STAR-RIS position optimization and beam forming design method based on coal mine wireless communication

Abstract

The invention provides a STAR-RIS position optimization and beam forming design method based on coal mine wireless communication, and relates to the technical field of wireless communication. The method comprises the following steps: constructing a communication model in a coal mine environment; according to the communication model, constructing an optimization problem of position and beam forming based on STAR-RIS; a position and beam forming design algorithm based on the STAR-RIS is adopted to optimize the optimization problem of the position and the beam forming based on the STAR-RIS, and an optimal solution of the optimization problem of the position and the beam forming based on the STAR-RIS is output; the sum rate through the STAR-RIS based channel is maximized according to the optimal solution. According to the invention, the communication rate of the wireless communication system can be improved, and the efficiency and accuracy of monitoring and remote control of mining equipment can be improved.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technologies, and particularly to a STAR-RIS position optimization and beamforming design method and device in coal mine wireless communication. Background Art

[0002] Beamforming technology is an advanced signal processing technology that combines antenna arrays and digital signal processing technologies for achieving directional transmission and reception of signals. This technology can form a beam with specific directivity in the spatial domain by adjusting the feeding amplitude and phase of each element in the antenna array. During beamforming, signals are transmitted or received simultaneously through multiple antenna elements, and the signals of each element are subject to specific weighting processes to adjust their amplitudes and phases. These weighted signals are superimposed on each other in space, thereby forming an enhanced signal beam in the target direction and signal suppression in other directions. This enhancement of directivity enables beamforming technology to significantly improve signal transmission efficiency and anti-interference ability. STAR-RIS technology is an innovative intelligent metasurface technology that can achieve simultaneous reflection and transmission of signals, overcoming the limitation of traditional intelligent metasurfaces that can only provide unilateral reflection functions. By splitting the input signal into two parts, reflection and transmission, it achieves 360-degree signal coverage. STAR-RIS technology not only enhances the flexibility of signal propagation but also significantly increases the design freedom to meet strict communication requirements, bringing revolutionary improvements to wireless communication systems. It shows great potential in aspects such as improving spectral efficiency, expanding coverage, and reducing energy consumption, and is one of the important directions for the development of 6G and future communication technologies.

[0003] Wireless communication in the limited environment of the underground mine channel model has been widely studied. However, none of the current studies provide a comprehensive channel model to characterize the characteristics of the wireless channel in the underground mine without considering the mine layout.

[0004] Evolution of coal mine communication technology to address the non-line-of-sight problem: In coal mine communication, an important issue is that signal propagation is blocked by non-line-of-sight paths, resulting in a significant reduction in the intensity of communication signals. Due to the availability of infrastructure, coal mines initially deployed wired communication systems to establish communication links. However, their limited scalability greatly reduces their effectiveness, especially in emergency situations where the mine structure changes. In contrast, wireless communication has proven to be more adaptable and reliable in such scenarios, capable of providing better response and coordination during rescue operations. Therefore, many coal mine wireless communication technologies based on wireless sensor networks have been proposed. However, the deployment and maintenance costs of wireless sensor networks are high, and they cannot provide communication services for underground equipment and workers, and cannot effectively solve the problem of non-line-of-sight paths in the coal mine environment.

[0005] To solve the above problems, reconfigurable intelligent surface (RIS) has been applied to coal mines. By studying the resource allocation problem of RIS-assisted joint communication and sensing systems in coal mine environments. Integrating RIS in coal mines improves wireless communication efficiency, but does not solve the complexity of intersections in multi-tunnel scenarios. By adopting multi-hop RIS, multiple communication links are established between surface devices and underground machinery, enabling signals to be transmitted through the optimal path. In the event of a link interruption, the system can immediately detect the location of the interruption, facilitating rapid response and ensuring mining safety, but using multi-hop RIS increases operating costs. Summary of the Invention

[0006] To solve the technical problems of poor communication performance in coal mine communication in the prior art, high deployment and maintenance costs based on wireless sensor networks, inability to provide communication services for underground equipment and workers, and inability to effectively solve non-line-of-sight paths in coal mine environments, embodiments of the present invention provide a method and device for STAR-RIS position optimization and beamforming design in coal mine wireless communication. The technical solutions are as follows:

[0007] On the one hand, a method for STAR-RIS position optimization and beamforming design in coal mine wireless communication is provided. This method is implemented by a device for STAR-RIS position optimization and beamforming design in coal mine wireless communication. The method includes:

[0008] S1. Construct a communication model in the coal mine environment;

[0009] S2. According to the communication model, construct an optimization problem for the position and beamforming based on STAR-RIS;

[0010] S3. Adopt an algorithm for STAR-RIS position and beamforming design to optimize the optimization problem for the position and beamforming based on STAR-RIS, and output the optimal solution of the optimization problem for the position and beamforming based on STAR-RIS; according to the optimal solution, maximize the sum rate of the channel based on STAR-RIS.

[0011] On the other hand, a device for STAR-RIS position optimization and beamforming design in coal mine wireless communication is provided. This device is applied to the method for STAR-RIS position optimization and beamforming design in coal mine wireless communication. The device includes:

[0012] A first construction unit for constructing a communication model in the coal mine environment;

[0013] A second construction unit for constructing an optimization problem for the position and beamforming based on STAR-RIS according to the communication model;

[0014] An optimization and output unit is configured to optimize the optimization problem of the STAR-RIS based position and beamforming by using a STAR-RIS based position and beamforming design algorithm, and output an optimal solution to the optimization problem of the STAR-RIS based position and beamforming; according to the optimal solution, maximize the sum rate of the channel based on STAR-RIS.

[0015] On the other hand, a STAR-RIS position optimization and beamforming design device in coal mine wireless communication is provided. The STAR-RIS position optimization and beamforming design device in coal mine wireless communication includes: a processor; a memory, on which computer-readable instructions are stored, and when the computer-readable instructions are executed by the processor, any one of the methods in the above-mentioned STAR-RIS position optimization and beamforming design method in coal mine wireless communication is implemented.

