Low complexity multi-intelligent metasurface dynamic threshold phase shift design method

Abstract

The application discloses a low-complexity multi-intelligent metasurface dynamic threshold phase shift design method, belongs to the wireless communication field, and is used for a communication system in which a single antenna is configured at a sending end and a receiving end and multiple intelligent metasurfaces are deployed, the electromagnetic wave path of each section of electromagnetic wave from the sending end to the receiving end through each intelligent metasurface is calculated, the ideal continuous phase shift of each unit on each intelligent metasurface is calculated according to the electromagnetic wave path, one of the intelligent metasurfaces is selected, the optimal quantization threshold of the intelligent metasurface is obtained through exhaustive search, the optimal quantization threshold of other intelligent metasurfaces is calculated according to the optimal quantization threshold of the intelligent metasurface and the electromagnetic wave path through other intelligent metasurfaces, and the ideal continuous phase shift of each unit is converted into discrete phase shift by using the optimal quantization threshold of each intelligent metasurface. The method can guarantee high received signal energy with low phase shift design complexity, effectively improves the channel quality of the multi-intelligent metasurface assisted single-antenna communication system, and has strong practicability and high effectiveness.

Description

Technical Field

[0001] This invention relates to the field of wireless communication technology, and in particular to a low-complexity multi-intelligent metasurface dynamic threshold phase shift design method. Background Technology

[0002] In recent years, with the commercial deployment of fifth-generation (5G) mobile communication technology, academics worldwide have begun research on sixth-generation (6G) mobile communication technology. During this process, scholars have proposed various communication technologies, such as massive MIMO and relay transmission, with the aim of improving channel quality. However, in practical system design, these technologies all have inherent drawbacks, such as high power consumption, high hardware complexity, and high cost.

[0003] With the rapid development of metamaterials and radio frequency microelectromechanical systems (MEMS), smart metasurfaces are expected to find widespread application in future wireless communication systems. Smart metasurfaces are a new type of controllable, low-power device proposed in recent years for wireless communication systems. They are widely considered a key technology for sixth-generation mobile communication systems and may serve as an alternative to large-scale multiple-input multiple-output (MIMO) systems. Smart metasurfaces are equipped with a large number of electromagnetically tunable reflective elements, which can be implemented using inexpensive antennas or metamaterials. These elements can control the amplitude and phase of electromagnetic waves in real time without generating signals themselves. The emergence of smart metasurface-assisted wireless communication systems has improved the spectral efficiency, energy efficiency, and communication range of wireless communication systems, bringing revolutionary changes to traditional wireless communication. Furthermore, the low power consumption, low cost, and programmability of smart metasurfaces meet the current requirements for green communication and sustainable development. However, the coverage area and gain performance of a single smart metasurface-assisted wireless communication system are limited. Therefore, it is necessary to study phase-shift design methods for multi-smart metasurface-assisted wireless communication systems.

[0004] Currently, phase shift design methods for multi-intelligent metasurface-assisted wireless communication systems are still in the exploratory stage. Existing phase shift design algorithms have several drawbacks: 1) they only focus on continuous phase shift design, applicable only to ideal conditions and neglecting discrete phase shifts in practical system design; 2) their algorithm complexity is too high, for example, the complexity of the traversal dynamic threshold phase shift design method increases exponentially with the number of intelligent metasurfaces; and 3) while possessing low complexity, they cannot guarantee system gain performance. Therefore, for multi-intelligent metasurface-assisted single-antenna systems, a discrete phase shift design method that achieves high communication performance with low computational complexity and high practicality deserves further exploration. Summary of the Invention

[0005] This invention provides a low-complexity multi-intelligent metasurface dynamic threshold phase shift design method, which can guarantee high received signal energy with low phase shift design complexity, effectively improve the channel quality of multi-intelligent metasurface assisted single-antenna communication systems, and has strong practicality and high effectiveness.

