CN117528771B - 5G user position positioning method - Google Patents

5G user position positioning method Download PDF

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Publication number
CN117528771B
CN117528771B CN202311609598.XA CN202311609598A CN117528771B CN 117528771 B CN117528771 B CN 117528771B CN 202311609598 A CN202311609598 A CN 202311609598A CN 117528771 B CN117528771 B CN 117528771B
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base station
user equipment
distance
grid
positioning
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CN117528771A (en
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唐建中
越海涛
黄山峰
裴福平
杨维
段先宇
罗焕平
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Shenzhen Mastercom Technology Corp
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Shenzhen Mastercom Technology Corp
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
    • H04W64/006—Locating users or terminals or network equipment for network management purposes, e.g. mobility management with additional information processing, e.g. for direction or speed determination
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/309—Measuring or estimating channel quality parameters
    • H04B17/318—Received signal strength
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/10—Scheduling measurement reports ; Arrangements for measurement reports

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Quality & Reliability (AREA)
  • Physics & Mathematics (AREA)
  • Electromagnetism (AREA)
  • Position Fixing By Use Of Radio Waves (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

The invention discloses a 5G user position locating method, and belongs to the technical field of 5G locating. The method comprises the steps of obtaining a time advance TA, an antenna horizontal arrival angle HAOA, reference signal received power RSRP and the position of a target base station, wherein the target base station comprises a main base station; determining a location area of the user equipment according to the positions of the TA, the HAOA and the main base station; dividing the position area into a plurality of grids with the same size and shape, and taking the distance between the target base station and the center point of each grid as the actual distance; calculating an estimated distance between the target base station and the user equipment according to the RSRP; according to the estimated distance and the actual distance, calculating the confidence coefficient of each grid by combining a preset confidence coefficient algorithm; and determining the position of the user equipment according to the confidence. The invention improves the positioning precision of the 5G user position positioning.

Description

5G user position positioning method
Technical Field
The invention relates to the technical field of 5G positioning, in particular to a 5G user position positioning method.
Background
With the advent of the 5G era, network bandwidth, communication delay, the number of internet of things connections, and the like have comprehensively overtaken the 4G network. Compared with the 4G network, the 5G network has the advantages of low time delay, higher mobile bandwidth, larger capacity and the like. However, in the positioning technical field, the 5G network does not support the user equipment to upload MDT (Minimization of Drive-tests) data, and cannot build a fingerprint library based on the MDT data, so that the position positioning of the user equipment is realized through fingerprint positioning.
At present, the 5G user position location can only adopt a triangle location method with slightly lower location precision, calculates and calculates the distance between the user equipment and the main base station through TA (TIMING ADVANCE ) values reported by the user equipment, calculates the distance between the user equipment and two adjacent base stations through RSRP (REFERENCE SIGNAL RECEIVING Power) of the adjacent base stations and a propagation model, and then reversely pushes and calculates the position of the user equipment by using the principle of mathematical three-point location, thereby realizing the 5G user position location.
However, since the radio propagation environments faced by each base station are different, the distances between all base stations and the user equipment are calculated by using the same propagation model or several typical propagation models, and a large error is inevitably generated, so that the position accuracy of the user equipment obtained based on the distance positioning is also lower.
Disclosure of Invention
The invention mainly aims to provide a 5G user position locating method, which aims to solve the technical problem of lower triangular locating precision caused by inaccurate propagation model in 5G user position locating.
In order to achieve the above object, the present invention provides a 5G user position locating method, the method comprising:
Acquiring a time advance TA, an antenna horizontal arrival angle HAOA, reference signal received power RSRP and a position of a target base station, wherein the target base station comprises a main base station;
determining a location area of the user equipment according to the positions of the TA, HAOA and the main base station;
Dividing the position area into a plurality of grids with the same size and shape, and taking the distance between the target base station and the center point of each grid as an actual distance;
calculating an estimated distance between the target base station and the user equipment according to the RSRP;
Calculating the confidence coefficient of each grid according to the estimated distance and the actual distance by combining a preset confidence coefficient algorithm;
and determining the position of the user equipment according to the confidence.
Optionally, the step of acquiring the time advance TA, the antenna horizontal arrival angle HAOA, the reference signal received power RSRP, and the location of the target base station includes:
After receiving a measurement report MS uploaded by the user equipment, analyzing the MS, acquiring a time advance TA, an antenna horizontal arrival angle HAOA, reference signal received power RSRP and a physical cell identifier PCI, and determining the position of a target base station corresponding to the PCI from preset base station industrial parameter information.
Optionally, the step of determining a location area of the user equipment according to the positions of the TA, HAOA and the master base station includes:
Calculating the propagation distance of the wireless signal from the user equipment to the main base station according to the TA;
Determining a propagation direction of the wireless signal from the user equipment to the master base station according to the HAOA;
And determining the position area of the user equipment according to the propagation distance, the propagation direction and the position of the main base station and combining a first preset threshold value.