[0016] On the other hand, a computer-readable storage medium is provided, in which at least one instruction is stored, and the at least one instruction is loaded and executed by a processor to implement any one of the methods in the above-mentioned STAR-RIS position optimization and beamforming design method in coal mine wireless communication.

[0017] The beneficial effects brought by the technical solutions provided in the embodiments of the present invention at least include:

[0018] In the embodiments of the present invention, a communication model in a coal mine environment is first constructed; secondly, according to the communication model, an optimization problem of STAR-RIS based position and beamforming is constructed; finally, a STAR-RIS based position and beamforming design algorithm is used to optimize the optimization problem of STAR-RIS based position and beamforming, and an optimal solution to the optimization problem of STAR-RIS based position and beamforming is output; according to the optimal solution, the sum rate of the channel based on STAR-RIS is maximized. By using the present invention, the communication rate of the wireless communication system can be improved, the efficiency and accuracy of the monitoring and remote control of mine equipment can be improved, the real-time data transmission and response capabilities can be improved, so that equipment failures can be detected and processed in time, the downtime can be reduced, the production continuity can be improved, and the production efficiency of coal mines can be greatly improved; by using the present invention, energy conservation and emission reduction in mines can be promoted, the production process can be optimized and resource waste can be reduced, and the sustainable development of the coal mining industry can be promoted. Description of the Drawings

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the accompanying drawings required for the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0020] Figure 1 It is a flowchart of a STAR-RIS position optimization and beamforming design method in coal mine wireless communication provided by an embodiment of the present invention;

[0021] Figure 2 It is a schematic structural diagram of a STAR-RIS assisted coal mine wireless communication system provided by an embodiment of the present invention;

[0022] Figure 3 It is a result graph of the comparison of the algorithm convergence provided by an embodiment of the present invention;

[0023] Figure 4 It is a result graph of the comparison between the STAR-RIS scheme and the traditional RIS scheme provided by an embodiment of the present invention;

[0024] Figure 5 It is a block diagram of a STAR-RIS position optimization and beamforming design device in coal mine wireless communication provided by an embodiment of the present invention;

[0025] Figure 6 It is a schematic structural diagram of a STAR-RIS position optimization and beamforming design device in coal mine wireless communication provided by an embodiment of the present invention. Specific implementation manners

[0026] The following will describe the technical solutions in the present invention with reference to the accompanying drawings.

[0027] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to represent examples, illustrations or explanations. Any embodiment or design solution described as "example" in the present invention should not be construed as more preferred or more advantageous than other embodiments or design solutions. Exactly speaking, the use of the word "example" aims to present concepts in a specific way. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one of the two can be selected.

[0028] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when the difference is not emphasized, their intended meanings are the same. "Of", "corresponding", and "corresponding" can sometimes be used interchangeably. It should be noted that when the difference is not emphasized, their intended meanings are the same.

[0029] In the embodiments of the present invention, sometimes subscripts such as W 1 may be written in a non-subscript form such as W1. When the difference is not emphasized, their intended meanings are the same.

[0030] To make the technical problems to be solved, technical solutions, and advantages of the present invention clearer, the following will be described in detail with reference to the accompanying drawings and specific embodiments.

[0031] The embodiments of the present invention provide a method for STAR-RIS position optimization and beamforming design in coal mine wireless communication. This method can be implemented by a device for STAR-RIS position optimization and beamforming design in coal mine wireless communication, and this device for STAR-RIS position optimization and beamforming design in coal mine wireless communication can be a terminal or a server. As Figure 1 shown in the flowchart of the method for STAR-RIS position optimization and beamforming design in coal mine wireless communication, the processing flow of this method can include the following steps:

[0032] S1. Construct a communication model in the coal mine environment.

[0033] In a feasible implementation, as Figure 2 shown in the schematic diagram of the structure of the wireless communication system, the system model consists of a base station equipped with M antennas, a movable STAR-RIS located at the corner of the underground roadway, and K single-antenna coal mine underground Internet of Things devices.

[0034] Among them, the signal path between the base station and the Internet of Things device is divided into a direct path and a reflection path. The direct path is from the base station to the Internet of Things device, and this path is a non-line-of-sight path; the reflection path is base station - STAR-RIS - Internet of Things device, and this path is a line-of-sight path; the STAR-RIS operates in the energy splitting mode to create LoS transmission and reflection links for the blocked underground Internet of Things devices.

[0035] Among them, it is assumed that the uniform planar array type STAR-RIS and the base station each contain multiple units. Define as the transmission / reflection coefficient, where represents the transmission coefficient; represents the reflection coefficient; is the amplitude coefficient of STAR-RIS transmission and reflection, indicating the corresponding phase shift introduced by the nth element.

[0036] Among them, for STAR-RIS, it is deployed at the intersection of two roadways. Without interrupting the LoS transmission and reflection links of underground IoT devices, it can move in a local area and establish a two-dimensional local coordinate system to describe the position of STAR-RIS, denoted as

[0037] In a feasible implementation, the channel between the base station and STAR-RIS is expressed as G ∈ C N×M , where N = N 1 ×N 2 represents the number of elements of STAR-RIS; M = M 1 ×M 2 represents the number of elements of the base station; among them, the channel between the base station and the kth underground IoT device is expressed as g k ∈C M ; the channel between STAR-RIS and the kth underground IoT device is expressed as h k ∈C N .

