Intelligent metasurface topological structure design method and device, equipment and medium

Abstract

The invention provides an intelligent metasurface topological structure design method and device, equipment and a medium. The intelligent metasurface topological structure design method comprises the steps that an intelligent metasurface unit initial model is established; adding a plurality of discrete patches on the metal patch layer, and establishing a reflection coefficient model of the intelligent metasurface unit initial model; sequentially reducing the number of rows or columns from the maximum number of rows and columns, and constructing different topological structures; constructing an objective function based on the reflection coefficient, screening the topological structures by adopting an optimization algorithm, and judging whether the optimized objective function of each topological structure meets a design requirement or not until the topological structure of the minimum design region is obtained; optimizing the topological structure of the minimum design area by using an optimization objective function combined with the number of discrete patches in the topological structure; and removing discrete patches which are not connected, and adjusting the position relationship between the patches to obtain the intelligent metasurface unit. According to the invention, adaptive miniaturization can be carried out on the intelligent metasurface unit under the condition that the working effect is not influenced.

Description

Technical Field

[0001] The present invention relates to the field of electromagnetic supersurface technology, and in particular to a method, device, equipment and medium for designing a topological structure of an intelligent supersurface. Background Art

[0002] Smart metasurface is an advanced artificial electromagnetic structure that can precisely manipulate the amplitude, phase, polarization and frequency of incident electromagnetic waves to achieve dynamic control of electromagnetic waves. Smart metasurfaces have a wide range of applications, including beam refraction, electromagnetic stealth, filtering, wireless communications and holographic imaging. The miniaturization of smart metasurfaces is an important development direction in the current wireless communication field. Miniaturized smart metasurfaces can integrate multi-band reflective surfaces on the same substrate. This integrated design not only saves valuable space resources, but also reduces the complexity and cost of the system. In addition, miniaturized smart metasurfaces can improve the performance of wireless communication systems, especially in high-frequency communications. They solve the problem of signal blind area coverage by constructing virtual line-of-sight paths, provide blind area communication and perception services, and provide additional paths to achieve signal enhancement and expand the system coverage radius.

[0003] At present, there are two main methods for designing miniaturized smart metasurfaces. The first is to explore the application of equivalent circuit models in the design of smart metasurfaces. This method simplifies the design process by converting complex electromagnetic problems into circuit problems, but it is difficult to obtain an accurate physical model for complex smart metasurfaces. The second is a smart metasurface design method based on deep learning. This method uses deep learning technology to establish the correspondence between the metasurface structure parameters and its electromagnetic response, so as to realize the rapid design of two common types of metasurfaces: continuous parameter structures and digital coding structures. However, since the deep learning method requires the use of electromagnetic simulation samples for modeling, it is difficult to fundamentally reduce the electromagnetic simulation cost used in the design of smart metasurfaces.

[0004] Therefore, a miniaturized intelligent metasurface design method is urgently needed to overcome the technical problems existing in the existing technology. Summary of the invention

[0005] In view of the defects of the prior art, the present invention provides a method, device, equipment and medium for designing a smart metasurface topological structure.

[0006] To achieve the above purpose, the technical solution adopted by the present invention is as follows: In one aspect, the present invention provides a method for designing a topological structure of an intelligent supersurface, comprising the following steps: S1. Establish an initial model of the smart metasurface unit, including a metal patch layer, a dielectric layer, and a metal bottom plate ground layer; S2. Add multiple discrete patches on the metal patch layer and use a multi-port network to establish the reflection coefficient model of the initial model of the smart metasurface unit:

[0007] in, is the reflection coefficient function obtained using a multi-port network; and are the internal discrete port vector and active device parameter vector respectively; It is a multi-port network model; is the load impedance of the internal discrete port; is the impedance matrix of multiple ports; is the load impedance of the external electromagnetic wave port; S3, traversing the number of rows and columns of discrete patches, reducing the number of rows or columns in sequence from the maximum number of rows and columns, and constructing different topological structures of smart metasurface units; S4. Based on the reflection coefficient function, the objective function is constructed using the phase and amplitude of different working states, and the topological structure is screened by the optimization algorithm to minimize the optimization objective function. The objective function is:

[0008] The optimization process is defined as:

