A multi-user downlink MISO system energy-saving safe communication method

Abstract

The application discloses a kind of multi-user downlink MISO system energy-saving safety communication method, belong to wireless communication and signal processing technical field, system includes: base station (access point, AP), with M Antenna is configured to generate and send beamforming signal;While transmitting and reflecting reconfigurable intelligent surface, contain N Adjustable electromagnetic unit, each unit simultaneously supports reflection and transmission mode, and the amplitude coefficient of reflection and transmission satisfies the energy conservation constraint, and the phase coefficient can be independently controlled;Legal user terminal is distributed in the reflection area and transmission area of STAR-RIS;Eavesdropper terminal is distributed in the reflection and transmission area of STAR-RIS;The application limits the QoS of eavesdropper terminal while guaranteeing the communication quality (Quality of Service, QoS) of legal user terminal, and saves the transmission power required by base station AP as far as possible.

Description

Technical Field

[0001] This invention relates to an energy-saving and secure communication method for a multi-user downlink MISO system, belonging to the field of wireless communication and signal processing technology. Background Technology

[0002] Reconfigurable Intelligent Surfaces (RIS), as an important emerging technology for realizing next-generation wireless communication networks, have been extensively studied for improving wireless network performance. RIS consists of a large number of passive reflective elements and can reconstruct the radio propagation environment by precisely adjusting the phase and amplitude of the incident signal, thereby enhancing signal quality, increasing system capacity, and reducing communication power consumption. Its core advantage lies in its ability to intelligently control the wireless channel without the need for additional RF links or signal processing units, thus holding significant application value in future green communication systems.

[0003] While RIS technology has shown great potential in wireless communication systems, traditional RIS requires the transmitter and receiver to be deployed on the same side of the RIS, limiting its application in certain complex scenarios, such as large-scale indoor communication, urban high-rise environments, and complex propagation environments with obstructions. To address the spatial coverage limitations of traditional RIS, researchers have proposed the Simultaneous Transmission and Reflection Reconfigurable Intelligent Surface (STAR-RIS). As an extension of RIS technology, STAR-RIS's core feature is its ability to simultaneously separate incident signals into transmitted and reflected signals, with the power ratio of the transmitted and reflected signals flexibly adjustable, thereby achieving 360° full-space wireless channel reconstruction. This characteristic enables STAR-RIS to be applied to a wider range of wireless communication scenarios, including dual-sided indoor-outdoor integrated communication and seamlessly connected smart Internet of Things (IoT) networks.

[0004] In wireless communication systems, to ensure the Quality of Service (QoS) of legitimate user terminals, it is typically necessary to jointly optimize the beamforming vector of the base station (AP) and the coefficient matrix of the STAR-RIS. However, due to the coupling between optimization variables, this optimization problem is non-convex, making it difficult to directly solve for the global optimum. Existing research usually employs the Alternating Optimization (AO) method, which gradually approaches the optimal solution by fixing a portion of variables and optimizing the remaining variables in each iteration. However, due to the strong coupling between variables, the AO method has a slow convergence speed and may get trapped in local optima, failing to guarantee global optimal performance. Therefore, how to efficiently optimize the transmission and reflection coefficient matrices of STAR-RIS and design more advanced optimization algorithms to improve convergence speed and optimization performance is a key challenge in current research.

[0005] On the other hand, eavesdropping terminals in wireless communication systems can also benefit from the channel gain boost provided by RIS (Remote Sensing and Receiver Interface), thus posing a potential threat to communication security. Therefore, how to effectively prevent eavesdropping terminals from obtaining confidential information in RIS-assisted wireless communication systems has become one of the key research issues. Physical Layer Security (PLS), as an effective anti-eavesdropping method, has received widespread attention in recent years. In traditional security optimization problems, research usually focuses on maximizing the system's secrecy rate, that is, maximizing the difference between the reachable rate of legitimate user terminals and the reachable rate of eavesdropping terminals. However, this method cannot directly impose strict constraints on the Quality of Service (QoS) of eavesdropping terminals, and cannot guarantee that communication security is always within a controllable range.

[0006] Furthermore, the addition of schedulable degrees of freedom (DoF) for transmitted / reflected signals by STAR-RIS further increases the complexity of the optimization problem. Specifically, STAR-RIS requires simultaneous optimization of both the transmission and reflection matrices, making existing RIS security optimization strategies difficult to directly apply to STAR-RIS systems. Therefore, how to fully utilize the additional optimization degrees of freedom in the STAR-RIS environment to enhance physical layer security and effectively reduce the signal quality of eavesdropping terminals while ensuring the QoS of legitimate user terminals is one of the important directions of current physical layer security research. On the one hand, in MISO systems, base station APs use beamforming technology to transmit information to legitimate user terminals, and STAR-RIS optimizes the wireless channel by intelligently controlling the reflection and transmission characteristics of the incident signal. However, the AP beamforming vector and the STAR-RIS coefficient matrix are highly coupled, both affecting the quality of the received signal. Therefore, how to effectively decouple them and optimize them collaboratively to maximize the communication quality of legitimate user terminals while suppressing the signal reception capability of eavesdropping terminals is one of the key problems that needs to be solved. On the other hand, STAR-RIS typically needs to satisfy phase constraints as well as energy conservation constraints for reflection and transmission coefficients. These constraints make the optimization problem highly non-convex, making it difficult to solve directly using traditional optimization methods. Therefore, designing efficient optimization algorithms that enable STAR-RIS to achieve optimal signal modulation while satisfying its own constraints is another key challenge. Summary of the Invention

[0007] The purpose of this invention is to overcome the shortcomings of the prior art and provide an energy-saving and secure communication method for a multi-user downlink MISO system. In the case of an eavesdropping terminal in the MISO system, by jointly designing the beamforming vector of the AP and the coefficient matrix of STAR-RIS, the QoS of legitimate user terminals is guaranteed while limiting the QoS of eavesdropping terminals, and the transmit power required by the base station AP is saved as much as possible.

