Vehicle adaptive communication control method, device and product

Abstract

This application relates to a vehicle adaptive communication control method, device, and product. The method includes: determining a comprehensive threat index and a comprehensive internal communication demand index based on the conflict between internal and external risks and communication needs of the vehicle; and adaptively meshing the vehicle's programmable metasurface accordingly: densifying or overlapping the mesh in high-risk areas and merging the mesh in low-risk areas; then iteratively optimizing the mesh configuration through a game-theoretic approach involving global and local protection strategies, with the game weights adjusted in real time according to the vehicle's dynamic state; finally, mapping the optimized configuration to a control array; and dynamically controlling the electromagnetic properties of the metasurface through phase shift and polarization angle commands, thereby achieving intelligent dynamic optimization of vehicle electromagnetic protection. This approach can balance communication quality and anti-interference capability in complex environments, improving vehicle communication security and electromagnetic interference protection efficiency.

Description

Technical Field

[0001] This application relates to the field of communication security technology, and in particular to a vehicle adaptive communication control method, device and product. Background Technology

[0002] In existing technologies, programmable metasurfaces have been initially applied in fields such as communications, radar, and stealth. By integrating tunable components such as PIN (Positive-Intrinsic-Negative) diodes, MEMS (Micro-Electro-Mechanical Systems), and phase change materials, they achieve dynamic control of electromagnetic wave amplitude, phase, and polarization characteristics. However, existing technologies are mostly limited to static or small-scale scenarios, lacking the capability for large-scale, adaptive, and real-time collaborative control in high-speed moving vehicles. Especially when facing multi-source interference and dynamic communication requirements, it is difficult to achieve timely and accurate dynamic allocation of electromagnetic protection and communication resources. Summary of the Invention

[0003] To address the aforementioned issues, embodiments of this application provide a vehicle adaptive communication control method, device, storage medium, and product.

[0004] According to a first aspect of the embodiments of this application, a vehicle adaptive communication control method is provided, the method comprising: Based on the conflict between the external risk interference frequency bands of the target vehicle and the bandwidth requirements corresponding to the internal communication task priorities, the comprehensive threat index and the comprehensive internal communication requirement index are determined. Based on the comprehensive threat index and the comprehensive internal communication requirement index, as well as the window geometry parameters of the target vehicle, the programmable metasurface of the target vehicle is meshed, and the meshes belonging to the first risk area are locally densified or regionally overlapped, while the meshes belonging to the second risk area are merged to obtain an initial programmable metasurface mesh configuration, wherein the risk level or priority of the first risk area is higher than that of the second risk area. For the initial programmable hypersurface mesh configuration, the payoff of the macroscopic layer is iterated according to the global protection strategy game of the entire mesh and the local protection strategy game of the first risk mesh, and the weights of the global protection strategy game and the local protection strategy game are dynamically adjusted based on the vehicle dynamic state to determine the target programmable hypersurface mesh configuration. The target programmable metasurface mesh configuration is mapped to each control subarray of the vehicle, and phase shift commands and polarization angle commands are issued to control the tunable units in each mesh of the vehicle.

[0005] In one implementation, the external risk interference frequency band is determined based on weighted aggregation data of multi-source sensor data of the target vehicle on a unified time axis. The determination of the comprehensive threat index and the comprehensive internal communication demand index based on the conflict between the external risk interference frequency band and the bandwidth requirements corresponding to the internal communication task priorities of the target vehicle includes: The set of external risk interference frequency bands is determined based on the interference risk of each frequency band of the external channel of the target vehicle on the unified time axis; Based on the communication resource requirements of internal communication tasks on the unified time axis and the set of external risk interference frequency bands, a comprehensive evaluation is performed according to the threat and demand fusion function to obtain a comprehensive ranking result of the internal communication task priorities. Based on the comprehensive ranking results and the external risk interference frequency band set, the comprehensive threat index and the comprehensive internal communication demand index are determined.

[0006] In one implementation, before determining the comprehensive threat index and the comprehensive internal communication requirement index based on the conflict between the external risk interference frequency bands and the bandwidth requirements corresponding to the internal communication task priorities of the target vehicle, the method further includes: The distance and speed information matrix collected by the millimeter-wave radar of the target vehicle, the image feature vector collected by the camera of the target vehicle, and the signaling information and link quality information output by the target vehicle through V2X (Vehicle-to-Everything) are aligned on a unified time axis. The weighted aggregated data is obtained by weighting and fusing the distance and speed information, the image feature vector, the signaling information and the link quality information according to their respective weights and data compensation amounts. The data compensation amount of the target information is the data compensation of the target information when the target vehicle accelerates and turns.

[0007] In one implementation, the global protection strategy game is used to determine the protection of the grid from a macro level, the local protection strategy game is used to optimize the protection for the first risk grid, and the payoff of the macro level is used to measure the overall payoff of grid shielding or windowing on a unified time axis. The process for determining the target programmable hypersurface mesh configuration involves iterating through a global protection strategy game across the entire mesh and a local protection strategy game for the first risk mesh, based on the macroscopic layer's payoff. The weights of the global and local protection strategy games are dynamically adjusted based on the vehicle's dynamic state. For the initial programmable hypersurface mesh configuration, the payoff of the macroscopic layer is iterated according to the global protection strategy game of the whole mesh and the local protection strategy game of the first risk mesh. The weights of the global protection strategy game and the weights of the local protection strategy game are dynamically adjusted based on the vehicle dynamic state. The first programmable hypersurface mesh configuration is determined when the iteration converges. The priority of the final masking or projection of all meshes in the first programmable metasurface mesh configuration is re-verified to form a globally executable list of equilibrium parameters to determine the second programmable metasurface mesh configuration. The second programmable metasurface mesh configuration is used as the target programmable metasurface mesh configuration.

[0008] In one implementation, the global protection strategy game is used to determine the protection of the grid from a macro level, the local protection strategy game is used to optimize the protection for the first risk grid, and the payoff of the macro level is used to measure the overall payoff of grid shielding or windowing on a unified time axis. The process for determining the target programmable hypersurface mesh configuration involves iterating through a global protection strategy game across the entire mesh and a local protection strategy game for the first risk mesh, based on the macroscopic layer's payoff. The weights of the global and local protection strategy games are dynamically adjusted based on the vehicle's dynamic state. For the initial programmable hypersurface mesh configuration, the payoff of the macroscopic layer is iterated according to the global protection strategy game of the whole mesh and the local protection strategy game of the first risk mesh. The weights of the global protection strategy game and the weights of the local protection strategy game are dynamically adjusted based on the vehicle dynamic state. The first programmable hypersurface mesh configuration is determined when the iteration converges. The priority of the final masking or projection of all meshes in the first programmable metasurface mesh configuration is verified to form a globally executable list of equalization parameters to determine the second programmable metasurface mesh configuration. The second programmable metasurface mesh configuration is further verified based on the real-time threat distribution and communication requirements of the target vehicle to determine the blocking metric for the first risk area or emergency communication channel. If the blocking metric does not exceed a preset threshold, then the second programmable metasurface mesh configuration is used as the target programmable metasurface mesh configuration, or... If the blocking metric exceeds the preset threshold, the grid of the first risk area is further subdivided, and based on the subdivided grid, the global protection strategy game of the entire grid and the local protection strategy game of the first risk grid are iterated according to the macro-level payoffs to obtain the target programmable metasurface grid configuration.

[0009] In one implementation, the step of mapping the target programmable metasurface mesh configuration to each control subarray of the vehicle and issuing phase shift commands and polarization angle commands to control the tunable units in each mesh of the vehicle includes: The priority of the control subarray is determined based on the urgency function; Based on the priority, the synchronous configuration of each control subarray of the same priority is performed by parallel triggering instruction set, and phase shift instructions and polarization angle instructions are issued to control the tunable units in each grid of the vehicle.

[0010] In one embodiment, the method further includes: Real-time monitoring of power consumption and temperature of each control subarray; fault-tolerant switching of backup subarray in case of failure of primary control subarray.

[0011] In one embodiment, the method further includes: Upon detecting extreme electromagnetic interference or communication interruption, the game iteration process is skipped, and a global forced shielding mode is activated to prioritize the protection of critical communications and vehicle safety.

[0012] According to a second aspect of the embodiments of this application, a vehicle adaptive communication control device is provided, the device comprising: The determination module is used to determine the comprehensive threat index and the comprehensive internal communication requirement index based on the conflict between the external risk interference frequency band and the bandwidth requirements corresponding to the internal communication task priority of the target vehicle. The partitioning module is used to partition the programmable metasurface of the target vehicle into a mesh based on the comprehensive threat index, the comprehensive internal communication requirement index, and the window geometry parameters of the target vehicle. The meshes belonging to the first risk area are locally densified or overlapped, and the meshes belonging to the second risk area are merged to obtain an initial programmable metasurface mesh configuration, wherein the risk level or priority of the first risk area is higher than that of the second risk area. The game theory module is used to iterate the global protection strategy game of the entire mesh and the local protection strategy game of the first risk mesh based on the macroscopic layer payoff for the initial programmable hypersurface mesh configuration, and dynamically adjust the weights of the global protection strategy game and the local protection strategy game based on the vehicle dynamic state to determine the target programmable hypersurface mesh configuration. The control module is used to map the target programmable metasurface mesh configuration to each control subarray of the vehicle, and to issue phase shift commands and polarization angle commands to control the tunable units in each mesh of the vehicle.

[0013] According to a third aspect of the embodiments of this application, an electronic device is provided, comprising: A memory on which computer programs are stored; A processor for executing the computer program in the memory to implement the steps of the method of any one of the first aspects.

[0014] According to a fourth aspect of the embodiments of this application, a non-transitory computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the steps of the method described in any one of the first aspects.

[0015] According to a fifth aspect of the embodiments of this application, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps of the method described in any one of the first aspects.

[0016] The embodiments of this application can achieve the following beneficial effects: Based on the conflict between internal and external risks and communication needs of the vehicle, the embodiments of this application determine the comprehensive threat index and the comprehensive internal communication need index, and accordingly perform adaptive meshing on the vehicle's programmable metasurface. The mesh is densified or overlapped in high-risk areas, and the mesh is merged in low-risk areas. Then, the mesh configuration is iteratively optimized through a game between global and local protection strategies. The game weight is adjusted in real time according to the dynamic state of the vehicle. Finally, the optimized configuration is mapped to the control array. The electromagnetic properties of the metasurface are dynamically controlled through phase shift and polarization angle commands, thereby realizing intelligent dynamic optimization of vehicle electromagnetic protection. It can balance communication quality and anti-interference capability in complex environments, and improve vehicle communication security and electromagnetic interference protection efficiency.

