Energy-saving scheduling method and system for metasurface array

Abstract

The invention relates to an energy-saving scheduling method and system for a metasurface array, and relates to the technical field of communication energy-saving scheduling. According to the energy-saving scheduling method of the metasurface array, the operation state data of each metasurface area, the three-dimensional position coordinates of the reflection units, the receiving data and the reflection data are acquired in real time, the energy efficiency evaluation set of each reflection unit is analyzed, an array topological graph of a set array reflection surface is constructed, and the energy-saving scheduling of the metasurface array is realized based on a pre-trained topological analysis model. According to the method, the energy efficiency scheduling strategy is dynamically adjusted, the analysis based on the array topological graph and the pre-training topological analysis model are utilized, the interaction and the environmental influence of the reflection units are comprehensively considered, and the energy efficiency scheduling strategy is optimized. Therefore, the energy-saving efficiency is improved, the energy efficiency waste is reduced, the capacity of the system for adapting to complex environment changes is enhanced, and the overall energy efficiency of the metasurface array is remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of communication energy-saving scheduling, and specifically to an energy-saving scheduling method and system for a metasurface array. Background Art

[0002] In the field of energy efficiency optimization of modern metasurface arrays, energy-saving scheduling is a critical and widely applicable important research topic. Traditional energy-saving scheduling methods usually rely on global optimization schemes based on preset models. These methods usually have disadvantages such as fixed parameters and lack of real-time feedback, resulting in unstable performance in dynamic and complex environments. Especially in the actual application of metasurface arrays, existing energy-saving scheduling methods usually find it difficult to monitor and analyze the state changes of each reflection unit in real time, making it difficult to accurately adjust the energy efficiency. This makes them face problems such as scheduling delays and energy efficiency waste. Especially in the case of frequent environmental changes, the limitations of existing methods become more and more obvious.

[0003] One of the biggest challenges of existing technologies is the difficulty in obtaining accurate performance data of each reflector unit in real time. Due to the lack of real-time monitoring and dynamic adjustment mechanisms, traditional methods usually rely on rough global evaluations, ignoring the changes and interactions of each reflector unit in actual operation.

[0004] Specifically, existing methods make it difficult to perform fine-grained scheduling based on the dynamic changes of each reflector unit, which can easily lead to insufficient energy efficiency optimization in some areas or miss the optimal scheduling opportunity. For example, in a complex working environment, the performance of the reflector unit may be affected by factors such as signal interference and environmental changes. Traditional methods find it difficult to respond to these changes in a timely manner, resulting in difficulty in maximizing system energy efficiency. Summary of the Invention

[0005] In response to the technical problems existing in the prior art, the present invention provides an energy-saving scheduling method and system for a metasurface array, which solves the problem that the prior art lacks real-time dynamic monitoring and precise scheduling of each reflective unit in the metasurface array, making it difficult to maximize the energy-saving effect.

[0006] The technical solution of the present invention to solve the above-mentioned technical problems is as follows: an energy-saving scheduling method for a metasurface array, comprising the following steps: real-time acquisition of operating status data of several metasurface areas of a set array reflection surface, three-dimensional position coordinates of each reflection unit, reception data, and reflection data, and analysis of the performance evaluation set of the corresponding reflection unit, including an energy consumption perception index, a reception adaptation index, and a reflection response index; based on the performance evaluation set of each reflection unit in each metasurface area of ​​the set array reflection surface, constructing an array topology map of the set array reflection surface, including several reflection nodes; based on a pre-trained topology parsing model, performing a comprehensive analysis of the array topology map of the set array reflection surface to obtain a comprehensive energy efficiency index of each reflection node in the array topology map of the set array reflection surface; and taking preset energy-saving scheduling measures for its corresponding reflection unit based on the comprehensive energy efficiency index of each reflection node in the array topology map of the set array reflection surface.

[0007] Furthermore, the operating status data includes power consumption value, mechanical disturbance response factor, micro-surface contamination index, dielectric fluctuation value, and heat dissipation load factor. The specific steps for analyzing the energy consumption perception index of each reflection unit in each super-surface area of ​​the set array reflection surface are as follows: based on the operating status data of each super-surface area of ​​the set array reflection surface, analyze the power consumption evaluation set of its corresponding super-surface unit, including load energy consumption index and energy consumption interference factor; obtain the environmental impact factor of each super-surface area of ​​the set array reflection surface, and analyze the energy consumption response index of its corresponding super-surface area in combination with the power consumption evaluation set of its corresponding super-surface area; obtain the three-dimensional position coordinates of the target signal source of the set array reflection surface, and perform a comprehensive analysis with the three-dimensional position coordinates of each reflection unit in each super-surface area of ​​the set array reflection surface to obtain the energy consumption coefficient of its corresponding reflection unit; based on the energy consumption response index of each super-surface area of ​​the set array reflection surface and the energy consumption coefficient of each reflection unit, analyze the energy consumption perception index of its corresponding reflection unit.

[0008] Furthermore, the specific steps of analyzing the power consumption evaluation set of each metasurface area of ​​the set array reflection surface are as follows: based on the power consumption value and heat dissipation load factor of each metasurface area of ​​the set array reflection surface, the load energy consumption index of the corresponding metasurface area is analyzed; based on the mechanical disturbance response factor, microsurface contamination index, and dielectric fluctuation value of each metasurface area of ​​the set array reflection surface, the energy consumption interference factor of the corresponding metasurface area is analyzed.

[0009] Furthermore, the received data includes a received signal strength value, a wavefront distortion index, a receiving angle offset, and an incident phase center offset index. The specific steps for analyzing the receiving adaptation index of each reflection unit in each super-surface area of ​​the set array reflection surface are as follows: standardizing the received data of each reflection unit in each super-surface area of ​​the set array reflection surface; and weighting the received data of each reflection unit in each super-surface area of ​​the set array reflection surface after standardization to obtain the receiving adaptation index of its corresponding reflection unit.

[0010] Furthermore, the reflection data includes a reflection efficiency value, a reflection phase response value, a reflection signal amplitude value, a spurious frequency intensity factor, and a reflection energy fluctuation factor. The specific steps for analyzing the reflection response index of each reflection unit of several super-surface areas of the set array reflection surface are as follows: based on the reflection data of each reflection unit of several super-surface areas of the set array reflection surface, analyze the reflection evaluation set of the corresponding reflection unit, including the reflection adaptation index and the reflection anti-interference index; based on the reflection evaluation set of each reflection unit of several super-surface areas of the set array reflection surface, analyze the reflection response index of the corresponding reflection unit.

