RIS intelligent coverage optimization system and method with integrated communication and sensing

Abstract

The invention belongs to the technical field of mobile communication, and particularly discloses a communication and sensing integrated RIS intelligent coverage optimization system and method, and the system comprises an intelligent cooperative control center, a train signal terminal disposed on a train, a plurality of 6G communication and sensing integrated base stations disposed at intervals along a train route, and a plurality of RIS array modules disposed at intervals along the train route. Through collaborative optimization of the 6G communication and induction integrated base station and the RIS array, a 6G signal propagation path can be accurately remodeled, the problem of signal attenuation in a weak coverage area is effectively solved, the 6G signal receiving power of a train is improved, and continuous coverage of 6G high-bandwidth services is guaranteed; doppler frequency shift can be accurately offset through dynamic phase adjustment, so that the signal distortion rate is reduced, and the stability of 6G communication of a train in a high-speed running state is ensured; and the channel feedback time delay of traditional base station switching can be eliminated, the success rate of uninterrupted signal switching is improved, and the continuity of 6G key services such as train control and passenger service is guaranteed.

Description

A synesthetic RIS intelligent coverage optimization system and method Technical Field

[0001] This invention belongs to the field of mobile communication technology, specifically relating to a RIS intelligent coverage optimization system and method integrating sensing and communication. Background Technology

[0002] With the rapid development of intelligent high-speed rail technology, traditional 5G and previous generations of mobile communication technologies can no longer meet the extreme communication requirements of future intelligent high-speed rail. Future high-speed rail communication needs to possess four core characteristics: "ultra-high speed, ultra-low latency, ultra-high reliability, and wide-area continuous coverage," which highly aligns with the core technical indicators of 6G mobile communication systems. Existing wireless communication systems face three major pain points in ultra-high-speed rail scenarios, and these pain points are even more pronounced under the demands of 6G services: First, signal attenuation is exacerbated in areas with weak coverage. Tunnels, mountainous terrain, and other terrains strongly obstruct wireless signals and cause multipath attenuation. The terahertz and other high-frequency bands used in 6G communication systems have weak signal penetration capabilities. Combined with the metal shielding effect of train carriages, this further exacerbates signal attenuation, easily leading to communication interruptions and making it impossible to guarantee the continuous transmission of high-bandwidth 6G services.

[0003] Second, the Doppler frequency shift effect caused by high-speed movement is significant. The high-speed relative movement between the ultra-high-speed train and the base station will cause a significant Doppler frequency shift in the wireless signal. The frequency offset sensitivity of 6G high-frequency band signals is even higher, which will cause serious signal frequency shift and rapid time-varying channel, greatly reducing the reliability of the communication link and causing a sharp increase in the bit error rate of 6G services.

[0004] Third, there is a high risk of handover failure across base stations. Traditional handover mechanisms rely on channel feedback between the terminal and the base station to complete resource scheduling and access, with latency typically in the tens of milliseconds. However, the dwell time of ultra-high-speed trains within the coverage area of ​​6G base stations is extremely short. Existing handover latency cannot meet the requirements of 6G ultra-high-speed scenarios, which can easily lead to handover failure and affect the continuity of critical services such as train control. Summary of the Invention

[0005] The purpose of this invention is to provide a RIS intelligent coverage optimization system and method integrating sensing to solve the above-mentioned problems existing in the prior art.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: Firstly, the present invention provides a RIS intelligent coverage optimization system integrating sensing and communication, comprising an intelligent collaborative control center, a train signal terminal installed on the train, a plurality of 6G integrated sensing and communication base stations deployed at intervals along the train route, and a plurality of RIS array modules deployed at intervals along the train route. The plurality of 6G integrated sensing and communication base stations are used to construct a continuous 6G signal network along the train route. The train signal terminal is used to receive 6G signals transmitted by the 6G integrated sensing and communication base stations and / or reflected by the RIS array modules, thereby realizing signal interaction with the 6G integrated sensing and communication base stations. The integrated sensing base station obtains train status perception data and channel status perception data through signal interaction with the train signal terminal, and establishes a signal connection with the intelligent collaborative control center. The train status perception data and channel status perception data are uploaded to the intelligent collaborative control center. The intelligent collaborative control center generates a phase adjustment matrix based on the train status perception data and channel status perception data, and sends the phase adjustment matrix to the corresponding RIS array module. The RIS array module adjusts the phase offset state of its reflection units according to the phase adjustment matrix to change the reflected wavefront of the 6G signal and reshape the propagation path of the 6G signal.

