Energy efficiency optimization method and system for STAR-RIS assisted multi-user communication under hardware damage

Abstract

The invention discloses an energy efficiency optimization method and system for STAR-RIS assisted multi-user communication under hardware damage, and belongs to the technical field of wireless communication. According to the method, a corresponding communication system model is established, and the model considers the influence of hardware damage on the system performance. On the basis, a joint optimization problem P0 of a BS (base station) transmitting precoding vector and an STAR-RIS reflection and transmission phase shift matrix is constructed, and the purpose is to maximize the system energy efficiency. In order to effectively solve the complex optimization problem, the method decomposes the complex optimization problem into two sub-problems: BS emission precoding vector optimization and STAR-RIS reflection and transmission phase shift matrix optimization. And iteratively solving the two sub-problems through an alternative optimization algorithm until the energy efficiency of the system is maximized. According to the method, an effective energy efficiency optimization strategy is provided for the STAR-RIS assisted multi-user communication system under hardware damage, and the technical problems that a traditional RIS is insufficient in coverage range and poor in energy efficiency are solved.

Description

Technical Field

[0001] The invention belongs to the technical field of wireless communications and relates to a method and system for optimizing energy efficiency of STAR-RIS assisted multi-user communications under hardware damage. Background Art

[0002] With the rapid development of wireless communication technology, reconfigurable intelligent surfaces (RIS) as an emerging technology, with its large number of low-cost components that can intelligently adjust the phase and amplitude of the input electromagnetic wave, show great potential in improving communication energy efficiency (EE). RIS components work in a nearly passive state and do not require additional power supply. This feature significantly improves the energy efficiency of the communication system. However, traditional RIS only has the ability to reflect the incident signal, which limits its signal coverage, especially for users located at the back of the RIS, who cannot effectively use RIS technology to enhance the communication effect.

[0003] In order to overcome this limitation, researchers have proposed Simultaneous Transmission and Reflection Reconfigurable Intelligent Surfaces (STAR-RIS) in recent years. STAR-RIS can reflect and transmit signals at the same time, which greatly expands the coverage of signals and improves communication quality and energy efficiency. Compared with traditional RIS that only reflects signals, STAR-RIS shows significant advantages in signal strength and communication reliability in the target area, bringing a new performance improvement path to wireless communication systems.

[0004] In view of the significant advantages of STAR-RIS, academia and industry have launched research on the performance optimization of wireless communication systems assisted by STAR-RIS. For example, patents such as CN119135218A and CN118748840A have disclosed the energy efficiency optimization method of wireless energy transmission system assisted by STAR-RIS and the downlink wireless resource allocation method of non-orthogonal multiple access system assisted by STAR-RIS based on energy efficiency. These research results provide a theoretical basis and practical guidance for the application of STAR-RIS in wireless communication systems.

[0005] However, it is worth noting that most of the above patents and studies are based on ideal transceiver models. In actual communication systems, RF components will inevitably suffer from hardware damage, including phase noise, quantization error, amplification noise, and nonlinear distortion. These hardware damages will have a serious impact on the performance of the communication system, reducing signal quality and communication reliability.

[0006] In response to the hardware damage problem, scholars such as Liangsen Zhai and others have conducted relevant research and proposed a robust transmission design method for RIS-assisted multi-cluster wireless power communication with hardware damage to improve the system and rate. However, while these methods solve the problem of insufficient coverage of traditional RIS, they also face the challenge of balancing the improvement of system and rate with the increase of overall power consumption. In particular, in the multi-user wireless communication system assisted by STAR-RIS, how to effectively improve energy efficiency while considering hardware damage has become a key technical problem that technicians in this field urgently need to solve. Summary of the invention

[0007] The purpose of the present invention is to solve the problem of insufficient coverage of traditional RIS in the prior art, while also facing the technical problem of poor energy efficiency, and to provide a method and system for optimizing energy efficiency of STAR-RIS assisted multi-user communication under hardware damage.

