present application will be described below in connection with specific embodiments of the present application and corresponding drawings. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of protection of the present application.

[0030] In order to facilitate the understanding of the technical solutions of the present application, some technical terms used in the embodiments of the present application will be introduced below.

[0031] The measurement report (MR) is a measurement report uploaded by a terminal device (such as a mobile phone). Measurement is an important function of the TD-SCDMA Long Term Evolution (TD-LTE) system, and measurement data has the advantages of being more specific, more comprehensive, more complete and easier to obtain than road test data.

[0032] Minimization of Drive-tests (MDT) is an automatic drive test technology introduced in the LTE and 3G systems in the R10 stage of the 3rd Generation Partnership Project (3GPP). Based on the design concept of minimizing the impact on terminal power consumption and maximizing the availability of location information, the MDT function is mainly realized by extending the existing Radio Resource Management (RRM) measurement function and the Trace function. The base station sends relevant measurement configurations to the terminal according to the MDT measurement tasks configured by the network management, and the terminal performs measurement and reports the measurement information when the measurement conditions are met. The base station reports the terminal measurement results and the base station's own measurement results to the network management or the MDT data storage processing network element as required. Compared with traditional drive testing, MDT directly uses commercial terminals and base stations in the existing network for measurement and data collection, without the need for additional investment in test personnel, test terminals, test vehicles and other supporting resources, which can greatly reduce the cost of drive testing and collect more abundant and more real network measurement data than road test data. Compared with the MR report, MDT can not only collect accurate position (latitude and longitude) information corresponding to the measurement results, but also support idle state terminal measurement data collection, support related measurement data collection during abnormal events such as Radio Link Failure (RLF), and support more measurement items for measurement reporting.

[0033] Engineering parameter, also known as work parameter, contains the ID of the base station, azimuth angle, base station height, coverage type, coverage scenario, cell unique identifier (E-UTRAN Cell Identifier, ECI), location area code (Location Area Code, LAC), base station controller (Base Station Controller, BSC), frequency point configuration and latitude and longitude information, and mainly helps engineers understand the network situation and serves as an important reference for optimization.

[0034] Antenna angle of arrival (Angle-of-Arrival, AOA) is a statistical index in MR. In the "TD-LTE Digital Cellular Mobile Communication Network Wireless Operation and Maintenance Center (OMC-R) Measurement Report Technical Requirements", the antenna angle of arrival is defined as follows: MR.AOA defines an estimated angle of a user in the counterclockwise direction relative to the reference direction. In the standard, the reference direction should be the north direction. It can assist in determining the position of the user and providing positioning services with an accuracy of 5 degrees. The measurement data represent the number of samples of the antenna angle of arrival in the statistical period according to the partition interval that meets the value range condition. The AOA value range is 0 to 71, a total of 72 equal parts, that is, AOA00 to AOA71, each equal part represents a 5-degree angle. When AOA is 00, the corresponding value is the number of samples in the interval [0, 5). Similarly, when AOA is 71, the corresponding value is the number of samples in the interval [355, 360).

[0035] In order to solve the problem that the existing identification scheme needs to rely on artificial way of auditing and determining, which is strongly related to the optimization experience and technical level of personnel, and is not sensitive to network changes, lacks automatic updating mechanism, and has deficiencies in identification accuracy, the embodiments of the present application provide a multipath propagation area identification method. The technical solutions provided by the embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0036] Specifically, the specific implementation flowchart of the multipath propagation area identification method provided by the present application is shown in Figure 1 The method mainly includes the following steps:

[0037] Step 11, obtaining the minimization of driving test (MTD) data, measurement report (MR) data and engineering parameter data uploaded by each user terminal (UE) in the to-be-identified area;

[0038] In the embodiment of the present application, the server can configure the MDT task through the network management system OMMB and issue it to the base station (Evolved NodeB, eNB), then the base station issues the periodic MDT measurement task to the UE, and then the UE collects data according to the measurement task issued by the base station, and then the terminal reports the measurement result to the base station, and finally the base station uploads the collected data to the server, realizing real-time collection of MDT data.

[0039] In the embodiment of the present application, the collected MTD data can include but is not limited to the following parameters: the cell unique identifier ECI corresponding to the UE, the signal received power RSRP (RSRP is one of the key parameters and physical layer measurement requirements that can represent the wireless signal strength in the LTE network, which is the average value of the signal power received on all REs (resource particles) carrying reference signals in a certain symbol), the frequency point number and the latitude and longitude data corresponding to the UE.