Optionally, the step of calculating an estimated distance between the target base station and the user equipment according to the RSRP includes:
Calculating the path loss of the wireless signal transmitted from the user equipment to the target base station according to the RSRP, the preset antenna transmitting power and the preset antenna gain;
And calculating to obtain the estimated distance between the target base station and the user equipment according to the path loss and a preset propagation model.
Optionally, the target base station further includes a plurality of neighboring base stations, the estimated distances include a first estimated distance, and a second estimated distance corresponding to each of the neighboring base stations, and the actual distances include a first actual distance, and a second actual distance corresponding to each of the neighboring base stations;
the step of calculating the confidence of each grid according to the estimated distance and the actual distance and by combining a preset confidence algorithm comprises the following steps:
Taking the estimated distance between the main base station and the user equipment as the first estimated distance, and taking the estimated distance between each adjacent base station and the user equipment as the second estimated distance corresponding to each adjacent base station;
taking one grid out of the grids as a target grid;
taking the distance between the main base station and the central point of the target grid as the first actual distance, and taking the distance between each adjacent base station and the central point of the target grid as the second actual distance corresponding to each adjacent base station;
Calculating the ratio of the first actual distance to the second actual distance corresponding to each adjacent base station respectively to obtain a first ratio corresponding to each adjacent base station;
Calculating the ratio of the first estimated distance to the second estimated distance corresponding to each adjacent base station respectively to obtain a second ratio corresponding to each adjacent base station;
respectively calculating the difference value of the first ratio and the second ratio corresponding to each adjacent base station, and counting the difference value quantity of each difference value smaller than a second preset threshold value;
Taking the difference value number as the confidence of the target grid, and returning to execute: and the step of taking one grid out of the grids as a target grid until all the grids are taken out.
Optionally, the step of determining the location of the user equipment according to the confidence level includes:
taking the grid with the highest confidence as a pre-positioning grid, and detecting the number of the pre-positioning grids;
And if the number of the pre-positioning grids is equal to one, determining the position of the center point of the pre-positioning grids as the position of the user equipment.
Optionally, after the step of detecting the number of pre-positioning grids, the method further includes:
If the number of the pre-positioning grids is greater than one, calculating the average position of the center points of the pre-positioning grids according to the positions of the center points of the pre-positioning grids, and determining the average position as the position of the user equipment, wherein the average position is the position with the minimum sum of the distances from the center points of the pre-positioning grids.
In addition, to achieve the above object, the present invention further provides a 5G user position locating device, including:
The data processing module is used for acquiring a time advance TA, an antenna horizontal arrival angle HAOA, reference signal received power RSRP and the position of a target base station, wherein the target base station comprises a main base station; determining a location area of the user equipment according to the positions of the TA, HAOA and the main base station; dividing the position area into a plurality of grids with the same size and shape, and determining an actual distance, wherein the actual distance is the distance between the target base station and the center point of each grid; calculating an estimated distance between the target base station and the user equipment according to the RSRP;
The confidence coefficient calculating module is used for calculating the confidence coefficient of each grid according to the estimated distance and the actual distance and by combining a preset confidence coefficient algorithm;
and the positioning module is used for determining the position of the user equipment according to the confidence coefficient.
In addition, to achieve the above object, the present invention further provides a 5G user position locating apparatus, the apparatus including: the system comprises a memory, a processor and a 5G user position location program stored on the memory and executable on the processor, wherein the 5G user position location program is configured to implement the steps of the 5G user position location method as described above.
In addition, to achieve the above object, the present invention also provides a computer-readable storage medium having stored thereon a 5G user position locating program which, when executed by a processor, implements the steps of the 5G user position locating method as described above.
The method comprises the steps of obtaining a time advance TA, an antenna horizontal arrival angle HAOA, reference signal receiving power RSRP and the position of a target base station, wherein the target base station comprises a main base station, so that the position area of user equipment is determined according to the TA, the HAOA and the position of the main base station, and preliminary positioning of the user equipment is realized; the user equipment is positioned more accurately by means of the grids by dividing the position area into a plurality of grids with the same size and shape and taking the distance between the target base station and the center point of each grid as the actual distance; according to the method, the estimated distance between the target base station and the user equipment is calculated according to the RSRP, the confidence coefficient of each grid is calculated according to the estimated distance and the actual distance by combining a preset confidence coefficient algorithm, so that the grid with the highest confidence coefficient is obtained, the position of the user equipment is determined according to the confidence coefficient, the user equipment is accurately positioned under the 5G network, positioning errors caused by inaccurate propagation models are effectively avoided, and the positioning precision of the 5G user position is improved.
