CN115567102A

CN115567102A - Attenuation determination method, device, equipment and storage medium

Info

Publication number: CN115567102A
Application number: CN202211167959.5A
Authority: CN
Inventors: 李莉; 南作用; 王亚
Original assignee: China United Network Communications Group Co Ltd; China Information Technology Designing and Consulting Institute Co Ltd
Current assignee: China United Network Communications Group Co Ltd; China Information Technology Designing and Consulting Institute Co Ltd
Priority date: 2022-09-23
Filing date: 2022-09-23
Publication date: 2023-01-03

Abstract

The application relates to an attenuation determination method, device, equipment and storage medium, and relates to the field of electromagnetic simulation. The method comprises the following steps: determining a vertical attenuation of the ray tracing model; determining a pheromone expectation table corresponding to a ray tracing model; the pheromone expectation table comprises pheromones accumulated on road sections included by a plurality of paths in the ray tracking model, each path comprises a road section through which a ray passes from an emitting point to a receiving point through different barrier points, and the pheromone is inversely related to path loss; acquiring a target path from the pheromone expectation list and determining the horizontal attenuation of the target path; the target path comprises a plurality of target road sections, and the pheromone accumulated on each target road section is the maximum value of the pheromones accumulated on a plurality of candidate road sections corresponding to each target road section; and determining the global attenuation of the ray tracking model according to the vertical attenuation and the horizontal attenuation, so that the determined global attenuation is more accurate.

Description

Attenuation determination method, device, equipment and storage medium

Technical Field

The present application relates to the field of electromagnetic simulation, and in particular, to an attenuation determination method, apparatus, device, and storage medium.

Background

Currently, in the field of electromagnetic simulation, a ray tracing model is generally constructed to generate a path loss model in electromagnetic wave propagation. Specifically, the electromagnetic simulation system sets the diffraction range and the diffraction times of the barrier points, obtains the position of each barrier point in the emission point, the receiving point and the plurality of barrier points in the ray tracking model, the antenna gain of the emission point, the receiving attenuation of the receiving point, and the penetration attenuation, the reflection loss and the diffraction loss of each barrier point, selects one or more rays, and successively calculates the horizontal attenuation of each ray from the emission point to the receiving point through the plurality of barrier points.

However, in the prior art, the total attenuation of the rays from the emission point to the receiving point is usually superimposed, so that the rays which are reflected and diffracted for multiple times but still have weak attenuation are ignored, and the global attenuation of the ray tracking model cannot be accurately acquired.

Disclosure of Invention

The application provides an attenuation determination method, an attenuation determination device, attenuation determination equipment and a storage medium, which at least solve the problem that the global attenuation of a ray tracking model cannot be accurately obtained in the prior art. The technical scheme of the application is as follows:

according to a first aspect of the present application, there is provided an attenuation determination method for determining a global attenuation of a ray tracing model, the ray tracing model comprising an emission point, a reception point and a plurality of obstacle points; the method comprises the following steps: determining a vertical attenuation of the ray tracing model; determining an pheromone expectation table corresponding to a ray tracing model; the pheromone expectation table comprises pheromones accumulated on road sections included by a plurality of paths in the ray tracking model, each path comprises a road section through which a ray passes from an emitting point to a receiving point through different barrier points, and the pheromone is inversely related to path loss; acquiring a target path from the pheromone expectation table, and determining the horizontal attenuation of the target path; the target path comprises a plurality of target road sections, the pheromone accumulated on each target road section is the maximum value of the pheromones accumulated on a plurality of candidate road sections corresponding to each target road section, and the plurality of candidate road sections corresponding to one road section comprise the road sections starting from the starting point of the one road section; and determining the global attenuation of the ray tracing model according to the vertical attenuation and the horizontal attenuation.

In one possible implementation, determining the pheromone expectation table corresponding to the ray tracing model comprises: performing multiple iterative training on multiple paths in the ray tracking model based on a preset ant colony algorithm to obtain an pheromone expectation list; under the condition that the current iterative training is the first iterative training in multiple iterative training, the pheromones accumulated on the road sections included by the paths in the ray tracking model are preset initial values; under the condition that the current iterative training is non-first iterative training in multiple iterative training, for a first road section on a first path in the current iterative training, determining the pheromone accumulated in the current iterative training of the first road section according to the pheromone accumulated in the previous iterative training of the first road section, the pheromone accumulated in the previous iterative training of a second road section, the pheromone obtained by single training of the first road section in the previous iterative training and the pheromone accumulated in the previous iterative training of the first path, and obtaining the pheromone accumulated on the road section included by a plurality of paths in the ray tracking model; the first path is any one of a plurality of paths, the first road section is any one road section on the first path, and the second road section is a road section behind the first road section.

In one possible implementation, in the current iteration training, determining the first path includes: starting from the starting point of the first road section, determining the first road section from a plurality of candidate road sections corresponding to the first road section according to the exploration probability of ants in the ant colony algorithm to obtain a first path; under the condition that the exploration probability is smaller than or equal to the preset probability, the pheromone accumulated in the last iterative training of the first road segment is the maximum value of the pheromones accumulated in the last iterative training of a plurality of candidate road segments corresponding to the first road segment; and under the condition that the exploration probability is greater than the preset probability, the first road section is any one of a plurality of candidate road sections corresponding to the first road section.

In one possible implementation, determining a global attenuation of the ray tracing model based on the vertical attenuation and the horizontal attenuation includes: and determining the minimum value of the vertical attenuation and the horizontal attenuation as the global attenuation of the ray tracing model.

According to a second aspect of the present application, an attenuation determining apparatus is provided for determining a global attenuation of a ray tracing model, the ray tracing model comprising an emission point, a reception point and a plurality of barrier points; the device comprises a determining unit and an acquiring unit; a determination unit for determining a vertical attenuation of the ray tracing model; the determining unit is further used for determining a pheromone expectation table corresponding to the ray tracing model; the pheromone expectation table comprises pheromones accumulated on road sections included by a plurality of paths in the ray tracking model, each path comprises a road section through which a ray passes from an emitting point to a receiving point through different barrier points, and the pheromone is inversely related to path loss; an acquisition unit configured to acquire a target path from the pheromone expectation table after the determination unit determines the pheromone expectation table; the target path comprises a plurality of target road sections, the pheromone accumulated on each target road section is the maximum value of the pheromones accumulated on a plurality of candidate road sections corresponding to each target road section, and the plurality of candidate road sections corresponding to one road section comprise the road sections starting from the starting point of the one road section; the determining unit is further used for determining the horizontal attenuation of the target path after the acquiring unit acquires the target path; and the determining unit is also used for determining the global attenuation of the ray tracking model according to the vertical attenuation and the horizontal attenuation.