[0006] A first aspect of this invention provides a low-complexity multi-intelligent metasurface dynamic threshold phase shift design method. A single antenna is configured at both the transmitter and receiver, and multiple intelligent metasurfaces are deployed between the transmitter and receiver. Each intelligent metasurface includes multiple reflecting elements, and each reflecting element has an independent phase shift. The low-complexity multi-intelligent metasurface dynamic threshold phase shift design method includes the following steps:

[0007] Step S1: Calculate the electromagnetic wave path from the transmitter to the receiver through each smart metasurface based on the information from the transmitter, receiver, and each smart metasurface.

[0008] Step S2: Calculate the ideal continuous phase shift of each unit on each smart metasurface based on the electromagnetic wave path length of each segment.

[0009] Step S3: Randomly select any smart metasurface and obtain the optimal quantization threshold of the smart metasurface through traversal search;

[0010] Step S4: Calculate the optimal quantization threshold of other smart metasurfaces based on the optimal quantization threshold of the smart metasurface and the electromagnetic wave path through other smart metasurfaces.

[0011] Step S5: The ideal continuous phase shift of each reflection unit is converted into a discrete phase shift using the optimal quantization threshold of each smart metasurface. The discrete phase shift obtained under the optimal quantization threshold is used as the configuration phase shift of the smart metasurface.

[0012] In one embodiment of the present invention, there are K smart metasurfaces, each smart metasurface consisting of M rows and N columns of reflective elements, each reflective element having a discrete phase shift resolution of q bits, and each reflective element having a 2 q The discrete phase shift set is ρ p Let p represent the p-th possible discrete phase shift, where p = 1, 2, ..., 2 q The relationship between the p-th discrete phase shift and the 1st discrete phase shift is: The calculation of the electromagnetic wave path from the transmitter to the receiver via each smart metasurface is based on information from the transmitter, receiver, and each smart metasurface, including:

[0013] For the k-th (k=1,...,K) intelligent metasurface, the distance between the transmitter and the reflective element at the m-th row and n-th column (m=1,...,M, n=1,...,N) is calculated. and the distance between the receiver and the reflective unit The formula is:

[0014]

[0015] in, and are the distances from the transmitter and receiver to the center of the k-th smart metasurface, respectively. and These are the elevation and azimuth angles of the transmitter relative to the center of the k-th smart metasurface, respectively. and d represents the elevation and azimuth angles of the receiver relative to the center of the k-th smart metasurface, respectively. x and d y These represent the lateral and longitudinal dimensions of each reflective unit of the smart metasurface.

[0016] In one embodiment of the present invention, calculating the ideal continuous phase shift of each unit on each smart metasurface based on the electromagnetic wave path lengths includes:

[0017] Calculate the ideal continuous phase shift matrix of a smart metasurface in Let K×M×N be a matrix, where the (k,m,n)th element is the ideal continuous phase shift φ of the reflection unit in the m-th row and n-th column of the k-th smart metasurface. k,m,n The calculation method is as follows:

[0018]

[0019] Where λ is the carrier wavelength, and the function mod(a1,a2) represents the operation of modulo a2 on variable a1.

[0020] In one embodiment of the present invention, any smart metasurface is randomly selected, and the optimal quantization threshold of the smart metasurface is obtained through a traversal search, including:

[0021] Step S301, let parameter τ = 1, initialize the number of search thresholds Q, performance index P0 = 0, γ a =0;

[0022] Step S302: Calculate the threshold γ = (τ-1)ε, where ε is the pre-set interval between adjacent thresholds;

[0023] Step S303: Based on the ideal continuous phase shift matrix and threshold γ of each reflective unit of the a-th smart metasurface, calculate the discrete phase shift Δ of each reflective unit of the a-th smart metasurface using the following formula. a,m,n (m=1,...,M, n=1,...,N):

[0024]

[0025] Step S304, calculate the performance index P1 at this time:

[0026]

[0027] in, and These are the angles between the main lobe directions of the transmitting and receiving antennas and the reflection unit in the m-th row and n-th column of the a-th smart metasurface, respectively. and These are the elevation angles of the m-th row and n-th column reflective unit of the a-th smart metasurface relative to the transmitter and receiver, respectively.