[0008] In order to achieve the above object, the present invention adopts the following technical solutions: A first aspect of the present invention provides a method for optimizing energy efficiency of STAR-RIS assisted multi-user communication under hardware impairment, comprising the following steps: Establish a STAR-RIS-assisted multi-user communication system model under hardware damage; Under the model, the joint optimization problem of BS transmit precoding vector and STAR-RIS reflection and transmission phase shift matrix is ​​constructed. P 0; The joint optimization problem of BS transmit precoding vector and STAR-RIS reflection and transmission phase shift matrix is ​​decomposed into two sub-problems: BS transmit precoding vector optimization and STAR-RIS reflection and transmission phase shift matrix optimization. The optimal solution is iteratively obtained through an alternating optimization algorithm to maximize the system energy efficiency.

[0009] Furthermore, the STAR-RIS-assisted multi-user communication system model under hardware damage includes a BS, a STAR-RIS and users; the BS transmits signals to the users through the STAR-RIS; some of the users receive signals reflected by the STAR-RIS, and the other users receive signals transmitted by the STAR-RIS.

[0010] Furthermore, the joint optimization problem of the BS transmit precoding vector and the STAR-RIS reflection and transmission phase shift matrices is P 0 is described as:

[0011]

[0012] in, is the total maximum transmit power of the BS; For the k The communication rate of each user; Communication rate for user needs; is the phase of the reflection of STAR-RIS; is the transmitted phase of STAR-RIS; C4 and C5 are the amplitude coefficient constraints of STAR-RIS; represents the amplitude of the reflection of STAR-RIS; represents the amplitude of the transmission of STAR-RIS; max() is the maximum value function; is the system energy efficiency; The base station k The beamforming vectors transmitted by each user; for The conjugate transpose of .

[0013] Furthermore, the iterative method of the alternating optimization algorithm to obtain the optimal solution to maximize the system energy efficiency is specifically as follows: Fixed the STAR-RIS reflection and transmission phase shift matrix to optimize the BS transmit precoding vector; Based on the optimized BS transmit precoding vector, the STAR-RIS reflection and transmission phase shift matrices are optimized; The above process is iterated until the system energy efficiency is maximized.

[0014] Furthermore, the fixed STAR-RIS reflection and transmission phase shift matrix optimizes the BS transmit precoding vector, specifically: The STAR-RIS reflection and transmission phase shift matrices are fixed, and the Dinkelbach method is used to transform the joint optimization problem into the first optimization problem of the BS transmit precoding vector. ; The variable substitution algorithm, SCA algorithm and Taylor series expansion algorithm are used to solve the first optimization problem of BS transmitting precoding vector Transformed into the second optimization problem ; Based on the second optimization problem , get the optimal BS transmit precoding vector.

[0015] Furthermore, based on the optimized BS transmit precoding vector, the STAR-RIS reflection and transmission phase shift matrices are optimized, specifically: Based on the optimized BS transmit precoding vector, the optimization problem of STAR-RIS reflection and transmission phase shift is transformed into SDP form through SDR algorithm and SCA algorithm to obtain the optimal STAR-RIS reflection and transmission phase shift matrix.

[0016] A second aspect of the present invention provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the energy efficiency optimization method for STAR-RIS-assisted multi-user communication under hardware damage when executing the computer program.

[0017] A third aspect of the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the energy efficiency optimization method for STAR-RIS-assisted multi-user communication under hardware damage.

[0018] A fourth aspect of the present invention provides a computer program product, the computer program product comprising computer instructions, the computer instructions instructing a computer to execute the above-mentioned method for optimizing energy efficiency of STAR-RIS-assisted multi-user communication under hardware damage.

[0019] A fifth aspect of the present invention provides a system for optimizing energy efficiency of STAR-RIS-assisted multi-user communication under hardware damage, comprising: System model building module, building a STAR-RIS-assisted multi-user communication system model under hardware damage; Energy efficiency problem building module, under the model, constructs the joint optimization problem of BS transmit precoding vector and STAR-RIS reflection and transmission phase shift matrix P 0; The energy efficiency optimization module decomposes the joint optimization problem of BS transmit precoding vector and STAR-RIS reflection and transmission phase shift matrix into two sub-problems: BS transmit precoding vector optimization and STAR-RIS reflection and transmission phase shift matrix optimization; and it iterates through an alternating optimization algorithm to obtain the optimal solution to maximize the system energy efficiency.

