Intelligent metasurface angle of arrival estimation method and device

Abstract

The application provides an intelligent metasurface wave direction of arrival estimation method and device, wherein the method content comprises: dividing a search space into a plurality of grids, each grid corresponding to a codebook; traversing all codebooks with an intelligent metasurface array, and counting power information reported by a receiving end; screening maximum power information in the power information and determining a preliminary direction of arrival according to the maximum power information; dividing the intelligent metasurface array into a plurality of subarrays, assigning phases to each element of the subarrays based on the preliminary direction of arrival; and calculating the direction of arrival according to the phase values of the assigned elements. The application effectively solves the problem of inaccurate element phase acquisition of RIS in a weak coverage case, and realizes high-precision DOA estimation of RIS.

Description

Technical Field

[0001] This application belongs to the field of wireless communication, specifically relating to an intelligent metasurface wave angle estimation method and device. Background Technology

[0002] In recent years, with the gradual maturation of 5G mobile communication systems and the advancement of next-generation mobile communication networks (6G), future mobile communication networks are developing towards higher speeds, lower latency, and massive connectivity. Based on the rapid development of metamaterials technology, RIS (Reconfigurable Intelligent Surface) is expected to help achieve a fully controllable electromagnetic environment, possessing enormous potential in wireless communication and positioning systems above 5G. RIS is a planar array composed of a large number of low-cost, low-power array elements. Unlike symmetrical reflection based on the law of reflection, each element of a RIS can apply an independent phase shift to the incident signal, achieving beamforming of the reflected (refracted) wave signal. This provides more degrees of freedom for the wireless transmission environment, playing a crucial role in expanding coverage, mitigating path loss, and enhancing signal strength at the receiver.

[0003] RIS-based wireless networks are compatible with existing wireless network standards and hardware, allowing RIS to be integrated into existing communication systems for reliable and high-precision location estimation at low cost and high energy efficiency. Currently, there are two common methods for RIS-based Direction of Arrival (DOA) estimation. The first is a beam scanning scheme, which involves spatial gridding, with each beam direction corresponding to a codebook. By traversing a pre-set set of codebooks, beam scanning in different directions is achieved. DOA estimation is completed by collecting the power values ​​reported by the terminals under each codebook. The second method is DOA estimation based on RIS element phase. This involves obtaining the phase information of the RIS elements on the cascaded channel through some means, and then using high-precision DOA algorithms, such as MUSIC, to achieve high-precision DOA estimation. The latter can overcome the aperture limitations of RIS, thus achieving higher estimation accuracy. However, in real-world networks, RIS deployments are often in weak coverage scenarios, where the signal energy reaching the terminal after passing through the RIS cascaded link is relatively small. Therefore, it is difficult to accurately obtain the phase of each element on the RIS on the cascaded channel, thus making accurate DOA estimation difficult. Summary of the Invention

[0004] To address the technical problem of accurately obtaining the phase of each element on the RIS in the cascaded channel under weak coverage scenarios, this application proposes an intelligent metasurface wave arrival angle estimation method and device.

[0005] Firstly, this application proposes an intelligent metasurface wave arrival angle estimation method, including:

[0006] The search space is divided into several grids, and each grid corresponds to a codebook;

[0007] Use a smart metasurface array to traverse all codebooks and collect power information reported by the receiver.

[0008] The maximum power information is filtered from the power information, and the preliminary angle of arrival direction is determined based on the maximum power information;

[0009] The intelligent metasurface array is divided into multiple subarrays, and the phase of each subarray is assigned based on the initial angle of arrival direction.

[0010] Calculate the angle of arrival based on the phase values ​​of each element after assignment.

[0011] Optionally, the phase assignment of each element of the subarray includes:

[0012] Insert the phase into the subarray at the i-th row and j-th column;

[0013] By traversing the K phase states of the subarray, the phase value of the i-th row and j-th column of the subarray is obtained in the k-th phase state.

[0014] Optionally, the plurality of subarrays are uniformly distributed, each subarray comprising a plurality of arranged subarrays, and the array manifold of the subarrays is a function relating to the geometric center of the subarrays.