[0011] Furthermore, the specific steps of constructing the array topology graph of the set array reflection surface are as follows: based on each reflection unit of each super-surface area of ​​the set array reflection surface, a reflection node set of the array topology graph of the set array reflection surface is constructed; based on the three-dimensional position coordinates of each reflection unit of each super-surface area of ​​the set array reflection surface, a connection edge set of the array topology graph of the set array reflection surface is constructed.

[0012] Furthermore, the specific steps for obtaining the comprehensive energy efficiency index of each reflection node in the array topology diagram of the set array reflection surface are as follows: inputting the array topology diagram of the set array reflection surface into a pre-trained topology parsing model for comprehensive analysis to obtain an energy efficiency evaluation set of each reflection node in the array topology diagram of the set array reflection surface, including an energy efficiency interaction perception index and an adjacent energy efficiency interference index; based on the energy efficiency evaluation set of each reflection node in the array topology diagram of the set array reflection surface, analyzing the comprehensive energy efficiency index of the corresponding reflection node.

[0013] Furthermore, the topology parsing model includes a collaborative subnetwork and an adjacent interactive subnetwork, and the specific steps for obtaining the energy efficiency evaluation set of each reflective node in the array topology diagram of the set array reflection surface are as follows: in the collaborative subnetwork of the topology parsing model, the array topology diagram of the set array reflection surface is received, and the energy efficiency interaction perception index of each reflective node in the array topology diagram of the set array reflection surface is analyzed; in the adjacent interactive subnetwork of the topology parsing model, the array topology diagram of the set array reflection surface is received, and the adjacent energy efficiency interference index of each reflective node in the array topology diagram of the set array reflection surface is analyzed.

[0014] Furthermore, the specific formula for calculating the comprehensive energy efficiency index of a reflective node in the array topology diagram of the set array reflective surface is as follows: ;in, 、 、 The comprehensive energy efficiency index, energy efficiency interaction perception index, and adjacent energy efficiency interference index of a reflective node in the array topology diagram of the set array reflective surface are respectively, 、 、 、 They are the interactive perception coefficient, adjacency coefficient, coordination coefficient, and proportional coefficient stored in the database.

[0015] The energy-saving scheduling system of a metasurface array includes: a performance evaluation and analysis module for acquiring in real time the operating status data of several metasurface areas of a set array reflection surface, the three-dimensional position coordinates of each reflection unit, reception data, and reflection data, and analyzing the performance evaluation set of its corresponding reflection unit, including an energy consumption perception index, a reception adaptation index, and a reflection response index; a topology map construction module for constructing an array topology map of the set array reflection surface based on the performance evaluation set of each reflection unit in each metasurface area of ​​the set array reflection surface, including several reflection nodes; a comprehensive energy efficiency analysis module for performing a comprehensive analysis of the array topology map of the set array reflection surface based on a pre-trained topology parsing model, and obtaining a comprehensive energy efficiency index of each reflection node in the array topology map of the set array reflection surface; and an energy-saving scheduling feedback module for performing energy-saving scheduling on the corresponding reflection unit based on the comprehensive energy efficiency index of each reflection node in the array topology map of the set array reflection surface.

[0016] The beneficial effect of the present invention is that by acquiring the operating status data of each metasurface area of ​​the set array reflection surface in real time, and combining the three-dimensional position coordinates, received data and reflected data of each reflection unit for comprehensive analysis, the energy efficiency of each reflection unit can be accurately evaluated. This method enables the system to dynamically adjust the energy efficiency scheduling strategy according to the specific performance of each reflection unit without relying on the traditional rough global optimization method, thereby significantly improving the accuracy and actual effect of energy efficiency optimization. Compared with the scheduling method that relies on static or fixed parameters in the prior art, the present invention introduces an analysis method based on the array topology map, combined with a pre-trained topology analysis model, and comprehensively considers the interaction between the reflection units and external environmental factors, ensuring that the system can efficiently adjust energy-saving measures in complex and dynamic environments, avoiding the energy efficiency waste caused by the failure to capture the performance changes of the reflection units in real time, and further optimizing the energy efficiency performance of the metasurface array by accurately calculating multiple key indicators such as the energy efficiency interaction perception index and the adjacent energy efficiency interference index, reducing energy efficiency waste, and enhancing the system's adaptability and stability to environmental changes. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a flow chart of the energy-saving scheduling method of the metasurface array of the present invention.

[0018] Figure 2 This is a specific flow chart for analyzing and setting the energy consumption perception index of each reflective unit in each metasurface area of ​​the array reflective surface in the energy-saving scheduling method of the metasurface array of the present invention.

[0019] Figure 3 This is a schematic diagram of the energy efficiency interaction perception index node sequence in the array topology diagram of the array reflection surface set in the energy-saving scheduling method of the metasurface array of the present invention.

[0020] Figure 4 This is a schematic diagram of the sequence of adjacent energy efficiency interference index nodes in the array topology diagram for setting the array reflection surface in the energy-saving scheduling method of the metasurface array of the present invention.

[0021] Figure 5 This is a block diagram of the energy-saving scheduling system of the metasurface array of the present invention. DETAILED DESCRIPTION

[0022] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without making creative efforts are within the scope of protection of this application.

[0023] In the description of this application, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of the technical features indicated. Therefore, a feature specified as "first" or "second" may explicitly or implicitly include one or more of the described features. In the description of this application, "plurality" means two or more, unless otherwise specifically specified.

[0024] In the description of this application, the term "for example" is used to mean "used as an example, illustration or explanation". Any embodiment described as "for example" in this application is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is given to enable any person skilled in the art to implement and use the present invention. In the following description, details are listed for the purpose of explanation. It should be understood that a person of ordinary skill in the art will recognize that the present invention can be implemented without using these specific details. In other examples, well-known structures and processes will not be elaborated in detail to avoid obscuring the description of the present invention with unnecessary details. Therefore, the present invention is not intended to be limited to the embodiments shown, but is consistent with the widest scope consistent with the principles and features disclosed in this application.