[0008] To achieve the above objectives, the present invention is implemented using the following technical solution:

[0009] In a first aspect, the present invention provides an energy-saving and secure communication method for a multi-user downlink MISO system, based on a wireless communication system, wherein the wireless communication system includes at least a base station, STAR-RIS, a legitimate user terminal, and an eavesdropping terminal.

[0010] The communication method includes the following steps:

[0011] An optimization problem is constructed with the objective of minimizing the base station AP transmit power, and the objective function is obtained;

[0012] Introduce an auxiliary variable and add it as a penalty term to the objective function;

[0013] The variables that need to be optimized are divided into: AP beamforming vector, STAR-RIS coefficient matrix and auxiliary variables;

[0014] The penalty coefficient of the penalty term in the objective function is dynamically adjusted to obtain the updated objective function. Based on the updated objective function, the block coordinate descent (BCD) method is used to solve the optimization problem. The AP beamforming vector, the coefficient matrix of STAR-RIS, and the auxiliary variables are optimized step by step until the preset conditions are met, and the optimization result is obtained.

[0015] Furthermore, the wireless communication network deploys a STAR-RIS with N units to assist a base station AP with M antennas in transmitting confidential information to two legitimate single-antenna user terminals (legitimate user terminal r in the reflection area and legitimate user terminal t in the transmission area) in the presence of two single-antenna eavesdropping terminals (eavesdropping terminal re in the reflection area and eavesdropping terminal te in the transmission area). Both re and te can eavesdrop on r and t. If variable e represents the eavesdropping terminal, then... If variable k represents a valid user terminal, then .

[0016] The base station AP's transmitted signal is , and Let r and t represent the data transmitted to r and t respectively, and satisfy the following conditions: . and They represent and The beamforming vector. Therefore, the total transmit power of the base station is .

[0017] STAR-RIS is a... A metasurface of electromagnetic units, wherein and These represent the number of horizontal and vertical units in STAR-RIS, respectively. The coefficient matrix of STAR-RIS is... When the legitimate user terminal or the eavesdropping terminal is in the reflection zone (i.e. , When ), the coefficient matrix of STAR-RIS is equal to the coefficient matrix of the valid user terminal r. When the legitimate user terminal or the eavesdropping terminal is located in the transmission area (i.e. , When ), the coefficient matrix of STAR-RIS is equal to the coefficient matrix of the valid user terminal t. .

[0018] The base station AP possesses perfect Channel State Information (CSI) for all channels. The path loss model adopts... ,in, The path loss is referenced when the distance is 1m. This is the path loss factor. This refers to the distance between the transmitting and receiving devices. This represents the equivalent baseband channel from the base station (AP) to STAR-RIS. and These represent the equivalent baseband channels from STAR-RIS to legitimate user terminal k (referring to legitimate user terminal r located in the reflection area and legitimate user terminal t located in the transmission area, respectively) and eavesdropping terminal e (referring to eavesdropping terminal re located in the reflection area and eavesdropping terminal te located in the transmission area, respectively). , and It follows the Rice decay model. This represents the equivalent baseband channel from base station AP to legitimate user terminal k. This represents the equivalent baseband channel from base station AP to eavesdropper terminal e. and Obey Rayleigh decay.

[0019] The signals received by user k and the eavesdropper terminal e can be represented as follows:

[0020]

[0021]

[0022] in, and The additive white Gaussian noise (AWGN) at user k and e-terminal e both obey the following rules:

[0023] Therefore, legitimate user terminal k ( The signal-to-interference-and-noise ratio (SINR) of the signal is: ,in, .

[0024] The signal-to-interference-plus-noise ratio (SIR) of the eavesdropping terminal e when eavesdropping on the legitimate user terminal k is: ,in, (when hour, ,when hour, ).

[0025] Furthermore, an optimization problem is constructed with the objective of minimizing the base station AP transmit power, including:

[0026] Construct an optimization problem that minimizes the transmit power required by the base station AP under the following constraints:

[0027] STAR-RIS Phase Constraints: Reflection Phase Coefficient of Each Unit and transmission phase coefficient Independently adjustable, and θ n r , θ n t ∈ [ 0 , 2 π ] ;

[0028] STAR-RIS amplitude constraint: reflection amplitude coefficient of each unit With transmission amplitude coefficient satisfy β n r , β n t ∈ [ 0 , 1 ] , β n r + β n t = 1 ;

[0029] QoS constraints for legitimate user terminals: The minimum signal-to-interference-plus-noise ratio (SINNR) for legitimate user terminals is a threshold. ;

[0030] QoS constraints for eavesdropping terminals: The maximum signal-to-interference-plus-noise ratio (SIR) of the eavesdropping terminal is a threshold. ;

[0031] The objective function is: .

[0032] Furthermore, auxiliary variables are introduced and added as penalty terms to the objective function, including:

[0033] By introducing auxiliary variables and This is then added as a penalty term to the objective function to decouple the AP beamforming vector and the STAR-RIS coefficient matrix coupled in the QoS constraints, and the penalty coefficient is set to obtain the objective function:

[0034]

[0035] Where obj is the processed objective function; Indicates the total power of the base station. The penalty coefficient is... For the channel of legitimate client terminal k; w i This represents the beamforming vector of the data from the i-th device. For the eavesdropper terminal e's channel.

[0036] Furthermore, the penalty coefficient of the penalty term in the objective function is dynamically adjusted to obtain an updated objective function. Based on the updated objective function, the block coordinate descent (BCD) method is used to solve the optimization problem, optimizing the AP beamforming vector, the coefficient matrix of STAR-RIS, and auxiliary variables step by step until the preset conditions are met, yielding the optimization results, including:

[0037] Step 1: Obtain simulation parameters, including the number of base station antennas M and the number of STAR-RIS units. and 3D coordinates of base station AP 3D coordinates of the STAR-RIS center 3D coordinates of legitimate user terminals in the reflection area 3D coordinates of legitimate user terminals in the transmission area 3D coordinates of the eavesdropping terminal in the reflection area 3D coordinates of the eavesdropping terminal in the transmission area Rice factor Path loss when reference distance is 1m Path loss factor ,noise QoS requirement thresholds for legitimate user terminals and eavesdropping terminals , Simulation times (frame), penalty coefficient scaling factor Convergence accuracy , , The maximum number of inner iterations (maxIter) and the total power. Average power .