In a possible implementation manner, the determining unit is specifically configured to: performing multiple iterative training on multiple paths in the ray tracking model based on a preset ant colony algorithm to obtain an pheromone expectation list; under the condition that the current iterative training is the first iterative training in multiple iterative training, the pheromones accumulated on the road sections included by the paths in the ray tracing model are preset initial values; under the condition that the current iterative training is non-first iterative training in multiple iterative training, for a first road section on a first path in the current iterative training, determining the pheromone accumulated in the current iterative training of the first road section according to the pheromone accumulated in the previous iterative training of the first road section, the pheromone accumulated in the previous iterative training of a second road section, the pheromone obtained by single training of the first road section in the previous iterative training and the pheromone accumulated in the previous iterative training of the first path, and obtaining the pheromone accumulated on the road section included by a plurality of paths in the ray tracking model; the first path is any one of a plurality of paths, the first road section is any one road section on the first path, and the second road section is a road section behind the first road section.

In a possible implementation manner, in the current iteration training, the determining unit is specifically configured to: starting from the starting point of the first road section, determining the first road section from a plurality of candidate road sections corresponding to the first road section according to the exploration probability of ants in the ant colony algorithm to obtain a first path; under the condition that the exploration probability is smaller than or equal to the preset probability, the pheromone accumulated in the last iterative training of the first road segment is the maximum value of the pheromones accumulated in the last iterative training of a plurality of candidate road segments corresponding to the first road segment; and under the condition that the exploration probability is greater than the preset probability, the first road section is any one of a plurality of candidate road sections corresponding to the first road section.

In a possible implementation manner, the determining unit is specifically configured to: under the condition that the terminal point of the first road section is a receiving point, determining pheromones obtained by single training of the first road section according to the main sight distance propagation attenuation of the first road section, the diffraction loss of the first road section and the reflection loss of the first road section; the pheromone obtained by the single training of the first road section is inversely related to the sum of the main sight distance propagation attenuation of the first road section, the diffraction loss of the first road section and the reflection loss of the first road section; and under the condition that the terminal point of the first road section is not the receiving point, determining that the pheromone obtained by single training of the first road section is a preset value.

In a possible implementation manner, the determining unit is specifically configured to: the minimum of the vertical attenuation and the horizontal attenuation is determined as the global attenuation of the ray tracing model.

According to a third aspect of the present application, there is provided an electronic device comprising: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to execute the instructions to implement the method of the first aspect and any possible implementation thereof.

According to a fourth aspect of the present application, there is provided a computer-readable storage medium, in which instructions, which, when executed by a processor of an electronic device, enable the electronic device to perform the method of any one of the above-mentioned first aspects and any one of its possible embodiments.

According to a fifth aspect of the present application, there is provided a computer program product comprising computer instructions which, when run on an electronic device, cause the electronic device to perform the method of the first aspect and any of its possible embodiments described above.

The technical scheme of the first aspect provided by the application at least brings the following beneficial effects: in the prior art, the total attenuation of each ray from a transmitting point to a receiving point is generally superposed, and the rays which are reflected and diffracted for multiple times and still have weak attenuation are ignored. The method includes the steps that on the basis of an pheromone expectation table corresponding to a determined ray tracing model, pheromones accumulated on road sections included by multiple paths in the ray tracing model are included in the pheromone expectation table; since the pheromone is inversely related to the path loss, and the plurality of target links in the target path obtained from the pheromone expectation table are the largest candidate links of the accumulated pheromones in the plurality of candidate links, it indicates that the path loss of the ray on the target path from the transmitting point to the receiving point is the smallest. Furthermore, the global attenuation obtained based on the horizontal attenuation of the target path and the vertical attenuation of the ray tracking model can consider the ray with weak attenuation in the ray propagation process, so that the determined global attenuation is more accurate.

It should be noted that, for technical effects brought by any implementation manner in the second aspect to the fifth aspect, reference may be made to technical effects brought by a corresponding implementation manner in the first aspect, and details are not described here.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the application and are not to be construed as limiting the application.

FIG. 1 is a schematic diagram of one implementation architecture shown in accordance with an exemplary embodiment;

FIG. 2 is a flow chart illustrating a method of attenuation determination according to an exemplary embodiment;

FIG. 3 is a flow chart illustrating yet another attenuation determination method in accordance with an exemplary embodiment;

FIG. 4 is a flow chart illustrating yet another attenuation determination method in accordance with an exemplary embodiment;

FIG. 5 is a flow chart illustrating yet another attenuation determination method in accordance with an exemplary embodiment;

FIG. 6 is a block diagram illustrating an attenuation determination apparatus in accordance with an exemplary embodiment;

FIG. 7 is a block diagram illustrating an electronic device in accordance with an example embodiment.

Detailed Description

In order to make those skilled in the art better understand the technical solutions of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are capable of operation in sequences other than those illustrated or described herein. The implementations described in the following exemplary examples do not represent all implementations consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

Before describing the attenuation determination method provided by the present application in detail, the implementation environment (implementation architecture) related to the present application will be briefly described.

The attenuation determining method provided by the embodiment of the invention can be suitable for an attenuation determining system. Fig. 1 shows a schematic configuration of the attenuation determining system. As shown in fig. 1, the attenuation determination system 10 includes an attenuation determination apparatus 11 and an electronic device 12. The attenuation determining device 11 is connected to the electronic device 12, and the attenuation determining device 11 and the electronic device 12 may be connected in a wired manner or in a wireless manner, which is not limited in the embodiment of the present invention.

The attenuation determining apparatus 11 may be configured to perform data interaction with the electronic device 12, for example, obtain parameter data of the ray tracing model from the electronic device 12, determine a global attenuation of the ray tracing model, and send the determined global attenuation of the ray tracing model to the electronic device 12.

The attenuation determining device 11 may be further configured to process the obtained parameter data of the ray tracing model, for example, according to the parameter data of the ray tracing model, determine a vertical attenuation of the ray tracing model and an pheromone expectation table of the ray tracing model, and obtain a target path according to the determined pheromone expectation table; and after the target path is obtained from the pheromone expectation table, determining the horizontal attenuation of the target path, and determining the global attenuation of the ray tracing model according to the vertical attenuation and the horizontal attenuation.