[0025] See also Figure 1 , an embodiment of the present invention provides a technical solution: an energy-saving scheduling method for a metasurface array, comprising the following steps: acquiring in real time operating status data of several metasurface regions of a set array reflective surface, three-dimensional position coordinates of each reflective unit, reception data, and reflection data, and analyzing a performance evaluation set of the corresponding reflective unit, including an energy consumption perception index, a reception adaptation index, and a reflection response index; constructing an array topology graph of the set array reflective surface based on the performance evaluation set of each reflective unit in each metasurface region of the set array reflective surface, including several reflective nodes (property sets and several connecting edges and corresponding edge weights); performing a comprehensive analysis on the array topology graph of the set array reflective surface based on a pre-trained topology parsing model to obtain a comprehensive energy efficiency index of each reflective node in the array topology graph of the set array reflective surface; Based on the comprehensive energy efficiency index of each reflective node in the array topology diagram of the set array reflective surface, a preset energy-saving scheduling measure is taken for its corresponding reflective unit, which is specifically: determining whether the comprehensive energy efficiency index of each reflective node in the array topology diagram of the set array reflective surface is lower than a preset first comprehensive energy efficiency index threshold (as a judgment for whether the reflective unit state remains unchanged); if it is not lower than the preset comprehensive energy efficiency index threshold, performing coordinated scheduling, that is, determining whether the comprehensive energy efficiency index thresholds of several reflective nodes within the set neighborhood of the reflective node are lower than the preset first comprehensive energy efficiency index threshold; if they are lower than the preset first comprehensive energy efficiency index threshold, the reflective nodes take on more signal reflection tasks, thereby reducing the burden on low-efficiency reflective units; If it is lower than the preset comprehensive energy efficiency index threshold, it will be judged against the preset second comprehensive energy efficiency index threshold (which is lower than the first comprehensive energy efficiency index threshold, used as the judgment that the reflector unit is closed). If it is still lower than the preset second comprehensive energy efficiency index threshold, the corresponding reflector unit will be subject to the first energy-saving scheduling measure, that is, it will be turned off. If it is higher than the preset second comprehensive energy efficiency index threshold, the corresponding reflector unit will be subject to the second energy-saving scheduling measure, that is, the power of the reflector unit will be adjusted (from normal working mode to low power consumption mode, its reflection intensity, frequency or other parameters will be lowered to reduce energy consumption) and signal strength optimization (by adjusting the signal transmission parameters of the reflector unit, such as reflection angle, intensity, etc., to ensure that the signal quality is not affected while reducing energy consumption).

[0026] Specifically, such as Figure 2 As shown, the operating status data includes power consumption value, mechanical disturbance response factor, micro-surface contamination index, dielectric fluctuation value, and heat dissipation load factor. The specific steps for analyzing the energy consumption perception index of each reflection unit in each super-surface area of ​​the set array reflection surface are as follows: based on the operating status data of each super-surface area of ​​the set array reflection surface, analyze the power consumption evaluation set of its corresponding super-surface unit, including the load energy consumption index and the energy consumption interference factor; obtain the environmental impact factor of each super-surface area of ​​the set array reflection surface, and analyze the energy consumption response index of its corresponding super-surface area in combination with the power consumption evaluation set of its corresponding super-surface area; obtain the three-dimensional position coordinates of the target signal source of the set array reflection surface, and perform a comprehensive analysis with the three-dimensional position coordinates of each reflection unit in each super-surface area of ​​the set array reflection surface to obtain the energy consumption coefficient of its corresponding reflection unit; based on the energy consumption response index of each super-surface area of ​​the set array reflection surface and the energy consumption coefficient of each reflection unit, analyze the energy consumption perception index of its corresponding reflection unit (that is, multiply the energy consumption response index of each super-surface area by the energy consumption coefficient of each reflection unit).

[0027] The power consumption value is the power consumption of the area. The voltage value and the current value can be obtained by a voltage sensor and a current sensor, and the voltage and current values ​​are multiplied together to obtain the power consumption value.

[0028] The mechanical disturbance response factor is the vibration / disturbance intensity experienced by the area. Large disturbances will cause unstable device operation and increased control loss. It can be obtained through a MEMS micro three-axis accelerometer (such as ADXL345), that is, the real-time acceleration values ​​in the X-axis, Y-axis, and Z-axis directions. The squares of these values ​​are summed and the square root is taken. The result is the mechanical disturbance response factor.

[0029] The micro-surface contamination index is the degree of contamination on the surface of a region, such as dust, smoke, and oil stains, which will affect the reflection efficiency and cause an increase in local power consumption. It can be achieved by deploying laser emitting components and reflected light intensity receiving components in the set metasurface area. The laser emitting component is used to project the incident light beam vertically to the set area array reflection surface and set the laser incident intensity; the reflected light intensity receiving component is used to measure the reflection intensity of the set area array reflection surface in real time and perform ratio processing, that is, 1-(reflection intensity / laser incident intensity). The result is the mechanical disturbance response factor.

[0030] The dielectric fluctuation value is the fluctuation of the dielectric constant of the material. Affected by temperature, humidity, electric field disturbance, etc., dielectric fluctuation will cause a decrease in control efficiency and error energy consumption. It can receive the echo signal through a broadband receiving antenna array and perform a fast Fourier transform on it to obtain the spectrum of the echo signal, extract the main peak position (that is, the main reflection peak frequency), and obtain the reference main reflection peak frequency (the reflection peak frequency stored in the partner database, that is, the factory calibration value of the equipment), and perform ratio processing, that is, |reference main reflection peak frequency-main reflection peak frequency| / reference main reflection peak frequency. The result is the dielectric fluctuation value.

[0031] The heat dissipation load factor is the instantaneous heat accumulation trend in the area. Heat accumulation will increase internal losses and nonlinear reactions, and increase energy consumption. It can obtain the current temperature value through the temperature sensor and perform numerical difference processing on the temperature value at the previous moment. The result is the heat dissipation load factor. It should be noted that at the first moment, the heat dissipation load factor is the normalized value of the temperature at the first moment.

[0032] The specific steps for obtaining the environmental impact factor of the set array reflective surface are as follows: The ambient light intensity value (obtained by the light sensor), ambient temperature value (obtained by the temperature sensor), and electromagnetic interference intensity value (obtained by the deployed electromagnetic interference sensor probe array) of the set array reflective surface are obtained and standardized. Based on the standardized processing results, weighted processing is performed, and the result obtained is the environmental impact factor.

[0033] The specific steps for calculating the energy consumption response index of a certain metasurface area of ​​a set array reflective surface are as follows: ;in, 、 、 、 The energy consumption response index, load energy consumption index, energy consumption interference factor, and environmental impact factor of a certain metasurface area of ​​the array reflection surface are set in sequence. 、 、 、 These are the load factor, interference factor, environment factor, and adjustment factor (the value is 3.000 in this implementation example) stored in the database.

[0034] It should be explained that the load factors stored in the database The specific acquisition steps are as follows: read the power consumption value and heat dissipation load factor of the metasurface area after standardization, extract the load mean and load standard deviation, and perform ratio processing, that is, 1-(load standard deviation / load mean), and use the result as the load coefficient ; Interference coefficients stored in the database The specific acquisition steps are as follows: read the mechanical disturbance response factor, microsurface contamination index, and dielectric fluctuation value of the metasurface area after standardization, extract the interference mean and interference standard deviation, and perform ratio processing, that is, 1-(interference standard deviation / interference mean), and use the result as the interference coefficient ; Environmental factors stored in the database The specific acquisition steps are as follows: read the standardized ambient light intensity value, ambient temperature value, and electromagnetic interference intensity value of the metasurface area, extract the ambient mean and ambient standard deviation, and perform ratio processing, that is, 1-(ambient standard deviation / ambient mean), and use the result as the environmental coefficient .

