An Enhanced Backscatter Communication Method and System Based on Movable Antenna Technology

Abstract

This invention discloses an enhanced backscatter communication method and system based on movable antenna technology, solving the technical problem that existing backscatter communication methods struggle to effectively avoid interference zones in complex environments, severely restricting the full exploitation and utilization of spatial degrees of freedom. The method includes acquiring the basic parameters of the backscatter communication system and constructing a corresponding basic parameter model. Using CST electromagnetic simulation software, full-position voltage calculations are performed on the parameter model and the system's basic parameters to obtain a full-position measurement voltage set for the transmit-receive array. After decoupling preprocessing of this voltage set, a decoupled receive voltage component set is output, which is then processed by sensing to obtain a dedicated backscatter communication channel matrix. Based on the system's basic parameters, channel optimization is performed on this channel matrix, ultimately outputting a target backscatter communication dedicated channel matrix that can be directly applied to backscatter communication.

Description

Technical Field

[0001] This invention relates to the field of communication technology, and in particular to an enhanced backscatter communication method and system based on movable antenna technology. Background Technology

[0002] With the continuous iteration and evolution of sixth-generation (6G) mobile communication technology, wireless systems are breaking through the traditional single communication boundaries and undergoing a comprehensive transformation towards a new architecture that deeply integrates communication, sensing, and intelligence. Emerging core applications such as smart city IoT, real-time environmental perception for autonomous driving, and ubiquitous industrial interconnection place dual rigid demands on wireless transmission, requiring high-capacity, high-reliability, low-latency communication and accurate real-time perception across the entire domain. Integrated Sensing and Communication (ISAC) technology, with its core advantages of resource sharing and efficiency collaboration, has become a key supporting technology for the implementation of 6G converged applications, attracting widespread attention and focused research from the global academic and industrial communities.

[0003] Within the Integrated Sensing and Communication (ISAC) technology framework, backscatter communication, as a low-power, low-cost passive communication method, is a core communication solution adapted to IoT tags, micro-terminals, and other devices, and also an important carrier for establishing a collaborative link between sensing and communication. However, traditional backscatter communication is susceptible to multipath effects in complex environments and non-line-of-sight propagation interference, making it difficult to simultaneously achieve high-precision target sensing and high-reliability data transmission. This makes it unable to fully match the performance requirements of integrated sensing and communication in 6G converged scenarios, becoming a core bottleneck restricting the application of ISAC technology in passive terminal scenarios.

[0004] Existing backscatter communication methods mostly rely on multiple-input multiple-output (MIMO) antenna architectures to achieve signal transmission. Passive communication terminals modulate reflected environmental radio frequency signals by adjusting their own antenna load impedance to complete data transmission and target perception coordination. This is the mainstream implementation method for passive terminals in current integrated sensing and communication scenarios. However, these methods generally use traditional MIMO antenna arrays deployed in fixed locations. The antenna spatial configuration is fixed and cannot be dynamically adjusted according to changes in the actual scene. In complex environments, it is difficult to effectively avoid interference areas, which seriously restricts the full exploitation and utilization of spatial freedom. Summary of the Invention

[0005] This invention provides an enhanced backscatter communication method and system based on movable antenna technology, which solves the technical problem that existing backscatter communication methods are difficult to effectively avoid interference areas in complex environments, which seriously restricts the full exploitation and utilization of spatial degrees of freedom.

[0006] The first aspect of this invention provides an enhanced backscatter communication method based on movable antenna technology, comprising: Obtain the basic parameters of the backscatter communication system, and construct a basic parameter model of the backscatter communication system based on the basic parameters of the backscatter communication system; Based on the CST electromagnetic simulation software, the voltage at all positions of the backscatter communication system is calculated using the basic parameter model and basic parameters of the backscatter communication system, and the voltage set of the transmitting and receiving array at all positions is output. The full-position measurement voltage set of the transmit-receive array is decoupled and preprocessed to output the decoupled receive voltage component set; The decoupled received voltage component set is sensed and calculated to output a backscatter communication dedicated channel matrix; Based on the basic parameters of the backscatter communication system, the backscatter communication dedicated channel matrix is ​​optimized to output the target backscatter communication dedicated channel matrix, which is used to realize backscatter communication.

[0007] Optionally, the basic parameters of the backscatter communication system include the range of the area under test, the number of transmitting antennas, the number of receiving antennas, the fixed reflection coefficient of the scatterer, the fixed antenna impedance of the tag, the dynamically adjustable load impedance of the tag, the movable coordinate range of the transmitting antenna, the movable coordinate range of the receiving antenna, the minimum antenna spacing constraint, and the transceiver array spacing; the step of constructing a basic parameter model of the backscatter communication system based on the basic parameters of the backscatter communication system includes: The electromagnetic sensing area is defined based on the range of the object to be measured. Configure the number of transmit antennas and the number of receive antennas as transmit array size parameters and receive array size parameters, respectively. Generate the initial position parameters of the transmitting antenna within the movable coordinate range of the transmitting antenna, and generate the initial position parameters of the receiving antenna within the movable coordinate range of the receiving antenna; The fixed reflection coefficient of the scatterer, the fixed antenna impedance of the tag, and the dynamically adjustable load impedance of the tag are integrated into the target scattering parameters; Set the minimum antenna spacing constraint and the transmit / receive array spacing as system position constraint parameters; An electromagnetic calculation coordinate system is established, and the boundary coordinates of the electromagnetic sensing area, the scale parameters of the transmitting array, the scale parameters of the receiving array, the initial position parameters of the transmitting antenna, the initial position parameters of the receiving antenna, the target scattering parameters, and the system position constraint parameters are entered and assigned to the electromagnetic calculation coordinate system one by one to obtain the basic parameter model of the backscatter communication system.

[0008] Optionally, the calculation of the all-position voltage based on the CST electromagnetic simulation software for the basic parameter model and basic parameters of the backscatter communication system, and the output of the all-position measurement voltage set of the transmitting and receiving array, includes: Extract the initial position parameters of the transmitting antenna, the initial position parameters of the receiving antenna, and the target scattering parameters from the basic parameter model of the backscatter communication system; The CST electromagnetic simulation software is used to perform electromagnetic field simulation based on the initial position parameters of the transmitting antenna, the initial position parameters of the receiving antenna, and the target scattering parameters, to obtain the original data files corresponding to the incident field, the scattered field, and the total electric field. The original data files corresponding to the incident field, the scattered field, and the total electric field are sequentially integrated by algorithms, data normalized, and linearly mapped to obtain a set of electric field distribution parameters. The nonlinear scattering field relationship corresponding to the electric field distribution parameter set is substituted into the preset Born approximation algorithm for simplification, and a linear mapping relationship between the scattering electric field and the received voltage is established to obtain the linearized received voltage calculation formula. According to the movable coordinate range of the transmitting antenna and the movable coordinate range of the receiving antenna in the basic parameters of the backscatter communication system, the transceiver array is controlled to traverse multiple movable positions. Substituting the electric field data of each of the movable positions into the linearized receiving voltage calculation formula, the full-position measurement voltage set of the transmitting and receiving array is obtained.

[0009] Optionally, the decoupling preprocessing of the full-position measurement voltage set of the transmit-receive array to output a decoupled receive voltage component set includes: The full-position measurement voltage set of the transmit-receive array is sequentially spliced ​​and data regularized according to the transmit antenna number, receive antenna number, and position coordinates to obtain the regularized full-position measurement voltage set of the transmit-receive array. Abnormal and invalid data are removed from the normalized full-position measurement voltage set of the transmit-receive array to obtain a linearized receive voltage parameter set with a unified format. The scattering response components corresponding to the clutter scatterer in the test environment are extracted from the linearized received voltage parameter set in the unified format to determine the clutter scattering field parameters. Based on the preset tag reflection coefficient definition, the linearized receiving voltage parameter set of the unified format is split into scattered field modes to separate the tag structure mode scattered field parameters and the tag antenna mode scattered field parameters. The tag structure mode scattering field parameters, the tag antenna mode scattering field parameters, and the clutter scattering field parameters are decoupled and decoupled according to the structure mode component and the antenna mode component to obtain the clutter combined voltage parameters and the tag independent voltage parameters. By integrating the clutter combined voltage parameters and the tag-independent voltage parameters, a decoupled receive voltage component set is obtained.

[0010] Optionally, the step of sensing and calculating the decoupled received voltage component set to output a backscatter communication-specific channel matrix includes: A sparse reconstruction optimization model is constructed based on the decoupled received voltage component set; The sparse reconstruction optimization model is iteratively solved to obtain the sparse reflection coefficient results; The sparse reflectance coefficient results are split to output a combined reflectance coefficient vector and a label-independent reflectance coefficient vector; Based on the combined reflectance coefficient vector and the tag-independent reflectance coefficient vector, a target localization and tag recognition result set is determined. Extract the spatial location information of the identified tags from the target localization and tag recognition result set; Based on the spatial location information of the identified tags, the channel vector of the identified tags is determined; Based on the channel vectors of the identified tags, a dedicated channel matrix for backscatter communication is constructed.

[0011] Optionally, the step of optimizing the backscatter communication dedicated channel matrix based on the fundamental parameters of the backscatter communication system to output the target backscatter communication dedicated channel matrix includes: The movable coordinate range of the transmitting antenna, the movable coordinate range of the receiving antenna, the minimum antenna spacing constraint, and the transceiver array spacing are extracted from the basic parameters of the backscatter communication system as position constraint parameters. With the goal of maximizing sensing capacity, a preset PSO particle swarm optimization algorithm is used to iteratively optimize the positions of the transmitting antenna and the receiving antenna to obtain the target antenna position vector. The backscatter communication dedicated channel matrix is ​​optimized based on the target antenna position vector to obtain the target backscatter communication dedicated channel matrix.

[0012] A second aspect of the present invention provides an enhanced backscatter communication system based on movable antenna technology, comprising: The acquisition module is used to acquire the basic parameters of the backscatter communication system and construct a basic parameter model of the backscatter communication system based on the basic parameters of the backscatter communication system. The calculation module is used to perform all-position voltage calculations on the basic parameter model and basic parameters of the backscatter communication system based on CST electromagnetic simulation software, and output the all-position measurement voltage set of the transmitting and receiving array; The preprocessing module is used to perform decoupling preprocessing on the full-position measurement voltage set of the transmit-receive array and output the decoupling receive voltage component set; The calculation module is used to perform sensing calculation on the decoupled received voltage component set and output a backscatter communication dedicated channel matrix; An optimization module is used to optimize the backscatter communication dedicated channel matrix based on the basic parameters of the backscatter communication system, and output the target backscatter communication dedicated channel matrix, which is used to realize backscatter communication.

[0013] A third aspect of the present invention provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of the enhanced backscatter communication method based on movable antenna technology as described above.

[0014] The fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed, implements the enhanced backscatter communication method based on movable antenna technology as described above.

