5G-R Wireless Network Optimization Method Based on Ray-Tracing Departure Angle Features

Abstract

The 5G-R wireless network optimization method based on the ray-tracing departure angle feature provided by the present invention includes the following steps: determining the optimal horizontal departure angle of the transmitting antenna to maximize the signal reception power on the railway line; determining the optimal elevation departure angle of the transmitting antenna to maximize the signal reception power on the railway line; the present invention utilizes the departure angle feature of the ray relative to the transmitting antenna, takes the 3dB beamwidth in the horizontal and vertical directions of the transmitting antenna as the physical boundary, and combines methods for obtaining the optimal solution including but not limited to the particle swarm optimization algorithm to complete the intelligent adjustment of the base station parameters; the network optimization scheme proposed by the present invention can, to a certain extent, solve problems such as low efficiency of traditional railway wireless network optimization, low resource utilization rate, and inability to achieve intelligent iteration of network optimization and station parameter adjustment, and improves the efficiency of the existing ray-tracing network optimization.

Description

Technical Field

[0001] The present invention relates to the technical field of electrified railway traction power supply, and particularly to a 5G-R wireless network optimization method based on the departure angle characteristics of ray tracing. Background Art

[0002] With the rapid development of 5G, relevant research on the deployment of 5G networks in high-speed railway scenarios has been carried out, and the railway 5G system (5G-Railway, 5G-R) has also entered the exploration stage. While meeting the requirements of high information reliability, high data transmission rate, and high transmission real-time, 5G-R technology also provides users with more high-performance service services.

[0003] Ray tracing technology is a general and effective wireless channel modeling tool. Based on operation principles such as geometric optics theory, Maxwell's equations, and electromagnetic wave theory, it equates the electromagnetic waves propagating between the transceiver as rays, and describes the channel characteristic parameters such as the path loss of each ray, the type of multipath propagation mechanism, the order of backscattering and the position of the backscattering point, the complex field strength, the wave departure angle and arrival angle in the vertical and horizontal planes through the interaction between the rays and the surrounding environmental objects. In addition, according to the direction patterns and polarization modes of different transceiver antennas, the gains of the transceiver antennas can be superimposed onto each ray correspondingly, making the wireless channel model established by the ray tracing method more accurate.

[0004] With the development of wireless network communication technology, users' demands for network transmission rate and communication stability are also constantly increasing. However, how to improve the network coverage to ensure stable communication in complex electromagnetic environment scenarios such as rail transit, dense urban areas, comprehensive hubs, and large venues is the pain point and difficulty of traditional railway wireless network optimization. Therefore, using ray tracing technology to perform accurate wireless channel modeling and using the departure angle characteristics therein to adjust the base station parameters is a powerful solution to promote the intelligent optimization of future railway wireless networks.

[0005] Current wireless network optimization often requires relying on tools such as signaling testers and test vehicles to conduct multiple measurements on-site to obtain data such as received signal strength first, and then combining manual debugging to correct base station parameters. Moreover, after the debugging is completed, manual measurements still need to be repeated to verify the network coverage effect after adjusting the base station parameters. There are problems such as long cycle, low resource utilization rate, and inability to achieve intelligent iteration of network optimization and base station parameter adjustment. In addition, at present, in addition to most network optimization schemes relying on road testing and manual debugging, a small number of research scholars have proposed using ray tracing technology for network optimization. However, the current application of ray tracing technology in the field of network optimization only uses it for simple iterative calculations without establishing an accurate channel model. Moreover, the current network optimization scheme based on ray tracing technology has too high a degree of freedom when setting simulation base station parameters and does not fully utilize the characteristics of the transmitting antenna radiation pattern to provide a range limit for adjusting base station parameters, thereby improving the optimization efficiency. Therefore, the problems of long optimization cycle, low accuracy, and high cost brought by multiple on-site measurements and repeated manual debugging, as well as the insufficient application of ray tracing technology in the existing scheme, have become the pain points of traditional railway wireless network optimization. Summary of the Invention

[0006] To solve the above pain points, the present invention proposes a 5G-R wireless network optimization scheme based on the departure angle characteristics of ray tracing technology. Ray tracing technology can convert abstract electromagnetic waves into visual rays and obtain channel characteristics such as path loss (PL), azimuth angle of departure (AOD) relative to the transmitting antenna, and elevation angle of departure (EOD) during the propagation of the ray. By using the departure angle characteristics of the ray relative to the transmitting antenna and taking the 3dB beamwidth in the horizontal and vertical directions of the transmitting antenna as the physical boundary, combined with methods for obtaining the optimal solution including but not limited to the particle swarm optimization algorithm, the intelligent adjustment of base station parameters can be completed. The network optimization scheme proposed by the present invention can, to a certain extent, solve the problems of low efficiency, low resource utilization rate, and inability to achieve intelligent iteration of network optimization and base station parameter adjustment in traditional railway wireless networks, improve the efficiency of the existing ray tracing network optimization, provide a new direction and simulation support for achieving precise and efficient railway wireless network optimization, and provide a reference for improving the intelligent railway technology system in China in the future.