[0038] Step 2: Construct the line-of-sight transmission portion of the channel.

[0039] Step 3: Set the simulation run count to 1.

[0040] Step 4: Add non-line-of-sight transmission components to each channel to form a complete channel, and initialize the AP beamforming vector, the coefficient matrix of STAR-RIS, auxiliary variables, and the reflection amplitude coefficient, transmission amplitude coefficient, reflection phase coefficient, and transmission phase coefficient of each adjustable electromagnetic unit of STAR-RIS.

[0041] Step 5: Initialize the objective function value objvalue=100, and set the iteration count iter=0.

[0042] Step 6: If If the iteration count is positive, increment iter by one, start the inner loop, use the block descent method (BCD) to solve the optimization problem, optimize the AP beamforming vector, the coefficient matrix of STAR-RIS and the auxiliary variables step by step, and proceed to step 7; otherwise, proceed to step 8.

[0043] Step 7: Calculate the objective function:

[0044] ,if Proceed to step 8; otherwise, set objvalue=obj and proceed to step 6.

[0045] Step 8: Update the penalty coefficient Proceed to step 9;

[0046] Step 9: Calculation and .if , and order If yes, proceed to step 10; otherwise, proceed to step 6.

[0047] Step 10: If the number of simulations is less than the maximum number of simulations, i.e. Proceed to step 4; otherwise, output... .

[0048] Furthermore, the optimization method for the AP beamforming vector includes:

[0049] calculate ,in, For size The identity matrix;

[0050] Will Substitution In the process, the AP beamforming vector is calculated. ( The closed-form solution of ).

[0051] Furthermore, the optimization method for the coefficient matrix of STAR-RIS includes:

[0052] From the reflection coefficient matrix and transmission coefficient matrix Obtain and , where “*” indicates conjugate;

[0053] for , , Calculate separately , , ,as well as , ;

[0054] make , , , ;

[0055] right and Perform eigenvalue decomposition and take the largest eigenvalue to obtain... and ;

[0056] calculate θ r = exp ( j arg [ ( λ r,max I N − Γ r ) v ̃ r − Ξ r ] ) and θ t = exp ( j arg [ ( λ t,max I N − Γ t ) v ̃ t − Ξ t ] ) Get at this time and ;

[0057] calculate , , β r = [ β 1 r , ⋯ β N r ] H , β t = [ β 1 t , ⋯ β N t ] H ;

[0058] The objective function is solved using CVX as follows:

[0059] ,

[0060] Constraints To solve the convex problem, we obtain the amplitude at this point. and .

[0061] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0062] 1. Unlike traditional methods, this invention adopts a more direct secure communication strategy, namely, constraining the QoS of legitimate user terminals and eavesdropping terminals respectively, so that legitimate user terminals can meet communication quality requirements while effectively suppressing the receiving capabilities of eavesdropping terminals, thus providing stronger security.

[0063] 2. Compared with common optimization of security rate, this invention can more directly constrain the QoS requirements of legitimate user terminals and eavesdropping terminals respectively, thereby ensuring the communication quality of legitimate user terminals while effectively limiting the received signal quality of eavesdropping terminals and minimizing the base station's transmission power.

[0064] 3. This method not only improves optimization efficiency but also significantly enhances the physical layer security of the system and reduces the risk of eavesdropping. By introducing auxiliary variables and penalty terms, the coupled AP beamforming vector and STAR-RIS coefficient matrix problems in QoS constraints are decoupled, making the optimization problem simpler and more solvable. BCD block optimization is used to optimize the AP beamforming vector, STAR-RIS coefficient matrix, and auxiliary variables. A closed-form solution for the AP beamforming vector is given through first-order optimality conditions, and a closed-form solution for the amplitude matrix in the STAR-RIS coefficient matrix is ​​given using the MM algorithm, reducing the algorithm's complexity and improving the convergence speed. Lagrange dual parallel optimization of auxiliary variables further accelerates the solution process and improves the overall system performance. Attached Figure Description

[0065] Figure 1 This is a schematic diagram of an energy-saving and secure communication system for a multi-user downlink MISO system provided in an embodiment of the present invention;

[0066] Figure 2 This is a schematic diagram showing the change curve of base station AP transmit power versus STAR-RIS unit number N provided in an embodiment of the present invention;

[0067] Figure 3 The transmit power of the base station AP provided in this embodiment of the invention is related to the transmit power of the legitimate user terminal. A schematic diagram of the change curve;

[0068] Figure 4 This is a flowchart of the algorithm of the present invention;

[0069] Figure 5 This is a flowchart for optimizing AP beamforming vectors;

[0070] Figure 6 This is a flowchart for optimizing the coefficient matrix of STAR-RIS;

[0071] Figure 7 It is to optimize auxiliary variables flow chart;

[0072] Figure 8 It is to optimize auxiliary variables flow chart. Detailed Implementation

[0073] The present invention will be further described below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and should not be used to limit the scope of protection of the present invention.

[0074] Example 1:

[0075] This embodiment first introduces an energy-saving and secure communication system for a multi-user downlink MISO system, including:

[0076] The base station AP is equipped with M antennas for generating and transmitting beamforming signals;

[0077] STAR-RIS contains N tunable electromagnetic units, each of which supports both reflection and transmission modes. The amplitude coefficients of reflection and transmission satisfy the energy conservation constraint, and the phase coefficients can be independently adjusted.

[0078] Legitimate user terminals are distributed in the reflection and transmission areas of STAR-RIS, receiving signals after being modulated by the base station AP through STAR-RIS, as well as signals from the direct link between the base station AP and the legitimate user terminals.

[0079] The eavesdropping terminals are located in the reflection or transmission areas of STAR-RIS and their received signal quality is limited.