[0015] The fifth aspect of the present invention provides a computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, wherein, when the program instructions are executed by a computer, the computer performs the steps of the enhanced backscatter communication method based on movable antenna technology as described above.

[0016] As can be seen from the above technical solutions, the present invention has the following advantages: The above technical solution of the present invention provides an enhanced backscatter communication method based on movable antenna technology. This method acquires the basic parameters of a backscatter communication system and constructs a basic parameter model of the backscatter communication system based on these parameters. Using CST electromagnetic simulation software, it performs all-position voltage calculations on the backscatter communication system's basic parameter model and parameters, outputting a set of all-position measured voltages for the transmit / receive array. It then performs decoupling preprocessing on the all-position measured voltages of the transmit / receive array, outputting a set of decoupled receive voltage components. Finally, it performs sensing calculations on the decoupled receive voltage components, outputting a dedicated backscatter communication channel matrix. Based on the basic parameters of the backscatter communication system, it performs channel optimization on the dedicated backscatter communication channel matrix, outputting a target dedicated backscatter communication channel matrix. This target dedicated backscatter communication channel matrix is ​​used to realize backscatter communication. This invention fully characterizes the overall system characteristics by building a basic system parameter model. Combined with all-position voltage calculation, it achieves complete acquisition of signal data in all spatial dimensions of the transceiver array, providing comprehensive data support for adapting to complex environments and exploring spatial degrees of freedom. Decoupling and preprocessing the all-position measured voltage set enables effective separation of mixed voltage components and accurate differentiation between interference-related components and valid signal components. This allows for effective avoidance of interference areas in complex environments from a data perspective. Based on the decoupled received voltage component set, sensing calculation is performed to construct a channel matrix, which can completely map the inherent response characteristics of the channel corresponding to different spatial positions, fully releasing and exploring the potential spatial degrees of freedom of the system. Furthermore, the channel matrix is ​​optimized in a targeted manner in combination with the basic system parameters to further adapt to the full-space transmission characteristics and regulate the differences in spatial dimensions of the channel. This enables the final target backscatter communication-specific channel matrix to adapt to the spatial transmission requirements of complex scenarios. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart illustrating the steps of an enhanced backscatter communication method based on movable antenna technology, as provided in Embodiment 1 of the present invention. Figure 2 This is a schematic diagram of the integrated sensing and backscatter communication system structure provided in Embodiment 1 of the present invention; Figure 3 This is a schematic diagram illustrating the convergence performance of the algorithm provided in Embodiment 1 of the present invention; Figure 4This is a schematic diagram comparing the sensing capabilities of different numbers of antennas according to Embodiment 1 of the present invention; Figure 5 This is a schematic diagram comparing the sensing capabilities of different transmit and receive array spacings according to Embodiment 1 of the present invention; Figure 6 This is a schematic diagram illustrating the comparison of sensing capabilities for different normalized region sizes provided in Embodiment 1 of the present invention. Figure 7 This is a schematic diagram illustrating the sensing and identification results of two closely spaced tags and a clutter scatterer provided in Embodiment 1 of the present invention. The edge-to-edge spacing of the tags is 75 mm. (a) Tag and clutter scatterer, (b) Two tags, (c)–(d) Only one tag. The PSNR and SSIM values ​​are (a) (PSNR=23.45dB, SSIM=0.97), (b) (PSNR=25.46dB, SSIM=0.98), (c) (PSNR=23.82dB, SSIM=0.98), and (d) (PSNR=23.98dB, SSIM=0.98), respectively. Figure 8 This is a schematic diagram comparing the BER performance of ESM, QSM, SM and GSM when SE (Spectral Efficiency) = 8 bits / s / Hz, as provided in Embodiment 1 of the present invention. Figure 9 This is a structural block diagram of an enhanced backscatter communication system based on movable antenna technology, provided in Embodiment 2 of the present invention. Detailed Implementation

[0019] This invention provides an enhanced backscatter communication method and system based on movable antenna technology, which can be applied to achieve accurate positioning and identification of tags in complex environments. It also supports highly reliable backscatter communication, solving the technical problem that existing backscatter communication methods are difficult to effectively avoid interference areas in complex environments, which seriously restricts the full exploitation and utilization of spatial degrees of freedom.

[0020] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. It should be noted that in the optional embodiments of the present invention, the object information and other related data involved require the permission or consent of the object when the embodiments of the present invention are applied to specific products or technologies, and the collection, use, and processing of related data must comply with relevant laws, regulations, and standards. That is to say, if the embodiments of the present invention involve data related to the object, it needs to be obtained with the authorization and consent of the object, the authorization and consent of relevant departments, and in compliance with relevant laws, regulations, and standards. If personal information is involved in the embodiments, the acquisition of all personal information requires the consent of the individual. If sensitive information is involved, the separate consent of the information subject is required, and the embodiments also need to be implemented with the authorization and consent of the object.

[0021] Please see Figure 1 , Figure 1 This is a flowchart illustrating the steps of an enhanced backscatter communication method based on movable antenna technology, as provided in Embodiment 1 of the present invention.

[0022] This invention provides an enhanced backscatter communication method based on movable antenna technology, comprising: Step 101: Obtain the basic parameters of the backscatter communication system, and construct the basic parameter model of the backscatter communication system based on the basic parameters of the backscatter communication system.

[0023] The basic parameters of a backscatter communication system refer to the set of raw data that comprehensively characterizes the hardware configuration, spatial layout constraints, electromagnetic scattering characteristics, and sensing and detection range of a mobile antenna backscatter communication system. These parameters include core basic data such as the area of ​​the object under test, the number of transmitting antennas, the number of receiving antennas, the fixed reflection coefficient of the scatterer, the fixed antenna impedance of the tag, the dynamically adjustable load impedance of the tag, the movable coordinate range of the transmitting antenna, the movable coordinate range of the receiving antenna, the minimum spacing constraints of the antennas, and the spacing between the transmitting and receiving arrays and dynamic load parameters. These parameters serve as the original input basis for building system models, conducting electromagnetic simulations, and performing channel calculations.

[0024] The backscatter communication system basic parameter model refers to a standardized digital electromagnetic calculation model adapted to the backscatter communication scenario of movable antennas, built based on the basic parameters of the backscatter communication system. The model uses a unified electromagnetic calculation coordinate system as the sole calculation reference, centrally integrates, assigns values ​​to and solidifies the core digital elements of the entire communication scenario. Specifically, it includes the spatial boundary coordinate parameters of the electromagnetic sensing area, the transmitter array size parameters and receiver array size parameters that define the specifications of the transceiver hardware, the initial position parameters of the transmitter antenna and receiver antenna that characterize the initial deployment state of the simulation, the target scattering parameters that uniformly characterize the scattering characteristics of the scenario, and the system position constraint parameters that constrain the spatial deployment rules of the antenna. It completely replicates all real physical scenario information such as the test space range, transceiver array hardware configuration, initial spatial position of the antenna, electromagnetic scattering characteristics of the environment and tags, and antenna deployment spacing constraints. It provides accurate, unified and callable standardized digital model support for subsequent CST electromagnetic simulation calculations, all-position voltage solutions, signal decoupling preprocessing, channel sensing calculations and channel optimization, and other full-process data calculations and signal processing work.

[0025] It should be noted that this step involves collecting various system basic data corresponding to the backscatter communication scenario, organizing and integrating parameters of different dimensions, assigning coordinate system values ​​and modeling, and completing the digital construction of the electromagnetic scenario and hardware constraints of the communication system. This provides a standardized model foundation and data support for subsequent all-position voltage simulation calculation, signal decoupling preprocessing, channel sensing calculation and channel optimization.

[0026] Further, step 101 may include the following sub-steps: S11. Delineate the electromagnetic sensing area based on the range of the object to be measured. S12. Configure the number of transmitting antennas and the number of receiving antennas as the transmitting array size parameter and the receiving array size parameter, respectively. S13. Generate the initial position parameters of the transmitting antenna within the movable coordinate range of the transmitting antenna, and generate the initial position parameters of the receiving antenna within the movable coordinate range of the receiving antenna. S14. Integrate the fixed reflection coefficient of the scatterer, the fixed antenna impedance of the tag, and the dynamically adjustable load impedance of the tag into target scattering parameters; S15. Set the minimum antenna spacing constraint and the transmit / receive array spacing as system position constraint parameters; S16. Establish an electromagnetic calculation coordinate system, and input and assign values ​​to the boundary coordinates of the electromagnetic sensing area, the scale parameters of the transmitting array, the scale parameters of the receiving array, the initial position parameters of the transmitting antenna, the initial position parameters of the receiving antenna, the target scattering parameters, and the system position constraint parameters into the electromagnetic calculation coordinate system to obtain the basic parameter model of the backscatter communication system.

[0027] The electromagnetic sensing region is an effective spatial area defined based on the range of the object under test. It is the exclusive spatial reference range for backscatter communication systems to carry out electromagnetic simulation calculations, signal sensing, and scattering parameter solving.

[0028] It should be noted that, firstly, based on the preset spatial boundary range of the target area, the effective electromagnetic sensing area for electromagnetic signal sensing and scattering calculation is precisely delineated. Then, the preset number of transmitting antennas and receiving antennas are configured one by one to correspond to the transmitting array scale parameters and receiving array scale parameters representing the hardware deployment specifications of the transmitting array. At the same time, based on the preset movable coordinate range of the transmitting antenna and the movable coordinate range of the receiving antenna, the initial position parameters of the transmitting antenna and the initial position parameters of the receiving antenna that conform to the deployment specifications are generated in the corresponding spatial intervals. Next, the fixed reflection coefficient of the scatterer in the scene, the fixed antenna impedance of the tag, and the dynamically adjustable load impedance of the tag are integrated and summarized to form the target scattering parameters that can uniformly characterize the electromagnetic scattering characteristics of the scene. At the same time, the minimum spacing constraint of the antenna and the spacing between the transmitting and receiving arrays are uniformly set as the system position constraint parameters that control the spatial deployment rules of the antenna. Subsequently, a dedicated electromagnetic calculation coordinate system is built, and the boundary coordinates of the electromagnetic sensing area, the scale parameters of the transmitting and receiving arrays, the initial position parameters of the transmitting and receiving antennas, the target scattering parameters, and the system position constraint parameters are all entered and assigned values ​​and matched one by one, completely replicating the real physical operation scenario of backscatter communication, and finally generating a standardized basic parameter model of the backscatter communication system.

[0029] Step 102: Based on the CST electromagnetic simulation software, perform all-position voltage calculations on the basic parameter model and basic parameters of the backscatter communication system, and output the all-position measurement voltage set of the transmit and receive array.

[0030] It should be noted that, based on the aforementioned completed backscatter communication system basic parameter model and corresponding backscatter communication system basic parameters, the CST (Computer Simulation Technology) electromagnetic simulation software is called to load the digital communication scenario and various system parameters. Electromagnetic field simulation calculations are carried out for all movable deployment positions of the transmitting and receiving antennas one by one. The full-domain voltage solution is completed by combining the electric field data conversion logic. The receiving voltage data corresponding to all antenna positions are summarized, and after regularization and integration, the full-position measurement voltage set of the transmitting and receiving array is generated and output.

