Cell scenario identification method and apparatus, network device, and program product

Abstract

The application relates to the technical field of communication, and provides a cell scene recognition method and device, network equipment and program product. The method comprises the following steps: obtaining target MR data corresponding to each of at least one to-be-recognized cell; for each to-be-recognized cell, the target MR data comprises target synchronization signal block (SSB) beam detection data and a target uplink arrival angle corresponding to each mobile terminal in the to-be-recognized cell; determining a downlink signal emission angle corresponding to each mobile terminal in the to-be-recognized cell based on the target SSB beam detection data of the to-be-recognized cell; determining a target mobile terminal proportion corresponding to the to-be-recognized cell based on the downlink signal emission angle corresponding to each mobile terminal and the target uplink arrival angle; and determining a scene recognition result of each to-be-recognized cell based on each target mobile terminal proportion. The cell scene recognition method and device, network equipment and program product provided by the application can improve the comprehensiveness and accuracy of scene recognition.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of communication, in particular to a cell scene identification method and device, network equipment and program product. BACKGROUND

[0002] At present, in the process of wireless network optimization, various coverage scenes are involved, such as highway, residential area, high-rise building and urban road coverage scenes, and the mobile state of the mobile terminal of the user is different in different coverage scenes. When performing wireless network optimization, it is often necessary to perform targeted parameter or coverage optimization for different cell coverage scenes. Therefore, how to identify the cell coverage scene is a problem to be solved at present.

[0003] In the prior art, on the one hand, the user flow scene is identified according to the actual topography, building features, traffic flow and other scene attributes of the to-be-identified cell, combined with artificial experience, by means of electronic map or field investigation. However, when identifying the cell scene according to artificial experience, the identification result is more subjective, resulting in low accuracy of cell coverage scene identification. On the other hand, the mobility of the terminal in the cell coverage scene is determined according to the traffic data such as the number of handovers and the proportion of handovers, and then the cell scene is identified. However, the scene identification according to the traffic data only stays at the level of coverage edge handover, and the mobility of the terminal in the cell coverage scene cannot be determined, resulting in a more one-sided identification result, and thus the accuracy of the cell coverage scene identification is low. SUMMARY

[0004] The embodiments of the present application provide a cell scene identification method, device, network equipment and program product, to solve the technical problem of low accuracy of cell coverage scene identification.

[0005] In a first aspect, the embodiments of the present application provide a cell scene identification method, comprising:

[0006] Obtaining target MR data corresponding to each of at least one to-be-identified cell, for each to-be-identified cell, the target MR data includes target synchronization signal block SSB beam detection data and target uplink arrival angle corresponding to each of at least one mobile terminal in the to-be-identified cell;

[0007] Determining the downlink signal emission angle corresponding to each of the mobile terminals in the to-be-identified cell based on the target SSB beam detection data of the to-be-identified cell;

[0008] Determining the target mobile terminal proportion corresponding to the to-be-identified cell based on the downlink signal emission angle corresponding to each of the mobile terminals and the target uplink arrival angle;

[0009] Determine a scene recognition result of each of the to-be-recognized cells based on the target mobile terminal proportion of each of the target mobile terminals.

[0010] In one embodiment, the cell scene recognition method provided in the embodiments of the present application comprises:

[0011] Obtain an antenna azimuth angle of the to-be-recognized cell and a beam quantity of at least one SSB beam;

[0012] Determine a beam initial vector of each of the SSB beams based on the antenna azimuth angle and the beam quantity;

[0013] Determine a downlink signal transmission angle corresponding to each of the mobile terminals in the to-be-recognized cell based on the beam initial vector of each of the SSB beams and the target SSB beam detection data.

[0014] In one embodiment, the cell scene recognition method provided in the embodiments of the present application comprises:

[0015] Obtain a horizontal width of the to-be-recognized cell;

[0016] Determine a beam width corresponding to each of the SSB beams based on the horizontal width and the beam quantity;

[0017] Determine a beam azimuth angle of each of the SSB beams based on the antenna azimuth angle and the beam width corresponding to each of the SSB beams;

[0018] Determine a beam initial vector of each of the SSB beams based on the beam azimuth angle of each of the SSB beams.

[0019] In one embodiment, the cell scene recognition method provided in the embodiments of the present application comprises that the target SSB beam detection data comprises a reference signal received power (RSRP) sub-intensity corresponding to each of the SSB beams.

[0020] The determination of the downlink signal transmission angle corresponding to each of the mobile terminals in the to-be-recognized cell based on the beam initial vector of each of the SSB beams and the target SSB beam detection data comprises:

[0021] For each of the SSB beams, determine a beam weight vector of the SSB beam based on the beam initial vector of the SSB beam and the RSRP sub-intensity;

[0022] Determine a beam sum vector corresponding to each of the mobile terminals in the to-be-identified cell based on a sum of beam weight vectors of each of the SSB beams, and determine an azimuth angle corresponding to the beam sum vector as a downlink signal transmission angle.

[0023] In one embodiment, according to the cell scene identification method provided in the embodiments of the present application, the target mobile terminal proportion corresponding to the to-be-identified cell is determined based on the downlink signal transmission angle corresponding to each of the mobile terminals and the target uplink arrival angle, and the method comprises the following steps:

[0024] Obtain idle time MR data corresponding to each of the mobile terminals.

[0025] Determine an idle time difference value corresponding to each of the mobile terminals based on the idle time MR data.

[0026] Determine an uplink-downlink difference value based on the downlink signal transmission angle corresponding to each of the mobile terminals and the target uplink arrival angle.

[0027] Determine a target mobile terminal based on the idle time difference value corresponding to each of the mobile terminals and the uplink-downlink difference value.

[0028] Determine the target mobile terminal proportion corresponding to the to-be-identified cell based on a ratio of a first number corresponding to all target mobile terminals in the to-be-identified cell to a second number corresponding to all mobile terminals.