The electronic device 12 is installed with simulation software, an input interface is displayed in the simulation software, and the simulation software responds to input operation of a user in the input interface to acquire three-dimensional coordinates of a transmitting point, three-dimensional coordinates of a plurality of obstacle points, three-dimensional coordinates of a receiving point, antenna gain of the transmitting point, receiving attenuation of the receiving point, and penetration attenuation, reflection loss and diffraction loss of each obstacle point in the ray tracking model.

The electronic device 12 may be used for data interaction with the attenuation determining means 11, for example, for sending parameter data of the ray tracing model to the attenuation determining means 11 and for receiving the global attenuation of the ray tracing model sent by the attenuation determining means 11.

Optionally, the electronic device may be a physical machine, for example: the desktop computer is also called a desktop computer or a desktop computer (desktop computer), a mobile phone, a tablet computer, a notebook computer, a super-mobile personal computer (UMPC), a netbook, a Personal Digital Assistant (PDA), and other terminal devices.

Optionally, the determining apparatus may also implement a function to be implemented by a Virtual Machine (VM) deployed on a physical machine.

It should be noted that the attenuation determining apparatus 11 and the electronic device 12 may be independent devices or may be integrated into the same device, and the disclosure is not limited thereto.

When the attenuation determining means 11 and the electronic device 12 are integrated in the same device, the communication mode between the attenuation determining means 11 and the electronic device 12 is the communication between the internal modules of the device. In this case, the communication flow between the two is the same as the "communication flow between the attenuation determining apparatus 11 and the electronic device 12 when they are independent of each other".

In the following embodiments provided by the present disclosure, the present disclosure is explained taking an example in which the attenuation determining apparatus 11 and the electronic device 12 are provided independently of each other.

For ease of understanding, the attenuation determination method provided herein is described in detail below with reference to the drawings.

Fig. 2 is a flowchart illustrating an attenuation determination method for determining a global attenuation of a ray tracing model according to an exemplary embodiment, which may be applied to an electronic device and an attenuation determination apparatus connected to the electronic device. Meanwhile, the method may also be applied to an apparatus similar to the electronic apparatus or the attenuation determining apparatus. In the following, the method is described by taking an example of the method applied to an electronic device, and as shown in fig. 2, the attenuation determining method includes the following steps:

s201, acquiring parameter data of a ray tracking model;

wherein the parameter data includes a transmission point, a reception point, and a position of each of the plurality of obstacle points, an antenna gain of the transmission point, a reception attenuation of the reception point, and a penetration attenuation, a reflection loss, and a diffraction loss of each of the obstacle points.

As a possible implementation manner, an input interface of parameter data is displayed in the simulation software of the electronic device, and the electronic device may obtain the parameter data input in the input interface by the user.

It should be noted that the simulation software is provided with the ray tracing model, and the ray tracing model may emit a plurality of rays from the emission point to the outside based on the parameter data. Accordingly, each ray reaches the receiving point after passing through a plurality of obstacle points.

The ray tracing model may be a three-dimensional ray tracing model, in which case, the positions of the emitting point, the receiving point and each obstacle point may be three-dimensional coordinates in simulation software.

The antenna gain is used for measuring the ability of the antenna to transmit and receive signals towards a specific direction, the receiving attenuation is the attenuation generated when the receiving point receives the rays, the penetrating attenuation is the attenuation generated when the rays penetrate through the obstacle point, the reflection loss is the loss generated when the rays reach the obstacle point, and the diffraction loss is the loss generated when the rays reach the obstacle point.

In practical application, the simulation software can simulate a base station to emit wireless signals outwards, in the simulation process, a transmitting point is an antenna of the base station, a receiving point is a user terminal, and a plurality of barrier points can be buildings, trees, mountains and the like. In the simulation software, the obstacle point may be simulated as a polyhedron or may be simulated as an abstract point.

S202, determining the vertical attenuation of the ray tracking model;

wherein the vertical attenuation includes attenuation generated in a vertical direction during the propagation of the ray.

As a possible implementation manner, after the electronic device acquires the parameter data, the vertical attenuation of each ray emitted by the ray tracing model in the vertical direction is calculated according to the parameter data. Further, the electronic device determines a minimum value of the calculated plurality of vertical attenuations as a vertical attenuation of the ray tracing model.

It should be noted that, in the case where there is an obstacle point in the vertical direction between the transmission point and the reception point, the vertical attenuation of each ray in the vertical direction satisfies the following formula one:

L _v ＝C+G+L _nlos +L _freq +L _eah +L _rm +L _am formula one

Wherein L is _v For vertical attenuation, C for reception attenuation at the reception point, G for antenna gain at the transmission point, L _nlos Attenuation of mainly non-line-of-sight propagation, L _freq As a frequency correction parameter, L _eah Highly attenuated for effective antenna, L _rm Attenuation from the top of the obstacle point to the receiving point, L _am The attenuation of the antenna at the transmission point to the obstruction point.

In the case that there is no obstacle point between the transmission point and the reception point in the vertical direction, the vertical attenuation of each ray in the vertical direction satisfies the following formula two:

L _v ＝C+G+L _los +L _freq +L _eahlos formula two

Wherein L is _v For vertical attenuation, C for reception attenuation at the reception point, G for antenna gain at the transmission point, L _los Attenuation of the dominant line-of-sight propagation, L _freq As a frequency correction parameter, L _eahlos Effective antenna height attenuation for line of sight.

The receiving attenuation of the receiving point, the antenna gain of the transmitting point, the main non-line-of-sight propagation attenuation, the frequency correction parameter, the effective antenna height attenuation, the attenuation from the top end of the barrier point to the receiving point, the attenuation from the antenna of the transmitting point to the barrier point, the main line-of-sight propagation attenuation and the line-of-sight effective antenna height attenuation can be preset in simulation software by operation and maintenance personnel.

Exemplarily, in an electromagnetic simulation system, in the case that an obstacle point exists between a transmitting point and a receiving point in the vertical direction, 10 rays are transmitted from the transmitting point to the receiving point through the obstacle point, the attenuation of the 10 rays in the vertical direction is calculated, and the minimum value of the attenuation is taken as the vertical attenuation; when there is no obstacle point between the transmission point and the reception point in the vertical direction, 10 rays are transmitted from the transmission point to the reception point, the attenuation of the 10 rays in the vertical direction is calculated, and the minimum value is taken as the vertical attenuation.

S203, determining a pheromone expectation table corresponding to the ray tracing model;

the pheromone expectation table comprises pheromones accumulated on road sections included by a plurality of paths in the ray tracing model, each path comprises the road sections through which a ray passes from a transmitting point to a receiving point through different barrier points, and the pheromone is inversely related to the path loss.