[0035] The specific steps for obtaining the energy consumption coefficient of each reflection unit in each super-surface area of ​​the set array reflection surface are as follows: based on the Euclidean distance formula, the three-dimensional position coordinates of each reflection unit in each super-surface area of ​​the set array reflection surface and the three-dimensional position coordinates of the target signal source are analyzed to obtain the distance value between the corresponding reflection unit and the target signal source, and the inverse is taken, that is, 1 / (1+distance value), to obtain the signal gain value of the corresponding reflection unit, and a sum analysis is performed to obtain the signal gain sum value, and the signal gain value of each reflection unit is ratioed with the signal gain sum value to obtain the energy consumption coefficient of the corresponding reflection unit.

[0036] The specific steps of analyzing the power consumption evaluation set of each metasurface area of ​​the set array reflection surface are as follows: based on the power consumption value and heat dissipation load factor of each metasurface area of ​​the set array reflection surface, analyzing the load energy consumption index of the corresponding metasurface area, specifically: standardizing the power consumption value and heat dissipation load factor of each metasurface area, and performing weighted processing based on the normalization result, and the result obtained is the load energy consumption index; based on the mechanical disturbance response factor, microsurface contamination index, and dielectric fluctuation value of each metasurface area of ​​the set array reflection surface, analyzing the energy consumption interference factor of the corresponding metasurface area, specifically: standardizing the mechanical disturbance response factor, microsurface contamination index, and dielectric fluctuation value of each metasurface area, and performing weighted processing based on the normalization result, and the result obtained is the energy consumption interference factor.

[0037] In this embodiment, through real-time monitoring of the operating status data of each metasurface area, the energy efficiency status of each metasurface area is comprehensively evaluated, and the energy consumption perception index of each reflection unit is analyzed, so that energy-saving scheduling can be optimized for each unit. Secondly, through the feedback and comprehensive analysis of real-time data, the working status of the reflection unit can be dynamically adjusted to achieve timely adjustment of high-energy consumption units. Finally, considering the impact of environmental changes on the performance of the reflection unit, it is ensured that the system can still maintain high energy efficiency performance under different environmental conditions. This environmental adaptability improves accuracy in practical applications.

[0038] Specifically, the received data includes a received signal strength value, a wavefront distortion index, a received angle offset, and an incident phase center offset index. The specific steps for analyzing the received adaptation index of each reflection unit in each super-surface area of ​​the set array reflection surface are as follows: standardizing the received data of each reflection unit in each super-surface area of ​​the set array reflection surface (that is, standardizing the received signal strength value, wavefront distortion index, received angle offset, and incident phase center offset index of each reflection unit in each super-surface area); and weighting the received data of each reflection unit in each super-surface area of ​​the set array reflection surface after the standardized processing (that is, weighting the received signal strength value, wavefront distortion index, received angle offset, and incident phase center offset index of each reflection unit in each super-surface area after the standardized processing) to obtain the received adaptation index of its corresponding reflection unit.

[0039] Among them, the received signal strength value is the received signal energy amplitude of the reflection unit. It uses the signal detection circuit integrated in each programmable reflection unit (built based on the original control path, using a low-power shunt feedback structure for instantaneous amplitude sampling) to obtain the instantaneous amplitude value at the receiving port of each unit in real time (such as through power monitoring pins, voltage feedback, etc.).

[0040] The wavefront distortion index is the phase continuity deviation between the reflection unit and the adjacent units. It can be used through the embedded phase-locked loop in each programmable reflection unit to extract the instantaneous phase value of the incident signal in real time, and perform difference processing with the instantaneous phase values ​​of its adjacent ones (such as four above, below, left and right) (such as |the instantaneous phase value of the reflection unit - the instantaneous phase value of the unit adjacent to the reflection unit above|), and perform weighted averaging processing based on the difference processing results. The result is the wavefront distortion index.

[0041] The receiving angle offset reflects the angle difference between the main propagation direction of the current incident signal at this reflective unit and the set reference incident direction. It obtains the instantaneous amplitude and instantaneous phase values ​​of the current reflective unit and the instantaneous amplitude and instantaneous phase values ​​corresponding to the four adjacent units (upper, lower, left, and right). Based on the current complex signal values ​​of the five units (that is, the complex numbers composed of the instantaneous amplitude and instantaneous phase values), the gradient of the signal change is calculated in the horizontal (X direction) and vertical (Y direction). That is, the rate of change of the complex signal between the left and right units and the upper and lower units is calculated respectively. Based on this, a two-dimensional complex gradient vector (representing the main propagation direction of the current local wavefront) is constructed. The angle between this propagation direction and the preset ideal incident direction unit vector (such as the horizontal direction) is then calculated. The result is the receiving angle offset.

[0042] The incident phase center offset index is the instantaneous deviation between the phase distribution center received by the reflection unit and the geometric center of the unit (that is, the coordinates of the unit). The three-dimensional coordinates and instantaneous phase values ​​of the reflection unit and four adjacent units (upper, lower, left, and right) are read, and the instantaneous phase values ​​of the reflection unit and the four adjacent units are summed to obtain the phase sum value. The instantaneous phase values ​​of the reflection unit and the four adjacent units are respectively analyzed with the phase sum value. The result is used as the corresponding weighting coefficient, and a weighted average is performed with the corresponding three-dimensional coordinate to obtain the three-dimensional coordinate of the phase distribution center. The difference between the three-dimensional coordinate and the three-dimensional coordinate of the reflection unit is analyzed based on the Euclidean distance formula to obtain the incident phase center offset index.

[0043] In this embodiment, the reception data of the reflection unit is standardized and weightedly analyzed to comprehensively evaluate the reception adaptation performance of each reflection unit, thereby ensuring that the working status of each unit can be accurately grasped, and then effective energy-saving scheduling is performed. Secondly, the reception adaptation index obtained by analysis is used to dynamically adjust the working status of the reflection unit. For example, for units with low energy efficiency, energy-saving measures such as power optimization or signal adjustment can be taken to reduce energy consumption while ensuring signal quality, thereby improving the energy efficiency of the overall system. Finally, while monitoring the signal strength, phase change and angle deviation in real time, adaptive adjustments can be made according to different environmental and working conditions to ensure that the metasurface array can operate efficiently and stably in various complex environments.