[0038] Among them, the communication link from the base station to STAR-RIS, that is, the complex channel gain of the link from the UPA array to the UPA array, can be expressed by the following formula (1):

[0039] G = γ B-S Q B-S μ n (1)

[0040] Among them, G represents the complex channel gain of the link from the UPA array to the UPA array; μ n represents the spatial correlation between the first port (as a reference point) and the nth port on STAR-RIS;

[0041] Among them, Q B-S represents the small-scale fading caused by multipath transmission. It is a geometric channel model with L scatterers and can be expressed by the following formula (2):

[0042]

[0043] Among them, represents the response of the STAR-RIS array in a specific direction and respectively represent the responses of the base station antenna array in specific directions; α lDenote the fading coefficient of the channel. For the line-of-sight (LoS) path, the fading coefficient is usually set to 1; for the non-line-of-sight (NLoS) path, the fading coefficient is regarded as a Gaussian variable.

[0044] Where L is the number of dominant paths; Denote for The response in the direction of, is the horizontal angle, and φ is the elevation angle; where, Can be expressed by the following formulas (3)-(5):

[0045]

[0046] Where, Denote the antenna response vector in the horizontal direction; a z (φ 1 ) denotes the antenna response vector in the vertical direction. P and Q represent the UPA antenna array of P×Q, that is, there are P rows and Q columns of antennas; Denote the azimuth angle of arrival related to the base station; φ 1 Denote the azimuth elevation angle related to the base station, Denote the azimuth angle of arrival related to the STAR-RIS; φ 2 The azimuth elevation angle related to the STAR-RIS, α l Denote the fading coefficient of the channel; to distinguish the LoS path and the NLoS path, it is defaulted that the first path is the LoS path, and the normalized energy is set to 1; while the energy of the NLoS path is a Gaussian variable. To reflect the energy difference from the LoS path, a decay coefficient is set;

[0047] Where γ B-S Denote the channel attenuation caused by the large-scale path loss of this section of the link; in the coal mine environment, γ B-S Can be expressed by the following formula (6):

[0048]

[0049] Where L roughness Denote the roughness of the tunnel wall; L tilt Denote the loss caused by the inclination of the tunnel wall; L refraction Denote the refraction loss; d represents the distance from the base station to the STAR-RIS; D 0 Denote a reference distance.

[0050] Where L refraction The specific expression can be expressed by the following formula (7):

[0051]

[0052] Where L roughnessThe specific expression can be represented by the following formula (8):

[0053]

[0054] Wherein, L tilt The specific expression can be represented by the following formula (9):

[0055]

[0056] Wherein, K 1 is the dielectric constant of the side wall, and K 2 is the dielectric constant of the top and bottom of the tunnel; d 1 and d 2 are the tunnel dimensions, h is the root mean square of the tunnel wall roughness, θ is the root mean square of the inclination; λ is the wavelength; z represents the direction along the tunnel

[0057] Wherein, in formula (1), due to the movement of the STAR-RIS, the spatial correlation at the STAR-RIS needs to be considered. A simplified channel model is adopted, and it is considered that the nth port is only coupled to the reference port. Therefore, taking the first port as the reference point, the correlation between the first port and the nth port is represented by the following formula (10):

[0058]

[0059] Wherein, J 0 (·) is the zero-order Bessel function of the first kind; n 1 represents the nth port along the x-axis direction; n 2 represents the nth port along the y-axis direction; N 1 represents that there are N uniformly distributed positions along the x-axis; N 2 represents that there are N uniformly distributed positions along the y-axis; W 1 represents a linear space with a length of Wλ in the x-axis direction; wherein, λ represents the wavelength; W 2 represents a linear space with a length of Wλ in the y-axis direction.

[0060] Wherein, this application considers the communication link from the STAR-RIS and the base station to the underground Internet of Things device, that is, from the UPA array to the single-antenna target position. The complex channel gain of this section of the link can be represented by the following formulas (11)-(12):

[0061] h k =γ S-E Q S-E μ n (11)

[0062] g k =γ B-E QB-E (12)

[0063] Among them, γ S-E represents the channel attenuation caused by the large-scale path loss from the STAR-RIS to the Internet of Things device; γ B-E represents the channel attenuation caused by the large-scale path loss from the base station to the Internet of Things device; Q S-E represents the small-scale fading caused by the multipath transmission from the STAR-RIS to the Internet of Things device; Q B-E represents the small-scale fading caused by the multipath transmission from the base station to the Internet of Things device.

[0064] Among them, the signal sent by the base station can be expressed by the following formula (13):

[0065]

[0066] Among them, s k is the unit power information symbol, w k ∈C M is the beamforming vector of the k-th device where k ∈ K; s represents the signal sent by the base station.

[0067] In a feasible implementation, by using the binary indicators α k and β k , and k ∈ K to indicate whether the k-th underground Internet of Things device can receive the transmitted or reflected signal from the STAR-RIS, the received signal at the underground Internet of Things device k can be expressed by the following formula (14):

[0068]

[0069] Among them, is the conjugate transpose of the channel vector from the base station to the n-th IoT device; is the conjugate transpose of the channel vector from the STAR-RIS to the n-th IoT device; Θ t represents the transmission matrix of the STAR-RIS; Θ T represents the reflection coefficient matrix of the STAR-RIS; G is the channel matrix from the base station to the STAR-RIS; s is the total signal transmitted by the base station

[0070] Among them, y k represents the received signal at the underground Internet of Things device k; is the additive white Gaussian noise, α k and β k are used to indicate whether the underground Internet of Things device is located in the transmission area or the reflection area at this time. When α k and β k change, its received signal form can be expressed by the following formula (15):

[0071]

[0072] where, Θ m = diag(z m ) represents a diagonal matrix, and the elements on the diagonal are given by the vector Z m ; represents the transmission / reflection coefficient; where, φ n represents that the nth reflection unit can be expressed by the following formula (16):

[0073]

[0074] where,

[0075] In a feasible implementation manner, according to formula (13) and formula (14), the received signal-to-noise ratio at the kth coal mine underground Internet of Things device can be expressed by the following formula (17):

[0076]

[0077] where, γ k represents the received signal-to-noise ratio at the kth coal mine underground Internet of Things device; σ 2 represents the noise power.