[0017] Other features and advantages of this application will be described in detail in the following detailed description section. Attached Figure Description

[0018] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 This is a flowchart of a vehicle adaptive communication control method provided in an embodiment of this application.

[0019] Figure 2 This is a flowchart of a vehicle adaptive communication control method provided in an embodiment of this application.

[0020] Figure 3 This is a flowchart of a vehicle adaptive communication control method provided in an embodiment of this application.

[0021] Figure 4 This is a flowchart of a vehicle adaptive communication control method provided in an embodiment of this application.

[0022] Figure 5 This is a flowchart of a vehicle adaptive communication control method provided in an embodiment of this application.

[0023] Figure 6 This is a flowchart of a vehicle adaptive communication control method provided in an embodiment of this application.

[0024] Figure 7 This is a flowchart of a vehicle adaptive communication control method provided in an embodiment of this application.

[0025] Figure 8 This is a flowchart of a vehicle adaptive communication control method provided in an embodiment of this application.

[0026] Figure 9 This is a block diagram of a vehicle adaptive communication control device provided in one embodiment of this application.

[0027] Figure 10 This is a block diagram of an electronic device provided in one embodiment of this application. Detailed Implementation

[0028] The specific embodiments of this application will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit this application.

[0029] It should be understood that the term "comprising" and its variations as used herein are open-ended, meaning "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Definitions of other terms will be given in the following description.

[0030] It should be noted that the concepts of "first" and "second" mentioned in this application are only used to distinguish different devices, modules, or units, and are not used to limit the order of functions performed by these devices, modules, or units or their interdependencies. The modifications of "one" and "multiple" mentioned in this application are illustrative rather than restrictive, and those skilled in the art should understand that, unless explicitly stated in the context, they should be understood as "one or more". In the description of this application, unless otherwise stated, "multiple" means two or more, and other quantifiers are similar; "at least one item", "one item or multiple items", or similar expressions refer to any combination of these items, including any combination of single or multiple items.

[0031] Although operations or steps are described in a specific order in the accompanying drawings in the embodiments of this application, this should not be construed as requiring these operations or steps to be performed in the specific order or serial order shown, or requiring all of the shown operations or steps to be performed to obtain the desired result. In the embodiments of this application, these operations or steps may be performed serially; they may be performed in parallel; or a portion of these operations or steps may be performed.

[0032] The names of the messages or information exchanged between multiple devices in the embodiments of this application are for illustrative purposes only and are not intended to limit the scope of these messages or information. It is understood that before using the technical solutions disclosed in the embodiments of this application, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in this application in an appropriate manner in accordance with relevant laws and regulations, and user authorization should be obtained.

[0033] First, the application scenarios of this application will be described. Traditional metasurfaces are composed of artificially designed subwavelength periodic structural units. Through precise arrangement and parameter design, the amplitude, phase, polarization, and other characteristics of electromagnetic waves can be flexibly controlled at ultra-thin thicknesses. Early metasurfaces were mostly static or passive, and once fabricated, it was difficult to dynamically switch their operating modes during subsequent use. With the development of digital circuits, radio frequency chips, and new materials, researchers have begun to integrate tunable devices (such as PIN diodes, MEMS, phase change materials, graphene, etc.) into metasurfaces, enabling them to achieve "real-time tunability" of electromagnetic properties under the action of external driving voltages or signals, thus further evolving into programmable or reconfigurable metasurfaces.

[0034] The core idea of ​​programmable metasurfaces (or digital, coded metasurfaces) lies in defining a digital tuning state for each metaunit, such as discretely encoding phase and amplitude using binary or multi-level methods. At the application level, in response to different external signals and requirements, feedback control of MCUs (Microcontroller Units), FPGAs (Field-Programmable Gate Arrays), and other similar devices can adjust the "coding" of all metaunits in real time, thereby switching between multiple functions such as reflection, transmission, and absorption. Even the same metasurface can perform differentiated control for beams in different directions or frequency bands. This control method expands metasurfaces from single-function devices into a new platform with "software-defined electromagnetic properties," combining flexibility and scalability.

[0035] Currently, programmable metasurfaces have achieved certain results in fields such as radar stealth, beamforming, communication transmission windows, and vortex electromagnetic wave generation. "Coded metasurface materials" have demonstrated excellent plasticity in beam control and information modulation. Subsequent research has further introduced various phase change materials and high-speed tuning devices, significantly improving the "switching" speed, power consumption, and reliability. (Switching speed refers to the time required for the metasurface to switch from one operating state to another. For example, when using tuning elements such as PIN diodes or phase change materials to change the reflection or transmission characteristics of a unit, the required reaction speed for the voltage signal to switch from "off" to "on" or from one phase change state to another. Faster switching speed means the metasurface can respond more promptly to external signals or environmental changes, achieving higher control bandwidth and more flexible real-time control. Power consumption refers to the energy consumed by the metasurface when switching states or maintaining a specific operating state. Tunable devices require a certain amount of electrical energy to drive them when changing their electromagnetic properties or maintaining a certain operating mode (e.g., applying bias current to PIN diodes, etc., for MEMS...). (Components provide mechanical driving force, etc.). Low power consumption means using less electrical energy for the same functional requirements, improving system endurance and reducing thermal management pressure. Reliability refers to the stability and lifespan of the metasurface and its internal tuning devices under different environments and long-term, large-scale use. For example, some phase change materials experience performance degradation after frequent phase transitions, and MEMS structures may fail under continuous vibration or external impact. High reliability means better device durability and stability, allowing for a wider range and higher frequency of switching operations without easily being damaged or experiencing performance degradation. Another part of the research focuses on the development of "adaptive metasurfaces," which utilize environmental or target information returned by sensors to dynamically update the encoding strategy of the metasurface, forming a closed-loop control system to cope with time-varying scenarios.

[0036] Based on the aforementioned underlying technologies, current technologies are typically applied to scenarios with small scales or relatively simple requirements. For example, tunable materials are used to replace traditional glass in certain building components to achieve basic shielding or transmission for fixed frequency bands. When using such solutions, it is often impossible to respond in real-time to various complex channel environments over a large area, and communication resources are rarely dynamically allocated through multi-source sensing. Therefore, the overall system structure is relatively simplified, lacking large-scale, adaptive, and real-time collaborative control capabilities in high-speed moving vehicles. Especially when facing multi-source interference and dynamic communication requirements, it is difficult to achieve timely and accurate dynamic allocation of electromagnetic protection and communication resources. Therefore, there is an urgent need for a vehicle adaptive communication control method, device, storage medium, and product. The following describes this application with specific embodiments.

[0037] Figure 1 This is a flowchart of a vehicle adaptive communication control method provided in one embodiment of this application. Figure 1 As shown in the figure, this application provides a vehicle adaptive communication control method, which may include the following steps: In step S10, the comprehensive threat index and the comprehensive internal communication demand index are determined based on the conflict between the external risk interference frequency bands of the target vehicle and the bandwidth requirements corresponding to the internal communication task priorities.

[0038] For example, the external risk interference frequency band set can be determined first based on the interference risk of each frequency band of the target vehicle's external channel on a unified time axis. Then, based on the communication resource requirements of the internal communication tasks on a unified time axis and the external risk interference frequency band set, a comprehensive evaluation is performed according to the threat and requirement fusion function to obtain a comprehensive ranking result of the internal communication task priority. Finally, based on the comprehensive ranking result and the external risk interference frequency band set, the comprehensive threat index and the comprehensive internal communication requirement index are determined.

[0039] The comprehensive threat index is a threat index determined based on the external risk interference frequency bands of the target vehicle, while the comprehensive internal communication demand index is a demand index determined based on the bandwidth requirements corresponding to the priority of internal communication tasks.

[0040] Optionally, in a specific embodiment, a threat-demand mapping matrix can be used to represent the threat synthesis index and the internal communication demand synthesis index, wherein the elements in the threat-demand mapping matrix are used to represent the mapping relationship between the threat synthesis index and the internal demand index, and carry information about the threat synthesis index and the internal demand index.

[0041] In the embodiments of this specification, the mapping relationship between threat comprehensive indicators and internal communication requirement comprehensive indicators can be integrated and encoded using a stack-based approach. For example, for threat comprehensive indicators... Comprehensive indicators of content communication needs ,Can This represents the integrated code, calculated by weighting the two indicators with different weights. Based on this integrated indicator, the final code can be directly parsed. and For example, Integers ranging from 1 to 50 Integers ranging from 1 to 100 are used. As a merged metric, assuming the merged metric is 30040, it is easy to derive from this metric... It is 30. The value is 40. This fusion method allows the threat-demand mapping matrix to retain relevant information between the comprehensive threat index (frequency interference characteristics) and the comprehensive content communication demand index (bandwidth urgency information). Subsequently, the comprehensive threat index and the comprehensive internal communication demand index can be quickly reconstructed from the elements in the threat-demand mapping matrix. By merging the comprehensive threat index and the comprehensive internal communication demand index using this method, the number of dimensions required to represent them can be reduced by half. Of course, other methods for representing the mapping relationship between the comprehensive threat index and the comprehensive internal demand index are not excluded.

[0042] In step S20, based on the comprehensive threat index and the comprehensive internal communication requirement index, as well as the window geometry parameters of the target vehicle, the programmable metasurface of the target vehicle is meshed, and the meshes belonging to the first risk area are locally encrypted or regionally overlapped, while the meshes belonging to the second risk area are merged to obtain an initial programmable metasurface mesh configuration, wherein the risk level or priority of the first risk area is higher than that of the second risk area.

[0043] In this step, based on comprehensive threat indicators, comprehensive internal communication demand indicators, and the window geometry parameters of the target vehicle, the programmable metasurface of the target vehicle is meshed. For high-risk areas (first-risk areas) and areas with high-priority communication needs, the local mesh's control over external interference and core communication tasks is improved by locally refining or overlapping the mesh. For low-risk areas (second-risk areas), the mesh subdivision level is reduced and merged. For areas where no new threats have appeared for a long time or where high bandwidth demands are not met, the mesh subdivision level is reduced to cut unnecessary computational and hardware scheduling burdens and free up resources for areas requiring priority processing. The continuity of neighbor coupling and partition boundaries is maintained. After the meshes of high-risk and low-risk areas have been initially adjusted, further attention is paid to the signal coupling between neighboring meshes to avoid boundary breaks caused by excessive refinement or random partitioning.