[0044] Specifically, the reflection data includes a reflection efficiency value, a reflection phase response value, a reflection signal amplitude value, a spurious frequency intensity factor, and a reflection energy fluctuation factor. The specific steps of analyzing the reflection response index of each reflection unit of several metasurface areas of the set array reflection surface are as follows: based on the reflection data of each reflection unit of several metasurface areas of the set array reflection surface, analyzing the reflection evaluation set of the corresponding reflection unit, including a reflection adaptation index and a reflection anti-interference index; based on the reflection evaluation set of each reflection unit of several metasurface areas of the set array reflection surface, analyzing the reflection response index of the corresponding reflection unit, which is specifically: weighting the reflection adaptation index and the reflection anti-interference index of each reflection unit to obtain the reflection response index of the corresponding reflection unit; It should be noted here that the weighting coefficient corresponding to each parameter in all the weighted processing involved in this implementation example is obtained by the entropy weight method. The specific steps of obtaining the weighting coefficients corresponding to the reflection adaptation index and the reflection anti-interference index are taken as an example: that is, the reflection adaptation index and the reflection anti-interference index of each reflection unit are normalized, and the reflection adaptation index and the reflection anti-interference index of each reflection unit after the normalization are summed to obtain the reflection adaptation index sum value and the reflection anti-interference index sum value, and then the reflection adaptation index and the reflection anti-interference index of each reflection unit after the normalization are ratioed with the reflection adaptation index sum value and the reflection anti-interference index sum value, respectively, to obtain the reflection adaptation index ratio value and the reflection anti-interference index ratio value of each reflection unit, and calculate the information entropy value of the reflection adaptation index; Specifically, the reflection adaptation index proportion of each unit is multiplied by the natural logarithm of the proportion, the calculation results of all units are summed and the negative is taken, and then divided by the natural logarithm of the total number of units. The information entropy value of the reflection anti-interference index is calculated according to the same logic, and the information entropy value of the reflection adaptation index is subtracted from 1 to obtain the information utility value of the reflection adaptation index of each reflection unit; the information entropy value of the reflection anti-interference index is subtracted from 1 to obtain the information utility value of the reflection anti-interference index of each reflection unit; the information utility value of the reflection adaptation index of each reflection unit is added to the information utility value of the reflection anti-interference index to obtain the total utility value; the information utility value of the reflection adaptation index is divided by the total utility value to obtain the weighted coefficient of the reflection adaptation index of each reflection unit; the information utility value of the reflection anti-interference index of each reflection unit is divided by the total utility value to obtain the weighted coefficient of the reflection anti-interference index of each reflection unit.

[0045] Among them, the reflection efficiency value is the proportion of the reflected energy of the incident signal by the reflection unit. It obtains the current received signal amplitude value of the unit and the signal amplitude value of the reflected signal output end respectively through the bidirectional coupling sampling path integrated in the reflection unit, and calculates based on the power ratio formed by the two (for example, approximating the power by the square amplitude). The ratio of the calculated reflected output power to the received input power is the reflection efficiency value. This calculation is completed in real time by the internal control circuit of the unit, without the need for additional external sensors.

[0046] The reflection phase response value is the phase offset generated by the unit's reflected signal relative to the incident signal. It is achieved by configuring a phase modulation structure (such as a varactor diode array or a voltage-controlled phase shift element) within the unit and integrating a phase feedback sampling circuit (such as a phase-locked structure or an IQ demodulation structure). The instantaneous phase value of the current reflected output signal of the reflection unit is read in real time, and the difference between this phase value and the instantaneous incident phase value obtained at its receiving port is calculated to obtain the reflection phase response value.

[0047] The reflected signal amplitude value is the signal strength reflected by the reflective unit. It uses the signal detection circuit integrated in each programmable reflective unit (built based on the original control path and using a low-power shunt feedback structure for instantaneous amplitude sampling) to obtain the instantaneous amplitude value at the output port of each unit in real time (such as through the power monitoring pin, voltage feedback, etc.), which is the reflected signal amplitude value.

[0048] The spurious frequency intensity factor is the relative energy intensity of non-set carrier frequency components (i.e., spurious frequency components) appearing in the reflected signal of the reflection unit. It uses a fast spectrum sampling circuit (such as low-resolution FFT demodulation) integrated in the unit reflection path to perform frequency domain transformation on the instantaneous reflected signal, extract frequency components outside the target operating frequency point, and normalize the total amplitude energy in the spurious frequency band with the energy of the main carrier frequency component. The resulting ratio is the spurious frequency intensity factor.

[0049] The reflected energy fluctuation factor measures the instantaneous fluctuation of the energy of the reflected signal from the reflective unit. It is calculated by reading the instantaneous amplitude value of the reflective unit, obtaining an instantaneous amplitude reference value (i.e., the average instantaneous amplitude value at several historical time points), and performing ratio processing, i.e., |instantaneous amplitude value - instantaneous amplitude reference value| / instantaneous amplitude reference value. The result is the reflected energy fluctuation factor.

[0050] The specific steps of analyzing the reflection evaluation set of each reflection unit of several metasurface areas of the set array reflection surface are as follows: standardize the reflection efficiency value, reflection phase response value, and reflection signal amplitude value of each reflection unit of several metasurface areas of the set array reflection surface, and perform weighted processing based on the normalization processing results to obtain the reflection adaptation index of the corresponding reflection unit; standardize the spurious frequency intensity factor and reflection energy fluctuation factor of each reflection unit of several metasurface areas of the set array reflection surface, and perform weighted processing based on the normalization processing results (take the inverse of the weighted processing result) to obtain the reflection anti-interference index of the corresponding reflection unit.

[0051] In this embodiment, by standardizing and weighting the parameters in the reflection data of the reflection unit, more accurate reflection adaptability index and reflection anti-interference index are obtained, thereby ensuring its stability and efficiency under different working conditions. Secondly, by real-time monitoring and analysis of the key parameters of the reflection unit, changes can be quickly responded to and adjusted. For example, by monitoring the reflection energy fluctuation factor, instantaneous fluctuations in signal energy can be detected in a timely manner to avoid energy loss caused by excessive fluctuations. Finally, by analyzing the reflection anti-interference index, the performance of the reflection unit under the influence of external interference is evaluated and optimized, thereby ensuring that the reflection unit can maintain stable performance and improving its overall anti-interference capability.

[0052] Specifically, the specific steps of constructing the array topology graph of the set array reflection surface are as follows: based on each reflection unit of each super-surface area of ​​the set array reflection surface, constructing the reflection node set of the array topology graph of the set array reflection surface (that is, taking the reflection unit as the node, one reflection unit corresponds to one node, and marking the performance evaluation set of its corresponding reflection unit as the attribute set of the corresponding reflection node); based on the three-dimensional position coordinates of each reflection unit in each super-surface area of ​​the set array reflection surface, constructing the connection edge set of the array topology graph of the set array reflection surface (that is, based on the Euclidean distance formula, the three-dimensional position coordinates of any two reflection units are analyzed to obtain the distance value of any two reflection units, and respectively judged with the preset distance threshold; if it is lower than the preset distance threshold, establishing a connection edge between the two reflection units, and performing similarity analysis on the attribute sets of the two reflection nodes that have established the connection edge, that is, the reflection units, based on the cosine similarity, and using the result as the edge weight of the connection edge).