Drawings
FIG. 1 is a schematic diagram of a 5G user position location device of a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a flowchart of a first embodiment of a 5G user position location method according to the present invention;
FIG. 3 is a flow chart illustrating determining a location area according to an embodiment of the present invention;
FIG. 4 is a flowchart of a second embodiment of the 5G user position location method of the present invention;
Fig. 5 is a schematic block diagram of a 5G user position locating device according to an embodiment of the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Referring to fig. 1, fig. 1 is a schematic structural diagram of a 5G user position locating device in a hardware running environment according to an embodiment of the present invention.
As shown in fig. 1, the 5G user position locating device may include: a processor 1001, such as a central processing unit (Central Processing Unit, CPU), a communication bus 1002, a user interface 1003, a network interface 1004, a memory 1005. Wherein the communication bus 1002 is used to enable connected communication between these components. The user interface 1003 may include a Display, an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may further include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., a wireless FIdelity (WI-FI) interface). The Memory 1005 may be a high-speed random access Memory (Random Access Memory, RAM) Memory or a stable Non-Volatile Memory (NVM), such as a disk Memory. The memory 1005 may also optionally be a storage device separate from the processor 1001 described above.
Those skilled in the art will appreciate that the structure shown in fig. 1 does not constitute a limitation of the 5G user position location apparatus, and may include more or fewer components than shown, or may combine certain components, or a different arrangement of components.
As shown in fig. 1, an operating system, a data storage module, a network communication module, a user interface module, and a 5G user position location program may be included in the memory 1005 as one type of computer-readable storage medium.
In the 5G user position location device shown in fig. 1, the network interface 1004 is mainly used for data communication with other devices; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 in the 5G user position locating device of the present invention may be provided in the 5G user position locating device, where the 5G user position locating device invokes a 5G user position locating program stored in the memory 1005 through the processor 1001, and executes the 5G user position locating method provided by the embodiment of the present invention.
An embodiment of the present invention provides a 5G user position positioning method, and referring to fig. 2, fig. 2 is a schematic flow chart of a first embodiment of the 5G user position positioning method of the present invention.
In this embodiment, the method for positioning a 5G user position includes:
Step S100: acquiring a time advance TA, an antenna horizontal arrival angle HAOA, reference signal received power RSRP and a position of a target base station, wherein the target base station comprises a main base station;
it should be noted that, the time advance TA (TIMING ADVANCE, time advance) is a time adjustment value sent to the ue after the radio frequency transmission delay caused by the estimated distance of the base station, where the TA is used to instruct the ue to preset to send uplink data in advance, so that the uplink data reaches the base station at a desired time.
The antenna arrival angle refers to an angle at which a wireless signal arrives at the base station antenna, and the antenna horizontal arrival angle HAOA (Horizontal Angle of Arrival, horizontal arrival angle) refers to an angle at which a wireless signal arrives at the base station antenna in the horizontal direction.
The reference signal received Power RSRP (REFERENCE SIGNAL RECEIVING Power, reference signal received Power) is one of the key parameters of radio signal strength and physical layer measurement requirements in a 5G network, and RSRP is the average value of the signal Power received on all the resource elements carrying the reference signal within a certain symbol.
As will be appreciated by those skilled in the art, in a 5G network, a cell is the basic unit of radio network coverage. Typically, one base station corresponds to 3 cells, and provides wireless communication services for user equipments within the 3 cells.
In this embodiment, the base station corresponding to the cell in which the user equipment is located is used as the main base station, and the base station of the main base station and the base station of the host station accessory are used as the target base station.
In this embodiment, TA is the time advanced by the ue to send uplink data to the primary base station, HAOA is the angle of the wireless signal reaching the primary base station antenna in the horizontal direction when the ue sends uplink data to the primary base station, RSRP is the RSRP of each target base station measured by the ue, and represents the signal strength of each target base station.
In this embodiment, the position of the ue relative to each target base station may be initially determined by acquiring the time advance TA, the antenna horizontal arrival angle HAOA, the reference signal received power RSRP, and the position of the target base station, so that the ue may be more accurately located subsequently.
Step S200: determining a location area of the user equipment according to the positions of the TA, HAOA and the main base station;
It will be appreciated by those skilled in the art that the maximum distance of the user equipment relative to the primary base station can be calculated from the TA and the approximate position of the user equipment relative to the primary base station can be determined from HAOA.
According to the embodiment, the position area where the user equipment is located is preliminarily determined through the maximum distance, the approximate azimuth and the position of the main base station, so that the user equipment is positioned more accurately on the basis of the position area, and the position positioning precision of the 5G user is improved.
Step S300: dividing the position area into a plurality of grids with the same size and shape, and taking the distance between the target base station and the center point of each grid as an actual distance;
To facilitate understanding, in an example, the step of dividing the location area into a plurality of grids of equal size and shape may be: the location area is divided into a plurality of square grids of 400 square meters.