[0020] Compared with the prior art, the present invention has the following beneficial effects: The present invention discloses a method for optimizing energy efficiency of STAR-RIS assisted multi-user communication under hardware damage. By establishing a STAR-RIS assisted multi-user communication system model including hardware damage factors, it can more accurately reflect the actual communication scenario, and then reduce the influence of hardware damage on system performance through optimization strategies, and enhance the stability and reliability of the entire communication system. By constructing the joint optimization problem P0 of BS transmission precoding vector and STAR-RIS reflection and transmission phase shift matrix, and cleverly decomposing it into two sub-problems for alternating optimization, the method can find the optimal configuration that minimizes system energy consumption while meeting user communication needs. This not only improves energy utilization efficiency, but also helps to extend the operating time of network equipment, reduce energy consumption, and conform to the current development trend of green communication. The application of the alternating optimization algorithm enables the transmission power of the BS and the phase shift configuration of STAR-RIS to be dynamically adjusted to adapt to different user needs and channel conditions, and realizes efficient and flexible allocation of resources. This adaptive mechanism ensures that the system can maintain efficient operation even in a complex communication environment, and improves user experience.

[0021] Furthermore, through the synchronous reflection and transmission function of STAR-RIS, the system can cover users more flexibly and meet the communication needs of different users. The reflected signal and the transmitted signal can serve different user groups respectively, thereby improving the breadth and depth of signal coverage. In the real environment where hardware damage is inevitable, this method effectively reduces the impact of hardware damage on the performance of the communication system through sophisticated model construction and optimization strategies.

[0022] Furthermore, facing the STAR-RIS assisted multi-user communication system with hardware impairments, its energy efficiency optimization problem is often highly complex and nonlinear. Through the alternating optimization algorithm, the original problem is decomposed into two relatively simple sub-problems, namely, optimizing the BS transmit precoding vector with a fixed STAR-RIS reflection and transmission phase shift matrix, and optimizing the STAR-RIS reflection and transmission phase shift matrix based on the optimized BS transmit precoding vector. This decomposition strategy significantly reduces the difficulty of solving the problem and improves the computational efficiency. The alternating optimization algorithm gradually approaches the optimal solution by iteratively updating the BS transmit precoding vector and the STAR-RIS reflection and transmission phase shift matrix. In each iteration, the system calculates the energy efficiency based on the current configuration and adjusts the optimization variables accordingly to ensure that the next iteration can further improve the energy efficiency. This iterative process ensures the maximization of the system energy efficiency, thereby improving the overall performance of the communication system.

[0023] Furthermore, in the case of fixed STAR-RIS reflection and transmission phase shift matrices, the optimization problem of the BS transmit precoding vector often exhibits highly nonlinear characteristics. By adopting the Dinkelbach method, the technology successfully transforms the joint optimization problem into a first optimization problem P1 about the BS transmit precoding vector, thereby reducing the complexity of the problem. In order to further solve the first optimization problem P1, the technology adopts a variable substitution algorithm, an SCA (Sequential Convex Approximation) algorithm, and a Taylor series expansion algorithm. The combined use of these algorithms not only demonstrates the flexibility of the optimization process, but also ensures the applicability of the algorithm in different scenarios. By applying these algorithms to the first optimization problem P1, it is successfully converted into a second optimization problem P3 that is easier to solve.

[0024] Furthermore, on the basis of optimizing the BS transmit precoding vector, the SDR (Semidefinite Relaxation) algorithm and the SCA (Sequential Convex Approximation) algorithm are further used to optimize the STAR-RIS reflection and transmission phase shift matrices. The optimization problem of STAR-RIS reflection and transmission phase shift is usually non-convex and difficult to solve directly. By introducing the SDR algorithm, the technology successfully transforms the original problem into a semi-definite programming (SDP) problem, thereby reducing the complexity of the solution. The SDP problem has good properties and mature solution methods in optimization theory, making the optimization process more efficient. After converting the problem into SDP form, the SCA algorithm is further used to solve it. The SCA algorithm gradually approaches the optimal solution of the original non-convex problem by constructing a series of convex approximation problems, thereby enhancing the convergence and stability of the optimization algorithm. This feature ensures that the system can stably find the optimal STAR-RIS reflection and transmission phase shift matrix even in the face of complex and changing communication environments. Based on the combined use of the SDR algorithm and the SCA algorithm, this technology can accurately solve the optimal STAR-RIS reflection and transmission phase shift matrix. The achievement of this result not only depends on the accuracy of the optimization algorithm, but also benefits from the rationality of the problem transformation. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0026] Figure 1Schematic diagram of the STAR-RIS assisted multi-user communication system model under hardware damage of the present invention; Figure 2 It is a schematic diagram of algorithm convergence performance of different distortion scale factors according to an embodiment of the present invention; Figure 3 Schematic diagram of the relationship between energy efficiency and actual transmission power under different distortion proportional factors according to an embodiment of the present invention; Figure 4 A schematic diagram of the relationship between energy efficiency and maximum transmit power of different transmission schemes according to an embodiment of the present invention; Figure 5 A schematic diagram of the relationship between energy efficiency and distortion proportional factor of different transmission schemes according to an embodiment of the present invention; Figure 6 A schematic diagram showing the relationship between the energy efficiency of different transmission schemes and the number of different STAR-RIS components according to an embodiment of the present invention; Figure 7 It is a block diagram of the energy efficiency optimization method of STAR-RIS assisted multi-user communication under hardware damage of the present invention. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. The components of the embodiments of the present invention described and marked in the drawings here can be arranged and designed in various different configurations.

