Pinching antenna position matching method and device applied to integrated network of sensing and feeling

Abstract

The application discloses a pinching antenna position matching method and device applied to a sensing and communication integrated network, and belongs to the technical field of wireless communication, and the method comprises the following steps: acquiring an antenna deployable position set and establishing a channel model, determining a communication user data rate requirement and a sensing accuracy requirement; based on the communication user data rate requirement and the sensing accuracy requirement, an optimization model is constructed with the communication user data rate and the sensing accuracy as optimization targets; an optimal pinching antenna position matching subset is explored by using a preset intelligent algorithm, optimal position matching of the pinching antenna in the sensing and communication integrated network is realized, and the communication performance and the sensing accuracy are maximized. The application solves the problem of position matching of the activated pinching antenna in the sensing and communication integrated network, effectively improves the communication performance and the sensing accuracy, and simultaneously optimizes the utilization efficiency of network resources. The application is suitable for various sensing and communication integrated scenes.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of wireless communication, in particular to a pinching antenna position matching method and device applied to an integrated sensing and communication network. BACKGROUND

[0002] With the continuous development of wireless communication technology, the new generation network architecture is gradually evolving from single function to multi-function integration. Integrated sensing and communication (ISAC) network, as a new network architecture that supports efficient communication and accurate environmental perception at the same time, has attracted widespread attention. Its core goal is to achieve efficient collaboration of communication and sensing by sharing hardware resources and spectrum resources, and to meet the wide application needs of future intelligent society in the fields of autonomous driving, smart city, industrial Internet of Things, etc. It is an important development direction of the next generation of wireless communication systems. Traditional fixed antenna design often cannot adapt to complex scene requirements. Specifically, the integrated sensing and communication network faces the following main challenges:

[0003] 1) Efficient use of spectrum resources: communication and sensing functions share spectrum resources, and the antenna needs to have high directivity and flexibility to reduce signal interference and improve resource utilization efficiency.

[0004] 2) Dynamic environment adaptability: in complex dynamic scenarios (such as urban high-density areas), the antenna needs to be dynamically adjusted according to environmental changes to ensure communication quality and sensing accuracy.

[0005] 3) Multi-antenna system coordination: Integrated sensing and communication networks usually use multi-antenna systems to achieve wider coverage and higher sensing resolution. However, the antenna position matching problem in the multi-antenna system directly affects the signal transmission performance and sensing accuracy.

[0006] In recent years, flexible antenna systems (such as intelligent reflecting surfaces, fluid antenna systems, and movable antennas) have received widespread attention. Due to their ability to dynamically reconfigure wireless channels, flexible antenna systems can significantly improve performance compared to traditional fixed-position antenna systems. However, in most existing flexible antenna systems, the range of antenna position changes is usually limited to the wavelength scale, which limits their ability to combat large-scale path loss. In addition, the high cost of many existing flexible antenna systems also limits their application in real-world scenarios. The pinching antenna system proposed in this context can create new line-of-sight links and / or enhance existing transceiver channels by applying low-cost dielectric materials (such as plastic clothespins) at arbitrary positions on the dielectric waveguide.

[0007] The pinching antenna has the following two significant features:

[0008] The ability to support line-of-sight communication: The use of Pinching antennas can create new line-of-sight transceiver links or enhance existing line-of-sight links, because the position of the Pinching antenna can be flexibly adjusted on a large scale, so the Pinching antenna can be easily deployed near the target receiver to establish a strong line-of-sight link.

[0009] The ability to flexibly configure the antenna system: By simply adding additional Pinching (or releasing existing Pinching), the size of the Pinching antenna system can be increased (or decreased). In addition, multiple Pinching antennas can be flexibly and low-cost applied to one or more waveguides, providing a new way for the implementation of MIMO systems.

