Communication optimization method and system for rate-splitting dual-polarized layered metasurface transceiver

Abstract

The present application relates to a communication optimization method and system of a rate-splitting dual-polarized layered metasurface transceiver, a communication system based on a jammer, a transmitter based on a rate-splitting dual-polarized layered metasurface and multiple receivers based on a rate-splitting dual-polarized layered metasurface, a communication anti-jamming system model of joint regulation of signal space and channel space is constructed, the system transmission and rate maximization of the communication system are taken as the objective function, under the conditions of non-ideal angle error and unknown cross-polarization coefficient of the wireless channel, the information transmission rate requirement of the receiver, the maximum power constraint and the dual-polarized metamaterial unit mode-one are taken as the constraint conditions, the optimization problem model to be solved is constructed according to the total power threshold information of the transmitter and the user rate threshold information of the receiver, and then the optimization problem model is solved respectively to realize the communication optimization of the communication system.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to a communication optimization method and system for a rate-splitting dual-polarization stacked metasurface transceiver. Background Art

[0002] The inherent openness of wireless channel propagation environments makes wireless communications increasingly vulnerable to security threats such as interference and information interception. Traditional secure communication methods for resisting interference and information interception primarily include direct sequence spread spectrum, frequency hopping, adaptive power control, cooperative relay transmission, artificial noise, and multi-antenna technology. These secure communication methods are typically limited to transceiver processing. However, wireless channel fading is uncontrollable and is a fundamental path for interference injection and information interception, making it a major limiting factor in improving the security performance of wireless communication systems. Digitally programmable smart metasurfaces, enabled by information metamaterials, utilize a large number of passive reflective elements integrated on a planar surface to intelligently configure the wireless propagation environment through software programming. This technology holds great potential and promising application prospects for improving the secure transmission capabilities of wireless communications. Communication anti-interference methods based on smart metasurface relays, transmitters, and receivers have the potential to reconstruct wireless channels, improve channel diversity gain, and increase the freedom of channel identification, respectively.

[0003] Channel-space anti-interference technology can also provide degrees of freedom in the frequency, polarization, and power domains. Therefore, combining signal-space and channel-space anti-interference technology is expected to further increase the degrees of freedom in anti-interference space. One of the key fundamental technical issues that need to be addressed in this field is how to leverage the dynamic and flexible manipulation of electromagnetic wave characteristics using RIS (Reconfigurable Intelligence Surface), explore anti-interference technologies that combine signal and channel space, establish intrinsic connections between signal spaces such as semantic space, polarization domain, and coding domain, and the channel space utilized for wireless channel manipulation, and simultaneously meet both wireless communication and anti-interference requirements. This breaks with the traditional design philosophy of stacking and combining anti-interference methods, and allows for the design of communication anti-interference systems that encompass signal waveform manipulation, wireless channel reconstruction, high channel diversity gain, and high degrees of freedom in channel identification. Summary of the Invention

[0004] In response to the problems existing in the above-mentioned traditional technologies, a communication optimization method for a rate-splitting dual-polarization stacked metasurface transceiver and a communication system are provided.

[0005] To achieve the above objectives, the embodiments of the present invention adopt the following technical solutions:

[0006] On the one hand, a communication optimization method for a rate-splitting dual-polarization stacked metasurface transceiver is provided, which is applied to a communication system. The communication system includes a jammer, a transmitter based on the rate-splitting dual-polarization stacked metasurface, and multiple receivers based on the rate-splitting dual-polarization stacked metasurface. The jammer uses a dual-polarization omnidirectional antenna to transmit high-power suppression interference to interrupt the communication link between the transmitter and the receiver. The transmitter includes a transmitting dual-polarization RS processing module, a transmitting dual-polarization active antenna, and a transmitting stacked metasurface that are cascaded in sequence. The receiver includes a receiving stacked metasurface, a receiving dual-polarization active antenna, and a receiving dual-polarization RS processing module that are cascaded in sequence. The transmitting stacked metasurface wirelessly communicates with the receiving stacked metasurface through a dual-polarization channel. The transmitting dual-polarization active antenna and the receiving dual-polarization active antenna are both composed of a horizontally polarized element and a vertically polarized element arranged in sequence to form a uniform planar array.

[0007] The communication optimization method comprises the following steps:

[0008] Set the total power threshold information of the transmitter and the user rate threshold information of the receiver;

[0009] Taking the maximization of the system transmission and rate of the communication system as the objective function, an optimization problem model to be solved is constructed based on the total power threshold information of the transmitter and the user rate threshold information of the receiver. Under the conditions of non-ideal angle error of the wireless channel and unknown cross-polarization coefficient, the information transmission rate requirement of the receiver, the maximum power constraint and the dual-polarization metamaterial unit module are used as the constraints of the optimization problem model.

[0010] The non-ideal angle error parameters of the wireless channel are discretized and the unknown cross-polarization coefficients are processed. Then, a heuristic beam optimization algorithm is used to solve the optimization problem model to obtain the optimal receiving digital beamforming vector under different polarization directions.

[0011] The optimization problem model is solved using the dimensionality reduction-dominated minimization algorithm to obtain the optimal transmit digital beamforming vector and the optimal broadcast rate coefficient vector under different polarization directions;

[0012] Utilize based K The optimization problem model is solved by a cyclic coordinate descent algorithm based on the dimensional bisection method to obtain the optimal transmit dual-polarization smart metasurface coefficient matrix and the optimal receive dual-polarization smart metasurface coefficient matrix; K is the number of receivers;

[0013] The communication system after communication optimization is obtained by debugging the optimal receiving digital beamforming vector, the optimal transmitting digital beamforming vector, the optimal broadcast rate coefficient vector, the optimal transmitting dual-polarization intelligent metasurface coefficient matrix and the optimal receiving dual-polarization intelligent metasurface coefficient matrix under different polarization directions.

