Beamforming optimization method and system for holographic antenna based on discrete amplitude control

Abstract

The present invention relates to a beamforming optimization method and system for a holographic antenna based on discrete amplitude control. The beamforming optimization method for a holographic antenna based on discrete amplitude control is based on the communication process between a base station and a user including a reconfigurable holographic metasurface. After obtaining a digital beamforming scheme based on the radiation amplitude and channel matrix design, and obtaining a holographic beamforming scheme based on the transmission characteristics of electromagnetic waves on the reconfigurable holographic metasurface, a joint optimization algorithm is used to iteratively determine the final holographic beamforming scheme. Finally, the transmission signal is processed according to the final holographic beamforming scheme, so as to fill the gap in the prior art that there is no work to study the influence of the holographic beamforming scheme based on discrete amplitude control on the performance of the communication system for multi-user communication assisted by RHS, and at the same time, the total user data rate is maximized.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technology, and in particular to a beamforming optimization method and system for a holographic antenna based on discrete amplitude control. Background Art

[0002] To realize ubiquitous intelligent information networks, the upcoming sixth generation (6G) wireless communications imposes stringent requirements on antenna technology, such as capacity enhancement and precise beam steering. Although the widely used dish antennas and phased array antennas are both capable of achieving these goals, they both have their own inherent defects that seriously hinder their future development. Specifically, dish antennas require heavy and expensive beam steering machinery, while phased arrays are highly dependent on power amplifiers, consume a lot of power, and have complex phase shift circuits and numerous phase shifters, especially in high-frequency bands. Therefore, in order to meet the data needs of the exponentially growing mobile devices in the future 6G wireless system, more cost-effective and efficient antenna technology is needed. Among the existing antenna technologies, holographic antennas, as a small-size, low-power planar antenna, have attracted increasing attention for their multi-beam steering capabilities with low manufacturing cost and low hardware cost. Specifically, holographic antennas use metal patches to construct holographic patterns on the surface and record the interference between reference waves and target waves based on the principle of interference. Then, the radiation characteristics of the reference wave can be changed by the holographic pattern to produce the desired radiation direction.

[0003] However, with the explosive growth of mobile devices, traditional holographic antennas face great challenges because once the holographic pattern is established, the radiation pattern of traditional holographic antennas is fixed, so they cannot meet the needs of mobile communications. Due to the controllability of metamaterials, the emerging RHS technology shows great potential in improving the shortcomings of traditional holographic antennas. Reconfigurable holographic metasurface (RHS) is an ultra-thin planar antenna with many metamaterial radiating units embedded on the antenna surface. Specifically, the reference wave generated by the antenna feed excites the RHS in the form of surface waves, making it possible to manufacture RHS with a compact structure based on printed circuit board (PCB) technology. According to the holographic pattern, each radiating unit can generate the desired radiation direction by electrically controlling the radiation amplitude of the reference wave. Therefore, compared with traditional dish antennas and phased array antennas, RHS can achieve dynamic beamforming without heavy mechanical motion devices and complex phase shifting circuits, which can greatly save antenna manufacturing costs and power loss. At the same time, its light and thin structure is also very easy to install.

[0004] Existing research work on RHS is mainly focused on RHS hardware component design and radiation direction control. However, most studies have only demonstrated the feasibility of RHS to achieve dynamic multi-beam control. There is currently no work studying the impact of RHS-assisted multi-user communication based on discrete amplitude control holographic beamforming schemes on communication system performance. Summary of the invention

[0005] In order to solve the above problems existing in the prior art, the present invention provides a beamforming optimization method and system for a holographic antenna based on discrete amplitude control.

[0006] To achieve the above object, the present invention provides the following solutions:

[0007] A beamforming optimization method for a holographic antenna based on discrete amplitude control is applied to communications including a reconfigurable holographic metasurface; the beamforming optimization method for a holographic antenna based on discrete amplitude control comprises:

[0008] Obtain holographic beamforming solutions;

[0009] A joint optimization algorithm is used to determine the final holographic beamforming scheme in an iterative manner.