[0010] Pinching antennas as a new type of antenna design scheme, its flexible radiation pattern and strong adaptability of layout capability show broad application prospects. However, there is still a lack of a systematic method to dynamically match the position of the Pinching antenna in the integrated sensing and communication network in the existing research, so as to fully exert its performance advantage. SUMMARY

[0011] The application provides a pinching antenna position matching method and device applied to an integrated sensing and communication network, to solve the technical problem that there is still a lack of a systematic method to dynamically match the position of the Pinching antenna in the integrated sensing and communication network in the existing research, so as to fully exert its performance advantage.

[0012] To solve the above technical problems, the application provides the following technical solutions:

[0013] On the one hand, the application provides a pinching antenna position matching method applied to an integrated sensing and communication network, which comprises:

[0014] Obtaining a set of deployable positions of the Pinching antenna, and establishing a channel model to determine the communication user data rate requirement and the sensing accuracy requirement in the integrated sensing and communication network;

[0015] Based on the communication user data rate requirement and the sensing accuracy requirement, the communication performance, the sensing accuracy and the resource utilization efficiency are comprehensively considered, and an optimization model with the communication user data rate and the sensing accuracy as the optimization objectives is constructed;

[0016] The preset intelligent algorithm is used for solving the optimization model, exploring an optimal pinching antenna position matching subset in a pinching antenna deployable position set, and realizing optimal position matching of the pinching antenna in the sensing and communication integrated network, so that the communication performance and sensing accuracy of the sensing and communication integrated network are maximized.

[0017] Further, the optimization model with the communication user data rate and the sensing accuracy as optimization objectives is constructed by comprehensively considering the communication performance, the sensing accuracy and the resource utilization efficiency based on the communication user data rate requirement and the sensing accuracy requirement, including:

[0018] The optimization model with the communication user data rate and the sensing accuracy as optimization objectives is constructed by setting the weighting coefficients of the communication user data rate and the sensing accuracy for performance trade-off to adapt to different network application requirements.

[0019] Further, the optimization model is expressed as:

[0020]

[0021] Wherein, S represents a pinching antenna deployable position set; Γ n represents a signal-to-interference-plus-noise ratio of the nth sensing target; Γ sen represents a preset threshold of the sensing accuracy; a represents a spherical wave parameter; ψ m represents the position of the mth user; p m represents the power allocated to the mth user by the base station; σ 2 is a noise power; e represents a natural constant, and the value is about 2.718; j represents an imaginary unit; τ represents a preset weight factor; M represents the total number of users; N represents the number of pinching antennas; λ represents the wavelength of a wireless signal; represents the position of the nth pinching antenna; θ n represents the phase shift of the signal at the nth antenna.

[0022] Further, the intelligent algorithm is a Q-learning algorithm, a particle swarm algorithm or a genetic algorithm.

[0023] In another aspect, the application further provides a pinching antenna position matching device applied to a sensing and communication integrated network, the pinching antenna position matching device applied to the sensing and communication integrated network comprising:

[0024] A data initialization module is configured to acquire a pinching antenna deployable position set, establish a channel model, and determine the communication user data rate requirement and the sensing accuracy requirement in the sensing and communication integrated network.

[0025] The optimization model construction module is configured to construct an optimization model with the communication user data rate and the sensing accuracy as optimization targets based on the communication user data rate requirement and the sensing accuracy requirement, and comprehensively consider the communication performance, the sensing accuracy and the resource utilization efficiency.

[0026] The optimization calculation module is configured to solve the optimization model by using a preset intelligent algorithm, explore an optimal pinching antenna position matching subset in a pinching antenna deployable position set, and realize optimal position matching of the pinching antenna in the integrated communication and sensing network, so that the communication performance and the sensing accuracy of the integrated communication and sensing network are maximized.

[0027] Further, the optimization model construction module is specifically configured to:

[0028] The optimization model is constructed with the communication user data rate and the sensing accuracy as optimization targets by setting the weighted coefficients of the communication user data rate and the sensing accuracy to perform performance trade-off, so as to adapt to different network application requirements.