[0015] Optionally, during the process of traversing the phase states of each subarray, the phase states of other subarrays are kept unchanged.

[0016] Optionally, the step of calculating the angle of arrival based on the phase values ​​of each assigned element includes:

[0017] Record the power information of the receiver in the k-th phase state;

[0018] After collecting a preset number of power information of phase states, the phase of the transmitter is estimated by using the phase value of the i-th row and j-th column of the subarray.

[0019] After X traversals, the phase values ​​of all subarrays on the intelligent metasurface array are solved;

[0020] By combining the phase values ​​of each subarray, the angle of arrival is calculated using an array angle of arrival estimation algorithm.

[0021] Optionally, the step of using an array angle of arrival estimation algorithm to solve for the angle of arrival includes:

[0022] By combining the phase values ​​of each subarray, the estimated frequency spectrum of the phase of the array and the subarray is obtained;

[0023] The angle of arrival of the receiver to the smart metasurface array is determined by peak search of the frequency spectrum.

[0024] Secondly, a smart metasurface angle of arrival estimation device is proposed, comprising:

[0025] The acquisition module is used to divide the search space into several grids, each grid corresponding to a codebook; the intelligent metasurface array is used to traverse all codebooks and count the power information reported by the receiver.

[0026] The determination module is used to filter the maximum power information in the power information and determine the preliminary angle of arrival direction based on the maximum power information; and to calculate the angle of arrival based on the phase values ​​of each element after assignment.

[0027] The generation module is used to divide the smart metasurface array into multiple subarrays and assign phase values ​​to each subarray based on the initial angle of arrival direction.

[0028] Thirdly, a computer storage medium is provided on which a computer program is stored, which, when executed by a processor, implements the intelligent metasurface wave arrival angle estimation method described in the first aspect.

[0029] Fourthly, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the intelligent metasurface wave arrival angle estimation method as described in the first aspect.

[0030] Fifthly, this application proposes a computer program product, including a computer program or instructions that, when executed by a processor, implement the aforementioned intelligent metasurface wave arrival angle estimation method.

[0031] Beneficial effects

[0032] This application proposes an intelligent metasurface angle-of-arrival (DOA) estimation method and apparatus. By combining pre-beam scanning with subarray segmentation, it fully acquires the array gain of the subarrays, effectively solving the problem of inaccurate subarray phase acquisition under weak coverage conditions and achieving high-precision DOA estimation for RIS. Secondly, the proposed scheme can design subarray shapes and stepping schemes to meet different needs, exhibiting high flexibility. Furthermore, during subarray traversal, stepping is performed by gradual movement, resulting in overlapping subarrays and greatly reducing accuracy loss caused by subarray segmentation. In future 6G networks, the intelligent metasurface device using this scheme has a very high application prospect of large-scale deployment. Attached Figure Description

[0033] Figure 1 This is a flowchart of an intelligent metasurface wave arrival angle estimation method according to an embodiment of this application;

[0034] Figure 2 This is a device architecture diagram of an angle estimation system based on a smart metasurface according to an embodiment of this application;

[0035] Figure 3 These are examples of subarray partitioning and stepping schemes in embodiments of this application;

[0036] Figure 4 This is a schematic diagram of the phase estimation results of each element using single-element estimation in an embodiment of this application.

[0037] Figure 5 This is a schematic diagram of the phase estimation results of each subarray using subarray estimation in an embodiment of this application;

[0038] Figure 6 This is a two-dimensional search spectrum peak diagram using a single array for estimation, as shown in an embodiment of this application.

[0039] Figure 7 This is a two-dimensional search spectrum peak diagram using subarray estimation in an embodiment of this application;

[0040] Figure 8 A schematic diagram of a smart metasurface wave arrival angle estimation device according to an embodiment of this application. Detailed Implementation

[0041] The terms "first," "second," "third," "fourth," etc. (if present) in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus. The technical solutions of the embodiments of this application will now be clearly and completely described in conjunction with the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them.