[0014] On the other hand, a communication system is also provided, including a transmitter based on a rate-splitting dual-polarized stacked metasurface and multiple receivers based on the rate-splitting dual-polarized stacked metasurface, wherein a jammer uses a dual-polarized omnidirectional antenna to transmit high-power suppression interference to interrupt the communication link between the transmitter and the receiver, the transmitter includes a transmitting dual-polarized RS processing module, a transmitting dual-polarized active antenna and a transmitting stacked metasurface cascaded in sequence, the receiver includes a receiving stacked metasurface, a receiving dual-polarized active antenna and a receiving dual-polarized RS processing module cascaded in sequence, the transmitting stacked metasurface wirelessly communicates with the receiving stacked metasurface through a dual-polarized channel, and the transmitting dual-polarized active antenna and the receiving dual-polarized active antenna are both composed of a horizontally polarized element and a vertically polarized element arranged in sequence to form a uniform planar array;

[0015] The communication system optimizes communication according to the optimal receiving digital beamforming vector, the optimal transmitting digital beamforming vector, the optimal broadcast rate coefficient vector, the optimal transmitting dual-polarization smart metasurface coefficient matrix, and the optimal receiving dual-polarization smart metasurface coefficient matrix under different polarization directions. The optimal receiving digital beamforming vector, the optimal transmitting digital beamforming vector, the optimal broadcast rate coefficient vector, the optimal transmitting dual-polarization smart metasurface coefficient matrix, and the optimal receiving dual-polarization smart metasurface coefficient matrix under different polarization directions are obtained through the following steps:

[0016] Set the total power threshold information of the transmitter and the user rate threshold information of the receiver;

[0017] Taking the maximization of the system transmission and rate of the communication system as the objective function, an optimization problem model to be solved is constructed based on the total power threshold information of the transmitter and the user rate threshold information of the receiver. Under the conditions of non-ideal angle error of the wireless channel and unknown cross-polarization coefficient, the information transmission rate requirement of the receiver, the maximum power constraint and the dual-polarization metamaterial unit module are used as the constraints of the optimization problem model.

[0018] The non-ideal angle error parameters of the wireless channel are discretized and the unknown cross-polarization coefficients are processed. Then, a heuristic beam optimization algorithm is used to solve the optimization problem model to obtain the optimal receiving digital beamforming vectors under different polarization directions.

[0019] The optimization problem model is solved using the dimensionality reduction-dominated minimization algorithm to obtain the optimal transmit digital beamforming vector and the optimal broadcast rate coefficient vector under different polarization directions;

[0020] Utilize based K The optimization problem model is solved by a cyclic coordinate descent algorithm based on the dimensional bisection method to obtain the optimal transmit dual-polarization smart metasurface coefficient matrix and the optimal receive dual-polarization smart metasurface coefficient matrix; K is the number of receivers.

[0021] One of the above technical solutions has the following advantages and beneficial effects:

[0022] The communication optimization method and system of the above-mentioned rate-splitting dual-polarization stacked metasurface transceiver is based on a communication system of an interferer, a transmitter based on a rate-splitting dual-polarization stacked metasurface, and multiple receivers based on a rate-splitting dual-polarization stacked metasurface. A communication anti-interference system model with joint control of signal space and channel space is constructed. The objective function is to maximize the system transmission and rate of the communication system. Under the conditions of non-ideal angle error of the wireless channel and unknown cross-polarization coefficient, the information transmission rate requirement, maximum power constraint and dual-polarization metamaterial unit module of the receiver are used as constraints. According to the total power threshold information of the transmitter and the user rate threshold information of the receiver, an optimization problem model to be solved is constructed. Then, the optimization problem model is solved separately to obtain the optimal receiving digital beamforming vector, the optimal transmitting digital beamforming vector, the optimal broadcast rate coefficient vector, the optimal transmitting dual-polarization intelligent metasurface coefficient matrix and the optimal receiving dual-polarization intelligent metasurface coefficient matrix under different polarization directions, so as to realize communication optimization of the communication system.

[0023] Compared with traditional technologies, the above scheme includes system model design and robust optimization algorithm, combines signal space and channel space degrees of freedom, designs a communication anti-interference transceiver architecture with signal waveform control capability, high channel diversity gain and high channel identification freedom, and proposes a dimensionality reduction-dominated minimization and K The cyclic coordinate descent algorithm of the dimensional bisection method provides theoretical support for realizing "N+1 dimensional" endogenous anti-interference. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the conventional technology, the following briefly introduces the drawings required for use in the embodiments or the conventional technology descriptions. 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 any creative work.

[0025] Figure 1 Schematic diagram of a flow chart of a communication optimization method for a rate-splitting dual-polarization stacked metasurface transceiver in one embodiment;

[0026] Figure 2 A communication anti-interference system model based on RS-DPSM combination in one embodiment;

[0027] Figure 3 A schematic diagram of the RS-DPSM transceiver architecture in one embodiment;

[0028] Figure 4Figure 1 is a portion of the normalized beam patterns in one embodiment, where (a) is the broadcast beam of the RS-DPSM transmitter on v, (b) is the unicast beam of the RS-DPSM transmitter on h, (c) is the broadcast beam of the RS-DPRIS transmitter on v, and (d) is the unicast beam of the RS-DPRIS transmitter on h.

[0029] Figure 5 1 is another part of the normalized beam pattern in one embodiment, (e) is the broadcast beam of the RS-DPMIMO transmitter on v, (f) is the unicast beam of the RS-DPMIMO transmitter on h, (g) is the receive beam of the RS-DPSM transmitter on v, and (h) is the receive beam of the RS-DPRIS transmitter on v;

[0030] Figure 6 The relationship between the transmission rate and the number of metasurface units in one embodiment;

[0031] Figure 7 The relationship between the transmission sum rate and the XPD coefficient of the communication channel in one embodiment;

[0032] Figure 8 The relationship between the transmission sum rate and the interference channel angle uncertainty in one embodiment;

[0033] Figure 9 FIG1 is a relationship between a transmission sum rate and a signal-to-interference-and-noise ratio in one embodiment;

[0034] Figure 10 FIG. 1 is a schematic diagram of the architecture of a communication system in one embodiment. DETAILED DESCRIPTION

[0035] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and Examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the description of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0036] It should be noted that the reference to "embodiment" in this document means that the specific features, structures or characteristics described in conjunction with the embodiment may be included in at least one embodiment of the present invention. The presentation of this phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It will be understood by those skilled in the art that the embodiments described herein may be combined with other embodiments. The term "and / or" used in the present specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes these combinations.