[0009] in, and are the internal discrete port vector and active device parameter vector respectively; and are the optimal internal discrete port vector and the optimal active device parameter vector respectively; and are the weight coefficients of the phase constraint and the amplitude constraint in the objective function respectively; For the The phase of a working state; For the ideal The phase of a working state; is a comparison function used to find and The minimum value between For the optimized The amplitude of a working state; For the The ideal amplitude of a working state, The value is 3; S5, judging whether the optimization objective function of each topological structure meets the design requirements, if so, reducing the design area size of the topological structure; if not, expanding the design area size of the topological structure; and returning to S4 after correcting the design area size of the topological structure according to the judgment, until a topological structure with a minimum design area is obtained; S6. Using the phase and amplitude of different working states and the number of discrete patches in the topological structure, an optimization objective function combining the number of discrete patches in the topological structure is constructed to optimize the topological structure of the minimum design area. The optimization objective function combining the number of discrete patches in the topological structure is:

[0010] The optimization process is defined as:

[0011] in, is the weight coefficient of the miniaturization function in the objective function; for The sum of the elements with value "1" in ; S7. Analyze the current distribution of the topological structure of the minimum design area after optimization, remove unconnected discrete patches, adjust the positional relationship between patches, and obtain the intelligent metasurface unit.

[0012] Furthermore, in the initial model of the intelligent super surface unit, the period length of the intelligent super surface unit is Calculated according to the following formula:

[0013] in, is the speed of light in a vacuum; is the maximum optimizable operating frequency.

[0014] Furthermore, the discrete patch is a square patch, and the length of the discrete patch is K / 20 to K / 30.

[0015] Further, in S2, the use of a multi-port network to establish a reflection coefficient model of the initial model of the smart metasurface unit comprises the following steps: Determine the spacing between patches based on the patch length and cycle length; An external electromagnetic wave port is added to the initial structure of the smart metasurface unit, and an internal discrete port is added between discrete patches. The impedance parameters of the external electromagnetic wave port and the internal discrete port are extracted using full-wave electromagnetic simulation to obtain the multi-port impedance matrix:

[0016] in, is the self-impedance between the same internal discrete ports; , Internal discrete port and external electromagnetic wave port The equivalent impedance between and Indicates direction; is the self-impedance between the same external electromagnetic wave ports; Construct a reflection coefficient model based on a multi-port impedance matrix.

[0017] Furthermore, the use of an optimization algorithm to screen the topological structure includes: Evaluate the electromagnetic performance of each topology based on reflection coefficient, phase shift range, and loss values; A topology structure with a reflection coefficient less than -3dB in the operating frequency range, a phase shift range of 0~315°, and a loss value of 0.002~0.0128 is selected.

[0018] Furthermore, the design requirements that the optimization objective function needs to meet are: The sum of the differences between the optimized value and the ideal value of each parameter in the optimization objective function does not exceed 30.

[0019] Furthermore, the optimization objective of the optimization objective function of the number of discrete patches in the combined topological structure is: Optimizing the objective function The function value is less than 30, or the number of iterations exceeds the set value.

[0020] On the other hand, the present invention provides an intelligent supersurface topological structure design device, comprising: The first module is used to establish the initial model of the smart metasurface unit, including the metal patch layer, the dielectric layer and the metal bottom plate ground layer; The second module is used to add multiple discrete patches on the metal patch layer and use a multi-port network to establish the reflection coefficient model of the initial model of the smart metasurface unit:

[0021] in, is the reflection coefficient function obtained using a multi-port network; and are the internal discrete port vector and active device parameter vector respectively; It is a multi-port network model; is the load impedance of the internal discrete port; is the impedance matrix of multiple ports; is the load impedance of the external electromagnetic wave port; The third module is used to traverse the number of rows and columns of discrete patches, reduce the number of rows or columns in sequence starting from the maximum number of rows and columns, and construct different topological structures of smart metasurface units; The fourth module is used to construct an objective function based on the reflection coefficient function using the phase and amplitude of different working states, and to screen the topological structure using an optimization algorithm to minimize the optimization objective function. The objective function is:

[0022] The optimization process is defined as:

[0023] in, and are the internal discrete port vector and active device parameter vector respectively; and are the optimal internal discrete port vector and the optimal active device parameter vector respectively; and are the weight coefficients of the phase constraint and the amplitude constraint in the objective function respectively; For the The phase of a working state; For the ideal The phase of a working state; is a comparison function used to find and The minimum value between For the optimized The amplitude of a working state; For the i The ideal amplitude of a working state, The value is 3; The fifth module is used to determine whether the optimization objective function of each topological structure meets the design requirements. If so, the design area size of the topological structure is reduced; if not, the design area size of the topological structure is expanded; after the design area size of the topological structure is corrected according to the judgment, the fourth module is returned until the topological structure with the smallest design area is obtained; The sixth module is used to use the phase and amplitude of different working states and the number of discrete patches in the topological structure to construct an optimization objective function combined with the number of discrete patches in the topological structure, and optimize the topological structure of the minimum design area. The optimization objective function combined with the number of discrete patches in the topological structure is:

[0024] The optimization process is defined as:

[0025] in, is the weight coefficient of the miniaturization function in the objective function; for The sum of the elements with value "1" in ; The seventh module is used to analyze the current distribution of the topological structure of the minimum design area after optimization, remove unconnected discrete patches, adjust the positional relationship between patches, and obtain the intelligent metasurface unit.

[0026] On the other hand, the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the intelligent metasurface topological structure design method when executing the computer program.

[0027] On the other hand, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method for designing a topological structure of an intelligent metasurface.

[0028] Compared with the prior art, the beneficial effects of the present invention are: The intelligent super surface topological structure design method provided by the present invention uses a multi-port microwave network to realize the miniaturization of the intelligent super surface unit, thereby shortening the design cycle. Specifically, by adding an external electromagnetic wave port to the intelligent super surface unit and adding an internal discrete port between discrete patches, a multi-port network model is constructed to obtain a multi-port impedance matrix of the intelligent super surface unit, and a reflection coefficient model of the initial model of the intelligent super surface unit is constructed based on the obtained impedance matrix, and an objective function is constructed and optimized by an optimization algorithm to achieve a preliminary screening of the topological structure of the intelligent super surface unit; then the electromagnetic response performance of the screened intelligent super surface unit is verified by optimizing the objective function, and the design area size of the topological structure is adaptively increased or decreased according to whether the electromagnetic response performance meets the design requirements, and the electromagnetic response performance of the adaptively modified intelligent super surface unit is verified again, until an intelligent super surface with a minimum design area topological structure that meets the design requirements is obtained. On the basis of the intelligent super surface with a minimum design area topological structure, the number of discrete patches is optimized again, the unconnected discrete patches are removed, and the arrangement spacing of the remaining patches is adjusted, so as to obtain the desired intelligent super surface.

[0029] The intelligent metasurface topological structure design method provided by the present invention can adaptively miniaturize the intelligent metasurface unit without affecting the working effect, reduce the number of surface patches of the intelligent metasurface unit, and reduce the space cost of the design. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying creative work.

[0031] Figure 1 A flow chart of a method for designing a topological structure of an intelligent metasurface provided by an embodiment; Figure 2 An equivalent model diagram of a multi-port microwave network provided by an embodiment; Figure 3 A schematic diagram of an initial model of a smart metasurface unit provided by an embodiment; Figure 4 A diagram of a smart metasurface unit structure of a minimum design area topology provided by an embodiment; Figure 5 A structural diagram of a miniaturized intelligent metasurface unit provided by an embodiment; Figure 6 Electromagnetic response diagrams of eight phase states obtained by electromagnetic simulation of an intelligent metasurface with an unoptimized topological structure in a minimum design area provided in an embodiment; Figure 7 Electromagnetic response diagrams of eight phase states obtained by electromagnetic simulation of an intelligent metasurface after optimization of the minimum design area topology structure provided in an embodiment. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0033] Reference Figure 1 , an embodiment provides a method for designing a topological structure of an intelligent metasurface, comprising the following steps: S1. Establish an initial model of the smart metasurface unit, including a metal patch layer, a dielectric layer, and a metal bottom plate ground layer; S2, adding multiple discrete patches on the metal patch layer, and using a multi-port network to establish a reflection coefficient model of the initial model of the smart metasurface unit; Reflection coefficient model of the initial model of the smart metasurface unit:

[0034] in, is the reflection coefficient function obtained using a multi-port network; and are the internal discrete port vector and active device parameter vector respectively; It is a multi-port network model; is the load impedance of the internal discrete port; is the impedance matrix of multiple ports; is the load impedance of the external electromagnetic wave port; S3, traversing the number of rows and columns of discrete patches, reducing the number of rows or columns in sequence from the maximum number of rows and columns, and constructing different topological structures of smart metasurface units; S4. Based on the reflection coefficient function, the objective function is constructed using the phase and amplitude of different working states, and the topological structure is screened by the optimization algorithm to minimize the optimization objective function. The objective function is:

[0035] The optimization process is defined as:

[0036] in, and are the internal discrete port vector and active device parameter vector respectively; and are the optimal internal discrete port vector and the optimal active device parameter vector respectively; and are the weight coefficients of the phase constraint and the amplitude constraint in the objective function respectively; For the The phase of a working state; For the ideal The phase of a working state; is a comparison function used to find and The minimum value between For the optimized The amplitude of a working state; For the The ideal amplitude of a working state, The value is 3; S5, judging whether the optimization objective function of each topological structure meets the design requirements, if so, reducing the design area size of the topological structure; if not, expanding the design area size of the topological structure; and returning to S4 after correcting the design area size of the topological structure according to the judgment, until a topological structure with a minimum design area is obtained; S6. Using the phase and amplitude of different working states and the number of discrete patches in the topological structure, an optimization objective function combining the number of discrete patches in the topological structure is constructed to optimize the topological structure of the minimum design area. The optimization objective function combining the number of discrete patches in the topological structure is:

[0037] The optimization process is defined as:

[0038] in, is the weight coefficient of the miniaturization function in the objective function; for The sum of the elements with value "1" in ; S7. Analyze the current distribution of the topological structure of the minimum design area after optimization, remove unconnected discrete patches, adjust the positional relationship between patches, and obtain the intelligent metasurface unit.

[0039] In the initial model of the smart super surface unit, the period length of the smart super surface unit is Calculated according to the following formula:

[0040] in, is the speed of light in a vacuum; is the maximum optimizable operating frequency.

[0041] In one embodiment, referring to Figure 3 , the period length of the initial model of the smart metasurface unit The thickness of the dielectric layer is 3.3 mm, and the dielectric constant is 2.65. The operating frequency of the smart metasurface is 2.6 GHz. The metal patch layer is composed of 56 rectangular metal patches of the same size arranged at a certain interval and symmetrically arranged along the Y axis.

[0042] The discrete patch is a square patch, and the length of the discrete patch is K / 20 to K / 30, in this embodiment, the length of the discrete patch is 2 mm, and the initial patch spacing is 0.3 mm.

[0043] Reference Figure 2 The method of using a multi-port network to establish a reflection coefficient model of an initial model of a smart metasurface unit comprises the following steps: Determine the spacing between patches based on the patch length and cycle length; An external electromagnetic wave port is added to the initial structure of the smart metasurface unit, and an internal discrete port is added between discrete patches. The impedance parameters of the external electromagnetic wave port and the internal discrete port are extracted using full-wave electromagnetic simulation to obtain the multi-port impedance matrix:

[0044] in, is the self-impedance between the same internal discrete ports; , Internal discrete port and external electromagnetic wave port The equivalent impedance between and Indicates direction; is the self-impedance between the same external electromagnetic wave ports; Construct a reflection coefficient model based on a multi-port impedance matrix:

[0045] in, is the reflection coefficient function obtained using a multi-port network; and are the internal discrete port vector and active device parameter vector respectively; It is a multi-port network model; is the load impedance of the internal discrete port; is the impedance matrix of multiple ports; is the load impedance of the external electromagnetic wave port, that is, the characteristic impedance of the electromagnetic wave in a vacuum.

[0046] According to the relationship between the period length of the smart metasurface unit and the size of the discrete patches, it is determined that the number of rows and the number of columns of the discrete patches in the smart metasurface unit are 8 and 9 respectively.

[0047] The number of rows and columns of the working discrete patches is traversed from the largest number to the smallest number, and the number of rows or columns is reduced in sequence from the largest number of rows and columns to construct the topological structures of different intelligent metasurface units. In the traversal process, based on the reflection coefficient function, the objective function is constructed using the phase and amplitude of different working states, and the topological structure is screened using the optimization algorithm to minimize the optimization objective function, which is:

[0048] The optimization process is defined as:

[0049] in, and are the internal discrete port vector and active device parameter vector respectively; and are the optimal internal discrete port vector and the optimal active device parameter vector respectively; and are the weight coefficients of the phase constraint and the amplitude constraint in the objective function respectively; For the The phase of a working state; For the ideal The phase of a working state; is a comparison function used to find and The minimum value between For the optimized i The amplitude of a working state; For the i The ideal amplitude of a working state, The value is 3; in this embodiment, 8 phase states of 0°, 45°, 90°, 135°, 180°, 225°, 270°, and 315° are selected as ideal phase states.