[0080] The system minimizes the base station AP's transmit power by jointly optimizing the beamforming vector of the base station AP and the coefficient matrix of STAR-RIS, while satisfying the QoS requirements of legitimate user terminals and suppressing the QoS of eavesdropping terminals.

[0081] Consider as Figure 1 The STAR-RIS-assisted downlink communication network shown deploys a STAR-RIS network with N units to assist a base station AP with M antennas in transmitting confidential information to two legitimate user terminals (legitimate user terminal r in the reflection area and legitimate user terminal t in the transmission area) in the presence of two single-antenna eavesdropping terminals (eavesdropping terminal re in the reflection area and eavesdropping terminal te in the transmission area). Both re and te can eavesdrop on r and t. If variable e represents the eavesdropping terminal, then... If variable k represents a valid user terminal, then .

[0082] The base station AP's transmitted signal is , and Let r and t represent the data transmitted to r and t respectively, and satisfy the following conditions: . and They represent and The beamforming vector. Therefore, the total transmit power of the base station is .

[0083] STAR-RIS is a... A metasurface of electromagnetic units, wherein and These represent the number of horizontal and vertical units in STAR-RIS, respectively. The coefficient matrix of STAR-RIS is... When the legitimate user terminal or the eavesdropping terminal is in the reflection zone (i.e. , When ), the coefficient matrix of STAR-RIS is equal to the coefficient matrix of the valid user terminal r. When the legitimate user terminal or the eavesdropping terminal is located in the transmission area (i.e. , When ), the coefficient matrix of STAR-RIS is equal to the coefficient matrix of the valid user terminal t. .

[0084] This invention employs the STAR-RIS energy splitting (ES) scheme, meaning that all electromagnetic units of the STAR-RIS are in simultaneous reflection and transmission modes. The reflection and transmission amplitude coefficients of the nth element of the STAR-RIS are expressed as... and It needs to meet the following requirements. The reflection and transmission phase coefficients of the nth element are expressed as follows: and It needs to meet the following requirements. .

[0085] To study the maximum performance gain brought by STAR-RIS, it is assumed that the base station AP has perfect Channel State Information (CSI) for all channels. The path loss model adopts... ,in, The path loss is referenced when the distance is 1m. This is the path loss factor. This refers to the distance between the transmitting and receiving devices. This represents the equivalent baseband channel from the base station (AP) to STAR-RIS. and These represent the equivalent baseband channels from STAR-RIS to legitimate user terminal k (referring to legitimate user terminal r located in the reflection area and legitimate user terminal t located in the transmission area, respectively) and eavesdropping terminal e (referring to eavesdropping terminal re located in the reflection area and eavesdropping terminal te located in the transmission area, respectively). , and It follows the Rice decay model. This represents the equivalent baseband channel from base station AP to legitimate user terminal k. This represents the equivalent baseband channel from base station AP to eavesdropper terminal e. and Obey Rayleigh decay.

[0086] The signals received by user k and the eavesdropper terminal e can be represented as follows:

[0087]

[0088]

[0089] in, and The additive white Gaussian noise (AWGN) at user k and e-terminal e both obey the following rules:

[0090] Therefore, legitimate user terminal k ( The signal-to-interference-and-noise ratio (SINR) of the signal is: ,in, .

[0091] The signal-to-interference-plus-noise ratio (SIR) of the eavesdropping terminal e when eavesdropping on the legitimate user terminal k is: ,in, (when hour, ,when hour, ).

[0092] To ensure the QoS of legitimate user terminals and limit the QoS of eavesdropping terminals, the minimum SINR of legitimate user terminals is required to be [value missing]. , that is The maximum SINR of the eavesdropping terminal is ,Right now .

[0093] Therefore, this patent provides for the following constraints:

[0094] Phase constraints of STAR-RIS ),

[0095] STAR-RIS amplitude constraint ( )as well as

[0096] QoS constraints for legitimate user terminals )and

[0097] QoS constraints of eavesdropping terminals ),

[0098] Minimize the transmit power required by the base station AP (i.e., minimize) (Design scheme)

[0099] To address the coupling between optimization variables and the nonconvexity introduced by STAR-RIS (i.e., and This patent proposes an energy-saving and secure communication method for a multi-user downlink MISO system, specifically employing a penalty-based algorithm and the Block Coodinate Descent (BCD) method to solve the problem.

[0100] Specifically, this patent invention proposes a two-layer algorithm based on penalty, in which the inner layer solves the penalty optimization problem by applying BCD, while the outer layer updates the penalty coefficient until convergence is achieved.

[0101] By introducing auxiliary variables and This is then added as a penalty term to the objective function to decouple the AP beamforming vector and the STAR-RIS coefficient matrix coupled in the QoS constraints. The variables to be optimized are then divided into three parts:

[0102] 1) Base station AP beamforming vector ,

[0103] 2) STAR-RIS coefficient matrix ,

[0104] 3) Auxiliary variables .

[0105] In one iteration, while keeping the other two blocks fixed, each of the three optimization variables mentioned above is optimized alternately. This process is repeated until convergence is achieved (i.e., the score of the objective function decreases less than a preset threshold or the maximum number of iterations is reached).

[0106] For details of the proposed energy-saving and secure communication method for multi-user downlink MISO systems, please refer to [link / reference]. Figure 4 The process includes the following steps:

[0107] Step 1: Given simulation parameters, including the number of base station antennas M and the number of STAR-RIS units. and 3D coordinates of base station AP 3D coordinates of the STAR-RIS center 3D coordinates of legitimate user terminals in the reflection area 3D coordinates of legitimate user terminals in the transmission area 3D coordinates of the eavesdropping terminal in the reflection area 3D coordinates of the eavesdropping terminal in the transmission area Rice factor Path loss when reference distance is 1m Path loss factor ,noise QoS requirement thresholds for legitimate user terminals and eavesdropping terminals , Simulation times (frame), penalty coefficient scaling factor Convergence accuracy , , The maximum number of inner iterations (maxIter) and the total power. Average power .

[0108] Step 2: Construct the line-of-sight transmission portion of the channel .definition , .