As a possible implementation manner, the electronic device obtains multiple paths corresponding to multiple rays of the ray tracing model one to one. Further, the electronic device performs multiple times of iterative training on multiple paths in the ray tracking model based on a preset ant colony algorithm to obtain an pheromone expectation list.

Specifically, for the first iteration training, the electronic device sets an pheromone with a preset initial value for a road segment in a path through which each ray of the ray tracking model passes, and uses the pheromone as an accumulated pheromone of the road segment in the first iteration training.

For subsequent non-first iteration training, the electronic equipment determines the pheromone obtained by single training of the first road section in the last iteration training, and determines the pheromone accumulated by the first road section in the current iteration training according to the pheromone accumulated by the first road section in the last iteration training, the pheromone accumulated by the next road section in the first iteration training, the pheromone obtained by single training of the first road section in the last iteration training and the pheromone accumulated by the first path in the last iteration training.

Further, the electronic device may obtain pheromones accumulated over segments included in the plurality of paths in the ray tracing model.

The specific implementation manner of this step may refer to the subsequent description of the embodiment of the present application, and is not described herein again.

S204, acquiring a target path from the pheromone expectation list;

the target path comprises a plurality of target road sections, the pheromone accumulated on each target road section is the maximum value of the pheromones accumulated on a plurality of candidate road sections corresponding to each target road section, and the plurality of candidate road sections corresponding to one road section comprise the road sections starting from the starting point of the one road section.

As a possible implementation manner, for an emission point in the simulation software, the electronic device determines a plurality of candidate segments corresponding to the emission point from the pheromone expectation table, and acquires pheromones accumulated on each candidate segment from the pheromone expectation table. Further, the electronic device determines a candidate road segment with the largest accumulated pheromone among the plurality of candidate road segments as a target road segment corresponding to the transmitting point, and determines an end point of the target road segment as a target obstacle point.

For each target obstacle point, the electronic equipment determines a plurality of candidate road sections corresponding to the target obstacle point from the pheromone expectation table, and acquires the pheromone accumulated on each candidate road section from the pheromone expectation table. Further, the electronic device determines a candidate road segment with the largest accumulated pheromone among the plurality of candidate road segments as a target road segment corresponding to the target obstacle point, and determines an end point of the target road segment as a next target obstacle point.

And the electronic equipment refers to the steps and sequentially carries out until the target road section corresponding to the previous obstacle point of the receiving point is determined, a plurality of target road sections are obtained, and the plurality of target road sections are determined as the target path.

The pheromone expectation table may be a table or a matrix.

Illustratively, the pheromone expectation table may be as shown in table 1 below:

TABLE 1 pheromone expectation Table

Candidate road section	Emission point	Obstacle point 1	Obstacle point 2	Obstacle point 3	Obstacle point 4	Obstacle point 5	Obstacle point 6
								Candidate road segment 1	37	19	13	15	17	23	29
Candidate road section 2	51	13	18	22	21	9	25
								Candidate road section 3	45	21	24	26	52	47	61

For example, as shown in table 1, a row of the pheromone expectation table includes an emission point or a candidate link (e.g., candidate link 1, candidate link 2, and candidate link 3) corresponding to each obstacle point, and a column of the pheromone expectation table includes an emission point and a plurality of obstacle points (obstacle point 1, obstacle point 2, obstacle point 3, obstacle point 4, obstacle point 5, obstacle point 6).

It should be noted that different candidate road segments are used to represent different emission modes, and may specifically include three types, namely reflection, diffraction and transmission; the element in the pheromone expectation table is an pheromone accumulated by a road segment passed by an ant, taking the candidate road segment 2 corresponding to the obstacle point 3 as an example, after the ant starts from the obstacle point 3 and passes through the candidate road segment 2 corresponding to the obstacle point 3, the accumulated pheromone is 22 when the ant reaches the end point of the candidate road segment 2.

Exemplarily, as shown in the above table 1, the ants start from the emission point, and the corresponding candidate links include candidate link 1, candidate link 2, and candidate link 3, where the pheromone accumulated for candidate link 1 is 37, the pheromone accumulated for candidate link 2 is 51, and the pheromone accumulated for candidate link 3 is 45. The ant determines the candidate segment 2 corresponding to the maximum value of the accumulated pheromone from the 3 candidate segments as the target segment. Meanwhile, the ant also takes the end point of the candidate link 2 as a target obstacle point. For example, in the case where the end point of the candidate link 2 is the obstacle point 2, the ant determines the obstacle point 2 as the target obstacle point of the emission point.

For each target obstacle point, for example, for obstacle point 2, ants start from obstacle point 2, the corresponding candidate links include candidate link 1, candidate link 2, and candidate link 3, the pheromone accumulated for candidate link 1 is 13, the pheromone accumulated for candidate link 2 is 18, and the pheromone accumulated for candidate link 3 is 24. The ant determines the candidate road segment 3 corresponding to the maximum accumulated pheromone as the target road segment from the 3 candidate road segments. Meanwhile, the ant also takes the end point of the candidate link 3 as the next target obstacle point. For example, in the case where the end point of the candidate link 3 is the obstacle point 6, the ant determines the obstacle point 6 as a next target obstacle point of the obstacle point 2.

And subsequently, the ants refer to the steps and sequentially perform the steps until a target road section corresponding to a barrier point before the receiving point is determined, a plurality of target road sections are obtained, and the plurality of target road sections are determined as target paths. For example, the target link corresponding to the obstacle point 6 is the candidate link 3, the end point of the candidate link 3 is the receiving point, in this case, the obstacle point 6 is the previous obstacle point of the receiving point, and the candidate link 3 corresponding to the obstacle point 6 is the last target link.

Based on the above steps, the ants may obtain all target road segments from the pheromone expectation table and determine a target path according to all the target road segments.

S205, determining the horizontal attenuation of the target path;

wherein the horizontal attenuation comprises attenuation generated in the horizontal direction during the propagation of the ray.

As a possible implementation manner, after the electronic device acquires the target path, the electronic device obtains a target road segment included in the target path, and calculates the horizontal attenuation of the target path according to the parameter data. It should be noted that the horizontal attenuation of a ray from the emission point to the receiving point through different obstacle points in the horizontal direction satisfies the following formula three:

wherein G is the antenna gain of the transmitting point, C is the receiving attenuation of the receiving point, n is the number of the ray reaching the obstacle point in the ray propagation process, and L _los-k Attenuation for the main line-of-sight propagation before the ray reaches the k-th obstacle point, DL _k Attenuation of diffraction when a ray reaches the k-th obstacle point, RL _k Is the attenuation of the reflection when the ray reaches the k-th obstruction point.

