An element movable cross-connect type intelligent omni-directional surface assisted 6g low power consumption communication system and method

Abstract

The application belongs to the technical field of 6G wireless communication, and particularly relates to a cross-connection type intelligent omni-directional surface auxiliary 6G low-power consumption communication system with movable elements, which comprises a base station, a cross-connection type intelligent omni-directional surface (STARS) with movable elements and a plurality of user terminals; the cross-connection type intelligent omni-directional surface with movable elements comprises a plurality of mutually parallel first sliding track groups and a plurality of mutually parallel second sliding track groups, the first sliding track groups and the second sliding track groups are perpendicularly crossed to form a two-dimensional plane grid structure, the application adopts a cross-connection type sliding track structure, and the independent movement of all electromagnetic regulating elements is realized through two groups of mutually perpendicular sliding tracks, compared with the traditional scheme that each element is equipped with an independent driving mechanism, the number of driving motors is greatly reduced, and the hardware cost and maintenance complexity of the system are significantly reduced.

Description

Technical Field

[0001] This invention belongs to the field of 6G wireless communication technology, specifically relating to a cross-connected intelligent omnidirectional surface-assisted 6G low-power communication system and method with movable components. Background Technology

[0002] With the commercialization of 5G mobile communication technology and the research and development of 6G mobile communication technology, wireless communication systems have placed higher demands on transmission rate, connection density, and energy efficiency. Simultaneously Transmitting and Reflecting Surface (STARS), as an emerging wireless communication technology, integrates a large number of low-cost electromagnetic control elements on a plane, enabling simultaneous transmission and reflection control of incident electromagnetic waves, thereby flexibly altering the propagation characteristics of the wireless channel.

[0003] Unlike traditional intelligent reflectors (IRS) that only reflect electromagnetic waves, STARS can provide services to users in both transmission and reflection zones simultaneously, effectively solving the signal obstruction problem in base station direct transmission links and significantly improving system coverage and communication performance. However, most existing STARS systems use fixed component structures, meaning the position of the electromagnetic control elements cannot be changed once fixed, making it difficult to flexibly adapt to dynamically changing wireless channel environments. When user locations change or channel conditions become obstructed, the performance of fixed STARS deteriorates sharply.

[0004] To address this issue, researchers have proposed movable antenna technology, which dynamically optimizes channel characteristics by moving the antenna within a confined space. However, existing movable antenna systems typically require an independent drive mechanism for each antenna element. This leads to a sharp increase in system hardware costs, energy consumption, and maintenance complexity as the number of elements increases, making large-scale deployment difficult.

[0005] Especially in 6G communication scenarios, a large number of STARS components need to be deployed to achieve high-precision channel control. Traditional mobile antenna technology solutions obviously cannot meet the requirements of low cost and low power consumption. Therefore, there is an urgent need to develop a new type of mobile STARS system and its optimization method to effectively reduce the hardware cost and energy consumption of the system while ensuring communication performance. Summary of the Invention

[0006] The purpose of this invention is to provide a cross-connected intelligent omnidirectional surface-assisted 6G low-power communication system and method with movable components. It aims to significantly reduce the base station's transmit power and the system's hardware cost while meeting the quality of service requirements of multiple users by adopting a cross-connected movable component structure and a joint optimization algorithm.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a cross-connected intelligent omnidirectional surface assisted 6G low-power communication system with movable components, including a base station, a cross-connected movable component intelligent omnidirectional surface (STARS), and multiple user terminals; The cross-connected movable element intelligent omnidirectional surface includes: Multiple parallel first sliding track groups and multiple parallel second sliding track groups, the first sliding track groups and the second sliding track groups intersecting each other perpendicularly to form a two-dimensional planar grid structure; Multiple electromagnetic control elements are provided, each of which is located at the intersection of the first sliding track and the second sliding track and can move independently along the first sliding track and the second sliding track. The drive control unit is electrically connected to all sliding tracks and is used to receive position control signals and drive the corresponding sliding track to move, so that the electromagnetic control element moves to the target position. The phase control unit is electrically connected to all electromagnetic control elements and is used to independently adjust the transmission coefficient and reflection coefficient of each electromagnetic control element. The base station is equipped with a beamforming module for generating and transmitting precoded signals; The system also includes a central processing unit, which is communicatively connected to the base station, the drive control unit, and the phase adjustment unit, and is used for: Acquire channel state information between the base station and the intelligent omnidirectional surface, channel state information between the intelligent omnidirectional surface and each user terminal, and the current position information of the electromagnetic control element; An alternating optimization framework is adopted to jointly optimize the base station precoding matrix, the phase coefficient matrix of the intelligent omnidirectional surface, and the two-dimensional position coordinates of the electromagnetic control element, so as to minimize the total transmit power of the base station while satisfying the quality of service constraints of all user terminals.

