Optimization method for STAR-RIS-assisted in-vehicle wireless safety communication beamforming

Abstract

To provide a method for optimizing STAR-RIS assisted in-vehicle wireless secure communication beamforming.SOLUTION: First, constructing a STAR-RIS assisted multi-in-vehicle user MISO downlink communication system model is considered in a scenario where eavesdropping users exist. Next, for an energy splitting mode of the STAR-RIS, an optimization problem for minimizing the power of a multi-antenna base station in the system is established by simultaneously optimizing the base station's transmission beamforming and STAR-RIS's transmission and reflection coefficient matrices. Finally, the original problem is solved by separating it into two sub-problems using an alternating optimization method. The present invention utilizes STAR-RIS to support physical layer security, improves the communication quality of in-vehicle wireless systems, and can achieve spatial coverage of the entire area and at the same time effectively reduce the total transmission power of the base station.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to the technical field of wireless communication, and particularly to an optimization method for STAR-RIS-assisted in-vehicle wireless safety communication beamforming. [Background technology]

[0002] Intelligent Transportation Systems (ITS) are a key component of future smart cities, relying on massive wireless communication connectivity and advanced sensing technologies to bring about profound changes in transportation security and comfort. Vehicle communication is now considered an emerging communication technology that can be used to further improve road safety, traffic efficiency, and driving experience in ITS and future autonomous driving systems. At the same time, rapid information dissemination can be achieved through two communication modes: vehicle-to-infrastructure and vehicle-to-vehicle. However, due to the broadcast and open nature of wireless signals and the strong dynamics of vehicles, the communication coverage, connectivity, and security of the Internet of Vehicles need to be further improved.

[0003] Smart metasurfaces (RIS) have attracted widespread attention in recent years as a key candidate technology for 6G, capable of restructuring the wireless propagation environment, effectively enhancing regional coverage and improving spectrum and energy efficiency. RIS technology utilizes a large number of passive reflective elements integrated on a planar surface. Through software programming, the RIS intelligently configures the reflection phase of wireless signals to increase effective signal amplitude or suppress interference signal amplitude, thereby achieving the goal of improving wireless communication system performance. However, conventional RIS can only reflect wireless signals in the same direction, thereby achieving half-space coverage, significantly limiting the deployment flexibility and coverage of RIS.

[0004] To overcome the shortcomings of conventional RIS, a new architecture called smart metasurface (STAR-RIS) has emerged, which can simultaneously transmit and reflect incident signals based on three different operating protocols: time switching (TS), mode switching (MS), and energy division (ES). This allows simultaneous service delivery to users on both sides of the STAR-RIS, achieving 360° full-area coverage and greater freedom of signal propagation and deployment. Summary of the Invention [Problem to be solved by the invention]

[0005] The present invention provides a method for optimizing STAR-RIS-assisted in-vehicle wireless safety communication beamforming, which aims to minimize the total transmission power of the base station by simultaneously optimizing the base station's transmission beamforming vector and the STAR-RIS transmission and reflection coefficients while ensuring the minimum service quality and safety communication requirements required by authorized in-vehicle users. [Means for solving the problem]

[0006] In order to achieve the above object, the present invention provides: Step 1: setting up a wireless communication scenario including a base station, STAR-RIS, an in-vehicle authorized user, and an eavesdropping user; Step 2: Building a STAR-RIS-assisted multi-vehicle user MISO downlink communication model; Step 3 of establishing a power minimization optimization problem for a multi-antenna base station of the corresponding system; A method for optimizing STAR-RIS-assisted in-vehicle wireless safety communication beamforming is provided, which includes step 4 of simultaneously optimizing the base station's transmission beamforming and the STAR-RIS transmission / reflection coefficient matrix using a method based on semidefinite relaxation and alternating optimization.

[0007] Optionally, the wireless communication scenario in step 1 includes a base station with M antennas, a STAR-RIS with N transmission / reflection elements, and two single-antenna eavesdropping users Eve t / Eve r , and K single-antenna vehicle-mounted regular users are included. STAR-RIS divides the space into a transmission area and a reflection area, and UR and UT represent the set of vehicle-mounted users in the reflection area and the transmission area, respectively. JPEG0007792654000001.jpg19170Eve t is located in the transparent area, and Eve r is located in the reflective area and Eve t , Eve r It is assumed that each of these systems will only intercept information sent by legitimate vehicle users located in the same area.