[0037] The following describes the embodiments of the present invention in detail with reference to the accompanying drawings.

[0038] In one embodiment, a communication optimization method for a rate-splitting dual-polarization stacked metasurface transceiver is provided, which is applied to a communication system. The communication system includes a jammer, a transmitter based on the rate-splitting dual-polarization stacked metasurface, and multiple receivers based on the rate-splitting dual-polarization stacked metasurface. The jammer uses a dual-polarization omnidirectional antenna to transmit high-power suppression interference to interrupt the communication link between the transmitter and the receiver. The transmitter includes a transmit dual-polarization RS processing module, a transmit dual-polarization active antenna, and a transmit stacked metasurface that are cascaded in sequence. The receiver includes a receive stacked metasurface, a receive dual-polarization active antenna, and a receive dual-polarization RS processing module that are cascaded in sequence. The transmit stacked metasurface wirelessly communicates with the receive stacked metasurface through a dual-polarization channel. The transmit dual-polarization active antenna and the receive dual-polarization active antenna are both composed of a horizontally polarized element and a vertically polarized element arranged in sequence to form a uniform planar array.

[0039] like Figure 1 As shown, the communication optimization method may include the following processing steps S10 to S20:

[0040] S10, setting the total power threshold information of the transmitter and the user rate threshold information of the receiver;

[0041] S12, taking the system transmission and rate maximization of the communication system as the objective function, constructing an optimization problem model to be solved based on the total power threshold information of the transmitter and the user rate threshold information of the receiver; under the conditions of non-ideal angle error of the wireless channel and unknown cross-polarization coefficient, taking the information transmission rate requirement of the receiver, the maximum power constraint and the dual-polarization metamaterial unit module as the constraints of the optimization problem model;

[0042] S14, discretizing the non-ideal angle error parameters of the wireless channel and processing the unknown cross-polarization coefficients, and then using a heuristic beam optimization algorithm to solve the optimization problem model to obtain the optimal receiving digital beamforming vectors under different polarization directions;

[0043] S16, using a dimensionality reduction-dominated minimization algorithm to solve the optimization problem model, and obtain the optimal transmit digital beamforming vector and the optimal broadcast rate coefficient vector under different polarization directions;

[0044] S18, using K The optimization problem model is solved by a cyclic coordinate descent algorithm based on the dimensional bisection method to obtain the optimal transmit dual-polarization smart metasurface coefficient matrix and the optimal receive dual-polarization smart metasurface coefficient matrix; K is the number of receivers;

[0045] S20, debugging the communication system after communication optimization according to the optimal receiving digital beamforming vector, the optimal transmitting digital beamforming vector, the optimal broadcast rate coefficient vector, the optimal transmitting dual-polarization intelligent metasurface coefficient matrix and the optimal receiving dual-polarization intelligent metasurface coefficient matrix under different polarization directions.

[0046] The above-mentioned communication optimization method of the rate-splitting dual-polarization stacked metasurface transceiver is based on a communication system of an interferer, a transmitter based on a rate-splitting dual-polarization stacked metasurface, and multiple receivers based on a rate-splitting dual-polarization stacked metasurface. A communication anti-interference system model with joint control of signal space and channel space is constructed. The objective function is to maximize the system transmission and rate of the communication system. Under the conditions of non-ideal angle error of the wireless channel and unknown cross-polarization coefficient, the information transmission rate requirement, maximum power constraint and dual-polarization metamaterial unit module of the receiver are used as constraints. According to the total power threshold information of the transmitter and the user rate threshold information of the receiver, an optimization problem model to be solved is constructed. Then, the optimization problem model is solved respectively to obtain the optimal receiving digital beamforming vector, the optimal transmitting digital beamforming vector, the optimal broadcast rate coefficient vector, the optimal transmitting dual-polarization intelligent metasurface coefficient matrix and the optimal receiving dual-polarization intelligent metasurface coefficient matrix under different polarization directions, so as to realize the communication optimization of the communication system.

[0047] Compared with traditional technologies, the above scheme includes system model design and robust optimization algorithm, combines signal space and channel space degrees of freedom, designs a communication anti-interference transceiver architecture with signal waveform control capability, high channel diversity gain and high channel identification freedom, and proposes a dimensionality reduction-dominated minimization and K The cyclic coordinate descent algorithm of the dimensional bisection method provides theoretical support for realizing "N+1 dimensional" endogenous anti-interference.

[0048] It can be understood that the communication optimization method of the rate splitting dual-polarization stacked metasurface transceiver provided can be applied to Figure 2In the application environment shown in FIG, the proposed rate splitting dual-polarized stacked metasurface (RS-DPSM) transceiver is shown in FIG. Figure 3 As shown, its architecture includes a transmitting dual-polarization RS processing module, a transmitting dual-polarization active antenna, a transmitting stacked metasurface, a receiving stacked metasurface, a receiving dual-polarization active antenna and a receiving dual-polarization RS processing module.

[0049] In one embodiment, the transmit dual-polarized RS processing module includes a cascaded information splitting unit, an information combining unit, an information encoding unit, and a dual-polarized digital beamforming unit. The information splitting unit is used to split the uncoded transmit information sequence into transmit broadcast information and transmit unicast information. The information combining unit is used to combine all transmit broadcast information into a single super-broadcast message. The information encoding unit is used to encode the super-broadcast information and the transmit unicast information into transmission symbols, respectively. The dual-polarized digital beamforming unit is used to beamform the two transmission symbols in different polarization directions. The receive dual-polarized RS processing module is used to implement the inverse process of the transmit dual-polarized RS processing module.

[0050] Specifically, the transmitting dual-polarization RS processing module is mainly composed of module units such as an information splitting unit, an information merging unit, an information encoding unit, and a dual-polarization digital beamforming unit. Among them, the information splitting unit is used to split the uncoded transmission information sequence into transmission broadcast information and transmission unicast information. The information merging unit is used to merge all transmission broadcast information into a single super broadcast information for decoding by all receivers. The information encoding unit is used to encode the super broadcast information and the transmission unicast information into transmission symbols. The dual-polarization digital beamforming unit is mainly used to beamform the transmission symbols corresponding to the two types of information in different polarization directions, thereby avoiding crosstalk between the two transmission symbols. The receiving dual-polarization RS processing module is the inverse process of the transmitting dual-polarization RS processing module, and also mainly includes module units such as a dual-polarization digital beamforming unit, an information decoding unit, an information splitting unit, and an information merging unit.