[0031] Furthermore, step 102 may include the following sub-steps: S21. Extract the initial position parameters of the transmitting antenna, the initial position parameters of the receiving antenna, and the target scattering parameters from the basic parameter model of the backscatter communication system; S22. Using CST electromagnetic simulation software, electromagnetic field simulation is carried out based on the initial position parameters of the transmitting antenna, the initial position parameters of the receiving antenna, and the target scattering parameters to obtain the original data files corresponding to the incident field, the scattered field, and the total electric field. S23. Perform algorithm integration, data normalization and linear mapping on the original data files corresponding to the incident field, scattered field and total electric field in sequence to obtain the electric field distribution parameter set; S24. Substitute the nonlinear scattering field relationship corresponding to the electric field distribution parameter set into the preset Born approximation algorithm for simplification, establish a linear mapping relationship between the scattering electric field and the received voltage, and obtain the linearized received voltage calculation formula. S25. According to the movable coordinate range of the transmitting antenna and the movable coordinate range of the receiving antenna in the basic parameters of the backscatter communication system, control the transceiver array to traverse multiple movable positions. S26. Substitute the electric field data of each movable position into the linearized receiving voltage calculation formula to obtain the full-position measurement voltage set of the transmitting and receiving array.

[0032] The electric field distribution parameter set is a structured data set obtained by integrating, normalizing and linearly mapping the original data files of incident field, scattered field and total electric field output by CST electromagnetic simulation software. It contains the incident field, scattered field and total electric field distribution information of each discrete location point in the area to be measured, and provides a standardized data basis for the subsequent derivation of the relationship between scattered field and received voltage.

[0033] The linearized received voltage calculation formula is a linear mapping expression between the scattered electric field and the received voltage established by simplifying the nonlinear scattered field relationship through the Born approximation algorithm. It can be directly used to solve the received voltage based on the electric field data under different antenna positions and is the core calculation basis for generating the full-position measurement voltage set of the transmit-receive array.

[0034] The full-position measurement voltage set of the transmit and receive array is a set of full-scene receive voltage data obtained by solving the linearized receive voltage calculation formula after traversing all movable deployment positions of the transmit and receive antennas. It includes the receive voltage data of all transmit and receive antenna pairs in different spatial positions, providing complete and comprehensive raw data support for subsequent decoupling preprocessing.

[0035] The original data file corresponding to the incident field refers to the original simulation file generated by the CST electromagnetic simulation software based on the initial position parameters of the antenna and the scattering parameters of the target. The file completely stores the electromagnetic field data generated by the direct radiation of the transmitting antenna at the discrete sampling points of the test object area. It includes the amplitude and phase distribution information of the incident electric field at different spatial coordinate positions, and records the numerical variation law of the whole-domain incident field under different transmitting antenna deployment states. It does not contain the field components brought by environmental scatterers and communication tag reflections. It is the basic original data source for subsequent electric field data processing and linear relationship construction.

[0036] The original data file corresponding to the scattered field is a dedicated original data file output by CST electromagnetic simulation software. It specifically stores the electromagnetic field data formed by various scatterers and backscattering communication tags reflecting incident electromagnetic waves within the area under test. It covers the amplitude and phase parameters of the scattered electric field at each spatial discrete sampling point, and also includes the original values ​​of the field distribution corresponding to the environmental clutter scattering component and the tag electromagnetic reflection component, characterizing the inherent data features of the scene's electromagnetic scattering response.

[0037] The original data file corresponding to the total electric field is a comprehensive original simulation data file generated by CST electromagnetic simulation software. It stores the global electromagnetic field data after the incident field and the scattered field are superimposed and coupled within the area of ​​the object under test. It includes complete information on the amplitude and phase of the synthesized total electric field at each discrete spatial location point. It integrates all electromagnetic components of the direct radiation from the antenna and the scattering from the environment and the tag, and completely restores the electric field distribution state under the real physical scene. It provides complete original data support for the subsequent Born approximation algorithm to simplify the nonlinear scattering field relationship.

[0038] It should be noted that the novel ISAC system assisted by a mobile antenna proposed in this invention aims to maximize the sensing capabilities of the ISAC systems at both the transmitting and receiving ends. For example... Figure 2 As shown, the system consists of a transmitting array and a receiving array, configured respectively. and Two mobile antennas, both arrays of which are placed parallel above the object under test (DOI, Domain of Interest).

[0039] Furthermore, the first The transmitting antenna and the first The position of each receiving antenna can be determined by a three-dimensional spatial position vector. and describe. and These correspond to the range of motion of the transmitting and receiving antennas, respectively. The DOI area contains a scatterer with a fixed reflection coefficient and a tag whose reflection coefficient can be adjusted to achieve backscatter communication. In this system, the... Each transmitting antenna is located at a position (i.e., a discrete spatial location sampling point within the area of ​​the object to be measured). The incident field and scattered field generated at point are respectively expressed as: and Total electric field Represented as: (1) Scattering field and total electric field Since these electric fields cannot be directly measured in practice, they are converted into a measurable voltage at the output of the receiving antenna. Specifically, this is determined by the spatial position vector of the receiving antenna (or the observation point of the scattered field). The Scattered field generated by each transmitting antenna It can be represented as: (2) In the formula, The angular frequency of the emitted electromagnetic wave. The permeability of free space, for The scattering coefficient at that location, After discretizing the region of the object to be measured, the location points The corresponding area element, The reflectance coefficient of the scatterer at the location and the tag is denoted as... Green's function Let be denoted as and can be replaced by the electric field generated by the receiving antenna under unit excitation. Therefore, the measured voltage and the scattered electric field can be combined: (3) in, Indicates the first The scattered field generated by the first transmitting antenna is produced by the scattering field of the second transmitting antenna. The voltage received by each receiving antenna represents a single voltage sample in the voltage set measured at all positions of the transmitting and receiving array; These are relevant parameters of the receiving antenna, used to characterize its effective receiving characteristics (such as effective length or equivalent gain). They are proportional coefficients that convert the scattered electric field value into a measurable voltage, representing a linear mapping relationship between the scattered electric field and the received voltage. Indicates the unit incentive. The incident electric field of each receiving antenna. This invention uses the Born Approximation (BA) algorithm to calculate the total electric field. Approximate as incident electric field Therefore, the received voltage Depends only on the reflection coefficient This simplifies equation (3) into a linearized form (i.e., a linearized formula for calculating the received voltage): (4) One transmitting antenna and The received voltages of each receiving antenna at all locations are combined into a column vector. : (5) The linearized system matrix (sensing matrix) integrates parameters such as the Green's function, the incident field of the transmitting and receiving antennas, and the spatial discrete elements to establish the received voltage vector. With scattering coefficient vector The linear mapping relationship between them represents the matrix form of the linearized received voltage calculation formula; The scattering coefficients at discrete locations within the area to be measured are given by... The vector, which contains information on the fixed reflection coefficients of fixed scatterers within the scene and the adjustable reflection coefficients of backscattering tags, represents the vectorized form of the target scattering parameters. It is the accept voltage column vector. It consists of the reflection coefficients at each location. The measurement matrix... Divide into sub-matrices by column .here, and Each by the first The first transmitting antenna and the first The incident electric field generated by each receiving antenna at various locations within the DOI is represented as: and ; N The total number of sampling points in the spatially discretized region of the object to be measured; For the received voltage column vector Subvectors divided according to the transmit antenna dimension; For measurement matrix The corresponding number in the middle A sub-matrix of transmitting antennas; Submatrix The corresponding number in the middle The receiving antenna, the first The matrix elements (or sub-vectors) of each transmitting antenna; For the first The row vector composed of the incident electric fields generated by each transmitting antenna at all discrete sampling points in the DOI region is the incident electric field distribution data of the transmitting antenna in the entire test area, providing the electric field coupling parameters of the transmitting end for the construction of the measurement matrix; For the first The row vector composed of the incident electric fields generated by each receiving antenna at all discrete sampling points in the DOI region is the incident electric field distribution data of the receiving antenna in the entire test area, providing the electric field coupling parameters of the receiving end for the construction of the measurement matrix; Based on the above foundation, and building upon the previously constructed basic parameter model of the backscatter communication system, we first extract the initial position parameters of the transmitting antenna and the receiving antenna, as well as the target scattering parameters that integrate the reflection characteristics of fixed scatterers in the scene and the electromagnetic response of the backscattering tag. These parameters correspond to the initial deployment state of the mobile transceiver array in the system and the electromagnetic scattering characteristics within the DOI (Domain of Detection), providing a reference input for subsequent simulations. Next, we call the CST electromagnetic simulation software, load the aforementioned initial position parameters and target scattering parameters, and perform a full-domain electromagnetic field simulation on the incident field generated by the transmitting antenna within the DOI region, the scattered field formed by the reflection of scatterers and tags within the DOI region, and the total electric field formed by the superposition of the incident and scattered fields. The simulation outputs the original simulation file containing data for each field component, completely reproducing the electromagnetic propagation and scattering process under the initial positions of the transmitting and receiving antennas. Subsequently, the raw data files of the incident field, scattered field, and total electric field obtained from the simulation were processed. Through algorithmic integration, the field data from different locations and components were normalized and regularized, and a correlation mapping between field components was established. This generated an electric field distribution parameter set containing field distribution information for each discrete location within the DOI region, providing a standardized data foundation for the subsequent derivation of the relationship between the scattered field and the received voltage. Considering the inherently nonlinear relationship between the scattered field and the received voltage, the pre-defined Born approximation algorithm was used to simplify the nonlinear scattered field relationship corresponding to the electric field distribution parameter set. The total electric field within the DOI region was approximated as the incident field, eliminating the coupling effect of the scattered field. This established a linear mapping relationship between the scattered electric field and the received voltage, resulting in a linearized formula for calculating the received voltage that can be directly used for numerical calculations, solving the problem of the difficulty in directly solving nonlinear relationships. Then, based on the movable coordinate ranges of the transmitting and receiving antennas defined in the basic parameters of the backscatter communication system, the movable transceiver array was controlled to traverse multiple different deployment positions within its respective movement range, covering all feasible antenna spatial configurations of the system, ensuring that subsequent calculations can acquire voltage data across the entire scenario. Finally, the electric field distribution data corresponding to each movable position is substituted into the aforementioned linearized receiving voltage calculation formula to solve the receiving voltage of each transmit / receive antenna pair at different positions. The voltage data of all positions and all transmit / receive combinations are summarized and organized into a structured full-position measurement voltage set of the transmit / receive array, providing complete raw data support for subsequent decoupling preprocessing.

[0040] Step 103: Perform decoupling preprocessing on the full-position measurement voltage set of the transmit-receive array and output the decoupling receive voltage component set.