[0040] When the user terminal equipment (User Equipment, UE) needs to establish a connection with the network side due to business needs (such as business request, location update, paging, etc.), the UE will trigger the establishment of a radio resource control (Radio Resource Control, RRC) connection with the base station, and after the RRC connection is established, the UE will enter the connected state. Then the base station can determine the UE in the connected state according to whether the UE establishes the RRC connection, and send a measurement report reporting instruction to the terminal equipment UE in the connected state, so that the terminal equipment UE uploads the MR measurement report to the base station, and uploads the MR data to the server through the base station.

[0041] In the embodiment of the present application, the MR data can include but is not limited to the following parameters: the ECI of the main cell corresponding to the UE, the main cell reference signal received power RSRP, the main cell timing advance TA, the angle of arrival MR-AOA, the ECI of the adjacent cell, and the RSRP of the adjacent cell.

[0042] At the same time, the base station will upload the engineering parameters to the server, and in the embodiment of the present application, the engineering parameter data can include but is not limited to the following parameters: the ID of the base station, the azimuth angle, the base station height, the coverage type, the coverage scenario, the cell unique identifier (E-UTRAN Cell Identifier, ECI), the location area code (Location Area Code, LAC), the base station controller (Base Station Controller, BSC), the frequency point configuration and the latitude and longitude information.

[0043] Step 12, according to the MTD data uploaded by each UE and the engineering parameter data, the angle of arrival AOA of each UE is calculated respectively;

[0044] In the embodiments of the present application, the server can calculate the angle of arrival AOA of each UE by making a grid map. Specifically, the server can grid and classify the sampling points of all UE devices on a high-precision grid map of 5M*5M (or also 10M*10M) according to the longitude and latitude coordinates of the UEs in the MTD data and the longitude and latitude coordinates of the base station carried in the engineering parameters, establish a coordinate system on the grid map with the longitude and latitude coordinates of the base station as the origin, determine the position coordinates of the UEs in the coordinate system according to the longitude and latitude coordinates of the UEs carried in the MTD data, and then establish a vector from the position point where the UE is located to the origin of the coordinate system (i.e. the position where the base station is located), as shown in Figure 2 According to the vector angle of the coordinate vector in the coordinate system, the vector angle is taken as the angle of arrival AOA of the UE.

[0045] Specifically, in an implementation, the specific implementation of step 12 can include: establishing a coordinate system according to the longitude and latitude data of the base station in the engineering parameter data as the origin; determining the coordinate vector of the UE in the coordinate system according to the longitude and latitude data of the UE contained in the MTD data; and determining the angle of arrival AOA of the UE according to the coordinate vector.

[0046] Step 13, according to the cell unique identifier ECI carried in the MTD data and the angle of arrival AOA calculated by performing step 12, calculating the proportion of the number of UEs corresponding to each angle of arrival AOA in each cell;

[0047] Specifically, the server can determine the number of user terminals UEs owned under the same cell according to the cell unique identifier ECI carried in the received MTD data, and determine the angle of arrival AOA contained in the cell and the number of user terminals UEs corresponding to each angle of arrival AOA according to the angle of arrival AOA of the user terminal UE obtained by performing step 12. For example, the server determines that cell A contains 100 user terminals UEs according to the cell unique identifier ECI carried in the MTD data, and the angles of arrival AOA corresponding to the user terminals UEs are 20, 80, 180 and 320 respectively, and the number of user terminals UEs corresponding to the angle of arrival AOA 20 is 30, the number of user terminals UEs corresponding to the angle of arrival AOA 80 is 10, the number of user terminals UEs corresponding to the angle of arrival AOA 180 is 40, and the number of user terminals UEs corresponding to the angle of arrival AOA 320 is 20, then the server can calculate and determine that the proportion of the number of the angle of arrival AOA 20 in the cell is 30%, the proportion of the number of the angle of arrival AOA 80 in the cell is 10%, the proportion of the number of the angle of arrival AOA 180 in the cell is 40%, and the proportion of the number of the angle of arrival AOA 320 in the cell is 20%.

[0048] In an embodiment, the implementation of step 13 can include: determining the total number of UEs belonging to the same cell according to the cell unique identifier ECI carried in the MTD data; determining the angle of arrival AOA of the same cell; determining the number of UEs corresponding to each angle of arrival AOA contained in the same cell; and determining the proportion of the number of each angle of arrival AOA in the same cell according to the number of UEs corresponding to the angle of arrival AOA and the total number of UEs in the same cell.