[0051] Both the transmitting dual-polarization active antenna and the receiving dual-polarization active antenna are composed of a horizontally polarized element and a vertically polarized element arranged in sequence to form a uniform planar array. Both the transmitting stacked metasurface and the receiving stacked metasurface are composed of multiple layers of metasurfaces stacked between the transmitting dual-polarization active antenna and the receiving dual-polarization active antenna, forming a cascade structure. Because each dual-polarization metamaterial unit in the transmitting stacked metasurface and the receiving stacked metasurface is controlled by two controllers, each independently regulating the electromagnetic wave characteristics in one polarization direction, a dual-polarization metamaterial unit can be viewed as a combination of two single-polarization metamaterial units, thereby improving channel diversity gain and channel identification freedom without increasing the aperture size.

[0052] In one embodiment, multiple receivers null-stuck interference and decode communication signals, achieving joint regulation of signal space and channel space, effectively suppressing mutual interference between nodes while improving anti-interference performance.

[0053] For the convenience of discussion, let K Indicates the number of receivers. N L = N L1 × N L2 Indicates the number of transmitting dual-polarization active antennas, N U,k = N U,k1 × N U,k2 Indicates the k The number of dual-polarization active antennas for each receiver, N L1 Indicates the number of units placed along the horizontal direction of the transmitting dual-polarized antenna array. N L2 Indicates the number of units placed along the longitudinal direction of the transmitting dual-polarized antenna array. N U,k1 Indicates the k The number of units placed horizontally along the dual-polarization antenna array of a receiver is N U,k2 Indicates the k The number of units placed along the vertical direction of the dual-polarized antenna array of the receiver is as follows; the symbol v represents the vertical polarization direction and the symbol h represents the horizontal polarization direction. In addition, it is assumed that the transmitting stacked metasurface (which can be recorded as Tx-DPSM) and the k The first receiving stacked metasurface (which can be recorded as Rx-DPSM) consists of an A-layer dual-polarization metasurface and an R-layer dual-polarization metasurface, and the Tx-DPSM a Layer M L,a = M L,a1 ×M L,a2 Dual-polarization metamaterial unit and Rx-DPSM r Layer M U,kr = M U,kr1 × M U,kr2 dual-polarization metamaterial unit, where M L,a1 Indicates Tx-DPSM a The number of units placed along the horizontal direction of the layer array, M L,a2 Indicates Tx-DPSM a The number of units placed along the longitudinal direction of the layer array, M U,kr1 Indicates the k Rx-DPSM r The number of units placed along the horizontal direction of the layer array, M U,kr2 Indicates the k Rx-DPSM r The number of units placed along the longitudinal direction of the layer array, k Not greater than K A positive integer, a is a positive integer not greater than A, r is a positive integer not greater than R.

[0054] In the RS-DPSM transmitter, the information sequence is first sent M k Split into broadcast information M C，k and unicast information M P，k Then, each broadcast information M C，1 ,…, M C，K Merge into a single super broadcast message M C , which is then encoded into transmission symbols for broadcast information S C At the same time, each unicast information M P，1 ,…, M P，K Transmission symbols encoded into unicast information S P，1 ,…, S P，K Next, the transmission symbol S C and S P，1 ,…, SP，K Digital beamforming is performed in different polarization directions, i.e. ,in and denote the transmit digital beamforming vectors in the v and h polarization directions, respectively.

[0055] The steps of the communication optimization method may be as follows:

[0056] Step 1: Set the total power threshold information of the transmitter P max and user rate threshold information R k,min .

[0057] Step 2: Take the system transmission and rate maximization as the objective function, where k The information received by each RS-DPSM receiver includes broadcast information M C Unicast information M P，k , non-ideal angle error in wireless channel Under the condition of unknown cross-polarization coefficient O, the information transmission rate requirement of the receiver, the maximum power constraint and the dual-polarization metamaterial unit mode 1 are constrained, and the optimization problem is constructed with the goal of maximizing system transmission and rate. The digital beamforming vectors received under different polarization directions are designed by joint optimization. and , broadcast rate coefficient vector and transmit digital beamforming vectors and , and the transmit dual-polarization RIS coefficient matrix and receive dual-polarization RIS coefficient matrix is the optimization variable. The optimization problem model to be solved is constructed as follows:

[0058] ;

[0059] in, Indicates the k The transmission rate of the partial broadcast information corresponding to each RS-DPSM receiver is R P , k Indicates the k The achievable transmission rate of unicast information for each RS-DPSM receiver is R C , k Indicates the k The achievable transmission rate of the total broadcast information of each RS-DPSM receiver is n Indicates the unit number.C 1 to C 4 represent the constraints respectively.

[0060] Step 3: Convert the wireless channel non-ideal angle error The parameters are discretized and the unknown cross-polarization coefficient O is processed. Then, a heuristic beam optimization algorithm is used to solve the optimization problem and obtain the optimal receiving digital beamforming vector.

[0061] Specifically, the LMMSE (Linear Minimum Mean Square Error Estimation) criterion is used to optimize the receiving digital beamforming vector and ,have:

[0062] ;

[0063] Among them, the intermediate variables are as follows:

[0064] ;

[0065] ;

[0066] ;

[0067] ;

[0068] ;

[0069] ;

[0070] in, and represents the Rx-DPSM equivalent phase shift coefficient matrix, and represents the jammer power, and represents the shared channel coefficient in the interference channel, and represents the far-field channel in the transmission channel, and represents the Tx-DPSM equivalent phase shift coefficient matrix. However, due to and There is a non-ideal angle error in the wireless channel And the unknown cross-polarization coefficient O, so it cannot be directly solved by the above formula and , and represents the noise power in the two polarization directions, Represents the identity matrix. By uniform discretization Continuous angles in and ,Right now:

[0071] .