[0109] (2.1) Constructing the line-of-sight transmission portion of the channel from the base station AP to STAR-RIS ;:

[0110] According to the formula It can calculate the distance from the base station AP to STAR-RIS. ;

[0111] According to the formula The angle of departure (AoD) from the base station (AP) to the STAR-RIS can be calculated. ,in, This represents the third position in the STAR-RIS three-dimensional coordinate system.

[0112] According to the formula It can calculate the angle of arrival from the base station AP to STAR-RIS. ;

[0113] According to the formula It can calculate the angle of arrival (AoA) from the base station (AP) to the STAR-RIS. .

[0114] According to the formula The array response of the base station can be calculated. ;

[0115] According to the formula:

[0116] Calculate the array response of STAR-RIS ;

[0117] According to the formula Constructing a line-of-sight channel from the base station AP to STAR-RIS .

[0118] (2.2) Constructing the line-of-sight channel from STAR-RIS to the legitimate user terminal r :

[0119] According to the formula The distance from STAR-RIS to the legitimate user terminal r can be calculated. ;

[0120] According to the formula The departure angle from STAR-RIS to the legitimate user terminal r can be calculated. ;

[0121] According to the formula The departure angle from STAR-RIS to the legitimate user terminal r can be calculated. ;

[0122] According to the formula:

[0123] Calculate the array response of STAR-RIS ;

[0124] According to the formula Constructing a line-of-sight channel from STAR-RIS to the legitimate user terminal r .

[0125] (2.3) Construct the line-of-sight channel from STAR-RIS to the legitimate user terminal :

[0126] According to the formula The distance from STAR-RIS to the legitimate user terminal t can be calculated. ;

[0127] According to the formula The departure angle from STAR-RIS to the legitimate user terminal t can be calculated. ;

[0128] According to the formula The departure angle from STAR-RIS to the legitimate user terminal t can be calculated. ;

[0129] According to the formula:

[0130] Calculate the array response of STAR-RIS ;

[0131] According to the formula Constructing a line-of-sight channel from STAR-RIS to the legitimate user terminal t .

[0132] (2.4) Constructing a line-of-sight channel from STAR-RIS to the eavesdropper terminal re :

[0133] According to the formula The distance from STAR-RIS to the eavesdropper's terminal re can be calculated. ;

[0134] According to the formula The departure angle from STAR-RIS to the eavesdropper terminal re can be calculated. ;

[0135] According to the formula The departure angle from STAR-RIS to the eavesdropper terminal re can be calculated. ;

[0136] According to the formula:

[0137] Calculate the array response of STAR-RIS ;

[0138] According to the formula Constructing a line-of-sight channel from STAR-RIS to the eavesdropping terminal re .

[0139] (2.5) Constructing a line-of-sight channel from STAR-RIS to the eavesdropper terminal te :

[0140] According to the formula The distance from STAR-RIS to the eavesdropper's terminal can be calculated. ;

[0141] According to the formula The departure angle from STAR-RIS to the eavesdropper's terminal can be calculated. ;

[0142] According to the formula The departure angle from STAR-RIS to the eavesdropper's terminal can be calculated. ;

[0143] According to the formula:

[0144] Calculate the array response of STAR-RIS ;

[0145] According to the formula Constructing a line-of-sight channel from STAR-RIS to the eavesdropper terminal .

[0146] Step 3: Simulation count run=1.

[0147] Step 4: Initialization.

[0148] (4.1) Add the NLoS component to construct the channel from the base station AP to STAR-RIS. ,in, ( Each element of ) follows a complex Gaussian distribution with a mean of 0 and a variance of 1, and they are independent of each other.

[0149] (4.2) Add the NLoS component to construct the channel from the base station AP to the legitimate user terminal k as follows: ,in, ( Each element of ) follows a complex Gaussian distribution with a mean of 0 and a variance of 1, and they are independent of each other.

[0150] (4.3) Add the NLoS component to construct the channel from the base station AP to the eavesdropping terminal e as follows: ,in, ( Each element of ) follows a complex Gaussian distribution with a mean of 0 and a variance of 1, and they are independent of each other.

[0151] (4.4) Construct the channel from base station AP to legitimate user terminal k as follows: According to the formula It can calculate the distance from the base station AP to the legitimate user terminal k. Then the channel from base station AP to legitimate user terminal k is: , ( Each element of ) follows a complex Gaussian distribution with a mean of 0 and a variance of 1, and they are independent of each other.

[0152] (4.5) Construct the channel from the base station AP to the eavesdropping terminal e as follows: According to the formula The distance from the base station AP to the eavesdropping terminal e can be calculated. The channel from the base station AP to the eavesdropper terminal e is then... , ( Each element of ) follows a complex Gaussian distribution with a mean of 0 and a variance of 1, and they are independent of each other.

[0153] (4.6) Generating random functions in MATLAB , , And order Then there is .

[0154] (4.7) Let , Initialize the beamforming vector to .

[0155] (4.8) Initialize the auxiliary variable to , .

[0156] Step 5: Initialize the objective function value objvalue=100, and set the iteration count iter=0.

[0157] Step 6: If ,make The inner loop begins, and the optimization problem is solved using the block coordinate descent method (BCD). The AP beamforming vector, the coefficient matrix of STAR-RIS, and the auxiliary variables are optimized step by step. That is, (6.1)-(6.4) are executed sequentially, and then step 7 is entered; otherwise, step 8 is entered.

[0158] (6.1) As Figure 5 As shown, the AP beamforming vector is optimized. ( ).

[0159] First calculate ,in, For size The identity matrix;

[0160] Will Substitution In the process, the AP beamforming vector is calculated. ( The closed-form solution of ).

[0161] (6.2) As Figure 6 As shown, the reflection and transmission coefficient matrices of STAR-RIS are optimized. and .

[0162] First from and Obtain and , where “*” indicates conjugate;

[0163] for , , Calculate the intermediate variables separately:

[0164] , , ,as well as , ;

[0165] make , , , .