[0029] In one embodiment, according to the cell scene identification method provided in the embodiments of the present application, the target mobile terminal is determined based on the idle time difference value corresponding to each of the mobile terminals and the uplink-downlink difference value, and the method comprises the following steps:

[0030] For each of the mobile terminals, if the uplink-downlink difference value of the mobile terminal is greater than or equal to a first preset threshold value, and the uplink-downlink difference value is greater than or equal to a sum of the idle time difference value and a second preset threshold value, the mobile terminal is determined as the target mobile terminal.

[0031] In one embodiment, according to the cell scene identification method provided in the embodiments of the present application, the target MR data corresponding to each of the at least one to-be-identified cell is obtained, and the method comprises the following steps:

[0032] Obtain MR data corresponding to each of the to-be-identified cells; for each of the to-be-identified cells, the MR data comprises SSB beam detection data corresponding to each of at least one mobile terminal in the to-be-identified cell, and the SSB beam detection data comprises an RSRP intensity.

[0033] If the RSRP intensity is greater than a third preset threshold value, the MR data corresponding to the RSRP intensity is determined as the target MR data.

[0034] In a second aspect, an embodiment of the present application provides a cell scene recognition device, comprising:

[0035] An acquisition module is configured to acquire target MR data corresponding to each of at least one to-be-recognized cell, wherein for each to-be-recognized cell, the target MR data comprises target synchronization signal block (SSB) beam detection data and a target uplink angle of arrival corresponding to each mobile terminal in the to-be-recognized cell.

[0036] A first determination module is configured to determine a downlink signal emission angle corresponding to each mobile terminal in the to-be-recognized cell based on the target SSB beam detection data of the to-be-recognized cell.

[0037] A second determination module is configured to determine a target mobile terminal proportion corresponding to the to-be-recognized cell based on the downlink signal emission angle corresponding to each mobile terminal and the target uplink angle of arrival.

[0038] A third determination module is configured to determine a scene recognition result of each to-be-recognized cell based on each target mobile terminal proportion.

[0039] In a third aspect, an embodiment of the present application provides a network device, comprising a memory, a transceiver, and a processor.

[0040] The memory is configured to store a computer program; the transceiver is configured to transceive data under control of the processor; and the processor is configured to read the computer program in the memory and perform steps of the cell scene recognition method in the first aspect.

[0041] In a fourth aspect, an embodiment of the present application provides a computer program product, comprising a computer program, which, when executed by a processor, implements steps of the cell scene recognition method in the first aspect.

[0042] The cell scene recognition method, device, network device, and program product provided in the embodiments of the present application can, after acquiring target MR data, simulate a downlink signal emission angle of each mobile terminal through target SSB beam detection data of each to-be-recognized cell in the target MR data, and differentially compare the downlink signal emission angle with a target uplink angle of arrival, determine a target mobile terminal proportion of a target mobile terminal with strong mobility, and quantitatively and objectively recognize scenes of each to-be-recognized cell according to the target mobile terminal proportion, thereby improving comprehensiveness and accuracy of scene recognition. In addition, the scene recognition of the to-be-recognized cell can be performed only according to the target MR data, thereby saving recognition cost and improving recognition efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the application or the prior art, the accompanying drawings needed to be used in the embodiments or prior art description will be briefly introduced as follows. Obviously, the accompanying drawings in the following description are some embodiments of the application, and other drawings can be obtained by those skilled in the art without creative effort on the basis of these drawings.

[0044] Figure 1 is one of the flowcharts of the cell scenario identification method provided by the embodiments of the application;

[0045] Figure 2 is an example schematic diagram of SSB beam provided by the embodiments of the application;

[0046] Figure 3 is an example schematic diagram of target uplink angle of arrival provided by the embodiments of the application;

[0047] Figure 4 is another flowchart of the cell scenario identification method provided by the embodiments of the application;

[0048] Figure 5 is an example schematic diagram of beam weight vector provided by the embodiments of the application;

[0049] Figure 6 is an example schematic diagram of beam and vector provided by the embodiments of the application;

[0050] Figure 7 is a structural schematic diagram of the cell scenario identification apparatus provided by the embodiments of the application;

[0051] Figure 8 is a structural schematic diagram of the network device provided by the embodiments of the application. DETAILED DESCRIPTION

[0052] In order to make the objects, technical solutions and advantages of the application clearer, the technical solutions in the application will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the application. Obviously, the described embodiments are some embodiments of the application, but not all the embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative effort belong to the protection scope of the application.

[0053] In order to solve the technical problem of low recognition accuracy of cell coverage scenario in the prior art, Figure 1 is one of the flowcharts of the cell scenario identification method provided by the embodiments of the application, as shown in Figure 1 The embodiments of the application provide a cell scenario identification method, which comprises the following steps.

[0054] In step 110, target MR (Measurement Report) data corresponding to each of the at least one to-be-identified cell is acquired, and for each of the at least one to-be-identified cell, the target MR data includes target SSB (Synchronized Signal Block) beam detection data and target AOA (Angle of Arrival) corresponding to each of at least one mobile terminal in the to-be-identified cell.

[0055] It should be noted that the target MR (Measurement Report) data is used for network evaluation and optimization of wireless environment quality, and the target MR data includes uplink signal information and downlink signal information, wherein the downlink signal information is measured and collected by a mobile terminal and reported to a network device through MR (Measurement Report) signaling of an Um interface, and the uplink signal information is measured and collected by a BTS (Base Transceiver Station) of the network device, and the BTS reports the uplink and downlink measurement information to a BSC (Base Station Controller) through MR signaling after summarizing the uplink and downlink measurement information.