[0044] In step S10, if a threat-demand mapping matrix is ​​constructed based on the weighted aggregated data along a unified time axis and the comprehensive ranking result of the external risk interference frequency band set and the internal communication task priority, then in step S20, the threat-demand mapping matrix, combined with the window geometry parameters, can be used to guide the meshing of the programmable metasurface. For each mesh, the associated high-risk frequency bands (obtained through the high-risk frequency band set H(t)) and corresponding task priorities are extracted within its projection area, forming the dynamic risk metric and communication bandwidth demand metric for that mesh, respectively, and are updated on a rolling basis within the observation period. The comprehensive threat index and the comprehensive internal communication demand index can be obtained by decoding and restoring the elements in the threat-demand mapping matrix.

[0045] When the overall encryption demand strength of a certain grid continuously exceeds the preset threshold, or when it still exhibits both high-risk and high-priority communication demands after iterative convergence, it is identified as a first-risk area, and local encryption or area overlap is performed. When the average threat and bandwidth idleness combination value of a certain grid is consistently positive and exceeds the threshold within the observation period, but does not meet high bandwidth demands, it is identified as a second-risk area, and the grid is reduced and merged at the subdivision level. When the vehicle's dynamic state changes, the judgment threshold and priority are corrected online through a dynamic weight update mechanism, so that the division of the first and second risk areas is adaptive to the driving scenario. The area division results are checked for boundary continuity by the adjacency matrix. If phase shift or polarization angle conflict occurs, the boundary is slightly corrected to avoid boundary breakage caused by over-refinement or random division. Finally, the above area division is written into the initial programmable hypersurface grid configuration.

[0046] To facilitate understanding of the grid division mentioned above, the following explanation will be provided in conjunction with some specific calculation formulas.

[0047] Optionally, based on the comprehensive threat index and the comprehensive internal communication requirement index, as well as the window geometry parameters of the target vehicle, the programmable metasurface of the target vehicle is meshed as follows: Define geometric factors This indicates the basic dimensions and curvature characteristics of the car window, making This indicates a comprehensive threat index, making These represent comprehensive indicators of internal communication needs. These two indicators can be derived from the elements of the threat-needs mapping matrix.

[0048] Will As corresponding weighting coefficients, the entire grid is divided to obtain a comprehensive grid division index. ; Formula 1 in Indicates the geometric distribution elements of the vehicle windows; This represents the triple weighting coefficient, used to balance the combined effects of geometric constraints, threats, and demands.

[0049] Among them, the comprehensive threat index It is a single index that quantifies the electromagnetic environment outside the vehicle based on the external interference judgment results and the high-risk frequency band set H(t). By normalizing and weighting the power spectrum intensity, occurrence probability and impact on key communication tasks of each high-risk frequency band, it uses a time-varying scalar to characterize the overall interference level at time t.

[0050] Comprehensive indicators of internal communication requirements It is a fusion metric for resource requests from various DistinctTasks within the vehicle in terms of bandwidth, latency, and security priority. By weighting and summing each task on a unified timeline according to its priority and resource requirements, and then normalizing, a scalar representing the overall communication urgency of the vehicle is obtained.

[0051] Ω(t) represents the mesh generation comprehensive index, which is used to combine the window geometry factor G0, the external threat comprehensive value ρ(t), and the internal demand index δ(t) into a unified measure that determines the initial mesh density through weighting coefficients α1, α2, and α3.

[0052] The larger Ω(t) is, the more initial partition interfaces N0 there are. The coefficients α1, α2, and α3 are specifically used to balance geometric constraints, external threats, and internal requirements in the initial mesh generation.

[0053] based on The calculated results determine the initial mesh density and define it on the metasurface. A split interface. (This is followed by a seemingly unrelated instruction: "Let...") This represents the initial set of grid boundaries, either horizontally or vertically.

[0054] like If it is larger, then This can be appropriately increased to reserve more partitioning units when facing high threats and high demands; if If the mesh size is smaller, a sparser initial mesh is maintained, reducing subsequent computational overhead.

[0055] After completing the initial grid division, focus on high-risk directions and areas with high-priority communication needs, and improve the local grid's control over external interference and core communication tasks by locally encrypting or overlapping the grid.

[0056] make Indicates the first Dynamic risk measurement of individual local grid cells Indicates the first Communication bandwidth requirement metric within each grid cell. Preliminary encryption determination: Formula 2 in Indicates the first The overall encryption strength required for each grid cell; Weighting coefficients for balancing local risks and bandwidth requirements; The threat mapping value and the demand priority value are respectively in the th... The value of the region, for the first Each local grid cell is first mapped from the threat-demand matrix based on its coverage of high-risk frequency bands and task partitions. and Extract the corresponding row and column elements and perform a weighted summation. Record the result as the dynamic risk measure. ; and then from Extract the demand priority elements associated with the grid cell and sum them in a weighted manner to obtain the communication bandwidth demand metric. .

[0057] like If the preset threshold is exceeded, the grid cell will be split into several sub-cells, and a partially overlapping grid structure can be applied at the interface.

[0058] In this embodiment of the application, local encryption enables more precise phase shift and polarization angle control on smaller units, meeting the need for rapid switching when external interference increases or core communication needs suddenly arise.

[0059] In addition, for areas that have not experienced new threats or high bandwidth demands for an extended period, reducing the mesh subdivision level can reduce unnecessary computational and hardware scheduling burdens and free up resources for areas that require priority processing.

[0060] In the In each grid cell, let This represents the average combination of threat level and bandwidth availability over a period of time. The following formula is defined to determine whether mesh subdivision needs to be reduced: Formula 3 in They represent time. The first moment Regional threats and bandwidth requirements; Indicates the threshold balance parameter; Indicates the duration of observation.

[0061] For the first The determination of reduced mesh subdivision level constructed from individual mesh cells. Within the time interval... Top The average integral reflects the duration of the most recent observations for that grid. Whether the overall threat level and bandwidth demand within the region have remained low in the long term. If the value is positive and greater than the preset threshold, it indicates that there are no obvious new threats or high bandwidth demands in the area within the time window. Therefore, the algorithm determines that the subdivision level of the merged grid cell can be reduced. If this condition is not met, the original mesh granularity remains unchanged.

[0062] By merging excessively subdivided network cells, the grid is restored to its initial or more relaxed size.

[0063] In this embodiment of the application, by releasing the load on computing and control, more local optimization can be carried out for high-risk or high-priority areas.

[0064] In step S30, for the initial programmable hypersurface mesh configuration, the payoff of the macroscopic layer is iterated according to the global protection strategy game of the entire mesh and the local protection strategy game of the first risk mesh, and the weights of the global protection strategy game and the local protection strategy game are dynamically adjusted based on the vehicle dynamic state to determine the target programmable hypersurface mesh configuration.

[0065] For example, for the initial programmable hypersurface mesh configuration, the global protection strategy game of the entire mesh and the local protection strategy game of the first risk mesh can be iterated based on the macroscopic layer payoff. The weights of the global protection strategy game and the local protection strategy game can be dynamically adjusted based on the vehicle dynamic state. When the iteration converges, the first programmable hypersurface mesh configuration is determined. Then, the priority of the final shielding or projection of all meshes in the first programmable hypersurface mesh configuration is re-verified to form a list of globally executable equilibrium parameters to determine the second programmable hypersurface mesh configuration. Then, the second programmable hypersurface mesh configuration is used as the target programmable hypersurface mesh configuration.

[0066] Alternatively, the second programmable hypersurface mesh configuration can be verified a second time based on the real-time threat distribution and communication requirements of the target vehicle to determine the blocking metric for the first risk area or emergency communication channel. If the blocking metric does not exceed the preset threshold, the second programmable hypersurface mesh configuration is used as the target programmable hypersurface mesh configuration.

[0067] Alternatively, if the blocking metric exceeds a preset threshold, the grid of the first risk area is further subdivided, and based on the subdivided grid, the global protection strategy game of the entire grid and the local protection strategy game of the first risk grid are iterated according to the macro-level payoffs to obtain the target programmable hypersurface grid configuration.

[0068] In step S40, the target programmable metasurface mesh configuration can be mapped to each control subarray of the vehicle, and phase shift commands and polarization angle commands can be issued to control the tunable units in each mesh of the vehicle.

[0069] For example, the priority of the control subarray can be divided based on the urgency function first, and then, based on the priority, the synchronous configuration of each control subarray of the same priority can be performed by using a parallel trigger instruction set, and phase shift instructions and polarization angle instructions can be issued to control the tunable units in each grid of the vehicle.

[0070] This application's embodiments generate a comprehensive threat index and a comprehensive internal communication demand index based on the conflict between internal and external risks and communication needs of the vehicle. Based on these, the vehicle's programmable metasurface is adaptively meshed: high-risk areas have denser or overlapping meshes, while low-risk areas have merged meshes. Subsequently, the mesh configuration is iteratively optimized through a game-theoretic approach involving global and local protection strategies. The game weights are adjusted in real-time according to the vehicle's dynamic state. Finally, the optimized configuration is mapped to the control array, and the electromagnetic properties of the metasurface are dynamically controlled through phase shift and polarization angle commands. This achieves intelligent dynamic optimization of vehicle electromagnetic protection, balancing communication quality and anti-interference capabilities in complex environments, and improving vehicle communication security and electromagnetic interference protection efficiency.

[0071] Figure 2 This is a flowchart of a vehicle adaptive communication control method according to an embodiment of this application. The external risk interference frequency band is determined based on weighted aggregation data of multi-source sensor data of the target vehicle on a unified time axis, such as... Figure 2 As shown, the determination of the comprehensive threat index and the comprehensive internal communication demand index based on the conflict between the external risk interference frequency band and the bandwidth requirements corresponding to the internal communication task priority of the target vehicle may include the following steps: In step S101, the set of external risk interference frequency bands is determined based on the interference risk of each frequency band of the external channel of the target vehicle on the unified time axis.