[0028] Step S305: If P1 > P0, then let P0 = P1 and γ a =γ;

[0029] Step S306: If τ < Q, then let τ = τ + 1 and proceed to step S302; otherwise, end the calculation and output the optimal quantization threshold γ of the a-th smart metasurface. a .

[0030] In one embodiment of the present invention, based on the optimal quantization threshold γ of the smart metasurface... a And by measuring the electromagnetic path length of other smart metasurfaces, the optimal quantization threshold γ for other smart metasurfaces is calculated. b The formula for calculating (b=1,...,K,b≠a) is:

[0031]

[0032] in, and are the distances from the transmitter and receiver to the center of the a-th smart metasurface, respectively. and , respectively, are the distances between the transmitter and receiver and the center of the b-th smart metasurface.

[0033] In one embodiment of the present invention, the ideal continuous phase shift of each reflective unit is converted into a discrete phase shift using the optimal quantization threshold of each smart metasurface, and the resulting discrete phase shift under the optimal quantization threshold is used as the configuration phase shift of the smart metasurface, including:

[0034] Based on the ideal continuous phase shift, the optimal quantization threshold γ is applied to the k-th smart metasurface. k This is quantized into a discrete phase shift matrix that can be configured in real-world conditions. Element Δ k,m,n The discrete phase shift of the m-th row and n-th column reflective unit of the k-th smart metasurface is calculated as follows:

[0035]

[0036] in,

[0037] The low-complexity multi-intelligent metasurface dynamic threshold phase shift design method of this invention has the following beneficial effects:

[0038] (1) This invention is applicable to a variety of communication scenarios and has universal applicability to phase shift alignment and beamforming problems in single-antenna wireless communication systems assisted by multiple intelligent metasurfaces;

[0039] (2) Threshold calculation method in this invention: Under ideal conditions, its system performance is close to the result of using ergonomic dynamic threshold phase design for each smart metasurface in the system; in actual communication environment, it is also close to the performance limit of smart metasurface beamforming in discrete domain.

[0040] (3) The discrete phase shift calculation method of the multi-intelligent metasurface designed in this invention has low complexity, with only the complexity of traversing and searching a single intelligent metasurface, thus ensuring its applicability in practical system design.

[0041] Compared to existing phase-shift design algorithms, the algorithm proposed in this invention reduces computational complexity while maintaining performance advantages, and still achieves high system performance in practical communication scenarios. Therefore, it is practical and efficient in multi-intelligent metasurface-assisted wireless communication systems.

[0042] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0043] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0044] Figure 1 A flowchart illustrating a low-complexity multi-intelligent metasurface dynamic threshold phase shift design method according to an embodiment of the present invention;

[0045] Figure 2 This is a flowchart illustrating a specific low-complexity multi-intelligent metasurface dynamic threshold phase shift design method according to an embodiment of the present invention. Detailed Implementation

[0046] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0047] Figure 1 This is a flowchart illustrating a low-complexity multi-intelligent metasurface dynamic threshold phase shift design method according to an embodiment of the present invention.

[0048] like Figure 1 As shown, this low-complexity multi-intelligent metasurface dynamic threshold phase shift design method is applicable to systems where the transmitter and receiver are each configured with a single antenna and multiple intelligent metasurfaces are deployed to assist communication. The method includes the following steps:

[0049] Step S1: Calculate the electromagnetic wave path from the transmitter to the receiver through each smart metasurface based on the information from the transmitter, receiver, and each smart metasurface.

[0050] In an embodiment of the invention, a single antenna is configured at both the transmitting and receiving ends, and K smart metasurfaces are deployed between the transmitting and receiving ends to assist communication; each deployed smart metasurface consists of M rows and N columns of reflective elements, and each element can be independently configured with a phase shift; each element has a discrete phase shift resolution of q bits, with a possible 2^32^23^2^ ... q The discrete phase shift set is Where ρ p Let p represent the p-th possible discrete phase shift, where p = 1, 2, ..., 2 q The relationship between the p-th discrete phase shift and the 1st discrete phase shift is: The value of ρ1 is determined by the hardware design of the smart metasurface.