[0010] Preferably, it also includes:

[0011] A maximization problem model for determining the total user data transmission rate is based on the transmission parameters of the reconfigurable holographic metasurface and the channel matrix; the transmission parameters include: a digital beamforming matrix, a propagation vector, and a distance vector from a feed source to a metamaterial radiation unit.

[0012] Preferably, it also includes:

[0013] Get digital beamforming solutions;

[0014] A joint optimization algorithm is used to iteratively determine a final digital beamforming solution; the final digital beamforming solution maximizes the value of the maximum problem model of the user's total data transmission rate.

[0015] Preferably, before obtaining the holographic beamforming solution, the method further includes:

[0016] Determine the optimal discrete amplitude value and the upper limit of the user's total data transmission rate without integer constraints;

[0017] Using a branch and bound method to optimize the optimal discrete amplitude value without integer constraints based on the upper limit of the user's total data transmission rate;

[0018] A holographic beamforming scheme is determined based on the optimized optimal discrete amplitude value without integer constraints.

[0019] Preferably, the determining of the optimal discrete amplitude value and the upper limit of the total user data transmission rate without integer constraints specifically includes:

[0020] Introducing auxiliary variables, and rewriting the maximization problem model of the user's total data transmission rate based on the auxiliary variables;

[0021] Determine the optimal auxiliary variable based on the rewritten maximization problem model of the total user data transmission rate;

[0022] MATLAB is used to determine the optimal discrete amplitude value and the upper limit of the user's total data transmission rate without integer constraints based on the optimal auxiliary variables.

[0023] Preferably, the optimal discrete amplitude value without integer constraints is optimized based on the upper limit of the total user data transmission rate by using a branch and bound method, specifically including:

[0024] Constructing a first constraint condition and a second constraint condition of a branch of the optimal discrete amplitude value without integer constraints;

[0025] Adding the first constraint condition to a first subsequent optimization problem, and adding the second constraint condition to a second subsequent optimization problem;

[0026] Determine the optimal discrete amplitude value and the upper limit of the total user data transmission rate corresponding to the first subsequent optimization problem and determine the optimal discrete amplitude value and the upper limit of the total user data transmission rate corresponding to the second subsequent optimization problem using a quadratic programming algorithm in MATLAB;

[0027] Take the first successor problem and the second successor problem as a branch and mark the solution results, compare them with the solutions of other successor problems, find the maximum upper limit of the total user data transmission rate as the new upper bound, and find the minimum upper limit of the total user data transmission rate as the new lower bound;

[0028] Return to execute "constructing the first constraint condition and the second constraint condition of a branch in the optimal discrete amplitude value without integer constraints". When the upper limit of the total user data transmission rate in each branch is less than the new lower bound, pruning is performed; when the upper limit of the total user data transmission rate in each branch is greater than the new lower bound but does not meet the integer condition, the branching operation is continued until the sum of the total user data transmission rates is equal to the new upper bound. The corresponding output data value is the optimal discrete amplitude value without integer constraints.

[0029] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0030] The beamforming optimization method of a holographic antenna based on discrete amplitude control provided by the present invention is based on the communication process between a base station and a user including a reconfigurable holographic metasurface. After a digital beamforming scheme is designed based on the radiation amplitude and the channel matrix, and a holographic beamforming scheme is designed based on the transmission characteristics of electromagnetic waves on the reconfigurable holographic metasurface, a joint optimization algorithm is used to iteratively determine the final holographic beamforming scheme. Finally, the transmission signal is processed according to the final holographic beamforming scheme, so as to fill the gap in the prior art that there is no work on the impact of the holographic beamforming scheme based on discrete amplitude control for multi-user communication assisted by RHS on the performance of the communication system, while maximizing the total user data rate.