[0008] Optionally, in the multi-vehicle user MISO downlink communication model in step 2, the equivalent channel gains from the base station to the vehicle regular user k, from the base station to the STAR-RIS, and from the STAR-RIS to the vehicle regular user k are: JPEG0007792654000002.jpg45170

[0009] Optionally, in the above multi-vehicle user MISO downlink communication model, it is assumed that both the base station and STAR-RIS can obtain perfect channel state information. Accordingly, the received signals of the vehicle-mounted regular users and eavesdropping users in the transmission area and reflection area are respectively: JPEG0007792654000003.jpg74170

[0010] JPEG0007792654000004.jpg58170Correspondingly, the signal-to-interference-to-noise ratios (SINRs) of the in-vehicle legitimate user and the eavesdropping user are respectively: JPEG0007792654000005.jpg55170

[0011] Optionally, the power minimization optimization problem of the multi-antenna base station is specifically to find the transmit beamforming vector w of the base station while ensuring the minimum service quality and secure communication requirements required by the authorized vehicle users. k and the STAR-RIS transmission / reflection coefficient matrix φ x The aim is to minimize the total transmit power of the base station by jointly optimizing JPEG0007792654000006.jpg63170

[0012] C1 is the phase constraint of each transmission and reflection element of STAR-RIS, C2 represents the requirement that the sum of the transmission and reflection signal energy of each element must be equal to the incident signal energy under the ES protocol, and C3 is the SINR constraint of the on-board regular user. However, R min is the minimum SINR threshold for in-vehicle regular users, JPEG0007792654000007.jpg12170C4 is the SINR constraint of the eavesdropping user, where R max is the maximum SINR threshold required to ensure that legitimate information is not intercepted.

[0013] Optionally, the process of jointly optimizing the base station's transmit beamforming and the STAR-RIS transmission / reflection coefficient matrix using a method based on semidefinite relaxation and alternating optimization in step 4 includes steps 4.1, 4.2, and 4.3.

[0014] Step 4.1: Rewrite to JPEG0007792654000008.jpg100170,

[0015] Problem P3 is an SDP problem and can be solved directly by a convex optimization solver. Step 4.2: BS transmit beamforming vector w k and set the transmission and reflection coefficient matrix φ of STAR-RIS. x Optimize. Finally, we relax the rank-1 constraint with the SDR method and solve the optimization problem P1 as Convert to JPEG0007792654000010.jpg64170, The optimization of the variable φx in P6 corresponds to finding the optimal solution for the variables Vt and Vr, Step 4.3: Solve problems P3 and P6 by the method of alternating optimization until the optimal value of the convergence of the objective optimization function of problem P1 is reached. [Effects of the Invention]

[0016] This invention provides a beamforming optimization method for STAR-RIS-assisted in-vehicle wireless security communications. First, it considers the construction of a STAR-RIS-assisted multi-user MISO downlink communications system model in the presence of eavesdropping users. Second, it establishes a power minimization optimization problem for the multi-antenna base station of the system by simultaneously optimizing the base station's transmit beamforming and the STAR-RIS transmission / reflection coefficient matrix for the STAR-RIS energy division mode. Finally, it separates the original problem into two subproblems using an alternating optimization method. The invention utilizes STAR-RIS to support physical layer security, improving the communication quality of in-vehicle wireless systems and achieving full spatial coverage while effectively reducing the total transmit power of the base station. [Brief explanation of the drawings]

[0017] In order to more clearly describe the embodiments of the present invention or the technical solutions in the prior art, the following will briefly describe the drawings necessary for the description of the embodiments or the prior art. It is obvious that the drawings in the following description are only some embodiments of the present invention, and those skilled in the art can obtain other drawings based on these drawings without any creative efforts. [Figure 1] 1 is a schematic structural diagram of the STAR-RIS-assisted multi-vehicle user MISO downlink communication model constructed in the present invention; [Figure 2]FIG. 1 is a schematic diagram of the algorithm framework based on SDR and alternating optimization of the present invention. [Figure 3] This is a three-dimensional change relationship diagram between the total transmission power of the BS of the present invention, the number N of STAR-RIS transmitting (reflecting) elements, and the number M of BS antennas. [Figure 4] 1 is a relationship diagram of the change in the total transmission power of the BS according to the location of the eavesdropping user under different solutions of the present invention; [Figure 5] FIG. 10 is a relationship diagram of the change in the total transmission power of the BS with the SINR of an eavesdropper under different solutions of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0018]

[0023] Hereinafter, the embodiments of the present invention will be described in detail, and examples of the embodiments are shown in the drawings, in which the same or similar reference numerals represent the same or similar elements or elements having the same or similar functions. The embodiments described with reference to the following drawings are merely examples for understanding the present invention, and should not be understood as limiting the present invention.