[0008] As a component-movable cross-connected intelligent omnidirectional surface-assisted 6G low-power communication system of the present invention, preferably, the first sliding track group and the second sliding track group both adopt a synchronous belt drive structure, each sliding track is driven by an independent stepper motor, and the drive control unit precisely adjusts the position of the electromagnetic control element by controlling the rotation angle and direction of the stepper motor.

[0009] As a cross-connected intelligent omnidirectional surface-assisted 6G low-power communication system with movable components according to the present invention, preferably, the electromagnetic control element is a metasurface unit with both transmission and reflection functions. Each metasurface unit integrates a PIN diode and a varactor diode. The phase control unit independently controls the transmission amplitude, transmission phase, reflection amplitude, and reflection phase of the unit by adjusting the conduction state of the PIN diode and the bias voltage of the varactor diode.

[0010] As a component-movable cross-connected intelligent omnidirectional surface-assisted 6G low-power communication system of the present invention, preferably, the central processing unit is further used for: Distinguish and identify user terminals in the transmission zone and user terminals in the reflection zone; When optimizing the phase coefficient matrix, a power allocation constraint is set for each electromagnetic control element so that the sum of the transmitted power and reflected power of the element does not exceed its maximum adjustable power.

[0011] As a component-movable cross-connected intelligent omnidirectional surface-assisted 6G low-power communication system of the present invention, preferably, the drive control unit further includes a position sensor for real-time detection of the actual position of each electromagnetic control element and sending the position feedback information to the central processing unit. The central processing unit adjusts the position control signal according to the feedback information to achieve closed-loop position control.

[0012] As a preferred embodiment of the present invention, the cross-connected intelligent omnidirectional surface-assisted 6G low-power communication method with movable components includes the following steps: S1: Construct a multipath hybrid channel model of base station-intelligent omnidirectional surface-user, and obtain the channel response matrix H(X,Y) between the base station and the intelligent omnidirectional surface, and the channel response matrix h between the intelligent omnidirectional surface and each user terminal. k (X,Y), where X and Y represent the horizontal and vertical coordinate vectors of the electromagnetic control element on the two-dimensional plane, respectively; S2: Establish a system optimization problem with the objective function of minimizing the total transmit power of the base station. The constraints include the minimum rate constraint of all user terminals, the boundary constraint of electromagnetic control elements, the minimum spacing constraint, and the phase coefficient constraint. S3: Decompose the system optimization problem into three interrelated sub-problems: the base station active beamforming optimization sub-problem, the intelligent omnidirectional surface passive beamforming optimization sub-problem, and the electromagnetic control element position optimization sub-problem; S4: Using an alternating iterative framework, the three sub-problems are solved sequentially until the total system transmit power converges; S5: Based on the converged optimal solution, adjust the precoding matrix of the base station, the phase coefficient matrix of the intelligent omnidirectional surface, and the position of the electromagnetic control element to achieve low-power communication.

[0013] As a preferred embodiment of the present invention, the method for solving the base station active beamforming optimization sub-problem in step S4 is as follows: The phase coefficient matrix of the fixed intelligent omnidirectional surface and the position of the electromagnetic control element; A fixed-point iterative algorithm is used to solve for the minimum power precoding matrix W that satisfies the signal-to-interference-plus-noise ratio (SIR) constraints for all user terminals. * .

[0014] As a method for cross-connected intelligent omnidirectional surface-assisted 6G low-power communication with movable components according to the present invention, preferably, the specific method for solving the intelligent omnidirectional surface passive beamforming optimization sub-problem in S4 is as follows: The location of the precoding matrix and electromagnetic control elements of the fixed base station; The softmax function is introduced to provide a smooth approximation of the minimum user rate target; By performing a second-order Taylor expansion on the user rate function, the non-convex optimization problem is transformed into a convex optimization problem; The optimal phase coefficient matrix is ​​obtained by solving using the interior point method. * ,in Includes transmission coefficient matrix t and reflection coefficient matrix r.