[0007] The technical solution adopted by the present invention is as follows:

[0008] A 5G-R wireless network optimization method based on the departure angle characteristics of ray tracing includes the following steps:

[0009] Determine the optimal horizontal departure angle of the transmitting antenna to maximize the signal reception power on the railway line;

[0010] Determine the optimal elevation departure angle of the transmitting antenna to maximize the signal reception power on the railway line.

[0011] Furthermore,

[0012] The method for determining the optimal horizontal departure angle of the transmitting antenna to maximize the signal reception power on the railway line is as follows:

[0013] Establish a ray-tracing simulation model to obtain the objective function that maximizes the signal reception power on the railway line;

[0014] Rotate the horizontal azimuth angle sector of the transmitting antenna to fully cover the target angle range in the horizontal direction;

[0015] Solve the objective function. Eventually, the horizontal departure angle of the ray that maximizes the reception power within the 3dB horizontal beam of the transmitting antenna can be calculated, and then the optimal antenna horizontal azimuth angle can be determined.

[0016] Furthermore, the objective function is:

[0017]

[0018] In formula (1): i represents the index value of the sector, starting from 0, and I represents the index value after the last rotation of the sector; assuming the horizontal beam width of the transmitting antenna is ψ, the starting angle of the 3dB beam in the horizontal direction of the transmitting antenna is α, and the ending angle is β, then the constraint condition β - α = ψ should be satisfied when seeking the optimal solution using the objective function; P AOD (i,j) represents the power when the ray with sector index i and ray index j leaves the transmitting antenna.

[0019] The method for solving the objective function is: Use the departure angle information in the ray-tracing simulation results and perform iterative operations and solutions using various methods for obtaining the optimal solution, including but not limited to the particle swarm algorithm and the bird swarm algorithm.

[0020] Furthermore,

[0021] The method for determining the optimal elevation departure angle of the transmitting antenna to maximize the signal reception power on the railway line is as follows:

[0022] Establish a ray-tracing simulation model to obtain the objective function that maximizes the signal reception power on the railway line;

[0023] Rotate the elevation angle sector of the transmitting antenna to fully cover the target angle range in the vertical direction;

[0024] Solve the objective function, and finally the elevation departure angle of the ray that maximizes the received power within the 3dB vertical beam of the transmitting antenna can be calculated, and then the optimal antenna elevation angle can be determined.

[0025] Furthermore, the objective function is:

[0026]

[0027] In formula (2): i represents the index value of the sector, starting from 0, then I represents the index value after the last rotation of the sector; assuming the vertical beam width of the transmitting antenna is χ, the starting angle of the 3dB beam in the vertical direction of the transmitting antenna is ξ, and the ending angle is ζ, then when using the objective function to seek the optimal solution, the constraint condition ζ - ξ = χ should be satisfied; P EOD (i, j) represents the power when the ray with sector index i and ray index j leaves the transmitting antenna.

[0028] The beneficial effect of the present invention is

[0029] On the premise of the existing base station site, the present invention improves the network coverage rate greater than the power threshold of the target network service stability level by adjusting the azimuth angle and elevation angle of the base station antenna, which is the principle of network optimization. The departure angle characteristics obtained by the ray tracing technology can be used to select the azimuth angle and elevation angle of the transmitting antenna that can achieve the best network coverage effect. Brief Description of the Drawings

[0030] Figure 1 It is the network optimization process based on the horizontal departure angle characteristics in Embodiment 1 of the present invention;

[0031] Figure 2 It is the network optimization effect diagram based on the horizontal departure angle characteristics in Embodiment 1 of the present invention;

[0032] Figure 3 It is the network optimization process based on the elevation departure angle characteristics in Embodiment 1 of the present invention;

[0033] Figure 4 It is the network optimization effect diagram based on the elevation departure angle characteristics in Embodiment 1 of the present invention;

[0034] Figure 5 It is the visualized multipath top view effect diagram in Embodiment 2 of the present invention;

[0035] Figure 6 It is the visualized multipath side view effect diagram in Embodiment 2 of the present invention. Detailed Description of the Invention

[0036] The present invention will be further described in detail below with reference to the drawings and specific embodiments:

[0037] Embodiment 1

[0038] As Figure 1 shown, the 5G-R wireless network optimization method based on the ray-tracing departure angle feature of the present invention includes the following steps:

[0039] Determine the optimal horizontal departure angle of the transmitting antenna to maximize the signal reception power on the railway line;

[0040] Determine the optimal elevation departure angle of the transmitting antenna to maximize the signal reception power on the railway line.