[0007] In one possible design, the train status perception data includes the train's real-time speed and current position. The 6G sensing integrated base station is also used to calculate the train trigger position based on the train's real-time speed and current position. When it is determined that the train trigger position has reached the boundary of the base station's signal coverage area, a resource reservation request is sent to the 6G sensing integrated base station to be switched in the direction of train travel. This allows the 6G sensing integrated base station to be switched to complete resource pre-configuration based on the resource reservation request. The intelligent collaborative control center is also used to synchronously determine the RIS array module corresponding to the 6G sensing integrated base station to be switched in the future based on the train's real-time speed and current position, and to issue a phase adjustment matrix to the RIS array module corresponding to the 6G sensing integrated base station to be switched in the future.

[0008] In one possible design, when the 6G integrated sensing base station calculates the train trigger position based on the train's real-time speed and current position, it substitutes the train's real-time speed and current position into a preset train trigger position calculation model to obtain the train trigger position. The train trigger position calculation model is a = x + v × t. pred Where a represents the train trigger position, x represents the train's current position, v represents the train's real-time speed, and t represents the train's speed. pred This represents the time reserved for resource allocation.

[0009] In one possible design, the intelligent collaborative control center includes a sensing data fusion unit, a dynamic optimization decision-making unit, and a global control distribution unit. The sensing data fusion unit is used to determine the train's trajectory and predicted future position based on the train status sensing data from each 6G integrated sensing base station. The dynamic optimization decision-making unit is used to generate a phase adjustment matrix for one or more RIS array modules, and a resource pre-configuration instruction for the 6G integrated sensing base station to be switched over, based on the predicted train position and channel status sensing data, with the joint optimization objectives of minimizing Doppler frequency shift and maximizing the full-link received signal-to-noise ratio. The global control distribution unit is used to send the phase adjustment matrix to the corresponding RIS array module and the resource pre-configuration instruction to the 6G integrated sensing base station to be switched over.

[0010] In one possible design, the train signal terminal includes a 6G signal antenna array. The train signal terminal is used to periodically feed back signal reception quality parameters to the 6G integrated sensing base station with which the current signal is being interacted. The signal reception quality parameters include reference signal received power, signal-to-interference-plus-noise ratio, and bit error rate.

[0011] In one possible design, the 6G integrated sensing base station is used to extract 6G channel parameters from the received signal using the LS channel estimation algorithm when interacting with the train signal terminal. The 6G channel parameters include channel gain, delay spread, and Doppler frequency offset. The received signal is then analyzed using a constant false alarm rate (CFAR) detection algorithm to obtain the train's real-time speed and current position. The 6G channel parameters and signal reception quality parameters are then incorporated into the channel status perception data, and the train's real-time speed and current position are incorporated into the train status perception data.

[0012] In one possible design, the RIS array module includes a controller and a reconfigurable smart surface composed of several reflective units arranged in a planar array. The controller is communicatively connected to the intelligent collaborative control center and is used to receive the phase adjustment matrix issued by the intelligent collaborative control center and adjust the phase offset state of each reflective unit of the reconfigurable smart surface according to the phase adjustment matrix.

