Modeling method, device and model of asymmetric intelligent metasurface and antenna array

Abstract

The invention relates to an asymmetric intelligent metasurface modeling method and device, a model and an antenna array. In at least one embodiment of the invention, a model matrix of the asymmetric intelligent metasurface is formed by multiplying a first real unitary matrix used for power distribution, a complex diagonal matrix used for phase adjustment and a second real unitary matrix used for power distribution, power distribution is firstly carried out on an input signal, and then phase adjustment is carried out. And finally, power distribution is carried out again, so that the transmission process of the input signal from the model matrix of the asymmetric intelligent metasurface is realized, and the asymmetric intelligent metasurface can be deployed in a transmission-type scene. Compared with the mode that the model matrix of the symmetric intelligent metasurface needs to be subjected to complex matrix decomposition for optimal configuration, the mode matrix of the asymmetric intelligent metasurface is obtained by multiplying the three matrixes, therefore, complex matrix decomposition does not need to be carried out, the three matrixes are directly optimized, the optimization efficiency is improved, and the cost is reduced. And computing resource consumption caused by matrix decomposition is reduced.

Description

Technical Field

[0001] This disclosure relates to the field of communication technology, specifically to a modeling method, apparatus, model, and antenna array for an asymmetric smart metasurface. Background Technology

[0002] Large-scale antenna arrays for future mobile communications include traditional phased arrays and reconfigurable intelligent surfaces (RIS). The mathematical model of a traditional intelligent metasurface is a diagonal matrix, where all elements except those on the diagonal are zero. Therefore, a traditional intelligent metasurface is a diagonal intelligent metasurface (DRIS). The mathematical model of a traditional superdiagonal intelligent metasurface (BDRIS) is a symmetric complex unitary matrix. Therefore, a traditional superdiagonal intelligent metasurface is a symmetric BDRIS.

[0003] However, symmetric BDRIS requires complex matrix decomposition for optimized configuration, consuming significant computational resources. Furthermore, in hardware implementation, symmetric BDRIS can only be deployed in reflective scenarios (i.e., scenarios where signals are reflected), not in transmissive scenarios (i.e., scenarios where signals are transmitted), while asymmetric BDRIS can be deployed in transmissive scenarios. Moreover, symmetric BDRIS can only implement its own and DRIS functionalities, while asymmetric BDRIS can implement all the functionalities of both symmetric BDRIS and DRIS. Therefore, there is an urgent need to provide a modeling and hardware implementation scheme for asymmetric intelligent metasurfaces. Summary of the Invention

[0004] At least one embodiment of this disclosure provides a method, apparatus, model, and antenna array for modeling asymmetric smart metasurfaces.

[0005] In a first aspect, embodiments of this disclosure propose a modeling method for asymmetric smart metasurfaces, the method comprising:

[0006] Determine the first real unitary matrix for power distribution, the complex diagonal matrix for phase adjustment, and the second real unitary matrix for power distribution;

[0007] The model matrix of the asymmetric intelligent metasurface is determined to be the product of the first real unitary matrix, the complex diagonal matrix, and the second real unitary matrix, and the product of the model matrix and the conjugate transpose of the model matrix is ​​the identity matrix.

[0008] In some embodiments, the modulus of each element on the diagonal of the complex diagonal matrix used for phase adjustment is 1.

[0009] In some embodiments, determining a first real unitary matrix for power allocation, a complex diagonal matrix for phase adjustment, and a second real unitary matrix for power allocation includes:

[0010] The first real unitary matrix is ​​determined based on a preset first power allocation strategy;

[0011] The complex diagonal matrix is ​​determined based on a preset phase adjustment strategy;

[0012] The second real unitary matrix is ​​determined based on the preset second power allocation strategy.

[0013] In some embodiments, after determining the model matrix of the asymmetric smart metasurface, the modeling method for the asymmetric smart metasurface further includes:

[0014] Model matrix verification of the first real unitary matrix, complex diagonal matrix and second real unitary matrix based on asymmetric intelligent metasurface.

[0015] In some embodiments, verifying the first real unitary matrix, the complex diagonal matrix, and the second real unitary matrix based on the model matrix of the asymmetric smart metasurface includes:

[0016] Extract the real part of the model matrix of the asymmetric smart metasurface;

[0017] Singular value decomposition of the real part matrix yields the first real unitary matrix and the second real unitary matrix;

[0018] The complex diagonal matrix is ​​determined to be the transpose of the first real unitary matrix, the model matrix of the asymmetric intelligent metasurface, and the product of the second real unitary matrix.

[0019] Secondly, this disclosure also proposes a model of an asymmetric smart metasurface, which includes a first power distribution module, a phase adjustment module, and a second power distribution module.

[0020] The first power distribution module corresponds to the first real unitary matrix, the phase adjustment module corresponds to the complex diagonal matrix, and the second power distribution module corresponds to the second real unitary matrix.