[0041] It should be noted that, following the previously obtained full-position measurement voltage set of the transmit and receive array, the data is systematically spliced ​​and standardized according to the transmit antenna number, receive antenna number, and corresponding position coordinate dimensions. At the same time, abnormal and invalid data that deviates from the normal value range are removed from the dataset. This results in a standardized linearized receive voltage parameter set. The scattering response components corresponding to the clutter scatterers in the test environment are extracted from this parameter set to determine the clutter scattering field parameters. Based on the definition of the preset tag reflection coefficient, the linearized receive voltage parameter set is split into scattering field modes to distinguish between tag structure mode scattering field parameters and tag antenna mode scattering field parameters. Then, the three types of field parameters are decoupled according to the division logic of structure mode components and antenna mode components to separate clutter combined voltage parameters and tag independent voltage parameters. After integrating and summarizing the two types of voltage parameters, the decoupled receive voltage component set is finally output.

[0042] Furthermore, step 103 may include the following sub-steps: S31. The full-position measurement voltage set of the transmit-receive array is sequentially spliced ​​and data regularized according to the transmit antenna number, receive antenna number, and position coordinates to obtain the regularized full-position measurement voltage set of the transmit-receive array. S32. Remove abnormal and invalid data from the normalized full-position measurement voltage set of the transmit and receive array to obtain a linearized receive voltage parameter set with a unified format. S33. Extract the scattering response components corresponding to the clutter scatterer in the environment under test from the linearized received voltage parameter set in a unified format, and determine the clutter scattering field parameters. S34. Based on the preset tag reflection coefficient definition, the linearized receiving voltage parameter set of the unified format is split into scattered field modes to separate the tag structure mode scattered field parameters and the tag antenna mode scattered field parameters. S35. Decouple the tag structure mode scattering field parameters, tag antenna mode scattering field parameters and clutter scattering field parameters according to the structure mode component and antenna mode component to obtain the clutter combined voltage parameters and tag independent voltage parameters. S36. Integrate the clutter combined voltage parameters and the tag-independent voltage parameters to obtain the decoupled receive voltage component set.

[0043] Clutter scattering field parameters are a set of scattering response components extracted from the linearized received voltage parameter set and generated by fixed clutter scatterers in the test environment. Specifically, they include the voltage components corresponding to the scattering fields generated by all non-tagged fixed scatterers (such as environmental obstacles and static objects) in the test area under different transceiver antenna combinations and different movable positions. Each component corresponds to a specific scatterer position, transceiver antenna identification, and spatial position information. The component values ​​in this set do not change with the load state of the backscattering tag and only characterize the electromagnetic scattering characteristics of the inherent clutter in the scene. They are the main component of fixed background noise in the received voltage.

[0044] The tag structure mode scattering field parameters are a set of scattering field component parameters obtained by decomposing based on the preset tag reflection coefficient definition. Specifically, they include the voltage components corresponding to the inherent scattering field of all backscattering tags in the test area under different transceiver antenna combinations and different movable positions, determined by the tag antenna physical structure (such as geometry, size, and material). Each component corresponds to a specific tag position, transceiver antenna identification, and spatial position information. The component values ​​in this set are not affected by the tag load impedance adjustment and are fixed inherent components in the tag scattering field. They do not carry any modulation information and belong to the received voltage background components that are unrelated to the tag load.

[0045] The tag antenna mode scattering field parameters are a set of scattering field component parameters obtained by decomposing based on the preset tag reflection coefficient definition. Specifically, they include the voltage components corresponding to the modulated scattering field of all backscattering tags in the test area under different transceiver antenna combinations and different movable positions, determined by the tag load impedance conditions. Each component corresponds to a specific tag position, transceiver antenna identification, and spatial position information. The component values ​​in this set change dynamically with the adjustment of the tag load impedance, carrying the data modulation information of backscatter communication. It is the core component in the received voltage that can be controlled and carries effective data, directly reflecting the tag's load modulation state.

[0046] The clutter combined voltage parameter is a set of voltage components formed by combining the clutter scattering field parameters and the tag structure mode scattering field parameters according to their corresponding positions and transceiver antenna combinations. Specifically, it includes all received voltage components in the area under test that are independent of the tag load impedance, i.e., the superposition result of environmental clutter scattering components and tag structure mode components. Each component corresponds to a specific transceiver antenna combination and spatial location information. The component values ​​in this set do not change with the tag load state and together constitute the fixed background noise part in the received voltage, which is completely separated from the modulated tag antenna mode components.

[0047] Tag-independent voltage parameters are a set of voltage components separated from the linearized received voltage parameters, consisting only of the voltage components corresponding to the tag antenna pattern scattering field. Specifically, they include modulated voltage components of all backscattering tags in the area under test under different transceiver antenna combinations and different movable positions. Each component corresponds to a specific tag position, transceiver antenna identification, and spatial location information. The component values ​​in this set change with the adjustment of the tag load impedance, carrying effective data information for backscatter communication. They are completely decoupled from clutter components and tag structure pattern components, and are not affected by fixed background noise. They are an effective signal source for subsequent sensing calculation and communication demodulation.

[0048] The predefined tag reflection coefficient is a standardized rule and benchmark specifically designed to define the electromagnetic reflection characteristics of backscatter communication tags. It fully covers the physical connotation, composition, value constraints, and field component relationships of the tag reflection coefficient. It clearly divides the overall tag reflection coefficient into a fixed reflection component determined by the antenna physical structure and an adjustable reflection component controlled by the external load impedance. It also defines the amplitude and phase change boundaries of the two types of components, establishes the mapping relationship between the tag structure mode scattering field, the antenna mode scattering field, and the corresponding reflection coefficient components, and standardizes the matching judgment rules of the reflection coefficient components in the linearized voltage data system. It can serve as a unified judgment standard for performing scattering field mode decomposition and distinguishing the tag's inherent scattering components from the linearized received voltage parameter set, providing theoretical and rule support for subsequent scattering field parameter separation and voltage component decoupling.

[0049] It should be noted that the tag includes a fixed antenna impedance. and dynamically adjustable load impedance The reflection coefficient can be changed by adjusting the load impedance of the tag. This modulates the tag's scattering field. The reflection coefficient is defined as follows: (6) When the When the antenna transmits, it carries a load impedance. tags The scattered field at point can be decomposed as follows: (7) in, Indicates the first Under the excitation of a single transmitting antenna, the position At the location, the load impedance is The total scattered field generated by the tag is composed of the superposition of the structure mode scattered field component and the antenna mode scattered field component, which fully characterizes the scattering response characteristics of the tag under specific load conditions. This represents the scattering field of the structure mode (i.e., the scattering field components of the structure mode). This represents the scattered field of the antenna mode. This represents the scattering current of the tag antenna (i.e., the current component of the antenna mode scattered field), while This represents the radiation field of the tag antenna under unit excitation. The structural mode components are unaffected by the load impedance and are determined solely by the antenna's physical characteristics (such as geometry). The antenna mode components depend on the load conditions and can be modulated to achieve data transmission in backscatter communication. Combining equation (7), the scattered field in equation (2) It can be represented as: (8) in, This represents the scattered field of the clutter scatterer (i.e., the scattered field component generated by the clutter scatterer). This represents the combined scattered field component formed by the superposition of the scattered field from the clutter scatterer and the scattered field from the tag structure mode, and both the scattered field from the scatterer and the scattered field from the tag structure mode can be written as a constant scattered field independent of the load impedance. .therefore, It can be broken down into: (9) in, The reflection coefficient represents the combination of clutter scatterer and tag structure mode components, while This represents the reflection coefficient of the tag antenna mode component. By substituting these reflection coefficients into equation (4), the received voltage can be decomposed. as follows: (10) in, and Let V represent the combined voltage of the clutter scatterer and the tag structure mode received at the i-th receiving antenna, and the voltage of the tag antenna mode, respectively. (11) (12) In summary, sensing and recognition can be achieved by measuring the received voltage and extracting the corresponding reflection coefficient. The physical form representing the combined voltage parameters of clutter. The physical form representing the tag's independent voltage parameters; Based on the above, the all-position measurement voltage set of the transmit-receive array is systematically spliced ​​and regularized according to the dimensions of transmit antenna number, receive antenna number, and antenna position coordinates. The received voltage data under different transmit / receive antenna combinations and different movable positions are organized into a unified structure, resulting in a regularized all-position measurement voltage set of the transmit-receive array. This process gives the originally scattered voltage data of the entire scene a unified organizational format, facilitating the subsequent extraction and processing of different scattered field components. Then, abnormal and invalid data are removed from the regularized voltage set, eliminating invalid measurement data that deviates from the normal numerical range, resulting in a linearized received voltage parameter set with a unified format and reliable data. This provides standardized basic data for subsequent scattered field mode decomposition and decoupling. Next, from this linearized received voltage parameter set, the scattering response components corresponding to fixed clutter scatterers in the test environment are extracted. These components are generated by other fixed scatterers in the scene besides the backscattering tag and are independent of the tag's load state, thus determining the clutter scattering field parameters. Finally, based on the preset tag reflection coefficient definition, combined with the tag... Based on the inherent decomposition characteristics of the tag's scattered field, the linearized received voltage parameter set is decomposed into scattered field modes, separating the scattered field components corresponding to the tag into two types of parameters: one type is the tag structure mode scattered field parameter, which is determined by the tag antenna physical structure and is unaffected by the load impedance; the other type is the tag antenna mode scattered field parameter, which is determined by the tag load conditions and can be modulated by adjusting the load impedance. Furthermore, the clutter scattered field parameters, tag structure mode scattered field parameters, and tag antenna mode scattered field parameters are decoupled based on the load independence and moduliability of the components. The clutter scattered field and tag structure mode scattered field are both fixed components independent of the tag load and can be combined into clutter combined voltage parameters, while the tag antenna mode scattered field is a moduliable independent component, forming tag-independent voltage parameters. Finally, the decoupled clutter combined voltage parameters and tag-independent voltage parameters are integrated to obtain a decoupled received voltage component set. This component set achieves complete separation of environmental clutter components and tag moduliable components, providing purified and effective data support for subsequent sensing and calculation.

[0050] Step 104: Perform sensing calculation on the decoupled received voltage component set and output the backscatter communication dedicated channel matrix.

[0051] The backscatter communication dedicated channel matrix is ​​a standardized structured matrix formed by sensing and solving modeling. The matrix contains electromagnetic propagation coupling characteristic parameters corresponding to different combinations of transmitting and receiving antennas. It has eliminated the interference caused by environmental clutter and fixed structure components of tags, and is fully adapted to the signal transmission and feature analysis business scenarios of backscatter communication. It can provide standardized and reliable matrix data support for subsequent communication signal demodulation and link quality analysis.

[0052] It should be noted that, based on the decoupled received voltage component set obtained from the aforementioned processing, and using the voltage parameters that have completed the separation of clutter and tag components, the sensing calculation processing is carried out in combination with the backscattering electromagnetic propagation coupling law. Based on the deployment location of the transmitting and receiving antennas, the spatial distribution characteristics of the area to be measured, and the correlation characteristics of the decoupled voltage components, the mapping relationship between the antenna link and electromagnetic scattering is deduced and established. Then, the link coupling relationship is integrated and modeled through dimension regularization and structured arrangement, and finally, a backscattering communication dedicated channel matrix adapted to the service requirements is generated and output.