[0028] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0029] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0030] The present invention is further described in detail below in conjunction with the accompanying drawings: See also Figure 7 The energy efficiency optimization method of STAR-RIS assisted multi-user communication under hardware damage disclosed by the present invention comprises the following steps: Step 1: Establish a STAR-RIS-assisted multi-user communication system model under hardware damage, such as Figure 1As shown in the figure, in this model, a base station with M antennas provides services to K single-antenna users through STAR-RIS, which has N simultaneously transmittable and reflective unit elements. Due to physical obstacles, the BS (Base Station) can only send signals to users through STAR-RIS, dividing the K users into and Two sets, of which and The signals received by the users in are reflected and transmitted by STAR-RIS respectively. Assume that the base station receives the user set and is known a priori.

[0031] In the STAR-RIS assisted multi-user communication system, the base station transmit signal can be expressed as: (1) in, The base station k Messages sent by users, The base station k The beamforming vectors transmitted by each user are distorted due to hardware impairments such as amplification noise, quantization error, and nonlinearity. , It is proportional to the transmission power of the base station and can be expressed as ,in It is the proportional factor of the base station transmission signal distortion.

[0032] In addition, users k The received signal can be expressed as

[0033] (2) in, is the required signal; The hardware of the transmitter is damaged; Interference between multiple users; represents user noise, with a mean of zero and a variance of The complex Gaussian white noise follows the distribution . Indicates user k The received distortion noise at , whose variance is related to the received signal is proportional to the power and can be expressed as ,in , which means user k The proportional factor of the received signal distortion describes the severity of hardware damage. is the reflection or transmission phase shift matrix of STAR-RIS, which depends on the user k The set to which it belongs is expressed by the following formula (3) in, , , represent the amplitude and phase of the reflection and transmission of STAR-RIS, respectively.

[0034] Accordingly, according to (2), the user k The SINR (Signal to Interference plus Noise Ratio) at is given in (4) (4) in, represents the multi-user interference considering hardware impairments, , .

[0035] Before further processing, the present invention defines the cascade channel of base station-STAR-RIS-user The phase shift vector of STAR-RIS is: (5) Based on the above transformation, formula (4) can be transformed into (6) Then the system energy efficiency considering the transceiver hardware damage can be defined as (7) in, represents the bandwidth of the system, , It represents the total power consumption of the system, which mainly includes the transmission power of the base station and the static power consumption of the system, and can be expressed as (8) in, , represents the efficiency of the base station power amplifier, where represents the transmission power of the base station, Indicates the power consumption of the system control circuit.

[0036] Step 2: Based on the system model of the STAR-RIS-assisted multi-user communication system, the joint optimization problem of the BS transmit precoding vector, STAR-RIS reflection and transmission phase shift matrices is established.

[0037] It should be noted that in step 2 of the present invention, the goal is to maximize the energy efficiency of the system under the conditions of considering the base station power consumption limit, user information rate, STAR-RIS amplitude coefficient constraint and transceiver hardware damage. The corresponding optimization problem is as follows

[0038] (10) Among them, C1 is the total maximum transmission power constraint of BS, C2 is the communication rate requirement constraint of K users, C3 is the phase shift angle constraint of STAR-RIS, and C4 and C5 are the amplitude coefficient constraints of STAR-RIS, which conforms to the law of conservation of energy.