[0053] In this implementation, an array topology diagram is constructed to associate each reflector unit with its performance evaluation set, thereby clearly visualizing the working status of each reflector unit and facilitating global management. Secondly, a connection edge set is constructed based on Euclidean distance and a preset threshold to accurately determine which reflector units are closely connected and which reflector units may affect the signal transmission quality. The similarity analysis of the attribute set is then combined with cosine similarity to better identify the synergistic effect between the reflector units, thereby more accurately performing performance optimization and scheduling.

[0054] Specifically, the specific steps for obtaining the comprehensive energy efficiency index of each reflection node in the array topology diagram of the set array reflection surface are as follows: input the array topology diagram of the set array reflection surface into a pre-trained topology parsing model for comprehensive analysis to obtain an energy efficiency evaluation set of each reflection node in the array topology diagram of the set array reflection surface, including an energy efficiency interaction perception index and an adjacent energy efficiency interference index; based on the energy efficiency evaluation set of each reflection node in the array topology diagram of the set array reflection surface, analyze the comprehensive energy efficiency index of the corresponding reflection node.

[0055] The topology parsing model includes a collaborative subnetwork and an adjacent interactive subnetwork. The specific steps of obtaining the energy efficiency evaluation set of each reflective node in the array topology diagram of the set array reflective surface are as follows: in the collaborative subnetwork of the topology parsing model, the array topology diagram of the set array reflective surface is received, and the energy efficiency interactive perception index of each reflective node in the array topology diagram of the set array reflective surface is analyzed. Specifically, the interactive layer performs interactive processing on the attribute set of each reflective node in the array topology diagram of the set array reflective surface, the fusion layer performs weighted processing on the interactive processing results, generates the energy efficiency interactive perception index, and the collaborative output layer performs weighted processing on the interactive processing results, generates the energy efficiency interactive perception index, and the collaborative output layer performs weighted processing on the energy efficiency interactive perception index. The energy efficiency interaction perception index is output as the first output port of the model; in the adjacency interaction subnetwork of the topology parsing model, the array topology map of the set array reflection surface is received, and the adjacency energy efficiency interference index of each reflection node in the array topology map of the set array reflection surface is analyzed, which is specifically as follows: the adjacency perception layer extracts the adjacency vector of each reflection node in the array topology map, the adjacency fusion layer weights the adjacency vector of each reflection node in the array topology map to obtain the adjacency energy efficiency interference index of the corresponding reflection node, and the adjacency output layer outputs the adjacency energy efficiency interference index as the second output port of the model.

[0056] Among them, the collaborative subnetwork includes the interaction layer, the fusion layer, and the collaborative output layer (as the first output port).

[0057] The interaction layer performs interactive processing on the energy consumption perception index, reception adaptation index, and reflection response index of the attribute set of each reflection node in the array topology diagram of the set array reflection surface (such as the interaction of any two indices in the attribute set and the interaction of the three indices, i.e., the product).

[0058] The fusion layer receives the interaction processing results of each reflective node in the array topology diagram and performs weighted processing on them to generate the energy efficiency interaction perception index of the corresponding reflective node.

[0059] The collaborative output layer receives the energy efficiency interaction perception index of each reflective node in the array topology diagram and maps the result between 0 and 1 through the Sigmoid function.

[0060] The adjacency interaction subnetwork includes the adjacency perception layer, the adjacency fusion layer, and the adjacency output layer (as the second output port).

[0061] The adjacency perception layer counts the number of adjacent reflector nodes of each reflector node in the array topology (i.e., the reflector nodes to which the reflector node is connected through connection edges); Extract the edge weight mean of each reflective node in the array topology graph (i.e., perform average processing on the edge weights of the edges connecting each reflective node and each adjacent reflective node in the array topology graph, and the result is the edge weight mean); The energy consumption perception index ratio, reception adaptation index ratio, and reflection response index ratio of each reflection node in the array topology are extracted respectively (that is, the edge weights of the connection edges of each adjacent reflection node are summed to obtain the adjacent edge weight sum, and the edge weights of the connection edges of each adjacent reflection node are respectively ratioed with the adjacent edge weight sum to obtain the corresponding adjacent weight coefficient, and then the energy consumption perception index, reception adaptation index, and reflection response index of each adjacent reflection node are weighted averaged respectively, and then the energy consumption perception index, reception adaptation index, and reflection response index of the reflection node are respectively ratioed with the index corresponding to the weighted average processing result to obtain the energy consumption perception index ratio, reception adaptation index ratio, and reflection response index ratio of the reflection node), and then the number of adjacent reflection nodes, edge weight average, energy consumption perception index ratio, reception adaptation index ratio, and reflection response index ratio of each reflection node in the array topology are marked as adjacent vectors.

[0062] The adjacency fusion layer performs weighted processing on the adjacency vector of each reflective node in the array topology graph to extract the adjacency energy efficiency interference index of each reflective node in the array topology graph.

[0063] The adjacency output layer passes the adjacency energy efficiency interference index of each reflection node in the array topology graph through the Sigmoid function and maps the result between 0 and 1.

[0064] The pre-training steps of the topology parsing model are as follows: First, a training dataset covering the multi-dimensional performance characteristics of each reflective node in the reflective surface topology is constructed. Specifically, the reflective surface topology diagram and its corresponding reflective unit status data are collected under multiple time periods and multiple working conditions. The node status data covers node attribute characteristics (such as reflective unit type, reflection efficiency, reflection angle, etc.), connection relationship characteristics (such as adjacency matrix, edge weight distribution, mutual influence between nodes) and performance labels (such as signal strength, reflection quality, etc.).

[0065] The topology parsing model is pre-trained separately. Taking the collaborative sub-network as an example, by training the node interaction layer and the node fusion layer, the model can accurately learn the interaction relationship between the reflection units and their synergistic impact on energy efficiency. By training the signal transmission and reflection interaction between the reflection units, it can capture the multi-dimensional performance characteristics changes. Loss function: The mean square error (MSE) loss function is used to evaluate the performance indicators of the regression output to optimize the prediction results. The Adam optimizer is used for back propagation and the weight parameters of each layer are iteratively updated. After completing the independent pre-training of the sub-network, the weights of each sub-network are loaded into the complete topology parsing model as initialization values.

[0066] A joint optimization mechanism is introduced to perform multi-task optimization in the fusion output layer, while optimizing the prediction results of the energy efficiency interaction perception index and the adjacent energy efficiency interference index, minimizing the overall prediction error and improving the model's ability to recognize complex topologies and fault modes. Through this process, the model's accuracy in different topologies and working conditions is enhanced, thereby improving the system's performance in fault diagnosis, signal transmission, and energy efficiency optimization.