[0053] Furthermore, step 104 may include the following sub-steps: S41. Construct a sparse reconstruction optimization model based on the decoupled received voltage component set; S42. Iteratively solve the sparse reconstruction optimization model to obtain the sparse reflection coefficient results; S43. Split the sparse reflectance coefficient results and output the combined reflectance coefficient vector and the label-independent reflectance coefficient vector; S44. Based on the combined reflectance coefficient vector and the tag-independent reflectance coefficient vector, determine the target localization and tag recognition result set; S45. Extract the spatial location information of the identified tags from the target localization and tag recognition result set; S46. Based on the spatial location information of the identified tags, determine the channel vector of the identified tags; S47. Construct a dedicated channel matrix for backscatter communication based on the channel vectors of the identified tags.

[0054] The sparse reflection coefficient results are obtained by iteratively solving the sparse reconstruction optimization model to obtain the reflection coefficient estimation set of each discrete location point. It has non-zero values ​​only at the locations of clutter scatterers and tags, and zero values ​​at other locations, showing obvious sparse characteristics. It fully contains the reflection characteristic information of all scatterers and tags in the scene.

[0055] The combined reflection coefficient vector is a vector composed of reflection coefficients jointly contributed by clutter scatterers and tag structure mode components. It is a component obtained by splitting the sparse reflection coefficient results and characterizes the inherent scattering characteristics of the scene that are independent of the tag load. It can be used to locate the spatial positions of clutter scatterers and tags.

[0056] The tag-independent reflection coefficient vector is a vector composed only of the reflection coefficients contributed by the tag antenna mode components. It is a component obtained by splitting the sparse reflection coefficient results, characterizing the effective scattering characteristics of the tag that can be modulated by the load. It is independent of the environmental clutter scatterer and can be used to distinguish the tag from the surrounding clutter.

[0057] The target localization and tag recognition result set contains a structured dataset of clutter scattering object location information, tag location information, and tag recognition results within the area to be tested. It is determined by the combined reflection coefficient vector and the tag-independent reflection coefficient vector, thus realizing the distinguishable localization of clutter scattering object and tag.

[0058] The channel vector is a set of electromagnetic propagation coupling characteristic parameters between a single identified tag and each antenna of the transceiver array. It is calculated based on the spatial location of the identified tag and the deployment location of the transceiver antennas. It contains the transmission characteristic information between the tag and each transceiver antenna and is the basic unit for constructing a dedicated channel matrix for backscatter communication.

[0059] It should be noted that, according to equation (6), the open-circuit and short-circuit states can be achieved by adjusting the load impedance of the tag, thereby obtaining two pilot signals. and According to equation (10), the received voltages of these two pilot signals are as follows: (13) (14) in, The reflection coefficient of the tag in the open-circuit state is +1. It is the pilot signal state used to construct the reference receiving voltage in backscatter communication, corresponding to the electromagnetic reflection characteristics of the tag when there is no load. The reflection coefficient of the tag under short-circuit load conditions is -1, which is related to... The other pilot signal state used in conjunction corresponds to the electromagnetic reflection characteristics when the tag load is directly short-circuited. The two are used together to separate the clutter component from the tag modulation component. Therefore, based on equations (13) and (14), the following conclusions can be drawn: (15) (16) For the first The transmitting antenna and the first With one receiving antenna combination, the tag reflection coefficient is The received voltage measured at +1 includes the combined components of clutter and tag structure patterns, as well as the superposition of tag antenna pattern components. It serves as one of the benchmark samples for constructing decoupled voltage components. For the first The transmitting antenna and the first With one receiving antenna combination, the tag reflection coefficient is The received voltage measured at =-1 includes the combined component of clutter and tag structure mode minus the tag antenna mode component, and... To facilitate component solution, This is the received voltage vector corresponding to the clutter scatterer and the tag structure mode component, representing the voltage vector under different transmit / receive combinations. The column vectors formed by sequential arrangement represent the vectorized form of clutter combined voltage parameters, characterizing the overall distribution of unmodulated voltage components independent of the tag load in the scenario; firstly... It can be used to locate clutter scatterers and tags. According to equation (5), a linear equation relating the received voltage and the reflection coefficient can be obtained: (17) The reflection coefficient vector within the region of the object under test is jointly contributed by clutter scatterers and tag structure mode components. It needs to be derived from... reconstruction The general method is to calculate the matrix. The inverse of . However, since the observation data at the transmitting and receiving ends are not completely independent, this means that the matrix Typically, it is irreversible. Since clutter scatterers are sparsely distributed within the DOI region, the corresponding reflection coefficient vector is also inherently sparse. For targets or scatterers with sparse characteristics, compressed sensing algorithms can be used to effectively solve underdetermined equations. Therefore, for the sparse reconstruction optimization model, the recovery of reflection coefficients can be reformulated as an optimization problem based on sparse reconstruction: (18) To further improve the sparse signal reconstruction performance, this invention employs a two-step iterative shrinkage / thresholding algorithm (TwIST). In each iteration, the estimated reflection coefficients are updated through shrinkage and thresholding operations; TwIST reconstructs the sparse reflection coefficient vector. Because... This represents the combination of the clutter scatterer reflection coefficient and the tag structure mode components, recovering the... It can locate scatterers and tags. However, in cluttered scattering environments, simply recovering... This is insufficient to identify the label. Therefore, further reconstruction is necessary. This allows the label to be distinguished from the surrounding clutter.

[0060] (19) This is the received voltage vector corresponding to the tag antenna mode component. The recovered value is the reflection coefficient vector within the region of the object under test, derived solely from the reflection coefficient vector corresponding to the tag antenna mode components. This represents the reflection coefficient that is only related to the tag antenna mode and is independent of other clutter scatterers. Therefore, by utilizing... It can accurately identify tags even in highly cluttered scattering environments.

[0061] Furthermore, after completing the sensing and identification phases, the tag enters the backscatter communication phase, generating multiple reflection coefficient states by dynamically modulating the tag's load impedance. These reflection states are mapped to The symbol of the meta-constellation is used to achieve efficient backscatter communication.

[0062] Consider a In a backscatter communication scenario consisting of multiple tags, the load impedance dependence characteristic can be utilized to effectively eliminate the influence of load impedance on the received signal. This mitigates the influence of clutter scatterers and tag structural modes, thereby suppressing interference. Therefore, the backscattered signal at the receiver can be expressed as: (20) in, For the first The reflection coefficient state generated by each tag during the communication phase corresponds to the modulation symbol sent by that tag; The total number of backscatter tags deployed in the backscatter communication scenario represents the tag scale in the multi-tag communication scenario. The backscattered signal vector at the receiver is formed by superimposing the reflected signals from multiple tags and adding noise; it is the baseband signal vector collected by the receiver. This represents Additive White Gaussian Noise (AWGN). It is derived from the measured channel matrix. Extracting the channel vector corresponding to the location of the identified tag allows us to construct a modified channel matrix. To describe the general case of multi-tag communication, all symbols sent by all tags are uniformly represented as symbol vectors. .right Apply a normalized power constraint, such that Since the average energy of each transmitted signal vector is Therefore, the communication model in equation (20) can be simplified to: ;(twenty one) For multi-tag unified symbol vectors, in the ESM (Enhanced Spatial Modulation) framework, the transmission mode is determined by index bits. When only one tag is activated, the number of available tag activation combinations is equal to... When two tags are activated simultaneously and two symbols selected from the first set of secondary constellation diagrams are transmitted independently, the number of valid tag-constellation combinations is: Similarly, when transmitting two symbols selected from the second set of secondary constellations, the number of effective combinations remains the same. Therefore, the total number of combinations of tag activation and constellation can be expressed as: ;(twenty two) This represents the total number of combinations of tag activation modes and constellation types; in the ESM scheme, the input information bits are divided into index bits and modulation bits. The number of index bits is... These bits are mapped to the combined index. This index is used to retrieve from a predefined index. Choose one combination from the given combinations to determine the subset of activated tags and the corresponding constellation type. For a given combination, utilize... Each modulation bit generates a constellation symbol. Based on this, a transmission signal vector is constructed. .when At this time, the system is in single-tag activation mode, where only one tag is activated to send symbols from the main constellation, denoted as . , M This refers to the modulation order of the constellation, which is the number of symbols in the constellation diagram. s It is a constellation symbol. When At this time, the system switches to dual-tag activation mode, activating two tags simultaneously to send two symbols from the secondary constellation, denoted as... Therefore, the spectral efficiency of ESM is expressed as: ;(twenty three) To determine the spectral efficiency of the ESM scheme; at the receiver, a maximum likelihood (ML) detector is used to estimate the transmitted index and symbol components: ;(twenty four) The combined index is estimated by the maximum likelihood detector at the receiver. The constellation symbol is estimated by the maximum likelihood detector at the receiver; if the transmitted signal Incorrectly detected as Given a channel matrix The conditional pairwise error probability is: (25) in Gauss function, It is noise power. and They represent the corresponding and The noiseless received signal vector, This is the transmitted signal vector obtained from error detection at the receiving end. Using the joint delimitation technique, the conditional bit error probability can be expressed as: (26) in, This represents the conditional bit error probability (upper bound of the system bit error rate) of the ESM scheme. The Hamming distance between the transmitted signal vector and the error detection signal vector, i.e., the number of different bits between them, is a weighting coefficient used to calculate the bit error probability. express and The number of different positions between them.

[0063] Based on the above foundation, and relying on the decoupled received voltage component set obtained from the aforementioned processing, the clutter-tag structure mode combined voltage component, which is independent of the tag load, and the independent voltage component contributed only by the tag antenna mode are first separated from the component set. Combining the sparsity characteristics of clutter scatterers and tag distribution in the backscattering scenario, a sparse reconstruction optimization model based on compressed sensing theory is constructed. This transforms the reflection coefficient recovery problem into a sparse optimization solution form of an underdetermined linear equation system, overcoming the difficulty of direct solution caused by the non-invertibility of the system matrix. Subsequently, a two-step iterative shrinkage / threshold algorithm is used to iteratively solve the sparse reconstruction optimization model. In each iteration, the estimated value of the reflection coefficient is updated through shrinkage and threshold operations, ultimately obtaining sparse reflection coefficient results that exhibit non-zero values ​​only at the locations of clutter scatterers and tags. Then, according to the preset scattering field component partitioning rules, the sparse reflection coefficient results are split, separating the combined reflection coefficient vector contributed by both clutter scatterers and tag structure mode components, and the tag-independent reflection coefficient vector contributed only by the tag antenna mode component. The vectors represent the inherent scattering characteristics of the scene independent of the tag payload and the effective scattering characteristics modulated only by the tag payload, respectively. Then, based on the combined reflection coefficient vector, the spatial positions of clutter scatterers and tags within the target area are located. Next, by combining the component characteristics of the tag's independent reflection coefficient vector, the tags are distinguished from the surrounding clutter, forming a target localization and tag identification result set containing the clutter scatterer positions, tag positions, and tag identification results. Successfully identified backscattering tags are selected from the target localization and tag identification result set, and their corresponding spatial position information is extracted to provide a positional reference for subsequent channel vector determination. Combining the deployment positions of the transceiver antennas and the spatial positions of the identified tags, the channel response corresponding to the identified tag positions is extracted from the measured system channel matrix to determine the channel vector corresponding to each identified tag. Finally, the channel vectors of all identified tags are arranged in a regularized manner according to the transceiver antenna number and tag position, integrating them to form a dedicated backscattering communication channel matrix, providing reliable channel support for subsequent backscattering communication signal transmission and demodulation.