[0015] As a method for cross-connected intelligent omnidirectional surface-assisted 6G low-power communication with movable components according to the present invention, preferably, the specific method for solving the sub-problem of electromagnetic control element position optimization in S4 is as follows: The precoding matrix of the fixed base station and the phase coefficient matrix of the smart omnidirectional surface; The softmax function is introduced to provide a smooth approximation of the minimum user rate target; Introduce standardized spacing variable d x and d y The boundary constraints and minimum spacing constraints of the electromagnetic control elements are transformed into unit simplex constraints. The standardized spacing variable is updated on the simplex using the exponential gradient descent algorithm to obtain the optimal electromagnetic control element position coordinates (X*, Y*).

[0016] As a component-movable cross-connected intelligent omnidirectional surface-assisted 6G low-power communication system and method of the present invention, preferably, the alternating iterative framework in S4 is as follows: The positions of the electromagnetic control elements are initialized to be uniformly distributed, and the phase coefficient matrix is ​​initialized to be an all-1 matrix. Iteratively execute the following steps: a) Fix the current phase coefficient matrix and component positions, and solve for the optimal precoding matrix; b) Fix the current precoding matrix and element positions, and solve for the optimal phase coefficient matrix; c) Fix the current precoding matrix and phase coefficient matrix, and solve for the optimal element position; When the difference in the total transmit power of the base station between two consecutive iterations is less than a preset threshold, the iteration stops and the optimal solution is output.

[0017] Compared with the prior art, the beneficial effects of the present invention are: This invention employs a cross-connected sliding track structure, which enables the independent movement of all electromagnetic control elements through two sets of mutually perpendicular sliding tracks. Compared with the traditional scheme where each element is equipped with an independent drive mechanism, this significantly reduces the number of drive motors and substantially lowers the system's hardware cost and maintenance complexity.

[0018] This invention, by jointly optimizing base station precoding, intelligent omnidirectional surface phase coefficients, and component locations, can minimize the total transmit power of the base station while meeting the quality of service requirements of all users. Simulation results show that, compared with a fixed STARS system, this invention can reduce the base station transmit power by 10-15 dB.

[0019] The present invention employs an electromagnetic control element that can move freely in a two-dimensional plane and dynamically adjust its position according to real-time channel state information, thereby better adapting to the dynamically changing wireless channel environment and improving the robustness and communication performance of the system.

[0020] This invention utilizes the dual-mode transmission and reflection characteristics of STARS to provide services to users in both transmission and reflection areas simultaneously, effectively solving the signal blockage problem and significantly expanding the system's coverage.

[0021] This invention decomposes a complex joint optimization problem into three easily solvable subproblems by adopting an alternating optimization framework, and solves them respectively using fixed-point iteration, interior-point method and exponential gradient descent algorithm. It has the advantages of fast convergence speed and low computational complexity, and is suitable for real-time applications. Attached Figure Description

[0022] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings: Figure 1 This is a schematic diagram of a cross-connected intelligent omnidirectional surface-assisted 6G low-power communication system with movable components.

[0023] Figure 2 A schematic diagram of an intelligent omnidirectional surface that assists in a 6G low-power communication method for cross-connected intelligent omnidirectional surfaces with movable components.

[0024] Figure 3 A schematic diagram showing the performance comparison between the proposed scheme and the comparative scheme of the cross-connected intelligent omnidirectional surface-assisted 6G low-power communication method for movable components.

[0025] Figure 4 This diagram illustrates the final component distribution of different schemes for a cross-connected intelligent omnidirectional surface-assisted 6G low-power communication system with movable components.

[0026] Figure 5 This is a flowchart illustrating a cross-connected intelligent omnidirectional surface-assisted 6G low-power communication method for movable components. Detailed Implementation

[0027] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0028] Please see Figure 1 This invention provides the following technical solution: a cross-connected intelligent omnidirectional surface-assisted 6G low-power communication system with movable components, comprising a base station, a cross-connected movable intelligent omnidirectional surface, and multiple user terminals. The base station is equipped with M uniform planar array antennas for transmitting precoded signals. The intelligent omnidirectional surface is deployed between the base station and the user terminals to regulate the propagation path of electromagnetic waves. The user terminals are divided into transmission zone users and reflection zone users, located on opposite sides of the intelligent omnidirectional surface.