[0031] Corresponding to the above-mentioned beamforming optimization method of the holographic antenna based on discrete amplitude control, the present invention also provides the following implementation system:

[0032] A beamforming optimization system for a holographic antenna based on discrete amplitude control is applied to communications including a reconfigurable holographic metasurface; the beamforming optimization system for a holographic antenna based on discrete amplitude control comprises:

[0033] A shaping scheme acquisition module, used to acquire a holographic beamforming scheme;

[0034] The optimization iteration module is used to adopt a joint optimization algorithm to iteratively determine the final holographic beamforming solution.

[0035] Preferably, it also includes:

[0036] A maximization problem model determination module is used to determine the maximization problem model of the user's total data transmission rate based on the transmission parameters of the reconfigurable holographic metasurface and the channel matrix; the transmission parameters include: a digital beamforming matrix, a propagation vector, and a distance vector from a feed source to a metamaterial radiation unit.

[0037] Preferably, it also includes:

[0038] A discrete amplitude value and rate upper limit determination module, used to determine the optimal discrete amplitude value and the upper limit of the user's total data transmission rate without integer constraints;

[0039] An optimization module, configured to optimize the optimal discrete amplitude value without integer constraints based on the upper limit of the total user data transmission rate by using a branch and bound method;

[0040] The holographic beamforming scheme determination module is used to determine the holographic beamforming scheme based on the optimized optimal discrete amplitude value without integer constraints.

[0041] Preferably, the discrete amplitude value and rate upper limit determination module includes:

[0042] A rewriting unit, used for introducing auxiliary variables and rewriting the maximization problem model of the user total data transmission rate based on the auxiliary variables;

[0043] an auxiliary variable determination unit, configured to determine an optimal auxiliary variable based on the rewritten maximization problem model of the total user data transmission rate;

[0044] The discrete amplitude value and rate upper limit determination unit is used to determine the optimal discrete amplitude value and the upper limit of the user's total data transmission rate without integer constraints based on the optimal auxiliary variable using MATLAB.

[0045] Since the technical effect achieved by the beamforming optimization method of the holographic antenna based on discrete amplitude control provided by the present invention is the same as the technical effect achieved by the beamforming optimization method of the holographic antenna based on discrete amplitude control provided above, it will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0047] Figure 1 A flow chart of a beamforming optimization method for a holographic antenna based on discrete amplitude control provided by the present invention;

[0048] Figure 2 A schematic diagram of the structure of the beamforming optimization system of the holographic antenna based on discrete amplitude control provided by the present invention. DETAILED DESCRIPTION

[0049] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0050] The purpose of the present invention is to provide a beamforming optimization method and system for a holographic antenna based on discrete amplitude control, so as to fill the gap in the prior art that there is no work studying the impact of the holographic beamforming scheme based on discrete amplitude control for multi-user communication assisted by RHS on the performance of the communication system, thereby maximizing the total user data rate.

[0051] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0052] The beamforming optimization method of the holographic antenna based on discrete amplitude control provided by the present invention is mainly applied to the communication process including a reconfigurable holographic metasurface. The reconfigurable holographic metasurface is composed of a feed source, a parallel plate waveguide and a metamaterial radiation unit array. Among them, the feed source emits an electromagnetic wave, and the electromagnetic wave propagates in the form of a surface wave on the parallel plate waveguide. During the propagation process, the metamaterial radiation unit is controlled by a plurality of PIN diodes. By adjusting the switch state of the PIN diode corresponding to the metamaterial radiation unit, the finite discrete radiation amplitude of the electromagnetic wave propagated to the metamaterial radiation unit can be adjusted. If there are I PIN diodes controlling a metamaterial radiation unit, the unit has 2I discrete amplitude adjustable values. Therefore, the switch state of the PIN diode in the metasurface unit is adjusted to the target switch value, and the amplitude value of the electromagnetic wave radiated on the metamaterial radiation unit is the target discretized amplitude value.