[0078] In a feasible implementation manner, calculate the sum rate of the kth coal mine underground Internet of Things device according to the received signal-to-noise ratio at the kth coal mine underground Internet of Things device, which is expressed by the following formula (18):

[0079] R k = Blog 2 (1 + γ k )(18)

[0080] where, B is the bandwidth of the channel; R k represents the sum rate of the kth coal mine underground Internet of Things device.

[0081] S2. According to the communication model, construct an optimization problem for location and beamforming based on STAR-RIS.

[0082] In a feasible implementation manner, given the considered system model, the objective problem of this application is to jointly optimize the passive beamforming of STAR-RIS, the transmit beamforming of the base station, and the STAR-RIS location to maximize the sum rate under the minimum rate requirement and total power constraint. Among them, the optimization problem for location and beamforming based on STAR-RIS can be expressed by the following formulas (19a)-(19g):

[0083]

[0084] s.t. R k ≥R min (19b)

[0085]

[0086] where R min is the minimum data rate requirement of the coal mine underground Internet of Things device, and P max is the maximum transmit power of the base station; is the amplitude coefficient of STAR-RIS transmission and reflection, represents the corresponding phase shift introduced by the nth element. When m is t, it represents transmission, and when m is r, it represents reflection.

[0087] Optionally, the constraint conditions of the optimization problem based on the position and beamforming of STAR-RIS include: the minimum rate constraint of each coal mine underground Internet of Things device, the total transmit power constraint of the base station, the amplitude and phase shift coefficient constraints of STAR-RIS, the constraint of the STAR-RIS energy conservation law, and the position constraint of STAR-RIS.

[0088] Among them, STAR-RIS is a new type of intelligent metasurface technology that can simultaneously transmit and reflect wireless signals, which is a technical means mastered by those skilled in the art and will not be further elaborated in this application.

[0089] Optionally, the optimization problems based on the position and beamforming of STAR-RIS include: the beamforming optimization problem with fixed phase shift, the optimization problem of the transmission and reflection phase shift matrix, and the position optimization problem based on STAR-RIS.

[0090] S3. Use the position and beamforming design algorithm based on STAR-RIS to optimize the optimization problem based on the position and beamforming of STAR-RIS, and output the optimal solution of the optimization problem based on the position and beamforming of STAR-RIS; according to the optimal solution, maximize the sum rate of the channel based on STAR-RIS.

[0091] Optionally, the position and beamforming design algorithm based on STAR-RIS includes two layers; among them, the outer layer is used to update the position of STAR-RIS; the inner layer is used to optimize the active beamforming of the base station and the passive beamforming of STAR-RIS.

[0092] Optionally, the position and beamforming design algorithm based on STAR-RIS includes: the SCA-based base station beamforming vector iterative algorithm, the SCA-based STAR-RIS phase shift matrix iterative algorithm, and the STAR-RIS position update algorithm based on the enumeration method.

[0093] Optionally, an SCA-based base station beamforming vector iterative algorithm is used to optimize the beamforming optimization problem with fixed phase shifts. By adopting the semidefinite relaxation method, relaxation variables are set for iterative calculation, and the optimal base station beamforming vector is output;

[0094] Among them, for fixed integer variable u and the amplitude and phase shift coefficient Θ of the STAR-RIS, formula (19) is rewritten as formula (20):

[0095]

[0096] s.t.R k ≥R min (20b)

[0097]

[0098] Among them, the quadratic norm in formula (20) is a non-convex norm, and it is more convenient to convert it into a matrix trace for solution. To optimize this sub-problem, the semidefinite relaxation method is adopted to optimize the base station beamforming vector. The specific implementation steps include:

[0099] In a feasible implementation manner, given the reflection and transmission matrix Θ of the STAR-RIS, let Define Among them, matrix W k is semidefinite and satisfies rank(W k ) = 1. Through the SDR technology, formula (20) can be rewritten as formula (21):

[0100]

[0101] Among them, to solve the non-convexity of formula (21), relaxation variable vectors are introduced, including the first vector ξ = [R 1 , …, R K T , the second vector η = [η 1 , …, η K T and the third vector γ = [γ 1 , …, γ K T , and formula (21) is rewritten as formula (22):

[0102]

[0103] Among them, to solve the non-convexity problem of formula (22b), formula (22b) is processed by adopting the first-order Taylor expansion, and the constraint condition of formula (22b) can be rewritten as formula (23):

[0104] ​​​

[0105] Among them, by using the above approximate method, the non-convex problem in formula (22) is rewritten as formula (24):

[0106]

[0107] s.t. (20c) to (20h), (21) (24b)

[0108] Among them, due to the rank-1 constraint (22h), formula (24) is non-convex. The optimal beamforming matrix W obtained by ignoring the rank-1 constraint (22h) in formula (24) k , still satisfies rank(W k ) = 1. Therefore, the rank-1 constraint (22h) can be ignored, and formula (24) is a standard convex SDP, which can be solved by the CVX Tool, and the optimal solution can be obtained by obtained, where is the largest eigenvalue of and

[0109]

[0110] Table 1

[0111]

[0112] Among them, the SCA-based STAR-RIS phase shift matrix iterative algorithm is used to optimize the optimization problem of the transmission and reflection phase shift matrix. By using the semi-definite relaxation method and the penalty-based norm approximation method, the slack variables and penalty factors are set for iterative calculation, and the optimal transmission coefficient and reflection coefficient of the STAR-RIS are output;

[0113] Among them, the specific implementation steps of the SCA-based STAR-RIS phase shift matrix iterative algorithm include:

[0114] In a feasible implementation manner, given the beamforming vector W, the phase shift matrix optimization problem can be expressed by the following formulas (25a)-(25e):

[0115]

[0116] s.t. R k ≥R min (25b)

[0117]

[0118] ​where, φ n indicates that the nth reflection unit can be represented by the following formula (26):

[0119]