[0029] Please see Figure 2 The cross-connected movable element intelligent omnidirectional surface includes a first sliding track group, a second sliding track group, multiple electromagnetic control elements, a drive control unit, and a phase control unit; the first sliding track group includes N X The second set of sliding tracks consists of N parallel horizontal sliding tracks. Y A series of parallel vertical sliding tracks, with horizontal sliding tracks intersecting perpendicularly to form N. X ×N Y The system employs a two-dimensional planar grid structure. Each electromagnetic control element is positioned at the intersection of a horizontal and a vertical sliding track, connected to both tracks via a mechanical linkage. When the horizontal sliding track moves, it moves all the electromagnetic control elements on that track horizontally; similarly, when the vertical sliding track moves, it moves all the electromagnetic control elements on that track vertically. By controlling different combinations of track movements, each electromagnetic control element can be moved to any target position within the two-dimensional plane.

[0030] The drive control unit includes N X +N YEach stepper motor driver and its corresponding position sensor are connected to a sliding track, which drives the track's movement. The position sensors are used to detect the actual position of each electromagnetic control element in real time and feed the position information back to the central processing unit.

[0031] The phase modulation unit includes N X ×N Y Each control circuit is an independent control circuit, and each control circuit is connected to an electromagnetic control element. The electromagnetic control element uses a metasurface unit that has both transmission and reflection functions, and integrates two PIN diodes and one varactor diode. By adjusting the conduction state of the PIN diodes, the operating mode of the metasurface unit (transmission mode, reflection mode, or full-duplex mode) can be selected; by adjusting the bias voltage of the varactor diode, the phase of the metasurface unit (0-2π) can be continuously adjusted.

[0032] The central processing unit (CPU) uses a high-performance FPGA or DSP chip and communicates with the base station, drive control unit, and phase modulation unit, respectively. The CPU is responsible for acquiring channel state information, executing optimization algorithms, and generating corresponding control signals.

[0033] The communication parameter optimization method of this invention adopts an alternating optimization framework, the process of which is as follows: Figure 5 As shown, the specific steps are as follows: Step 1: Constructing the channel model To address the dual-area coverage characteristics of STARS, a multipath hybrid channel model incorporating line-of-sight (LOS) and non-line-of-sight (NLOS) components is constructed. The channel response matrix from the base station to STARS is represented as follows: ; in, It is obtained by the Kronecker product of the horizontal and vertical array response matrices. This is the path power diagonal matrix. This is the small-scale fading matrix.

[0034] The channel response vector from STARS to user k is represented as: ; in, and These are the array response vectors in the horizontal and vertical directions, respectively. Let be the path coefficient vector, which satisfies the Ricean fading distribution.

[0035] The signal received by user k is: ; in, These represent the transmission and reflection modes, respectively. t and r represents the transmission coefficient matrix and the reflection coefficient matrix, respectively. Let be the precoding vector of the base station for user k. For user k, send a signal. It is additive white Gaussian noise.

[0036] Step 2: Define the optimization problem The system's optimization objective is to minimize the base station's total transmit power while satisfying the minimum rate constraints for all users. The optimization problem can be expressed as: ; in, Let k be the achievable rate. For the user's minimum rate requirement, and These are the x and y coordinates of the nth element, respectively. and These represent the minimum spacing between components in the horizontal and vertical directions, respectively. and These represent the maximum lengths of the component in the horizontal and vertical directions, respectively. and These are the transmission phase and reflection phase of the nth element, respectively. and These are the transmission amplitude and reflection amplitude of the nth element, respectively.

[0037] Step 3: Decompose and optimize the problem Since the above optimization problem is a non-convex mixed integer programming problem, it is very difficult to solve directly. This invention adopts an alternating optimization framework, decomposing it into three sub-problems: active beamforming optimization for base stations, passive beamforming optimization for STARS systems, and component location optimization.

[0038] Step 4: Solve the active beamforming optimization subproblem With the phase coefficient matrix and element positions of the STARS fixed, optimizing the precoding matrix of the base station transforms the optimization problem into a convex optimization problem, which can be solved using a fixed-point iterative algorithm. Specifically, the optimal precoding vector is obtained by solving the following system of equations: ; in, For the equivalent channel vector, For Lagrange multipliers, Let k be the transmit power of user k.

[0039] Step 5: Solve the passive beamforming optimization subproblem With the precoding matrix and element positions of the fixed base station fixed, the phase coefficient matrix of STARS is optimized. Since the minimum user rate objective function is non-smooth, a softmax function is introduced to approximate it smoothly. ; in, As a smoothing factor, This is a vector containing the transmission and reflection coefficients of all components.