[0049] Step 14, generating a low proportion angle of arrival AOA list based on the angle of arrival AOA whose proportion is less than the preset proportion threshold according to the proportion of each angle of arrival AOA of the same cell calculated by performing step 13.

[0050] In the embodiment of the present application, the server can preset the proportion threshold, for example, the proportion threshold can be set to 1%, and then the angle of arrival AOA whose proportion is less than 1% in the same cell is determined as the low proportion angle of arrival AOA, and the low proportion angle of arrival AOA list is generated according to the determined low proportion angle of arrival AOA.

[0051] Step 15, matching the angle of arrival MR-AOA data carried in the MR data uploaded by each UE with the low proportion angle of arrival AOA list, and determining the multipath propagation UE according to the matching result.

[0052] In the embodiment of the present application, by performing the above-mentioned step 12, the server can simulate and calculate the angle of arrival AOA of each user terminal UE based on the MTD data, and since the MTD data carries the latitude and longitude coordinates of each UE, the accuracy and comprehensiveness of the angle of arrival AOA simulated and calculated using the MTD data are higher than that of the angle of arrival MR-AOA data carried in the traditional MR data. In order to improve the accuracy of determining the multipath propagation area based on the angle of arrival AOA, in the embodiment of the present application, the angle of arrival AOA simulated and calculated based on the MDT data can be associated and compared with the AOA data of the MR data, by strongly associating and matching the user terminal UE corresponding to the MR data with the angle of arrival AOA simulated and calculated based on the MDT data, the multipath propagation UE is determined according to the matching result, and the proportion of the number of multipath propagation UEs in the target area is output by statistics, and then the high multipath propagation area is finally determined.

[0053] In an embodiment, the server can determine the multipath propagation UE according to the following method, which can specifically include: judging whether there is the same angle of arrival (AOA) as the angle of arrival (AOA) data of the multipath propagation in the low-occupancy AOA list; when the result of the judgment is yes, determining that the angle of arrival (AOA) data of the multipath propagation matches the low-occupancy AOA list, and determining that the UE corresponding to the angle of arrival (AOA) of the multipath propagation is the multipath propagation UE.

[0054] Step 16: determining the area feature corresponding to the multipath propagation UE according to the MR data of the multipath propagation UE obtained by performing step 15, and determining the multipath propagation area according to the area feature.

[0055] After the multipath propagation UE is determined through the above-mentioned step 15, the server can determine whether there is the same attribute information of the multipath propagation UE according to the attribute information (such as the ECI of the primary cell and the ECI of the adjacent cell, the RSRP of the primary cell and the RSRP of the adjacent cell, etc.) corresponding to the multipath propagation UE, group the UEs with the same attribute information into a multipath propagation UE set, generate the area feature corresponding to the multipath propagation UE set according to the attribute information of each user terminal UE in the same multipath propagation UE set, and then take the area feature as the area feature of the multipath propagation area.

[0056] In an embodiment, the server can determine the area feature corresponding to the multipath propagation UE according to the following sub-steps, which can specifically include:

[0057] Sub-step 1601: screening the UE with the same ECI of the primary cell and the ECI of the adjacent cell as the multipath propagation UE from other UEs corresponding to the MR data of the multipath propagation UE in the same cell to obtain a first matching UE set;

[0058] In the embodiment of the present application, the server can randomly select a multipath propagation UE in a certain cell as the starting point of the judgment, take the multipath propagation UE as the starting UE of the judgment, screen whether there is the UE with the same ECI of the primary cell and the ECI of the adjacent cell as the starting UE of the judgment in the cell, and construct the first matching UE set based on the UE screened.

[0059] Sub-step 1602: screening the UE with the RSRP difference of the primary cell and the adjacent cell within the preset receiving power threshold range from the multipath propagation UE from the first matching UE set according to the MR data of each UE in the first matching UE set obtained by performing sub-step 1601 to obtain a second matching UE set;

[0060] Further, the server can screen the UEs in the first matched UE set, which have a difference between the RSRP of the primary cell of the determining starting UE and the RSRP of the neighboring cell within a preset receiving power threshold, such as a difference of 3 decibels (dB).