[0021] The first power distribution module, the phase offset module, and the second power distribution module are connected in series. The model matrix corresponding to the model of the asymmetric intelligent metasurface is the product of the first real unitary matrix, the complex diagonal matrix, and the second real unitary matrix, and the product of the model matrix and the conjugate transpose of the model matrix is ​​the identity matrix.

[0022] In some embodiments, the first power distribution module and the second power distribution module are both fully connected networks or combinations of multiple fully connected networks. The first power distribution module includes at least one input terminal and multiple output terminals, the second power distribution module includes multiple input terminals and at least one output terminal, and the phase offset module includes multiple input terminals and multiple output terminals.

[0023] The multiple output terminals of the first power distribution module are connected one-to-one with the multiple input terminals of the phase offset module, and the multiple output terminals of the phase offset module are connected one-to-one with the multiple input terminals of the second power distribution module.

[0024] In some embodiments, the signal flow between the first power distribution module, the phase adjustment module, and the second power distribution module includes:

[0025] The first power distribution module distributes the power of the received signal from any input terminal and outputs it through multiple output terminals of the first power distribution module;

[0026] The phase adjustment module adjusts the phase of the signals output from multiple output terminals of the first power distribution module and then outputs them through multiple output terminals of the phase adjustment module.

[0027] The second power distribution module distributes the power of the signal output from any output terminal of the phase adjustment module and then outputs it through multiple output terminals of the second power distribution module.

[0028] In some embodiments, the input terminal of the first power distribution module is an antenna port or a metasurface, and the output terminal of the second power distribution module is an antenna port or a metasurface.

[0029] In some embodiments, the first power distribution module is a power divider or a waveguide, and the second power distribution module is a power divider or a waveguide.

[0030] In some embodiments, the phase adjustment module is a metamaterial unit or a true time-delay line device.

[0031] Thirdly, embodiments of this disclosure also propose an antenna array comprising a model of an asymmetric smart metasurface as described in any embodiment of the second aspect.

[0032] Fourthly, embodiments of this disclosure also propose a modeling apparatus for asymmetric smart metasurfaces, the apparatus comprising:

[0033] The first unit is used to determine the first real unitary matrix for power allocation, the complex diagonal matrix for phase adjustment, and the second real unitary matrix for power allocation;

[0034] The second unit is used to determine that the model matrix of the asymmetric intelligent metasurface is the product of the first real unitary matrix, the complex diagonal matrix, and the second real unitary matrix, and the product of the model matrix and the conjugate transpose of the model matrix is ​​the identity matrix.

[0035] Fifthly, embodiments of this disclosure also provide a communication device, which includes a memory, a transceiver, and a processor;

[0036] Memory is used to store computer programs; transceiver is used to send and receive data under the control of the processor; processor is used to read the computer program from memory and execute it.

[0037] Determine the first real unitary matrix for power distribution, the complex diagonal matrix for phase adjustment, and the second real unitary matrix for power distribution;

[0038] The model matrix of the asymmetric intelligent metasurface is determined to be the product of the first real unitary matrix, the complex diagonal matrix, and the second real unitary matrix, and the product of the model matrix and the conjugate transpose of the model matrix is ​​the identity matrix.

[0039] In some embodiments, the modulus of each element on the diagonal of the complex diagonal matrix used for phase adjustment is 1.

[0040] In some embodiments, determining a first real unitary matrix for power allocation, a complex diagonal matrix for phase adjustment, and a second real unitary matrix for power allocation includes:

[0041] The first real unitary matrix is ​​determined based on a preset first power allocation strategy;

[0042] The complex diagonal matrix is ​​determined based on a preset phase adjustment strategy;

[0043] The second real unitary matrix is ​​determined based on the preset second power allocation strategy.

[0044] In some embodiments, the processor is further configured to:

[0045] After determining the model matrix of the asymmetric smart metasurface, the first real unitary matrix, the complex diagonal matrix, and the second real unitary matrix are verified based on the model matrix of the asymmetric smart metasurface.

[0046] In some embodiments, verifying the first real unitary matrix, the complex diagonal matrix, and the second real unitary matrix based on the model matrix of the asymmetric smart metasurface includes:

[0047] Extract the real part of the model matrix of the asymmetric smart metasurface;

[0048] Singular value decomposition of the real part matrix yields the first real unitary matrix and the second real unitary matrix;

[0049] The complex diagonal matrix is ​​determined to be the transpose of the first real unitary matrix, the model matrix of the asymmetric intelligent metasurface, and the product of the second real unitary matrix.

[0050] In a sixth aspect, embodiments of this disclosure also provide a processor-readable storage medium storing a program for causing a processor to execute a modeling method for asymmetric smart metasurfaces according to any embodiment of the first aspect.