[0013] Secondly, this invention provides a RIS intelligent coverage optimization method integrating sensing and communication, comprising: a 6G sensing-integrated base station on a train route continuously transmitting and receiving co-source 6G signals for communication and sensing, and obtaining train status sensing data and channel status sensing data through coherent signal processing, and sending the train status sensing data and channel status sensing data to an intelligent collaborative control center; the intelligent collaborative control center predicting the train's predicted position in a future prediction time domain based on the train status sensing data uploaded by each 6G sensing-integrated base station; the intelligent collaborative control center generating a phase adjustment matrix for one or more RIS array modules based on the train's current position, predicted position, and channel status sensing data, with the joint optimization objectives of minimizing Doppler frequency shift and maximizing the full-link received signal-to-noise ratio; and the intelligent collaborative control center distributing the phase adjustment matrix to the corresponding RIS array module, so that the corresponding RIS array module adjusts the phase offset state of its reflection units according to the phase adjustment matrix, thereby reshaping the propagation path of the 6G signal.

[0014] In one possible design, the method further includes: the intelligent collaborative control center generating a resource pre-configuration instruction for the future 6G integrated sensing base station to be switched based on the train's current location, the train's predicted location, and channel status perception data, and sending the resource pre-configuration instruction to the future 6G integrated sensing base station to be switched.

[0015] In one possible design, the method further includes: the switched 6G integrated sensing base station continuously monitors the signal strength and Doppler frequency offset when the train signal terminal receives the signal, and transmits the signal strength and Doppler frequency offset as feedback data to the intelligent collaborative control center.

[0016] Beneficial effects: 1. By coordinating a 6G integrated sensing base station and a RIS array, this invention can accurately reshape the 6G signal propagation path, effectively solve the signal attenuation problem in weak coverage areas such as tunnels and mountainous areas, improve the 6G signal reception power inside the train, and ensure continuous coverage of 6G high-bandwidth services.

[0017] 2. This invention addresses the frequency offset sensitivity of 6G high-frequency signals by using dynamic phase adjustment to precisely cancel Doppler frequency shift, thereby reducing signal distortion and ensuring the stability of 6G communication when trains are running at high speeds.

[0018] 3. Based on the 6G integrated sensing and pre-configuration mechanism, this invention can eliminate the channel feedback delay of traditional base station handover, improve the success rate of uninterrupted signal handover, and ensure the continuity of 6G key services such as train control and passenger services.

[0019] 4. By deploying a RIS array, this invention can be upgraded and transformed to be compatible with existing railway communication infrastructure without the need for large-scale construction of new 6G base stations, which can significantly reduce the construction and operation and maintenance costs of 6G railway communication networks.

[0020] 5. This invention adopts a modular design, which can flexibly expand the application of 6G base stations and RIS arrays according to the evolution of 6G technology and the upgrading of railway business needs, and adapt to the communication needs of future higher-speed trains. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 is a schematic diagram of the system structure in Example 1; Figure 2 is a flowchart of the method in Example 2; Figure 3 is a schematic diagram of the intelligent collaborative control center structure in Example 3. Detailed Implementation

[0023] It should be noted that the descriptions of these embodiments are intended to aid in understanding the invention and do not constitute a limitation thereof. The specific structural and functional details disclosed herein are merely for describing exemplary embodiments of the invention. However, the invention may be embodied in many alternative forms and should not be construed as being limited to the embodiments described herein.

[0024] It should be understood that, unless otherwise explicitly specified and limited, the corresponding terms should be interpreted broadly. For example, "connection" can be a fixed connection, a detachable connection, or an integral connection; it can be an electrical connection, a direct connection, or an indirect connection through an intermediate medium; it can also refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in the embodiments according to the specific circumstances.

[0025] Specific details are provided in the following description to provide a complete understanding of the exemplary embodiments. However, those skilled in the art will understand that the exemplary embodiments can be implemented without these specific details. For example, the system may be shown in block diagrams to avoid obscuring the example with unnecessary details. In other embodiments, well-known processes, structures, and techniques may be shown without non-essential details to avoid obscuring the embodiments.