[0120] where Therefore is equivalent to

[0121] where can be written as Let v m = [z m , 1] H , m ∈ {t, r} represents the first intermediate variable defined for computational convenience represents the second intermediate variable defined for computational convenience, and the objective function can be transformed into the following formula (27):

[0122]

[0123] where, the semi-definite relaxation method is used to optimize the phase shift matrix of STAR-RIS, and V m = v m v mH represents the first computational variable defined for computational convenience represents the second computational variable defined for computational convenience, where the matrix V is semi-definite and satisfies rank(V m ) = 1. Formula (25) can be rewritten as formula (28):

[0124]

[0125]

[0126] diag(V t ) + diag(V r ) = [1 N ; 2](28e)

[0127]

[0128] rank(V r ) = 1(28i)

[0129] rank(V t ) = 1(28j)

[0130] where, the symbol [1 N ; 2] represents a vector, where the first N elements are 1 and the last element is 2

[0131] In a feasible implementation, formula (29) can be deduced from formula (22):

[0132]

[0133] (24c)~(24j)(29f)

[0134] In a feasible implementation, according to formula (29), a penalty-based norm approximation method is used to solve it. The specific implementation process includes:

[0135] Among them, the following formulas (30) and (31) are used to replace the constraints (28i) and (28j):

[0136] Tr(V t ) - ||V t || 2 =0(30)

[0137] Tr(V r ) - ||V r || 2 =0(31)

[0138] Among them, for any Hermitian matrix, the inequality Tr(V m ) - ||V m || 2 ≥0 always holds. When and only when rank(V m ) = 1, the equation is satisfied. Due to the difference in convex functions, the norm equations formulas (30) and (31) are still non-convex constraints; the norms ||V t || 2 and ||V r || 2 are approximated by the lower bounds of the first-order Taylor expansion and can be expressed by the following formulas (32) and (33):

[0139]

[0140] Among them, V t(n-1) and V r(n-1) represent the given points in the nth iteration, represents the eigenvector of Vt associated with the largest eigenvalue; represents the eigenvector of Vr associated with the largest eigenvalue. Among them, V t(n-1) and V r(n-1) satisfy the following formulas (34) and (35):

[0141]

[0142] In a feasible implementation, the constraint formula (32) and the constraint formula (33) are used as penalty terms and added to the objective function. Formula (27) can be rewritten as formula (36):

[0143]

[0144] s.t.(27b)~(27e),(26c)~(26h)(36b)

[0145] where c 1 , c 2 >0, c 1 is the first penalty factor; c 2 is the second penalty factor; when c 1 , c 2 is large enough, the solution V will satisfy the rank-one constraint. Therefore, based on the penalty function approximation method, a good initial point can be obtained from a relatively low c 1 , c 2 . By gradually increasing c 1 , c 2 to find a feasible solution of V that satisfies the rank-one constraint, it can be obtained that formula (36) is convex and can be solved by CVX; the iteration termination condition is or n>n max where δ is a predefined precision and n max is the maximum number of iterations, and v t =V t (:,N + 1), v r =V r (:,N + 1), where V m (:,N + 1), m∈{t,r} is the last column of V m . Among them, the transmission coefficient of the STAR-RIS is v r =v r (1:N) , and the reflection coefficient of the STAR-RIS is v t =v t (1:N) . Among them, v m (1:N) , m∈{t,r} represents the elements from the 1st to the Nth element extracted from v m .

[0146] In a feasible implementation, as shown in Table 2, the calculation process of the STAR-RIS phase shift matrix iteration algorithm based on SCA is presented.

[0147] Table 2

[0148]

[0149] Among them, the location update algorithm of STAR-RIS based on the enumeration method is used to optimize the location optimization problem of STAR-RIS; by adopting the base station beamforming vector iterative algorithm based on SCA and the STAR-RIS phase shift matrix iterative algorithm based on SCA to calculate the sum rate, the maximum sum rate and the location of STAR-RIS are obtained.

[0150] Among them, under the given RIS phase shift matrix Θ and beamforming matrix W, the optimization problem of formula (19) is the STAR-RIS location vector of the non-linear integer optimization problem. In this application, the enumeration method is used to update the STAR-RIS location in each outer iteration until the maximum sum rate is obtained under the condition of satisfying the constraint (19g).

[0151] Among them, as shown in Table 3 is the calculation process of the location update algorithm of STAR-RIS based on the enumeration method.

[0152] Table 3

[0153]

[0154]

[0155] In a feasible implementation, the specific calculation process of Algorithm 3 includes: input λ, u reference and R before , where is the deployable space of STAR-RIS, λ is the wavelength, u reference is the reference port, and R before is used to save the iterative value of the sum rate in the previous time; according to the input values, establish a loop and update the STAR-RIS location and channel correlation coefficient; according to the updated STAR-RIS location and channel correlation coefficient, calculate the rate R update ; further, through the new sum rate R, obtain the maximum sum rate R * and its corresponding STAR-RIS location u * .

[0156] Optionally, the specific implementation process of S3 includes S31 - S35:

[0157] S31. Set the initial values, including: the deployable space of STAR-RIS, wavelength, reference port, the iterative value of the sum rate saved in the previous time, transmission coefficient, reflection coefficient, and penalty factor;

[0158] S32. According to the initial values, adopt the base station beamforming vector iterative algorithm based on SCA to optimize the beamforming vector of the base station, and output the optimal beamforming vector of the base station;

[0159] S33. According to the beamforming vector of the optimal base station, adopt the STAR-RIS phase shift matrix iterative algorithm based on SCA to optimize the optimization problem of the transmission and reflection phase shift matrix, and output the optimal transmission coefficient and reflection coefficient;

[0160] S34. Adopt the position of STAR-RIS based on the enumeration method to update the STAR-RIS position vector and the channel correlation coefficient, and obtain the updated STAR-RIS position vector and channel correlation coefficient;

[0161] S35. Calculate the maximum sum rate according to the beamforming vector of the optimal base station, the optimal transmission coefficient and reflection coefficient, and the updated STAR-RIS position and channel correlation coefficient.