[0061] In substep 1603, the server screens the UEs in the second matched UE set, which have a difference between the TA of the primary cell of the multipath propagation UE within a preset timing advance threshold, to obtain a third matched UE set, according to the MR data corresponding to each UE in the second matched UE set.

[0062] Specifically, the server can screen the UEs in the second matched UE set, which have a difference between the TA of the primary cell of the determining starting UE within 1, to obtain the third matched UE set.

[0063] In substep 1604, the server determines the area feature corresponding to the multipath propagation UE, according to the MR data corresponding to each UE in the third matched UE set.

[0064] After determining the area feature corresponding to the multipath propagation UE, the server can further determine the proportion of the number of the multipath propagation UE in the users having the same area feature in the same cell, and then determine the area feature with a proportion of the number greater than a preset threshold as a multipath propagation area feature, and determine the area corresponding to the multipath propagation area feature as a multipath propagation area.

[0065] Specifically, the method provided in the embodiments of the present application can include: determining the proportion of the number of the multipath propagation UE in the UEs corresponding to each area feature in the same cell; and determining the area corresponding to the area feature as a multipath propagation area when the proportion of the number of the multipath propagation UE in the UEs corresponding to the area feature is greater than a preset proportion threshold.

[0066] In the embodiments of the present application, the server can further eliminate the multipath propagation UEs in the same area, and then analyze the coverage features of each area.

[0067] The server can obtain the minimization drive test (MDT) data, the measurement report (MR) data and the engineering parameter data uploaded by each user equipment (UE) in a region to be identified, and then calculates the angle of arrival (AOA) of each UE according to the MDT data and the engineering parameter data uploaded by each UE, to realize the simulation of AOA calculation based on the MDT data. Then, the proportion of the number of UEs corresponding to each AOA in each cell is determined according to the cell unique identifier (ECI) carried in the MDT data and the AOA, and a low-proportion AOA list is generated according to the AOA whose proportion of the number is less than a preset proportion threshold. The multi-path propagation UE is determined by matching the angle of arrival (MR-AOA) data carried in the MR data uploaded by each UE with the low-proportion AOA list. The region feature corresponding to the multi-path propagation UE is determined according to the MR data corresponding to the multi-path propagation UE, and finally the multi-path propagation region can be determined according to the region feature. The method provided in the embodiment of the application is based on the differential comparison of AOA data of MDT and MR data, and the multi-path signal proportion of the target region and the sampling feature number of high multi-path are output by strong correlation MR sampling point matching, so as to identify the uplink multi-path coverage scene information of the cell and solve the problem of insufficient accuracy of the traditional checking method.

[0068] In one embodiment, the embodiment of the application further provides a multi-path propagation region identification device to solve the problem that the existing identification scheme needs to rely on manual verification and determination, which is strongly related to the optimization experience and technical level of personnel, is not sensitive to network changes, lacks an automatic updating mechanism, and has insufficient identification accuracy. The specific structure diagram of the multi-path propagation region identification device is shown in Figure 3 The multi-path propagation region identification device includes a data acquisition unit 31, an angle of arrival calculation unit 32, an angle of arrival proportion determination unit 33, a low-proportion angle of arrival list generation unit 34, a multi-path propagation identification unit 35 and a multi-path propagation region determination unit 36.

[0069] The data acquisition unit 31 is configured to obtain the minimization drive test (MDT) data, the measurement report (MR) data and the engineering parameter data uploaded by each user equipment (UE) in a region to be identified.

[0070] The angle of arrival calculation unit 32 is configured to calculate the angle of arrival (AOA) of each UE according to the MDT data and the engineering parameter data uploaded by each UE.

[0071] The angle of arrival proportion determination unit 33 is configured to calculate the proportion of the number of UEs corresponding to each AOA in each cell according to the cell unique identifier (ECI) carried in the MDT data and the AOA.

[0072] The low-occupancy angle-of-arrival list generation unit 34 is configured to generate a low-occupancy angle-of-arrival (AOA) list according to the angle-of-arrival (AOA) that has an occupancy less than a preset occupancy threshold.

[0073] The multipath propagation identification unit 35 is configured to match the angle-of-arrival (AOA) data carried in the multipath radio (MR) data uploaded by each UE with the low-occupancy angle-of-arrival (AOA) list, and determine a multipath propagation UE according to a matching result.

[0074] The multipath propagation area determination unit 36 is configured to determine a region feature corresponding to the multipath propagation UE according to the MR data corresponding to the multipath propagation UE, and determine a multipath propagation area according to the region feature.