[0042] In one implementation example, the topology of the test setup used in this application is shown in the attached figure. Figure 2 As shown, it includes one intelligent metasurface device, one signal transmitter, and one signal receiver.

[0043] Obviously, signal transmitting equipment is used to generate and transmit wireless signals, and can be indoor base stations, WiFi routers, etc.

[0044] Assuming the RIS array contains The RIS array has phase adjustment capability, and the adjustable phase states are determined by the number of phase adjustment bits in the array. For example, for a RIS array with a phase adjustment capability of 2 bits, its adjustable phase states are 0°, 90°, 180°, and 270°. Therefore, for the RIS array with a phase adjustment capability of 2 bits, its adjustable phase states are 0°, 90°, 180°, and 270°. In this period, the phase it sets can be expressed as: .

[0045] For DOA estimation, the most important aspect is obtaining the phase of each element in the RIS array and estimating the arrival angle using a high-precision DOA estimation algorithm. Therefore, accurately obtaining the phase of each element becomes crucial. However, in real-world environments, RIS deployments often have weak signal coverage, making it difficult for the receiver to accurately obtain the phase information of the received signal. This poses a significant challenge to obtaining the phase of the RIS elements.

[0046] The principle of this application to solve this problem is as follows: First, all codebooks of the smart metasurface are traversed. Under different codebook states, the power information reported by the terminal is statistically analyzed, and the preliminary DOA direction is determined based on the maximum power information reported by the terminal. Next, the RIS is divided into multiple uniformly distributed subarrays. For each subarray, based on the preliminary determined DOA direction, the phase of each element of the subarray is assigned, and the gain of the subarray is aligned with the direction of arrival. Finally, based on methods such as the rotation vector method, the phase information of all wireless links of "transmitter-RIS subarray-receiver" is estimated, and DOA estimation is achieved based on a high-precision angle estimation algorithm.

[0047] The specific implementation methods of this application will be further described in detail below with reference to the accompanying drawings and embodiments.

[0048] Example 1

[0049] Firstly, this application provides an intelligent metasurface wave angle estimation method. This method can accurately estimate the phase information of each subarray based on pre-beam scanning and subarray segmentation in weak signal coverage scenarios, thereby accurately estimating the wave angle of arrival of the signal.

[0050] Specifically, such as Figure 1 As shown, the steps are as follows:

[0051] Step S1: Divide the search space into several grids, each grid corresponding to a codebook;

[0052] For containing A RIS array of RIS arrays, assuming it contains Q codebooks, the RIS array of the RIS array... The spatial angle corresponding to each codebook is ,in For horizontal angles, It is a vertical angle.

[0053] Step S2: Use the intelligent metasurface array to traverse all codebooks and count the power information reported by the receiver.

[0054] Iterate through all Q codebooks and calculate the received signal strength (i.e., signal power information) of all terminals (i.e., receivers) under each codebook: ;

[0055] Among them, the intelligent metasurface is an array device based on metamaterial technology. It can change the phase state of each element through programming. The terminal is used to receive wireless signals and report signal power information. It can be used for intelligent terminals, intelligent wearable devices, etc.

[0056] Step S3: Filter the maximum power information in the power information and determine the preliminary angle of arrival direction based on the maximum power information;

[0057] The optimal codebook index is obtained by filtering the statistical results of step S2:

[0058] …………………… (1)

[0059] Based on the codebook, the direction of arrival of the wave, i.e., the direction of the angle of arrival, is initially determined as follows: .

[0060] Step S4: Divide the smart metasurface array into multiple subarrays, and assign phase values ​​to each element of the subarray based on the initial angle of arrival direction; the steps are as follows:

[0061] Step S4.1: Insert the element in the i-th row and j-th column of the subarray into the phase;

[0062] Specifically, assuming adjacent If we take each of the given arrays as a subarray, then for the first subarray, suppose the position of the array in the i-th row and j-th column of the subarray is... Then the array manifold of this subarray is:

[0063] …………………… (2)

[0064]

[0065]

[0066] in, Let be the angle of arrival, k be the wave number, and M be the number of elements on one side of the square subarray. An array manifold for square subarrays. For horizontal angles, It is a vertical angle. The geometric center of the subarray;

[0067] It is evident that the array manifold of the subarray is a function related to the geometric center of the array.