[0029] Further, the optimization model is represented as:

[0030]

[0031] wherein S represents a pinching antenna deployable position set; Γ n represents a signal-to-interference-plus-noise ratio of an nth sensing target; Γ sen represents a preset threshold of the sensing accuracy; a represents a spherical wave parameter; ψ m represents a position of an mth user; p m represents power allocated to the mth user by a base station; σ 2 is a noise power; e represents a natural constant, and the value is about 2.718; j represents an imaginary unit; τ represents a preset weight coefficient; M represents a total number of users; N represents a number of pinching antennas; and λ represents a wavelength of a wireless signal. represents a position of an nth pinching antenna; θ n represents a phase shift of a signal at the nth antenna.

[0032] Further, the intelligent algorithm is a Q-learning algorithm, a particle swarm algorithm or a genetic algorithm.

[0033] In still another aspect, the present application further provides an electronic device comprising a processor and a memory; wherein the memory stores at least one instruction, which is loaded and executed by the processor to implement the above method.

[0034] In yet another aspect, the present application also provides a computer readable storage medium, wherein at least one instruction is stored in the storage medium, and the instruction is loaded and executed by a processor to implement the above method.

[0035] The technical solution provided by the present application has at least the following beneficial effects:

[0036] The pinching antenna position matching scheme provided by the present application considers the set of deployable antenna positions and the communication and sensing performance requirements; a target optimization model is constructed with the communication user data rate and the sensing accuracy as the targets, and constraint conditions such as the number of activated antennas and interference control are set; an intelligent algorithm is used to explore the optimal activated antenna subset in the discrete position set, and the optimal activated antenna set and its deployment position are output, so as to realize the optimal position matching of the pinching antenna in the integrated communication and sensing network, and further maximize the communication performance and the sensing accuracy. The problem of the position matching of the activated pinching antenna in the integrated communication and sensing network is solved, the communication performance and the sensing accuracy are effectively improved, and the utilization efficiency of the network resources is optimized. The present application is suitable for various integrated communication and sensing scenarios. BRIEF DESCRIPTION OF DRAWINGS

[0037] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative effort on the basis of these drawings.

[0038] Figure 1 is a position model of the integrated communication and sensing network and the pinching antenna provided by the embodiment of the present application;

[0039] Figure 2 is an execution flow diagram of the pinching antenna position matching method applied to the integrated communication and sensing network provided by the embodiment of the present application;

[0040] Figure 3 is a system block diagram of the electronic device provided by the embodiment of the present application. DETAILED DESCRIPTION

[0041] In order to make the purpose, technical solutions and advantages of the present application clearer, the embodiments of the present application will be further described in detail below with reference to the drawings.

[0042] First, it should be pointed out that in the embodiments of the present application, the words such as "exemplarily", "for example" and the like are used to represent as an example, illustration or description. Any embodiment or design scheme described as "exemplary" in the present application should not be interpreted as more preferred or more advantageous than other embodiments or design schemes. Rather, the word "exemplarily" is intended to present the concept in a specific manner. In addition, in the embodiments of the present application, the meaning expressed by "and / or" can be both, or can be either one of the two.

[0043] First embodiment

[0044] The present embodiment provides a pinching antenna position matching method applied to a sensing-integrated network. For a scenario in which a set of deployable positions of a pinching antenna is known, a solution to a discrete pinching antenna position optimization problem is proposed, which is used to match users and sensing targets in an intelligent manner according to the known set of antenna positions, so as to determine an optimal set of activated antennas, thereby maximizing the communication and sensing performance of the integrated network. As shown in the position model of the sensing-integrated network and the pinching antenna, Figure 1 the execution flow of the method is as shown in Figure 2 . Specifically, the method comprises the following steps:

[0045] S1, data initialization: obtaining a set of deployable positions of an antenna, analyzing a reconstructed link channel model of the pinching antenna, and communication user data rate requirement and sensing accuracy requirement.