[0039] In the above optimization problem, there are variables and , It is not easy to solve mutually coupled non-convex optimization problems directly. The optimization variables can be decoupled by using the idea of ​​alternating optimization, that is, the optimization problem can be divided into two sub-problems: BS transmit precoding vector optimization and STAR-RIS phase shift optimization, and then optimized and solved separately.

[0040] Step 3: Fix the STAR-RIS reflection and transmission phase shift matrices, and the original optimization problem can be simplified to the optimization problem of the BS transmit precoding vector. Since the objective function is in fractional form, based on the Dinkelbach method, it is converted into a more tractable form, and the optimization problem (P0) can be rewritten as (11) in is the energy efficiency auxiliary variable introduced, defined as , They are the optimal energy efficiency and optimal base station transmit precoding vector for problem (P1), It can be expressed as (12) However, due to the non-convexity of the objective function and constraint C2, ( P 1) cannot be solved directly. Next, we use the variable substitution algorithm to deal with it. The optimization problem (P1) can be further rewritten as (13) in is the auxiliary variable introduced, and then the auxiliary variable is introduced , Dealing with the non-convexity of constraint C6, it can be rewritten as (14) (15) (16) Furthermore, to deal with the non-convexity of (14), based on the SCA algorithm and Taylor series expansion algorithm, (14) becomes (17) in, , , is an auxiliary variable introduced, represents the Taylor expansion process Next, we deal with the non-convexity of (15) and (16). Specifically, let , , and using the properties , Can be transformed into (18) Furthermore, (15) and (16) can be transformed into convex forms (19) (20) Finally, the non-convex problem (P2) is successfully transformed into a solvable convex problem as follows (twenty one) in, The C9 rank-one constraint can be relaxed, making problem (P3) a typical semidefinite programming problem that can be solved by the optimization toolbox CVX.

[0041] Step 4: According to the BS transmit precoding vector obtained in step 3, further optimize the reflection and transmission phase shift matrices at STAR-RIS. First, the C5 constraint is equivalently transformed (twenty two) definition , , (22) can be further transformed into an equivalent linear form (twenty three) For problem (P1), the objective function is The non-convexity of and , the problem (P0) can be changed to the following equivalent form (twenty four) Constraint C11 is non-convex. Similarly, we introduce auxiliary variables , , , , which can be rewritten as (25) (26) (27) (28) (29) (30) Formulas (25) and (28) are still non-convex, and the SCA algorithm can also be used. Formulas (25) and (28) can be transformed into two equivalent convex constraints: (31) in, , , , , , is an auxiliary variable. For non-convex forms (26), (27), (29), (30), we define , , we can get (32) (33) (34) (35) Then problem (P4) can be transformed into the following convex form (36) in, It can be seen that problem (P5) is a typical semidefinite programming problem, and only the rank-one constraint is non-convex. The rank-one constraint is relaxed by SDR technology, and it can also be solved by the CVX toolbox of Matlab software.

[0042] Step 5: Optimize the transmit precoding vector at the BS in step 3 and the reflection and transmission phase shift matrices at the STAR-IRS in step 4. Through the alternating optimization algorithm, the optimal BS transmit precoding vector, reflection and transmission phase shift matrices are iteratively solved to maximize the system energy efficiency. Specifically, the present invention first initializes the number of iterations, the transmission and reflection coefficient matrices, and the auxiliary variables introduced when optimizing the BS precoding matrix and the STAR-IRS phase shift; then fixes the STAR-IRS phase shift vector and , after replacing the user's rate variable, use the Dinklebach algorithm and SCA algorithm to find the optimal ; Next, given the optimized BS precoding matrix , the optimization problem of STAR-RIS phase shift is transformed into SDP form by SDR algorithm and SCA algorithm to obtain the optimal and ; Finally, through the obtained , and Calculate the system energy efficiency and update the iteration value until the system energy efficiency converges to the accuracy or the maximum number of iterations is reached.