[0051] In at least one embodiment of this disclosure, the model matrix of the asymmetric smart metasurface is formed by multiplying a first real unitary matrix for power allocation, a complex diagonal matrix for phase adjustment, and a second real unitary matrix for power allocation. The input signal is first power allocated, then phase adjusted, and finally power allocated again, achieving a "transmission" process of the input signal through the model matrix of the asymmetric smart metasurface, enabling the asymmetric smart metasurface to be deployed in transmissive scenarios. Furthermore, compared to the symmetric smart metasurface model matrix, which requires complex matrix decomposition for optimization, the asymmetric smart metasurface model matrix in this embodiment is obtained by multiplying three matrices. Therefore, complex matrix decomposition is unnecessary, and the three matrices are directly optimized, improving optimization efficiency and reducing computational resource consumption caused by matrix decomposition. Attached Figure Description

[0052] To more clearly illustrate the technical solutions of the embodiments of this disclosure, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings.

[0053] Figure 1 A schematic diagram of a symmetrical BDRIS hardware model;

[0054] Figure 2 A schematic flowchart illustrating a modeling method for an asymmetric smart metasurface provided in this embodiment of the disclosure;

[0055] Figure 3 A schematic diagram of a modeling device for an asymmetric smart metasurface provided in an embodiment of this disclosure;

[0056] Figure 4 A schematic diagram of an asymmetric smart metasurface provided in an embodiment of this disclosure;

[0057] Figure 5 This is a schematic diagram of a communication device provided in an embodiment of the present disclosure. Detailed Implementation

[0058] To better understand the above-described objectives, features, and advantages of this disclosure, the present disclosure will be further described in detail below with reference to the accompanying drawings and embodiments. It is to be understood that the described embodiments are only some, not all, of the embodiments of this disclosure. The specific embodiments described herein are merely for explaining this disclosure and are not intended to limit it. All other embodiments obtained by those skilled in the art based on the described embodiments of this disclosure are within the scope of protection of this disclosure.

[0059] It should be noted that in this article, relational terms such as “first” and “second” are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0060] Traditional diagonal smart metasurfaces (DRIS), whether active or passive, are mathematically modeled as diagonal matrices, for example:

[0061]

[0062] Among them, a1…a n All are non-zero. Theoretically, this diagonal array cannot achieve the optimal solution for channel control. That is, for example, for a single-input single-output (SISO) system, the traditional diagonal intelligent metasurface DRIS cannot maximize the channel gain.

[0063] Similarly, the mathematical model of the traditional symmetric superdiagonal smart metasurface (BDRIS) is a symmetric complex unitary matrix, which cannot achieve the optimal solution for channel control. However, symmetric BDRIS requires complex matrix decomposition to optimize configuration, consuming a lot of computational resources.

[0064] Furthermore, the mathematical model of symmetric BDRIS is a symmetric complex unitary matrix, in which all elements can be non-zero, but the following two constraints must be satisfied:

[0065] Condition 1: Passive device limitation. That is, the product of a symmetric complex unitary matrix and its conjugate transpose is an identity matrix.

[0066] Condition 2: Reciprocity Restriction. The reciprocity restriction can be understood as ensuring that uplink and downlink reciprocity has no impact on performance. That is, a symmetric complex unitary matrix is ​​identical to its transpose.

[0067] It is evident that the mathematical model of symmetric BDRIS has two constraints, resulting in a low degree of control freedom.

[0068] Figure 1 This is a schematic diagram of a symmetric BDRIS hardware model. Figure 1 As shown, the hardware model of the symmetric BDRIS includes a first module 1 and a second module 2. The first module 1 has four ports A, B, C, and D, and is fully connected to the second module 2. The signal processing flow of the symmetric BDRIS hardware model is as follows: steps 1 to 3.

[0069] Step 1: The incident wave in free space is received by the four ports (A, B, C and D) of the first module 1 and then processed inside the first module 1.

[0070] Step 2: The signal processed by the first module 1 is reflected back by the second module 2.

[0071] Step 3: The signal reflected back from the second module 2 is emitted again through the four ports (A, B, C and D) of the first module 1 and returns to free space.

[0072] As can be seen, in the hardware implementation scheme, since the second module 2 of the symmetric BDRIS only has reflection function and not projection function, the symmetric BDRIS can only be deployed in reflective scenarios (i.e., scenarios where signals are reflected) and cannot be deployed in transmissive scenarios (i.e., scenarios where signals are transmitted). In addition, the symmetric BDRIS can only realize its own and DRIS functions, and cannot realize asymmetric BDRIS.

[0073] At least one embodiment of this disclosure provides a modeling method, apparatus, model, antenna array, communication device, or medium for asymmetric smart metasurfaces. The model matrix of the asymmetric smart metasurface is composed of the multiplication of a first real unitary matrix for power allocation, a complex diagonal matrix for phase adjustment, and a second real unitary matrix for power allocation. The input signal is first power allocated, then phase adjusted, and finally power allocated again, realizing the "transmission" process of the input signal through the model matrix of the asymmetric smart metasurface, enabling the asymmetric smart metasurface to be deployed in transmissive scenarios. Furthermore, compared to the model matrix of symmetric smart metasurfaces, which requires complex matrix decomposition for optimization, the model matrix of the asymmetric smart metasurface in this embodiment is obtained by multiplying three matrices. Therefore, complex matrix decomposition is unnecessary, and the three matrices are directly optimized, improving optimization efficiency and reducing the computational resource consumption caused by matrix decomposition.