[0064] Step 105: Optimize the backscatter communication dedicated channel matrix based on the basic parameters of the backscatter communication system, and output the target backscatter communication dedicated channel matrix. The target backscatter communication dedicated channel matrix is ​​used to realize backscatter communication.

[0065] The target backscatter communication dedicated channel matrix is ​​a standardized channel matrix obtained by optimizing the channel based on the basic parameters of the backscatter communication system. It completes parameter deviation correction, link gain equalization and redundant component cleanup on the basis of the original channel matrix. The internal parameters of the matrix fully match the system deployment constraints and electromagnetic communication performance indicators, and can directly carry the link mapping, signal transmission and data demodulation related operations in the backscatter communication process.

[0066] It should be noted that, using the established basic parameters of the backscatter communication system as constraints and optimization criteria, and referring to the system antenna layout specifications, electromagnetic transmission characteristics, and link adaptation requirements, the established backscatter communication dedicated channel matrix is ​​optimized by parameter correction, link equalization, and removal of redundant and invalid components. The parameter deviations within the matrix are corrected and the overall data structure is regularized. After optimization, the target backscatter communication dedicated channel matrix that meets the system performance indicators is output, providing a compliant and usable channel foundation for the subsequent formal launch of backscatter communication services.

[0067] Furthermore, step 105 may include the following sub-steps: S51. Extract the movable coordinate range of the transmitting antenna, the movable coordinate range of the receiving antenna, the minimum spacing constraint of the antenna, and the spacing between the transmitting and receiving arrays from the basic parameters of the backscatter communication system as position constraint parameters. Then, with the goal of maximizing the sensing capacity, use the preset PSO particle swarm optimization algorithm to iteratively optimize the positions of the transmitting antenna and the receiving antenna to obtain the target antenna position vector. S52. Optimize the backscatter communication dedicated channel matrix based on the target antenna position vector to obtain the target backscatter communication dedicated channel matrix.

[0068] It should be noted that the backscatter communication dedicated channel matrix Playing a crucial role in the entire system, it describes both the relationship between the measured voltage (generated by the scattering field of the tag and surrounding clutter) and the associated reflection coefficient, and provides Channel State Information (CSI) obtained during the identification phase. To quantitatively evaluate the system's imaging performance, this invention employs the concept of sensing capacity. By performing Singular Value Decomposition (SVD) on the measurement matrix and utilizing the obtained eigenvalues, the sensing capacity is: (27) in, C To sense capacity, Representation matrix The maximum normalized non-zero eigenvalues ​​obtained after Singular Value Decomposition (SVD) and , This represents the signal-to-noise ratio. The concept of sensing capability is similar to channel capacity in communication theory. (Matrix) eigenvalues This is a key parameter; the more non-zero eigenvalues ​​a system has, the greater its sensing capability. This invention studies the joint optimization of the positions of the transmitting and receiving antennas. Therefore, the problem of maximizing sensing capacity can be formulated as: (28) (29) (30) (31) (32) in, Let be the antenna position vector, containing the position information of all transmitting and receiving antennas, and it is a variable in the sensing capacity maximization optimization problem; For the first m t The position vectors of the transmitting antennas; For the first m r The position vectors of the transmitting antennas; This refers to the movable area of ​​the transmitting antenna; This refers to the movable area of ​​the receiving antenna; D This is the minimum distance threshold between antennas; This refers to the number of transmitting antennas; This refers to the number of receiving antennas; Constraints (29) and (30) restrict the movable regions of the transmitting and receiving antennas, respectively. (31) and (32) mitigate antenna coupling effects by limiting the minimum distance between antennas to no less than a certain value. This optimization problem is highly non-convex, making it difficult to solve directly. Furthermore, the solution space of the APV (Antenna Position Vector) is typically very large. To address this, we developed an APV optimization algorithm based on Particle Swarm Optimization (PSO).

[0069] In the proposed PSO algorithm, only the antenna position is considered. and The coordinates need optimization. First, initialize them randomly. There are 1 particle, and its position is 1. The speed is Each of these represents a feasible implementation of APV, namely: (33) (34) (35) in, K The total number of particles in the particle swarm; This represents the initial set of positions for the particle swarm. This represents the initial velocity set of the particle swarm. Indicates the first Initial APV values ​​(antenna position vector) for each particle. Indicates the first The initial value of the emission APV of each particle (i.e., the initial position vector of the transmitting antenna). Indicates the first The initial APV value of each particle (i.e., the initial position vector of the receiving antenna). For the first k The first particle m t Initial of each transmitting antenna x, y coordinate, , For the first k The first particle m r Initial of each receiving antenna x, y Coordinates. Furthermore... , and This ensures that the initial position of each movable antenna is within the movable area, i.e. (29) and (30). It is the distance between the transmitting array and the receiving array. A This is the side length parameter of the movable area of ​​the antenna.

[0070] During the iteration process, each particle relies on its individual experience (the known local optimum, i.e., the first...) to determine its position. k The individual historical best position of each particle ) and swarm experience (the known global optimal position, i.e., the global historical optimal position of the particle swarm) The particle adjusts its motion based on the overall situation. Specifically, for each iteration, the velocity and position of each particle are updated as follows: (36) (37) in, For the first k The particle in the first t The velocity vector at each iteration determines the update step size and direction of the particle's position; For the first k The particle in the first t Position vector at the next iteration (APV configuration); Inertial weight; For position projection operators; T This represents the maximum number of iterations for the algorithm. Indicates the current iteration index. and These represent the individual learning factor and the global learning factor, respectively; their magnitudes determine the step size by which a particle moves toward its individual historical best position and its global historical best position. These are two independent random variables used to enhance the randomness of the search process and enable the algorithm to escape local optima. To achieve a balance between search speed and solution accuracy, the inertia weight gradually decreases with each iteration, specifically in the following manner: (38) This represents the maximum number of iterations. To strictly satisfy constraints (29) and (30), if a particle moves beyond the boundary of the movable region, its position component will be projected to the corresponding minimum or maximum allowable value: (39) The fitness of each particle is evaluated based on Equation (27) and used to maximize the perception capability of any given APV. Furthermore, to ensure that constraints (31) and (32) are satisfied, we introduce an adaptive penalty factor into the fitness function, defined as follows: (40) in, For the first k The particle in the first t The fitness function value at the next iteration; Represents a collection of current APVs All violations of the predefined minimum spacing constraint The set of movable antenna pairs, defined as follows: (41) This is a large positive penalty parameter, designed to significantly reduce the fitness value of particle configurations containing movable antenna pairs that violate the distance constraint. As shown in Table 1, during the iterative selection process, particles that fail to meet the constraints are eliminated due to their low fitness. The algorithm guides the particle swarm to a feasible solution region that meets the minimum distance requirement, eventually reducing the number of movable antenna pairs that violate the constraint to zero. After evaluating the fitness of each particle, the local optimal position of each particle and the global optimal position of the entire swarm are continuously updated, iterating until the convergence condition is met. Ultimately, the optimal position among all particles can be considered an approximate optimal solution to the APV problem.

[0071] Table 1. PSO-based algorithms used to solve the problem.

[0072] Algorithm 1 provides the overall process for solving (28) using a PSO-based algorithm. During the initialization phase, the position and velocity information of most particles are... Random initialization is performed within the dimensional search space, with each component uniformly distributed within its respective feasible region. Furthermore, to improve the algorithm's feasibility, the APV of some particles is initialized based on geometric configurations, such as uniform planar arrays or circular arrays, ensuring that the minimum spacing between antennas is not less than [value missing]. This ensures that at least a portion of the particles in the swarm have non-negative fitness.

[0073] In lines 2–3, each particle is evaluated using a fitness function to determine its local and global optimum positions. In line 5, the inertia weights increase from a maximum value as the number of iterations increases. linearly decrease to minimum value In line 7, the velocity and position of each particle are updated based on its local and global best positions, guiding the particles to explore the feasible solution space. Subsequently, in lines 8 to 14, the fitness of each particle is evaluated, and the results are compared with the fitness values ​​of the local and global best positions. If the current particle has a better fitness value, its local or global best position is updated accordingly. From lines 4 to 16, the global optimal solution is continuously optimized, and its fitness value maintains a monotonically increasing trend throughout the iteration. Since the objective function of problem (28) is inherently bounded, the convergence of the PSO-based algorithm is guaranteed. Thus, the original problem (28) is effectively solved.

[0074] Specifically, after constructing the dedicated channel matrix for backscatter communication, constraints for antenna position optimization are extracted based on the basic configuration parameters of the backscatter communication system. These constraints include the movable coordinate range of the transmitting antenna, the movable coordinate range of the receiving antenna, the minimum spacing requirement between all antennas, and the spacing between the transmitting and receiving arrays, providing clear boundary constraints for antenna position optimization. This scheme aims to maximize the system's sensing capacity. Sensing capacity is a core indicator for evaluating the system's imaging and sensing performance, and its concept is similar to channel capacity in communication theory. It is calculated based on the characteristics of the system's measurement matrix and reflects the system's overall sensing capability of the target scene; the more non-zero eigenvalues, the stronger the system's sensing capability. Since the joint optimization problem of the transmitting and receiving antenna positions is highly non-convex and the feasible solution space is large, direct solutions are difficult. Therefore, a pre-defined particle swarm optimization (PSO) algorithm is used to iteratively optimize the antenna positions.

[0075] In particle swarm optimization, the particle swarm is first initialized, with each particle representing a set of feasible antenna location configurations, targeting only the antennas. x, yThe coordinates are optimized, and the initial positions of all particles are randomly generated based on the movable range, ensuring that the initial positions of both the transmitting and receiving antennas fall within the allowed area. During the iteration process, each particle adjusts its motion state based on its historical best position and the global best position of the particle swarm. Simultaneously, an inertial weight that decays linearly with the number of iterations is introduced to balance the algorithm's global exploration capability and local exploitation capability, preventing premature entrapment in local optima. To strictly satisfy the antenna position constraints, when a particle's position component exceeds the boundary of the movable area, it is automatically projected to the corresponding allowed value. Furthermore, in the particle fitness evaluation stage, sensing capacity is used as the core evaluation metric, and an adaptive penalty mechanism is introduced to reduce the fitness value of configurations that violate the minimum antenna spacing constraint, guiding particles to move towards a feasible solution region that satisfies all constraints. The iteration process continues until a preset convergence condition is met, ultimately yielding the target antenna position vector that maximizes the system's sensing capacity.