[0026] Example 1: This example provides a RIS intelligent coverage optimization system integrating sensing and communication, as shown in Figure 1. It includes an intelligent collaborative control center, a train signal terminal installed on the train, several 6G integrated sensing base stations deployed at intervals along the train route, and several RIS array modules deployed at intervals along the train route. The 6G integrated sensing base stations are used to construct a continuous 6G signal network along the train route. The train signal terminal is used to receive 6G signals transmitted by the 6G integrated sensing base stations and / or reflected by the RIS array modules, enabling signal interaction with the 6G integrated sensing base stations. Through signal interaction with the train signal terminal, the 6G integrated sensing base stations obtain train status perception data and channel status perception data, and establish a signal connection with the intelligent collaborative control center, uploading the train status perception data and channel status perception data to the intelligent collaborative control center. The intelligent collaborative control center generates a phase adjustment matrix based on the train status perception data and channel status perception data, and distributes the phase adjustment matrix to the corresponding RIS array modules. The RIS array modules adjust the phase offset state of each reflecting unit according to the phase adjustment matrix to change the reflected wavefront of the 6G signal and reshape the propagation path of the 6G signal.

[0027] In practical implementation, 6G integrated sensing base station arrays can be deployed along the railway line at preset intervals to form a continuous 6G communication and sensing coverage network. For areas with weak 6G signal coverage, such as tunnels and mountainous areas, RIS (Reconfigurable Intelligent Surface) arrays can be deployed more densely to achieve precise reflection and enhancement of 6G signals. Train signal terminals can be integrated on the roof of the train to ensure efficient interaction with the 6G integrated sensing base stations and the reflected signals from the RIS arrays. A 6G integrated sensing base station is deployed every 2-3 km on conventional sections, shortening the interval in areas with weak coverage. RIS array modules are deployed longitudinally along the sidewalls inside tunnels, with one group deployed every 500m. In mountainous sections, they are deployed on poles along the line, at the same height as the train roof, ensuring that the 6G signal, after being reflected by the RIS array, can accurately cover the train carriage area.

[0028] Furthermore, the train status perception data includes the train's real-time speed and current position. The 6G integrated sensing base station is also used to calculate the train trigger position based on the train's real-time speed and current position. For example, the train's real-time speed and current position are substituted into a preset train trigger position calculation model to obtain the train trigger position. The train trigger position calculation model is a = x + v × t. pred Where a represents the train trigger position, x represents the train's current position, v represents the train's real-time speed, and t represents the train's speed. predThis represents the reserved resource configuration time. When the train's trigger position is determined to have reached the boundary of the base station's signal coverage area, the 6G integrated sensing base station sends a resource reservation request to the 6G integrated sensing base station to be switched to in the direction of train travel. This allows the 6G integrated sensing base station to be switched to complete resource pre-configuration based on the resource reservation request. Simultaneously, the intelligent collaborative control center also determines the RIS array module corresponding to the 6G integrated sensing base station to be switched to based on the train's real-time speed and current position, and issues a phase adjustment matrix to the corresponding RIS array module. Through this dual pre-configuration of RIS status and signal coverage strategy, the system can access the pre-configured resources of the target base station when the train enters the switching area without additional channel feedback and resource negotiation. Furthermore, the RIS array can continuously provide suitable signal coverage for passengers in the carriage according to the pre-configured coverage strategy, achieving uninterrupted 6G communication link switching and precise adaptation to passenger signal needs throughout the entire process.

[0029] Furthermore, the 6G integrated sensing base station integrates a service communication module and a sensing module in the millimeter wave or terahertz frequency band. This module can design 6G sensing reference symbols based on orthogonal frequency division multiplexing signals, embed the sensing reference symbols into the 6G communication signals, realize the co-source transmission of communication and sensing signals, avoid interference between the two, and extract 6G channel state sensing data (including channel gain, delay spread, Doppler frequency offset, angle of arrival and channel impulse response parameters, etc.) from the received signals through the LS channel estimation algorithm (least square estimation algorithm). Then, the reflected signal echo is analyzed through the target detection algorithm (using constant false alarm rate detection algorithm) to obtain train state sensing data such as real-time position, speed and direction of movement of the train.