For example, in combination with the pheromone expectation table shown in table 1, if the electronic device determines that the target path is the transmission point-the obstacle point 2-the obstacle point 6-the receiving point, and passes through 3 target road segments, the electronic device determines the main line-of-sight propagation attenuation, the diffraction attenuation, and the reflection attenuation of each of the 3 target road segments, and calculates the horizontal attenuation of the target path according to the antenna gain of the transmission point, the reception attenuation of the receiving point, and the formula three.

And S206, determining the global attenuation of the ray tracking model according to the vertical attenuation and the horizontal attenuation.

Wherein the global attenuation is the minimum of the vertical attenuation and the horizontal attenuation.

As one possible implementation, after acquiring the vertical attenuation and the horizontal attenuation, the electronic device takes the minimum value of the vertical attenuation and the horizontal attenuation as the global attenuation of the ray tracing model.

It can be understood that in the prior art, the total attenuation of each ray from the emission point to the receiving point is generally superposed, and the rays which are reflected and diffracted for multiple times and still have weak attenuation are ignored. The method includes the steps that an pheromone expectation table corresponding to a determined ray tracing model is based, wherein the pheromone expectation table comprises pheromones accumulated on road sections included by a plurality of paths in the ray tracing model; since the pheromone is inversely related to the path loss, and the plurality of target road segments in the target path acquired from the pheromone expectation table are the candidate road segments with the largest accumulated pheromone in the plurality of candidate road segments, the path loss of the ray on the target path from the transmitting point to the receiving point is the smallest. Furthermore, the global attenuation obtained based on the horizontal attenuation of the target path and the vertical attenuation of the ray tracking model can consider the rays with weak attenuation in the ray propagation process, so that the determined global attenuation is more accurate.

In some embodiments, in order to determine the pheromone expectation table corresponding to the ray tracing model, as shown in fig. 3, the step S203 provided in the embodiments of the present application specifically includes the following steps:

s2031, carrying out multiple iterative training on multiple paths in the ray tracking model based on a preset ant colony algorithm to obtain a pheromone expectation list.

As a possible implementation, the multiple iterative training may be divided into first iterative training and non-first iterative training.

And under the condition that the current iterative training is the first iterative training in the multiple iterative training, the electronic equipment sets an pheromone with a preset initial value for all road sections included by the multiple paths, and determines the pheromone with the preset initial value as the pheromone accumulated on the road sections.

For example, the preset initial value may be 0 or 1, which is not limited in this application.

It is understood that, in the case where the electronic device sets the preset initial value to 0, all elements in the pheromone expectation table are 0.

Under the condition that the current iterative training is non-first iterative training in multiple iterative training, the ants start from the emission points, the electronic device determines a first path based on an ant colony algorithm, and respectively determines pheromones accumulated by the first path in the last iterative training, pheromones accumulated by a second path in the last iterative training, pheromones obtained by single training of the first path in the last iterative training, and pheromones accumulated by the first path in the last iterative training.

The first path is any one of a plurality of paths, the first road section is any one road section on the first path, and the second road section is a road section behind the first road section.

It should be noted that the pheromone accumulated in the previous iteration training of the first path and the pheromone accumulated in the previous iteration training of the second path may be directly obtained by querying from the pheromone expectation table obtained in the previous iteration training.

The pheromone obtained by a single training of the first road section in the last iterative training can be determined based on the end point type of the first road section and the main line-of-sight propagation attenuation, diffraction attenuation and reflection attenuation of the first road section, and the specific implementation mode can refer to the subsequent description of the embodiment of the application, and is not repeated here.

The calculation formula of the pheromone accumulated in the Nth iteration training of the first path meets the following formula IV:

wherein, Δ AQ _n (s _τ ，a _τ ) The pheromone accumulated in the Nth iteration training for the first path, a is the execution behavior of the ant reaching the barrier point or the receiving point, tau is the execution step of the ant, a _τ Executing behaviors in the Tth executing step for ants, wherein the executing behaviors comprise three types of reflection, diffraction and transmission; s is the position state of ants _τ Position status after the τ -th execution step is performed for ants. w is the weight of the pheromone accumulated by the first path in all paths, L (p) _N Path loss in the nth iteration training for the first path. It should be noted that w may be set in the simulation software by the operation and maintenance staff in advance.

Further, the electronic device determines the pheromone accumulated in the current iterative training of the first road section according to the pheromone accumulated in the previous iterative training of the first road section, the pheromone accumulated in the previous iterative training of the second road section, the pheromone obtained by single training of the first road section in the previous iterative training, and the pheromone accumulated in the previous iterative training of the first path, so as to obtain the pheromone accumulated on the road section included in the multiple paths in the ray tracing model.

Specifically, a formula for calculating pheromones accumulated in the current iteration training of the first road segment is shown as the following formula five:

where N is an iteration number, for example, N may be 100 or 200, which is not limited in this application.

AQ _N (s _τ ，a _τ ) Accumulated information for the first segment in the Nth iteration trainingBenzotins, AQ _N-1 (s _τ ，a _τ ) Pheromones, AQ, accumulated for the first segment in the N-1 st iterative training _N-1 (s _τ+1 ，a _τ+1 ) For the pheromone, Δ AQ, accumulated in the second segment in the N-1 th iterative training _N-1 (s _τ ，a _τ ) Pheromone, r, accumulated in the N-1 st iterative training for the first path _(τ，N-1) Pheromones obtained by single training of the first path in the N-1 st iterative training; alpha is learning rate and its value range is [0,1 ]]λ is attenuation coefficient, and its value range is [0,1 ]]。

It should be noted that when the current iterative training is the nth iterative training, the previous iterative training is the N-1 st iterative training.

And subsequently, calculating a plurality of paths in the ray tracking model by referring to the pheromone calculation formula accumulated in the current iterative training of the first road section until an pheromone expectation table after the Nth iterative training is obtained.

As can be understood, the method and the device for the ray tracing of the multi-path in the ray tracing model are based on the preset ant colony algorithm and are used for carrying out multiple times of iterative training; when the current iterative training is the first iterative training, setting a preset initial value to obtain pheromones accumulated on the road sections included by the multiple paths; when the current iterative training is not the first iterative training, acquiring pheromones accumulated by a first path in the last iterative training, pheromones accumulated by a second path in the last iterative training, pheromones obtained by a single training of the first path in the last iterative training and pheromones accumulated by a first path in the last iterative training, determining the pheromones accumulated by the first path in the current iterative training according to the acquired pheromones accumulated by the first path in the last iterative training, pheromones accumulated by the second path in the last iterative training, pheromones obtained by a single training of the first path in the last iterative training and pheromones accumulated by the first path in the last iterative training, and obtaining the pheromones accumulated on the path sections included by all paths in the ray tracking model according to the step until the Nth iterative training is completed to obtain an pheromone expectation table after the Nth iterative training.