[0056] After the target MR data corresponding to each of the at least one to-be-identified cell is acquired, key field information is extracted from the target MR data to reduce the data amount in the target MR data. The key field information can include a home ECI (E-UTRAN Cell Identifier), target SSB (Synchronized Signal Block) beam detection data, and target AOA (Angle of Arrival). Wherein:

[0057] 1) The home ECI is used to locate a cell where a mobile terminal is located.

[0058] 2) The target SSB beam detection data is the downlink signal information measured and collected by the mobile terminal when accessing the corresponding cell, which is configured and sent by the cell network device, so as to facilitate the mobile terminal to perform cell search, beam measurement, beam selection and beam recovery operations. The number of SSB beams is configured by the cell network device according to time slot matching and scenario beam, and each SSB beam corresponds to a unique number (SSB index). The target SSB beam detection data can include RSRP (Reference Signal Receiving Power, reference signal receiving power) strength and RSRP sub-strength corresponding to each SSB beam. The RSRP sub-strength corresponding to each SSB beam is configured by the cell network device, and the RSRP strength is determined based on each RSRP sub-strength. The RSRP strength can be the arithmetic mean or weighted average of each RSRP sub-strength, and the embodiments of the present application do not limit this. The SSB beam can be used to improve signal coverage area and network throughput.

[0059] For example, 8 beams are taken as an example, Figure 2 is an example of sending SSB beams provided by the embodiments of the present application, as Figure 2 shown, the cell network device can configure the number of SSB beams to be 8 according to time slot matching and scenario beam, and configure the RSRP sub-strength corresponding to each SSB beam. The RSRP sub-strength corresponding to SSB beam B0 measured and received by the cell network device or the mobile terminal can be -100dBm, the RSRP sub-strength corresponding to SSB beam B1 can be -95dBm, the RSRP sub-strength corresponding to SSB beam B2 can be -80dBm, the RSRP sub-strength corresponding to SSB beam B3 can be -90dBm, the RSRP sub-strength corresponding to SSB beam B4 can be -100dBm, the RSRP sub-strength corresponding to SSB beam B5 can be -105dBm, the RSRP sub-strength corresponding to SSB beam B6 can be -105dBm, and the RSRP sub-strength corresponding to SSB beam B7 is very weak, and the mobile terminal does not detect the RSRP sub-strength corresponding to SSB beam B7. It should be noted that after the cell network device configures and sends the RSRP sub-strength corresponding to each SSB beam, the distance between the cell network device and the mobile terminal, buildings, terrain and other interference factors in the transmission environment will all affect the transmission and reception of each SSB beam, resulting in that the RSRP sub-strength corresponding to each SSB beam received and measured by the mobile terminal may be different from the RSRP sub-strength corresponding to each SSB beam configured and sent by the cell network device. The influence of the above interference factors is ignored in the above example.

[0060] 3) Figure 3is an example schematic diagram of a target uplink arrival angle provided by an embodiment of the present application, as shown in Figure 3 The target uplink arrival angle is the angle between the arrival direction of the mobile terminal's transmission signal detected by the cell network device and the horizontal direction, and the target uplink arrival angle belongs to the uplink signal information detected by the cell network device.

[0061] In addition, the key field information also includes a sampling point ID (Identity document, identity), which is a unique identifier of the mobile terminal. For example, taking the number of SSB beams as 8, the target MR data obtained is shown in Table 1.

[0062] Table 1 Target MR data

[0063]

[0064] Further, the method comprises:

[0065] obtaining MR data corresponding to each of the to-be-identified cells; for each of the to-be-identified cells, the MR data includes SSB beam detection data corresponding to each of the at least one mobile terminal in the to-be-identified cell, and the SSB beam detection data includes RSRP intensity;

[0066] In the case where the RSRP intensity is greater than a third preset threshold, the MR data corresponding to the RSRP intensity is determined as the target MR data.

[0067] Specifically, after obtaining the MR data corresponding to each of the to-be-identified cells, the RSRP intensity corresponding to each mobile terminal in the MR data is compared with the third preset threshold. For each mobile terminal, if the RSRP intensity is less than or equal to the third preset threshold, the MR data corresponding to the mobile terminal is removed; if the RSRP intensity is greater than the third preset threshold, the MR data corresponding to the mobile terminal is determined as the target MR data, ensuring that the RSRP intensity of each mobile terminal is large, and further ensuring the accuracy of the simulated downlink signal transmission angle.

[0068] Step 120, based on the target SSB beam detection data of the to-be-identified cell, determining the downlink signal transmission angle corresponding to each of the mobile terminals in the to-be-identified cell.

[0069] Specifically, Figure 4 is a second flowchart of a cell scene recognition method provided by an embodiment of the present application, as shown in Figure 4The target MR data is determined after the MR data is preprocessed in the above step, and for each to-be-identified cell, the downlink signal transmission angle of each mobile terminal is simulated according to the target SSB beam detection data corresponding to each mobile terminal in the target MR data, that is, the downlink signal transmission angle corresponding to each mobile terminal is simulated according to the RSRP sub-intensity of each SSB beam.

[0070] Further, the downlink signal transmission angle corresponding to each mobile terminal in the to-be-identified cell is determined based on the target SSB beam detection data of the to-be-identified cell, and the method comprises the steps of:

[0071] The horizontal width of the to-be-identified cell is obtained;

[0072] Based on the horizontal width and the number of beams, the beam width corresponding to each SSB beam is determined;

[0073] Based on the horizontal width and the number of beams, the beam width corresponding to each SSB beam is determined;

[0074] Based on the horizontal width and the number of beams, the beam width corresponding to each SSB beam is determined;

[0075] Further, the downlink signal transmission angle corresponding to each mobile terminal in the to-be-identified cell is determined based on the target SSB beam detection data of the to-be-identified cell, and the method comprises the steps of:

[0076] The horizontal width of the to-be-identified cell is obtained;

[0077] Based on the horizontal width and the number of beams, the beam width corresponding to each SSB beam is determined;

[0078] Based on the horizontal width and the number of beams, the beam width corresponding to each SSB beam is determined;

[0079] determine a beam initial vector of each of the SSB beams based on the beam azimuth angle of each of the SSB beams.