[0068] The subarray consisting of adjacent M×M arrays can be regarded as a single array, the position of which is the geometric center of the array, and the orientation pattern of which is the array manifold of the subarray.

[0069] Insert the element in the i-th row and j-th column of the subarray into the phase:

[0070] ………………… (3)

[0071] in, Based on the preliminary angle and direction vector determined in step 1, To quantize the phase one of the, The preset number of phase states for the array (including 1, 2...k... K (each phase state), therefore this subarray can acquire... The array gain of each array.

[0072] Step S4.2: Traverse the subarray Given a k-th phase state, the phase value of the subarray in the i-th row and j-th column is obtained.

[0073] Specifically, for the subarray in step S4.1, traverse... Given a k-th phase state, while keeping other subarray states unchanged during traversal, the phase of the subarray in the i-th row and j-th column of the k-th phase state is:

[0074] ……………… (4)

[0075] Step S5: Calculate the angle of arrival based on the phase values ​​of each element after assignment.

[0076] Specifically, the steps include the following:

[0077] Step S5.1: Record the power information of the receiver in the k-th phase state;

[0078] Specifically, the signal power information reported by the receiver in the k-th phase state of the subarray is recorded. For each channel state, the signal power information reported by the receiver in the k-th phase state of the subarray is recorded. The power information of the receiver in each phase state is as follows In WiFi and 5G communication networks, the receiving end reports its signal power information to the base station at regular intervals. The network side can use this power reporting mechanism to obtain the power information of the receiving end.

[0079] Step S5.2: After collecting power information of a preset number of phase states, the phase of the transmitting end is estimated using the phase value of the i-th row and j-th column of the subarray.

[0080] Specifically, the sending end collects all the data from the subarray. After obtaining the signal power information for each phase state, the subarray phase is estimated; the specific method is as follows: for the receiver power information... It can be represented as:

[0081] …………………………… (5)

[0082]

[0083] in, This represents the phase difference between the subarray and the remaining subarrays. To determine the transmission coefficients from the transmitter to the receiver for all remaining elements in the entire RIS array after removing this subarray, This refers to the transmission coefficients from the transmitter to the receiver that only include this subarray. The phase of the k-th phase state of the subarray.

[0084] Observing the above formula, we can see that, It is actually the sum of three unknowns, combined with all... The power information for each phase state yields the following system of equations:

[0085] …………………… (6)

[0086] Solving the above system of equations yields:

[0087]

[0088] The phase difference between this subarray and the remaining subarrays can then be estimated as follows: ;

[0089] The above steps can also be solved using other methods, and the specific method is not limited.

[0090] Step S5.3: After a total of X traversals, solve for the phase values ​​of all subarrays on the smart metasurface array;

[0091] Specifically, the traversal method is as follows: Figure 3As shown, traversing steps S5.1 to S5.2, a total of The phase values ​​of all subarrays on all RIS arrays are obtained by iterating through the arrays.

[0092] Step S5.4: Combining the phase values ​​of each subarray, calculate the angle of arrival using the array angle of arrival estimation algorithm. The steps are as follows:

[0093] Step S5.4.1: Combine the phase values ​​of each subarray to obtain the estimated frequency spectrum of the phase of the array and the subarray;

[0094] like Figure 4 and Figure 5 The figures show the phase values ​​estimated based on the subarray and the M=3 subarray on an RIS array with a subarray size of 11×11. As can be seen from the figures, it can be determined that the phase value is more accurate when the estimation is performed using the subarray-based method.

[0095] Step S5.4.2: Determine the angle of arrival of the receiver for the smart metasurface array by performing peak search on the frequency spectrum.