[0074] Figure 2 A schematic flowchart illustrating a modeling method for an asymmetric smart metasurface provided in this disclosure is shown below. Figure 2 As shown, the modeling method for this asymmetric smart metasurface may include, but is not limited to, steps 201 and 202:

[0075] In step 201, a first real unitary matrix for power allocation, a complex diagonal matrix for phase adjustment, and a second real unitary matrix for power allocation are determined.

[0076] The first real unitary matrix (denoted as U1) is used to distribute the power of the input signal, the complex diagonal matrix (denoted as λ) is used to adjust the phase of the output signal of the first real unitary matrix, and the second real unitary matrix (denoted as U2) is used to further distribute the power of the output signal of the complex diagonal matrix and output the signal.

[0077] As can be seen, after the input signal undergoes power distribution through the first real unitary matrix, it is phase-adjusted by the complex diagonal matrix, and then output after power distribution again by the second real unitary matrix. This process realizes the "transmission" of the input signal from the first real unitary matrix, the complex diagonal matrix to the second real unitary matrix.

[0078] In some embodiments, the modulus of each element on the diagonal of the complex diagonal matrix λ used for phase adjustment is 1.

[0079] In step 202, the model matrix of the asymmetric smart metasurface is determined to be the product of the first real unitary matrix, the complex diagonal matrix, and the second real unitary matrix, and the product of the model matrix and the conjugate transpose of the model matrix is ​​the identity matrix.

[0080] The model matrix of the asymmetric intelligent metasurface is denoted as . Wherein, U1 is the first real unitary matrix, λ is the complex diagonal matrix, and U2 is the second real unitary matrix. The model matrix of the asymmetric intelligent metasurface first performs power distribution on the input signal (corresponding to U1), then phase adjustment (corresponding to λ), and finally power distribution again (corresponding to U2), realizing the "transmission" process of the input signal from the model matrix of the asymmetric intelligent metasurface, enabling the asymmetric intelligent metasurface to be deployed in transmissive scenarios.

[0081] Furthermore, compared to the symmetric BDRIS model matrix which requires complex matrix decomposition for optimization, the model matrix of the asymmetric smart metasurface in this embodiment is obtained by multiplying three matrices. Therefore, there is no need for complex matrix decomposition; the three matrices can be directly optimized, improving optimization efficiency and reducing computational resource consumption caused by matrix decomposition.

[0082] Furthermore, the product of the model matrix and its conjugate transpose is the identity matrix, that is, in, Model matrix The conjugate transpose of , where I is the identity matrix. This ensures that the model matrix of the asymmetric smart metasurface satisfies the passive device constraint.

[0083] It can be seen that, due to the model matrix of the asymmetric intelligent metasurface Only the passive device limitation needs to be met, i.e. No reciprocity constraint needs to be satisfied, that is, no reciprocity constraint needs to be satisfied. in Model matrix The transpose of the matrix. Therefore, compared to the model matrix of symmetric BDRIS, which needs to simultaneously satisfy passive device constraints and reciprocity constraints, the model matrix of the asymmetric smart metasurface in this embodiment... It has a higher degree of freedom in regulation.

[0084] In some embodiments, step 201, determining a first real unitary matrix for power allocation, a complex diagonal matrix for phase adjustment, and a second real unitary matrix for power allocation, includes:

[0085] The first real unitary matrix is ​​determined based on a preset first power allocation strategy;

[0086] The complex diagonal matrix is ​​determined based on a preset phase adjustment strategy;

[0087] The second real unitary matrix is ​​determined based on the preset second power allocation strategy.

[0088] The preset first power allocation strategy, preset phase adjustment strategy, and preset second power allocation strategy can be determined by optimizing the configuration based on the goal of maximizing channel gain. This optimization configuration is a conventional configuration in this field and will not be elaborated further. The first power allocation strategy is then converted into its corresponding matrix representation (i.e., the first real unitary matrix), the phase adjustment strategy is converted into its corresponding matrix representation (i.e., the complex diagonal matrix), and the second power allocation strategy is converted into its corresponding matrix representation (i.e., the second real unitary matrix).

[0089] In some embodiments, after determining the model matrix of the asymmetric smart metasurface in step 202, the modeling method for the asymmetric smart metasurface further includes a verification step, namely, verifying the first real unitary matrix, the complex diagonal matrix, and the second real unitary matrix based on the model matrix of the asymmetric smart metasurface.