In some embodiments, in order to determine the first path in the current iteration training, as shown in fig. 4, the attenuation determination method provided in the embodiment of the present application further includes:

s301, starting from the starting point of the first road section, determining the first road section from a plurality of candidate road sections corresponding to the first road section according to the exploration probability of ants in the ant colony algorithm, and obtaining a first path.

Under the condition that the exploration probability is smaller than or equal to the preset probability, the pheromone accumulated in the last iterative training of the first road segment is the maximum value of the pheromones accumulated in the last iterative training of a plurality of candidate road segments corresponding to the first road segment; and under the condition that the exploration probability is greater than the preset probability, the first road section is any one of a plurality of candidate road sections corresponding to the first road section.

As a possible implementation manner, the electronic device sets a preset probability, determines a plurality of candidate road segments corresponding to the emitting points from the pheromone expectation table under the condition that the starting point of the first road segment is the emitting point of the simulation software, and acquires pheromones accumulated on each candidate road segment from the pheromone expectation table; further, when the exploration probability is smaller than or equal to the preset probability, the first road section is determined as the road section with the largest accumulated pheromone in the candidate road sections, when the exploration probability is larger than the preset probability, the first road section is determined as any one of the candidate road sections, and the end point of the first road section is used as the starting point of the next first road section.

Under the condition that the starting point of the first road section is an obstacle point of the simulation software, the electronic equipment determines a plurality of candidate road sections corresponding to the starting point from the pheromone expectation table and acquires the pheromone accumulated on each candidate road section from the pheromone expectation table; further, when the exploration probability is smaller than or equal to the preset probability, the first road section is determined as the road section with the largest accumulated pheromone in the candidate road sections, when the exploration probability is larger than the preset probability, the first road section is determined as any one of the candidate road sections, and the end point of the first road section is used as the starting point of the next first road section.

And the electronic equipment refers to the steps and sequentially carries out until the terminal point of the first road section is determined to be a receiving point, and determines a first path according to all the determined first road sections.

Exemplarily, in an electromagnetic simulation system, setting a preset probability to be 0.8, and obtaining an obtained pheromone expectation table as shown in table 1 above, wherein the candidate road sections corresponding to ants starting from an emission point include candidate road section 1, candidate road section 2 and candidate road section 3; the pheromone accumulated by the candidate road section 1 is 37, the pheromone accumulated by the candidate road section 2 is 51, and the pheromone accumulated by the candidate road section 3 is 45; the electromagnetic simulation system randomly determines that the exploration probability is 0.7, the exploration probability 0.7 is smaller than the preset probability 0.8, determines that the first road section is the candidate road section with the largest pheromone in the multiple candidate road sections corresponding to the first road section, namely determines that the candidate road section 2 is the first road section, and takes the terminal point of the first road section, namely the obstacle point 2, as the starting point of the next first road section.

Aiming at the barrier point 2, when the ants start from the barrier point 2, the corresponding candidate road sections comprise a candidate road section 1, a candidate road section 2 and a candidate road section 3; the pheromone accumulated for candidate road segment 1 is 13, the pheromone accumulated for candidate road segment 2 is 18, and the pheromone accumulated for candidate road segment 3 is 24; the electromagnetic simulation system randomly determines that the exploration probability is 0.9, the exploration probability 0.9 is larger than the preset probability 0.8, determines that the first road section is any one of a plurality of candidate road sections corresponding to the first road section, namely randomly determines that the candidate road section 1 is the first road section, and takes the terminal point of the first road section, namely the obstacle point 5, as the starting point of the next first road section.

And subsequently, the ants refer to the steps and sequentially perform the steps until the end point of the first road section is determined to be a receiving point, and determine the first path according to all the determined first road sections.

It can be understood that, in the present application, the first road segment is determined from the starting point of the first road segment according to the exploration probability of the ants in the ant colony algorithm, and from a plurality of candidate road segments corresponding to the first road segment. Specifically, the electronic device sets a preset probability, and determines the first road segment as the road segment with the largest accumulated pheromone in the candidate road segments when the exploration probability is smaller than or equal to the preset probability; and under the condition that the exploration probability is greater than the preset probability, determining the first road section as any one of the candidate road sections, and taking the end point of the first road section as the starting point of the next first road section, so that ants can continuously explore a new path in iterative training, further the ants can avoid being trapped in a loop in the iterative training, and meanwhile, the determined paths can be more comprehensive.

In some embodiments, in order to determine pheromones obtained by a single training of the first segment, as shown in fig. 5, the attenuation determining method provided in the embodiment of the present application further includes;

s401, determining whether the end point of the first path segment is a receiving point.

S402, under the condition that the terminal point of the first road section is a receiving point, determining pheromones obtained by single training of the first road section according to the main line-of-sight propagation attenuation, the diffraction loss and the reflection loss of the first road section.

The calculation formula of the pheromone obtained by the first path section through single training meets the following formula six:

r＝K/(DL _τ +RL _τ +L _los ) Formula six

Wherein r is pheromone obtained by single training of the first path segment, DL _τ For diffraction attenuation of the radiation at the end of the first route section, RL _τ Attenuation of reflection of the radiation at the end of the first distance, L _los The main sight distance propagation attenuation before the ray reaches the end point of the first road section, and K is a feedback coefficient used for indicating pheromone and DL obtained by single training of the first road section _τ 、RL _τ And L _los The relationship (2) of (c).

It should be noted that K may be set in the simulation software by the operation and maintenance personnel in advance.

And S403, under the condition that the end point of the first road section is not the receiving point, determining that the pheromone obtained by single training of the first road section is a preset value.

Illustratively, the preset value may be 0.

It can be understood that, under the condition that the end point of the first road section is a receiving point, obtaining diffraction attenuation when the ray reaches the end point of the first road section, reflection attenuation when the ray reaches the end point of the first road section, and main sight distance propagation attenuation before the ray reaches the end point of the first road section, and calculating to obtain pheromone obtained by single training of the first road section according to the diffraction attenuation when the ray reaches the end point of the first road section, reflection attenuation when the ray reaches the end point of the first road section, and main sight distance propagation attenuation before the ray reaches the end point of the first road section; under the condition that the end point of the first road section is not the receiving point, the pheromone obtained by the single training of the first road section is 0, and the calculated amount of the pheromone obtained by the single training of the first road section can be greatly reduced.