[0075] In an embodiment, the MTD data includes a cell unique identifier (ECI) corresponding to the UE, a signal reception power (RSRP), and latitude and longitude data corresponding to the UE; the engineering parameter data includes base station latitude and longitude data; and the angle-of-arrival calculation unit 32 is specifically configured to: establish a coordinate system with the base station latitude and longitude data in the engineering parameter data as an origin; determine a coordinate vector of the UE in the coordinate system according to the latitude and longitude data of the UE included in the MTD data; and determine an angle-of-arrival (AOA) of the UE according to the coordinate vector.

[0076] In an embodiment, the angle-of-arrival occupancy determination unit 33 is specifically configured to: determine a total number of UEs belonging to a same cell according to the cell unique identifier (ECI) carried in the MTD data; determine an angle-of-arrival (AOA) included in the same cell; determine a number of UEs corresponding to each of the angle-of-arrival (AOA) included in the same cell; and determine an occupancy of each of the angle-of-arrival (AOA) in the same cell according to the number of UEs corresponding to the angle-of-arrival (AOA) and the total number of UEs in the same cell.

[0077] In an embodiment, the multipath propagation identification unit 35 is specifically configured to: determine whether there is an angle-of-arrival (AOA) that is the same as the angle-of-arrival (AOA) data in the low-occupancy angle-of-arrival (AOA) list; and when the determination result is yes, determine that the angle-of-arrival (AOA) data matches the low-occupancy angle-of-arrival (AOA) list, and determine that the UE corresponding to the angle-of-arrival (AOA) is a multipath propagation UE.

[0078] In an embodiment, the MR data comprises: a primary cell ECI corresponding to the UE, a primary cell reference signal received power (RSRP), a primary cell timing advance (TA), a MR-AOA, a neighbor cell ECI, and a neighbor cell RSRP; the multipath propagation area determining unit 36 is specifically configured to: according to the MR data corresponding to other UEs belonging to the same cell as the multipath propagation UE, screen the UEs with the same primary cell ECI and neighbor cell ECI as the multipath propagation UE from the other UEs to obtain a first matched UE set; according to the MR data corresponding to each UE in the first matched UE set, screen the UEs with the primary cell RSRP and neighbor cell RSRP difference within a preset received power threshold range from the multipath propagation UE in the first matched UE set to obtain a second matched UE set; according to the MR data corresponding to each UE in the second matched UE set, screen the UEs with the primary cell TA difference within a preset timing advance threshold range from the multipath propagation UE in the second matched UE set to obtain a third matched UE set; and determine the area feature corresponding to the multipath propagation UE according to the MR data corresponding to each UE in the third matched UE set.

[0079] In an embodiment, the multipath propagation area determining unit 36 is specifically configured to: determine the proportion of the multipath propagation UE in the UEs corresponding to each area feature belonging to the same cell; and when the proportion of the multipath propagation UE in the UEs corresponding to the area feature is greater than a preset proportion threshold, determine the area corresponding to the area feature as a multipath propagation area.

[0080] The device provided in the embodiment of the application can be used for identifying a multipath propagation area. The server can obtain the minimization drive test (MDT) data, measurement report (MR) data and engineering parameter data uploaded by each user equipment (UE) in the area to be identified, and then calculate the angle of arrival (AOA) of each UE according to the MDT data and the engineering parameter data uploaded by each UE, so as to realize the simulation of AOA calculation based on MDT data. Then, the server can determine the proportion of the number of UEs corresponding to each AOA in each cell according to the cell unique identifier (ECI) carried in the MDT data and the AOA, and generate a low-proportion AOA list according to the AOA whose proportion of the number is less than a preset proportion threshold. The server can match the angle of arrival MR-AOA data carried in the MR data uploaded by each UE with the low-proportion AOA list, and determine the multipath propagation UE according to the matching result. The server can determine the area feature corresponding to the multipath propagation UE according to the MR data corresponding to the multipath propagation UE, and finally determine the multipath propagation area according to the area feature. The method provided in the embodiment of the application can be used for differentiating and comparing the AOA data based on MDT and MR data, matching the strong correlation MR sampling points, counting the proportion of multipath signals in the target area and the number of sampling feature numbers of high multipath, and then identifying the uplink multipath coverage scene information of the cell, so as to solve the problem of insufficient accuracy of the traditional checking method.