[0072] In this step, the results of the purification and polymerization can be used as a basis. The system can quickly screen potential high-risk interference frequency bands through a critical interference prediction model, and dynamically adjust the judgment threshold when the driving environment changes, thereby improving response speed and reducing false alarm rate.

[0073] For example, the power spectrum information in the vehicle's external channel can be represented as ,in Indicates the discrete frequency component number. This indicates the total number of frequency components.

[0074] right Normalization process is performed to obtain This enables a unified measurement of the power spectrum under different driving speeds and channel conditions.

[0075] Determine the interference risk for each frequency component. : Formula 4 in Indicates the corresponding frequency The reference power spectrum; Represents the static safety factor; Indicates a scenario for vehicles The dynamic correction function; Indicates the vehicle's driving status; For frequency The results of the high-risk interference assessment. Indicates high-risk interference. Indicates the normal state.

[0076] Will Frequency components added to high-risk frequency band sets It then removes non-critical alarm information from the database and outputs the final critical interference frequency bands. (This is relevant to vehicle driving scenarios.) If a jump occurs, then according to The changes in the threshold are corrected online to shorten the detection lag time.

[0077] In step S102, based on the communication resource requirements of internal communication tasks on the unified time axis and the set of external risk interference frequency bands, a comprehensive evaluation is performed according to the threat and demand fusion function to obtain a comprehensive ranking result of the internal communication task priorities.

[0078] For example, the perception and prioritization of in-vehicle DistinctTask demands can be fused, based on the output high-risk frequency band set. With the interior of the vehicle, there are many types of Requirements are evaluated in parallel, and bandwidth and security are quantified and integrated on the same timeline to achieve a comprehensive ranking of the priorities of multiple tasks.

[0079] Collect data from the vehicle's internal network to meet different needs. , , where I represents the number of tasks. Each This includes specific resource requests regarding bandwidth and latency.

[0080] DistinctTask refers to a set of distinct task types within a vehicle, that is, a category of tasks that differ in their resource requirements such as bandwidth, latency, and security levels. Tasks such as autonomous driving control, in-vehicle communication, and in-vehicle entertainment can all be considered as different DistinctTasks.

[0081] make Indicates that for the first indivual Priority, based on The bandwidth, urgency, and time continuity factors are assessed to define an objective function that integrates threats and needs. : Formula 5 in Indicates the first The priority of each task; For the first The weight of each task priority; l is the number of tasks; Represents frequency Weight of the overall threat; The result represents the interference determination, where F represents the number of frequencies.

[0082] pass Internal demands and external interference are quantified and integrated to obtain a comprehensive ranking result. If internal bandwidth requests conflict with high-risk frequency bands, a penalty coefficient is applied to the corresponding tasks to avoid potential bandwidth loss or security risks. The resulting output... Priority table It is dynamically updated when the vehicle is traveling at high speed or when the base station is switching.

[0083] In step S103, based on the comprehensive ranking result and the external risk interference frequency band set, the comprehensive threat index and the comprehensive internal communication demand index are determined.

[0084] In a preferred embodiment, a threat-demand mapping matrix can be used to represent the overall threat index and the overall internal communication demand index, thereby significantly reducing the data dimensions required for information representation.

[0085] For example, it can be done in high-risk frequency band sets Priority of internal partition requirements Establish cross-domain mapping and output the threat-demand mapping matrix. Input for adaptive mesh partitioning and adversarial game optimization: Formula 6 in Indicates high-risk frequency band With internal tasks The threat-demand mapping value can be understood as a comprehensive threat index. Comprehensive indicators of communication demand The encoding of the mapping relationship can be found in step S10 above; Indicates the high-risk frequency band number. Indicates the internal task number.

[0086] Directly assess the intensity of external threats Prioritizing internal needs Through stacked integration coding The resulting integration matrix Preserving frequency interference characteristics and bandwidth urgency information allows for direct input into the adaptive mesh generation module.

[0087] Of course, it should be understood that the embodiments of this application may also directly use the threat comprehensive index and the internal communication demand comprehensive index, for example, represented by two separate matrices instead of merging them into one matrix. The embodiments of this specification do not limit this.

[0088] The embodiments of this application clearly present the correspondence between external threats and internal needs, providing a precise basis for decision-making in subsequent grid partitioning and protection strategy formulation, and avoiding the blind allocation of resources.

[0089] In addition, it is worthwhile to define prior indicators. Real-time driving conditions of the vehicle Together, they are used for subsequent dynamic mesh generation and adversarial game calculations, ensuring that more resources can be allocated to high-risk areas and critical tasks during the configuration of the hypermorphic surface of the vehicle window.

[0090] Values, prior indicators In this application embodiment, the aforementioned integration matrix is ​​used. List of high-risk frequency bands and internal partitioning requirements priority A unified abstraction, representing at time Comprehensive prior information on external threats and internal needs. This prior indicator is correlated with the vehicle's real-time operating conditions. Together, the input quantities of various risk measures, demand measures and weight functions in the adaptive grid partitioning and multi-level adversarial game steps appear as latent variables in the formula derivation of subsequent steps.

[0091] Optionally, the continuity of neighbor coupling and boundary division can be maintained. After the meshes of high-risk and low-risk areas have been initially adjusted, further attention should be paid to the signal coupling between neighboring meshes to avoid boundary breakage caused by excessive refinement or random division.

[0092] You can also define an adjacency matrix. When grid cells With unit When they are directly adjacent and have strong coupling ,otherwise Compatibility between meshes can be expressed in the following form: Formula 7 in Representation unit and Boundary continuity index; , They represent and State differences in phase shift control; Indicates the boundary continuity threshold.

[0093] like If the result is negative, it indicates that there is a significant conflict between the two in terms of phase shift control or polarization angle, and it is necessary to fine-tune or correct the shape of their segmentation boundary.

[0094] Will Mesh boundaries with values ​​less than zero are marked centrally, and continuity correction operations are performed on these adjacency relationships to ensure that the partition shape does not have broken zones or isolated meshes at the boundary between high-risk and low-risk areas, thereby reducing the complexity of adversarial games and synchronous scheduling.

[0095] It should be understood that the continuity correction operation, in its implementation, mainly involves making small-scale joint geometric and parametric adjustments to these marked adjacency boundaries. Specifically, it involves finding all boundaries in the adjacency matrix that satisfy... For each mesh pair, their common boundary curve is locked. The phase shift control values ​​and polarization angles of the meshes on both sides of this boundary are then weighted and averaged or limited at the current moment. Based on this, the control point coordinates of the boundary curve are slightly translated or smoothed so that the new boundary position satisfies the requirement that the differences in phase shift and polarization angle between the two meshes fall back within a preset threshold. The updated boundary and corresponding parameters are then written back into the mesh generation results, thus completing one continuous correction.

[0096] The embodiments of this application can avoid the occurrence of abrupt break zones or isolated grids at the boundary between high-risk and low-risk areas.

[0097] Figure 3 This is a flowchart of a vehicle adaptive communication control method provided in one embodiment of this application. Figure 3 As shown, before determining the comprehensive threat index and the comprehensive internal communication demand index based on the conflict between the external risk interference frequency bands of the target vehicle and the bandwidth requirements corresponding to the internal communication task priorities, the method may further include the following steps: In step S05, the distance and speed information matrix collected by the millimeter-wave radar of the target vehicle, the image feature vector collected by the camera of the target vehicle, and the signaling information and link quality information output by the target vehicle through V2X are aligned on a unified time axis. Then, the distance and speed information, the image feature vector, the signaling information and link quality information are weighted and fused according to their corresponding weights and data compensation amounts to obtain the weighted aggregated data. The data compensation amount of the target information is the data compensation of the target information by the target vehicle when accelerating and turning.

[0098] For example, the range and velocity information output by millimeter-wave radar can be represented as a matrix. The image feature vector output by the camera is denoted as... ,Will The output signaling information and link quality and quantity information are denoted as follows: ,in Represents a time index. This is achieved through a unified time marker. Below Alignment is performed to eliminate the time difference in data acquisition when the vehicle is at high speed and turning.

[0099] The aligned multi-source data is weighted using a matrix. Perform unified aggregation and define the weighted time. aggregation results .make Indicates the data source number. hour ,when hour ,when hour Define the correction function. This indicates the data source during vehicle acceleration and cornering. The amount of compensation, Indicates the number of data sources: Formula 8 in Indicates the first The weight of each data source; Indicates the first Output from one data source; Indicates targeting the data source The correction amount.

[0100] against After introducing an adaptive filter to generate purification The coefficients of the adaptive filter are driven by both vehicle speed and direction, dynamically adjusting to address data distortion during high speeds or sharp turns, and the output... It exhibits consistent and stable spatiotemporal characteristics under different driving conditions.

[0101] The embodiments of this application fully correct the distortion of sensor data in high-speed dynamic scenarios, making the identification of subsequent external risks and internal needs more reliable, and laying a solid data foundation for the formulation of overall control strategies.

[0102] Figure 4 This is a flowchart of a vehicle adaptive communication control method provided in one embodiment of this application. The global protection strategy game is used to determine mesh protection at the macro level, the local protection strategy game is used to optimize protection for a first-risk mesh, and the macro-level payoff is used to measure the overall payoff of mesh shielding or windowing on a unified time axis; such as Figure 4 As shown, the process of determining the target programmable hypersurface mesh configuration by iterating through a global protection strategy game of the entire mesh and a local protection strategy game of the first risk mesh based on the macroscopic layer payoffs, and dynamically adjusting the weights of the global protection strategy game and the local protection strategy game based on the vehicle's dynamic state, may include the following steps: In step S301a, for the initial programmable hypersurface mesh configuration, the payoff of the macroscopic layer is iterated according to the global protection strategy game of the entire mesh and the local protection strategy game of the first risk mesh, and the weights of the global protection strategy game and the local protection strategy game are dynamically adjusted based on the vehicle dynamic state, and the first programmable hypersurface mesh configuration is determined when the iteration converges.

[0103] For example, after completing the large-scale meshing of the programmable metasurface, the confrontation process between the "defender" (the overall strategy of all mesh cells) and the "attacker" (the global potential threat) can be simulated at the macroscopic level to quickly evaluate the attacker's overall suppression strategy in different directions and frequency bands.

[0104] We construct a unified payoff function for macro-level adversarial games, derive preliminary defense strategies, and provide directional guidance for subsequent actions.