[0067] Through joint training and multi-task optimization, a topology parsing model is obtained that can monitor and optimize the reflection units in the reflection surface topology structure in real time. The trained model is deployed in the actual system, using real-time data for topology identification and performance evaluation, and providing sustainable energy-saving scheduling and optimization solutions.

[0068] The specific formula for calculating the comprehensive energy efficiency index of a reflective node in the array topology diagram of a set array reflective surface is as follows: ;in, 、 、 The comprehensive energy efficiency index, energy efficiency interaction perception index, and adjacent energy efficiency interference index of a reflective node in the array topology diagram of the set array reflective surface are respectively, 、 、 、 These are the interaction perception coefficient, adjacency coefficient, coordination coefficient, and proportional coefficient (the value is 2.000 in this implementation example) stored in the database.

[0069] It should be explained that the interaction perception coefficient stored in the database The specific acquisition steps are as follows: obtain the historical energy efficiency interaction perception index of the reflective node at several historical time points, perform ratio processing on them respectively with the current energy efficiency interaction perception index, perform weighted processing on the results, and use the weighted processing results as the interaction perception coefficient ; Adjacency coefficient stored in the database The specific acquisition steps are as follows: obtain the historical adjacent energy efficiency interference index of the reflective node at several historical time points, perform ratio processing on them respectively with the current adjacent energy efficiency interference index, perform weighted processing on the results, and use the weighted processing results as the adjacent coefficient ; Coordination coefficients stored in the database The specific acquisition steps are as follows: read the historical energy efficiency interaction perception index and historical adjacent energy efficiency interference index of the reflective node at several historical time points, extract the interaction value at the corresponding time point (historical energy efficiency interaction perception index × historical adjacent energy efficiency interference index), and then perform ratio processing with the current interaction value respectively, perform weighted processing on the results, and use the weighted processing result as the coordination coefficient .

[0070] The specific implementation example of calculating the comprehensive energy efficiency index of a reflective node in the array topology of the set array reflective surface is as follows. The existing data is as follows: including the energy efficiency interaction perception index and adjacent energy efficiency interference index of 5 reflective nodes (randomly selected) in the array topology of the set array reflective surface, as shown in Table 1 and Figure 3-4 As shown: Table 1 Example of energy efficiency evaluation data for node sequence in array topology diagram with set array reflection surface

[0071] Interaction perception coefficients stored in the database Approximately: 0.467; Adjacency coefficient stored in the database Approximately: 0.513; Coordination coefficients stored in the database Approximately: 0.352; Substituting the data in Table 1 and the above coefficients into the specific formula for calculating the comprehensive energy efficiency index of a reflective node in the array topology diagram of the set array reflective surface, we obtain: The comprehensive energy efficiency index of the first reflector node in the array topology of the array reflector surface is set to ln(1+((0.684^0.467+(1 / (1+0.364))^0.513) / 2.000))×(1+tanh(0.352×(0.684 / 0.364)))≈0.964; The comprehensive energy efficiency index of the second reflector node in the array topology of the array reflector surface is set to ln(1+((0.726^0.467+(1 / (1+0.285))^0.513) / 2.000))×(1+tanh(0.352×(0.726 / 0.285)))≈1.073; The comprehensive energy efficiency index of the third reflector node in the array topology of the array reflector surface is set to ln(1+((0.597^0.467+(1 / (1+0.341))^0.513) / 2.000))×(1+tanh(0.352×(0.597 / 0.341)))≈0.927; The comprehensive energy efficiency index of the fourth reflector node in the array topology of the array reflector surface is set to ln(1+((0.714^0.467+(1 / (1+0.413))^0.513) / 2.000))×(1+tanh(0.352×(0.714 / 0.413)))≈0.946; The comprehensive energy efficiency index of the fifth reflector node in the array topology diagram of the array reflector surface is set to be ln(1+((0.628^0.467+(1 / (1+0.396))^0.513) / 2.000))×(1+tanh(0.352×(0.628 / 0.396)))≈0.904.

[0072] In this implementation scheme, by analyzing the comprehensive energy efficiency index of each reflection node, the performance of each reflection unit can be carefully evaluated to ensure the accurate implementation of energy-saving scheduling measures. Secondly, the energy efficiency interaction perception index and the adjacent energy efficiency interference index are used, combined with the coefficients in the database to perform a detailed analysis of the impact of each node, which can optimize energy efficiency. By analyzing the ratio of historical data to current node data, the changing law of energy efficiency interaction between nodes can be captured, and the adaptive ability can be improved, so that the energy efficiency status of the node can be flexibly adjusted in real-time work, and energy efficiency and reflection quality can be improved. Finally, by weightedly merging the node's energy efficiency interaction perception index and the adjacent energy efficiency interference index and introducing a coordination coefficient, the interaction and synergistic impact between nodes can be comprehensively considered to optimize the overall energy efficiency.

[0073] See also Figure 5 The energy-saving scheduling system of the metasurface array includes: a performance evaluation and analysis module, which is used to obtain the operating status data of several metasurface areas of the set array reflection surface, the three-dimensional position coordinates of each reflection unit, the reception data, and the reflection data in real time, and analyze the performance evaluation set of its corresponding reflection unit, including the energy consumption perception index, the reception adaptation index, and the reflection response index; a topology map construction module, which is used to construct the array topology map of the set array reflection surface based on the performance evaluation set of each reflection unit in each metasurface area of ​​the set array reflection surface, including several reflection nodes; a comprehensive energy efficiency analysis module, which is used to perform a comprehensive analysis on the array topology map of the set array reflection surface based on a pre-trained topology parsing model, and obtain the comprehensive energy efficiency index of each reflection node in the array topology map of the set array reflection surface; an energy-saving scheduling feedback module, which is used to perform energy-saving scheduling on the corresponding reflection unit based on the comprehensive energy efficiency index of each reflection node in the array topology map of the set array reflection surface.

[0074] It should be noted that, in the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0075] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0076] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0077] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0078] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0079] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0080] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. An energy-saving scheduling method for a metasurface array, characterized in that: The following steps are involved: Real-time acquisition of operating status data of several metasurface areas of a set array reflective surface, the three-dimensional position coordinates of each reflective unit, reception data, and reflection data, and analysis of the performance evaluation set of the corresponding reflective unit, including energy consumption perception index, reception adaptation index, and reflection response index; Based on the performance evaluation set of each reflection unit in each metasurface area of ​​the set array reflection surface, construct an array topology diagram of the set array reflection surface, including a plurality of reflection nodes; Based on the pre-trained topology analysis model, a comprehensive analysis is performed on the array topology of the set array reflection surface to obtain the comprehensive energy efficiency index of each reflection node in the array topology of the set array reflection surface; Based on the comprehensive energy efficiency index of each reflective node in the array topology diagram of the set array reflective surface, preset energy-saving scheduling measures are taken for its corresponding reflective unit.