[0096] Figure 6 and Figure 7 To utilize the MUSIC algorithm, based on the spectrum estimated by the subarray and the M=3 subarray, the angle value of the receiver relative to the RIS array can be determined by performing peak search on the two-dimensional spectrum. It can be seen that the DOA estimation based on the subarray has smaller sidelobes in the search spectrum and better results.

[0097] This application proposes a smart metasurface-based angle of arrival (AHA) estimation method. Addressing the multi-source AHA estimation scenario based on smart metasurfaces in complex environments, it constructs multiple composite AHA estimation signals based on smart metasurfaces. By generating and transmitting these signals in real time, it comprehensively simulates the multi-source AHA estimation scenario based on smart metasurfaces, providing a test basis for improving the anti-smart metasurface-based AHA estimation and time security performance of target time-consuming devices.

[0098] Example 2

[0099] This embodiment proposes an intelligent metasurface angle of arrival estimation device, such as... Figure 8 As shown, it includes:

[0100] The acquisition module is used to divide the search space into several grids, each grid corresponding to a codebook; the intelligent metasurface array is used to traverse all codebooks and count the power information reported by the receiver.

[0101] The determination module is used to filter the maximum power information in the power information and determine the preliminary angle of arrival direction based on the maximum power information; and to calculate the angle of arrival based on the phase values ​​of each element after assignment.

[0102] The generation module is used to divide the smart metasurface array into multiple subarrays and assign phase values ​​to each subarray based on the initial angle of arrival direction.

[0103] The intelligent metasurface wave angle estimation device provided in this embodiment has the same technical features as the intelligent metasurface wave angle estimation method provided in Embodiment 1, so it can also solve the same technical problems and achieve the same technical effects.

[0104] Example 3

[0105] This application provides a computer storage medium storing a computer program that, when executed by a processor, implements the intelligent metasurface wave arrival angle estimation method of Embodiment 1.

[0106] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0107] Therefore, this application also proposes a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the methods described in any embodiment of this application. The computer-readable storage medium can be configured in any device of this application.

[0108] Example 4

[0109] This application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the intelligent metasurface wave arrival angle estimation method as described in Embodiment 1.

[0110] For example, it includes: one or more processors; and a storage device for storing one or more programs, which, when executed by the one or more processors, cause the one or more processors to implement the method provided in the embodiments of this application. The methods described are included in the functional descriptions above and will not be repeated here.

[0111] The electronic device also includes input and output devices; the processor, storage device, input and output devices in the electronic device can be connected by a bus or other means.

[0112] A storage device, as a computer-readable storage medium, can be used to store software programs, computer-executable programs, and module units, such as program instructions corresponding to the methods in the embodiments of this application. The storage device may mainly include a program storage area and a data storage area. The program storage area may store the operating system and at least one application program required for a function; the data storage area may store data created based on the use of the terminal, etc. Furthermore, the storage device may include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some instances, the storage device may further include memory remotely located relative to the processor, and these remote memories can be connected via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof. The various embodiments in this application are described in a progressive manner; similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments.

[0113] Example 5

[0114] This embodiment proposes a computer program product, including a computer program or instructions, which, when executed by a processor, implements the intelligent metasurface wave arrival angle estimation method of Embodiment 1.

[0115] Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or part of the technical solution, can be embodied in the form of a computer program product.

[0116] The various embodiments in this application are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0117] The scope of protection of this application is not limited to the embodiments described above. Obviously, those skilled in the art can make various modifications and variations to this disclosure without departing from the scope and spirit of this disclosure. If such modifications and variations fall within the scope of the claims of this disclosure and their equivalents, then the intent of this disclosure also includes such modifications and variations.