[0019] The following describes the English abbreviations used in the present invention, and the English abbreviations may be used in some places later in this specification.

[0020] BS:Base Station, MISO: Multiple-Input Single-Output, multiple input single output, SINR: Signal to Interference plus Noise Ratio, signal to interference plus noise ratio, SDR: Semidefinite Relaxation, SDP: Semidefinite Programming, QoS: Quality of Service.

[0021] The present invention provides Step 1: constructing a wireless communication scenario including a base station, STAR-RIS, an in-vehicle regular user, and an eavesdropping user; Step 2: Building a STAR-RIS-assisted multi-vehicle user MISO downlink communication model; Step 3 of establishing a power minimization optimization problem for a multi-antenna base station of the corresponding system; A method for optimizing STAR-RIS-assisted in-vehicle wireless safety communication beamforming is provided, which includes step 4 of simultaneously optimizing the base station's transmission beamforming and the STAR-RIS transmission / reflection coefficient matrix using a method based on semidefinite relaxation and alternating optimization.

[0022] The following is a detailed description of the steps: As shown in Figure 1, in step 1, a wireless communication scenario is constructed, including a base station (BS), a STAR-RIS, a regular user on board a vehicle, and an eavesdropping user. The scenario includes a BS with M antennas, a STAR-RIS with N transmission (reflection) elements, and two single-antenna eavesdropping users (Eve t / Eve r ) and K single-antenna vehicle-mounted regular users. STAR-RIS divides the space into two areas: the transmission area (T area) and the reflection area (R area). UR and UT represent the set of vehicle-mounted users in the reflection area and the transmission area, respectively. JPEG0007792654000011.jpg14170

[0023] Also, Eve t is located in the transparent area, and Eve r is located in the reflective area and Eve t , Eve r Assume that each of the STAR-RIS elements only intercepts information transmitted by authorized vehicle users located in the same area. The STAR-RIS of the present invention operates in ES protocol mode, i.e., the signal energy incident on each STAR-RIS element is typically split into transmitted signal energy and reflected signal energy.

[0024] In step 2, the construction of the STAR-RIS-assisted multi-vehicle user MISO downlink communication model is as follows: The equivalent channel gains from the BS to the vehicle regular user k, from the BS to the STAR-RIS, and from the STAR-RIS to the vehicle regular user k are: It can be seen that it is represented by JPEG0007792654000012.jpg106170,

[0025] In formula (1) and formula (2), JPEG0007792654000013.jpg88170

[0026] JPEG0007792654000014.jpg84170

[0027] Furthermore, the optimization problem of minimizing the power of the multi-antenna BS in the system described in step 3 is established as follows: The transmit beamforming vector w of the BS is calculated while ensuring the minimum QoS and secure communication requirements required by the authorized vehicle users. k and the STAR-RIS transmission / reflection coefficient matrix φ x The total transmit power of the BSs is minimized by jointly optimizing JPEG0007792654000015.jpg55170

[0028] In equation (7), C1 is the phase constraint for each transmission and reflection element of STAR-RIS. C2 indicates that under the ES protocol, the sum of the transmission and reflection signal energy of each element must be equal to the incident signal energy. C3 is the SINR constraint for the in-vehicle regular user, where R min is the minimum SINR threshold for in-vehicle regular users, JPEG0007792654000016.jpg15170C4 is the SINR constraint of the eavesdropping user, and R max is the maximum SINR threshold required to ensure that legitimate information is not intercepted.

[0029] Non-convexity of constraints and variable w in optimization problem P1k and φ x Considering the highly associative nature of the optimization, it is difficult to solve the original optimization problem directly. Therefore, we use an algorithm based on SDR and alternating optimization to solve the proposed problem. Specifically, (1) STAR-RIS transmission / reflection coefficient matrix φ x and the beamforming vector w k Optimize The original optimization problem P1 is Rewrite to JPEG0007792654000017.jpg39170, In this case, Equation (8) is a non-convex problem that is very difficult to solve directly, so we consider converting it to an SDP problem. First, we define the following matrices: JPEG0007792654000018.jpg31170