[0081] Figure 4 is a structural schematic diagram of an electronic device according to an embodiment of the application. Please refer to Figure 4 At the hardware level, the electronic device includes a processor, and optionally further includes an internal bus, a network interface and a memory. The memory can include an internal memory such as a random-access memory (RAM), and can further include a non-volatile memory such as at least one disk memory. Of course, the electronic device can further include other hardware required by a business.

[0082] The processor, the network interface and the memory can be connected to each other through the internal bus, which can be an industry standard architecture (ISA) bus, a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus and a control bus. For the convenience of representation, Figure 4 In the figure, only one bidirectional arrow is used to represent the bus, but it does not mean that there is only one bus or only one type of bus.

[0083] The memory is configured to store a program. Specifically, the program can include program code including computer operation instructions. The memory can include an internal memory and a non-volatile memory, and provide instructions and data for the processor.

[0084] The processor reads the corresponding computer program from the non-volatile memory into the internal memory and then runs, and forms the multipath propagation area identification device at a logical level. The processor executes the program stored in the memory, and is specifically configured to perform the following operations:

[0085] Obtain minimization of drive test (MTD) data, measurement report (MR) data and engineering parameter data uploaded by each user equipment (UE) in a to-be-identified area; calculate an angle of arrival (AOA) of each UE according to the MTD data and the engineering parameter data uploaded by each UE; calculate a proportion of a number of UEs corresponding to each AOA in each cell according to a cell unique identity (ECI) carried in the MTD data and the AOA; generate a low-proportion AOA list according to an AOA whose proportion is less than a preset proportion threshold; match MR-AOA data carried in the MR data uploaded by each UE with the low-proportion AOA list, and determine a multipath propagation UE according to a matching result; determine an area feature corresponding to the multipath propagation UE according to MR data corresponding to the multipath propagation UE, and determine a multipath propagation area according to the area feature.

[0086] The above as described in the present application Figure 4The method executed by the multipath propagation area identification electronic device disclosed by the embodiment shown can be applied in a processor or implemented by the processor. The processor can be an integrated circuit chip with signal processing capability. In the implementation process, each step of the above method can be completed by integrated logic circuit of hardware in the processor or instruction in the form of software. The processor mentioned above can be a general processor, including a central processing unit (CPU), a network processor (NP), etc.; can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component. Each method, step and logic block disclosed in the embodiment of the present application can be implemented or executed. The general processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in combination with the embodiment of the present application can be directly embodied as a hardware decoding processor for execution, or executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a random access memory, a flash memory, a read only memory, a programmable read only memory, an electrically erasable programmable memory, a register, etc. The storage medium in the art. The storage medium is located in the memory, and the processor reads the information in the memory, and combines the hardware to complete the steps of the above method.

[0087] Of course, in addition to the software implementation, the electronic device of the present application does not exclude other implementation manners, such as logic device or combination of software and hardware, etc. That is, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or logic device.

[0088] The embodiment of the present application also proposes a computer readable storage medium, the computer readable storage medium stores one or more programs, the one or more programs include instructions, when the instructions are executed by the portable electronic device including a plurality of application programs, the portable electronic device can execute Figure 1 The method of the embodiment shown, and specifically for executing the following operations:

[0089] Obtaining minimization of driving test (MTD) data, measurement report (MR) data and engineering parameter data uploaded by user equipment (UE) in a to-be-identified area; calculating an angle of arrival (AOA) of each UE according to the MTD data and the engineering parameter data uploaded by each UE; calculating a proportion of the number of UEs corresponding to each AOA in each cell according to the cell unique identity (ECI) carried in the MTD data and the AOA; generating a low-proportion AOA list according to the AOA whose proportion is less than a preset proportion threshold; matching the angle of arrival MR-AOA data carried in the MR data uploaded by each UE with the low-proportion AOA list, and determining a multipath propagation UE according to a matching result; determining a region feature corresponding to the multipath propagation UE according to the MR data corresponding to the multipath propagation UE, and determining a multipath propagation region according to the region feature.

[0090] Those skilled in the art will understand that embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage, etc.) containing computer usable program code.

[0091] The present application is described in reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing apparatus to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing apparatus produce an apparatus that implements the functions specified in the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 an apparatus with the functions specified in one or more flows and / or blocks.