[0166] right and Perform eigenvalue decomposition and take the largest eigenvalue to obtain... and ;

[0167] calculate and Get at this time and ;

[0168] calculate , , , ;

[0169] Solving the objective function using CVX is:

[0170] ,

[0171] Constraints To solve the convex problem, we obtain the amplitude at this point. and .

[0172] renew and .

[0173] (6.3) such as Figure 7 As shown, optimize auxiliary variables :

[0174] definition , .

[0175] First consider In the case of, if Then Updated to Otherwise, enter ;

[0176] initialization , , .

[0177] make Bring it in ,if Then let Otherwise, .calculate ,if Then the iteration ends, and Updated to Otherwise, let ,repeat .

[0178] (6.4) such as Figure 8 As shown, optimize auxiliary variables :

[0179] definition , .

[0180] First consider In the case of, if Then Updated to Otherwise, enter ;

[0181] initialization , , .

[0182] make Bring it in ,if Then let Otherwise, .calculate ,if Then the iteration ends, and Updated to Proceed to step 7; otherwise, let ,repeat .

[0183] Step 7: Calculate the objective function:

[0184] ,if Proceed to step 8; otherwise, set objvalue=obj and proceed to step 6.

[0185] Step 8: Update the penalty coefficient Proceed to step 9;

[0186] Step 9: Calculate the convergence metric and .if ,but and order If the channel is random, proceed to step 10; otherwise, proceed to step 6. Since the channel is random, multiple simulations are required to obtain the average value.

[0187] Step 10: If the number of simulations is less than the maximum number of simulations, i.e. Proceed to step 4; otherwise, output... .

[0188] Compared to common optimization methods for security ratios, this invention can more directly constrain the QoS requirements of legitimate user terminals and eavesdropping terminals separately. This ensures the communication quality of legitimate user terminals while effectively limiting the received signal quality of eavesdropping terminals and minimizing the base station's transmit power. This method not only improves optimization efficiency but also significantly enhances the physical layer security of the system and reduces the risk of eavesdropping. By introducing auxiliary variables and penalty terms, the coupled AP beamforming vector and STAR-RIS coefficient matrix problems in the QoS constraints are decoupled, making the optimization problem simpler and more solvable. BCD block optimization is used to optimize the AP beamforming vector, the STAR-RIS coefficient matrix, and auxiliary variables. A closed-form solution for the beamforming vector is given through first-order optimal conditions, and a closed-form solution for the amplitude matrix in the STAR-RIS coefficient matrix is ​​given using the MM algorithm, reducing algorithm complexity and improving convergence speed. Lagrange dual parallel optimization of auxiliary variables further accelerates the solution process and improves the overall system performance.

[0189] Example 2:

[0190] This embodiment provides an energy-saving and secure communication method for a multi-user downlink MISO system, applied to the system described in Embodiment 1, including:

[0191] Channel parameters are measured in real time and updated based on Ricean fading model and Rayleigh fading model;

[0192] Based on the updated channel parameters, the reflection amplitude coefficient, transmission amplitude coefficient, reflection phase coefficient, and transmission phase coefficient of each STAR-RIS unit are initialized to obtain the initial coefficient matrix;

[0193] Based on the channel parameters and the initial coefficient matrix, an optimization problem is constructed with the objective of minimizing the base station AP transmit power, and the objective function and initial feasible solution are obtained.

[0194] The penalty coefficient of the objective function is dynamically adjusted to obtain the updated objective function;

[0195] Based on the updated objective function, the block coordinate descent (BCD) method is used to optimize the AP beamforming vector, the coefficient matrix of STAR-RIS, and auxiliary variables step by step until the preset conditions are met, and the optimization results are output.

[0196] When initializing the reflection amplitude coefficient, transmission amplitude coefficient, reflection phase coefficient, and transmission phase coefficient of each STAR-RIS unit, the energy conservation constraint is satisfied: and phase range: .

[0197] The optimization method for the AP beamforming vector includes:

[0198] calculate ,in, For size The identity matrix;

[0199] Will Substitution In the process, the AP beamforming vector is calculated. ( The closed-form solution of ).

[0200] The optimization method for the STAR-RIS coefficient matrix includes:

[0201] From the reflection coefficient matrix and transmission coefficient matrix Obtain and , where “*” indicates conjugate;

[0202] for , , Calculate separately , , ,as well as , ;

[0203] make , , , ;

[0204] right and Perform eigenvalue decomposition and take the largest eigenvalue to obtain... and ;

[0205] calculate and Get at this time and ;

[0206] calculate , , , ;

[0207] The objective function is solved using CVX as follows:

[0208] ,

[0209] Constraints To solve the convex problem, we obtain the amplitude at this point. and .

[0210] The optimization methods for the auxiliary variables include:

[0211] Optimize auxiliary variables :

[0212] definition , ;

[0213] First consider In the case of, if Then Updated to Otherwise, enter ;

[0214] initialization , , .

[0215] make Bring it in ,if Then let Otherwise, .calculate ,if Then the iteration ends, and Updated to Otherwise, let ,repeat ;

[0216] Optimize auxiliary variables :

[0217] definition , ;

[0218] First consider In the case of, if Then Updated to Otherwise, enter ;

[0219] initialization , , ;

[0220] make Bring it in ,if Then let Otherwise, .calculate ,if Then the iteration ends, and Updated to Otherwise, let ,repeat .

[0221] The following description, in conjunction with a preferred embodiment, illustrates the content involved in the above embodiments.

[0222] The specific method for energy-saving optimization in this embodiment includes the following steps:

[0223] Table 1 Simulation Parameters

[0224]

[0225] 1. According to step 1 above, set the system according to the parameters given in Table 1.

[0226] 2. Construct the channel according to step 2. Calculate... , , , ,

[0227] , , ,

[0228] , , ,

[0229] , , ,

[0230] , , ,

[0231] , , ,

[0232] Then , And the calculated and , Substituting this into step 2, we obtain the line-of-sight transmission portion of the channel. , ( ),and ( ).

[0233] III. Take the first simulation, i.e., as an example to illustrate the process of one simulation in the frame simulations.

[0234] IV. Initialize according to Step 4.