[0043] As a specific embodiment of the present invention, the above optimization method is simulated to obtain simulation results. The simulation results verify the effectiveness of the energy efficiency optimization method of a STAR-RIS-assisted multi-user communication system under hardware damage of the present invention, indicating that STAR-RIS has higher energy efficiency than the traditional RIS that can only reflect, and the communication scheme considering hardware damage has stronger robustness. In this embodiment, the present invention proposes to evaluate the performance of the energy efficiency optimization method of a STAR-RIS-assisted multi-user communication system under hardware damage of the present invention through numerical results. In this embodiment, a two-dimensional (2D) coordinate system is considered, and the coordinates are set to (0 meters, 0 meters) and (50 meters, 10 meters) respectively by using a uniform linear array and a uniform rectangular array at the BS and STAR-RIS. The BS and STAR-RIS are equipped with M = 4 antennas and N = 16 elements respectively. The coordinates of the users in the area are set to (0m, 40m) and (0m, 45m) respectively. The coordinates of the users in the area are set to (0m, 55m) and (0m, 60m) respectively.

[0044] In the simulation, for the selected channel environment, one of the advantages of STAR-RIS is its ease of deployment, which can be manually adjusted according to specific needs, and its position is relatively fixed. Installing STAR-RIS within the line of sight of the BS can significantly improve system performance. Similarly, the user is also within the line of sight of STAR-RIS. Therefore, by and the channel between STAR-RIS and the user The Rice channel model is established and expressed using the following formula (37) (38) in and are the distances between BS and STAR-RIS and between STAR-RIS and user k, respectively. and are the corresponding path loss factors respectively; It indicates the path loss when the reference distance is 1m; and is the LOS component of the corresponding channel above, and is the random NLOS component of the corresponding channel, which obeys Rayleigh fading; and is the Rice factor. Set , , The noise power of the channel is set to , the efficiency of the BS amplifier is set to , the BS antenna power consumption is set to , the constant power consumption of the BS and user circuits is set to and , the control circuit power consumption of STAR-RIS components Table 1 provides the simulation experiment parameter settings.

[0045] Table 1 Simulation experiment parameter settings

[0046] Figure 2 This is a simulation result of the convergence performance of the method of the present invention. This embodiment considers the convergence performance of the proposed method under three different distortion scale factors. From the convergence performance of the method, the three different distortion scale factors can be quickly converged within 10 rounds using the proposed method. Figure 3It is the simulation result of energy efficiency changing with actual transmission power. From the simulation results, it can be seen that the system energy efficiency of the method of the present invention first increases and then decreases with the increase of actual transmission power, because when the transmission power is small, when the transmission power of the BS is small, the increased system energy consumption will improve the energy efficiency. When the transmission power of the BS increases and the system energy consumption is saturated, further increasing the transmission power will lead to a decrease in system energy efficiency.

[0047] Figure 4 In order to compare the simulation results of various schemes, this embodiment considers four different transmission schemes: Scheme 1, the proposed method is used to obtain the optimal BS precoding matrix and STAR-RIS phase design; Scheme 2, the system assumes that the transceiver hardware is an ideal non-robust method; Scheme 3, using traditional RIS for transmission, using a reflection-only RIS and a transmission-only RIS to replace STAR-RIS, the two metasurface devices are deployed in similar positions and the number of elements of both is half of the original STAR-RIS, that is, N / 2; Scheme 4, the phase of the working unit on STAR-RIS is set to a random phase. From the simulation results, in the system considering hardware damage, the performance of the proposed method is better than the non-robust method and the method of the traditional RIS-assisted communication system. This is because the non-robust method does not take into account the hardware damage in the design, resulting in the solution obtained not being the optimal solution in the actual system.

[0048] Figure 5 The simulation results of the relationship between various schemes and distortion scale factors are shown in Figure 2. From the simulation results, as the distortion scale factor gradually increases, the system energy efficiency under all scheme optimizations decreases. This is because when the distortion scale factor increases, the intensity of the noise interference contained in the received signal of each user increases, which ultimately reduces the system energy efficiency. The system energy efficiency performance of the method proposed in the present invention decreases slowly with the increase of the distortion scale factor, reflecting excellent robustness.