In the embodiment, the position area is divided into a plurality of grids with the same size and shape, and the distances between the target base stations and the center points of the grids are respectively determined, so that the confidence coefficient of each grid can be calculated better later, and the user equipment can be positioned accurately.
Step S400: calculating an estimated distance between the target base station and the user equipment according to the RSRP;
as will be appreciated by those skilled in the art, 5G user position location typically employs a propagation model, and the distance between the base station and the user equipment to which RSRP corresponds is calculated from the RSRP.
According to the method and the device, the estimated distance between each target base station and the user equipment is calculated sequentially through the RSRP and the preset propagation model, so that the confidence coefficient of each grid is calculated conveniently according to the estimated distance, and the user equipment is positioned accurately.
Step S500: calculating the confidence coefficient of each grid according to the estimated distance and the actual distance by combining a preset confidence coefficient algorithm;
It should be noted that, because the radio propagation environments facing each base station are different, the distances between all base stations and the user equipment are calculated by using the same propagation model or several typical propagation models, and a large error inevitably occurs, so that when the triangulation is caused, the position accuracy of the user equipment calculated according to the distances is also lower,
Although the wireless environment difference of different areas is large, the 5G user position location cannot be realized directly through the propagation model, the wireless environment difference is relatively small in a local area. That is, the ratio of the actual distances of two neighboring base stations to the same location is substantially the same as the ratio of the estimated distances of the two neighboring base stations to the same location calculated from the propagation model. Based on the above, the embodiment calculates the confidence coefficient of each grid by combining a preset confidence coefficient algorithm based on the estimated distance predicted by the propagation model and the ratio of the estimated distance to the actual distance, thereby realizing the accurate positioning of the user equipment.
To facilitate understanding, in one example, the estimated distance a1 between the target base station a and the user equipment is 1000 meters. The estimated distance B1 between the target base station B and the user equipment is 1200 meters. The actual distance a2 between the target base station a and the center point of the grid C is 1500 meters. The actual distance B2 between the target base station B and the center point of the grid C is 1800 meters. The actual distance a3 between the target base station a and the center point of the grid D is 1500 meters. The actual distance B3 between the target base station B and the center point of the grid D is 2000 meters.
Therefore, the ratio c1 of a1 to b1 is calculated to be 5/6, the ratio c2 of a2 to b2 is calculated to be 5/6, and the ratio c3 of a3 to b3 is calculated to be 3/4.
Since the difference between C1 and C2 is 0, the confidence of grid C is set to 100, and the difference between C1 and C3 is about 0.083, the confidence of grid D is set to 99.17.
Step S600: and determining the position of the user equipment according to the confidence.
According to the embodiment, the position of the center point of the grid with the highest confidence is determined according to the confidence of each grid, and the position is used as the position of the user equipment, so that the accurate positioning of the user equipment is realized.
In the embodiment, the time advance TA, the antenna horizontal arrival angle HAOA, the reference signal receiving power RSRP and the position of the target base station are acquired, wherein the target base station comprises a main base station, so that the position area of the user equipment is determined according to the positions of the TA, the HAOA and the main base station, and the preliminary positioning of the user equipment is realized; the user equipment is positioned more accurately by means of the grids by dividing the position area into a plurality of grids with the same size and shape and taking the distance between the target base station and the center point of each grid as the actual distance; according to the method, the estimated distance between the target base station and the user equipment is calculated according to the RSRP, the confidence coefficient of each grid is calculated according to the estimated distance and the actual distance by combining a preset confidence coefficient algorithm, so that the grid with the highest confidence coefficient is obtained, the position of the user equipment is determined according to the confidence coefficient, the user equipment is accurately positioned under the 5G network, positioning errors caused by inaccurate propagation models are effectively avoided, and the positioning precision of the 5G user position is improved.
In one possible implementation manner, the step of acquiring the time advance TA, the antenna horizontal arrival angle HAOA, the reference signal received power RSRP, and the location of the target base station includes:
Step S110: after receiving a measurement report MS uploaded by the user equipment, analyzing the MS, acquiring a time advance TA, an antenna horizontal arrival angle HAOA, reference signal received power RSRP and a physical cell identifier PCI, and determining the position of a target base station corresponding to the PCI from preset base station industrial parameter information.
In this embodiment, the measurement report MR (Measurement Report ) is a report uploaded by the ue and can reflect the current wireless environment of the ue, and the physical cell identifier PCI (PHYSICAL CELL IDENTIFIER ) is used to distinguish wireless signals of different cells, and the base station parameter information includes basic information such as PCI, latitude and longitude, and direction angle.
In the embodiment, the MS uploaded by the user equipment is analyzed to obtain TA, HAOA, RSRP and PCI, and the longitude and latitude of the target base station, namely the position of the target base station, are determined through the PCI and the base station industrial parameter information, so that the user equipment can be positioned in real time conveniently according to TA, HAOA, RSRP and the position of the target base station.