[0040] Then, a second-order Taylor expansion is performed on the user rate function to transform the non-convex optimization problem into a convex optimization problem, and the optimal phase coefficient matrix is ​​obtained by using the interior-point method. * .

[0041] Step 6: Solve the component location optimization subproblem The precoding matrix of the fixed base station and the phase coefficient matrix of STARS are used to optimize the position of the electromagnetic control elements. Since the minimum user rate objective function is non-smooth, a softmax function is introduced to approximate it smoothly. ; To handle the boundary constraints and minimum spacing constraints of the components, we introduce a standardized spacing variable: ; ; in , .

[0042] Through the above transformation, the positional constraint of the element is converted into a unit simplex constraint: ; ; Then, the standardized distance variable is updated on the simplex using the exponential gradient descent algorithm: ; ; in, and For learning rate, Let be the objective function after smooth approximation. .

[0043] Step 7: Iterate alternately until convergence The electromagnetic control elements are initialized to a uniform distribution, and the phase coefficient matrix is ​​initialized to an all-one matrix. Then, steps 4-6 are executed alternately until the difference in the total transmit power of the base station between two adjacent iterations is less than a preset threshold (e.g., 10^-3). Finally, the optimal base station precoding matrix, STARS phase coefficient matrix, and element positions are output.

[0044] Step 8: System parameter adjustment Based on the converged optimal solution, the central processing unit sends a precoding control signal to the base station to adjust the base station's transmit beam; sends a phase control signal to the phase modulation unit to adjust the transmission coefficient and reflection coefficient of each electromagnetic control element; and sends a position control signal to the drive control unit to drive the sliding track to move the electromagnetic control element to the optimal position.

[0045] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A cross-connected intelligent omnidirectional surface-assisted 6G low-power communication system with movable components, characterized in that, It includes base stations, cross-connected movable element smart omnidirectional surfaces (STARS), and multiple user terminals; The cross-connected movable element intelligent omnidirectional surface includes: Multiple parallel first sliding track groups and multiple parallel second sliding track groups, the first sliding track groups and the second sliding track groups intersecting each other perpendicularly to form a two-dimensional planar grid structure; Multiple electromagnetic control elements are provided, each of which is located at the intersection of the first sliding track and the second sliding track and can move independently along the first sliding track and the second sliding track. The drive control unit is electrically connected to all sliding tracks and is used to receive position control signals and drive the corresponding sliding track to move, so that the electromagnetic control element moves to the target position. The phase control unit is electrically connected to all electromagnetic control elements and is used to independently adjust the transmission coefficient and reflection coefficient of each electromagnetic control element. The base station is equipped with a beamforming module for generating and transmitting precoded signals; The system also includes a central processing unit, which is communicatively connected to the base station, the drive control unit, and the phase adjustment unit, and is used for: Acquire channel state information between the base station and the intelligent omnidirectional surface, channel state information between the intelligent omnidirectional surface and each user terminal, and the current position information of the electromagnetic control element; An alternating optimization framework is adopted to jointly optimize the base station precoding matrix, the phase coefficient matrix of the intelligent omnidirectional surface, and the two-dimensional position coordinates of the electromagnetic control element, so as to minimize the total transmit power of the base station while satisfying the quality of service constraints of all user terminals.

2. The component-movable cross-connected intelligent omnidirectional surface-assisted 6G low-power communication system according to claim 1, characterized in that: Both the first and second sliding rail groups adopt a synchronous belt drive structure. Each sliding rail is driven by an independent stepper motor. The drive control unit precisely adjusts the position of the electromagnetic control element by controlling the rotation angle and direction of the stepper motor.

3. The component-movable cross-connected intelligent omnidirectional surface-assisted 6G low-power communication system according to claim 1, characterized in that: The electromagnetic control element is a metasurface unit that has both transmission and reflection functions. Each metasurface unit integrates a PIN diode and a varactor diode. The phase control unit independently controls the transmission amplitude, transmission phase, reflection amplitude, and reflection phase of the unit by adjusting the conduction state of the PIN diode and the bias voltage of the varactor diode.

4. The component-movable cross-connected intelligent omnidirectional surface-assisted 6G low-power communication system according to claim 1, characterized in that: The central processing unit is also used for: Distinguish and identify user terminals in the transmission zone and user terminals in the reflection zone; When optimizing the phase coefficient matrix, a power allocation constraint is set for each electromagnetic control element so that the sum of the transmitted power and reflected power of the element does not exceed its maximum adjustable power.