[0105] make To indicate the number of grid cells, let This indicates the total number of threat types and interference sources identified. This indicates the defender's macro-level protection configuration in each grid, making This indicates the attacker's offensive strategy under different threat types.

[0106] Define the defender's payoff function at the macro level. This includes a double summation term between the mesh and the threat, as well as a global time-domain integral term, used to comprehensively measure the benefits of shielding and windowing at different times: Formula 9 in Indicates the grid number, Indicates the threat type number, ; Indicates the first Grid in Strategy The following are the types of threats The resulting protective benefits; This indicates the cost of the disruption caused by opening a window under the same circumstances; This represents the balance coefficient between local benefits and local costs at a static level. Indicates time The effectiveness of global shielding in evolution; Indicates time The overall offensive intensity of the evolution; , This represents the time-weighted coefficient for the benefits of global shielding and the intensity of the attack; This represents the total duration of the game when examined at the macro level.

[0107] The unified revenue function It is the objective function of macro-level adversarial games, used to simultaneously measure the performance of a given defensive strategy. With offensive strategy Below, we analyze the protection benefits, vulnerability costs, overall shielding effectiveness, and attack strength of each grid against various threats. This is achieved through analysis of... By solving minimax or other game theory problems, we can obtain the equilibrium strategy at the macroscopic level. and In subsequent steps, when conducting localized refined game theory on high-risk or high-demand grids, the initial grid configuration given by this macro-equilibrium strategy is used as a basis for further refined iterations. Therefore, although the symbols... Although not explicitly stated again later, the solution result is already fixed in [the text]. The value is used in subsequent steps.

[0108] Global shielding effectiveness Given a macro-defense strategy This is a quantitative result of the overall shielding capability of all grids against high-risk frequency bands outside the vehicle under the current configuration. The calculation first utilizes a set of high-risk frequency bands. and external power spectrum information Then, combining the phase shift, polarization angle, and shielding / windowing configuration determined for each grid, the attenuation ratio of these configurations to the incident interference power in each high-risk frequency band is calculated. A weighted average is then taken of all high-risk frequency bands and all grids according to their area and importance to obtain the attenuation ratio at time [time value missing]. global shielding effectiveness .

[0109] Overall offensive strength This refers to the current offensive strategy This involves quantifying the overall suppression capability across all threat types and interference sources. The calculation is based on external threat assessment results and a set of high-risk frequency bands, and is performed for each threat type. Intensity, number of incident directions, and power spectrum in high-risk frequency bands By performing weighted summation, the time-series of this type of threat can be obtained. The intensity of the attack, and then according to the attack strategy The overall global offensive strength is obtained by weighting and summing the adoption levels of different threat types. .

[0110] After obtaining the initial strategy for macro-game, focus on high-priority communication areas and high-threat areas, refine the game model to perform more precise iterative optimization of the shielding-transmission ratio for handling single grids or adjacent grids, and highlight the response to sudden interference hotspots.

[0111] make This indicates a subset of high-risk or high-demand grids (first-risk grids) that requires priority attention. For each The defensive strategy is subdivided into The attacking strategy is subdivided into By repeatedly calculating the respective payoffs during local game scenarios and updating the strategy accordingly.

[0112] The cumulative payoff for each local game round is expressed as a double integral, focusing on measuring the matching degree between high-frequency disturbances and polarization angle control. A local cumulative payoff function is defined. :

[0113] Formula 10 in Indicates the first Mesh coordinates in two-dimensional space The corresponding projection area above; This indicates that, given a local strategy and scenario Contribution to protection during the time; This represents the transmission cost under the same conditions; , This represents the weighting coefficients of protection and cost at the local layer; Indicates the coordinates of the car window Dynamic driving environment parameters at that time.

[0114] Local cumulative payoff function It is the objective function in the local adversarial game phase, used to quantify the defensive strategy in a given local environment. With offensive strategy Next, the Each key grid is located in its projection area. The overall benefit within. The first part of the integrand and The relevant terms characterize the grid's contribution to suppressing high-frequency interference; the second part is related to... The related terms characterize the cost incurred to maintain necessary transmission under the same strategy, with two weighting coefficients. This is used to balance the transmission loss caused by high-frequency interference suppression and polarization angle control. In the local game iteration, with To optimize the objective, by... The update brings the function to a local optimum, thus determining the critical grid in the shielding. Refined configuration of transmission ratio and polarization control. (While this will not be explicitly stated in subsequent steps...) The symbol, but the local equilibrium strategy obtained in this step is... It will directly proceed to the subsequent dynamic weight update and local-global mapping verification. The solution of this benefit function will continue to participate in the subsequent processing in the form of a local optimal strategy.

[0115] During the iterative process of macro and local game, vehicle speed, route, and threat type will change. The strategy weights of the attacker and defender are adjusted in real time to prevent game lag in sudden scenarios. This sub-step proposes a dynamic weight update mechanism to enable the game model to maintain rapid response capability when the environment changes abruptly.

[0116] make Let represent a normalized vector containing key attributes of vehicle speed, turning radius, and channel switching, and let Indicates according to different times Factors that modulate threat and defense strategies.

[0117] For the macro level and local layers And other related parameters, dynamically updated : Formula 11 in This represents the updated game equilibrium coefficient; This represents the adjustment factor based on vehicle driving attributes; This indicates the expression in a multi-layered nested polynomial. The scaling factor; This indicates the number of nested summations and exponentiation levels.

[0118] In this part, Defined as a normalized vector composed of vehicle speed, turning radius, and key channel switching attributes. It is a factor that adjusts the game weights based on the current driving state; the function This factor is then mapped to the updated equilibrium coefficients for various games. Specifically, It is a weighting coefficient in the macro-level benefit function used to balance the benefits of local protection with the costs of opening windows; It is the effectiveness of global shielding in the macroscopic time integral term. With overall offensive intensity Time weighting factor; These are the weighting coefficients in the local cumulative benefit function used to balance the contribution of high-frequency interference suppression with the transmission cost. These coefficients are constants in the static case, but through... Received This is the new value that is dynamically adjusted according to the vehicle's driving status. In the formula... This indicates that each term of a multiple nested polynomial affects the adjustment factor. The scaling factor is a calibration parameter given during the design phase; These represent the number of nested summations and exponentiations, respectively, which are used to control the order and flexibility of the nonlinear mapping, so that the game weights can be dynamically updated with appropriate amplitude and curve shape under different vehicle speeds, turning radii and channel switching conditions.

[0119] After dynamically adjusting the weight coefficients, the first programmable hypersurface mesh configuration is determined during iterative convergence.

[0120] In step S302a, the priority of the final masking or projection of all meshes in the first programmable metasurface mesh configuration is re-verified to form a globally executable list of equilibrium parameters to determine the second programmable metasurface mesh configuration.

[0121] It should be understood that when the benefits of the macroscopic layer are used to measure the overall benefits of mesh shielding on a unified time axis, the priority of the final shielding of all meshes in the first programmable metasurface mesh configuration can be re-verified; when the benefits of the macroscopic layer are used to measure the overall benefits of mesh windowing on a unified time axis, the priority of the final projection of all meshes in the first programmable metasurface mesh configuration can be re-verified. The priorities of final shielding or projection mentioned in other embodiments of this application are similar and will not be repeated here.

[0122] For example, after the repeated iterations of the macroscopic and local game converge, the final shielding or transmission priority of all grid cells is re-verified to form a globally executable list of equilibrium parameters. A local-global mapping kernel is constructed to check the protection targets under all grids and determine the final equilibrium solution of the multi-level game to determine the grid configuration of the second programmable hypersurface.

[0123] Define the overall equilibrium parameter vector of the defending side. The overall equilibrium parameter vector of the attacking side Furthermore, a block matrix approach is introduced to verify the consistency between each sub-grid and the global policy. Let the following expression represent the grid. With threats Equilibrium vector matching degree : Formula 12 in Indicates to Grid and The final strategy mapping output for type-specific threats; This indicates a reference strategy based on historical scenarios or security benchmarks. The L2 norm operation of vectors is represented. The square of the L2 norm operation of a vector; if If the value is less than the threshold, it indicates that the grid has reached a stable equilibrium after multi-level game, and the priority of shielding or transmission accurately meets the needs of confrontation.

[0124] The equilibrium vector matching degree of all grids is summarized. If all meet the threshold requirements, a list of multi-level adversarial game equilibrium point parameters is output, including the shielding and transmission priorities of each grid cell, and the configuration suggestions for the corresponding phase shift and polarization angle.

[0125] The equilibrium parameters and equilibrium parameter set here refer to the overall equilibrium strategy parameter vector obtained after the convergence of the multi-level adversarial game. , The specific values ​​for each grid cell correspond to the final shielding and transmission priorities, as well as control variables such as phase shift and polarization angle configurations that match these priorities. Summarizing these equilibrium values ​​for all grid cells constitutes the multi-level adversarial game equilibrium parameter set, which serves as the second programmable hypersurface grid configuration.

[0126] In step S303a, the second programmable metasurface mesh configuration is used as the target programmable metasurface mesh configuration.

[0127] For example, after summarizing the equilibrium points of the multi-level game, it can be cross-checked with the scenario-based adaptive grid partitioning scheme to avoid the contradiction that the macro defense strategy is not suitable for the local grid refinement conditions, and ultimately achieve a robust balance between external attacks and internal communication needs.

[0128] The boundary coordinates, risk coefficients, and nearest-neighbor coupling relationships of each grid cell are checked to see if there is any deviation from the game equilibrium parameters output in this step. If the deviation exceeds the preset threshold, the process is to revert to the local game of the previous iteration for minor adjustments, and then the obtained second programmable hypersurface grid configuration is used as the target programmable hypersurface grid configuration.

[0129] The embodiments of this application, through layered game theory and dynamic weight adjustment, take into account both the global protection effect and the local optimization accuracy, making the grid configuration more in line with actual needs and improving the dynamic adaptability of the system.