[0051] Specifically, the electromagnetic wave path from the transmitter to the receiver via each smart metasurface is calculated based on information from the transmitter, receiver, and each smart metasurface, including:

[0052] For the k-th (k=1,...,K) intelligent metasurface, the distance between the transmitter and the reflective element at the m-th row and n-th column (m=1,...,M, n=1,...,N) is calculated. and the distance between the receiver and the reflective unit The formula is:

[0053]

[0054]

[0055] in and are the distances from the transmitter and receiver to the center of the k-th smart metasurface, respectively. and These are the elevation and azimuth angles of the transmitter relative to the center of the k-th smart metasurface, respectively. and d represents the elevation and azimuth angles of the receiver relative to the center of the k-th smart metasurface, respectively. x and d y These represent the lateral and longitudinal dimensions of each unit of the smart metasurface.

[0056] Step S2: Calculate the ideal continuous phase shift of each unit on each smart metasurface based on the path length of each electromagnetic wave segment.

[0057] In an embodiment of the present invention, the ideal continuous phase shift matrix of the intelligent metasurface is calculated. in Let K×M×N be a matrix, where the (k,m,n)th element is the ideal continuous phase shift φ of the reflection unit in the m-th row and n-th column of the k-th smart metasurface. k,m,n The calculation method is as follows:

[0058]

[0059] Where λ is the carrier wavelength, and the function mod(a1,a2) represents the operation of modulo a2 on variable a1.

[0060] Step S3: Randomly select any smart metasurface and obtain the optimal quantization threshold of the smart metasurface through traversal search.

[0061] In embodiments of the present invention, the specific components include:

[0062] Step S301, let parameter τ = 1, initialize the number of search thresholds Q, performance index P0 = 0, γ a =0;

[0063] Step S302: Calculate the threshold γ = (τ-1)ε, where ε is the pre-set interval between adjacent thresholds;

[0064] Step S303: Based on the ideal continuous phase shift matrix and threshold γ of each reflective unit of the a-th smart metasurface, calculate the discrete phase shift Δ of each reflective unit of the a-th smart metasurface using the following formula. a,m,n (m=1,...,M, n=1,...,N):

[0065]

[0066] Step S304, calculate the performance index P1 at this time:

[0067]

[0068] in, and These are the angles between the main lobe directions of the transmitting and receiving antennas and the reflection unit in the m-th row and n-th column of the a-th smart metasurface, respectively. and These are the elevation angles of the m-th row and n-th column reflective unit of the a-th smart metasurface relative to the transmitter and receiver, respectively.

[0069] Step S305: If P1 > P0, then let P0 = P1 and γ a =γ;

[0070] Step S306: If τ < Q, then let τ = τ + 1 and proceed to step S302; otherwise, end the calculation and output the optimal quantization threshold γ of the a-th smart metasurface. a .

[0071] Step S4: Calculate the optimal quantization threshold of other smart metasurfaces based on the optimal quantization threshold of the smart metasurface and the electromagnetic wave path through other smart metasurfaces.

[0072] In an embodiment of the present invention, based on the optimal quantization threshold γ of the smart metasurface... a And by measuring the electromagnetic path length of other smart metasurfaces, the optimal quantization threshold γ for other smart metasurfaces is calculated. b The formula for calculating (b=1,...,K,b≠a) is:

[0073]

[0074] in, and are the distances from the transmitter and receiver to the center of the a-th smart metasurface, respectively. and , respectively, are the distances between the transmitter and receiver and the center of the b-th smart metasurface.

[0075] Step S5: The ideal continuous phase shift of each reflection unit is converted into a discrete phase shift using the optimal quantization threshold of each smart metasurface. The discrete phase shift obtained under the optimal quantization threshold is used as the configuration phase shift of the smart metasurface.