[0053] Based on this application scenario, the present invention provides a beamforming optimization method for a holographic antenna based on discrete amplitude control, such as Figure 1 As shown, including:

[0054] Step 100: Obtain a holographic beamforming solution.

[0055] Step 101: Using a joint optimization algorithm, determine the final holographic beamforming solution in an iterative manner.

[0056] On the basis of obtaining the final holographic beamforming solution, in order to further improve the transmission efficiency of the total user data, the present invention also includes:

[0057] Get digital beamforming solutions;

[0058] A joint optimization algorithm is used to iteratively determine a final digital beamforming solution; the final digital beamforming solution maximizes the value of the maximum problem model of the user's total data transmission rate.

[0059] The digital beamforming scheme and the holographic beamforming scheme designed in the present invention both need to maximize the total user data transmission rate. Based on this purpose, the present invention also needs to perform the following steps when designing the holographic beamforming scheme:

[0060] The maximization problem model of the total user data transmission rate is determined based on the transmission parameters and channel matrix of the reconfigurable holographic metasurface. The transmission parameters include: digital beamforming matrix, propagation vector and distance vector from the feed source to the metamaterial radiation unit.

[0061] In order to further improve the total data transmission rate of the user, the present invention further includes, before obtaining the holographic beamforming solution:

[0062] Step 102: Determine the optimal discrete amplitude value and the upper limit of the user total data transmission rate without integer constraints.

[0063] Step 103: Adopting the branch and bound method to optimize the optimal discrete amplitude value without integer constraints based on the upper limit of the total user data transmission rate.

[0064] Step 104: Determine a holographic beamforming scheme based on the optimized optimal discrete amplitude value without integer constraints.

[0065] Then, further, based on determining the maximization problem model of the total user data transmission rate, the implementation process of step 102 can be:

[0066] Auxiliary variables are introduced, and the maximization problem model of the user's total data transmission rate is rewritten based on the auxiliary variables.

[0067] The optimal auxiliary variables are determined based on the rewritten maximization problem model of the total user data transmission rate.

[0068] MATLAB is used to determine the optimal discrete amplitude value and the upper limit of the user's total data transmission rate without integer constraints based on the optimal auxiliary variables.

[0069] The implementation process of step 103 may be:

[0070] Construct the first constraint condition and the second constraint condition of a branch in the optimal discrete amplitude value without integer constraints.

[0071] The first constraint condition is added to the first successor optimization problem, and the second constraint condition is added to the second successor optimization problem.

[0072] The quadratic programming algorithm in MATLAB is used to determine the optimal discrete amplitude value and the upper limit of the user's total data transmission rate corresponding to the first successor optimization problem, and to determine the optimal discrete amplitude value and the upper limit of the user's total data transmission rate corresponding to the second successor optimization problem.

[0073] Take the first successor problem and the second successor problem as a branch respectively and mark the solution results, compare them with the solutions of other successor problems, find the one with the largest upper limit of the total user data transmission rate as the new upper bound, and find the one with the smallest upper limit of the total user data transmission rate as the new lower bound.

[0074] Return to execute "Construct the first and second constraints of a branch in the optimal discrete amplitude value without integer constraints". When the upper limit of the total user data transmission rate in each branch is less than the new lower bound, prune. When the upper limit of the total user data transmission rate in each branch is greater than the new lower bound, but does not meet the integer condition, continue to perform branch operations until the sum of the total user data transmission rate is equal to the new upper bound. The corresponding output data value is the optimal discrete amplitude value without integer constraints.