[0130] Figure 5 This is a flowchart of a vehicle adaptive communication control method provided in one embodiment of this application. The global protection strategy game is used to determine mesh protection at the macro level, the local protection strategy game is used to optimize protection for a first-risk mesh, and the macro-level payoff is used to measure the overall payoff of mesh shielding or windowing on a unified time axis; such as Figure 5 As shown, the process of determining the target programmable hypersurface mesh configuration by iterating through a global protection strategy game of the entire mesh and a local protection strategy game of the first risk mesh based on the macroscopic layer payoffs, and dynamically adjusting the weights of the global protection strategy game and the local protection strategy game based on the vehicle's dynamic state, may include the following steps: In step S301b, for the initial programmable hypersurface mesh configuration, the payoff of the macroscopic layer is iterated according to the global protection strategy game of the entire mesh and the local protection strategy game of the first risk mesh. The weights of the global protection strategy game and the weights of the local protection strategy game are dynamically adjusted based on the vehicle dynamic state. The first programmable hypersurface mesh configuration is determined when the iteration converges.

[0131] For example, the implementation of this step can be referred to step S301a, which will not be repeated here.

[0132] In step S302b, the priority of the final masking or projection of all meshes in the first programmable metasurface mesh configuration is verified to form a globally executable list of equalization parameters to determine the second programmable metasurface mesh configuration.

[0133] For example, the implementation of this step can be referred to step S302a, which will not be repeated here.

[0134] In step S303b, the configuration of the second programmable metasurface mesh is verified a second time based on the real-time threat distribution and communication requirements of the target vehicle to determine the blocking metric for the first risk area or emergency communication channel.

[0135] For example, the system can be re-examined based on the real-time threat distribution and communication needs of vehicles to determine whether there are high-risk areas (first risk areas) or blocked emergency communication channels. If the indicators exceed the limits, the grid will be re-divided.

[0136] make Indicates frequency The intensity of external threats, ,make Indicates the first kind The intensity of communication resource occupancy, .

[0137] Within each time period, the current data is compared with the archived information from the previous time period.

[0138] Triggering determination function Used to comprehensively measure the fluctuation range of threats and communication needs, if Exceeding a given threshold If this occurs, it is considered that an extreme rise in temperature and communication disruption have occurred in a certain area. Formula 13 in Indicates time The intensity of historical threats at any given moment; Indicates time Historical communication usage at any given moment; is the detection interval; max is the maximum value.

[0139] In step S304b, if the blocking metric does not exceed a preset threshold, the second programmable metasurface mesh configuration is used as the target programmable metasurface mesh configuration; or, if the blocking metric exceeds the preset threshold, the mesh of the first risk region is subdivided a second time, and based on the subdivided mesh, the target programmable metasurface mesh configuration is obtained by iteratively playing the global protection strategy game of the entire mesh and the local protection strategy game of the first risk mesh according to the macro-level payoff.

[0140] For example, if Then the second programmable metasurface mesh configuration is used as the target programmable metasurface mesh configuration; if Then, the moment and the corresponding grid region are taken as the trigger point for grid re-division. The grid of the first risk region is subdivided a second time. Based on the subdivided grid, the global protection strategy game of the whole grid and the local protection strategy game of the first risk grid are iterated according to the macro-level benefits to obtain the target programmable hypersurface grid configuration.

[0141] Once a high-risk area or critical communication disruption is confirmed, this sub-step further subdivides the grid cells in that area, and if necessary, reshapes the original boundaries to allow for greater scheduling flexibility in both protection and transmission.

[0142] make This is the set of grid cell indices that require secondary repartitioning, where This indicates the total number of current grid cells. For each cell... Record the original boundary function in the mesh skeleton. , Represents the parametric coordinates along the boundary.

[0143] To further enhance the detail of local areas, a correction term is introduced. This represents the boundary compensation amount used to compensate for external interference or communication deviations, and a new boundary function is constructed. : Formula 14 in Indicates the starting position of the curve parameters; Indicates in the parameter The local boundary correction function is introduced; by adding partial derivatives and integrals to the original template, the local boundary is guaranteed not to break discretely, while improving the flexibility of the mesh element after refinement.

[0144] We then perform more refined adversarial game calculations on the newly added subgrids to find a shield-transmission equilibrium strategy at the new fine-grained level.

[0145] make This represents the set of newly added subgrids generated after secondary subdivision, with each grid representing a subgrid within it. The updated strategy needs to be output. and respond to the attacking threat Engage in multiple rounds of game theory.

[0146] To characterize the differences between jamming and communication control at a more precise spatial scale, a local defense payoff function in the form of a triple integral is introduced as follows. : Formula 15 in Indicates the first Subgrids in 3D coordinates The corresponding control body; It indicates the contribution to security protection achieved under a specified offensive and defensive strategy; This represents the cost of communication transmission under the same strategy combination. , This represents the weighting coefficient used to measure the protection-to-transmission ratio during optimization; the triple integral facilitates fine-grained analysis of the deflection and polarization effects of the window surface in a three-dimensional environment, and determines a new local shielding-transmission balance after repeated iterations.

[0147] Local defense payoff function Used for a given local defense strategy in the subgrid fine-grained adversarial game phase. and corresponding threats Below, the sub-mesh is shielded. The overall effect of the transmission configuration is measured. Specifically, the function is applied to the submesh volume. Top Triple integration will be performed to assess the contribution of security protection. Costs of communication transmission By accumulating spatially, the net protection benefit corresponding to that subgrid is obtained.

[0148] In local multi-round adversarial games, with As an evaluation indicator, (in the established) (The following) iteratively updates the function until it reaches its maximum value; when all newly added sub-grids... When all converge, the shielding at the current fine-grained level is obtained. A transmission equalization strategy is employed, and these equalization results are output as the final local configuration of the region to obtain the target programmable metasurface mesh configuration.

[0149] The embodiments of this application realize dynamic optimization of grid configuration, which can quickly respond to sudden changes in threats and requirements, and significantly improve the robustness of the system in dealing with complex scenarios.

[0150] In one possible implementation, after the local grid is further subdivided and multiple rounds of game play are completed, the coupling relationship between the newly added subgrid and the original adjacent grids can be further coordinated to ensure the continuity of the global strategy.

[0151] make Represents the adjacency matrix, if the grid With grid When they have a common boundary and potential coupling, ,otherwise After secondary subdivision, newly added subgrids need to be re-aggregated into the adjacency matrix.

[0152] When grid With grid When there is strong coupling, the following formula is defined to quantify the continuity between the two in instruction configuration. : Formula 16 in Represents a grid With grid A shared set of subarray indices; express Mesh in subarray The phase shift or polarization vector on; express Mesh in subarray The phase shift or polarization vector on; express In game theory strategies, grids are a certain Order arrangement parameters; express In game theory strategies, grids are a certain Order arrangement parameters; Represents a subarray set. Let Q represent the square of the norm, and let Q represent the total number of encoded parameters participating in the adjacent grid consistency check, i.e., the number of grids in the game strategy set. The length or highest order of this string of encoded parameters. Product term. It's right here. Compare the grid one by one along each of the coding parameter dimensions. With grid The difference is used to comprehensively measure the continuity between the two in terms of configurations such as phase shift and polarization angle.

[0153] like If the preset limit is exceeded, then the grid will be... With grid The shared parameters are merged for calculation to eliminate conflicts.

[0154] This application embodiment ensures the continuity of the global strategy by further coordinating the coupling relationship between the newly added sub-grid and the original adjacent grids.

[0155] Figure 6 This is a flowchart of a vehicle adaptive communication control method provided in one embodiment of this application. Figure 6 As shown, the process of mapping the target programmable metasurface mesh configuration to each control subarray of the vehicle and issuing phase shift commands and polarization angle commands to control the tunable units in each mesh of the vehicle may include the following steps: In step S401, the priority of the control subarray is divided based on the urgency function.

[0156] For example, by combining threat and communication indicators in the current driving scenario, it can be determined which subarrays are in a high-risk or urgent communication need state. This sub-step scans all subarrays by constructing an urgency function, thereby including urgent or high-threat areas in the priority partition.

[0157] make Subarray In frequency components The strength of the threat received above makes Subarray For the first Bandwidth requirement weights for different types of communication requests. , , .

[0158] The output of the local game phase can provide rapid data support for the aforementioned threats and needs.

[0159] Define urgency function Quantitative First Subarray at time The combination of high risks and high bandwidth requirements, if If the given threshold is exceeded, the subarray is determined to enter the priority partition: Formula 17 in , These represent the balance coefficients between external threats and bandwidth requirements when determining the subarray. If... If the value exceeds the threshold, the subarray will be processed first, and it will be given priority in execution when instructions are issued and configurations are updated.

[0160] After identifying which subarrays are assigned to priority partitions, a distributed parallel instruction mode replaces the traditional sequential loading, shortening the execution latency of the control bus and ensuring that multiple subarrays can switch collaboratively or operate together within a microsecond timescale.

[0161] make Indicates that for O The configuration instruction set for each subarray, wherein each This includes information such as phase shift values, polarization angles, and shielding-transmission options. To simultaneously activate distributed delivery, it is configured on the vehicle control bus for each... Assign a parallel trigger flag.

[0162] Define the total delay cost function in parallel mode. This value is used to evaluate the overall efficiency of a centralized configuration distribution. The smaller the value after equalization, the better the parallel control effect. Formula 18 in This indicates the number of multiple instruction channels that may exist in a distributed delivery system. Indicates the first Subarray in command channel The resource allocation ratio below; Indicates the instruction scheduling weight; Indicates the length of the execution path; , They represent the first on the global control plane, respectively. The weight and load of each key synchronization instruction; This captures the synergistic effects of multiple critical instructions being issued in a single parallel process.

[0163] In step S402, based on the priority, the synchronous configuration of each control subarray of the same priority is performed by a parallel trigger instruction set, and phase shift instructions and polarization angle instructions are issued to control the tunable units in each grid of the vehicle.

[0164] For example, after the parallel instruction execution order, multi-point power consumption monitoring and temporary detour strategy have been verified to be feasible, these operation instructions are summarized and encapsulated on the control bus to generate a "subarray quick-match instruction set", which provides the final basis for the dynamic scheduling of the programmable metasurface of the window, and issues phase shift instructions and polarization angle instructions to control the tunable units in each grid of the vehicle.

[0165] make The mixed instruction matrix represents the global subarray configuration, with matrix row numbers. Corresponding subarray number, column number This represents different control elements, such as phase shift value, polarization angle, windowing, or shielding coefficient. This is achieved by integrating the instructions for each subarray into a single matrix. Achieve one-time parallel deployment on the hardware bus: Formula 19 in Indicates for subarray The Each control indicator value.