[0090] The verification of the first real unitary matrix, the complex diagonal matrix, and the second real unitary matrix based on the model matrix of the asymmetric intelligent metasurface includes the following steps 1 to 3:

[0091] Step 1: Extract the real part of the model matrix of the asymmetric smart metasurface.

[0092] For example, extracting the model matrix of asymmetric smart metasurfaces. real part matrix

[0093] Step 2: Perform singular value decomposition on the real part matrix to obtain the first real unitary matrix and the second real unitary matrix.

[0094] For example, for the real part matrix Perform Singular Value Decomposition (SVD) to obtain Where U1 is the first real unitary matrix used for power allocation, and U2 is the second real unitary matrix used for power allocation.

[0095] Step 3: Determine that the complex diagonal matrix is ​​the product of the transpose of the first real unitary matrix, the model matrix of the asymmetric intelligent metasurface, and the second real unitary matrix.

[0096] For example, complex diagonal matrices used for phase adjustment in, Let be the transpose of the first real unitary matrix. Let U1 be the model matrix of the asymmetric smart metasurface, and U2 be the second real unitary matrix. It should be noted that when U1 = U2, the asymmetric smart metasurface can be transformed into a symmetric smart metasurface (e.g., a symmetric BDRIS).

[0097] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art will understand that the embodiments of this disclosure are not limited to the described order of actions, because according to the embodiments of this disclosure, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art will understand that the embodiments described in the specification are all optional embodiments.

[0098] Figure 3 This is a schematic diagram of a modeling device for an asymmetric smart metasurface provided in an embodiment of the present disclosure, as shown below. Figure 3 As shown, the modeling device for this asymmetric smart metasurface includes, but is not limited to, a first unit 31 and a second unit 32, as detailed below:

[0099] Unit 31 is used to determine the first real unitary matrix for power distribution, the complex diagonal matrix for phase adjustment, and the second real unitary matrix for power distribution;

[0100] The second unit 32 is used to determine that the model matrix of the asymmetric intelligent metasurface is the product of the first real unitary matrix, the complex diagonal matrix, and the second real unitary matrix, and the product of the model matrix and the conjugate transpose of the model matrix is ​​the identity matrix.

[0101] In some embodiments, the modulus of each element on the diagonal of the complex diagonal matrix used for phase adjustment is 1.

[0102] In some embodiments, the first unit 31 is configured to:

[0103] The first real unitary matrix is ​​determined based on a preset first power allocation strategy;

[0104] The complex diagonal matrix is ​​determined based on a preset phase adjustment strategy;

[0105] The second real unitary matrix is ​​determined based on the preset second power allocation strategy.

[0106] In some embodiments, the modeling apparatus for asymmetric smart metasurfaces further includes:

[0107] The third unit is used to verify the first real unitary matrix, the complex diagonal matrix, and the second real unitary matrix based on the model matrix of the asymmetric intelligent metasurface determined in the second unit.

[0108] In some embodiments, the third unit verifies the first real unitary matrix, the complex diagonal matrix, and the second real unitary matrix based on the model matrix of the asymmetric smart metasurface, including:

[0109] Extract the real part of the model matrix of the asymmetric smart metasurface;

[0110] Singular value decomposition of the real part matrix yields the first real unitary matrix and the second real unitary matrix;

[0111] The complex diagonal matrix is ​​determined to be the transpose of the first real unitary matrix, the model matrix of the asymmetric intelligent metasurface, and the product of the second real unitary matrix.

[0112] Figure 3 For details of the various embodiments of the modeling apparatus for the asymmetric smart metasurface shown, please refer to [reference needed]. Figure 2 The various embodiments of the modeling method for asymmetric smart metasurfaces shown are not described again to avoid repetition.

[0113] This disclosure also provides a processor-readable storage medium storing a program for causing a processor to execute steps of various embodiments of the modeling method for asymmetric smart metasurfaces. The processor-readable storage medium can be any available medium or data storage device accessible to the processor, including but not limited to magnetic memory (e.g., floppy disk, hard disk, magnetic tape, magneto-optical disk (MO), etc.), optical memory (e.g., CD, DVD, BD, HVD, etc.), and semiconductor memory (e.g., ROM, EPROM, EEPROM, non-volatile memory (NAND FLASH), solid-state drive (SSD)).

[0114] Figure 4This is a schematic diagram of an asymmetric smart metasurface provided in an embodiment of this disclosure. This model is a hardware model. Figure 4 As shown, the model includes a first power distribution module 1, a phase adjustment module 2, and a second power distribution module 3.

[0115] In this embodiment, the first power distribution module 1 corresponds to the first real unitary matrix, the phase adjustment module 2 corresponds to the complex diagonal matrix, and the second power distribution module 3 corresponds to the second real unitary matrix. The first real unitary matrix, the complex diagonal matrix, and the second real unitary matrix are the same as in the previous embodiment and will not be repeated.