[0092] These computer program instructions can also be stored in a computer-readable memory that can direct the computer or other programmable data processing apparatus to work in a specific manner, so that the instructions stored in the computer-readable memory produce a product including instruction apparatus, which implements the functions specified in the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 an apparatus with the functions specified in one or more flows and / or blocks.

[0093] These computer program instructions can also be loaded into a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 Figure 1

[0094] In one typical configuration, the computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0095] The memory can include non-persistent memory and / or volatile memory, such as random access memory (RAM) about which the processor can execute instructions. The memory can also include non-volatile memory, such as read only memory (ROM), electrically programmable read only memory (EPROM), electrically erasable programmable read only memory (EEPROM), programmable read only memory (PROM), erasable programmable read only memory (EPROM), flash memory, or a combination of non-volatile memories in different types. The memory is an example of computer readable storage media.

[0096] Computer readable media includes permanent and non-permanent, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory (ROM), electrically programmable read only memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital versatile disc (DVD), or other optical storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible to computing devices. According to the definition herein, computer readable media does not include transitory media, such as modulated data signals and carrier waves.

[0097] It should also be noted that the terms "comprising", "comprises", "including", "includes" or any other variation thereof are intended to cover a non-exclusive inclusion, such that a process, method, article or apparatus that comprises a list of elements does not include only those elements recited, but can also include other elements not expressly listed or inherent to such process, method, article or apparatus. Without further limitation, an element preceded by "comprises a" does not, without more constraints, foreclose the existence of additional identical elements in the process, method, article or apparatus that includes the recited element.

[0098] ​​Those skilled in the art will appreciate that embodiments of the present application can be devised for a method, a system, or a computer program product. Accordingly, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application can take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage devices, etc.) embodying computer-readable program code thereon for use by or in connection with an instruction execution system. For the purposes of this description, a computer-usable or computer readable storage medium can be any apparatus that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.

[0099] The above descriptions are only some embodiments of the present application and are not intended to limit the present application. Various modifications and changes can be made by those skilled in the art to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the scope of claims of the present application.

Claims

1. A multipath propagation region identification method characterized by comprising: The method comprises the following steps: Obtaining the minimization road test (MDT) data, the measurement report (MR) data and the engineering parameter data uploaded by each user terminal (UE) in a to-be-identified area; Calculating the angle of arrival (AOA) of each UE according to the MDT data and the engineering parameter data uploaded by each UE; Calculating the proportion of the number of UEs corresponding to each AOA in each cell according to the cell unique identifier (ECI) carried in the MDT data and the AOA; Generating a low-proportion AOA list according to the AOA whose proportion of the number of UEs is less than a preset proportion threshold; Matching the AOA MR-AOA data carried in the MR data uploaded by each UE with the low-proportion AOA list, and determining the multipath propagation UE according to the matching result; Determining the area feature corresponding to the multipath propagation UE according to the MR data corresponding to the multipath propagation UE, and determining the multipath propagation area according to the area feature.

2. The method of claim 1, wherein, The MDT data comprises the ECI, the received signal power (RSRP) and the latitude and longitude data of the UE; The engineering parameter data comprises the latitude and longitude data of the base station; Then, the AOA of each UE is calculated according to the MDT data and the engineering parameter data uploaded by each UE, specifically comprising the following steps: Establishing a coordinate system with the latitude and longitude data of the base station as the origin point according to the engineering parameter data; Determining the coordinate vector of the UE in the coordinate system according to the latitude and longitude data of the UE contained in the MDT data; Determining the AOA of the UE according to the coordinate vector.

3. The method of claim 1, wherein, The proportion of the number of UEs corresponding to each AOA in each cell is calculated according to the ECI carried in the MDT data and the AOA, specifically comprising the following steps: Determining the total number of UEs belonging to the same cell according to the ECI carried in the MDT data; Determining the AOA contained in the same cell; Determining the number of UEs corresponding to each AOA contained in the same cell; Determining the proportion of the number of UEs corresponding to each AOA in the same cell according to the number of UEs corresponding to each AOA and the total number of UEs in the same cell.

4. The method of claim 1, wherein, The multipath propagation UE is determined according to the matching result of matching the AOA MR-AOA data carried in the MR data uploaded by each UE with the low-proportion AOA list, specifically comprising the following steps: Determining whether there is an AOA same as the AOA MR-AOA data in the low-proportion AOA list; When the determination result is yes, it is determined that the AOA MR-AOA data matches the low-proportion AOA list, and the UE corresponding to the AOA MR-AOA is determined as the multipath propagation UE.