[0076] The target antenna position vector obtained through iterative solution using the particle swarm optimization algorithm strictly satisfies the boundary constraints of the movable areas of the transmitting and receiving antennas, the minimum spacing constraints between all antennas, and the spacing requirements of the transceiver arrays. This represents the optimal antenna configuration that maximizes the system's sensing capacity. First, the three-dimensional coordinate information of all transmitting and receiving antennas is extracted from this vector to clarify the spatial geometric positional relationship of each pair of transmit-receive antenna links. Combining this with the propagation environment characteristics of the backscattering system, the path loss, free-space propagation delay, and inter-antenna coupling attenuation parameters for each link are recalculated to construct an updated system measurement matrix. This matrix retains the original matrix's ability to describe the mapping relationship between measurement voltage and reflection coefficient, while also mitigating channel interference caused by antenna coupling effects through optimal antenna positions. Furthermore, based on this updated measurement matrix, the channel state information obtained during the identification phase is extracted, including the channel gain, phase offset, and signal-to-noise ratio parameters of each link. Emphasis is placed on enhancing the signal-to-noise ratio parameters of the identified backscattering tags. The backscatter communication-specific channel matrix is ​​optimized and corrected based on the updated measurement matrix and channel state information. This corrects the channel estimation error caused by excessive link path loss and significant coupling effect under the initial antenna position configuration, eliminates redundant clutter components introduced by non-optimal antenna positions, and optimizes the eigenvalue distribution of the measurement matrix by singular value decomposition to maximize sensing capacity. This ensures that the sensing capacity corresponding to the corrected channel matrix reaches the preset maximum value, eliminating the impact of insufficient sensing capability under the initial configuration on subsequent communication demodulation. Finally, a target backscatter communication-specific channel matrix adapted to the optimal antenna configuration is obtained. This matrix has purer tag-related channel components, lower link estimation error, and higher system sensing capacity, which can provide more reliable and accurate channel support for multi-tag signal transmission and demodulation in the subsequent backscatter communication stage, effectively reducing the bit error rate and improving the overall performance of the communication system.

[0077] It is worth mentioning that antenna position optimization, scatterer / tag sensing and identification, and communication channel matrix calibration are carried out simultaneously. The data obtained after antenna position optimization and simulation can be used for sensing and identification and communication channel matrix calibration.

[0078] Furthermore, regarding the simulation results and analysis, Figure 3 The convergence performance of the APV optimization algorithm in a backscattering ISAC system assisted by a movable antenna is demonstrated. As the number of iterations increases, the system's sensing capability gradually improves and stabilizes after 250 iterations, showing rapid convergence and thus verifying the convergence of Algorithm 1. Furthermore, the red curve tracks the penalty value corresponding to the particle with the best sensing capability output by the algorithm. This value remains zero after 200 iterations, indicating that the minimum spacing constraint is satisfied.

[0079] Figure 4 The comparison of sensing capacity under different numbers of antennas is shown. FPA scheme: Both the transmit and receive arrays consist of uniform linear arrays. APS scheme: The movable area is quantized into discrete positions spaced at half-wavelength intervals. An Alternating Position Selection (APS) method is used, alternately selecting the position of each movable antenna while keeping the positions of other movable antennas fixed.

[0080] Overall, the sensing capacity of all three schemes increases with the number of antennas, but the growth rate slows significantly once the number of antennas exceeds a certain threshold. This is because within a fixed array area, a smaller number of antennas is sufficient to adequately sample spatial channel variations and effectively utilize diversity gains. Further increasing the number of antennas leads to increased interference between antennas, thus slowing down the improvement in sensing capacity. The PSO-based scheme significantly outperforms the traditional FPA (Fixed Position Antennas) and APS schemes. By jointly optimizing the positions of all movable antennas in a continuous spatial domain, the PSO-based scheme can make fuller use of spatial degrees of freedom, thereby achieving the same sensing capability with fewer antennas.

[0081] Figure 5 The comparison of sensing capabilities under different transmit and receive array spacings is shown. The results indicate that the PSO-based scheme still outperforms all other schemes. It was observed that the sensing capabilities of the PSO and APS schemes gradually decrease with increasing array spacing, while the sensing capability of the FPA array is less affected by the array spacing. Considering both optimal sensing capability and inter-antenna coupling, half a wavelength was ultimately chosen as the array spacing for subsequent experiments.

[0082] Figure 6 The comparison of sensing capabilities under different normalized region sizes is shown. It can be observed that the sensing capabilities achieved by the PSO and APS schemes increase at a decreasing rate as the normalized region size increases. This is because a larger mobile region provides greater flexibility for the movable antenna to adjust its position, thus enabling a more comprehensive exploration of the spatial degrees of freedom of the electromagnetic field. However, the resolvable variations in the spatial electromagnetic field are limited due to the finite number of physical scattering paths between the transmitting and receiving arrays. When the mobile region is sufficiently large, the movable antenna has already adequately sampled and utilized the diversity of spatial channel variations. Therefore, the sensing capability no longer increases significantly with region size but tends to saturate. In contrast, the sensing capability of the FPA scheme decreases with increasing normalized region size, due to the increased spacing between the transmitting and receiving arrays.

[0083] To evaluate the quality of the reconstructed image, this invention employs two metrics: Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM). Generally, a higher PSNR value or an SSIM value closer to 1 indicates better reconstructed image quality. To verify the system's perception and recognition capabilities, we tested the reconstruction results as follows: Figure 7 As shown in the figure, the white rectangle represents the true boundary of the clutter scatterer, while the red rectangle represents the true boundary of the tag. The tag uses a copper dipole antenna with a radius of 10 mm and a height of 56.5 mm.

[0084] This configuration considers the performance of two adjacent tags with different spacing to evaluate the system's ability to distinguish densely deployed tags. The scenario also introduces another copper scatterer of the same size as the tag, and the corresponding perception and recognition results are as follows: Figure 7 As shown. Figure 7 As shown in (a), the energy response regions of the two tags partially overlap. However, the system is still able to accurately locate the positions of both tags and the scatterer. Furthermore, as... Figure 7 (c) Figure 7 As shown in (d), the system can also identify any label individually in dense scenes.

[0085] The experimental results demonstrate that the proposed system is accurate and reliable in target localization and identification tasks, whether handling single-tag or multi-tag complex scenarios. By effectively combining backscattering technology with movable antenna technology, the system can not only accurately distinguish between targets and clutter, but also exhibits a certain degree of fault tolerance and resolution when facing the challenge of signal aliasing caused by reduced tag spacing. This verifies its practical potential and reliability in complex electromagnetic environments.

[0086] Next, Monte Carlo simulations were performed to evaluate the bit error rate (BER) performance of a mobile antenna-assisted backscatter communication system employing Enhanced Spatial Modulation (ESM). First, the simulated BER results were compared with the derived theoretical upper bound to validate the adopted analytical framework and simulation model. Second, to illustrate the performance advantages of the ESM scheme, a comparative study was conducted against three alternative spatial modulation techniques—Quadrature Spatial Modulation (QSM), Spatial Modulation (SM), and Generalized Spatial Modulation (GSM)—under the same spectral efficiency.

[0087] In the proposed inverse scattering communication framework, Figure 8 The bit error rate (BER) performance of ESM, QSM, SM, and GSM was compared at a spectral efficiency (SE) of 8 bits / second / Hz. This scheme uses four tags. ESM's BER performance in the low signal-to-noise ratio (SNR) region is comparable to other schemes, while it exhibits a significant performance advantage in the high SNR region. This performance improvement mainly stems from the joint optimization of index modulation and constellation design in ESM. ESM transmits twice the number of index bits compared to SM and GSM by combining active tags and constellation. This allows ESM to achieve the same spectral efficiency using a lower-order constellation modulation. Although QSM transmits the same number of index bits as ESM and uses the same constellation as ESM's primary constellation, ESM uses a lower-order constellation in its secondary modulation scheme; therefore, ESM outperforms QSM in bit error rate performance.

[0088] For comparison of technical effectiveness, existing technologies can be referenced. Current research integrates positioning into backscatter communication systems, but traditional methods are susceptible to multipath and non-line-of-sight propagation, making it difficult to achieve high-precision positioning. Backscatter reconstruction, by processing electromagnetic scattering data to reconstruct the physical properties of the target region, has become a promising alternative. However, this problem is inherently nonlinear and ill-posed. To address this, researchers have proposed different algorithms: under weak scattering conditions, linear methods such as the Born approximation and Rytov approximation are used; under high contrast conditions, iterative linearization methods such as the distortion Born iteration method and the distortion Rytov iteration method are used to improve reconstruction accuracy and stability.

[0089] Multiple-input multiple-output (MIMO) technology enables spatial multiplexing, which is key to improving communication capacity and reliability. However, traditional MIMO uses fixed-position antennas, whose fixed spatial configuration makes it difficult to adapt to complex environments and limits the full utilization of spatial freedom. To address this, movable antenna technology has been developed. This technology allows movable antennas to dynamically adjust their positions within a certain range, thereby optimizing channel conditions, reducing inter-antenna interference, and enabling each antenna to avoid areas with strong interference.

[0090] To address the aforementioned issues, this invention proposes an enhanced backscatter communication method based on movable antenna technology. Compared to ISAC systems using APS-optimized movable antennas and traditional FPA-based ISAC systems without movable antennas, the proposed system and algorithm exhibit significant advantages in sensing capabilities, especially in complex environments and with sufficiently large transmit / receive areas. Results for single-tag, multi-tag, and clutter scattering devices demonstrate that the proposed system achieves more accurate reconstruction capabilities and exhibits superior resolution, specifically distinguishing two tags spaced only 75 mm apart. In the communication section, backscatter communication utilizing ESM technology outperforms QSM and SM technologies in bit error rate (BER), thus achieving low-power and highly reliable data transmission.