2. The energy-saving scheduling method of the metasurface array according to claim 1, characterized in that: The operating status data includes power consumption value, mechanical disturbance response factor, micro-surface contamination index, dielectric fluctuation value, and heat dissipation load factor. The specific steps for analyzing and setting the energy consumption perception index of each reflective unit in each metasurface area of ​​the array reflective surface are as follows: Based on the operating status data of each metasurface area of ​​the set array reflective surface, the power consumption evaluation set of its corresponding metasurface unit is analyzed, including the load energy consumption index and the energy consumption interference factor; Obtain the environmental impact factor of each metasurface area of ​​the set array reflective surface, and analyze the energy consumption response index of the corresponding metasurface area in combination with the power consumption evaluation set of the corresponding metasurface area; Obtaining the three-dimensional position coordinates of the target signal source of the set array reflection surface, and performing a comprehensive analysis with the three-dimensional position coordinates of each reflection unit of each metasurface area of ​​the set array reflection surface to obtain the energy consumption coefficient of its corresponding reflection unit; Based on the energy consumption response index of each metasurface area of ​​the set array reflection surface and the energy consumption coefficient of each reflection unit, the energy consumption perception index of the corresponding reflection unit is analyzed.

3. The energy-saving scheduling method of the metasurface array according to claim 2, characterized in that: The specific steps for analyzing the power consumption evaluation set for each metasurface region of the array reflector are as follows: Based on the power consumption value and heat dissipation load factor of each metasurface area of ​​the set array reflective surface, the load energy consumption index of the corresponding metasurface area is analyzed; Based on the mechanical disturbance response factor, microsurface contamination index, and dielectric fluctuation value of each metasurface area of ​​the set array reflective surface, the energy consumption interference factor of the corresponding metasurface area is analyzed.

4. The energy-saving scheduling method of the metasurface array according to claim 1, characterized in that: The received data includes a received signal strength value, a wavefront distortion index, a receiving angle offset, and an incident phase center offset index. The specific steps for analyzing and setting the receiving adaptation index of each reflective unit in each metasurface area of ​​the array reflective surface are as follows: performing normalization processing on the received data of each reflection unit of each metasurface region of the set array reflection surface; The received data of each reflective unit in each metasurface area of ​​the set array reflective surface after the standardized processing is weighted to obtain the receiving adaptation index of its corresponding reflective unit.

5. The energy-saving scheduling method of the metasurface array according to claim 1, characterized in that: The reflection data includes reflection efficiency value, reflection phase response value, reflection signal amplitude value, spurious frequency intensity factor, and reflection energy fluctuation factor. The specific steps for analyzing the reflection response index of each reflection unit in several metasurface areas of the array reflection surface are as follows: Based on the reflection data of each reflection unit in several metasurface areas of the set array reflection surface, the reflection evaluation set of the corresponding reflection unit is analyzed, including the reflection adaptation index and the reflection anti-interference index; Based on the reflection evaluation set of each reflection unit in several metasurface areas of the set array reflection surface, the reflection response index of its corresponding reflection unit is analyzed.

6. The energy-saving scheduling method of the metasurface array according to claim 1, characterized in that: The specific steps for constructing an array topology diagram for setting the array reflective surface are as follows: Constructing a reflection node set of an array topology graph of the set array reflection surface based on each reflection unit of each metasurface region of the set array reflection surface; Based on the three-dimensional position coordinates of each reflection unit in each metasurface area of ​​the set array reflection surface, a connection edge set of the array topology graph of the set array reflection surface is constructed.

7. The energy-saving scheduling method of the metasurface array according to claim 1, characterized in that: The specific steps for obtaining the comprehensive energy efficiency index of each reflective node in the array topology diagram of the set array reflective surface are as follows: The array topology of the set array reflection surface is input into the pre-trained topology analysis model for comprehensive analysis to obtain the energy efficiency evaluation set of each reflection node in the array topology of the set array reflection surface, including the energy efficiency interaction perception index and the adjacent energy efficiency interference index; Based on the energy efficiency evaluation set of each reflective node in the array topology of the set array reflective surface, the comprehensive energy efficiency index of the corresponding reflective node is analyzed.

8. The energy-saving scheduling method for a metasurface array according to claim 7, characterized in that: The topology analysis model includes a collaborative subnetwork and an adjacent interactive subnetwork. The specific steps for obtaining the energy efficiency evaluation set of each reflective node in the array topology diagram of the set array reflective surface are as follows: In the collaborative subnetwork of the topology analysis model, an array topology diagram of a set array reflection surface is received, and an energy efficiency interaction perception index of each reflection node in the array topology diagram of the set array reflection surface is analyzed; In the adjacency interaction subnetwork of the topology analysis model, an array topology diagram of a set array reflection surface is received, and an adjacency energy efficiency interference index of each reflection node in the array topology diagram of the set array reflection surface is analyzed.

9. The energy-saving scheduling method for a metasurface array according to claim 7, characterized in that: The specific formula for calculating the comprehensive energy efficiency index of a reflective node in the array topology diagram of a set array reflective surface is as follows: ； in, 、 、 The comprehensive energy efficiency index, energy efficiency interaction perception index, and adjacent energy efficiency interference index of a reflective node in the array topology diagram of the set array reflective surface are respectively, 、 、 、 They are the interactive perception coefficient, adjacency coefficient, coordination coefficient, and proportional coefficient stored in the database.

10. An energy-saving scheduling system for a metasurface array, applying the energy-saving scheduling method for a metasurface array according to any one of claims 1 to 9, characterized in that: include: The performance evaluation and analysis module is used to obtain in real time the operating status data of several metasurface areas of the set array reflective surface, the three-dimensional position coordinates of each reflective unit, the reception data, and the reflection data, and analyze the performance evaluation set of the corresponding reflective unit, including the energy consumption perception index, the reception adaptation index, and the reflection response index; A topology map construction module is used to construct an array topology map of the set array reflection surface based on a performance evaluation set of each reflection unit in each metasurface area of ​​the set array reflection surface, including a plurality of reflection nodes; A comprehensive energy efficiency analysis module is used to perform a comprehensive analysis on the array topology of the set array reflection surface based on a pre-trained topology analysis model to obtain a comprehensive energy efficiency index of each reflection node in the array topology of the set array reflection surface; The energy-saving scheduling feedback module is used to perform energy-saving scheduling on the corresponding reflection unit based on the comprehensive energy efficiency index of each reflection node in the array topology diagram of the set array reflection surface.

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