FIG. 6 is a block diagram illustrating an attenuation determination apparatus 500 for determining a global attenuation for a ray tracing model including an emission point, a reception point, and a plurality of obstruction points, according to an exemplary embodiment. The apparatus includes a determination unit 501 and an acquisition unit 502.

A determination unit 501 for determining the vertical attenuation of the ray tracing model.

The determining unit 501 is further configured to determine a pheromone expectation table corresponding to the ray tracing model; the pheromone expectation table comprises pheromones accumulated on a road section included by a plurality of paths in the ray tracing model, each path comprises a road section through which a ray passes from an emitting point to a receiving point through different barrier points, and the pheromones are inversely related to path loss.

An acquisition unit 502 for acquiring a target path from the pheromone expectation table after the determination unit 501 determines the pheromone expectation table; the target path comprises a plurality of target road sections, the pheromone accumulated on each target road section is the maximum value of the pheromones accumulated on a plurality of candidate road sections corresponding to each target road section, and the plurality of candidate road sections corresponding to one road section comprise the road sections starting from the starting point of the one road section.

The determining unit 501 is further configured to determine a horizontal attenuation of the target path after the acquiring unit 502 acquires the target path.

The determining unit 501 is further configured to determine a global attenuation of the ray tracing model according to the vertical attenuation and the horizontal attenuation.

Optionally, as shown in fig. 6, the determining unit 501 provided in the embodiment of the present application is specifically configured to:

and performing multiple times of iterative training on multiple paths in the ray tracking model based on a preset ant colony algorithm to obtain an pheromone expectation list.

When the current iterative training is the first iterative training in multiple iterative training, the pheromones accumulated on the road sections included by the paths in the ray tracing model are preset initial values.

Under the condition that the current iterative training is non-first iterative training in multiple iterative training, for a first road section on a first path in the current iterative training, determining pheromones accumulated in the current iterative training of the first road section according to the pheromones accumulated in the previous iterative training of the first road section, the pheromones accumulated in the previous iterative training of a second road section, the pheromones obtained by single training of the first road section in the previous iterative training and the pheromones accumulated in the previous iterative training of the first path, and obtaining the pheromones accumulated on the road sections included by a plurality of paths in the ray tracing model; the first path is any one of a plurality of paths, the first road section is any one road section on the first path, and the second road section is a road section behind the first road section.

and starting from the starting point of the first road section, determining the first road section from a plurality of candidate road sections corresponding to the first road section according to the exploration probability of ants in the ant colony algorithm, and obtaining a first path.

under the condition that the terminal point of the first road section is a receiving point, determining pheromones obtained by single training of the first road section according to the main sight distance propagation attenuation of the first road section, the diffraction loss of the first road section and the reflection loss of the first road section; the pheromone obtained by a single training of the first road section is inversely related to the sum of the main line-of-sight propagation attenuation of the first road section, the diffraction loss of the first road section and the reflection loss of the first road section.

And under the condition that the terminal point of the first road section is not the receiving point, determining that the pheromone obtained by single training of the first road section is a preset value.

the minimum of the vertical attenuation and the horizontal attenuation is determined as the global attenuation of the ray tracing model.

FIG. 7 is a block diagram illustrating an electronic device in accordance with an example embodiment. As shown in fig. 7, electronic device 600 includes, but is not limited to: a processor 601 and a memory 602.

The memory 602 is configured to store executable instructions of the processor 601. It will be appreciated that the processor 601 is configured to execute instructions to implement the attenuation determination method in the above embodiments.

It should be noted that the electronic device structure shown in fig. 7 does not constitute a limitation of the electronic device, and the electronic device may include more or less components than those shown in fig. 7, or combine some components, or arrange different components, as will be understood by those skilled in the art.

The processor 601 is a control center of the electronic device, connects various parts of the whole electronic device by using various interfaces and lines, performs various functions of the electronic device and processes data by operating or executing software programs and/or modules stored in the memory 602 and calling data stored in the memory 602, thereby integrally monitoring the electronic device. Processor 601 may include one or more processing units. Optionally, the processor 601 may integrate an application processor and a modem processor, wherein the application processor mainly handles operating systems, user interfaces, application programs, and the like, and the modem processor mainly handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 601.

The memory 602 may be used to store software programs as well as various data. The memory 602 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program (such as a determination unit, a processing unit, etc.) required by at least one functional module, and the like. Further, the memory 602 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.

In an exemplary embodiment, a computer-readable storage medium comprising instructions, such as a memory comprising instructions, executable by a processor of an electronic device to implement the attenuation determination method in the above-described embodiments is also provided.

In practical implementation, the functions of the determining unit 501 and the obtaining unit 502 can be implemented by the processor 601 in fig. 7 calling the computer program stored in the memory 602. The specific implementation process may refer to the description of the attenuation determining method in the above embodiment, and is not described herein again.

Alternatively, the computer-readable storage medium may be a non-transitory computer-readable storage medium, which may be, for example, a read-only memory (ROM), a Random Access Memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.

In an exemplary embodiment, the present application further provides a computer program product including one or more instructions, which can be executed by a processor of an electronic device to complete the transaction method in the above embodiment.

It should be noted that the instructions in the computer-readable storage medium or one or more instructions in the computer program product are executed by a processor of the electronic device to implement the processes of the transaction method embodiment, and the same technical effects as the transaction method can be achieved, and in order to avoid repetition, details are not repeated here.

Through the above description of the embodiments, it is clear to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional modules is merely used as an example, and in practical applications, the above function distribution may be completed by different functional modules according to needs, that is, the internal structure of the device may be divided into different functional modules to complete the above-described full-classification part or part of the functions.

In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, a module or a unit may be divided into only one logic function, and may be implemented in other ways, for example, a plurality of units or components may be combined or integrated into another apparatus, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

Units described as separate parts may or may not be physically separate, and parts displayed as units may be one physical unit or a plurality of physical units, may be located in one place, or may be distributed to a plurality of different places. The partial or full classification units can be selected according to actual needs to achieve the purpose of the scheme of the embodiment.

In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit may be implemented in the form of hardware, or may also be implemented in the form of a software functional unit.

The integrated unit, if implemented as a software functional unit and sold or used as a separate product, may be stored in a readable storage medium. Based on such understanding, the technical solutions of the embodiments of the present application, or portions thereof that substantially contribute to the prior art, or the whole classification part or portions thereof, may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a device (which may be a single chip, a chip, etc.) or a processor (processor) to execute the whole classification part or some steps of the methods of the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a U disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk.