[0041] The implementation process of the network optimization process based on the horizontal departure angle feature in the present invention is as Figure 1 shown:

[0042] ① Set ray-tracing simulation configurations such as the simulation scenario, materials, antenna model, etc., and establish a ray-tracing simulation model;

[0043] ② Select the horizontal azimuth sector of the transmitting antenna, and set the initial horizontal azimuth angle u 0 = 0°, and the rotation angle each time is Rotate the sector in sequence to complete the full coverage of the target angle range ω 1 in the horizontal direction;

[0044] ③ Let the index of the sector be i, and the index of each ray obtained by ray-tracing simulation be j. The sector index increases by 1 each time the sector rotates. According to the horizontal 3dB beamwidth of different transmitting antennas, an angular constraint range can be provided for finding the sector with the maximum sum of ray power values included in the main lobe direction of the antenna;

[0045] ④ Use formula (1) as the objective function and combine various methods for finding the optimal solution, including but not limited to the particle swarm algorithm, bird swarm algorithm, etc., to perform iterative operations. Finally, the horizontal departure angle of the ray that maximizes the received power can be calculated, and then the optimal horizontal azimuth angle can be determined.

[0046]

[0047] In formula (1): i represents the index value of the sector, starting from 0. According to the method described above, the number of rotations required for the sector can be determined, and then I represents the index value after the last rotation of the sector. Assume that the horizontal beamwidth of the transmitting antenna is ψ, the starting angle of the horizontal 3dB beam of the transmitting antenna is α, and the ending angle is β. Then, when using the objective function to seek the optimal solution, the constraint condition β - α = ψ should be satisfied; P AOD (i,j) represents the power of the ray departing from the transmitting antenna when the sector index is i and the ray index is j.

[0048] The network optimization effect based on the horizontal departure angle feature is as Figure 2As shown in the figure, the sectors are rotated in sequence according to the optimization process described above. For example, the initial sector index is ①; the sector index after rotation is ②; the sector index after rotation again is ③, and so on to complete the coverage of the target range. The power of each ray when leaving the transmitting antenna is P AOD (i, j), and iterative operations are performed using various algorithms for finding the optimal solution, including but not limited to the particle swarm algorithm, so that the sum of the powers of all rays included in the main lobe direction of the antenna is maximized finally.

[0049] The implementation process of the network optimization process based on the elevation departure angle feature in the present invention is as Figure 3 shown:

[0050] ① Set the ray tracing simulation configurations such as the simulation scenario, materials, antenna model, etc., and establish a ray tracing simulation model;

[0051] ② Select the elevation angle sector of the transmitting antenna, and set the initial horizontal azimuth angle v 0 = 0°, and the rotation angle each time is φ. Rotate the sector in sequence to complete the full coverage of the target angle range ω 2 in the vertical direction;

[0052] ③ Let the index of the sector be i, and the index of each ray obtained by ray tracing simulation be j. The sector index increases by 1 each time the sector rotates; according to the vertical 3dB beam width of different transmitting antennas, an angle constraint range can be provided for finding the sector where the sum of the powers of all rays included in the main lobe direction of the antenna is maximized;

[0053] ④ Use formula (2) as the objective function and combine various methods for finding the optimal solution, including but not limited to the particle swarm algorithm and the bird swarm algorithm, to perform iterative operations. Finally, the elevation departure angle of the ray with the maximum received power can be calculated, and then the optimal elevation angle can be determined.

[0054]

[0055] In formula (2): i represents the index value of the sector, starting from 0. According to the method described above, the number of times the sector needs to rotate can be determined, then I represents the index value after the last rotation of the sector. Assume that the vertical beam width of the transmitting antenna is χ, the starting angle of the vertical 3dB beam of the transmitting antenna is ξ, and the ending angle is ζ. Then, when using the objective function to seek the optimal solution, the constraint condition ζ - ξ = χ should be satisfied; P EOD (i, j) represents the power of the ray with sector index i and ray index j when leaving the transmitting antenna.

[0056] The network optimization effect based on the elevation departure angle feature is as Figure 4As shown, the sectors are rotated in sequence according to the optimization process described above. For example, the initial sector index is ①; the sector index after rotation is ②; the sector index after rotation again is ③, and so on to complete the coverage of the target range. The power of each ray when leaving the transmitting antenna is P EOD (i,j), iterative operations are performed using various algorithms for finding the optimal solution, including but not limited to the particle swarm algorithm, etc., so that the sum of the powers of all rays included in the main lobe direction of the antenna reaches the maximum finally.