[0050] Evaluate the electromagnetic performance of each topology based on reflection coefficient, phase shift range, and loss values; A topology structure with a reflection coefficient less than -3dB in the operating frequency range, a phase shift range of 0~315°, and a loss value of 0.002~0.0128 is selected.

[0051] Determine whether the optimization objective function of each topological structure meets the design requirements. If so, reduce the design area size of the topological structure. Specifically, continue to reduce the number of rows and columns of the working discrete patches. If not, expand the design area size of the topological structure and increase the number of rows and columns of the working discrete patches. After correcting the design area size of the topological structure according to the judgment, return to calculate the optimization objective function of the topological structure, record the design area size of each topological structure that meets the design requirements, select the topological structure with the smallest design area, and refer to Figure 4 ; By using the phase and amplitude of different working states and the number of discrete patches in the topological structure, an optimization objective function combining the number of discrete patches in the topological structure is constructed to optimize the topological structure of the minimum design area. The optimization objective function combining the number of discrete patches in the topological structure is:

[0052] The optimization process is defined as:

[0053] in, is the weight coefficient of the miniaturization function in the objective function; for The sum of the elements with value "1" in ; By adding the number of discrete patches to the performance optimization of the smart metasurface unit, the number of open-circuit states in the internal discrete port vector is calculated and accumulated. By accumulating the value of the port vector, the number of "1" in the vector increases, that is, the number of ports in the "open-circuit" state increases, thereby obtaining more discrete patches that are not connected to the surrounding areas and deleting them to increase the degree of miniaturization.

[0054] The optimization objective of the optimization objective function of the number of discrete patches in the combined topological structure is: Optimizing the objective function The function value is less than 30, or the number of iterations exceeds the set value.

[0055] Reference Figure 5 , analyze the current distribution of the topological structure of the minimum design area after optimization, remove the unconnected discrete patches, adjust the positional relationship between the patches, and obtain the intelligent metasurface unit.

[0056] Reference Figure 6 , which are the electromagnetic response diagrams of eight phase states obtained from electromagnetic simulation of the smart metasurface with unoptimized topological structure in the minimum design area, refer to Figure 7 , which are the electromagnetic response diagrams of 8 phase states obtained by electromagnetic simulation of the intelligent metasurface after the topological structure of the minimum design area is optimized. Figure 6 It can be seen that due to the coupling effect between discrete patches, the simulation results have frequency deviation compared with the case where the discrete patches are not deleted. In order to reduce the frequency deviation effect, the lateral and longitudinal distances between discrete patches are adjusted to reduce the electromagnetic coupling between patches and ensure the performance of the smart metasurface unit, such as Figure 7 shown.

[0057] In one embodiment, a device for designing a topological structure of an intelligent metasurface is provided, comprising: The first module is used to establish the initial model of the smart metasurface unit, including the metal patch layer, the dielectric layer and the metal bottom plate ground layer; The second module is used to add multiple discrete patches on the metal patch layer and use a multi-port network to establish the reflection coefficient model of the initial model of the smart metasurface unit:

[0058] in, is the reflection coefficient function obtained using a multi-port network; and are the internal discrete port vector and active device parameter vector respectively; It is a multi-port network model; is the load impedance of the internal discrete port; is the impedance matrix of multiple ports; is the load impedance of the external electromagnetic wave port; The third module is used to traverse the number of rows and columns of discrete patches, reduce the number of rows or columns in sequence starting from the maximum number of rows and columns, and construct different topological structures of smart metasurface units; The fourth module is used to construct an objective function based on the reflection coefficient function using the phase and amplitude of different working states, and to screen the topological structure using an optimization algorithm to minimize the optimization objective function. The objective function is:

[0059] The optimization process is defined as:

[0060] in, and are the internal discrete port vector and active device parameter vector respectively; and are the optimal internal discrete port vector and the optimal active device parameter vector respectively; and are the weight coefficients of the phase constraint and the amplitude constraint in the objective function respectively; For the The phase of a working state; For the ideal The phase of a working state; is a comparison function used to find and The minimum value between For the optimized The amplitude of a working state; For the The ideal amplitude of a working state, The value is 3; The fifth module is used to determine whether the optimization objective function of each topological structure meets the design requirements. If so, the design area size of the topological structure is reduced; if not, the design area size of the topological structure is expanded; after the design area size of the topological structure is corrected according to the judgment, the fourth module is returned until the topological structure with the smallest design area is obtained; The sixth module is used to use the phase and amplitude of different working states and the number of discrete patches in the topological structure to construct an optimization objective function combined with the number of discrete patches in the topological structure, and optimize the topological structure of the minimum design area. The optimization objective function combined with the number of discrete patches in the topological structure is:

[0061] The optimization process is defined as:

[0062] in, is the weight coefficient of the miniaturization function in the objective function; for The sum of the elements with value "1" in ; The seventh module is used to analyze the current distribution of the topological structure of the minimum design area after optimization, remove unconnected discrete patches, adjust the positional relationship between patches, and obtain the intelligent metasurface unit.

[0063] On the other hand, the present invention provides a computer device, including a memory and a processor, the memory stores a computer program, and the processor implements the steps of the intelligent supersurface topological structure design method provided in any of the above embodiments when executing the computer program. The computer device may be a server. The computer device includes a processor, a memory, a network interface and a database connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store sample data. The network interface of the computer device is used to communicate with an external terminal through a network connection.

[0064] On the other hand, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the intelligent metasurface topological structure design method provided in any of the above embodiments.

[0065] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0066] Matters not covered by the present invention are known technologies.

[0067] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0068] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention. It should be pointed out that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

[0069] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for designing a topological structure of an intelligent metasurface, characterized in that: The following steps are involved: S1. Establish an initial model of the smart metasurface unit, including a metal patch layer, a dielectric layer, and a metal bottom plate ground layer; S2. Add multiple discrete patches on the metal patch layer and use a multi-port network to establish the reflection coefficient model of the initial model of the smart metasurface unit: in, is the reflection coefficient function obtained using a multi-port network; and are the internal discrete port vector and active device parameter vector respectively; It is a multi-port network model; is the load impedance of the internal discrete port; is the impedance matrix of multiple ports; is the load impedance of the external electromagnetic wave port; S3, traversing the number of rows and columns of discrete patches, reducing the number of rows or columns in sequence from the maximum number of rows and columns, and constructing different topological structures of smart metasurface units; S4. Based on the reflection coefficient function, the objective function is constructed using the phase and amplitude of different working states, and the topological structure is screened by the optimization algorithm to minimize the optimization objective function. The objective function is: The optimization process is defined as: in, and are the internal discrete port vector and active device parameter vector respectively; and are the optimal internal discrete port vector and the optimal active device parameter vector respectively; and are the weight coefficients of the phase constraint and the amplitude constraint in the objective function respectively; For the The phase of a working state; For the ideal The phase of a working state; is a comparison function used to find and The minimum value between For the optimized The amplitude of a working state; For the i The ideal amplitude of a working state, The value is 3; S5, judging whether the optimization objective function of each topological structure meets the design requirements, if so, reducing the design area size of the topological structure; if not, expanding the design area size of the topological structure; and returning to S4 after correcting the design area size of the topological structure according to the judgment, until a topological structure with a minimum design area is obtained; S6. Using the phase and amplitude of different working states and the number of discrete patches in the topological structure, an optimization objective function combining the number of discrete patches in the topological structure is constructed to optimize the topological structure of the minimum design area. The optimization objective function combining the number of discrete patches in the topological structure is: The optimization process is defined as: in, is the weight coefficient of the miniaturization function in the objective function; for The sum of the elements with "1" in ; S7. Analyze the current distribution of the topological structure of the minimum design area after optimization, remove unconnected discrete patches, adjust the positional relationship between patches, and obtain the intelligent metasurface unit.

2. The method for designing a topological structure of an intelligent supersurface according to claim 1, wherein: In the initial model of the smart super surface unit, the period length of the smart super surface unit is Calculated according to the following formula: in, is the speed of light in a vacuum; is the maximum optimizable operating frequency.