The above is only an embodiment of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions within the technical scope of the present disclosure should be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. An attenuation determination method for determining a global attenuation of a ray tracing model, the ray tracing model comprising a transmitting point, a receiving point and a plurality of obstacle points; the method comprises the following steps:

determining a vertical attenuation of the ray tracing model;

determining a pheromone expectation table corresponding to the ray tracking model; the pheromone expectation table comprises pheromones accumulated on road sections included by a plurality of paths in the ray tracing model, each path comprises a road section through which a ray passes from the emitting point to the receiving point through different barrier points, and the pheromone is inversely related to path loss;

acquiring a target path from the pheromone expectation table, and determining the horizontal attenuation of the target path; the target path comprises a plurality of target road sections, the pheromone accumulated on each target road section is the maximum value of the pheromones accumulated on a plurality of candidate road sections corresponding to each target road section, and the candidate road sections corresponding to one road section comprise the road sections starting from the starting point of the road section;

and determining the global attenuation of the ray tracking model according to the vertical attenuation and the horizontal attenuation.

2. The attenuation determination method of claim 1, wherein the determining a pheromone expectation table corresponding to the ray tracing model comprises:

performing multiple iterative training on the multiple paths in the ray tracking model based on a preset ant colony algorithm to obtain the pheromone expectation list;

when the current iterative training is the first iterative training in the multiple iterative training, the pheromones accumulated on the road sections included by the multiple paths in the ray tracing model are preset initial values;

when the current iterative training is non-first iterative training in the multiple iterative training, determining, for a first road segment on a first road segment in the current iterative training, the pheromone accumulated by the first road segment in the last iterative training, the pheromone accumulated by a second road segment in the last iterative training, the pheromone obtained by the first road segment in a single training in the last iterative training, and the pheromone accumulated by the first road segment in the last iterative training, the pheromone accumulated by the first road segment in the current iterative training, and obtaining the pheromone accumulated on a road segment included by the multiple paths in the ray tracing model; the first path is any one of the paths, the first road section is any one road section on the first path, and the second road section is a road section behind the first road section.

3. The attenuation determination method of claim 2, wherein determining the first path in the current iteration of training comprises:

starting from the starting point of the first road section, determining the first road section from a plurality of candidate road sections corresponding to the first road section according to the exploration probability of ants in the ant colony algorithm to obtain the first path;

when the exploration probability is smaller than or equal to a preset probability, the pheromone of the first road segment accumulated in the last iterative training is the maximum value of the pheromones accumulated in the last iterative training of a plurality of candidate road segments corresponding to the first road segment; and under the condition that the exploration probability is greater than the preset probability, the first road section is any one of a plurality of candidate road sections corresponding to the first road section.

4. The attenuation determination method according to claim 2 or 3, wherein determining the pheromone obtained by a single training of the first segment comprises:

under the condition that the terminal point of the first road section is the receiving point, determining the pheromone obtained by single training of the first road section according to the main line-of-sight propagation attenuation of the first road section, the diffraction loss of the first road section and the reflection loss of the first road section; the pheromone obtained by the single training of the first road section is inversely related to the sum of the main line-of-sight propagation attenuation of the first road section, the diffraction loss of the first road section and the reflection loss of the first road section;

5. The attenuation determination method of claim 1, wherein determining a global attenuation of the ray tracing model from the vertical attenuation and the horizontal attenuation comprises:

determining a minimum of the vertical attenuation and the horizontal attenuation as a global attenuation of the ray tracing model.

6. An attenuation determination apparatus, for determining a global attenuation of a ray tracing model, the ray tracing model comprising a transmission point, a reception point and a plurality of obstacle points; the device comprises a determining unit and an acquiring unit;

the determination unit is used for determining the vertical attenuation of the ray tracing model;

the determining unit is further configured to determine an pheromone expectation table corresponding to the ray tracing model; the pheromone expectation table comprises pheromones accumulated on road sections included by a plurality of paths in the ray tracing model, each path comprises a road section through which a ray passes from the emitting point to the receiving point through different barrier points, and the pheromone is inversely related to path loss;

the acquiring unit is used for acquiring a target path from the pheromone expectation table after the determining unit determines the pheromone expectation table; the target path comprises a plurality of target road sections, the pheromone accumulated on each target road section is the maximum value of the pheromones accumulated on a plurality of candidate road sections corresponding to each target road section, and the plurality of candidate road sections corresponding to one road section comprise road sections starting from the starting point of the one road section;

the determining unit is further configured to determine a horizontal attenuation of the target path after the acquiring unit acquires the target path;

the determining unit is further configured to determine a global attenuation of the ray tracing model according to the vertical attenuation and the horizontal attenuation.

7. The attenuation determination apparatus according to claim 6, wherein the determination unit is specifically configured to:

when the current iterative training is the first iterative training in the multiple iterative training, the pheromones accumulated on the road sections included by the paths in the ray tracing model are preset initial values;

when the current iterative training is not the first iterative training in the multiple iterative training, for a first road section on a first path in the current iterative training, determining the pheromone accumulated by the first road section in the current iterative training according to the pheromone accumulated by the first road section in the previous iterative training, the pheromone accumulated by a second road section in the previous iterative training, the pheromone obtained by the first road section in the previous iterative training in a single training, and the pheromone accumulated by the first path in the previous iterative training, so as to obtain the pheromone accumulated on the road section included by the multiple paths in the ray tracing model; the first path is any one of the paths, the first road section is any one road section on the first path, and the second road section is a road section behind the first road section.

8. The attenuation determination apparatus according to claim 7, wherein in the current iteration training, the determination unit is specifically configured to:

9. The attenuation determination apparatus according to claim 7 or 8, characterized in that the determination unit is specifically configured to:

under the condition that the terminal point of the first road section is the receiving point, determining the pheromone obtained by single training of the first road section according to the main line-of-sight propagation attenuation of the first road section, the diffraction loss of the first road section and the reflection loss of the first road section; the pheromone obtained by the first road section through single training is inversely related to the sum of the main sight distance propagation attenuation of the first road section, the diffraction loss of the first road section and the reflection loss of the first road section;

10. The attenuation determination apparatus according to claim 6, wherein the determination unit is specifically configured to:

11. An electronic device, comprising:

a processor;

a memory for storing the processor-executable instructions;

wherein the processor is configured to execute the instructions to implement the method of any one of claims 1 to 5.

12. A computer-readable storage medium, wherein computer-executable instructions stored in the computer-readable storage medium, when executed by a processor of an electronic device, enable the electronic device to perform the method of any of claims 1-5.