[0116] The first power distribution module 1, the phase offset module 2, and the second power distribution module 3 are connected in series. The model matrix corresponding to the model of the asymmetric intelligent metasurface is the product of the first real unitary matrix, the complex diagonal matrix, and the second real unitary matrix, and the product of the model matrix and the conjugate transpose of the model matrix is ​​the identity matrix.

[0117] As can be seen, the model of the asymmetric smart metasurface disclosed in this embodiment is formed by connecting the first power distribution module 1, the phase shift module 2, and the second power distribution module 3 in series. This allows the input signal to be power-distributed by the first power distribution module 1, then phase-adjusted by the phase shift module 2, and finally output after being power-distributed again by the first power distribution module 3. This realizes the "transmission" process of the input signal from the first power distribution module 1 and the phase shift module 2 to the second power distribution module 3, enabling the model of the asymmetric smart metasurface to be deployed in a transmission scenario.

[0118] Furthermore, compared to the symmetric BDRIS model matrix which requires complex matrix decomposition for optimization, the model matrix of the asymmetric smart metasurface in this embodiment is obtained by multiplying three matrices. Therefore, there is no need for complex matrix decomposition; the three matrices can be directly optimized, improving optimization efficiency and reducing computational resource consumption caused by matrix decomposition.

[0119] Furthermore, the product of the model matrix and its conjugate transpose is the identity matrix, meaning that the model matrix of the asymmetric smart metasurface satisfies the passive device constraint. It is evident that since the model matrix of the asymmetric smart metasurface only needs to satisfy the passive device constraint and does not need to satisfy the reciprocity constraint, compared to the symmetric BDRIS model matrix which needs to simultaneously satisfy both the passive device constraint and the reciprocity constraint, the asymmetric smart metasurface model matrix in this embodiment offers greater controllability.

[0120] In some embodiments, the first power distribution module 1 and the second power distribution module 3 are both fully connected networks or combinations of multiple fully connected networks. The first power distribution module 1 includes at least one input terminal and multiple output terminals, the second power distribution module 3 includes multiple input terminals and at least one output terminal, and the phase shift module 2 includes multiple input terminals and multiple output terminals. The multiple output terminals of the first power distribution module 1 are connected one-to-one with the multiple input terminals of the phase shift module 2, and the multiple output terminals of the phase shift module 2 are connected one-to-one with the multiple input terminals of the second power distribution module 3.

[0121] For example, in Figure 4 In this configuration, the first power distribution module 1 includes four input terminals (A1, B1, C1, and D1) and four output terminals. The phase shift module 2 includes four input terminals and four output terminals. The second power distribution module 3 includes four input terminals and four output terminals (A2, B2, C2, and D2). The four output terminals of the first power distribution module 1 are connected one-to-one with the four input terminals of the phase shift module 2, and the four output terminals of the phase shift module 2 are connected one-to-one with the four input terminals of the second power distribution module 3.

[0122] In some embodiments, the signal flow between the first power distribution module 1, the phase adjustment module 2, and the second power distribution module 3 includes:

[0123] The first power distribution module 1 distributes the power of the received signal from any input terminal and outputs it through multiple output terminals. The phase adjustment module 2 adjusts the phase of the signals output from the multiple output terminals of the first power distribution module 1 and outputs them through multiple output terminals. The second power distribution module 3 distributes the power of the signal output from any output terminal of the phase adjustment module 2 and outputs it through multiple output terminals.

[0124] For example, in Figure 4 In this configuration, the first power distribution module 1 distributes the power of the received signal from any input terminal and outputs it through its four output terminals. The phase adjustment module 2 adjusts the phase of the signals output from the four output terminals of the first power distribution module 1 and outputs them through its four output terminals. The second power distribution module 3 distributes the power of the signal output from any output terminal of the phase adjustment module 2 and outputs it through its four output terminals.

[0125] In some embodiments, the input terminal of the first power distribution module 1 is an antenna port or a metasurface, and the output terminal of the second power distribution module 3 is an antenna port or a metasurface.

[0126] In some embodiments, the first power distribution module 1 is a power divider or a waveguide, and the second power distribution module 3 is a power divider or a waveguide. The port connection between the first power distribution module 1 and the phase adjustment module 2 is a direct connection. The port connection between the second power distribution module 3 and the phase adjustment module 2 is also a direct connection.

[0127] In some embodiments, the phase adjustment module 2 is a metamaterial unit or a true time delay line device.

[0128] This disclosure also proposes an antenna array, which includes... Figure 4 The model of the asymmetric smart metasurface described in the relevant embodiments is also provided. In terms of array configuration, the asymmetric smart metasurface (e.g., asymmetric BDRIS) can have arbitrary shapes, such as linear arrays, area arrays, conformal arrays, distributed arrays, etc.

[0129] Figure 5 A schematic diagram of a communication device provided in an embodiment of this disclosure, such as... Figure 5 As shown, the communication device provided in this embodiment includes a memory 51, a transceiver 52, and a processor 53.

