Method and apparatus for analysing communication channel in consideration of material and contours of objects
A signal transmission characteristic analysis method for use in a wireless communication system and an apparatus thereof are provided. The method includes locating transmission and reception positions, checking at least one object on a transmission path of a signal from the transmission position to the reception position and material of the at least one object, and determining the signal transmission characteristic based on information on the material of the at least one object. The present disclosure relates to a communication method and system for converging a 5th-Generation (5G) communication system for supporting higher data rates beyond a 4th-Generation (4G) system with a technology for Internet of Things (IoT). The present disclosure may be applied to intelligent services based on 5G communication technology and IoT-related technology.
1. A method by a device for a wireless communication system, the method comprising:
obtaining, by a processor of the device, data associated with a material of an object in an area, wherein the data includes signal characteristic information of a category including the material;
processing, by the processor, a simulation for the area by identifying the category corresponding to the material of the object in the area and applying a transmission characteristic value of the identified category of the material to the object based on the data associated with the material; and
displaying, by the processor, a result of the simulation.
2. The method of claim 1 ,
wherein the signal characteristic information is determined based on a contour of the object, and
wherein the contour includes a pattern with a groove appearing on a surface of the object.
3. The method of claim 1 , further comprising:
identifying the object from an image for the area;
identifying the material of the object; and
mapping the object and the material to a 3-dimensional map for the area based on at least one of a shooting location, a direction, or an angle of the image.
4. The method of claim 3 , wherein the identifying the material of the object further comprises:
identifying, by the processor of the device, the material based on the image and learned information related to the image,
wherein the learned information is acquired, by the processor of the device, using deep learning-based computer vision technology.
5. The method of claim 3 , wherein the identifying of the material of the object further comprises:
identifying at least one element from the image based on at least one of a color, a light and darkness, a reflectivity, a relative location relationship, or an arrangement of elements, and
identifying a material of each of the at least one element based on an analyzing result for a plurality of images stored in a memory.
6. The method of claim 1 ,
wherein the signal characteristic information is determined based on an incidence angle of a signal to the object and attenuation information of the signal, and
wherein the signal characteristic information comprises at least one of a permittivity, a transmittivity, a diffraction coefficient, or a reflexibility of the material.
7. The method of claim 1 ,
wherein at least one material having a reflection characteristic difference less than a threshold is included in the category, and
wherein the signal characteristic information of the category is determined by an average value of characteristics of the at least one material included in the category.
8. The method of claim 7 ,
wherein the average value is determined by applying different weights to the characteristics of the at least one material included in the category, and
wherein a higher weight is applied to a material appearing more frequently in the area.
9. The method of claim 1 ,
wherein the processing of the simulation for the area further comprises identifying a location of a transmission position and a location of a reception position for the simulation, and
wherein the simulation is processed for a transmission path of a signal from the transmission position to the reception position.
10. The method of claim 1 , further comprising:
obtaining data associated with a shape of the object in the area,
wherein the simulation is processed by using the data associated with the material and the data associated with the shape.
11. A device for a wireless communication system, the device comprising;
a memory; and
at least one processor configured to:
obtain data associated with a material of an object in an area, wherein the data includes a signal characteristic information of a category including the material,
process a simulation for the area by identifying the category corresponding to the material of the object in the area and applying a transmission characteristic value of the identified category of the material to the object based on the data associated with the material, and
display a result of the simulation.
12. The device of claim 11 ,
wherein the signal characteristic information is determined based on a contour of the object, and
wherein the contour includes a pattern with a groove appearing on a surface of the object.
13. The device of claim 11 , wherein the at least one processor is further configured to:
identify the object from an image for the area,
identify the material of the object, and
map the object and the material to a 3-dimensional map for the area based on at least one of a shooting location, a direction, or an angle of the image.
14. The device of claim 13 ,
wherein the at least one processor is further configured to:
identify the material based on the image and learned information related to the image, and
wherein the learned information is acquired using deep learning-based computer vision technology.
15. The device of claim 13 , wherein the at least one processor is further configured to:
identify at least one element from the image based on at least one of a color, a light and darkness, a reflectivity, a relative location relationship, or an arrangement of elements, and
identify a material of each of the at least one element based on an analyzing result for a plurality of images stored in the memory.
16. The device of claim 11 ,
wherein the signal characteristic information is determined based on an incidence angle of a signal to the object and attenuation information of the signal, and
wherein the signal characteristic information comprises at least one of a permittivity, a transmittivity, a diffraction coefficient, or a reflexibility of the material.
17. The device of claim 11 ,
wherein at least one material having a reflection characteristic difference less than a threshold is included in the category, and
wherein the signal characteristic information of the category is determined by an average value of characteristics of the at least one material included in the category.
18. The device of claim 17 ,
wherein the average value is determined by applying different weights to the characteristics of the at least one material included in the category, and
wherein a higher weight is applied to a material appearing more frequently in the area.
19. The device of claim 11 ,
wherein the at least one processor is further configured to identify a location of a transmission position and a location of a reception position for the simulation, and
wherein the simulation is processed for a transmission path of a signal from the transmission position to the reception position.
20. The device of claim 11 ,
wherein the at least one processor is further configured to obtain data associated with a shape of the object in the area, and
wherein the simulation is processed by using the data associated with the material and the data associated with the shape.