[0030] JPEG0007792654000019.jpg88170

[0031] JPEG0007792654000020.jpg80170

[0032] JPEG0007792654000021.jpg78170

[0033] JPEG0007792654000022.jpg44170

[0034] (2) BS transmit beamforming vector w k and set the transmission and reflection coefficient matrix φ of STAR-RIS. x Optimize

[0035] The original optimization problem P1 is JPEG0007792654000023.jpg64170

[0036] In order to convert the quadratic terms of the SINR of the in-vehicle regular users in the T and R areas in equation (14) into a linear form, the following auxiliary matrix is ​​defined: JPEG0007792654000024.jpg45170

[0037] Similarly, to convert the quadratic terms of the SINRs of eavesdropping users in T and R areas in equation (14) into a linear form, we define the following auxiliary matrix: JPEG0007792654000025.jpg45170

[0038] Next, let the reflection and transmission coefficient vectors of STAR-RIS be v t and v r Defined as JPEG0007792654000026.jpg118170

[0039] In equations (19) and (20), JPEG0007792654000027.jpg92170

[0040] Since there is a rank-1 constraint in (21) and the above problem is still non-convex, we use the SDR method to relax the rank-1 constraint.

[0041] Therefore, the optimization problem P5 is JPEG0007792654000028.jpg66170

[0042] Variable φ in P6 x The optimization of variable V t and V r This corresponds to finding the optimal solution of problem P6, and the present invention solves problem P6 in a similar manner to the method for solving problem P3. As described above, problems P3 and P6 are solved using the SDR method, and P3 and P6 are alternately optimized until the optimal value of the convergence of the objective optimization function of problem P1 is reached. The algorithm framework based on SDR and alternating optimization is shown in Figure 2.

[0043] Furthermore, in order to verify the advantages of the STAR-RIS-assisted in-vehicle wireless safety communication beamforming optimization method of the present invention, the present invention proposes a specific example to compare the performance with the proposed STAR-RIS strategy using the following three strategies. Specifically, the present invention is verified in the Matlab R2021a environment, and the strategy of the present invention is compared with the STAR-RIS strategy without RIS, the conventional RIS, and the equal amplitude and phase STAR-RIS strategy:

[0044] (1) Without RIS: In-vehicle wireless safety communication without smart metasurface support. (2) Conventional RIS: In-vehicle wireless safety communication supported by two conventional RISs with N / 2 elements, which respectively serve users in the reflective area and users in the transparent area; (3) STAR-RIS with equal amplitude and phase: STAR-RIS-assisted in-vehicle wireless safety communication with the same amplitude and phase.

[0045] According to the actual design needs, we set the parameters of the algorithm, the number of initial users is 4, the number of BS antennas is 4, and the eavesdropper's SINR threshold is 0.8.

[0046] Figure 3 shows the three-dimensional relationship between the total BS transmit power, the number of STAR-RIS transmitting (reflecting) elements N, and the number of BS antennas M. As can be seen from Figure 3, when N is constant, the total BS transmit power continues to decrease as M increases. This is because the BS uses multi-antenna technology to focus signals toward specific users, which reduces the total BS transmit power. Similarly, when M is constant, the total BS transmit power is inversely proportional to N. This is because an increase in the number of elements N allows STAR-RIS to better transmit and reflect the BS's beamforming signal, providing more spatial degrees of freedom and thereby reducing the transmit power required for the BS.

[0047] Figure 4 shows the effect of the eavesdropper's location on the total BS transmit power under different solutions. The larger the Y-axis coordinate of the eavesdropper, the farther the eavesdropper is from the BS. As can be seen from Figure 4, the total BS transmit power is inversely proportional to the eavesdropper's location distance. This is because when the eavesdropper is located between the BS and STAR-RIS, and when the eavesdropper is farther from the BS and closer to STAR-RIS, the transmitted and reflected signals from STAR-RIS gradually dominate the eavesdropper's position, gradually reducing the total BS transmit power required. Furthermore, the total transmit power required by the proposed BS is lower than that of the other three solutions, further reflecting the effectiveness of the proposed solution. However, as the eavesdropper approaches STAR-RIS, the performance gap between the proposed solution and the equal-amplitude-phase STAR-RIS solution gradually widens. For example, when the Y-axis coordinate of the eavesdropper changes from 13 to 15 and 17, the power difference between the two increases from 0.2722 to 0.3804, and then to 0.4631.