[0072] in, and Represents the azimuth angle and elevation The number of sampling points can be used to obtain the interference channel Worst-case CSI (channel state information) ,have:

[0073] ;

[0074] in, for The corresponding discretization .

[0075] Then, the unknown cross-polarization coefficient O is processed using the quadratic function property, and the worst-case XPD (cross-polarization discrimination) coefficient is for:

[0076] ;

[0077] Based on this, Convert to , the worst-case receive digital beamforming vector can be obtained and Closed-form solution:

[0078] ;

[0079] Among them, the intermediate variables are as follows:

[0080]

[0081] In one embodiment, step 4: using a dimensionality reduction-dominated minimization algorithm to solve the optimization problem to obtain the optimal transmit digital beamforming vector and , and the broadcast rate coefficient vector That is, in the process of solving the optimization problem model using the dimensionality reduction-dominated minimization algorithm, the high-dimensional optimization variables to be optimized are reduced in dimension using the low-dimensional subspace, and the objective function is approximated by the MM algorithm and then converted into a convex quadratic constrained quadratic programming problem.

[0082] Specifically, in solving the receiving digital beamforming vector in two polarization directions and Afterwards, the broadcast rate coefficient vector and transmit digital beamforming vectors and For optimization, the corresponding optimization sub-problem can be mathematically expressed as:

[0083]

[0084] However, the above optimization sub-problems also have , non-convex objective function, high-dimensional optimization variables and multiple constraints make it difficult to solve. Therefore, for the above problem, we first use the method in step 3 to remove the optimization sub-problem Then, and The expression is converted into an equivalent form to facilitate the subsequent processing of its non-convexity, the dimension of the optimization variable, and multiple constraints, namely:

[0085] ;

[0086] ;

[0087] Thus, high-dimensional optimization variables can be and Dimensionality reduction into low-dimensional variables. Specifically, for and , which can be represented by their low-dimensional subspace and Linear representation, that is and ,in, and represents the unique solution. In addition, the low-dimensional subspace with full row rank and It can be further expressed as:

[0088] ;

[0089] in, .

[0090] Based on this, the optimization variables and Transformed into and . Therefore, the optimization subproblem is equivalently converted to:

[0091] ;

[0092] in, Indicates that and Constraints CAlthough the dimension of the optimization variables has been significantly reduced, the optimization subproblem is still difficult to solve due to multiple constraints. To address this problem, the full power property is proposed to remove the maximum power constraint. .

[0093] Due to the constraints The equality condition is satisfied at the optimal solution, that is, the transmit beam power is equal to the maximum transmit power. Therefore, the optimization sub-problem can be transformed into:

[0094] ;

[0095] Where, Indicates that middle Replace with In addition, The expression is:

[0096] ;

[0097] in, , . Using the solution of the optimization subproblem and ,pass and Obtain the solution to the original optimization subproblem, where is the conversion factor.

[0098] However, non-convex and The expression makes the optimization subproblem still unsolvable. Therefore, the MM (Majorization-Minimization) algorithm is used to approximate and ,have:

[0099] ;

[0100] ;

[0101] in, ;

[0102]

[0103] Then, we can make the two intermediate variables and , making and It can be further simplified to and .also, and It can be further decomposed into:

[0104] ;

[0105] Among them, the intermediate variables can be as follows:

[0106] ;

[0107] ;

[0108] Therefore, we can get and middle and The equivalent form is as follows:

[0109] ;

[0110] Substituting these two formulas into the above optimization subproblem of this step and discarding the constant term, the optimization subproblem can be restated as:

[0111] ;

[0112] in, ,and:

[0113] ;

[0114] This low-complexity QCQP (Quadratic Constrained Quadratic Programming) problem can be solved using CVX (a commonly used Matlab convex optimization solver), and then using and Obtaining the optimal transmit digital beamforming vector and and the broadcast rate coefficient vector .

[0115] Step 5: Utilize K The optimal transmit dual-polarization RIS coefficient matrix is ​​obtained by using the cyclic coordinate descent algorithm of the dimensional bisection method. and receive dual-polarization RIS coefficient matrix .

[0116] Specifically, first optimize the transmit dual-polarization RIS coefficient matrix .make and ,against The optimization sub-problem is:

[0117]

[0118] Using matrix transformation, the The optimization subproblem can be equivalently converted to:

[0119]

[0120] Next, using the Lagrange multiplier and The constraints and Introducing the above The objective function of the optimization sub-problem is:

[0121] ;

[0122] in, .

[0123] Then use the CCD (conjugate gradient method) algorithm to solve the The optimization sub-problem of Divide optimization variables; in In the iterative process, first let The solution obtained in the last iteration , and then update middle variables ; Finally, alternate optimization until convergence to a stable solution. Specifically, First, it can be expanded into:

[0124] ;

[0125] in, From this we can get Optimization variables , and then updated by the following CCD algorithm:

[0126] ;

[0127] Among them, update middle variables The optimization subproblem can be expressed as:

[0128] ;

[0129] Obviously, according to the properties of conjugate function, we can get the updated The closed-form solution of :

[0130] ;

[0131] However, the optimization subproblem still faces the problem of how to solve the optimal Lagrange multiplier. and Here is the question. K Dimensional bisection to search for the optimal and , that is, use the bisection method to search for a Lagrange multiplier in turn, and finally alternately search to converge to the optimal solution. The optimization problem of the optimal Lagrange multiplier is

[0132] ;

[0133] in, and As shown in the optimal Lagrangian multiplier optimization subproblem above. Then, the optimal Lagrangian multiplier optimization problem is searched through the following steps to obtain and ,Right now:

[0134] like , .like , .

[0135] like , .like , .

[0136] Otherwise, due to and It's about , A monotonically decreasing function can be searched using binary search and .

[0137] Through the above CCD algorithm and K Dimensional bisection alternating optimization and , , we can get the optimal transmit dual-polarization RIS coefficient matrix .