[0080] Specifically, before determining the beam initial vector, a horizontal width of the to-be-identified cell can be acquired, and based on the horizontal width and the number of beams, a beam width corresponding to each SSB beam can be determined according to a quotient of the horizontal width and the number of beams. The beam width can be understood as a central angle of a sector with the cell network device as the origin. After determining the beam width, a beam interval of each SSB beam is further determined based on the antenna azimuth angle and the beam width, and then a midpoint of the beam interval corresponding to the azimuth angle is determined as the beam azimuth angle corresponding to each SSB beam. For each SSB beam, the vector direction of the beam initial vector can be determined based on the beam azimuth angle, the vector length of the beam initial vector can be determined based on the coverage range of the to-be-identified cell, and the beam initial vector can be determined based on the vector direction and the vector length.

[0081] For example, the azimuth angle corresponding to the north direction is 0 degrees, the azimuth angle increases in the counterclockwise direction, the number of SSB beams is 8, the antenna azimuth angle is 0°, and the horizontal width is 105°. Based on the horizontal width and the number of beams, it can be determined that the beam width of each SSB beam in SSB beam B0-SSB beam B2 and SSB beam B5-SSB beam B7 is 13 degrees, the beam width corresponding to SSB beam B3 and SSB beam B4 is 13.5 degrees respectively, and there is an overlap between two adjacent SSB beams. Since the antenna azimuth angle is 0°, the parameters of each SSB beam can be determined as shown in Table 2, wherein the beam azimuth angle is the average of the upper limit value and the lower limit value of the beam interval.

[0082] Table 2: Parameters of each SSB beam

[0083] Home ECI Beam number Beam width Beam interval Beam azimuth A B0 13° 307.5°-320.5° 314° A B1 13° 320.5°-333.5° 327° A B2 13° 333.5°-346.5° 340° A B3 13.5° 346.5°-0° 353° A B4 13.5° 0°-13.5° 6° A B5 13° 13.5°-26.5° 19° A B6 13° 26.5°-39.5° 32° A B7 13° 39.5°-52.5° 45°

[0084] Further, the target SSB beam detection data includes a reference signal received power (RSRP) sub-intensity corresponding to each of the SSB beams.

[0085] The determination of the downlink signal transmission angle corresponding to each of the mobile terminals in the to-be-identified cell based on the beam initial vector of each of the SSB beams and the target SSB beam detection data includes:

[0086] For each of the SSB beams, a beam weight vector of the SSB beam is determined based on the beam initial vector of the SSB beam and the RSRP sub-intensity.

[0087] The beam sum vector corresponding to each of the mobile terminals in the to-be-identified cell is determined based on a sum of the beam weight vectors of each of the SSB beams, and an azimuth angle corresponding to the beam sum vector is determined as a downlink signal transmission angle.

[0088] Specifically, after determining the beam initial vector of each SSB beam, the beam initial vector of each SSB beam is multiplied by the RSRP sub-intensity to obtain the beam weight vector of the SSB beam. The vector direction of the beam weight vector is the same as that of the beam initial vector, but the vector length of the beam weight vector is different from that of the beam initial vector. After determining each beam weight vector, vector addition is performed on each beam weight vector to obtain the beam sum vector corresponding to the mobile terminal. The azimuth angle of the beam sum vector can be determined according to the vector direction of the beam sum vector, and the azimuth angle is determined as the downlink signal transmission angle of the mobile terminal.

[0089] For example, taking the target MR data corresponding to the sampling point ID 1 in Table 1 as an example, after determining the beam initial vector corresponding to each of the 8 SSB beams, the beam initial vector of each SSB beam is multiplied by the RSRP sub-intensity to obtain 8 beam weight vectors in theory. Since the mobile terminal does not detect the RSRP sub-intensity of SSB beam B7 in the target MR data corresponding to the sampling point ID 1, 7 beam weight vectors are actually obtained. Figure 5 is an example schematic diagram of the beam weight vector provided by the embodiment of the present application. As shown in Figure 5 With the difference of the RSRP sub-intensity, the vector length of the 7 beam weight vectors changes, wherein R represents the radius of the cell coverage. After determining the 7 beam weight vectors, vector addition is performed on the 7 beam weight vectors to determine the final beam sum vector. Figure 6 is an example schematic diagram of the beam sum vector provided by the embodiment of the present application. As shown in Figure 6 After determining the beam sum vector, the azimuth angle of the beam sum vector is determined to be 350° based on the vector direction of the beam sum vector, and the downlink signal transmission angle corresponding to the mobile terminal is further determined to be 350°.

[0090] Step 130, based on the downlink signal transmission angle corresponding to each of the mobile terminals and the target uplink arrival angle, determining a target mobile terminal proportion corresponding to the to-be-identified cell.

[0091] Specifically, as Figure 4As shown, after determining the downlink signal transmission angle of the mobile terminal and the target uplink arrival angle, the uplink-downlink difference value can be determined according to the difference between the downlink signal transmission angle and the target uplink arrival angle, and the target mobile terminal proportion can be determined according to the uplink-downlink difference value, so as to quantitatively and intuitively identify the scene according to the target mobile terminal proportion. Compared with manual experience for scene identification, the accuracy of scene identification is improved.