[0075] Based on the above application scenario, consider a base station (transmitter) equipped with K feed sources and L mobile users to communicate. The position of the L mobile users relative to the transmitter is the direction of the transmission beam required by the transmitter. Assume that the RHS is composed of M×N metamaterial radiation units, and the radiation amplitude of each radiation unit can be taken as The radiation amplitude M of each metamaterial radiation unit m,n Initialize between 0 and 1. m,n The ratio of the energy of the reference wave transmitted to each metamaterial radiation unit to the free space. The transmission channel between each RHS radiation unit and each user The computer can be used for simulation according to the actual situation. The total channel matrix between the base station and each user l is represented by H l It is represented by , whose dimension is 1×MN. Assume that the signal sent by the base station to the user is s, where s is an L-dimensional column vector, s l Represents a signal sent to user l.

[0076] The base station first performs digital beamforming on the signal sent to the user, and then inputs the encoded signal into the feed source of the RHS. The feed source sends a reference wave carrying the transmission signal to each user through the holographic beamforming of the RHS. The signal received by each user can be expressed as:

[0077] y l =H l MV l s l +H l M∑ l'≠l V l' s l' +z l ,

[0078] Where l′ is the user number, V is the digital beamforming matrix of size K×L, and V l is the lth column of V, and M is composed of elements The size of the matrix is ​​MN×K, k s is the propagation vector of the reference wave propagating on the RHS surface, is the distance vector from the kth feed to the (m,n)th radiating element, z l is the Gaussian white noise in the channel.

[0079] Among them, holographic beamforming is to form a beam for each radiation unit according to M m,n The reference wave energy is radiated into the self-use space to form a beam in a fixed direction.

[0080] Based on the above setting background, the user total transmission rate maximization problem is:

[0081]

[0082]

[0083] Among them, σ 2 is the noise power.

[0084] Based on the above-set user total transmission rate maximization problem (i.e., the user total data transmission rate maximization problem model), the specific implementation process of the beamforming optimization method of the holographic antenna based on discrete amplitude control provided by the present invention is:

[0085] Step 1: Digital Beamforming Module Design

[0086] According to the initial radiation amplitude M of the metamaterial radiation unit obtained by simulation m,n and the channel matrix H l , in order to maximize the total data rate of all users, the digital beamforming scheme can be expressed as:

[0087]

[0088] in, P = diag{p1,p2,...,p L} is a diagonal matrix, the optimal μ l Q H (QQ H ) -1 The lth diagonal element of , ν satisfies the equation

[0089] Step 2: Design of holographic beamforming scheme based on RHS

[0090] The branch and bound method is used to determine the optimal discrete amplitude value of each radiation unit. By optimizing the integer s m,n The value of can determine the optimal holographic beamforming solution, specifically:

[0091] (1) First, find the optimal s without integer constraints.m,n Value and user total data transfer rate limit

[0092] By introducing the auxiliary variable γ l ,δ l , the user's total transmission rate maximization problem can be rewritten as:

[0093]

[0094]

[0095]

[0096] definition for Regarding the MN-dimensional column vector obtained by vectorizing the subscripts m and n, then The linear approximation can be expressed as Here η l is the matrix Re(b l )[Re(b l )] T +Im(b l )[Im(b l )] T The maximum eigenvalue of corresponds to η l The (m-1)N+nth component of the eigenvector of .

[0097] pass The optimal γ can be obtained l ,δ l , specifically expressed as follows:

[0098]

[0099]

[0100] According to the obtained The optimal s can be solved using the quadratic programming algorithm in MATLAB. m,n The value and the corresponding maximum total data rate are recorded as Rmax, and the optimal s m,n Are all values ​​integers? If so, the optimization of holographic beamforming is terminated; otherwise, the branch and bound optimization described below is performed.

[0101] (2) Branch and Bound Optimization m,n

[0102] Branch: Choose an arbitrary non-integer Branch and record its value Construct two constraints: and in Represents no more than f m,n The maximum integer.

[0103] Add these two constraints to the subsequent optimization problem (i.e., formula (*)) and use the quadratic programming algorithm in MATLAB to continue solving the two subsequent optimization problems (i.e., the first subsequent optimization problem and the second subsequent optimization problem) to obtain the optimal s m,n values ​​and the corresponding maximum total data rate and.