[0130] Memory 51 is used to store computer programs; transceiver 52 is used to send and receive data under the control of processor 53; processor 53 is used to read the computer program from memory 51 and execute it.

[0131] Determine the first real unitary matrix for power distribution, the complex diagonal matrix for phase adjustment, and the second real unitary matrix for power distribution;

[0132] The model matrix of the asymmetric intelligent metasurface is determined to be the product of the first real unitary matrix, the complex diagonal matrix, and the second real unitary matrix, and the product of the model matrix and the conjugate transpose of the model matrix is ​​the identity matrix.

[0133] In some embodiments, the modulus of each element on the diagonal of the complex diagonal matrix used for phase adjustment is 1.

[0134] In some embodiments, determining a first real unitary matrix for power allocation, a complex diagonal matrix for phase adjustment, and a second real unitary matrix for power allocation includes:

[0135] The first real unitary matrix is ​​determined based on a preset first power allocation strategy;

[0136] The complex diagonal matrix is ​​determined based on a preset phase adjustment strategy;

[0137] The second real unitary matrix is ​​determined based on the preset second power allocation strategy.

[0138] In some embodiments, the processor 53 is further configured to:

[0139] After determining the model matrix of the asymmetric smart metasurface, the first real unitary matrix, the complex diagonal matrix, and the second real unitary matrix are verified based on the model matrix of the asymmetric smart metasurface.

[0140] In some embodiments, verifying the first real unitary matrix, the complex diagonal matrix, and the second real unitary matrix based on the model matrix of the asymmetric smart metasurface includes:

[0141] Extract the real part of the model matrix of the asymmetric smart metasurface;

[0142] Singular value decomposition of the real part matrix yields the first real unitary matrix and the second real unitary matrix;

[0143] The complex diagonal matrix is ​​determined to be the transpose of the first real unitary matrix, the model matrix of the asymmetric intelligent metasurface, and the product of the second real unitary matrix.

[0144] Figure 5 In this configuration, transceiver 52 is used to receive and transmit data under the control of processor 53. The bus architecture may include any number of interconnected buses and bridges, specifically linking various circuits of one or more processors represented by processor 53 and memory represented by memory 51. The bus architecture may also link various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. A bus interface provides an interface. Transceiver 52 may be multiple elements, including transmitters and receivers, providing a unit for communicating with various other devices over transmission media, including wireless channels, wired channels, optical fibers, etc. Processor 53 is responsible for managing the bus architecture and general processing, and memory 51 may store data used by processor 53 during operation.

[0145] Figure 5In this implementation, processor 53 can be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed through integrated logic circuits in the hardware of processor 53 or through software instructions. Processor 53 can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. A general-purpose processor can be a microprocessor or any conventional processor.

[0146] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0147] Those skilled in the art will understand that although some embodiments described herein include certain features included in other embodiments but not others, combinations of features from different embodiments are meant to be within the scope of this disclosure and form different embodiments.

[0148] Those skilled in the art will understand that the descriptions of the various embodiments have different focuses, and for parts not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0149] Although embodiments of the present disclosure have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present disclosure, and all such modifications and variations fall within the scope defined by the appended claims.

Claims

1. A modeling method for asymmetric smart metasurfaces, the method comprising: Determine the first real unitary matrix for power distribution, the complex diagonal matrix for phase adjustment, and the second real unitary matrix for power distribution; The model matrix of the asymmetric intelligent metasurface is determined to be the product of the first real unitary matrix, the complex diagonal matrix, and the second real unitary matrix, and the product of the model matrix and the conjugate transpose of the model matrix is ​​the identity matrix.

2. The method according to claim 1, wherein, The diagonal elements of the complex diagonal matrix used for phase adjustment have a modulus of 1.

3. The method according to claim 1, wherein, The determination of the first real unitary matrix for power allocation, the complex diagonal matrix for phase adjustment, and the second real unitary matrix for power allocation includes: The first real unitary matrix is ​​determined based on a preset first power allocation strategy; The complex diagonal matrix is ​​determined based on a preset phase adjustment strategy; The second real unitary matrix is ​​determined based on a preset second power allocation strategy.

4. The method according to claim 1, wherein, After determining the model matrix of the asymmetric smart metasurface, the method further includes: The first real unitary matrix, the complex diagonal matrix, and the second real unitary matrix are verified based on the model matrix of the asymmetric intelligent metasurface.

5. The method according to claim 4, wherein, The verification of the first real unitary matrix, the complex diagonal matrix, and the second real unitary matrix based on the model matrix of the asymmetric intelligent metasurface includes: Extract the real part of the model matrix of the asymmetric smart metasurface; Singular value decomposition is performed on the real part matrix to obtain the first real unitary matrix and the second real unitary matrix; The complex diagonal matrix is ​​determined to be the product of the transpose of the first real unitary matrix, the model matrix of the asymmetric intelligent metasurface, and the second real unitary matrix.