[0091] In this embodiment of the invention, an enhanced backscatter communication method based on movable antenna technology is provided. The method acquires the fundamental parameters of the backscatter communication system and constructs a fundamental parameter model of the backscatter communication system based on these parameters. Using CST electromagnetic simulation software, the method performs all-position voltage calculations on the fundamental parameter model and the fundamental parameters of the backscatter communication system, outputting a set of all-position measured voltages for the transmit-receive array. The all-position measured voltages of the transmit-receive array are decoupled and preprocessed, outputting a set of decoupled received voltage components. The decoupled received voltage components are then processed using sensing to output a dedicated backscatter communication channel matrix. Based on the fundamental parameters of the backscatter communication system, the dedicated backscatter communication channel matrix is ​​optimized to output a target dedicated backscatter communication channel matrix, which is used to realize backscatter communication. This invention fully characterizes the overall system characteristics by building a basic system parameter model. Combined with all-position voltage calculation, it achieves complete acquisition of signal data across the entire spatial dimension of the transceiver array. This provides comprehensive data support for adapting to complex environments and exploring spatial degrees of freedom. Decoupling and preprocessing the all-position measured voltage set enables effective separation of mixed voltage components, accurately distinguishing interference-related components from valid signal components. This allows for effective avoidance of interference areas in complex environments from a data perspective. Based on the decoupled received voltage component set, a channel matrix is ​​constructed through sensing calculations. This fully maps the inherent channel response characteristics corresponding to different spatial locations, fully releasing and exploring the system's potential spatial degrees of freedom. Furthermore, the channel matrix is ​​optimized in conjunction with the system's basic parameters to further adapt to the full-space transmission characteristics and regulate spatial dimension channel differences. This ensures that the final target backscatter communication-specific channel matrix can meet the spatial transmission requirements of complex scenarios.

[0092] Please see Figure 9 , Figure 9 This is a structural block diagram of an enhanced backscatter communication system based on movable antenna technology, provided in Embodiment 2 of the present invention.

[0093] This invention provides an enhanced backscatter communication system based on movable antenna technology, comprising: The acquisition module 901 is used to acquire the basic parameters of the backscatter communication system and construct a basic parameter model of the backscatter communication system based on the basic parameters of the backscatter communication system. Calculation module 902 is used to perform all-position voltage calculations on the basic parameter model and basic parameters of the backscatter communication system based on CST electromagnetic simulation software, and output the all-position measurement voltage set of the transmitting and receiving array; Preprocessing module 903 is used to perform decoupling preprocessing on the full-position measurement voltage set of the transmit-receive array and output the decoupling receive voltage component set; The calculation module 904 is used to perform sensing calculation on the decoupled received voltage component set and output the backscatter communication dedicated channel matrix; The optimization module 905 is used to optimize the backscatter communication dedicated channel matrix based on the basic parameters of the backscatter communication system, and output the target backscatter communication dedicated channel matrix, which is used to realize backscatter communication.

[0094] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process of the system and modules described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0095] This invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program; when the computer program is executed by the processor, the processor performs the steps of the enhanced backscatter communication method based on movable antenna technology as described in the above embodiments.

[0096] This invention also provides a computer-readable storage medium storing a computer program / instructions thereon, which, when executed by a processor, implement the steps of the enhanced backscatter communication method based on movable antenna technology as described in the above embodiments.

[0097] This invention also provides a computer program product, including a computer program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions, wherein when the program instructions are executed by a computer, the computer performs the steps of the enhanced backscatter communication method based on movable antenna technology as described in the above embodiments.

[0098] In the several embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0099] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0100] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0101] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0102] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An enhanced backscatter communication method based on movable antenna technology, characterized in that, include: Obtain the basic parameters of the backscatter communication system, and construct a basic parameter model of the backscatter communication system based on the basic parameters of the backscatter communication system; Based on the CST electromagnetic simulation software, the voltage at all positions of the backscatter communication system is calculated using the basic parameter model and basic parameters of the backscatter communication system, and the voltage set of the transmitting and receiving array at all positions is output. The full-position measurement voltage set of the transmit-receive array is decoupled and preprocessed to output the decoupled receive voltage component set; The decoupled received voltage component set is sensed and calculated to output a backscatter communication dedicated channel matrix; Based on the basic parameters of the backscatter communication system, the backscatter communication dedicated channel matrix is ​​optimized to output the target backscatter communication dedicated channel matrix, which is used to realize backscatter communication.

2. The enhanced backscatter communication method based on movable antenna technology according to claim 1, characterized in that, The basic parameters of the backscatter communication system include the range of the area to be measured, the number of transmitting antennas, the number of receiving antennas, the fixed reflection coefficient of the scatterer, the fixed antenna impedance of the tag, the dynamically adjustable load impedance of the tag, the movable coordinate range of the transmitting antenna, the movable coordinate range of the receiving antenna, the minimum spacing constraint of the antennas, and the spacing between the transmitting and receiving arrays. The step of constructing a basic parameter model for the backscatter communication system based on its basic parameters includes: The electromagnetic sensing area is defined based on the range of the object to be measured. Configure the number of transmit antennas and the number of receive antennas as transmit array size parameters and receive array size parameters, respectively. Generate the initial position parameters of the transmitting antenna within the movable coordinate range of the transmitting antenna, and generate the initial position parameters of the receiving antenna within the movable coordinate range of the receiving antenna; The fixed reflection coefficient of the scatterer, the fixed antenna impedance of the tag, and the dynamically adjustable load impedance of the tag are integrated into the target scattering parameters; Set the minimum antenna spacing constraint and the transmit / receive array spacing as system position constraint parameters; An electromagnetic calculation coordinate system is established, and the boundary coordinates of the electromagnetic sensing area, the scale parameters of the transmitting array, the scale parameters of the receiving array, the initial position parameters of the transmitting antenna, the initial position parameters of the receiving antenna, the target scattering parameters, and the system position constraint parameters are entered and assigned to the electromagnetic calculation coordinate system one by one to obtain the basic parameter model of the backscatter communication system.

3. The enhanced backscatter communication method based on movable antenna technology according to claim 1, characterized in that, The CST electromagnetic simulation software is used to perform all-position voltage calculations on the basic parameter model and basic parameters of the backscatter communication system, outputting a set of all-position measured voltages for the transmitting and receiving arrays, including: Extract the initial position parameters of the transmitting antenna, the initial position parameters of the receiving antenna, and the target scattering parameters from the basic parameter model of the backscatter communication system; The CST electromagnetic simulation software is used to perform electromagnetic field simulation based on the initial position parameters of the transmitting antenna, the initial position parameters of the receiving antenna, and the target scattering parameters, to obtain the original data files corresponding to the incident field, the scattered field, and the total electric field. The original data files corresponding to the incident field, the scattered field, and the total electric field are sequentially integrated by algorithms, data normalized, and linearly mapped to obtain a set of electric field distribution parameters. The nonlinear scattering field relationship corresponding to the electric field distribution parameter set is substituted into the preset Born approximation algorithm for simplification, and a linear mapping relationship between the scattering electric field and the received voltage is established to obtain the linearized received voltage calculation formula. According to the movable coordinate range of the transmitting antenna and the movable coordinate range of the receiving antenna in the basic parameters of the backscatter communication system, the transceiver array is controlled to traverse multiple movable positions. Substituting the electric field data of each of the movable positions into the linearized receiving voltage calculation formula, the full-position measurement voltage set of the transmitting and receiving array is obtained.

4. The enhanced backscatter communication method based on movable antenna technology according to claim 1, characterized in that, The decoupling preprocessing of the full-position measurement voltage set of the transmit-receive array, outputting a decoupled receive voltage component set, includes: The full-position measurement voltage set of the transmit-receive array is sequentially spliced ​​and data regularized according to the transmit antenna number, receive antenna number, and position coordinates to obtain the regularized full-position measurement voltage set of the transmit-receive array. Abnormal and invalid data are removed from the normalized full-position measurement voltage set of the transmit-receive array to obtain a linearized receive voltage parameter set with a unified format. The scattering response components corresponding to the clutter scatterer in the test environment are extracted from the linearized received voltage parameter set in the unified format to determine the clutter scattering field parameters. Based on the preset tag reflection coefficient definition, the linearized receiving voltage parameter set of the unified format is split into scattered field modes to separate the tag structure mode scattered field parameters and the tag antenna mode scattered field parameters. The tag structure mode scattering field parameters, the tag antenna mode scattering field parameters, and the clutter scattering field parameters are decoupled and decoupled according to the structure mode component and the antenna mode component to obtain the clutter combined voltage parameters and the tag independent voltage parameters. By integrating the clutter combined voltage parameters and the tag-independent voltage parameters, a decoupled receive voltage component set is obtained.

5. The enhanced backscatter communication method based on movable antenna technology according to claim 1, characterized in that, The step of sensing and calculating the decoupled received voltage component set to output a backscatter communication dedicated channel matrix includes: A sparse reconstruction optimization model is constructed based on the decoupled received voltage component set; The sparse reconstruction optimization model is iteratively solved to obtain the sparse reflection coefficient results; The sparse reflectance coefficient results are split to output a combined reflectance coefficient vector and a label-independent reflectance coefficient vector; Based on the combined reflectance coefficient vector and the tag-independent reflectance coefficient vector, a target localization and tag recognition result set is determined; Extract the spatial location information of the identified tags from the target localization and tag recognition result set; Based on the spatial location information of the identified tags, the channel vector of the identified tags is determined; Based on the channel vectors of the identified tags, a dedicated channel matrix for backscatter communication is constructed.

6. The enhanced backscatter communication method based on movable antenna technology according to claim 1, characterized in that, The process of optimizing the backscatter communication dedicated channel matrix based on the fundamental parameters of the backscatter communication system to output the target backscatter communication dedicated channel matrix includes: The movable coordinate range of the transmitting antenna, the movable coordinate range of the receiving antenna, the minimum antenna spacing constraint, and the transceiver array spacing are extracted from the basic parameters of the backscatter communication system as position constraint parameters. With the goal of maximizing sensing capacity, a preset PSO particle swarm optimization algorithm is used to iteratively optimize the positions of the transmitting antenna and the receiving antenna to obtain the target antenna position vector. The backscatter communication dedicated channel matrix is ​​optimized based on the target antenna position vector to obtain the target backscatter communication dedicated channel matrix.

7. An enhanced backscatter communication system based on movable antenna technology, characterized in that, include: The acquisition module is used to acquire the basic parameters of the backscatter communication system and construct a basic parameter model of the backscatter communication system based on the basic parameters of the backscatter communication system. The calculation module is used to perform all-position voltage calculations on the basic parameter model and basic parameters of the backscatter communication system based on CST electromagnetic simulation software, and output the all-position measurement voltage set of the transmitting and receiving array; The preprocessing module is used to perform decoupling preprocessing on the full-position measurement voltage set of the transmit-receive array and output the decoupling receive voltage component set; The calculation module is used to perform sensing calculation on the decoupled received voltage component set and output a backscatter communication dedicated channel matrix; An optimization module is used to optimize the backscatter communication dedicated channel matrix based on the basic parameters of the backscatter communication system, and output the target backscatter communication dedicated channel matrix, which is used to realize backscatter communication.

8. An electronic device, characterized in that, The device includes a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor causes the processor to perform the steps of the enhanced backscatter communication method based on movable antenna technology as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed, it implements the enhanced backscatter communication method based on movable antenna technology as described in any one of claims 1-6.

10. A computer program product, characterized in that, The computer program product includes a computer program stored on a non-transitory computer-readable storage medium, the computer program including program instructions, wherein when the program instructions are executed by a computer, the computer performs the steps of the enhanced backscatter communication method based on movable antenna technology as described in any one of claims 1-6.

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