In a possible implementation manner, please refer to fig. 3, fig. 3 is a schematic flow chart of determining a location area according to an embodiment of the present invention, and the step of determining the location area of the ue according to the positions of the TA, HAOA and the primary base station includes:
step S210: calculating the propagation distance of the wireless signal from the user equipment to the main base station according to the TA;
in this embodiment, TA reflects the signal propagation time of the user equipment to the master base station, which is the propagation distance multiplied by the speed of light.
During random access gNodeB (i.e., the master base station) determines a time advance value by measuring the received pilot signal, the time advance value ranging from (0, 1,2,..3846). Times.16 Ts/2u, where u is the subcarrier spacing configuration (0-15 kHz, 1-30 kHz, 2-60 kHz, 3-120 kHz, 4-240 kHz).
In an RRC (Radio Resource Control ) connected state, gNodeB determines a TA adjustment value for each UE based on measuring uplink transmission of the corresponding UE (User Equipment), the TA adjustment value ranging from (0, 1,2,..63) ×16Ts/2u.
The latest TA reported this time is the sum of the last recorded TA and the TA adjustment value measured this time gNodeB, and the unit of the latest TA accords with the time measurement dimension.
Currently, the subcarrier spacing configuration of 5G is typically 30khz, with a unit TADV in mr corresponding to a distance of about 40 meters. Thus, the approximate distance (i.e., propagation distance) of the UE from the primary base station may be estimated initially based on (ta+1) x 40, but this distance is the propagation distance of the wireless signal and not the true distance between the UE and the primary base station.
Step S220: determining a propagation direction of the wireless signal from the user equipment to the master base station according to the HAOA;
In this embodiment, the AOA defines an estimated angle of the UE with respect to the reference direction in the horizontal direction. The reference direction is defined herein as the antenna horizontal azimuth direction. The horizontal arrival angle of the antenna is a counterclockwise angle relative to the reference direction, the value azimuth is 0 to 360 degrees, and the unit is 1 degree.
In this embodiment, the azimuth angle of the antenna of the main base station is obtained from the preset base station industrial parameter information, and the azimuth information (i.e. the propagation direction) of the user equipment relative to the main base station is estimated by combining HAOA.
Step S230: and determining the position area of the user equipment according to the propagation distance, the propagation direction and the position of the main base station and combining a first preset threshold value.
It is to be understood that, in the case of shielding, the radio signal sent by the UE reaches the antenna through multiple refraction, and HAOA may deviate from the actual direction of the UE greatly. Moreover, the antenna azimuth of the main base station in the base station parameter information may be wrong, resulting in misestimation of the azimuth (i.e., propagation direction) of the UE.
Therefore, there is a certain error in the location of the user equipment determined only by the propagation distance, the propagation direction and the location of the master base station.
On the basis, the maximum distance (i.e. propagation distance) between the UE and the main base station is determined through the TA, the approximate direction (i.e. propagation direction) of the UE relative to the main base station is determined through VAOA, and the location range (i.e. location area) of the UE is primarily determined on the basis of a given HAOA error threshold (i.e. a first preset threshold).
According to the embodiment, according to the TA, the propagation distance of the wireless signal from the user equipment to the main base station is calculated, according to HAOA, the propagation direction of the wireless signal from the user equipment to the main base station is determined, according to the propagation distance, the propagation direction and the position of the main base station, the position area of the user equipment is determined by combining a first preset threshold value, the preliminary positioning of the user equipment is realized, the positioning range is reduced for the follow-up accurate positioning, and the positioning accuracy is improved.
In a possible implementation manner, please refer to fig. 4, fig. 4 is a flowchart of a second embodiment of the 5G ue positioning method according to the present invention, wherein the step of calculating the estimated distance between the target base station and the ue according to the RSRP includes:
Step S410: calculating the path loss of the wireless signal transmitted from the user equipment to the target base station according to the RSRP, the preset antenna transmitting power and the preset antenna gain;
As known to those skilled in the art, the antenna transmit power refers to the radiation power of an antenna, and the antenna gain refers to the ratio of the radiation power flux density of the antenna in a certain specified direction to the maximum radiation power flux density of a reference antenna at the same input power
In this embodiment, the antenna transmitting power and the antenna gain of each target base station are obtained from the preset base station industrial parameter information, and the path loss of the wireless signal transmitted from the user equipment to each target base station is calculated according to the RSRP of each target base station, the antenna transmitting power of each target base station and the antenna gain of each target base station, so that the estimated distance is calculated according to the path loss and the preset transmission model.
It should be noted that, in this embodiment, according to RSRP, antenna transmitting power and antenna gain, a formula for calculating path loss is as follows: path loss = antenna transmit power + antenna gain-RSRP.
Step S420: and calculating to obtain the estimated distance between the target base station and the user equipment according to the path loss and a preset propagation model.