[0076] In an embodiment of the present invention, for a communication system with K smart metasurfaces, based on an ideal continuous phase shift matrix, an optimal quantization threshold γ is applied to the k-th smart metasurface. k This is quantized into a discrete phase shift matrix that can be configured in real-world conditions. Element Δ k,m,n The discrete phase shift of the m-th row and n-th column reflective unit of the k-th smart metasurface is calculated as follows:

[0077]

[0078] in,

[0079] The following detailed description of the low-complexity multi-intelligent metasurface dynamic threshold phase shift design method of the present invention is provided through a specific embodiment.

[0080] Consider a single-antenna system assisted by K smart metasurfaces, with a single antenna configured at both the transmitter and receiver; each smart metasurface consists of M rows and N columns of reflective elements. This invention considers the cascaded channels from the transmitter to the receiver via each smart metasurface. Based on improving channel quality and enhancing beamforming effects, the following phase-shift design scheme is proposed:

[0081] The transmitter sends electromagnetic wave signals to the smart metasurface. After appropriate phase shift configuration, the smart metasurface reflects the electromagnetic wave signals back to the receiver. During this process, the phase shift configuration of the smart metasurface units can be changed in real time via external signals. If the phase shift configuration is appropriate, it will significantly improve the channel quality of the system and enhance beamforming effects. Therefore, firstly, based on the position information of the transmitter, each smart metasurface, and the receiver, the path length of each electromagnetic wave in the channel is calculated. Based on the electromagnetic wave path length, the continuous phase shift matrix of each smart metasurface unit is calculated. Subsequently, based on the continuous phase shift matrix, a smart metasurface is selected, and its optimal quantization threshold is obtained through a traversal search. Then, based on the optimal quantization threshold of this smart metasurface and the electromagnetic wave path lengths through other smart metasurfaces, the optimal quantization thresholds of other smart metasurfaces are calculated. Using the optimal quantization thresholds of each smart metasurface, the ideal continuous phase shift of each unit is transformed into a discrete phase shift, and the discrete phase shift under this quantization threshold is used as the configured phase shift of the smart metasurface.

[0082] This invention solves the problem of discrete phase shift configuration in the deployment of multi-intelligent metasurface-assisted communication. Compared with traditional algorithms, such as traversal search of all intelligent metasurfaces, the method in this invention effectively reduces algorithm complexity while ensuring that the beamforming performance of intelligent metasurfaces is close to optimal in actual communication environments, thus possessing practicality and efficiency.

[0083] For a smart metasurface with q-bit phase shift resolution, the technical solution provided in this invention is implemented as follows: Figure 2 As shown in the diagram. The transmitting and receiving ends are each configured with a single antenna. Two smart metasurfaces are deployed between the transmitting and receiving ends to assist communication. Each of the two smart metasurfaces consists of 32 rows and 16 columns of reflective elements, and each element can be independently configured with a phase shift. Each element has a discrete phase shift resolution of 1 bit, and its two possible discrete phase shift sets are... Where ρ1=0 and ρ2=π represent the first and second discrete phase shifts, respectively, determined by the hardware design of the smart metasurface. The method includes the following steps:

[0084] Step 1: Consider the distance between the transmitter and the center of the smart metasurface. meters, the distance between the receiver and the center of the smart metasurface. meters, the pitch angle θ of the transmitter relative to the center of the intelligent metasurface. t =π / 4, azimuth angle of the transmitter relative to the center of the intelligent metasurface The pitch angle θ of the receiver relative to the center of the smart metasurface r =π / 4, the azimuth angle of the receiver relative to the center of the smart metasurface Lateral dimension d of each unit of the intelligent metasurface x and longitudinal dimension d y Both are 0.05 meters. The electromagnetic wave frequency is 2.6 GHz, and the wavelength λ = [3 × 10⁻⁶]. 8 / (2.6×10 9 )]rice.