[0049] Figure 6The comparison of energy efficiency between the scheme proposed by the present invention and the comparative scheme under different numbers of STAR-RIS elements is shown, and the influence on energy efficiency is studied by gradually increasing the number of STAR-RIS elements. As can be seen from the figure, the system energy efficiency of the four schemes increases with the increase of the number of STAR-RIS elements. This is because the dimension of its transmission and reflection coefficient matrix becomes larger, which means that it has more adjustment methods for the incident signal and can provide more control freedom. The signal processed by STAR-RIS can be better aligned with the user, thereby improving the energy efficiency performance of the system. In addition, it can also be noted that as the number of STAR-RIS elements increases, the improvement of energy efficiency becomes slower. This is because although increasing the number of STAR-RIS elements can provide more control and optimization space, due to the fixed maximum transmission power, the distribution of available energy between channels becomes more limited, and the feasible domain of each channel becomes narrower. In addition, the energy consumption of the additional STAR-RIS elements will also cause the slope of the curve to gradually decrease.

[0050] The energy efficiency optimization method of the STAR-RIS assisted multi-user communication system under hardware damage proposed in the present invention can achieve higher energy efficiency in more practical scenarios where the transceiver hardware is not ideal, and can expand the service range of communication. Compared with the traditional RIS that only reflects signals, STAR-RIS significantly enhances the signal strength and communication reliability in the target area.

[0051] An embodiment of the present invention provides a system for optimizing energy efficiency of STAR-RIS-assisted multi-user communication under hardware damage, including: System model building module, building a STAR-RIS-assisted multi-user communication system model under hardware damage; Energy efficiency problem building module, under the model, constructs the joint optimization problem of BS transmit precoding vector and STAR-RIS reflection and transmission phase shift matrix P 0; The energy efficiency optimization module decomposes the joint optimization problem of BS transmit precoding vector and STAR-RIS reflection and transmission phase shift matrix into two sub-problems: BS transmit precoding vector optimization and STAR-RIS reflection and transmission phase shift matrix optimization; and it iterates through an alternating optimization algorithm to obtain the optimal solution to maximize the system energy efficiency.

[0052] In one embodiment of the present invention, the present invention further provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a terminal device for storing programs and data. It is understandable that the computer-readable storage medium here can include both the built-in storage medium in the terminal device and the extended storage medium supported by the terminal device, and can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it. The computer-readable storage medium provides a storage space, which stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by the processor are also stored in the storage space, and these instructions can be one or more computer programs (including program codes). It should be noted that more specific examples (non-exhaustive list) of the computer-readable storage medium here include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0053] Computer readable storage media also include data signals propagated in baseband or as part of a carrier wave, which carry readable program codes. Such propagated data signals can take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The readable storage medium can also be any readable medium other than a readable storage medium, which can send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, device, or device. The program code contained on the readable storage medium can be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the above.

[0054] Program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., through the Internet using an Internet service provider).

[0055] The processor may load and execute one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of the energy efficiency optimization method for STAR-RIS-assisted multi-user communication under hardware damage in the above embodiment.

[0056] In another embodiment of the present invention, an electronic device is provided, the electronic device comprising a processor and a memory, the memory being used to store a computer program, the computer program comprising program instructions, and the processor being used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or may be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc., which are the computing core and control core of the terminal, which are suitable for implementing one or more instructions, and are specifically suitable for loading and executing one or more instructions to implement the corresponding method flow or corresponding function; the processor described in the embodiment of the present invention can be used for the operation of the energy efficiency optimization method of STAR-RIS-assisted multi-user communication under hardware damage.

[0057] One embodiment of the present invention provides a computer program product, which is intended to achieve energy efficiency optimization of a STAR-RIS (intelligent simultaneous reflecting and transmitting surface) assisted multi-user communication system under hardware damage. The computer program product includes a series of carefully designed computer instructions, which are specially written to guide a computer to execute the above-mentioned energy efficiency optimization method of STAR-RIS assisted multi-user communication under hardware damage.

[0058] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for optimizing energy efficiency of STAR-RIS-assisted multi-user communication under hardware impairment, characterized in that: The following steps are involved: Establish a STAR-RIS-assisted multi-user communication system model under hardware damage; Under the model, the joint optimization problem of BS transmit precoding vector and STAR-RIS reflection and transmission phase shift matrix is ​​constructed. P 0; The joint optimization problem of BS transmit precoding vector and STAR-RIS reflection and transmission phase shift matrix is ​​decomposed into two sub-problems: BS transmit precoding vector optimization and STAR-RIS reflection and transmission phase shift matrix optimization. The optimal solution is iteratively obtained through an alternating optimization algorithm to maximize the system energy efficiency.