[0138] In some embodiments, as Figure 4 and Figure 5As shown, the normalized beam patterns of different transceiver architectures in vertical and horizontal polarization directions are given, (a) is the broadcast beam of RS-DPSM transmitter in v, (b) is the unicast beam of RS-DPSM transmitter in h, (c) is the broadcast beam of RS-DPRIS transmitter in v, (d) is the unicast beam of RS-DPRIS transmitter in h, (e) is the broadcast beam of RS-DPMIMO transmitter in v, (f) is the unicast beam of RS-DPMIMO transmitter in h, (g) is the receiving beam of RS-DPSM transmitter in v, (h) is the receiving beam of RS-DPRIS transmitter in v. The following conclusions can be drawn: first, all unicast beams can point the maximum beam direction to the target receiver (i.e., receiver Rx1), but due to the strong correlation between receiver channels, unicast beams can only produce nulls in the area of receiver Rx3, while causing serious mutual interference to receiver Rx2. Second, thanks to the application of dual-polarized RS modules, the transmitter generates broadcast beams that can be aligned with all receivers, greatly suppressing inter-node interference. In addition, the receiver can align the receiving beam to the transmitter Tx area, while producing at least -50 dB nulls in the jammer area, which verifies the effectiveness of the interference nulling of the architecture described in the specification. Finally, the beam amplitude and null depth generated by the RS-DPSM transceiver are about 10 dB larger than those of other comparative architectures, which indicates that the transmit channel diversity gain and receive channel recognition degree are further improved.

[0139] As shown in Figure 6 , the relationship between transmission and rate and the number of each layer of metamaterial units is given, where RS-SPSM represents rate-splitting single-polarized stacked super surface, RS-DPRIS represents rate-splitting single-polarized single-layer super surface, NoRS-DPSM represents dual-polarized stacked super surface without rate splitting, and RS-DPMIMO represents rate-splitting dual-polarized stacked multiple-input multiple-output system. The following conclusions can be drawn: first, the transmission and rate increase with the increase of M , because the increase of M will improve the channel diversity gain and channel recognition degree; second, the communication anti-jamming performance of the proposed RS-DPSM joint-based scheme is significantly better than other comparative schemes, which shows that the method proposed in the specification significantly improves the signal space and channel space degree of freedom, and achieves good communication anti-jamming performance; finally, as M increases, the performance gap between the method proposed in the specification and the SCA (successive convex approximation)-CCP algorithm becomes larger and larger, because the SCA-CCP algorithm will fall into a suboptimal solution under multiple high-dimensional variables and constraint conditions, which further verifies the effectiveness of the method proposed in the specification. M

[0140] As shown in Figure 7 ​As shown, the transmission rate and communication channel XPD coefficient are given It can be found that due to the crosstalk caused by cross polarization, all dual polarization anti-interference systems decrease with the increase of However, thanks to the RS's ability to adjust in the power domain, this specification's RS-DPSM-based communication anti-interference method can select a better polarization channel to avoid the performance loss caused by the XPD effect. Combined with its higher channel diversity gain and channel identification freedom, it can achieve higher transmission and data rates.

[0141] like Figure 8 As shown in the figure, the relationship between the transmission sum rate and the interference channel angle uncertainty is given. It can be seen that the transmission sum rate increases with the non-ideal angle error of the wireless channel. The increase of the communication interference reduction is reduced, and the communication interference reduction based on the RS-DPSM combination in this specification can achieve a higher transmission rate than other solutions. In addition, the communication interference reduction based on the RS-SPSM combination is affected by The influence of this specification is very great, and the communication anti-interference given in this specification almost maintains the The above results show that the communication anti-interference based on RS-DPSM can utilize the signal-channel spatial freedom to suppress mutual interference while resisting interference attacks, so it has strong robustness. In addition, it can be seen that the performance gap between SCA-CCP and the method proposed in this specification increases with time. This is because the SCA-CCP algorithm introduces multiple auxiliary variables and obtains the suboptimal solution of the DPSM beamforming matrix vector through CVX, making it difficult to It has strong robustness when it increases, and the method proposed in this specification directly obtains the optimal closed-form solution of the optimization variable, which has strong robustness.

[0142] like Figure 9 The figure shows the relationship between the transmission sum rate and the signal-to-interference-plus-noise ratio (SJNR). The following conclusions can be drawn: First, the transmission sum rate of all schemes decreases as the SJNR decreases; second, the communication anti-interference performance based on the RS-DPSM combination is highly robust at low SJNRs, due to the high channel diversity gain and channel identification freedom brought by DPSM; finally, as the SJNR decreases, the performance gap between the proposed method and the SCA-CCP algorithm widens. This is because the SCA-CCP algorithm directly optimizes the entire P, while the RMM-CCD proposed in this specification obtains the optimal closed-form solution for each optimization variable in P.

[0143] It should be understood that although Figure 2 and Figure 3The steps in the diagram are shown in the order indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Figure 2 and Figure 3 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily performed at the same time, but can be performed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0144] In one embodiment, Figure 10 As shown, a communication system 100 is provided, which may include a transmitter based on a rate-splitting dual-polarization stacked metasurface and multiple receivers based on the rate-splitting dual-polarization stacked metasurface. A jammer uses a dual-polarization omnidirectional antenna to transmit high-power interference to interrupt the communication link between the transmitter and the receiver. The transmitter includes a transmit dual-polarization RS processing module, a transmit dual-polarization active antenna, and a transmit stacked metasurface, which are cascaded in sequence. The receiver includes a receive stacked metasurface, a receive dual-polarization active antenna, and a receive dual-polarization RS processing module, which are cascaded in sequence. The transmit stacked metasurface wirelessly communicates with the receive stacked metasurface via a dual-polarization channel. The transmit dual-polarization active antenna and the receive dual-polarization active antenna each consist of a horizontally polarized element and a vertically polarized element arranged in sequence to form a uniform planar array. The communication system achieves communication optimization based on the optimal receive digital beamforming vector, the optimal transmit digital beamforming vector, the optimal broadcast rate coefficient vector, the optimal transmit dual-polarization smart metasurface coefficient matrix, and the optimal receive dual-polarization smart metasurface coefficient matrix under different polarization directions. The optimal receive digital beamforming vector, the optimal transmit digital beamforming vector, the optimal broadcast rate coefficient vector, the optimal transmit dual-polarization smart metasurface coefficient matrix, and the optimal receive dual-polarization smart metasurface coefficient matrix under different polarization directions are obtained through the following steps:

[0145] Set the total power threshold information of the transmitter and the user rate threshold information of the receiver;

[0146] Taking the maximization of the system transmission and rate of the communication system as the objective function, an optimization problem model to be solved is constructed based on the total power threshold information of the transmitter and the user rate threshold information of the receiver. Under the conditions of non-ideal angle error of the wireless channel and unknown cross-polarization coefficient, the information transmission rate requirement of the receiver, the maximum power constraint and the dual-polarization metamaterial unit module are used as the constraints of the optimization problem model.