[0092] Further, the target mobile terminal proportion corresponding to the to-be-identified cell is determined based on the downlink signal transmission angle and the target uplink arrival angle corresponding to each mobile terminal, including:

[0093] Idle time MR data corresponding to each mobile terminal is obtained;

[0094] Idle time difference values corresponding to each mobile terminal are determined based on the idle time MR data;

[0095] Uplink-downlink difference values are determined based on the downlink signal transmission angle and the target uplink arrival angle corresponding to each mobile terminal;

[0096] Target mobile terminals are determined based on the idle time difference values and the uplink-downlink difference values corresponding to each mobile terminal;

[0097] The target mobile terminal proportion corresponding to the to-be-identified cell is determined based on the ratio of the first number corresponding to all target mobile terminals in the to-be-identified cell to the second number corresponding to all mobile terminals.

[0098] Specifically, after determining the downlink signal transmission angle and the target uplink arrival angle corresponding to each mobile terminal, the uplink-downlink difference value corresponding to the mobile terminal can be determined according to the difference between the downlink signal transmission angle and the target uplink arrival angle. In addition, idle time MR data corresponding to each mobile terminal is further obtained, and the idle time difference value corresponding to each mobile terminal is determined according to the idle time uplink arrival angle in the idle time MR data and the difference between the idle time downlink signal transmission angle simulated according to the idle time MR data. After determining the idle time difference value and the uplink-downlink difference value corresponding to each mobile terminal, the idle time difference value and the uplink-downlink difference value can be further compared, and it is judged whether the mobile terminal is a target mobile terminal according to the comparison result, that is, it is judged whether the mobile terminal has strong mobility according to the comparison result. If the mobile terminal has strong mobility, the mobile terminal is determined as a target mobile terminal. Then, the first number corresponding to all target mobile terminals in each to-be-identified cell is counted according to the home ECI in the target MR data, and the second number corresponding to all mobile terminals in each to-be-identified cell is counted, and the target mobile terminal proportion with strong mobility in each to-be-identified cell is determined according to the ratio of the first number to the second number.

[0099] It should be noted that the idle time MR data is MR data of the mobile terminal in local traffic idle time, which can be understood as static MR data, and the traffic idle time can be 0-5 o'clock in a day.

[0100] Further, the target mobile terminal is determined based on the idle time difference and the uplink-downlink difference corresponding to each mobile terminal, including:

[0101] For each mobile terminal, if the uplink-downlink difference of the mobile terminal is greater than or equal to a first preset threshold, and the uplink-downlink difference is greater than or equal to the sum of the idle time difference and a second preset threshold, the mobile terminal is determined as the target mobile terminal.

[0102] Specifically, after determining the uplink-downlink difference and the idle time difference of each mobile terminal, the uplink-downlink difference is compared with the first preset threshold. If the uplink-downlink difference is greater than or equal to the first preset threshold, the sum of the idle time difference and the second preset threshold is further determined, and the uplink-downlink difference is compared with the sum. If the uplink-downlink difference is greater than or equal to the sum, it is determined that the mobile terminal corresponding to the uplink-downlink difference has strong mobility. At this time, the mobile terminal can be determined as the target mobile terminal.

[0103] For example, taking the first preset threshold value as 245° and the second preset threshold value as 30°, according to the target MR data of the sampling point ID 1, the target MR data of the sampling point ID 2, and the beam parameters of each SSB beam in Table 2, the downlink signal emission angle corresponding to the mobile terminal of the sampling point ID 1 can be determined as 350°, and the target uplink arrival angle corresponding to the mobile terminal of the sampling point ID 1 can be determined as 80°, the downlink signal emission angle corresponding to the mobile terminal of the sampling point ID 2 can be determined as 330°, and the target uplink arrival angle corresponding to the mobile terminal of the sampling point ID 2 can be determined as 90°, and then according to the above data, the uplink-downlink difference value corresponding to the mobile terminal of the sampling point ID 1 can be determined as 270°, and the uplink-downlink difference value corresponding to the mobile terminal of the sampling point ID 2 can be determined as 240°. In addition, the idle time MR data corresponding to the mobile terminal of the sampling point ID 1 and the mobile terminal of the sampling point ID 2 can be obtained, and the first idle time difference value corresponding to the mobile terminal of the sampling point ID 1 can be determined as 205°, and the second idle time difference value corresponding to the mobile terminal of the sampling point ID 2 can be determined as 200°. Then, whether the above mobile terminals have strong mobility can be further determined, and the determination result is shown in Table 3. As shown in Table 3, the uplink-downlink difference value corresponding to the mobile terminal of the sampling point ID 1 is greater than the first preset threshold value, and greater than the sum of the first idle time difference value and the second preset threshold value, so the mobile terminal of the sampling point ID 1 has strong mobility, and the mobile terminal of the sampling point ID 1 can be determined as the target terminal, and the uplink-downlink difference value corresponding to the mobile terminal of the sampling point ID 2 is less than the first preset threshold value, so the mobile terminal of the sampling point ID 1 has weak mobility, that is, the mobile terminal of the sampling point ID 1 is relatively stable.

[0104] Table 3

[0105]

[0106] In addition, after determining the target mobile terminal of each to-be-identified cell, the first number of the target mobile terminal of each to-be-identified cell and the second number of all mobile terminals in each to-be-identified cell can be counted, and according to the ratio of the first number and the second number, the proportion of the target mobile terminal of each to-be-identified cell can be further determined. For example, as shown in Table 4, in the to-be-identified cell A, the second number of all mobile terminals is 100, and the first number of the target mobile terminal is 30, so the proportion of the target mobile terminal of the to-be-identified cell A can be determined as 30%, and the proportion of the target mobile terminal of the to-be-identified cell B can be determined as 10%, and the proportion of the target mobile terminal of the to-be-identified cell C can be determined as 20%.

[0107] Table 4

[0108] Home ECI First number Second number Target mobile terminal proportion A 30 100 30％ B 20 200 10％ C 60 300 20％ …… …… …… ……

[0109] In step 140, a target mobile terminal proportion of each target mobile terminal is determined based on the target mobile terminal proportion of each target mobile terminal.