[0030] Furthermore, the intelligent collaborative control center includes a sensing data fusion unit, a dynamic optimization decision-making unit, and a global control distribution unit. The sensing data fusion unit receives and fuses asynchronous sensing data from each 6G integrated sensing base station, and uses extended Kalman filtering or particle filtering algorithms to generate continuous high-precision predicted positions of the train's trajectory and future times. The dynamic optimization decision-making unit, based on the train's predicted position and channel state sensing data, constructs a nonlinear constrained optimization objective function f(θ) = α·P(θ) + (1-α)·D(θ), with the joint optimization objectives of minimizing Doppler frequency shift and maximizing the full-link received signal-to-noise ratio, where θ is the phase adjustment matrix of the RIS array, P(θ) is the received power, D(θ) is the Doppler frequency shift cancellation amount, and α is a weighting coefficient (which can be dynamically adjusted according to requirements, ranging from 0.4 to 0.6). Then, the optimal phase matrix is ​​solved iteratively using the alternating direction multiplier method to ensure the real-time performance of the algorithm (the iteration step size can also be dynamically adjusted through 6G channel state feedback to improve the accuracy of phase adjustment). This generates a phase adjustment matrix for one or more RIS array modules and determines the resource pre-configuration instructions for the 6G integrated sensing base station to be switched in the future. The global control distribution unit is used to send the phase adjustment matrix to the corresponding RIS array module and to send the resource pre-configuration instructions to the 6G integrated sensing base station to be switched in the future.

[0031] Furthermore, the train signal terminal includes a 6G signal antenna array, and the train signal terminal is used to periodically feed back signal reception quality parameters to the 6G integrated sensing base station of the current signal interaction. The signal reception quality parameters include reference signal reception power, signal-to-interference-plus-noise ratio and bit error rate.

[0032] Furthermore, the RIS array module includes a controller and a reconfigurable smart surface composed of several reflective units arranged in a planar array (a single array can contain 32-128 subwavelength tunable electromagnetic reflective units). The controller is communicatively connected to the intelligent collaborative control center and is used to receive the phase adjustment matrix issued by the intelligent collaborative control center. The phase adjustment matrix is ​​a complex matrix, and each element corresponds to the phase offset value to be applied to a reflective unit. The controller can dynamically adjust the phase state of each reflective unit of the reconfigurable smart surface according to the phase adjustment matrix, realizing non-uniform phase modulation and beamforming of the incident 6G signal wavefront to dynamically reshape the 6G signal propagation path: on the one hand, it accurately focuses the 6G signal energy to the passenger area in the train carriage with communication needs, specifically enhancing the signal strength in weak coverage areas and high demand areas; on the other hand, it accurately cancels the Doppler frequency shift caused by ultra-high speed movement through phase compensation, ensuring the stability of 6G signal transmission. Ultimately, it achieves collaborative control of 6G signal coverage optimization, Doppler frequency shift cancellation, and seamless switching.

[0033] Example 2: This example provides a RIS intelligent coverage optimization method integrating sensing and communication, which can be applied to the RIS intelligent coverage optimization system of Example 1. As shown in Figure 2, the method includes the following steps: S1. The 6G sensing and communication integrated base station on the train route continuously transmits and receives the same source 6G signal for communication and sensing, and obtains train status sensing data and channel status sensing data through coherent signal processing, and sends the train status sensing data and channel status sensing data to the intelligent collaborative control center.

[0034] S2. The intelligent collaborative control center predicts the train's predicted position in the future time domain based on the train status perception data uploaded by each 6G integrated sensing base station.

[0035] S3. The intelligent collaborative control center generates a phase adjustment matrix for one or more RIS array modules based on the train's current position, predicted position, and channel status perception data, with the joint optimization objectives of minimizing Doppler frequency shift and maximizing the full-link received signal-to-noise ratio.

[0036] S4. The intelligent collaborative control center sends the phase adjustment matrix to the corresponding RIS array module, so that the corresponding RIS array module adjusts the phase offset state of each reflection unit according to the phase adjustment matrix, and reshapes the propagation path of the 6G signal.