[0085] For the reflective element in the m-th row and n-th column (m=1,...,32, n=1,...,16) of the k-th (k=1,2) smart metasurface, the distance between the transmitter and the reflective element is calculated using the following formula. and the distance between the receiver and the reflective unit

[0086]

[0087] Step 2: Calculate the ideal continuous phase shift matrix of the intelligent metasurface. in This represents a 2×32×16 matrix, where the (k,m,n)th element is the ideal continuous phase shift φ of the m-th row and n-th column reflective unit of the k-th smart metasurface. k,m,n The calculation method is as follows:

[0088]

[0089] Step 3: Calculate the optimal quantization threshold γ1 on the first smart metasurface as follows:

[0090] Step 301: Set parameter τ = 1, initialize the number of search thresholds Q = 180, performance index P0 = 0, γ1 = 0;

[0091] Step 302: Generate a set of thresholds γ = (τ-1)π / 180 with intervals of ε = π / 180.

[0092] Step 303: Based on the ideal continuous phase shift matrix and threshold γ of each reflective unit of the first smart metasurface, calculate the discrete phase shift Δ of each reflective unit of the first smart metasurface using the following formula.1,m,n :

[0093]

[0094] Step 304: Calculate the performance index P1 at this time;

[0095]

[0096] in and These are the elevation angles from the transmitter and receiver to the m-th row and n-th column reflection unit of the first smart metasurface, respectively. and These are the elevation angles from the m-th row and n-th column reflective unit of the first smart metasurface to the transmitter and receiver, respectively.

[0097] Step 305: If P1 > P0, then let P0 = P1 and γ1 = γ;

[0098] Step 306: If τ < 180, then let τ = τ + 1 and proceed to step S2; otherwise, end the calculation and output the first optimal quantization threshold γ1 for the smart metasurface.

[0099] Step 4: Calculate the optimal quantization threshold γ2 of the second smart metasurface based on the electromagnetic wave path length. The calculation method is as follows:

[0100]

[0101] Step 5: For the communication system with two smart metasurfaces, based on the ideal continuous phase shift matrix, the optimal quantization thresholds γ1 and γ2 are applied to both smart metasurfaces to quantize them into discrete phase shift matrices that are configurable under actual conditions. Element Δ k,m,n The discrete phase shift of the m-th row and n-th column reflective unit of the k-th smart metasurface is calculated as follows:

[0102]

[0103] The low-complexity multi-intelligent metasurface dynamic threshold phase shift design method proposed in this invention firstly calculates the electromagnetic wave path lengths from the transmitter to the receiver via each intelligent metasurface after acquiring information about the transmitter, receiver, and each intelligent metasurface. Secondly, based on the electromagnetic wave path lengths, the ideal continuous phase shift configuration of each intelligent metasurface is calculated. Subsequently, an intelligent metasurface is selected, and its optimal quantization threshold is obtained through a traversal search. Then, based on the optimal quantization threshold of this intelligent metasurface and the electromagnetic wave path lengths via other intelligent metasurfaces, the optimal quantization thresholds of other intelligent metasurfaces are calculated. Finally, the ideal continuous phase shift of each unit is transformed into a discrete phase shift using the optimal quantization thresholds of each intelligent metasurface, and the resulting discrete phase shifts under the optimal quantization thresholds are used as the configuration phase shifts of the intelligent metasurfaces. This method can guarantee high received signal energy with low phase shift design complexity, effectively improve the channel quality of multi-intelligent metasurface assisted single-antenna communication systems, and has strong practicality and high effectiveness.

[0104] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0105] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0106] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of preferred embodiments of the invention includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as will be understood by those skilled in the art to which embodiments of the invention pertain.