In this embodiment, the propagation model may be a COST 231-Hata propagation model.
To aid understanding, in one example, the COST 231-Hata propagation model is specified as follows ：Pathloss＝K1+K2lgd+K3(Hms)+K4lg(Hms)+K5lg(Heff)+K6lg(Heff)lg(d)+K7+Kclutter;
Wherein Pathloss is path loss, K1 is a constant related to frequency, K2 is a distance attenuation constant, K3 and K4 are user equipment antenna height correction coefficients, K5 and K6 are base station antenna height correction coefficients, K7 is a diffraction correction coefficient, kclutter is a ground object attenuation correction coefficient, d is an estimated distance between a base station and user equipment, hms and Heff are effective heights of the user equipment and the base station antenna.
According to the embodiment, a propagation model is obtained from preset base station industrial parameter information, and according to the propagation model and path loss, the estimated distance between each target base station and user equipment is calculated, so that the confidence coefficient of each grid is determined according to the estimated distance, and accurate positioning of the user equipment is realized.
In a possible implementation manner, the target base station further includes a plurality of neighboring base stations, the estimated distances include a first estimated distance, and a second estimated distance corresponding to each of the neighboring base stations, and the actual distances include a first actual distance, and a second actual distance corresponding to each of the neighboring base stations;
the step of calculating the confidence of each grid according to the estimated distance and the actual distance and by combining a preset confidence algorithm comprises the following steps:
Step S510: taking the estimated distance between the main base station and the user equipment as the first estimated distance, and taking the estimated distance between each adjacent base station and the user equipment as the second estimated distance corresponding to each adjacent base station;
step S520: taking one grid out of the grids as a target grid;
It is to be understood that the location area is divided into a plurality of grids with the same size and shape, and accordingly, confidence needs to be calculated for each grid, so that the grid where the user equipment is located is determined, and positioning of the user equipment is achieved.
In this embodiment, by sequentially taking out one grid from each grid as a target grid, the confidence of the target grid is calculated.
The extracted grid is not extracted for the second time so as not to be repeatedly extracted, and the grid with confidence calculated is not used as the target grid so as not to be repeatedly calculated.
Step S530: taking the distance between the main base station and the central point of the target grid as the first actual distance, and taking the distance between each adjacent base station and the central point of the target grid as the second actual distance corresponding to each adjacent base station;
Step S540: calculating the ratio of the first actual distance to the second actual distance corresponding to each adjacent base station respectively to obtain a first ratio corresponding to each adjacent base station;
step S550: calculating the ratio of the first estimated distance to the second estimated distance corresponding to each adjacent base station respectively to obtain a second ratio corresponding to each adjacent base station;
step S560: respectively calculating the difference value of the first ratio and the second ratio corresponding to each adjacent base station, and counting the difference value quantity of each difference value smaller than a second preset threshold value;
Step S570: taking the difference value number as the confidence of the target grid, and returning to execute: and the step of taking one grid out of the grids as a target grid until all the grids are taken out.
It is to be understood that, in addition to the confidence coefficient of the target grid, which is the number of differences in the present embodiment, the execution degree of the target grid may be determined according to the average value of the differences, where the smaller the average value is, the highest the confidence coefficient.
It should be noted that the difference of the wireless environments in the local area is relatively small, and the ratio of the actual distances from two adjacent base stations to the same location is substantially the same as the ratio of the estimated distances from the two adjacent base stations to the same location calculated according to the propagation model.
Therefore, in this embodiment, by calculating the difference value of the first ratio and the second ratio corresponding to each neighboring base station, and counting the difference value number of each difference value smaller than the second preset threshold, the confidence coefficient of the target grid is used as the difference value number, so as to determine the confidence coefficient of each grid, further locate the user equipment, avoid the defect that the estimated distance predicted by the propagation model has errors, and effectively improve the accuracy of 5G user position location.
In a possible implementation manner, the step of determining the location of the user equipment according to the confidence level includes:
step S610: taking the grid with the highest confidence as a pre-positioning grid, and detecting the number of the pre-positioning grids;
Step S620; and if the number of the pre-positioning grids is equal to one, determining the position of the center point of the pre-positioning grids as the position of the user equipment.
In this embodiment, if the number of pre-positioning grids is one, that is, the number of grids with the highest confidence coefficient is one, the position of the center point of the pre-positioning grid is determined to be the position of the user equipment, so that accurate positioning of the user equipment is completed, and the accuracy of positioning the 5G user position is improved.
Further, after the step of detecting the number of pre-positioning grids, the method further includes:
step S630: if the number of the pre-positioning grids is greater than one, calculating the average position of the center points of the pre-positioning grids according to the positions of the center points of the pre-positioning grids, and determining the average position as the position of the user equipment, wherein the average position is the position with the minimum sum of the distances from the center points of the pre-positioning grids.