6. A model of an asymmetric smart metasurface, the model comprising a first power distribution module, a phase adjustment module, and a second power distribution module; The first power distribution module corresponds to a first real unitary matrix, the phase adjustment module corresponds to a complex diagonal matrix, and the second power distribution module corresponds to a second real unitary matrix. The first power allocation module, the phase offset module, and the second power allocation module are connected in series. The model matrix corresponding to the model of the asymmetric smart metasurface is the product of the first real unitary matrix, the complex diagonal matrix, and the second real unitary matrix, and the product of the model matrix and the conjugate transpose of the model matrix is ​​the identity matrix.

7. The model according to claim 6, wherein, Both the first power distribution module and the second power distribution module are fully connected networks or combinations of multiple fully connected networks. The first power distribution module includes at least one input terminal and multiple output terminals, the second power distribution module includes multiple input terminals and at least one output terminal, and the phase offset module includes multiple input terminals and multiple output terminals. The multiple output terminals of the first power distribution module are connected one-to-one with the multiple input terminals of the phase offset module, and the multiple output terminals of the phase offset module are connected one-to-one with the multiple input terminals of the second power distribution module.

8. The model according to claim 7, wherein, The signal flow between the first power distribution module, the phase adjustment module, and the second power distribution module includes: The first power distribution module distributes the power of the received signal at any input terminal and outputs it through multiple output terminals of the first power distribution module. The phase adjustment module adjusts the phase of the signals output from multiple output terminals of the first power distribution module and then outputs them through multiple output terminals of the phase adjustment module. The second power distribution module distributes the power of the signal output from any output terminal of the phase adjustment module and outputs it through multiple output terminals of the second power distribution module.

9. The model according to claim 6, wherein, The input terminal of the first power distribution module is an antenna port or a metasurface, and the output terminal of the second power distribution module is an antenna port or a metasurface.

10. The model according to claim 6, wherein, The first power distribution module is a power divider or a waveguide, and the second power distribution module is a power divider or a waveguide.

11. The model according to claim 6, wherein, The phase adjustment module is a metamaterial unit or a true time-delay line device.

12. An antenna array comprising a model of an asymmetric smart metasurface as described in any one of claims 6 to 11.

13. A modeling apparatus for an asymmetric smart metasurface, the apparatus comprising: The first unit is used to determine the first real unitary matrix for power allocation, the complex diagonal matrix for phase adjustment, and the second real unitary matrix for power allocation; The second unit is used to determine that the model matrix of the asymmetric intelligent metasurface is the product of the first real unitary matrix, the complex diagonal matrix, and the second real unitary matrix, and the product of the model matrix and the conjugate transpose of the model matrix is ​​the identity matrix.

14. A communication device, wherein, Includes memory, transceiver, and processor; The memory is used to store computer programs; the transceiver is used to send and receive data under the control of the processor; the processor is used to read the computer programs in the memory and execute them. Determine the first real unitary matrix for power distribution, the complex diagonal matrix for phase adjustment, and the second real unitary matrix for power distribution; The model matrix of the asymmetric intelligent metasurface is determined to be the product of the first real unitary matrix, the complex diagonal matrix, and the second real unitary matrix, and the product of the model matrix and the conjugate transpose of the model matrix is ​​the identity matrix.

15. The communication device according to claim 14, wherein, The diagonal elements of the complex diagonal matrix used for phase adjustment have a modulus of 1.

16. The communication device according to claim 14, wherein, The determination of the first real unitary matrix for power allocation, the complex diagonal matrix for phase adjustment, and the second real unitary matrix for power allocation includes: The first real unitary matrix is ​​determined based on a preset first power allocation strategy; The complex diagonal matrix is ​​determined based on a preset phase adjustment strategy; The second real unitary matrix is ​​determined based on a preset second power allocation strategy.

17. The communication device according to claim 14, wherein, The processor is also used for: After determining the model matrix of the asymmetric smart metasurface, the first real unitary matrix, the complex diagonal matrix, and the second real unitary matrix are verified based on the model matrix of the asymmetric smart metasurface.

18. The communication device according to claim 17, wherein, The verification of the first real unitary matrix, the complex diagonal matrix, and the second real unitary matrix based on the model matrix of the asymmetric intelligent metasurface includes: Extract the real part of the model matrix of the asymmetric smart metasurface; Singular value decomposition is performed on the real part matrix to obtain the first real unitary matrix and the second real unitary matrix; The complex diagonal matrix is ​​determined to be the product of the transpose of the first real unitary matrix, the model matrix of the asymmetric intelligent metasurface, and the second real unitary matrix.

19. A processor-readable storage medium, wherein, The processor-readable storage medium stores a program for causing the processor to execute the modeling method for asymmetric smart metasurfaces as described in any one of claims 1 to 5.

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