[0162] In a feasible implementation manner, as shown in Table 4, it is the calculation process of the STAR-RIS-based position and beamforming design algorithm.

[0163] Table 4

[0164]

[0165] In a feasible implementation manner, Figure 3 It represents the schematic diagram of the algorithm convergence result. In the coal mine communication system, the mobile STAR-RIS scheme has remarkable effects; Figure 4 It represents the comparison of the achievable sum rate between the STAR-RIS scheme and the traditional RIS scheme, and shows the relationship between the sum rate and the number N of RIS reflection elements in the two schemes. From Figure 4 It can be seen that in the two schemes, the algorithm has good convergence, and the sum rate increases with the increase of the number of RIS reflection elements. Comparing the STAR-RIS scheme with the traditional RIS scheme, it can be seen that under the condition of meeting the minimum rate constraint of all underground Internet of Things devices, the STAR-RIS scheme improves by 47.3% compared with the traditional RIS scheme.

[0166] In the embodiment of the present invention, a communication model in a coal mine environment is first constructed; secondly, an optimization problem of position and beamforming based on STAR-RIS is constructed according to the communication model; finally, a position and beamforming design algorithm based on STAR-RIS is used to optimize the optimization problem of position and beamforming based on STAR-RIS, and the optimal solution of the optimization problem of position and beamforming based on STAR-RIS is output; according to the optimal solution, the sum rate of the channel based on STAR-RIS is maximized. The use of the present invention can improve the communication rate of the wireless communication system, improve the efficiency and accuracy of the monitoring and remote control of mine equipment, improve the real-time data transmission and response capabilities, enable equipment failures to be detected and processed in a timely manner, reduce downtime, improve production continuity, and can greatly improve the production efficiency of coal mines; the use of the present invention can promote energy conservation and emission reduction in mines, optimize the production process and reduce resource waste, and promote the sustainable development of the coal mining industry.

[0167] Figure 5 FIG. is a block diagram of a STAR-RIS position optimization and beamforming design device in coal mine wireless communication according to an exemplary embodiment, and the device is used for the STAR-RIS position optimization and beamforming design method in coal mine wireless communication. Refer to Figure 5 , the device includes a first construction unit 510, a second construction unit 520, and an optimization and output unit 530. Among them:

[0168] The first construction unit 510 is used to construct a communication model in a coal mine environment;

[0169] The second construction unit 520 is used to construct an optimization problem of position and beamforming based on STAR-RIS according to the communication model;

[0170] The optimization and output unit 530 is used to use a position and beamforming design algorithm based on STAR-RIS to optimize the optimization problem of position and beamforming based on STAR-RIS, and output the optimal solution of the optimization problem of position and beamforming based on STAR-RIS; according to the optimal solution, the sum rate of the channel based on STAR-RIS is maximized.

[0171] Optionally, the optimization problem of position and beamforming based on STAR-RIS includes: a beamforming optimization problem with fixed phase shift, an optimization problem of the transmission and reflection phase shift matrix, and a position optimization problem based on STAR-RIS.

[0172] Optionally, the constraints of the optimization problem for STAR-RIS based position and beamforming include: the minimum rate constraint of each underground coal mine Internet of Things device, the total transmit power constraint of the base station, the amplitude and phase shift coefficient constraints of STAR-RIS, the constraint of the energy conservation law of STAR-RIS, and the position constraint of STAR-RIS.

[0173] Optionally, the STAR-RIS based position and beamforming design algorithm includes: the SCA-based base station beamforming vector iterative algorithm, the SCA-based STAR-RIS phase shift matrix iterative algorithm, and the STAR-RIS position update algorithm based on the enumeration method.

[0174] Optionally, the SCA-based base station beamforming vector iterative algorithm is used to optimize the beamforming optimization problem with fixed phase shifts. By adopting the semi-definite relaxation method and setting relaxation variables for iterative calculation, the optimal base station beamforming vector is output.

[0175] Among them, the SCA-based STAR-RIS phase shift matrix iterative algorithm is used to optimize the optimization problem of the transmission-reflection phase shift matrix. By adopting the semi-definite relaxation method and the penalty-based norm approximation method, and setting relaxation variables and penalty factors for iterative calculation, the optimal transmission coefficient and reflection coefficient of STAR-RIS are output.

[0176] Among them, the STAR-RIS position update algorithm based on the enumeration method is used to optimize the STAR-RIS based position optimization problem; by calculating the sum rate using the SCA-based base station beamforming vector iterative algorithm and the SCA-based STAR-RIS phase shift matrix iterative algorithm, the maximum sum rate and the position of STAR-RIS are obtained.

[0177] Optionally, the optimization and output unit 530 is used for:

[0178] Setting initial values, including: the deployable space of STAR-RIS, wavelength, reference port, the iterative value for saving the previous sum rate, transmission coefficient, reflection coefficient, and penalty factor.

[0179] According to the initial values, the SCA-based base station beamforming vector iterative algorithm is used to optimize the base station beamforming vector, and the optimal base station beamforming vector is output.

[0180] According to the optimal base station beamforming vector, the SCA-based STAR-RIS phase shift matrix iterative algorithm is used to optimize the optimization problem of the transmission-reflection phase shift matrix, and the optimal transmission coefficient and reflection coefficient are output.

[0181] Update the position of the STAR-RIS using the enumeration-based method, and update the STAR-RIS position vector and channel correlation coefficient to obtain the updated STAR-RIS position vector and channel correlation coefficient;

[0182] Calculate the maximum sum rate according to the optimal beamforming vector of the base station, the optimal transmission coefficient and reflection coefficient, and the updated STAR-RIS position and channel correlation coefficient.

[0183] Optionally, the STAR-RIS-based position and beamforming design algorithm includes two layers; the outer layer is used to update the position of the STAR-RIS; the inner layer is used to optimize the active beamforming of the base station and the passive beamforming of the STAR-RIS.