It should be noted that, in addition to taking the average position as the position of the user equipment, the center points of the two closest grids in each pre-positioning grid may be connected, and the midpoint of the connection may be taken as the position of the user equipment.
In this embodiment, if the number of the pre-positioning grids is greater than one, that is, if there are a plurality of grids with the highest confidence, the average position of the center points of each pre-positioning grid is calculated according to the positions of the center points of each pre-positioning grid, and the average position is determined as the position of the user equipment, so that the position of the user equipment is optimized under the condition that the plurality of pre-positioning grids are provided, and the positioning accuracy is improved.
In addition, the present invention further provides a 5G user position positioning device, referring to fig. 5, fig. 5 is a schematic block diagram of a 5G user position positioning device according to an embodiment of the present invention, where the device includes:
a data processing module 10, configured to obtain a time advance TA, an antenna horizontal arrival angle HAOA, a reference signal received power RSRP, and a location of a target base station, where the target base station includes a main base station; determining a location area of the user equipment according to the positions of the TA, HAOA and the main base station; dividing the position area into a plurality of grids with the same size and shape, and determining an actual distance, wherein the actual distance is the distance between the target base station and the center point of each grid; calculating an estimated distance between the target base station and the user equipment according to the RSRP;
The confidence coefficient calculating module 20 is configured to calculate a confidence coefficient of each grid according to the estimated distance and the actual distance and in combination with a preset confidence coefficient algorithm;
and the positioning module 30 is used for determining the position of the user equipment according to the confidence level.
In an embodiment, the data processing module 10 is further configured to:
After receiving a measurement report MS uploaded by the user equipment, analyzing the MS, acquiring a time advance TA, an antenna horizontal arrival angle HAOA, reference signal received power RSRP and a physical cell identifier PCI, and determining the position of a target base station corresponding to the PCI from preset base station industrial parameter information.
In an embodiment, the data processing module 10 is further configured to:
Calculating the propagation distance of the wireless signal from the user equipment to the main base station according to the TA;
Determining a propagation direction of the wireless signal from the user equipment to the master base station according to the HAOA;
And determining the position area of the user equipment according to the propagation distance, the propagation direction and the position of the main base station and combining a first preset threshold value.
In an embodiment, the data processing module 10 is further configured to:
Calculating the path loss of the wireless signal transmitted from the user equipment to the target base station according to the RSRP, the preset antenna transmitting power and the preset antenna gain;
And calculating to obtain the estimated distance between the target base station and the user equipment according to the path loss and a preset propagation model.
In an embodiment, the target base station further includes a plurality of neighboring base stations, the estimated distances include a first estimated distance, and a second estimated distance corresponding to each of the neighboring base stations, the actual distances include a first actual distance, and a second actual distance corresponding to each of the neighboring base stations, and the confidence coefficient calculating module 20 is further configured to:
Taking the estimated distance between the main base station and the user equipment as the first estimated distance, and taking the estimated distance between each adjacent base station and the user equipment as the second estimated distance corresponding to each adjacent base station;
taking one grid out of the grids as a target grid;
taking the distance between the main base station and the central point of the target grid as the first actual distance, and taking the distance between each adjacent base station and the central point of the target grid as the second actual distance corresponding to each adjacent base station;
Calculating the ratio of the first actual distance to the second actual distance corresponding to each adjacent base station respectively to obtain a first ratio corresponding to each adjacent base station;
Calculating the ratio of the first estimated distance to the second estimated distance corresponding to each adjacent base station respectively to obtain a second ratio corresponding to each adjacent base station;
respectively calculating the difference value of the first ratio and the second ratio corresponding to each adjacent base station, and counting the difference value quantity of each difference value smaller than a second preset threshold value;
Taking the difference value number as the confidence of the target grid, and returning to execute: and the step of taking one grid out of the grids as a target grid until all the grids are taken out.
In one embodiment, the positioning module 30 is further configured to:
taking the grid with the highest confidence as a pre-positioning grid, and detecting the number of the pre-positioning grids;
And if the number of the pre-positioning grids is equal to one, determining the position of the center point of the pre-positioning grids as the position of the user equipment.
In one embodiment, the positioning module 30 is further configured to:
If the number of the pre-positioning grids is greater than one, calculating the average position of the center points of the pre-positioning grids according to the positions of the center points of the pre-positioning grids, and determining the average position as the position of the user equipment, wherein the average position is the position with the minimum sum of the distances from the center points of the pre-positioning grids.
The 5G user position positioning device provided by the embodiment of the invention can solve the technical problem of lower triangular positioning precision caused by inaccurate propagation model in 5G user position positioning by adopting the 5G user position positioning method in the embodiment. Compared with the prior art, the 5G user position positioning device provided by the embodiment of the present invention has the same beneficial effects as the 5G user position positioning method provided by the above embodiment, and other technical features in the 5G user position positioning device are the same as the features disclosed by the method of the above embodiment, and are not repeated herein.