[0104] Bounding: Take each successor problem as a branch and mark the result of the solution. Among the results of the solutions to other successor problems, find the one with the largest total data rate as the new upper bound. Find the branch with the smallest total data rate from the branches that meet the integer condition as the new lower bound R .

[0105] Compare and prune: If the data rate in each branch is less than R If there are more than R If the integer condition is not met, the branch operation will continue until the maximum rate sum is equal to the new upper bound. So far, the corresponding integer s m,n That is what you want. m,n You can get M m,n The value of .

[0106] Step 3: Use computer to iteratively optimize digital beamforming and holographic beamforming solutions

[0107] Based on the algorithms proposed in step 1 and step 2, the present invention adopts a joint optimization algorithm for the total user data rate to solve the problem of maximizing the total user data rate in an iterative manner. Specifically, while maintaining the holographic beamforming scheme {M m,n} is fixed, the digital beamforming solution V can be obtained by equation (a). Then the holographic beamforming optimization algorithm proposed in step 3 is used to optimize {M m,n} is optimized. The optimized digital beamformer and holographic beamformer are used as the initial solution. In each subsequent iteration, the two sub-problems are solved alternately. The iteration is completed until the value difference of the user total data rate between two adjacent iterations is less than the predefined threshold, and the optimal digital beamforming solution V is obtained. * Holographic beamforming The digital beamforming module and RHS are respectively based on V * and The transmitted signal can be processed. The predefined threshold is determined according to actual needs.

[0108] In summary, the beamforming optimization method of the holographic antenna based on discrete amplitude control provided by the present invention solves the problems of large size, high power consumption, high hardware cost, etc. of the existing antenna with beamforming capability; and solves the problem that there is no existing beamforming optimization method based on discrete amplitude control. In addition, the present invention can maximize the data rate of a multi-user communication system.

[0109] Corresponding to the above-mentioned beamforming optimization method of the holographic antenna based on discrete amplitude control, the present invention also provides a beamforming optimization system of the holographic antenna based on discrete amplitude control, which can be applied to communications including reconfigurable holographic metasurfaces. Figure 2 As shown, the beamforming optimization system of the holographic antenna based on discrete amplitude control includes: a digital beamforming scheme design module 1 and an optimization iteration module 2.

[0110] Wherein, the shaping scheme acquisition module 1 is used to acquire the holographic beamforming scheme;

[0111] The optimization iteration module 2 is used to adopt a joint optimization algorithm to iteratively determine the final holographic beamforming solution.

[0112] Furthermore, the beamforming optimization system of the holographic antenna based on discrete amplitude control provided by the present invention also includes: a maximization problem model determination module.

[0113] The maximization problem model determination module is used to determine the maximization problem model of the user's total data transmission rate based on the transmission parameters and channel matrix of the reconfigurable holographic metasurface. The transmission parameters include: digital beamforming matrix, propagation vector and distance vector between the feed source and the metamaterial radiation unit.

[0114] Furthermore, it also includes: a discrete amplitude value and rate upper limit determination module, an optimization module and a holographic beamforming scheme determination module.

[0115] The discrete amplitude value and rate upper limit determination module is used to determine the optimal discrete amplitude value and the upper limit of the user's total data transmission rate without integer constraints.

[0116] The optimization module is used to optimize the optimal discrete amplitude value without integer constraints based on the upper limit of the user's total data transmission rate by using a branch and bound method.

[0117] The holographic beamforming scheme determination module is used to determine the holographic beamforming scheme based on the optimized optimal discrete amplitude value without integer constraints.

[0118] The discrete amplitude value and rate upper limit determination module includes: a rewriting unit, an auxiliary variable determination sub-unit and a discrete amplitude value and rate upper limit determination unit.

[0119] The rewriting unit is used for introducing auxiliary variables and rewriting the maximization problem model of the total data transmission rate of users based on the auxiliary variables.