[0147] The wireless channel non-ideal angle error parameter is discretized, and the unknown cross-polarization coefficient is processed, and then a heuristic beam optimization algorithm is used to solve the optimization problem model to obtain the optimal receiving digital beamforming vector under different polarization directions;

[0148] The optimization problem model is solved by using a dimension reduction dominant minimization algorithm to obtain the optimal transmitting digital beamforming vector under different polarization directions and the optimal broadcast rate coefficient vector;

[0149] The optimization problem model is solved by using a cyclic coordinate descent algorithm based on K dimensional bisection method to obtain the optimal transmitting dual-polarized intelligent surface coefficient matrix and the optimal receiving dual-polarized intelligent surface coefficient matrix; K The number of receivers is determined.

[0150] The above communication system 100, the communication system of the jammer, the transmitter based on the rate-splitting dual-polarized layered super surface and a plurality of receivers based on the rate-splitting dual-polarized layered super surface, constructs a communication anti-jamming system model jointly regulated by signal space and channel space, takes the system transmission and rate maximization of the communication system as the objective function, under the conditions of wireless channel non-ideal angle error and unknown cross-polarization coefficient, takes the information transmission rate requirement of the receiver, the maximum power constraint and the dual-polarized metamaterial unit mode as the constraint condition, constructs the optimization problem model to be solved according to the total power threshold information of the transmitter and the user rate threshold information of the receiver, and then solves the optimization problem model to obtain the optimal receiving digital beamforming vector under different polarization directions, the optimal transmitting digital beamforming vector, the optimal broadcast rate coefficient vector, the optimal transmitting dual-polarized intelligent surface coefficient matrix and the optimal receiving dual-polarized intelligent surface coefficient matrix, so as to realize the communication optimization of the communication system.

[0151] Compared with the traditional technology, the above scheme contains system model design and robust optimization algorithm, and jointly uses the degrees of freedom of signal space and channel space to design a communication anti-jamming transceiver architecture with signal waveform regulation capability, high channel diversity gain and high channel recognition degree of freedom, and proposes a dimension reduction dominant minimization algorithm and a cyclic coordinate descent algorithm based on K dimensional bisection method, which provides theoretical support for realizing "N+1 dimensional" endogenous anti-jamming.

[0152] In one embodiment, the transmit dual-polarized RS processing module includes a cascaded information splitting unit, an information merging unit, an information encoding unit, and a dual-polarized digital beamforming unit, wherein the information splitting unit is configured to split an uncoded transmit information sequence into transmit broadcast information and transmit unicast information, the information merging unit is configured to merge all transmit broadcast information into a single super broadcast information, the information encoding unit is configured to encode the super broadcast information and the transmit unicast information into transmission symbols, respectively, and the dual-polarized digital beamforming unit is configured to perform beamforming on the two transmit symbols in different polarization directions;

[0153] The receiving dual-polarization RS processing module is used to implement the inverse process of the transmitting dual-polarization RS processing module.

[0154] In one embodiment, a plurality of receivers null out interference and decode the communication signal.

[0155] In one embodiment, in the process of solving the optimization problem model using the dimensionality reduction-dominated minimization algorithm, the high-dimensional optimization variables to be optimized are reduced in dimension using a low-dimensional subspace, and the objective function is approximated by the MM algorithm and then converted into a convex quadratic constrained quadratic programming problem.

[0156] It can be understood that for the specific limitations of the communication system 100, please refer to the corresponding limitations of the communication optimization method of the rate-splitting dual-polarization stacked metasurface transceiver mentioned above, which will not be repeated here.

[0157] Those skilled in the art will appreciate that all or part of the processes in the above-described method embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the above-described method embodiments. Any reference to memory, storage, database, or other media used in the various embodiments provided herein may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus DRAM (RDRAM), and DDR DRAM.

[0158] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0159] The above embodiments merely illustrate several implementations of the present invention, and while their descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention. It should be noted that a person skilled in the art would be able to make numerous modifications and improvements without departing from the spirit of the present invention, all of which fall within the scope of the present invention. Therefore, the scope of the present invention shall be determined by the appended claims.

Claims

1. A communication optimization method for a rate-splitting dual-polarization stacked metasurface transceiver, characterized in that: Applied to a communication system, the communication system includes a jammer, a transmitter based on a rate-splitting dual-polarization stacked metasurface, and multiple receivers based on the rate-splitting dual-polarization stacked metasurface, the jammer uses a dual-polarization omnidirectional antenna to transmit high-power suppression interference to interrupt the communication link between the transmitter and the receiver, the transmitter includes a transmitting dual-polarization RS processing module, a transmitting dual-polarization active antenna, and a transmitting stacked metasurface cascaded in sequence, the receiver includes a receiving stacked metasurface, a receiving dual-polarization active antenna, and a receiving dual-polarization RS processing module cascaded in sequence, the transmitting stacked metasurface wirelessly communicates with the receiving stacked metasurface through a dual-polarization channel, and the transmitting dual-polarization active antenna and the receiving dual-polarization active antenna are both composed of a horizontally polarized element and a vertically polarized element arranged in sequence to form a uniform planar array; The communication optimization method comprises the steps of: Setting the total power threshold information of the transmitter and the user rate threshold information of the receiver; Taking the system transmission and rate maximization of the communication system as the objective function, constructing an optimization problem model to be solved according to the total power threshold information of the transmitter and the user rate threshold information of the receiver; Under the conditions of non-ideal angle error of the wireless channel and unknown cross-polarization coefficient, the information transmission rate requirement of the receiver, the maximum power constraint and the dual-polarization metamaterial unit module are used as the constraints of the optimization problem model; Discretizing the non-ideal angle error parameters of the wireless channel and processing the unknown cross-polarization coefficients, and then using a heuristic beam optimization algorithm to solve the optimization problem model to obtain optimal receiving digital beamforming vectors under different polarization directions; Solving the optimization problem model using a dimensionality reduction-dominated minimization algorithm to obtain optimal transmit digital beamforming vectors and optimal broadcast rate coefficient vectors under different polarization directions; Utilize based K The optimization problem model is solved by a cyclic coordinate descent algorithm of a dimensional bisection method to obtain an optimal transmit dual-polarization smart metasurface coefficient matrix and an optimal receive dual-polarization smart metasurface coefficient matrix; K is the number of receivers; The communication system after communication optimization is obtained by debugging the optimal receiving digital beamforming vector, the optimal transmitting digital beamforming vector, the optimal broadcast rate coefficient vector, the optimal transmitting dual-polarization intelligent metasurface coefficient matrix and the optimal receiving dual-polarization intelligent metasurface coefficient matrix under different polarization directions.