[0110] Specifically, after the target mobile terminal proportion of each target mobile terminal is determined, the target mobile terminal proportion can be used to identify the scene of each target mobile terminal. For example, for each target mobile terminal, if the target mobile terminal proportion of the target mobile terminal is high, for example, as shown in Table 4, the target mobile terminal proportion of target mobile terminal A is 30%, it can be determined that the mobile terminal in the coverage range of the target mobile terminal has high mobility, and the scene identification result can be determined as the target mobile terminal being in a high-mobility scene such as a high-speed scene, a high-speed rail scene, a city road scene, and the like. Further, it can be determined that the mobile terminal is in a high-mobility object such as a vehicle, a high-speed rail, and the like. If the target mobile terminal proportion of the target mobile terminal is low, for example, as shown in Table 4, the target mobile terminal proportion of target mobile terminal B is 10%, it can be determined that the mobile terminal in the coverage range of the target mobile terminal has low mobility and high stability, and the scene identification result can be determined as the target mobile terminal being in a low-mobility scene such as a residential area, a village, a supermarket, and the like. In addition, after the scene identification result is determined, the implementation parameters can be optimized in the wireless network optimization process. The implementation parameters can include handover parameters and scheduling thresholds.

[0111] The cell scene identification method provided by the embodiments of the present application can simulate the downlink signal transmission angle of each mobile terminal by using the target SSB beam detection data of each target mobile terminal in the target MR data, and can compare the downlink signal transmission angle with the target uplink arrival angle to determine the target mobile terminal proportion of the target mobile terminal with strong mobility. The target mobile terminal proportion can be used to quantitatively and objectively identify the scene of each target mobile terminal, thereby improving the comprehensiveness and accuracy of the scene identification. In addition, the scene identification of the target mobile terminal can be performed only by using the target MR data, thereby saving the identification cost and improving the identification efficiency.

[0112] The cell scene identification device provided by the embodiments of the present application is described below. The cell scene identification device described below can be correspondingly referred to the cell scene identification method described above.

[0113] The embodiments of the present application also provide a cell scene identification device, Figure 7 is a structural schematic diagram of the cell scene identification device provided by the embodiments of the present application, and Figure 7 The cell scene identification device 700 includes an acquisition module 710, a first determination module 720, a second determination module 730, and a third determination module 740.

[0114] The acquisition module 710 is configured to acquire target MR data corresponding to each of the to-be-identified cells, and for each to-be-identified cell, the target MR data includes target synchronization signal block (SSB) beam detection data and a target uplink angle of arrival corresponding to each mobile terminal in the to-be-identified cell.

[0115] The first determination module 720 is configured to determine a downlink signal emission angle corresponding to each mobile terminal in the to-be-identified cell based on the target SSB beam detection data of the to-be-identified cell.

[0116] The second determination module 730 is configured to determine a target mobile terminal proportion corresponding to the to-be-identified cell based on the downlink signal emission angle corresponding to each mobile terminal and the target uplink angle of arrival.

[0117] The third determination module 740 is configured to determine a scene recognition result of each to-be-identified cell based on each target mobile terminal proportion.

[0118] The cell scene recognition device provided by the embodiments of the present application can simulate the downlink signal emission angle of each mobile terminal through the target SSB beam detection data of each to-be-identified cell in the target MR data after acquiring the target MR data, and can differentiate and compare the downlink signal emission angle with the target uplink angle of arrival, determine the target mobile terminal proportion of the target mobile terminal with strong mobility, and quantitatively and objectively recognize the scene of each to-be-identified cell according to the target mobile terminal proportion, thereby improving the comprehensiveness and accuracy of scene recognition. In addition, the scene recognition of the to-be-identified cell can be performed only according to the target MR data, thereby saving the recognition cost and improving the recognition efficiency.

[0119] Optionally, the acquisition module 710 is specifically configured to:

[0120] acquire MR data corresponding to each to-be-identified cell, and for each to-be-identified cell, the MR data includes SSB beam detection data corresponding to each mobile terminal in the to-be-identified cell, and the SSB beam detection data includes an RSRP intensity.

[0121] In a case where the RSRP intensity is greater than a third preset threshold, the MR data corresponding to the RSRP intensity is determined as the target MR data.

[0122] Optionally, the first determination module 720 is specifically configured to:

[0123] acquire an antenna azimuth angle of the to-be-identified cell and a beam quantity of at least one SSB beam.

[0124] determine a beam initial vector of each SSB beam based on the antenna azimuth angle and the beam quantity.

[0125] determine, based on the beam initial vector of each of the SSB beams and the target SSB beam detection data, a downlink signal transmission angle corresponding to each of the mobile terminals in the to-be-identified cell.

[0126] Optionally, the first determination module 720 is specifically configured to:

[0127] obtain a horizontal width of the to-be-identified cell;

[0128] determine a beam width corresponding to each of the SSB beams based on the horizontal width and the number of beams;

[0129] determine a beam azimuth angle of each of the SSB beams based on the antenna azimuth angle and the beam width corresponding to each of the SSB beams;

[0130] determine a beam initial vector of each of the SSB beams based on the beam azimuth angle of each of the SSB beams.

[0131] Optionally, the target SSB beam detection data comprises a reference signal receiving power (RSRP) sub-intensity corresponding to each of the SSB beams.

[0132] Optionally, the first determination module 720 is specifically configured to:

[0133] determine, for each of the SSB beams, a beam weight vector of the SSB beam based on the beam initial vector of the SSB beam and the RSRP sub-intensity;

[0134] determine a beam sum vector corresponding to each of the mobile terminals in the to-be-identified cell based on a sum of the beam weight vectors of each of the SSB beams, and determine an azimuth angle corresponding to the beam sum vector as the downlink signal transmission angle.