[0048] Figure 5 shows the impact of the system safety threshold on the total BS transmit power under different solutions. As can be seen from Figure 5, as the safety threshold increases, the total BS transmit power tends to gradually decrease. This is because the lower the eavesdropper's SINR, the higher the system security performance. Therefore, the BS needs to increase its transmit power to meet the quality of service requirements of legitimate users. By rationally designing the beamforming at the BS and the transmission and reflection coefficients of STAR-RIS, the transmit power required by the BS can be appropriately reduced.

[0049] The above disclosure is merely a preferred embodiment of the present invention, and it is to be understood that this does not limit the scope of the claims of the present invention. Those skilled in the art can understand that the whole or part of the process for realizing the above embodiment and the equivalent modifications made in accordance with the claims of the present invention still fall within the scope of the present invention.

Claims

[Claim 1] A method for optimizing STAR-RIS-assisted in-vehicle wireless safety communication beamforming, comprising: Step 1: constructing a wireless communication scenario including a base station, a STAR-RIS, an in-vehicle regular user, and an eavesdropping user; Step 2: constructing a STAR-RIS-assisted multi-vehicle user MISO downlink communication model; Step 3 of establishing an optimization problem of power minimization for a multi-antenna base station of the corresponding system; Step 4 includes using a method based on semidefinite relaxation and alternating optimization to jointly optimize the transmit beamforming vector of the base station and the transmission / reflection coefficient matrix of the STAR-RIS; Step 1 includes a base station with M antennas, a STAR-RIS with N transmission / reflection elements, two single-antenna eavesdropping users Evet / Ever, and K single-antenna vehicle-mounted regular users. The STAR-RIS divides the space into a transmission area and a reflection area, and UR and UT represent the sets of vehicle-mounted users in the reflection area and the transmission area, respectively. It is assumed that Eve t is located in a transmission area, Eve r is located in a reflection area, and Eve t and Eve r only intercept information transmitted by authorized vehicle users located in the same area. In the multi-vehicle user MISO downlink communication model in step 2, the equivalent channel gains from the base station to the vehicle regular user k, from the base station to the STAR-RIS, and from the STAR-RIS to the vehicle regular user k are: The equivalent channel gain from the base station and STAR-RIS to the eavesdropping user is In the above multi-vehicle user MISO downlink communication model, it is assumed that both the base station and the STAR-RIS can obtain perfect channel state information. The received signals of the regular vehicle users and the eavesdropping users in the transmission area and reflection area are respectively The signal-to-interference-to-noise ratios (SINRs) of the in-vehicle legitimate user and the eavesdropping user are respectively The optimization problem of minimizing the power of the multi-antenna base station is specifically to find the optimum transmit beamforming vector w of the base station while ensuring the minimum service quality and secure communication requirements required by authorized vehicle users. ｋ and the STAR-RIS transmission / reflection coefficient matrix Φ ｘ The aim is to minimize the total transmit power of the base station by jointly optimizing and C1 is the phase constraint of each transmission and reflection element of STAR-RIS, C2 represents that under the ES protocol, the sum of the energy of the transmission and reflection signals of each element must be equal to the energy of the incident signal, and C3 is the SINR constraint of the in-vehicle regular user, where R ｍｉｎ is the minimum SINR threshold for in-vehicle regular users, C4 is the SINR constraint of the eavesdropping user, and R ｍａｘ is the maximum SINR threshold required to ensure that legitimate information is not intercepted, In step 4, the base station transmit beamforming vector w is calculated using a method based on semidefinite relaxation and alternating optimization. ｋ and the STAR-RIS transmission / reflection coefficient matrix Φ ｘ The process of jointly optimizing includes steps 4.1, 4.2, and 4.3, Step 4.1: Finally, we solve the original optimization problem P1 using the SDR method as follows: Rewrite it to Problem P3 is an SDP problem, which can be solved directly by a convex optimization solver to find the optimal F ｋ By calculating the optimal transmit beamforming vector w ｋ Seeking As a result, the optimization problem P1 can be solved as follows: Convert to Positive semidefinite matrix V in problem P6 ｔ and V ｒ By finding the optimal solution of ｘ Seeking Step 4.3: By using the method of alternating optimization, the problem P3 and the problem P6 are alternately and repeatedly optimized to obtain the transmit beamforming vector w that reaches the optimal value of the convergence of the objective optimization function of the optimization problem P1. ｋ and the transmission / reflection coefficient matrix Φ ｘ and seek, A method for optimizing STAR-RIS-assisted in-vehicle wireless safety communication beamforming, characterized by:

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