2. The communication optimization method of the rate-splitting dual-polarization stacked metasurface transceiver according to claim 1, characterized in that: The transmit dual-polarized RS processing module includes a cascaded information splitting unit, an information merging unit, an information encoding unit, and a dual-polarized digital beamforming unit, wherein the information splitting unit is used to split the uncoded transmit information sequence into transmit broadcast information and transmit unicast information, the information merging unit is used to merge all transmit broadcast information into a single super broadcast information, the information encoding unit is used to encode the super broadcast information and the transmit unicast information into transmission symbols, respectively, and the dual-polarized digital beamforming unit is used to perform beamforming on the two transmission symbols in different polarization directions; The receiving dual-polarization RS processing module is used to implement the inverse process of the transmitting dual-polarization RS processing module.

3. The communication optimization method of the rate-splitting dual-polarization stacked metasurface transceiver according to claim 1 or 2, characterized in that: The plurality of receivers null out interference and decode the communication signal.

4. The communication optimization method of the rate-splitting dual-polarization stacked metasurface transceiver according to claim 1, characterized in that: In the process of solving the optimization problem model using the dimensionality reduction-dominant minimization algorithm, the high-dimensional optimization variables to be optimized are reduced in dimension using a low-dimensional subspace, and the objective function is approximated by the Majorization-Minimization algorithm and then converted into a convex quadratic constrained quadratic programming problem.

5. A communication system, characterized in that: The communication system includes a transmitter based on a rate-splitting dual-polarization stacked metasurface and multiple receivers based on the rate-splitting dual-polarization stacked metasurface, wherein a jammer uses a dual-polarization omnidirectional antenna to transmit high-power suppression interference to interrupt the communication link between the transmitter and the receiver, the transmitter includes a transmitting dual-polarization RS processing module, a transmitting dual-polarization active antenna and a transmitting stacked metasurface that are cascaded in sequence, and the receiver includes a receiving stacked metasurface, a receiving dual-polarization active antenna and a receiving dual-polarization RS processing module that are cascaded in sequence, the transmitting stacked metasurface wirelessly communicates with the receiving stacked metasurface through a dual-polarization channel, and the transmitting dual-polarization active antenna and the receiving dual-polarization active antenna are both composed of a horizontally polarized element and a vertically polarized element arranged in sequence to form a uniform planar array; The communication system realizes communication optimization according to the optimal receiving digital beamforming vector, the optimal transmitting digital beamforming vector, the optimal broadcast rate coefficient vector, the optimal transmitting dual-polarization smart metasurface coefficient matrix, and the optimal receiving dual-polarization smart metasurface coefficient matrix under different polarization directions; wherein the optimal receiving digital beamforming vector, the optimal transmitting digital beamforming vector, the optimal broadcast rate coefficient vector, the optimal transmitting dual-polarization smart metasurface coefficient matrix, and the optimal receiving dual-polarization smart metasurface coefficient matrix under different polarization directions are obtained by the following steps: Setting the total power threshold information of the transmitter and the user rate threshold information of the receiver; Taking the system transmission and rate maximization of the communication system as the objective function, an optimization problem model to be solved is constructed based on the total power threshold information of the transmitter and the user rate threshold information of the receiver; under the conditions of non-ideal angle error of the wireless channel and unknown cross-polarization coefficient, the information transmission rate requirement of the receiver, the maximum power constraint, and the dual-polarization metamaterial unit module are used as constraints of the optimization problem model; Discretizing the non-ideal angle error parameters of the wireless channel and processing the unknown cross-polarization coefficients, and then using a heuristic beam optimization algorithm to solve the optimization problem model to obtain optimal receiving digital beamforming vectors under different polarization directions; Solving the optimization problem model using a dimensionality reduction-dominated minimization algorithm to obtain optimal transmit digital beamforming vectors and optimal broadcast rate coefficient vectors under different polarization directions; Utilize based K The optimization problem model is solved by a cyclic coordinate descent algorithm of a dimensional bisection method to obtain an optimal transmit dual-polarization smart metasurface coefficient matrix and an optimal receive dual-polarization smart metasurface coefficient matrix; K is the number of receivers.

6. The communication system according to claim 5, characterized in that The transmit dual-polarized RS processing module includes a cascaded information splitting unit, an information merging unit, an information encoding unit, and a dual-polarized digital beamforming unit, wherein the information splitting unit is used to split the uncoded transmit information sequence into transmit broadcast information and transmit unicast information, the information merging unit is used to merge all transmit broadcast information into a single super broadcast information, the information encoding unit is used to encode the super broadcast information and the transmit unicast information into transmission symbols, respectively, and the dual-polarized digital beamforming unit is used to perform beamforming on the two transmission symbols in different polarization directions; The receiving dual-polarization RS processing module is used to implement the inverse process of the transmitting dual-polarization RS processing module.

7. The communication system according to claim 5 or 6, characterized in that The plurality of receivers null out interference and decode the communication signal.

8. The communication system according to claim 5, wherein: In the process of solving the optimization problem model using the dimensionality reduction-dominant minimization algorithm, the high-dimensional optimization variables to be optimized are reduced in dimension using a low-dimensional subspace, and the objective function is approximated by the Majorization-Minimization algorithm and then converted into a convex quadratic constrained quadratic programming problem.

Images