[0135] Optionally, the second determination module 730 is specifically configured to:

[0136] obtain idle time MR data corresponding to each of the mobile terminals;

[0137] determine an idle time difference value corresponding to each of the mobile terminals based on the idle time MR data;

[0138] determine an uplink-downlink difference value based on the downlink signal transmission angle and the target uplink arrival angle corresponding to each of the mobile terminals;

[0139] determine a target mobile terminal based on the idle time difference value and the uplink-downlink difference value corresponding to each of the mobile terminals.

[0140] Determine a target mobile terminal proportion corresponding to the to-be-identified cell based on a ratio of a first quantity corresponding to all target mobile terminals in the to-be-identified cell to a second quantity corresponding to all mobile terminals.

[0141] Optionally, the second determining module 730 is specific to:

[0142] In a case where the uplink-downlink difference of each mobile terminal is greater than or equal to a first preset threshold, and the uplink-downlink difference is greater than or equal to a sum of the idle time difference and a second preset threshold, the mobile terminal is determined as the target mobile terminal.

[0143] The network device related to the embodiments of the present application can be a base station, which can include multiple cells providing services for mobile terminals. According to different application scenarios, the base station can also be referred to as an access point, or can be a device in an access network that communicates with wireless mobile terminal devices through one or more sectors over an air interface, or other names.

[0144] Figure 8 is a structural schematic diagram of the network device provided by the embodiments of the present application, with reference to Figure 8 The embodiments of the present application also provide a network device, which can include a memory 810, a transceiver 820, and a processor 830.

[0145] The memory 810 is used to store computer programs; the transceiver 820 is used to transceive data under the control of the processor 830; and the processor 830 is used to read the computer programs in the memory 810 and perform the following operations:

[0146] Obtain target MR data corresponding to each of at least one to-be-identified cell, and for each to-be-identified cell, the target MR data includes target synchronization signal block SSB beam detection data and target uplink arrival angle corresponding to each of at least one mobile terminal in the to-be-identified cell.

[0147] Determine a downlink signal transmission angle corresponding to each mobile terminal in the to-be-identified cell based on the target SSB beam detection data of the to-be-identified cell.

[0148] Determine a target mobile terminal proportion corresponding to the to-be-identified cell based on a ratio of a first quantity corresponding to all target mobile terminals in the to-be-identified cell to a second quantity corresponding to all mobile terminals.

[0149] Determine a scene recognition result of each to-be-identified cell based on each target mobile terminal proportion.

[0150] Wherein, in Figure 8In particular embodiments, the bus architecture can include any number of interconnecting buses and bridges, depending on the specific application of the processor 830 and the architecture of the memory 810 that is represented by the various circuits linking the processor 830 and the memory 810. The bus architecture can also link various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and thus, not further described herein. The bus interface provides an interface. The transceiver 820 can be a plurality of elements, including a transmitter and a receiver, that provides a means for communicating with various other apparatus over a transmission medium. The processor 830 is responsible for managing the bus architecture and general processing, and the memory 810 can store data used by the processor 830 in executing its operations.

[0151] It should be noted that the network device provided by the embodiments of the present application can realize all the method steps achieved by the above-mentioned method embodiments, and achieve the same technical effects. Therefore, the same parts and beneficial effects of the method embodiments in the embodiments will not be described in detail.

[0152] In another aspect, the embodiments of the present application also provide a computer program product, which comprises a computer program, the computer program can be stored on a non-transitory computer readable storage medium, and the computer program can be executed by a processor to enable a computer to execute the steps of the cell scene identification method provided by the above-mentioned embodiments, for example, including:

[0153] Obtaining target MR data corresponding to each of the at least one to-be-identified cell, for each to-be-identified cell, the target MR data comprises target synchronization signal block (SSB) beam detection data and a target uplink arrival angle corresponding to each mobile terminal in the to-be-identified cell;

[0154] Determining a downlink signal emission angle corresponding to each mobile terminal in the to-be-identified cell based on the target SSB beam detection data of the to-be-identified cell;

[0155] Determining a target mobile terminal proportion corresponding to the to-be-identified cell based on the downlink signal emission angle corresponding to each mobile terminal and the target uplink arrival angle;

[0156] Determining a scene identification result of each to-be-identified cell based on each target mobile terminal proportion.

[0157] In another aspect, the embodiments of the present application also provide a processor readable storage medium, which stores a computer program, and the computer program is used to enable a processor to execute the steps of the method provided by the above-mentioned embodiments, for example, including:

[0158] acquire target MR data corresponding to each of the at least one to-be-identified cell, wherein the target MR data comprises target synchronization signal block (SSB) beam detection data and target uplink angle of arrival corresponding to each of the at least one mobile terminal in the to-be-identified cell;

[0159] determine, based on the target SSB beam detection data of the to-be-identified cell, a downlink signal emission angle corresponding to each of the mobile terminals in the to-be-identified cell;

[0160] determine, based on the downlink signal emission angle corresponding to each of the mobile terminals and the target uplink angle of arrival, a target mobile terminal proportion corresponding to the to-be-identified cell;

[0161] determine, based on each of the target mobile terminal proportions, a scene recognition result of each of the to-be-identified cells.

[0162] The processor-readable storage medium can be any available medium or data storage device that the processor can access, including but not limited to a magnetic storage (such as a floppy disk, a hard disk, a magnetic tape, a magneto-optical disk (MO), etc.), an optical storage (such as a CD, a DVD, a BD, a HVD, etc.), and a semiconductor storage (such as a ROM, an EPROM, an EEPROM, a non-volatile memory (NAND FLASH), a solid-state disk (SSD), etc.), etc.