[0235] According to Steps (4.1)-(4.5), add the NLOS component of the channel to obtain the complete channel for the current simulation and , , , and , , , .

[0236] Obtain

[0237] ,

[0238] ,

[0239] ,

[0240] ,

[0241] Obtain

[0242] ,

[0243] ,

[0244] Obtain

[0245] , , , ,

[0246] , , ,,

[0247] V. At this time, iter = 0 < maxIter, let Proceed to Step 6.

[0248] VI. Calculate the AP beamforming vector according to (6.1) as

[0249] ,

[0250] ,

[0251] VII. According to (6.2) and calculate , , , After that, and Perform eigenvalue decomposition and take its largest eigenvalue to obtain... and Substitute into (6.2) get and ,

[0252] 8. Solve (6.2) For the convex problem, we get:

[0253] ,

[0254] ,

[0255] Will and Updated to and .

[0256] 9. According to (6.3), we obtain ,Will Updated to , , , .

[0257] 10. According to (6.4), we obtain ,Will Updated to , , , Proceed to step 7.

[0258] 11. Calculate according to step 7 ,at this time Then let Continue repeating step 6 until... Proceed to step 8.

[0259] 12. Update according to step 8 .

[0260] 13. Calculate according to step 9 and ,at this time Then proceed to step 6 and repeat the above steps until... Then let .

[0261] XIV. At this time Proceed to step 4 to perform the next simulation, and continue until completion. In the second simulation, the average transmit power of the base station AP at this time is output as follows: .

[0262] Algorithm simulation results:

[0263] Figure 2 shows a performance comparison of the base station AP transmit power optimized using this patent with two other schemes as the number of STAR-RIS units N increases. It can be seen that the performance of this patent surpasses both the STAR-RIS scheme using a fixed coefficient matrix and the scheme without STAR-RIS, and the performance difference between the three schemes becomes more pronounced as N increases.

[0264] Figure 3 compares the relationship between base station AP transmit power and the SINR of legitimate user terminals. As expected, higher SINR requires higher transmit power to meet the required communication quality. Compared to STAR-RIS using a fixed coefficient matrix and schemes without STAR-RIS, this patent achieves lower transmit power. This well illustrates the effectiveness of STAR-RIS in saving transmit power under SINR constraints.

[0265] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for energy-saving and secure communication in a multi-user downlink MISO system, characterized in that, Based on a wireless communication system, the wireless communication system includes at least a base station AP, a STAR-RIS, a legitimate user terminal, and an eavesdropping terminal; The communication method includes the following steps: An optimization problem is constructed with the objective of minimizing the base station AP transmit power, and the objective function is obtained; Introduce an auxiliary variable and add it as a penalty term to the objective function; The variables that need to be optimized are divided into: AP beamforming vector, STAR-RIS coefficient matrix and auxiliary variables; The penalty coefficient of the penalty term in the objective function is dynamically adjusted to obtain the updated objective function. Based on the updated objective function, the block coordinate descent method is used to solve the optimization problem. The AP beamforming vector, the coefficient matrix of STAR-RIS, and the auxiliary variables are optimized step by step until the preset conditions are met, and the optimization result is obtained. Introduce auxiliary variables and add them as penalty terms to the objective function, including: By introducing auxiliary variables and and adding them as penalty terms to the objective function to decouple the coupled AP beamforming vectors and the coefficient matrix of STAR-RIS in the QoS constraint, and add a penalty coefficient, get the processed objective function: ； Wherein, obj is the processed objective function; denotes the total power of the base station, is a penalty coefficient, is the channel of the legal client terminal k; w i denotes the beamforming vector of the first i device data, is the channel of the eavesdropper terminal e k; re This indicates the eavesdropping terminal located in the reflection zone. te This indicates the eavesdropping terminal located in the transmission zone. r This indicates a legitimate user terminal located in the reflection zone. ，t This indicates a legitimate user terminal located in the transmission area, and re and te All are capable of eavesdropping r and t ; Use variables e Indicates the eavesdropper's terminal, then ; Use variables k If it represents a legitimate user terminal, then .

2. The energy-saving and secure communication method for a multi-user downlink MISO system according to claim 1, characterized in that, The wireless communication system is deployed with a N STAR-RIS with individual units assists in having M A base station access point with one antenna is vulnerable to two single-antenna eavesdropping terminals, including one eavesdropping terminal located in a reflection area. re and eavesdropping terminals located in the transmission area te In this case, confidential information is transmitted to two single-antenna legitimate user terminals, including the legitimate user terminal located in the reflection area. r and legitimate user terminals located in the transmission area t ,and re and te All are capable of eavesdropping r and t ; Use variables e Indicates the eavesdropper's terminal, then ; Use variables k If it represents a legitimate user terminal, then ; The base station AP's transmitted signal is , and They represent the transmission to r and t The data, and satisfy ; and They represent and The beamforming vector, the total transmit power of the base station is ; STAR-RIS is a... A metasurface of electromagnetic units, wherein and These represent the number of horizontal and vertical units in STAR-RIS, respectively; the coefficient matrix of STAR-RIS is... ; When the legitimate user terminal or the eavesdropping terminal is in the reflection zone, the coefficient matrix of STAR-RIS is equal to that of the legitimate user terminal. r The coefficient matrix, ; When the legitimate user terminal or the eavesdropping terminal is located in the transmission area, the coefficient matrix of STAR-RIS is equal to that of the legitimate user terminal. t The coefficient matrix, ; The base station AP has perfect channel state information for all channels; the path loss model adopts... ,in, The path loss is referenced when the distance is 1m. This is the path loss factor. The distance between the transceiver devices; This represents the equivalent baseband channel from the base station (AP) to STAR-RIS. and These represent the connection from STAR-RIS to the legitimate user terminal. k and eavesdropping terminals e The equivalent baseband channel; , and Follows the Rice decay model; This indicates the connection from the base station (AP) to the legitimate user terminal. k The equivalent baseband channel, This indicates the distance from the base station AP to the eavesdropping terminal. e The equivalent baseband channel, and Obeying Rayleigh decay; user k and eavesdropping terminals e The signal received at the location is represented as ； ； in, and Indicates user k and eavesdropping terminals e The additive white Gaussian noise at each location follows the rules. ; Therefore, legitimate user terminals k The signal-to-interference-plus-noise ratio is Among them, legitimate user terminals k channel ; eavesdropping terminal e Eavesdropping on legitimate user terminals k The signal-to-interference-plus-noise ratio is , Among them, eavesdropping terminals e channel ,when hour, ,when hour, .