In addition, the invention also provides 5G user position locating equipment, which comprises a memory, a processor and a 5G user position locating program stored in the memory and capable of running on the processor, wherein the 5G user position locating program realizes the steps of the 5G user position locating method when being executed by the processor.
In addition, the invention also provides a computer readable storage medium, wherein the computer readable storage medium stores a 5G user position locating program, and the 5G user position locating program realizes the steps of the 5G user position locating method when being executed by a processor.
The specific implementation manner of the computer readable storage medium of the present invention is basically the same as the above embodiments of the 5G user position locating method, and will not be described herein.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) as described above, comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method according to the embodiments of the present invention.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.

Claims (6)

1. The 5G user position locating method is characterized by comprising the following steps of:
Acquiring a time advance TA, an antenna horizontal arrival angle HAOA, reference signal received power RSRP and a position of a target base station, wherein the target base station comprises a main base station;
determining a location area of the user equipment according to the positions of the TA, HAOA and the main base station;
Dividing the position area into a plurality of grids with the same size and shape, and taking the distance between the target base station and the center point of each grid as an actual distance;
calculating an estimated distance between the target base station and the user equipment according to the RSRP;
Calculating the confidence coefficient of each grid according to the estimated distance and the actual distance by combining a preset confidence coefficient algorithm;
determining the position of the user equipment according to the confidence level;
The target base station further comprises a plurality of adjacent base stations, the estimated distance comprises a first estimated distance and a second estimated distance corresponding to each adjacent base station, and the actual distance comprises a first actual distance and a second actual distance corresponding to each adjacent base station;
the step of calculating the confidence of each grid according to the estimated distance and the actual distance and by combining a preset confidence algorithm comprises the following steps:
Taking the estimated distance between the main base station and the user equipment as the first estimated distance, and taking the estimated distance between each adjacent base station and the user equipment as the second estimated distance corresponding to each adjacent base station;
taking one grid out of the grids as a target grid;
taking the distance between the main base station and the central point of the target grid as the first actual distance, and taking the distance between each adjacent base station and the central point of the target grid as the second actual distance corresponding to each adjacent base station;
Calculating the ratio of the first actual distance to the second actual distance corresponding to each adjacent base station respectively to obtain a first ratio corresponding to each adjacent base station;
Calculating the ratio of the first estimated distance to the second estimated distance corresponding to each adjacent base station respectively to obtain a second ratio corresponding to each adjacent base station;
respectively calculating the difference value of the first ratio and the second ratio corresponding to each adjacent base station, and counting the difference value quantity of each difference value smaller than a second preset threshold value;
Taking the difference value number as the confidence of the target grid, and returning to execute: and the step of taking one grid out of the grids as a target grid until all the grids are taken out.
2. The 5G user position locating method according to claim 1, wherein the step of acquiring the time advance TA, the antenna horizontal arrival angle HAOA, the reference signal received power RSRP, and the position of the target base station comprises:
After receiving a measurement report MS uploaded by the user equipment, analyzing the MS, acquiring a time advance TA, an antenna horizontal arrival angle HAOA, reference signal received power RSRP and a physical cell identifier PCI, and determining the position of a target base station corresponding to the PCI from preset base station industrial parameter information.
3. The 5G user location positioning method of claim 1 wherein said step of determining a location area of a user device based on the locations of said TA, said HAOA and said master base station comprises:
Calculating the propagation distance of the wireless signal from the user equipment to the main base station according to the TA;
Determining a propagation direction of the wireless signal from the user equipment to the master base station according to the HAOA;
And determining the position area of the user equipment according to the propagation distance, the propagation direction and the position of the main base station and combining a first preset threshold value.
4. A 5G user position location method according to claim 3, wherein said step of calculating an estimated distance between said target base station and said user equipment based on said RSRP comprises:
Calculating the path loss of the wireless signal transmitted from the user equipment to the target base station according to the RSRP, the preset antenna transmitting power and the preset antenna gain;
And calculating to obtain the estimated distance between the target base station and the user equipment according to the path loss and a preset propagation model.
5. The 5G user location positioning method of claim 1, wherein the step of determining the location of the user device based on the confidence level comprises:
taking the grid with the highest confidence as a pre-positioning grid, and detecting the number of the pre-positioning grids;
And if the number of the pre-positioning grids is equal to one, determining the position of the center point of the pre-positioning grids as the position of the user equipment.
6. The 5G user location positioning method of claim 5, further comprising, after the step of detecting the number of pre-positioning grids:
If the number of the pre-positioning grids is greater than one, calculating the average position of the center points of the pre-positioning grids according to the positions of the center points of the pre-positioning grids, and determining the average position as the position of the user equipment, wherein the average position is the position with the minimum sum of the distances from the center points of the pre-positioning grids.
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