[0046] Specifically, in the present embodiment, a pinching antenna link channel model is established according to the fact that the pinching antenna realizes enhanced or reconstructed line-of-sight transmission link through its leaky-wave characteristics; the state is initialized by comprehensively considering the discrete set of antenna positions and the communication and sensing performance requirements. Let the positions of user n and activated antenna l be respectively: n (x n ,y n ,0), For L potential antennas, the channel vector of user n can be expressed as:

[0047]

[0048] According to the channel state, the communication and sensing performance requirements are analyzed, and the state is initialized.

[0049] S2, constructing an optimization model: based on the communication user data rate requirement and the sensing accuracy requirement, an optimization model is constructed by comprehensively considering the communication performance, the sensing accuracy and the resource utilization efficiency;

[0050] Specifically, in the embodiment, by comprehensively analyzing the communication data rate and the sensing accuracy performance expression, the weighted coefficients of the communication data rate and the sensing accuracy are set to perform performance trade-off to adapt to different network application requirements, and a collaborative optimization target of the integrated sensing and communication network introducing the weighted coefficients is constructed.

[0051] Set of pinching antenna positions at time slot t Position of user m m = (x m , y m , 0), the power allocated to user m by the base station is p m , σ 2 is the noise power, κ is the spherical radiation parameter, and the data rate of user m under the action of multiple active antennas is:

[0052]

[0053] where e represents the natural constant, whose value is about 2.718; j represents the imaginary unit; τ represents the weight factor; M represents the total number of users; N represents the number of pinching antennas; λ represents the wavelength of the wireless signal; represents the position of the nth pinching antenna; θ n represents the phase shift of the signal at the nth antenna.

[0054] The signal-to-interference-plus-noise ratio (SINR, Signal to Interference plus Noise Ratio) Γ n of the sensing target n is considered while optimizing the user data rate, and the threshold value of the sensing accuracy is Γ sen The weighted integrated sensing and communication performance optimization target is:

[0055]

[0056] S3, optimization calculation: an intelligent algorithm is used to explore the optimal active antenna subset in the discrete position set of the pinching antenna, and the joint optimization target is maximized by dynamically adjusting the antenna selection state.

[0057] where the optimization target is the weighted optimization of the integrated sensing and communication performance of the discrete decision variable, an intelligent algorithm is used to explore the optimal active antenna subset in the discrete position set of the pinching antenna, and the weighted optimization target is maximized by dynamically adjusting the position of the active antenna. The intelligent algorithm can be a Q-learning algorithm, a particle swarm algorithm or a genetic algorithm, which has stronger adaptability and flexibility in matching the optimization target of the discrete position.

[0058] In summary, the embodiment provides a pinching antenna position matching method applied to a sensing-integrated network, which considers a set of deployable positions of the antenna and communication and sensing performance requirements; constructs an optimization model with communication user data rate and sensing accuracy as target optimization models, sets constraint conditions such as the number of activated antennas and interference control; uses an intelligent algorithm to explore the optimal activated antenna subset in the discrete position set, and outputs the optimal activated antenna set and its deployment position, so as to realize the optimal position matching of the pinching antenna in the sensing-integrated network, and further maximize the communication performance and sensing accuracy. The problem of matching the position of the activated pinching antenna in the sensing-integrated network is solved, the communication performance and sensing accuracy are effectively improved, and the utilization efficiency of network resources is optimized. It is suitable for various sensing-integrated scenarios.

[0059] Second embodiment

[0060] The embodiment provides a pinching antenna position matching device applied to a sensing-integrated network, which comprises the following modules:

[0061] A data initialization module is configured to obtain a set of deployable positions of a pinching antenna, establish a channel model, and determine communication user data rate requirements and sensing accuracy requirements in the sensing-integrated network.

[0062] An optimization model construction module is configured to construct an optimization model with communication user data rate and sensing accuracy as optimization targets based on the communication user data rate requirements and the sensing accuracy requirements, and comprehensively consider communication performance, sensing accuracy, and resource utilization efficiency.