5. The method of claim 1, wherein, The MR data comprises the ECI, the RSRP, the TA, the AOA MR-AOA, the ECI and the RSRP of the UE corresponding to the primary cell. Then, determining the regional features corresponding to the multipath propagation UE according to the MR data corresponding to the multipath propagation UE specifically includes: According to MR data corresponding to other UEs in the same cell as the multipath propagation UE, UEs having the same primary cell ECI and neighboring cell ECI as those corresponding to the multipath propagation UE are selected from the other UEs to obtain a first matching UE set; According to the MR data corresponding to each UE in the first matching UE set, UEs whose difference between the primary cell RSRP and the neighboring cell RSRP of the multipath propagation UE is within a preset receive power threshold range are selected from the first matching UE set to obtain a second matching UE set; According to the MR data corresponding to each UE in the second matching UE set, UEs whose TA difference with the primary cell of the multipath propagation UE is within a preset timing advance threshold range are screened in the second matching UE set to obtain a third matching UE set; The regional feature corresponding to the multipath propagation UE is determined according to the MR data corresponding to each UE in the third matching UE set.

6. The method of claim 5, wherein, The determining of the multipath propagation area according to the regional characteristics specifically includes: Determine a proportion of the multipath propagation UEs among the UEs corresponding to the regional characteristics of the same cell; When the proportion of multipath propagation UEs in the UEs corresponding to the regional characteristics is greater than a preset proportion threshold, it is determined that the area corresponding to the regional characteristics is a multipath propagation area.

7. A multipath propagation region identifying apparatus characterized by comprising: include: A data acquisition unit, configured to acquire Minimization of Drive Test (MDT) data, Measurement Report (MR) data, and engineering parameter data uploaded by each user terminal (UE) in the area to be identified; An angle of arrival calculation unit, configured to calculate the angle of arrival AOA of each UE according to the MDT data and the engineering parameter data uploaded by each UE; an angle of arrival ratio determination unit, configured to calculate a ratio of the number of UEs corresponding to each angle of arrival AOA in each cell based on the cell unique identifier ECI and the angle of arrival AOA carried in the MDT data; A low-proportion arrival angle list generating unit is configured to generate a low-proportion arrival angle AOA list according to the arrival angle AOA whose number proportion is less than a preset proportion threshold; a multipath propagation identification unit, configured to match the arrival angle MR-AOA data carried in the MR data uploaded by each UE with the low-proportion arrival angle AOA list, and determine the multipath propagation UE according to the matching result; The multipath propagation area determining unit is configured to determine the area characteristics corresponding to the multipath propagation UE according to the MR data corresponding to the multipath propagation UE, and determine the multipath propagation area according to the area characteristics.

8. The multipath propagation region identifying apparatus according to claim 7, wherein The MDT data includes: a cell unique identifier ECI corresponding to the UE, a signal received power RSRP, and latitude and longitude data corresponding to the UE; The engineering parameter data includes: base station longitude and latitude data; The arrival angle calculation unit is specifically used to: Establishing a coordinate system based on the base station longitude and latitude data in the engineering parameter data as the origin; Determining a coordinate vector of the UE in the coordinate system according to the UE latitude and longitude data included in the MDT data; According to the coordinate vector, an angle of arrival (AOA) of the UE is determined. 9.A multi-path propagation area identification electronic device, comprising: a processor; and a memory arranged to store computer executable instructions that, when executed, cause the processor to perform the following operations: obtain minimization of drive test (MDT) data, measurement report (MR) data and engineering parameter data uploaded by each user equipment (UE) in an area to be identified; calculate an angle of arrival (AOA) of each UE according to the MDT data and the engineering parameter data uploaded by each UE; calculate a proportion of the number of UEs corresponding to each AOA in each cell according to a cell unique identity (ECI) carried in the MDT data and the AOA; generate a low-proportion AOA list according to the AOA whose proportion is less than a preset proportion threshold; match angle of arrival (MR-AOA) data carried in the MR data uploaded by each UE with the low-proportion AOA list, and determine multi-path propagation UEs according to a matching result; determine an area feature corresponding to the multi-path propagation UEs according to MR data corresponding to the multi-path propagation UEs, and determine a multi-path propagation area according to the area feature. 10.A computer-readable storage medium storing one or more programs, which, when executed by an electronic device including multiple applications, cause the electronic device to perform the method of any of claims 1-6.

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