[0037] S5. The intelligent collaborative control center generates resource pre-configuration instructions for the 6G integrated sensing base station to be handed over in the future based on the train's current location, predicted location, and channel status perception data. These instructions are then sent to the 6G integrated sensing base station. This allows the base station to pre-allocate preamble signals, synchronization signals, and radio resources to the train signal terminal, and triggers rapid signaling interaction at the handover time. This enables the train signal terminal to seamlessly switch the millimeter-wave or terahertz beam of the serving base station during high-speed movement.

[0038] S6. The switched 6G integrated sensing base station continuously monitors the signal strength and Doppler frequency offset when the train signal terminal receives signals, and transmits the signal strength and Doppler frequency offset as feedback data to the intelligent collaborative control center for online correction and parameter updates of the sensing data fusion unit and the dynamic optimization decision unit, so as to realize dynamic adaptive adjustment of the coverage optimization process.

[0039] Example 3: This example provides an intelligent collaborative control center, as shown in Figure 3. At the hardware level, it includes: a data interface for establishing data connection between the processor and each 6G integrated sensing base station and each RIS array module; a memory for storing instructions; and a processor for reading the instructions stored in the memory and executing the execution steps of the intelligent collaborative control center in Example 2 according to the instructions.

[0040] Optionally, the intelligent collaborative control center also includes an internal bus, through which the processor, memory, and data interface can be interconnected. This internal bus can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc.

[0041] The memory may include, but is not limited to, random access memory (RAM), read-only memory (ROM), flash memory, first-in-first-out (FIFO) memory, and / or first-in-last-out (FILO) memory. The processor may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0042] Finally, it should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A RIS intelligent coverage optimization system integrating sensing, characterized in that, The system includes an intelligent collaborative control center, train signal terminals installed on the train, several 6G integrated sensing base stations deployed at intervals along the train route, and several RIS array modules deployed at intervals along the train route. The 6G integrated sensing base stations are used to construct a continuous 6G signal network along the train route. The train signal terminals are used to receive 6G signals transmitted by the 6G integrated sensing base stations and / or reflected by the RIS array modules, enabling signal interaction with the 6G integrated sensing base stations. Through signal interaction with the train signal terminals, the 6G integrated sensing base stations obtain train status perception data and channel status perception data, establish a signal connection with the intelligent collaborative control center, and upload the train status perception data and channel status perception data to the intelligent collaborative control center. The intelligent collaborative control center is used to generate a phase adjustment matrix based on the train status perception data and channel status perception data, and distribute the phase adjustment matrix to the corresponding RIS array modules. The RIS array modules are used to adjust the phase offset state of each reflecting unit according to the phase adjustment matrix to change the reflected wavefront of the 6G signal and reshape the propagation path of the 6G signal.

2. The RIS intelligent coverage optimization system integrating sensing as described in claim 1, characterized in that, The train status perception data includes the train's real-time speed and current position. The 6G sensing integrated base station is also used to calculate the train trigger position based on the train's real-time speed and current position. When it is determined that the train trigger position has reached the boundary of the base station's signal coverage area, a resource reservation request is sent to the 6G sensing integrated base station to be switched in the direction of the train's travel, so that the 6G sensing integrated base station to be switched in the future can complete the resource pre-configuration according to the resource reservation request. The intelligent collaborative control center is also used to synchronously determine the RIS array module corresponding to the 6G sensing integrated base station to be switched in the future based on the train's real-time speed and current position, and send a phase adjustment matrix to the RIS array module corresponding to the 6G sensing integrated base station to be switched in the future.

3. The RIS intelligent coverage optimization system integrating sensing as described in claim 2, characterized in that, When calculating the train trigger position based on the train's real-time speed and current position, the 6G integrated sensing base station substitutes these two values ​​into a preset train trigger position calculation model to obtain the train trigger position. The train trigger position calculation model is a = x + v × t. pred Where a represents the train trigger position, x represents the train's current position, v represents the train's real-time speed, and t represents the train's speed. pred This represents the time reserved for resource allocation.