[0184] In the embodiments of the present invention, first, a communication model in a coal mine environment is constructed; second, according to the communication model, an optimization problem based on the position and beamforming of the STAR-RIS is constructed; finally, the STAR-RIS-based position and beamforming design algorithm is used to optimize the optimization problem based on the position and beamforming of the STAR-RIS, and the optimal solution of the optimization problem based on the position and beamforming of the STAR-RIS is output; according to the optimal solution, the sum rate through the STAR-RIS-based channel is maximized. The use of the present invention can improve the communication rate of the wireless communication system, improve the efficiency and accuracy of the monitoring and remote control of mining equipment, improve the real-time data transmission and response capabilities, enable equipment failures to be detected and processed in a timely manner, reduce downtime, improve production continuity, and significantly improve the production efficiency of coal mines; the use of the present invention can promote energy conservation and emission reduction in mines, optimize the production process and reduce resource waste, and promote the sustainable development of the coal mining industry.

[0185] Figure 6 is a schematic structural diagram of a STAR-RIS position optimization and beamforming design device in coal mine wireless communication provided by an embodiment of the present invention, as Figure 6 shown, the STAR-RIS position optimization and beamforming design device in coal mine wireless communication may include the above-mentioned Figure 5 shown STAR-RIS position optimization and beamforming design device in coal mine wireless communication. Optionally, the STAR-RIS position optimization and beamforming design device 610 in coal mine wireless communication may include a first processor 2001.

[0186] Optionally, the STAR-RIS position optimization and beamforming design device 610 in coal mine wireless communication may further include a memory 2002 and a transceiver 2003.

[0187] Among them, the first processor 2001, the memory 2002, and the transceiver 2003 can be connected through a communication bus, for example.

[0188] Next, in combination with Figure 6 Specific components of the STAR-RIS position optimization and beamforming design device 610 in coal mine wireless communication will be specifically introduced:

[0189] Among them, the first processor 2001 is the control center of the STAR-RIS position optimization and beamforming design device 610 in coal mine wireless communication. It can be a single processor or a collective term for multiple processing elements. For example, the first processor 2001 is one or more central processing units (CPUs), or can be an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present invention. For example: one or more digital signal processors (DSPs), or one or more field programmable gate arrays (FPGAs).

[0190] Optionally, the first processor 2001 can execute various functions of the STAR-RIS position optimization and beamforming design device 610 in coal mine wireless communication by running or executing software programs stored in the memory 2002 and calling data stored in the memory 2002.

[0191] In a specific implementation, as an embodiment, the first processor 2001 can include one or more CPUs, such as Figure 6 CPU0 and CPU1 shown in

[0192] In a specific implementation, as an embodiment, the STAR-RIS position optimization and beamforming design device 610 in coal mine wireless communication can also include multiple processors, such as Figure 6 the first processor 2001 and the second processor 2004 shown in

[0193] Among them, the memory 2002 is used to store the software program for implementing the solution of the present invention and is controlled by the first processor 2001 for execution. The specific implementation manner can refer to the above method embodiments and will not be elaborated here.

[0194] Optionally, the memory 2002 can be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or can also be an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM), or other optical disc storage, optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), magnetic disk storage media, or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but not limited thereto. The memory 2002 can be integrated with the first processor 2001 or exist independently and is coupled to the first processor 2001 through an interface circuit ( Figure 6 not shown) of the STAR-RIS position optimization and beamforming design device 610 in coal mine wireless communication. The embodiments of the present invention do not make specific limitations on this.

[0195] The transceiver 2003 is used to communicate with a network device or communicate with a terminal device.

[0196] Optionally, the transceiver 2003 can include a receiver and a transmitter ( Figure 6 not shown separately). Among them, the receiver is used to implement the receiving function, and the transmitter is used to implement the transmitting function.

[0197] Optionally, the transceiver 2003 can be integrated with the first processor 2001 or exist independently and is coupled to the first processor 2001 through an interface circuit ( Figure 6 not shown) of the STAR-RIS position optimization and beamforming design device 610 in coal mine wireless communication. The embodiments of the present invention do not make specific limitations on this.

[0198] It should be noted that Figure 6The structure of the STAR-RIS location optimization and beamforming design device 610 in coal mine wireless communication shown does not limit the router. The actual knowledge structure recognition device may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0199] In addition, for the technical effects of the STAR-RIS location optimization and beamforming design device 610 in coal mine wireless communication, reference can be made to the technical effects of the STAR-RIS location optimization and beamforming design method in coal mine wireless communication described in the above method embodiments, which will not be elaborated here.

[0200] It should be understood that the first processor 2001 in the embodiments of the present invention may be a central processing unit (CPU), and this processor may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or this processor may also be any conventional processor, etc.

[0201] It should also be understood that the memory in the embodiments of the present invention may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchlink DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0202] The above embodiments can be implemented in whole or in part by software, hardware (such as circuits), firmware, or any combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions described in the embodiments of the present invention are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wired (such as infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that contains one or more collections of available media. The available medium can be a magnetic medium (such as a floppy disk, a hard disk, or a magnetic tape), an optical medium (such as a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0203] It should be understood that the term "and / or" in this document is merely a description of the association relationship between associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. Here, A and B can be singular or plural. In addition, the character " / " in this document generally represents an "or" relationship between the associated objects before and after, but it may also represent an "and / or" relationship, which can be specifically understood by referring to the context before and after.

[0204] In the present invention, "at least one" means one or more, and "a plurality" means two or more. "At least one of the following" or its similar expressions refer to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can represent: a, b, c, a - b, a - c, b - c, or a - b - c, where a, b, and c can be single or multiple.

[0205] It should be understood that in various embodiments of the present invention, the magnitudes of the sequence numbers of the above processes do not mean the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0206] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or by a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0207] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the devices, apparatuses, and units described above can refer to the corresponding processes in the foregoing method embodiments, and will not be elaborated herein.