[0166] This sub-step integrates instruction issuance order, multi-point sensor monitoring, and hardware fault tolerance schemes under the distributed parallel management approach, ultimately generating an instruction set capable of scheduling all sub-arrays with a single click. This model effectively connects the dynamic game strategy of the programmable metasurface of a car window with distributed hardware execution.

[0167] This application's embodiments overcome the latency limitations of traditional sequential loading, reduce the overall time consumption of instruction transmission, ensure rapid response in high-priority areas, and meet the real-time control requirements of vehicles traveling at high speeds.

[0168] Figure 7 This is a flowchart of a vehicle adaptive communication control method provided in one embodiment of this application. Figure 7 As shown, the method may further include the following steps: In step S50, the power consumption and temperature of each control subarray are monitored in real time, and in the event of an anomaly in the primary control subarray, a fault-tolerant switchover of the backup subarray is performed.

[0169] For example, in the distributed parallel control mode, in order to prevent instantaneous power overload or "response lag" caused by rapid switching of subarrays, power consumption and configuration execution efficiency are captured in real time by multiple sensors of the subarray, and temporary detour and backup subarray takeover strategies are introduced to enhance system robustness.

[0170] make express Real-time power consumption and response state vectors of each subarray, each It consists of data such as current, voltage, and temperature collected by multiple sensors, used to determine whether the subarray is under overload or has signs of impending failure.

[0171] Constructing system reliability measurement Indicates at time The overall availability is monitored. If the availability falls below a certain threshold, a bypass or backup subarray takeover must be initiated to perform a fault-tolerant switchover of the backup subarray. Formula 20 in Indicates in subarray The reliability function under changes in sensor data The gradient; Indicates in subarray Global coupling penalty caused by power fluctuations or line mismatches occurring at the layer; if If the value drops below the safety line, it will trigger a local game strategy to switch the subarray's bypass shielding or call a backup subarray to take over.

[0172] Summation terms use subscripts right Integrating each subarray individually yields the reliability contribution of each subarray under normal operating conditions. The product term is indicated by a subscript. Analyze the cells in these subarrays that exhibit power fluctuations or line mismatches, and assign a penalty factor to each corresponding subarray. . From The set of subarray indices selected from those that have experienced anomalies generally includes: .

[0173] The embodiments of this application ensure the continuity of the control link, avoid the failure of the overall protection or communication function due to the abnormality of a single subarray, and significantly improve the operational reliability and stability of the entire system.

[0174] Figure 8 This is a flowchart of a vehicle adaptive communication control method provided in one embodiment of this application. Figure 8 As shown, the method may further include the following steps: In step S60, when extreme electromagnetic interference or communication interruption is detected, the game iteration process is skipped, and a global forced shielding mode is enabled to prioritize the protection of critical communications and vehicle safety.

[0175] For example, after receiving the instruction set output from the preceding steps, voltage tuning and temperature drift compensation can be performed on all tunable units to eliminate phase shift deviations caused by temperature and power fluctuations in the vehicle's driving environment, ensuring the accuracy and stability of subsequent execution. After tuning compensation, phase shift switching and polarization control are performed first to address grid areas with high threats or urgent communication needs, ensuring that external interference is shielded in a timely manner or that important bandwidth is reserved first, enabling the vehicle to maintain a high level of security for priority protection and core communication during complex driving processes. The phase shift switching of other grid areas is executed in parallel through synchronous clock pulses triggered by parallel clocks, allowing all subarrays to complete electromagnetic state updates at the same time, reducing the latency accumulation caused by sequential loading, and meeting the timeliness requirements for dynamic window control when the vehicle is traveling at high speed. For the call to the reserve strategy in extreme emergency scenarios, when the autonomous driving system detects extreme environments (such as strong electromagnetic pulse interference or attacks), the backup reserve strategy is immediately triggered, and an emergency shielding mode is adopted in critical areas, eliminating the long process of waiting for global game updates and ensuring passenger safety and core communication as quickly as possible. For the final parameter writing and dynamic electromagnetic protection implementation, after completing the key grid phase shift switching, parallel execution and emergency retention strategies, all tuning parameters that match the game optimization and grid partitioning results are written into the tunable metasurface hardware to form a "regional differentiated" electromagnetic shielding and transmission effect. Thus, the vehicle can achieve low latency, high security electromagnetic protection and efficient communication in high-speed driving scenarios.

[0176] This application prioritizes ensuring the smooth operation of critical vehicle communication links and vehicle safety, without waiting for global policy updates. It mitigates extreme risks with the shortest response time, providing reliable protection for the safe operation and core communication of vehicles in sudden extreme scenarios.

[0177] Figure 9 This is a block diagram of a vehicle adaptive communication control device according to an embodiment of this application. Figure 9 As shown in the figure, this application provides a vehicle adaptive communication control device 900, which may include the following modules: The determination module 910 is used to determine the comprehensive threat index and the comprehensive internal communication requirement index based on the conflict between the external risk interference frequency band and the bandwidth requirements corresponding to the internal communication task priority of the target vehicle.

[0178] The partitioning module 920 is used to partition the programmable metasurface of the target vehicle into a mesh based on the comprehensive threat index, the comprehensive internal communication requirement index, and the window geometry parameters of the target vehicle. The meshes belonging to the first risk area are locally densified or overlapped, and the meshes belonging to the second risk area are merged to obtain an initial programmable metasurface mesh configuration, wherein the risk level or priority of the first risk area is higher than that of the second risk area.

[0179] The game module 930 is used to iterate the global protection strategy game of the entire mesh and the local protection strategy game of the first risk mesh based on the payoff of the macro layer for the initial programmable hypersurface mesh configuration, and dynamically adjust the weights of the global protection strategy game and the local protection strategy game based on the vehicle dynamic state to determine the target programmable hypersurface mesh configuration.

[0180] The control module 940 is used to map the target programmable metasurface mesh configuration to each control subarray of the vehicle, and to issue phase shift commands and polarization angle commands to control the tunable units in each mesh of the vehicle.

[0181] In one possible implementation, the vehicle adaptive communication control device 900 further includes a fusion module for: Before determining the comprehensive threat index and comprehensive internal communication demand index based on the conflict between the external risk interference frequency band and the bandwidth requirements corresponding to the internal communication task priority of the target vehicle, the range and speed information matrix collected by the millimeter-wave radar of the target vehicle, the image feature vector collected by the camera of the target vehicle, and the signaling information and link quality information output by the target vehicle through V2X are aligned on a unified time axis. Then, the range and speed information, the image feature vector, the signaling information and the link quality information are weighted and fused according to the weights and data compensation amounts corresponding to them to obtain the weighted aggregated data. The data compensation amount of the target information is the data compensation of the target information by the target vehicle when accelerating and turning.

[0182] In one possible implementation, the determining module 910 is further configured to: The set of external risk interference frequency bands is determined based on the interference risk of each frequency band of the external channel of the target vehicle on the unified time axis; Based on the communication resource requirements of internal communication tasks on the unified time axis and the set of external risk interference frequency bands, a comprehensive evaluation is performed according to the threat and demand fusion function to obtain a comprehensive ranking result of the internal communication task priorities. Based on the comprehensive ranking results and the external risk interference frequency band set, the comprehensive threat index and the comprehensive internal communication demand index are determined.

[0183] In one possible implementation, the game-playing module 930 is further configured to: For the initial programmable hypersurface mesh configuration, the payoff of the macroscopic layer is iterated according to the global protection strategy game of the whole mesh and the local protection strategy game of the first risk mesh. The weights of the global protection strategy game and the weights of the local protection strategy game are dynamically adjusted based on the vehicle dynamic state. The first programmable hypersurface mesh configuration is determined when the iteration converges. The priority of the final masking or projection of all meshes in the first programmable metasurface mesh configuration is re-verified to form a globally executable list of equilibrium parameters to determine the second programmable metasurface mesh configuration. The second programmable metasurface mesh configuration is used as the target programmable metasurface mesh configuration.

[0184] In one possible implementation, the game-playing module 930 is further configured to: For the initial programmable hypersurface mesh configuration, the payoff of the macroscopic layer is iterated according to the global protection strategy game of the whole mesh and the local protection strategy game of the first risk mesh. The weights of the global protection strategy game and the weights of the local protection strategy game are dynamically adjusted based on the vehicle dynamic state. The first programmable hypersurface mesh configuration is determined when the iteration converges. The priority of the final masking or projection of all meshes in the first programmable metasurface mesh configuration is verified to form a globally executable list of equalization parameters to determine the second programmable metasurface mesh configuration. The second programmable metasurface mesh configuration is further verified based on the real-time threat distribution and communication requirements of the target vehicle to determine the blocking metric for the first risk area or emergency communication channel. If the blocking metric does not exceed a preset threshold, then the second programmable metasurface mesh configuration is used as the target programmable metasurface mesh configuration, or... If the blocking metric exceeds the preset threshold, the grid of the first risk area is further subdivided, and based on the subdivided grid, the global protection strategy game of the entire grid and the local protection strategy game of the first risk grid are iterated according to the macro-level payoffs to obtain the target programmable metasurface grid configuration.

[0185] In one possible implementation, the control module 940 is further configured to: The priority of the control subarray is determined based on the urgency function; Based on the priority, the synchronous configuration of each control subarray of the same priority is performed by parallel triggering instruction set, and phase shift instructions and polarization angle instructions are issued to control the tunable units in each grid of the vehicle.

[0186] In one possible implementation, the vehicle adaptive communication control device 900 further includes a switching module for: Real-time monitoring of power consumption and temperature of each control subarray; fault-tolerant switching of backup subarray in case of failure of primary control subarray.

[0187] In one possible implementation, the vehicle adaptive communication control device 900 further includes a shielding module for: Upon detecting extreme electromagnetic interference or communication interruption, the game iteration process is skipped, and a global forced shielding mode is activated to prioritize the protection of critical communications and vehicle safety.