4. The RIS intelligent coverage optimization system integrating sensing as described in claim 2, characterized in that, The intelligent collaborative control center includes a sensing data fusion unit, a dynamic optimization decision-making unit, and a global control distribution unit; the sensing data fusion unit is used to determine the train's running trajectory and the predicted position of the train at future times based on the train status sensing data of each 6G integrated sensing base station. The dynamic optimization decision unit is used to generate a phase adjustment matrix for one or more RIS array modules and a resource pre-configuration instruction for the 6G integrated sensing base station to be switched in the future, based on the train's predicted position and channel state sensing data, with the joint optimization objectives of minimizing Doppler frequency shift and maximizing the full-link received signal-to-noise ratio. The global control distribution unit is used to send the phase adjustment matrix to the corresponding RIS array module and to send the resource pre-configuration command to the 6G integrated sensing base station to be switched over in the future.

5. The RIS intelligent coverage optimization system integrating sensing as described in claim 1, characterized in that, The train signal terminal includes a 6G signal antenna array. The train signal terminal is used to periodically feed back signal reception quality parameters to the 6G integrated sensing base station with which the current signal is being interacted. The signal reception quality parameters include reference signal reception power, signal-to-interference-plus-noise ratio, and bit error rate.

6. The RIS intelligent coverage optimization system integrating sensing as described in claim 5, characterized in that, The 6G integrated sensing base station is used to extract 6G channel parameters from the received signal using the LS channel estimation algorithm when interacting with the train signal terminal. The 6G channel parameters include channel gain, delay spread, and Doppler frequency offset. The station also uses a constant false alarm rate (CFAR) detection algorithm to analyze the received signal and obtain the train's real-time speed and current position. The station integrates the 6G channel parameters and signal reception quality parameters into the channel status perception data, and integrates the train's real-time speed and current position into the train status perception data.

7. The RIS intelligent coverage optimization system integrating sensing as described in claim 1, characterized in that, The RIS array module includes a controller and a reconfigurable smart surface composed of several reflective units arranged in a planar array. The controller is communicatively connected to the intelligent collaborative control center and is used to receive the phase adjustment matrix issued by the intelligent collaborative control center and adjust the phase offset state of each reflective unit of the reconfigurable smart surface according to the phase adjustment matrix.

8. A synesthetic RIS intelligent coverage optimization method, applied to the synesthetic RIS intelligent coverage optimization system according to any one of claims 1-7, characterized in that, include: The 6G integrated sensing base stations on the train route continuously transmit and receive co-source 6G signals for communication and sensing. Through coherent signal processing, they obtain train status sensing data and channel status sensing data, and send the train status sensing data and channel status sensing data to the intelligent collaborative control center. The intelligent collaborative control center predicts the train's predicted position in a future prediction time domain based on the train status sensing data uploaded by each 6G integrated sensing base station. Based on the train's current location, predicted location, and channel status perception data, the intelligent collaborative control center generates a phase adjustment matrix for one or more RIS array modules with the joint optimization objectives of minimizing Doppler frequency shift and maximizing the full-link received signal-to-noise ratio. The intelligent collaborative control center sends the phase adjustment matrix to the corresponding RIS array module, enabling the corresponding RIS array module to adjust the phase offset state of each reflection unit according to the phase adjustment matrix, thereby reshaping the propagation path of the 6G signal.

9. The RIS intelligent coverage optimization method integrating sensing as described in claim 8, characterized in that, The method further includes: the intelligent collaborative control center generates a resource pre-configuration instruction for the 6G integrated sensing base station to be switched in the future based on the train's current location, the train's predicted location, and channel status perception data, and sends the resource pre-configuration instruction to the 6G integrated sensing base station to be switched in the future.

10. The RIS intelligent coverage optimization method integrating sensing as described in claim 9, characterized in that, The method further includes: the switched 6G integrated sensing base station continuously monitors the signal strength and Doppler frequency offset when the train signal terminal receives the signal, and transmits the signal strength and Doppler frequency offset as feedback data to the intelligent collaborative control center.

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