[0120] The auxiliary variable determination unit is used to determine the optimal auxiliary variable based on the rewritten maximization problem model of the total user data transmission rate.

[0121] The discrete amplitude value and rate upper limit determination unit is used to determine the optimal discrete amplitude value and the upper limit of the user's total data transmission rate without integer constraints based on the optimal auxiliary variable using MATLAB.

[0122] In addition, the present invention also provides a computer-readable storage medium, in which a computer software program for executing the above-mentioned method for optimizing the beamforming of a holographic antenna based on discrete amplitude control is stored.

[0123] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0124] The principles and implementation methods of the present invention are described in this article using specific examples. The description of the above embodiments is only used to help understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A beamforming optimization method for holographic antenna based on discrete amplitude control. It is characterized in that Applications include communications with reconfigurable holographic metasurfaces; The beamforming optimization method of the holographic antenna based on discrete amplitude control includes: A maximization problem model for determining the total user data transmission rate based on the transmission parameters and channel matrix of the reconfigurable holographic metasurface; the transmission parameters include: a digital beamforming matrix, a propagation vector, and a distance vector from a feed source to a metamaterial radiation unit; The radiation amplitude M of the metamaterial radiation unit in the mth row and nth column m,n is the discrete amplitude, and its value is Among them, 2 I is the number of adjustable discrete amplitudes; Determine the holographic beamforming scheme, including: Introduce auxiliary variables, and rewrite the maximization problem model of the user's total data transmission rate based on the auxiliary variables; let The rewritten maximization problem model of the total user data transmission rate is s m,n ∈{0,1,2,…,2 I -2,2 I -1} is a constraint condition; Determine the optimal auxiliary variable based on the rewritten maximization problem model of the total user data transmission rate; Using the quadratic programming algorithm in MATLAB, the optimal S without integer constraints is determined based on the optimal auxiliary variables. m,n and the user's total data transfer rate cap; Check the optimal S m,n Are they all integers? If the optimal S m,n are all integers, then the optimal S m,n The corresponding determined optimal discrete amplitude is used as the optimized optimal discrete amplitude without integer constraints; If the optimal S m,n If they are not all integers, the branch and bound method is used to optimize S m,n , including: Arbitrarily choose a non-integer S m,n Perform branching and construct the first constraint condition and the second constraint condition of the branch; Adding the first constraint condition to a first subsequent optimization problem, and adding the second constraint condition to a second subsequent optimization problem; The quadratic programming algorithm in MATLAB is used to determine the optimal S corresponding to the first subsequent optimization problem. m,n and the upper limit of the total data transmission rate of the user, determine the optimal S corresponding to the second subsequent optimization problem m,n and the user's total data transfer rate cap; The first successor optimization problem and the second successor optimization problem are respectively regarded as a branch and the solution results are marked, and the results of the solutions to other successor optimization problems are compared to find the one with the largest upper limit of the total user data transmission rate as a new upper bound, and find the one with the smallest upper limit of the total user data transmission rate as a new lower bound; Return to execute "arbitrarily select a non-integer S m,n When the upper limit of the total user data transmission rate in each branch is less than the new lower limit, pruning is performed; when the upper limit of the total user data transmission rate in each branch is greater than the new lower limit, but does not meet the integer condition, the branch operation is continued until the total user data transmission rate is equal to the new upper limit. The corresponding output data value is the optimal S without integer constraints. m,n ; Through the optimal integer value S m,n Obtain the optimal discrete amplitude; Determining a holographic beamforming scheme based on the optimized optimal discrete amplitude without integer constraints; Get digital beamforming solutions, including: Keeping the holographic beamforming scheme fixed, obtaining a corresponding digital beamforming scheme, where the digital beamforming scheme is determined based on an optimal discrete amplitude and a channel matrix; The holographic beamforming scheme and the digital beamforming scheme are used as initial solutions to the problem model of maximizing the total user data transmission rate and are iterated; in each subsequent iteration, the holographic beamforming scheme is optimized and the corresponding digital beamforming scheme is obtained, until the value difference of the total user data rate between two adjacent iterations is less than a predefined threshold, then the iteration is completed, and the final holographic beamforming scheme and the final digital beamforming scheme are obtained.