[0188] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0189] This application embodiment achieves precise electromagnetic protection and efficient communication in high-speed vehicle driving scenarios through the coordinated operation of a determination module, a partitioning module, a game theory module, and a control module. The determination module first collects multi-source sensor data from the vehicle, including millimeter-wave radar, cameras, and V2X communication signaling information. It then aligns, weights, fuses, and compensates the data on a unified timeline to obtain accurate weighted aggregated data. This data is used to identify external risk interference frequency bands and internal communication task priorities, and to construct a comprehensive threat index and a comprehensive internal communication demand index based on their conflict. The partitioning module, based on these indicators and the vehicle's window geometry parameters, performs mesh partitioning on the programmable metasurface. The high-risk first-risk area mesh is locally densified or overlapped, while the low-risk second-risk area mesh is merged to form an initial mesh configuration. Simultaneously, the mesh boundary continuity is maintained to avoid partition mismatch. The game theory module focuses on macro-level payoffs, iteratively calculating the global protection strategy across the entire grid and the local protection strategy for the first-risk grid based on the initial grid configuration. During this process, the weights of both game types are adjusted in real-time according to dynamic states such as vehicle speed and steering, ensuring the strategy adapts to changing operating conditions. After iterative convergence, the target programmable hypersurface grid configuration is formed. The control module maps the target grid configuration to each control subarray of the vehicle, issuing phase shift and polarization angle commands in a distributed parallel mode to achieve precise control of the tunable units in each grid. The seamless integration of all modules enables a closed-loop operation of interference perception, grid adaptation, strategy optimization, and execution control, effectively improving the targeting of vehicle electromagnetic protection and communication stability, and adapting to the complex requirements of high-speed dynamic driving scenarios.

[0190] Figure 10 This is a block diagram of an electronic device provided in one embodiment of this application. For example... Figure 10 As shown, the electronic device 1000 may include: a processor 1001 and a memory 1002. The electronic device 1000 may also include one or more of a multimedia component 1003, an input / output (I / O) interface 1004, and a communication component 1005.

[0191] The processor 1001 controls the overall operation of the electronic device 1000 to complete all or part of the steps in the aforementioned vehicle adaptive communication control method. The memory 1002 stores various types of data to support the operation of the electronic device 1000. This data may include, for example, instructions for any application or method operating on the electronic device 1000, and application-related data such as contact data, sent and received messages, images, audio, video, etc. The memory 1002 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. Multimedia component 1003 may include a screen and an audio component. The screen may be, for example, a touchscreen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signals may be further stored in memory 1002 or transmitted via communication component 1005. The audio component also includes at least one speaker for outputting audio signals. I / O interface 1004 provides an interface between processor 1001 and other interface modules, such as a keyboard, mouse, buttons, etc. These buttons may be virtual or physical buttons. Communication component 1005 is used for wired or wireless communication between the electronic device 1000 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G, 4G, NB-IoT, eMTC, or other 5G technologies, or combinations thereof, is not limited here. Therefore, the corresponding communication component 1005 may include: a Wi-Fi module, a Bluetooth module, an NFC module, etc.

[0192] In an exemplary embodiment, the electronic device 1000 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the vehicle adaptive communication control method described above.

[0193] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, which, when executed by a processor, implement the steps of the vehicle adaptive communication control method described above. For example, the computer-readable storage medium may be the memory 1002 including the program instructions described above, which may be executed by the processor 1001 of the electronic device 1000 to complete the vehicle adaptive communication control method described above.

[0194] In another exemplary embodiment, a computer program product is also provided, comprising a computer program executable by a programmable device, the computer program having a code portion for performing the above-described vehicle adaptive communication control method when executed by the programmable device.

[0195] The preferred embodiments of this application have been described in detail above with reference to the accompanying drawings. However, this application is not limited to the specific details of the above embodiments. Within the scope of the technical concept of this application, various simple modifications can be made to the technical solution of this application, and these simple modifications all fall within the protection scope of this application.

[0196] It should also be noted that the various specific technical features described in the above embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, this application will not describe the various possible combinations separately.

[0197] Furthermore, various different implementations of this application can be combined in any way, as long as they do not violate the spirit of this application, they should also be regarded as the content disclosed in this application.

Claims

1. A vehicle adaptive communication control method, characterized in that, The method includes: Based on the conflict between the external risk interference frequency bands and the bandwidth requirements corresponding to the internal communication task priorities of the target vehicle, the comprehensive threat index and the comprehensive internal communication requirement index are determined. Based on the comprehensive threat index and the comprehensive internal communication requirement index, as well as the window geometry parameters of the target vehicle, the programmable metasurface of the target vehicle is meshed, and the meshes belonging to the first risk area are locally densified or regionally overlapped, while the meshes belonging to the second risk area are merged to obtain an initial programmable metasurface mesh configuration, wherein the risk level or priority of the first risk area is higher than that of the second risk area. For the initial programmable hypersurface mesh configuration, the payoff of the macroscopic layer is iterated according to the global protection strategy game of the entire mesh and the local protection strategy game of the first risk mesh, and the weights of the global protection strategy game and the local protection strategy game are dynamically adjusted based on the vehicle dynamic state to determine the target programmable hypersurface mesh configuration. The target programmable metasurface mesh configuration is mapped to each control subarray of the vehicle, and phase shift commands and polarization angle commands are issued to control the tunable units in each mesh of the vehicle.

2. The method according to claim 1, characterized in that, The external risk interference frequency band is determined based on weighted aggregation data of multi-source sensor data of the target vehicle on a unified time axis. The determination of the comprehensive threat index and the comprehensive internal communication demand index based on the conflict between the external risk interference frequency band and the bandwidth requirements corresponding to the internal communication task priorities of the target vehicle includes: The set of external risk interference frequency bands is determined based on the interference risk of each frequency band of the external channel of the target vehicle on the unified time axis; Based on the communication resource requirements of internal communication tasks on the unified time axis and the set of external risk interference frequency bands, a comprehensive evaluation is performed according to the threat and demand fusion function to obtain a comprehensive ranking result of the internal communication task priorities. Based on the comprehensive ranking results and the external risk interference frequency band set, the comprehensive threat index and the comprehensive internal communication demand index are determined.

3. The method according to claim 2, characterized in that, Before determining the comprehensive threat index and comprehensive internal communication requirement index based on the conflict between the external risk interference frequency bands of the target vehicle and the bandwidth requirements corresponding to the internal communication task priorities, the method further includes: The distance and speed information matrix collected by the millimeter-wave radar of the target vehicle, the image feature vector collected by the camera of the target vehicle, and the signaling information and link quality information output by the target vehicle through V2X vehicle-to-everything (V2X) are aligned on a unified time axis. The weighted aggregated data is obtained by weighting and fusing the distance and speed information, the image feature vector, the signaling information and the link quality information according to their respective weights and data compensation amounts. The data compensation amount of the target information is the data compensation of the target information when the target vehicle accelerates and turns.

4. The method according to claim 1, characterized in that, The global protection strategy game is used to determine the protection of the grid from the macro level, the local protection strategy game is used to optimize the protection of the first risk grid, and the payoff of the macro level is used to measure the overall payoff of grid shielding or opening windows on a unified time axis. The process for determining the target programmable hypersurface mesh configuration involves iterating through a global protection strategy game across the entire mesh and a local protection strategy game for the first risk mesh, based on the macroscopic layer's payoff. The weights of the global and local protection strategy games are dynamically adjusted based on the vehicle's dynamic state. For the initial programmable hypersurface mesh configuration, the payoff of the macroscopic layer is iterated according to the global protection strategy game of the whole mesh and the local protection strategy game of the first risk mesh. The weights of the global protection strategy game and the weights of the local protection strategy game are dynamically adjusted based on the vehicle dynamic state. The first programmable hypersurface mesh configuration is determined when the iteration converges. The priority of the final masking or projection of all meshes in the first programmable metasurface mesh configuration is re-verified to form a globally executable list of equilibrium parameters to determine the second programmable metasurface mesh configuration. The second programmable metasurface mesh configuration is used as the target programmable metasurface mesh configuration.

5. The method according to claim 1, characterized in that, The global protection strategy game is used to determine the protection of the grid from the macro level, the local protection strategy game is used to optimize the protection of the first risk grid, and the payoff of the macro level is used to measure the overall payoff of grid shielding or opening windows on a unified time axis. The process for determining the target programmable hypersurface mesh configuration involves iterating through a global protection strategy game across the entire mesh and a local protection strategy game for the first risk mesh, based on the macroscopic layer's payoff. The weights of the global and local protection strategy games are dynamically adjusted based on the vehicle's dynamic state. For the initial programmable hypersurface mesh configuration, the payoff of the macroscopic layer is iterated according to the global protection strategy game of the whole mesh and the local protection strategy game of the first risk mesh. The weights of the global protection strategy game and the weights of the local protection strategy game are dynamically adjusted based on the vehicle dynamic state. The first programmable hypersurface mesh configuration is determined when the iteration converges. The priority of the final masking or projection of all meshes in the first programmable metasurface mesh configuration is verified to form a globally executable list of equalization parameters to determine the second programmable metasurface mesh configuration. The second programmable metasurface mesh configuration is further verified based on the real-time threat distribution and communication requirements of the target vehicle to determine the blocking metric for the first risk area or emergency communication channel. If the blocking metric does not exceed a preset threshold, then the second programmable metasurface mesh configuration is used as the target programmable metasurface mesh configuration, or... If the blocking metric exceeds the preset threshold, the grid of the first risk area is further subdivided, and based on the subdivided grid, the global protection strategy game of the entire grid and the local protection strategy game of the first risk grid are iterated according to the macro-level payoffs to obtain the target programmable metasurface grid configuration.

6. The method according to claim 1, characterized in that, The process of mapping the target programmable metasurface mesh configuration to each control subarray of the vehicle and issuing phase shift commands and polarization angle commands to control the tunable units in each mesh of the vehicle includes: The priority of the control subarray is determined based on the urgency function; Based on the priority, the synchronous configuration of each control subarray of the same priority is performed by parallel triggering instruction set, and phase shift instructions and polarization angle instructions are issued to control the tunable units in each grid of the vehicle.

7. The method according to claim 6, characterized in that, The method further includes: The system monitors the power consumption and temperature of each control subarray in real time, and performs fault-tolerant switching of the backup subarray in case of an anomaly in the primary control subarray.

8. The method according to claim 1, characterized in that, The method further includes: Upon detecting extreme electromagnetic interference or communication interruption, the game iteration process is skipped, and a global forced shielding mode is activated to prioritize critical communication and vehicle safety.

9. An electronic device, characterized in that, include: A memory on which computer programs are stored; A processor for executing the computer program in the memory to implement the steps of the method according to any one of claims 1-8.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1-8.

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