5. The component-movable cross-connected intelligent omnidirectional surface-assisted 6G low-power communication system according to claim 1, characterized in that: The drive control unit also includes a position sensor for real-time detection of the actual position of each electromagnetic control element and for sending position feedback information to the central processing unit. The central processing unit adjusts the position control signal based on the feedback information to achieve closed-loop position control.

6. A method for cross-connected intelligent omnidirectional surface-assisted 6G low-power communication with movable components, characterized in that, Includes the following steps: S1: Construct a multipath hybrid channel model of base station-intelligent omnidirectional surface-user, and obtain the channel response matrix H(X,Y) between the base station and the intelligent omnidirectional surface, and the channel response matrix h between the intelligent omnidirectional surface and each user terminal. k (X,Y), where X and Y represent the horizontal and vertical coordinate vectors of the electromagnetic control element on the two-dimensional plane, respectively; S2: Establish a system optimization problem with the objective function of minimizing the total transmit power of the base station. The constraints include the minimum rate constraint of all user terminals, the boundary constraint of electromagnetic control elements, the minimum spacing constraint, and the phase coefficient constraint. S3: Decompose the system optimization problem into three interrelated sub-problems: the base station active beamforming optimization sub-problem, the intelligent omnidirectional surface passive beamforming optimization sub-problem, and the electromagnetic control element position optimization sub-problem; S4: Using an alternating iterative framework, the three sub-problems are solved sequentially until the total system transmit power converges; S5: Based on the converged optimal solution, adjust the precoding matrix of the base station, the phase coefficient matrix of the intelligent omnidirectional surface, and the position of the electromagnetic control element to achieve low-power communication.

7. The method for cross-connected intelligent omnidirectional surface-assisted 6G low-power communication with movable components according to claim 6, characterized in that: The specific method for solving the base station active beamforming optimization sub-problem in S4 is as follows: The phase coefficient matrix of the fixed intelligent omnidirectional surface and the position of the electromagnetic control element; A fixed-point iterative algorithm is used to solve for the minimum power precoding matrix W that satisfies the signal-to-interference-plus-noise ratio (SINNR) constraints for all user terminals. * .

8. The method for cross-connected intelligent omnidirectional surface-assisted 6G low-power communication with movable components according to claim 6, characterized in that: The specific method for solving the intelligent omnidirectional surface passive beamforming optimization sub-problem in S4 is as follows: The location of the precoding matrix and electromagnetic control elements of the fixed base station; The softmax function is introduced to provide a smooth approximation of the minimum user rate target; By performing a second-order Taylor expansion on the user rate function, the non-convex optimization problem is transformed into a convex optimization problem; The optimal phase coefficient matrix is ​​obtained by solving using the interior point method. * ,in Includes transmission coefficient matrix t and reflection coefficient matrix r.

9. A method for cross-connected intelligent omnidirectional surface-assisted 6G low-power communication with movable components according to claim 6, characterized in that: The specific method for solving the electromagnetic control element position optimization subproblem in S4 is as follows: The precoding matrix of the fixed base station and the phase coefficient matrix of the smart omnidirectional surface; The softmax function is introduced to provide a smooth approximation of the minimum user rate target; Introduce standardized spacing variable d x and d y The boundary constraints and minimum spacing constraints of the electromagnetic control elements are transformed into unit simplex constraints. The standardized spacing variable is updated on the simplex using the exponential gradient descent algorithm to obtain the optimal electromagnetic control element position coordinates (X*, Y*).

10. A method for cross-connected intelligent omnidirectional surface-assisted 6G low-power communication with movable components according to claim 6, characterized in that: The alternating iteration framework in S4 is specifically as follows: The positions of the electromagnetic control elements are initialized to be uniformly distributed, and the phase coefficient matrix is ​​initialized to be an all-1 matrix. Iteratively execute the following steps: a) Fix the current phase coefficient matrix and component positions, and solve for the optimal precoding matrix; b) Fix the current precoding matrix and element positions, and solve for the optimal phase coefficient matrix; c) Fix the current precoding matrix and phase coefficient matrix, and solve for the optimal element position; When the difference in the total transmit power of the base station between two consecutive iterations is less than a preset threshold, the iteration stops and the optimal solution is output.

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