2. A beamforming optimization system for holographic antenna based on discrete amplitude control, It is characterized in that Applications include communications with reconfigurable holographic metasurfaces; The beamforming optimization system of the holographic antenna based on discrete amplitude control includes: A maximization problem model determination module is used to determine a maximization problem model of a user's total data transmission rate based on transmission parameters and a channel matrix of a reconfigurable holographic metasurface; the transmission parameters include: a digital beamforming matrix, a propagation vector, and a distance vector from a feed source to a metamaterial radiation unit; A discrete amplitude and rate upper limit determination module is used to introduce auxiliary variables and rewrite the maximization problem model of the user's total data transmission rate based on the auxiliary variables; let The rewritten maximization problem model of the total user data transmission rate is s m,n ∈{0,1,2,…,2 I -2,2 I -1} as a constraint condition; determine the optimal auxiliary variable based on the rewritten maximization problem model of the total user data transmission rate; use the quadratic programming algorithm in MATLAB to determine the optimal S without integer constraints based on the optimal auxiliary variable m,n and the upper limit of the total data transmission rate of the user; where the radiation amplitude M of the metamaterial radiation unit in the mth row and the nth column m,n is the discrete amplitude, and its value is Among them, 2 I is the number of adjustable discrete amplitudes; Optimization module, used to test the optimal S m,n Are they all integers? If the optimal S m,n are all integers, then the optimal S m,n The corresponding determined optimal discrete amplitude is used as the optimized optimal discrete amplitude without integer constraints; if the optimal S m,n If they are not all integers, then arbitrarily choose a non-integer S m,n Branching is performed to construct the first constraint condition and the second constraint condition of the branch; the first constraint condition is added to the first subsequent optimization problem, and the second constraint condition is added to the second subsequent optimization problem; the quadratic programming algorithm in MATLAB is used to determine the optimal S corresponding to the first subsequent optimization problem m,n and the upper limit of the total data transmission rate of the user, determine the optimal S corresponding to the second subsequent optimization problem m,n and the upper limit of the total data transmission rate of users; take the first successor optimization problem and the second successor optimization problem as a branch and indicate the solution results, compare them with the solutions of other successor optimization problems, find the maximum upper limit of the total data transmission rate of users as the new upper bound, find the minimum upper limit of the total data transmission rate of users as the new lower bound; return to execute "arbitrarily select a non-integer S m,n When the upper limit of the total user data transmission rate in each branch is less than the new lower limit, pruning is performed; when the upper limit of the total user data transmission rate in each branch is greater than the new lower limit, but does not meet the integer condition, the branch operation is continued until the total user data transmission rate is equal to the new upper limit. The corresponding output data value is the optimal S without integer constraints. m,n ; Through the optimal integer value S m,n Obtain the optimal discrete amplitude; A holographic beamforming scheme determination module, used to determine a holographic beamforming scheme based on the optimized optimal discrete amplitude without integer constraints; An optimization iteration module is used to keep the holographic beamforming scheme fixed and obtain a corresponding digital beamforming scheme, where the digital beamforming scheme is determined based on an optimal discrete amplitude and a channel matrix; the holographic beamforming scheme and the digital beamforming scheme are used as initial solutions to a problem model for maximizing the user's total data transmission rate and are iterated; in each subsequent iteration, the holographic beamforming scheme is optimized and a corresponding digital beamforming scheme is obtained, until the value difference of the user's total data rate between two adjacent iterations is less than a predefined threshold, then the iteration is completed, and a final holographic beamforming scheme and a final digital beamforming scheme are obtained.

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