2. The method for optimizing energy efficiency of STAR-RIS-assisted multi-user communication under hardware damage according to claim 1, characterized in that: The STAR-RIS assisted multi-user communication system model under hardware damage includes a BS, a STAR-RIS and users; the BS transmits signals to the users through the STAR-RIS; some of the users receive signals reflected by the STAR-RIS, and the other users receive signals transmitted by the STAR-RIS.

3. The method for optimizing energy efficiency of STAR-RIS-assisted multi-user communication under hardware damage according to claim 1, characterized in that: The joint optimization problem of the BS transmit precoding vector and the STAR-RIS reflection and transmission phase shift matrices P 0 is described as: in, is the total maximum transmit power of the BS; For the k The communication rate of each user; Communication rate for user needs; is the phase of the reflection of STAR-RIS; is the transmitted phase of STAR-RIS; C4 and C5 are the amplitude coefficient constraints of STAR-RIS; represents the amplitude of the reflection of STAR-RIS; represents the amplitude of the transmission of STAR-RIS; max() is the maximum value function; is the system energy efficiency; The base station k The beamforming vectors transmitted by each user; for The conjugate transpose of .

4. The method for optimizing energy efficiency of STAR-RIS-assisted multi-user communication under hardware damage according to claim 1, characterized in that: The method of iteratively obtaining the optimal solution through the alternating optimization algorithm to maximize the system energy efficiency is specifically as follows: Fixed the STAR-RIS reflection and transmission phase shift matrix to optimize the BS transmit precoding vector; Based on the optimized BS transmit precoding vector, the STAR-RIS reflection and transmission phase shift matrices are optimized; The above process is iterated until the system energy efficiency is maximized.

5. The method for optimizing energy efficiency of STAR-RIS-assisted multi-user communication under hardware damage according to claim 4, characterized in that: The fixed STAR-RIS reflection and transmission phase shift matrix optimizes the BS transmit precoding vector, specifically: The STAR-RIS reflection and transmission phase shift matrices are fixed, and the Dinkelbach method is used to transform the joint optimization problem into the first optimization problem of the BS transmit precoding vector. ; The variable substitution algorithm, SCA algorithm and Taylor series expansion algorithm are used to solve the first optimization problem of BS transmitting precoding vector Transformed into the second optimization problem ; Based on the second optimization problem , get the optimal BS transmit precoding vector.

6. The method for optimizing energy efficiency of STAR-RIS-assisted multi-user communication under hardware damage according to claim 4, characterized in that: Based on the optimized BS transmit precoding vector, the STAR-RIS reflection and transmission phase shift matrices are optimized as follows: Based on the optimized BS transmit precoding vector, the optimization problem of STAR-RIS reflection and transmission phase shift is transformed into SDP form through SDR algorithm and SCA algorithm to obtain the optimal STAR-RIS reflection and transmission phase shift matrix.

7. An electronic device, characterized in that: The invention comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the energy efficiency optimization method of STAR-RIS-assisted multi-user communication under hardware damage as described in any one of claims 1 to 6 is implemented.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for optimizing energy efficiency of STAR-RIS-assisted multi-user communication under hardware damage according to any one of claims 1 to 6 is implemented.

9. A computer program product, comprising computer instructions, characterized in that: The computer instructions instruct the computer to execute the energy efficiency optimization method of STAR-RIS assisted multi-user communication under hardware damage described in any one of claims 1-6.

10. A system for optimizing energy efficiency of STAR-RIS-assisted multi-user communication under hardware damage, characterized in that: include: System model building module, building a STAR-RIS-assisted multi-user communication system model under hardware damage; Energy efficiency problem building module, under the model, constructs the joint optimization problem of BS transmit precoding vector and STAR-RIS reflection and transmission phase shift matrix P 0; The energy efficiency optimization module decomposes the joint optimization problem of BS transmit precoding vector and STAR-RIS reflection and transmission phase shift matrix into two sub-problems: BS transmit precoding vector optimization and STAR-RIS reflection and transmission phase shift matrix optimization; and it iterates through an alternating optimization algorithm to obtain the optimal solution to maximize the system energy efficiency.

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