3. The energy-saving and secure communication method for a multi-user downlink MISO system according to claim 2, characterized in that, The optimization problem aimed at minimizing the base station AP transmit power includes: Construct an optimization problem that minimizes the transmit power required by the base station AP under the following constraints: STAR-RIS Phase Constraints: Reflection Phase Coefficient of Each Unit and transmission phase coefficient Independently adjustable, and ; STAR-RIS amplitude constraint: reflection amplitude coefficient of each unit With transmission amplitude coefficient satisfy ; QoS constraints for legitimate user terminals: The minimum signal-to-interference-plus-noise ratio (SINNR) for legitimate user terminals is a threshold. ; QoS constraints for eavesdropping terminals: The maximum signal-to-interference-plus-noise ratio (SIR) of the eavesdropping terminal is a threshold. ; The objective function is: ; in, w k Indicates the first k Beamforming vectors for each device's data.

4. The energy-saving and secure communication method for a multi-user downlink MISO system according to claim 3, characterized in that, The penalty coefficient of the penalty term in the objective function is dynamically adjusted to obtain an updated objective function. Based on the updated objective function, the block coordinate descent (BCD) method is used to solve the optimization problem. The AP beamforming vector, the coefficient matrix of STAR-RIS, and auxiliary variables are optimized step by step until the preset conditions are met, and the optimization results are obtained, including: Step 1: Obtain simulation parameters, including the number of base station antennas. M STAR-RIS unit count and 3D coordinates of base station AP 3D coordinates of the STAR-RIS center 3D coordinates of legitimate user terminals in the reflection area 3D coordinates of legitimate user terminals in the transmission area 3D coordinates of the eavesdropping terminal in the reflection area 3D coordinates of the eavesdropping terminal in the transmission area Rice factor Path loss when reference distance is 1m Path loss factor ,noise QoS requirement thresholds for legitimate user terminals and eavesdropping terminals , Simulation times (frame), penalty coefficient scaling factor Convergence accuracy , , The maximum number of inner iterations (maxIter) and the total power. Average power ; Step 2: Construct the line-of-sight transmission portion of the channel; Step 3: Set the simulation run count to 1; Step 4: Add non-line-of-sight transmission components to each channel to form a complete channel, and initialize the AP beamforming vector, the coefficient matrix of STAR-RIS, auxiliary variables, and the reflection amplitude coefficient, transmission amplitude coefficient, reflection phase coefficient, and transmission phase coefficient of each STAR-RIS unit. Step 5: Initialize the objective function objvalue =100, number of iterations iter =0; Step 6: If Then let the number of iterations be... iter Add one, start the inner loop, use the block coordinate descent method (BCD) to solve the optimization problem, optimize the AP beamforming vector, the coefficient matrix of STAR-RIS and auxiliary variables step by step, and proceed to step 7; otherwise, proceed to step 8. Step 7: Calculate the processed objective function: ,if Proceed to step 8; otherwise, initialize the objective function. objvalue The value is equal to obj Proceed to step 6; Step 8: Update the penalty coefficient Proceed to step 9; Step 9: Calculate the convergence index and power consumption ;if Total power consumption If the simulation count (run) is incremented by one, proceed to step 10; otherwise, proceed to step 6. Step 10: If the number of simulations is less than the maximum number of simulations. Proceed to step 4; otherwise, output the average power consumption. .

5. The energy-saving and secure communication method for a multi-user downlink MISO system according to claim 4, characterized in that, The block coordinate descent (BCD) method is used to solve the optimization problem, optimizing the AP beamforming vector, the STAR-RIS coefficient matrix, and auxiliary variables step by step, including: While fixing two parts of the AP beamforming vector, STAR-RIS coefficient matrix, and auxiliary variables in sequence, optimize the other part of the AP beamforming vector, STAR-RIS coefficient matrix, and auxiliary variables.

6. The energy-saving and secure communication method for a multi-user downlink MISO system according to claim 5, characterized in that, The optimization method for the AP beamforming vector includes: calculate ,in, For size The identity matrix; Will Substitution In the process, the AP beamforming vector is calculated. , The closed-form solution.

7. The energy-saving and secure communication method for a multi-user downlink MISO system according to claim 6, characterized in that, The optimization method for the coefficient matrix of STAR-RIS includes: From the reflection coefficient matrix and transmission coefficient matrix Obtain and , where "*" indicates conjugate; for , , Calculate separately , , ,as well as , ; make , , , ; right and Perform eigenvalue decomposition and take the largest eigenvalue to obtain... and ; calculate and Get at this time and ; calculate , , , ; The objective function is solved using CVX as follows: ， Constraints To solve the convex problem, we obtain the amplitude at this point. and .

8. The energy-saving and secure communication method for a multi-user downlink MISO system according to claim 7, characterized in that, The optimization methods for the auxiliary variables include: Optimize auxiliary variables : ① Definition , ; ② First consider In the case of, if Then Updated to Otherwise, proceed to step ③; ③ Initialization , , ; ④ Order Bring it in ,if Then let Otherwise, ;calculate ,if Then the iteration ends, and Updated to Otherwise, let Repeat ④.

9. The energy-saving and secure communication method for a multi-user downlink MISO system according to claim 8, characterized in that, Optimize auxiliary variables : ① Definition , ; ② First consider In the case of, if Then Updated to Otherwise, proceed to step ③; ③ Initialization , , ; ④ Order Bring it in ,if Then let Otherwise, ;calculate ,if Then the iteration ends, and Updated to Otherwise, let Repeat ④.

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