3. The method for designing a topological structure of an intelligent supersurface according to claim 1, wherein: The discrete patch is a square patch, and the length of the discrete patch is K / 20 to K / 30.

4. The method for designing a topological structure of an intelligent supersurface according to claim 1, wherein: In S2, the use of a multi-port network to establish a reflection coefficient model of an initial model of an intelligent metasurface unit comprises the following steps: Determine the spacing between patches based on the patch length and cycle length; An external electromagnetic wave port is added to the initial structure of the smart metasurface unit, and an internal discrete port is added between discrete patches. The impedance parameters of the external electromagnetic wave port and the internal discrete port are extracted using full-wave electromagnetic simulation to obtain the multi-port impedance matrix: in, is the self-impedance between the same internal discrete ports; , Internal discrete port and external electromagnetic wave port The equivalent impedance between and Indicates direction; is the self-impedance between the same external electromagnetic wave ports; Construct a reflection coefficient model based on a multi-port impedance matrix.

5. The method for designing a topological structure of an intelligent supersurface according to claim 1, wherein: The use of an optimization algorithm to screen the topological structure includes: Evaluate the electromagnetic performance of each topology based on reflection coefficient, phase shift range, and loss values; A topology structure with a reflection coefficient less than -3dB in the operating frequency range, a phase shift range of 0~315°, and a loss value of 0.002~0.0128 is selected.

6. The method for designing a topological structure of an intelligent supersurface according to claim 1, wherein: The design requirements that the optimization objective function needs to meet are: The sum of the differences between the optimized value and the ideal value of each parameter in the optimization objective function does not exceed 30.

7. The method for designing a topological structure of an intelligent supersurface according to claim 1, wherein: The optimization objective of the optimization objective function of the number of discrete patches in the combined topological structure is: Optimizing the objective function The function value is less than 30, or the number of iterations exceeds the set value.

8. Intelligent super surface topological structure design device, characterized in that: include: The first module is used to establish the initial model of the smart metasurface unit, including the metal patch layer, the dielectric layer and the metal bottom plate ground layer; The second module is used to add multiple discrete patches on the metal patch layer and use a multi-port network to establish the reflection coefficient model of the initial model of the smart metasurface unit: in, is the reflection coefficient function obtained using a multi-port network; and are the internal discrete port vector and active device parameter vector respectively; It is a multi-port network model; is the load impedance of the internal discrete port; is the impedance matrix of multiple ports; is the load impedance of the external electromagnetic wave port; The third module is used to traverse the number of rows and columns of discrete patches, reduce the number of rows or columns in sequence starting from the maximum number of rows and columns, and construct different topological structures of smart metasurface units; The fourth module is used to construct an objective function based on the reflection coefficient function using the phase and amplitude of different working states, and to screen the topological structure using an optimization algorithm to minimize the optimization objective function. The objective function is: The optimization process is defined as: in, and are the internal discrete port vector and active device parameter vector respectively; and are the optimal internal discrete port vector and the optimal active device parameter vector respectively; and are the weight coefficients of the phase constraint and the amplitude constraint in the objective function respectively; For the The phase of a working state; For the ideal The phase of a working state; is a comparison function used to find and The minimum value between For the optimized The amplitude of a working state; For the The ideal amplitude of a working state, The value is 3; The fifth module is used to determine whether the optimization objective function of each topological structure meets the design requirements. If so, the design area size of the topological structure is reduced; if not, the design area size of the topological structure is expanded; after the design area size of the topological structure is corrected according to the judgment, the fourth module is returned until the topological structure with the smallest design area is obtained; The sixth module is used to use the phase and amplitude of different working states and the number of discrete patches in the topological structure to construct an optimization objective function combined with the number of discrete patches in the topological structure, and optimize the topological structure of the minimum design area. The optimization objective function combined with the number of discrete patches in the topological structure is: The optimization process is defined as: in, is the weight coefficient of the miniaturization function in the objective function; for The sum of the elements with "1" in ; The seventh module is used to analyze the current distribution of the topological structure of the minimum design area after optimization, remove unconnected discrete patches, adjust the positional relationship between patches, and obtain the intelligent metasurface unit.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the intelligent supersurface topological structure design method as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a processor, the steps of the intelligent supersurface topological structure design method as described in any one of claims 1 to 7 are implemented.

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