[0057] Embodiment 2

[0058] As an example, in this embodiment, the calculation of the optimal azimuth angle of the antenna is carried out. The ray-tracing simulation configurations such as the simulation scenario, materials, and propagation mechanism model are set. A directional antenna with a 3dB beam width of 65° in the horizontal direction is used as the transmitting antenna, and the ray-tracing simulation is started (it is required to find the optimal antenna azimuth angle within the 360° angle range in the horizontal direction).

[0059] Figure 5 is the visualized multi-path top-down effect diagram presented after the ray-tracing simulation. Each ray has different energy when leaving the transmitting antenna. Let the initial horizontal azimuth angle u of the sector 0 = 0°, rotate 60° each time, and rotate 6 times in sequence to complete the 360° full coverage in the horizontal direction and find the optimal antenna azimuth angle within the horizontal coverage range. Let the index of the sector be i, and the index of each ray obtained from the ray-tracing simulation be j. The sector index increases by 1 each time the sector rotates. According to the optimization process described above, the horizontal departure angle of the ray with the maximum received power can be calculated to determine the optimal horizontal azimuth angle.

[0060] Similarly, the calculation of the optimal elevation angle of the antenna is carried out. The ray-tracing simulation configurations such as the simulation scenario, materials, and propagation mechanism model are set. A directional antenna with a 3dB beam width of 5° in the vertical direction is used as the transmitting antenna, and the ray-tracing simulation is started (it is required to find the optimal antenna elevation angle within the 20° range in the vertical direction).

[0061] Figure 6 is the visualized multi-path side view effect diagram presented after the ray-tracing simulation. Each ray has different energy when leaving the transmitting antenna. Let the initial elevation angle v of the sector 0 = 0°, rotate 5° each time, and rotate 4 times in sequence to complete the 20° full coverage in the vertical direction and find the optimal antenna elevation angle within the vertical coverage range. Let the index of the sector be i, and the index of each ray obtained from the ray-tracing simulation be j. The sector index increases by 1 each time the sector rotates. According to the optimization process described above, the elevation departure angle of the ray with the maximum received power can be calculated to determine the optimal antenna elevation angle.

[0062] It should be noted that the protection scope of the present invention is not limited to the above specific example embodiments. According to the basic technical concept of the present invention, the same structure can also be used to achieve the purpose of the present invention. As long as those skilled in the art can think of the implementation manners without creative work, they all belong to the protection scope of the present invention.

Claims

1. 5G-R wireless network optimization method based on ray-tracing departure angle characteristics, Characterized in that, It includes the following steps: Determine the optimal horizontal departure angle of the transmitting antenna to maximize the signal reception power on the railway line; Determine the optimal elevation departure angle of the transmitting antenna to maximize the signal reception power on the railway line; The method of determining the optimal horizontal departure angle of the transmitting antenna to maximize the signal reception power on the railway line is: Establish a ray-tracing simulation model to obtain the objective function that maximizes the signal reception power on the railway line; Rotate the horizontal azimuth sector of the transmitting antenna to fully cover the target angle range in the horizontal direction; Solve the objective function. Finally, the ray horizontal departure angle that maximizes the reception power within the 3dB horizontal beam range of the transmitting antenna can be calculated, and then the optimal antenna horizontal azimuth angle can be determined. The objective function is: In Equation (1): i represents the index value of the sector, starting from 0, and I represents the index value after the last rotation of the sector; assuming that the horizontal beamwidth of the transmitting antenna is ψ, the starting angle of the 3 dB beam of the transmitting antenna in the horizontal direction is α, and the ending angle is β, then the constraint condition β - α = ψ should be satisfied when seeking the optimal solution using the objective function; P AOD (i, j) represents the power when the ray with sector index i and ray index j leaves the transmitting antenna; The method of solving the objective function is: Use the departure angle information in the ray-tracing simulation results and combine it with the particle swarm algorithm for iterative operation to solve; The method of determining the optimal elevation departure angle of the transmitting antenna to maximize the signal reception power on the railway line is: Establish a ray-tracing simulation model to obtain the objective function that maximizes the signal reception power on the railway line; Rotate the elevation angle sector of the transmitting antenna to fully cover the target angle range in the vertical direction; Solve the objective function. Finally, the ray elevation departure angle that maximizes the reception power within the 3dB vertical beam range of the transmitting antenna can be calculated, and then the optimal antenna elevation angle can be determined. The objective function is: In formula (2): i represents the index value of the sector, starting from 0, and I represents the index value after the last rotation of the sector; assuming that the vertical beamwidth of the transmitting antenna is χ, the starting angle of the 3 dB beam in the vertical direction of the transmitting antenna is ξ, and the ending angle is Then, when seeking the optimal solution using the objective function, the constraint conditions should be satisfied P EOD (i, j) represents the power when the ray with sector index i and ray index j leaves the transmitting antenna.

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