[0163] The device embodiments described above are merely illustrative, wherein the units described as separate components can or can not be physically separated, and the components displayed as units can or can not be physical units, i.e., can be located in one place or distributed on multiple network units. Part or all of the modules can be selected to achieve the purpose of the embodiment scheme according to actual needs. Those skilled in the art can understand and implement without creative labor.

[0164] From the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be realized by means of software and necessary general hardware platforms, and of course can also be realized by hardware. Based on such understanding, the above technical solutions can be embodied in the form of a software product, which can be stored in a computer readable storage medium, such as a ROM / RAM, a magnetic disk, an optical disk, etc., and includes a plurality of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute the methods described in each embodiment or some parts of the embodiments.

[0165] Finally, it should be noted that the above examples are only used to illustrate the technical solutions of the present application, and are not intended to limit the same; although the present application has been described in detail with reference to the foregoing examples, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing examples, or make equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A cell scenario identification method, characterized in that, The method comprises: obtaining target MR data corresponding to each of at least one to-be-identified cell, wherein the target MR data comprises target synchronization signal block (SSB) beam detection data and target uplink arrival angle corresponding to each of at least one mobile terminal in the to-be-identified cell; determining a downlink signal emission angle corresponding to each of the mobile terminals in the to-be-identified cell based on the target SSB beam detection data of the to-be-identified cell; determining a target mobile terminal proportion corresponding to the to-be-identified cell based on the downlink signal emission angle corresponding to each of the mobile terminals and the target uplink arrival angle; determining a scene recognition result of each of the to-be-identified cells based on the target mobile terminal proportion.

2. The cell scenario identification method of claim 1, wherein, The method comprises: obtaining an antenna azimuth angle and a number of beams of at least one SSB beam of the to-be-identified cell; determining a beam initial vector of each of the SSB beams based on the antenna azimuth angle and the number of beams; determining a downlink signal emission angle corresponding to each of the mobile terminals in the to-be-identified cell based on the beam initial vector of each of the SSB beams and the target SSB beam detection data.

3. The cell scene identification method of claim 2, wherein, The method comprises: obtaining a horizontal width of the to-be-identified cell; determining a beam width corresponding to each of the SSB beams based on the horizontal width and the number of beams; determining a beam azimuth angle of each of the SSB beams based on the antenna azimuth angle and the beam width corresponding to each of the SSB beams; determining a beam initial vector of each of the SSB beams based on the beam azimuth angle of each of the SSB beams.

4. The cell scenario identification method of claim 2 or 3, characterized in that, The target SSB beam detection data comprises a reference signal receiving power (RSRP) sub-intensity corresponding to each of the SSB beams. The method comprises: determining a beam weight vector of each of the SSB beams based on the beam initial vector of each of the SSB beams and the RSRP sub-intensity; determining a beam sum vector corresponding to each of the mobile terminals in the to-be-identified cell based on a sum of the beam weight vectors of each of the SSB beams, and determining an azimuth angle corresponding to the beam sum vector as the downlink signal emission angle.

5. The cell scenario identification method of any one of claims 1-3, wherein, The method comprises: obtaining idle-time MR data corresponding to each of the mobile terminals; determining an idle-time difference value corresponding to each of the mobile terminals based on the idle-time MR data; determining an uplink-downlink difference value based on the downlink signal emission angle corresponding to each of the mobile terminals and the target uplink arrival angle; determining a target mobile terminal based on the idle-time difference value corresponding to each of the mobile terminals and the uplink-downlink difference value. Determine a target mobile terminal proportion corresponding to the to-be-identified cell based on a ratio of a first quantity corresponding to all target mobile terminals in the to-be-identified cell to a second quantity corresponding to all mobile terminals.

6. The cell scene identification method of claim 5, wherein, The determining the target mobile terminal based on the idle time difference and the uplink-downlink difference corresponding to each mobile terminal comprises: For each mobile terminal, if the uplink-downlink difference of the mobile terminal is greater than or equal to a first preset threshold, and the uplink-downlink difference is greater than or equal to a sum of the idle time difference and a second preset threshold, the mobile terminal is determined as the target mobile terminal.

7. The cell scenario identification method of any one of claims 1-3, wherein, The obtaining target MR data corresponding to each of the at least one to-be-identified cell comprises: Obtaining MR data corresponding to each to-be-identified cell; for each to-be-identified cell, the MR data comprises SSB beam detection data corresponding to each of at least one mobile terminal in the to-be-identified cell, and the SSB beam detection data comprises RSRP intensity; In a case where the RSRP intensity is greater than a third preset threshold, the MR data corresponding to the RSRP intensity is determined as target MR data.

8. A community scene recognition device, characterized in that, Comprise: An obtaining module, configured to obtain target MR data corresponding to each of at least one to-be-identified cell, and for each to-be-identified cell, the target MR data comprises target SSB beam detection data corresponding to each of at least one mobile terminal in the to-be-identified cell and target uplink arrival angle; A first determining module, configured to determine a downlink signal transmission angle corresponding to each mobile terminal in the to-be-identified cell based on the target SSB beam detection data of the to-be-identified cell; A second determining module, configured to determine a target mobile terminal proportion corresponding to the to-be-identified cell based on the downlink signal transmission angle corresponding to each mobile terminal and the target uplink arrival angle; A third determining module, configured to determine a scene recognition result of each to-be-identified cell based on each target mobile terminal proportion.

9. A network device, comprising: Comprise memory, transceiver, processor; Memory, configured to store computer programs; Transceiver, configured to transceive data under control of the processor; Processor, configured to read computer programs in the memory and perform steps of the cell scene recognition method in any one of claims 1-7.

10. A computer program product comprising a computer program, characterized in that, The computer programs are executed by the processor to implement steps of the cell scene recognition method in any one of claims 1-7. The computer programs are executed by the processor to implement steps of the cell scene recognition method in any one of claims 1-7.

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