Claims

1. A smart metasurface wave arrival angle estimation method, characterized in that, include: The search space is divided into several grids, and each grid corresponds to a codebook; Use a smart metasurface array to traverse all codebooks and collect power information reported by the receiver. The maximum power information is filtered from the power information, and the preliminary angle of arrival direction is determined based on the maximum power information; The intelligent metasurface array is divided into multiple subarrays, and the phase of each subarray is assigned based on the initial angle of arrival direction. Calculate the angle of arrival based on the phase values ​​of each element after assignment; The phase assignment of each element of the subarray includes: Insert the phase into the subarray at the i-th row and j-th column; Traversing the subarray Given a k-th phase state, the phase value of the subarray in the i-th row and j-th column is obtained. Assigning phase values ​​to each element of the subarray also includes: during the traversal of the subarray... During the process of one phase state, the phase states of other phases remain unchanged; The multiple subarrays are uniformly distributed, each subarray comprising multiple arranged elements. The array manifold of the subarray is a function related to the geometric center of the subarray, meaning that a subarray consisting of adjacent M×M elements is considered a single element, the position of which is the geometric center of the subarray, and the radiation pattern of the element is the array manifold of the subarray. In the k-th phase state, the phase of the element in the i-th row and j-th column of the subarray is: ,in, To determine the initial direction vector of the angle of arrival, This indicates that the phase is quantized as one of the, The preset number of phase states for the array, including 1, 2...k... K Each phase state The geometric center of the subarray. Let be the position of the subarray in the i-th row and j-th column.

2. The intelligent metasurface wave arrival angle estimation method according to claim 1, characterized in that, The calculation of the angle of arrival based on the phase values ​​of each assigned element includes: Record the power information of the receiver in the k-th phase state; After collecting a preset number of power information of phase states, the phase of the transmitter is estimated by using the phase value of the i-th row and j-th column of the subarray. After X traversals, the phase values ​​of all subarrays on the intelligent metasurface array are solved; By combining the phase values ​​of each subarray, the angle of arrival is calculated using an array angle of arrival estimation algorithm.

3. The intelligent metasurface wave angle estimation method according to claim 2, characterized in that, The method of using the array angle of arrival estimation algorithm to solve for the angle of arrival includes: By combining the phase values ​​of each subarray, the estimated frequency spectrum of the phase of the array and the subarray is obtained; The angle of arrival of the receiver to the smart metasurface array is determined by peak search of the frequency spectrum.

4. A smart metasurface wave angle estimation device, characterized in that, include: The acquisition module is used to divide the search space into several grids, with each grid corresponding to a codebook; Use a smart metasurface array to traverse all codebooks and collect power information reported by the receiver. The determination module is used to filter the maximum power information in the power information and determine the preliminary angle of arrival direction based on the maximum power information; and to calculate the angle of arrival based on the phase values ​​of each element after assignment. The generation module is used to divide the smart metasurface array into multiple subarrays and assign phase values ​​to each subarray based on the initial angle of arrival direction. The phase assignment of each element of the subarray includes: Insert the phase into the subarray at the i-th row and j-th column; Traversing the subarray Given a k-th phase state, the phase value of the subarray in the i-th row and j-th column is obtained. Assigning phase values ​​to each element of the subarray also includes: during the traversal of the subarray... During the process of one phase state, the phase states of other phases remain unchanged; The multiple subarrays are uniformly distributed, each subarray comprising multiple arranged elements. The array manifold of the subarray is a function related to the geometric center of the subarray, meaning that a subarray consisting of adjacent M×M elements is considered a single element, the position of which is the geometric center of the subarray, and the radiation pattern of the element is the array manifold of the subarray. In the k-th phase state, the phase of the element in the i-th row and j-th column of the subarray is: ,in, To determine the initial direction vector of the angle of arrival, This indicates that the phase is quantized as one of the, The preset number of phase states for the array, including 1, 2...k... K Each phase state The geometric center of the subarray. Let be the position of the subarray in the i-th row and j-th column.

5. A computer storage medium having a computer program stored thereon, characterized in that, When executed by a processor, this program implements the intelligent metasurface wave arrival angle estimation method as described in any one of claims 1 to 3.

6. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the intelligent metasurface wave arrival angle estimation method as described in any one of claims 1 to 3.

7. A computer program product, comprising a computer program or instructions, characterized in that, When the computer program or instructions are executed by the processor, they implement the intelligent metasurface wave arrival angle estimation method according to any one of claims 1 to 3.

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