Claims

1. A low-complexity multi-intelligent metasurface dynamic threshold phase shift design method, comprising configuring a single antenna at both the transmitter and receiver, and deploying multiple intelligent metasurfaces between the transmitter and receiver, each intelligent metasurface including multiple reflecting elements, each reflecting element having an independent phase shift, characterized in that, Includes the following steps: Step S1: Calculate the electromagnetic wave path from the transmitter to the receiver through each smart metasurface based on the information from the transmitter, receiver, and each smart metasurface. Specifically, it includes: For the first The first intelligent metasurface Line number The reflective unit of the array calculates the distance between the transmitter and the reflective unit based on information from the transmitter, receiver, and each smart metasurface. and the distance between the receiver and the reflective unit , , , Intelligent metasurfaces are Each intelligent metasurface consists of [number] components. OK, The column consists of reflective units, each reflective unit having Discrete phase shift resolution of bits, per reflection unit The discrete phase shift set is , Indicates the first One possible discrete phase shift, , No. The discrete phase shift and the... The relationship between the discrete phase shifts is: ; Step S2 involves calculating the ideal continuous phase shift of each unit on each intelligent metasurface based on the electromagnetic wave path lengths of each segment; specifically including: Calculate the ideal continuous phase shift matrix of a smart metasurface ,in express The matrix whose first... The element is the first The first intelligent metasurface Line number Ideal continuous phase shift of the column reflector unit The calculation method is as follows: in, For the carrier wavelength, the function Represents the variable Making a mold The operation; Step S3: Randomly select any smart metasurface and obtain the optimal quantization threshold of the smart metasurface through traversal search; Step S4, based on the optimal quantization threshold of the intelligent metasurface. And by measuring the electromagnetic path length of other smart metasurfaces, the optimal quantization threshold for those smart metasurfaces is calculated. The calculation formula is: in, , , and The transmitting end and the receiving end are respectively connected to the first The distance between the centers of the intelligent metasurface and The transmitting end and the receiving end are respectively connected to the first The distance between the centers of the intelligent metasurface The carrier wavelength; Step S5 involves converting the ideal continuous phase shift of each reflective unit into a discrete phase shift using the optimal quantization threshold of each smart metasurface, and then using the resulting discrete phase shift under the optimal quantization threshold as the configuration phase shift of the smart metasurface. This includes: Based on the ideal continuous phase shift, for the first Each intelligent metasurface employs the optimal quantization threshold. This is quantized into a discrete phase shift matrix that can be configured in real-world conditions. ,element For the first The first intelligent metasurface Line number The discrete phase shift of the column reflection unit is calculated as follows: in, .

2. The method according to claim 1, characterized in that, For the first The first intelligent metasurface Line number For each reflective element in a column, calculate the distance between the transmitter and the reflective element. and the distance between the receiver and the reflective unit The formula is: in, and The transmitting end and the receiving end are respectively connected to the first The distance between the centers of the intelligent metasurface and These are the transmitters relative to the first... The pitch and azimuth angles of the center of the intelligent metasurface and These are the receivers relative to the first... The pitch and azimuth angles of the center of the intelligent metasurface and These represent the lateral and longitudinal dimensions of each reflective unit of the smart metasurface.

3. The method according to claim 2, characterized in that, Randomly select any intelligent metasurface, and obtain the optimal quantization threshold for that intelligent metasurface through a traversal search, including: Step S301, set the parameter Initialize the number of search thresholds Performance indicators , ; Step S302, calculate the threshold ,in The pre-defined interval between adjacent thresholds; Step S303, based on the first Ideal continuous phase shift matrix and threshold of each reflection unit of a smart metasurface Calculate the first using the following formula Discrete phase shift of each reflective unit of the intelligent metasurface : Step S304: Calculate the performance indicators at this time. : in, and The main lobe directions of the transmitting and receiving antennas are respectively related to the first... The first intelligent metasurface Line number The included angle of the column of reflective units; and The first The first intelligent metasurface Line number The elevation angle of the column reflector relative to the transmitter and receiver; Step S305, if Then let and ; Step S306, if Then let If the calculation ends, proceed to step S302; otherwise, terminate the calculation and output the first... Optimal quantization threshold for a smart metasurface .

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