[0208] In several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division, and there can be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces, and the indirect couplings or communication connections of the devices or units can be in electrical, mechanical, or other forms.

[0209] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they can be located in one place, or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0210] In addition, the functional units in each embodiment of the present invention can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit.

[0211] When the above-mentioned functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0212] As described above, the above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A STAR-RIS position optimization and beamforming design method based on coal mine wireless communication, characterized in that: The method comprises: S1. Construct a communication model in a coal mine environment; S2. According to the communication model, construct a STAR-RIS-based position and beamforming optimization problem; S3. Use the STAR-RIS-based position and beamforming design algorithm to optimize the STAR-RIS-based position and beamforming optimization problem, and output the optimal solution of the STAR-RIS-based position and beamforming optimization problem; according to the optimal solution, maximize the channel and rate based on STAR-RIS.

2. The STAR-RIS position optimization and beamforming design method based on coal mine wireless communication according to claim 1 is characterized in that: The optimization problem of position and beamforming based on STAR-RIS includes: the optimization problem of beamforming with fixed phase shift, the optimization problem of transmission-reflection phase shift matrix and the optimization problem of position based on STAR-RIS.

3. The STAR-RIS position optimization and beamforming design method based on coal mine wireless communication according to claim 2 is characterized in that: The constraints of the optimization problem of position and beamforming based on STAR-RIS include: the minimum rate constraint of each coal mine underground IoT device, the total transmission power constraint of the base station, the amplitude and phase shift coefficient constraint of STAR-RIS, the constraint of the STAR-RIS energy conservation law and the position constraint of STAR-RIS.

4. The STAR-RIS position optimization and beamforming design method based on coal mine wireless communication according to claim 1 is characterized in that: The position and beamforming design algorithm based on STAR-RIS includes: a base station beamforming vector iteration algorithm based on SCA, a STAR-RIS phase shift matrix iteration algorithm based on SCA, and a STAR-RIS position update algorithm based on enumeration method.

5. The STAR-RIS position optimization and beamforming design method based on coal mine wireless communication according to claim 4 is characterized in that: The SCA-based base station beamforming vector iteration algorithm is used to optimize the beamforming optimization problem of fixed phase shift, and outputs the optimal base station beamforming vector by setting relaxation variables for iterative calculation using a semidefinite relaxation method; The SCA-based STAR-RIS phase shift matrix iterative algorithm is used to optimize the optimization problem of the transmission-reflection phase shift matrix, and the relaxation variables and penalty factors are set for iterative calculation by adopting a semidefinite relaxation method and a penalty-based norm approximation method to output the optimal STAR-RIS transmission coefficient and reflection coefficient. The enumeration-based STAR-RIS position update algorithm is used to optimize the STAR-RIS-based position optimization problem; the sum rate is calculated by adopting the SCA-based base station beamforming vector iteration algorithm and the SCA-based STAR-RIS phase shift matrix iteration algorithm to obtain the maximum sum rate and the STAR-RIS position.

6. The STAR-RIS position optimization and beamforming design method based on coal mine wireless communication according to claim 1 is characterized in that: The S3 adopts a STAR-RIS-based position and beamforming design algorithm to optimize the STAR-RIS-based position and beamforming optimization problem, and outputs an optimal solution to the STAR-RIS-based position and beamforming optimization problem, including: S31. Set initial values, including: deployable space, wavelength, reference port, iteration value for saving the last sum rate, transmission coefficient, reflection coefficient and penalty factor of STAR-RIS; S32, optimizing the beamforming vector of the base station using the SCA-based base station beamforming vector iteration algorithm according to the initial value, and outputting the optimal beamforming vector of the base station; S33, according to the optimal beamforming vector of the base station, using the STAR-RIS phase shift matrix iterative algorithm based on SCA, optimizing the optimization problem of the transmission-reflection phase shift matrix, and outputting the optimal transmission coefficient and reflection coefficient; S34, using the position of STAR-RIS based on the enumeration method, updating the STAR-RIS position vector and the channel correlation coefficient to obtain an updated STAR-RIS position vector and the channel correlation coefficient; S35. Calculate the maximum sum rate according to the optimal beamforming vector of the base station, the optimal transmission coefficient and reflection coefficient, and the updated STAR-RIS position and channel correlation coefficient.

7. The STAR-RIS position optimization and beamforming design method based on coal mine wireless communication according to claim 1 is characterized in that: The position and beamforming design algorithm based on STAR-RIS comprises two layers, wherein the outer layer is used to update the position of STAR-RIS; and the inner layer is used to optimize the active beamforming of the base station and the passive beamforming of STAR-RIS.

8. A STAR-RIS position optimization and beamforming design device based on coal mine wireless communication, the STAR-RIS position optimization and beamforming design device based on coal mine wireless communication is used to implement the STAR-RIS position optimization and beamforming design method based on coal mine wireless communication as claimed in any one of claims 1 to 7, characterized in that: The device comprises: The first construction unit is used to construct a communication model in a coal mine environment; A second construction unit is used to construct a STAR-RIS-based position and beamforming optimization problem according to the communication model; The optimization and output unit is used to optimize the optimization problem of the position and beamforming based on STAR-RIS by adopting the position and beamforming design algorithm based on STAR-RIS, and output the optimal solution of the optimization problem of the position and beamforming based on STAR-RIS; according to the optimal solution, the sum rate of the channel based on STAR-RIS is maximized.

9. A STAR-RIS position optimization and beamforming design device based on coal mine wireless communication, characterized in that: The STAR-RIS position optimization and beamforming design device based on coal mine wireless communication includes: processor; A memory having computer-readable instructions stored thereon, wherein when the computer-readable instructions are executed by the processor, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores program codes, which can be called by a processor to execute the method according to any one of claims 1 to 7.

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