[0063] An optimization calculation module is configured to use a preset intelligent algorithm to solve the optimization model, explore the optimal pinching antenna position matching subset in the set of deployable positions of the pinching antenna, realize the optimal position matching of the pinching antenna in the sensing-integrated network, and maximize the communication performance and sensing accuracy of the sensing-integrated network.

[0064] It should be noted that the pinching antenna position matching device applied to the sensing-integrated network in the embodiment corresponds to the pinching antenna position matching method applied to the sensing-integrated network in the first embodiment; the functions of each functional module in the pinching antenna position matching device applied to the sensing-integrated network in the embodiment correspond to each process step in the pinching antenna position matching method applied to the sensing-integrated network in the first embodiment; therefore, no further description is given here.

[0065] Third embodiment

[0066] The present embodiment provides an electronic device, such as Figure 3 As shown in the figure, the electronic device comprises a processor and a memory; wherein the processor and the memory can be connected through a communication bus; the memory stores at least one instruction, which is loaded and executed by the processor to implement the method of the first embodiment. In addition, the electronic device can further comprise a transceiver, the processor and the transceiver can be connected through a communication bus, and the transceiver is used for communication with other devices.

[0067] Next, the first embodiment of the present application will be described in detail in combination with Figure 3 The various components of the electronic device will be described in detail:

[0068] The processor is the control center of the electronic device, and the electronic device can comprise a plurality of processors, each of which can be a single-CPU or a multi-CPU. The processor here can be a processor or a general term for a plurality of processing elements. For example, the processor is one or more central processing units (CPU), which can also be other general-purpose processors, application specific integrated circuits (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application, such as one or more microprocessors (digital signal processors, DSP), or one or more field programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc. The processor can perform various functions of the electronic device by running or executing software programs stored in the memory and calling data stored in the memory.

[0069] In a specific implementation, as an embodiment, the processor can comprise one or more CPUs, such as CPU0 and CPU1 shown in Figure 3 of course, this is only an exemplary description.

[0070] The memory is used to store software programs for implementing the solutions of the present application, and is controlled by the processor to execute, and the specific implementation manner can refer to the above-mentioned method embodiments, which will not be described here.

[0071] Optionally, the memory can be a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (RAM) or other type of dynamic storage device that can store information and instructions, an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disk storage, a magnetic disk storage or other magnetic storage devices, or any other medium capable of storing desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to this. The memory can be integrated with the processor or exist independently and be coupled to the processor through the interface circuit (not shown in the figure) of the electronic device, and the embodiments of the present application do not make specific limitations hereon. Figure 3

[0072] The transceiver can include a receiver and a transmitter (not shown separately in the figure). The receiver is configured to implement the receiving function, and the transmitter is configured to implement the transmitting function. The transceiver can be integrated with the processor or exist independently and be coupled to the processor through the interface circuit (not shown in the figure) of the electronic device, and the embodiments of the present application do not make specific limitations hereon. Figure 3 Figure 3

[0073] In addition, it should be noted that the structure of the electronic device shown in the figure does not constitute a limitation on the device, and the actual device can include more or fewer components than shown in the figure, or combine certain components, or different component arrangements. In addition, the technical effects achieved by the electronic device when executing the method of the first embodiment can refer to the technical effects described in the first embodiment, and therefore, will not be described here. Figure 3

[0074] Fourth embodiment

[0075] The present embodiment provides a computer readable storage medium, the storage medium stores at least one instruction, the instruction is loaded and executed by the processor to realize the method of the first embodiment. Wherein, the computer readable storage medium can be ROM, random access memory, CD-ROM, magnetic tape, floppy disk and optical data storage device, etc. The instructions stored therein can be loaded and executed by the processor in the terminal to execute the above method.

[0076] ​​​​Moreover, it should be noted that the present application can be provided as a method, an apparatus, or a computer program product. Therefore, the embodiments of the present application can take the form of an entirely or partially hardware embodiment, an entirely or partially software embodiment, or an embodiment combining software and hardware aspects. Furthermore, when implemented in software, the embodiments of the present application can take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, a computer diskette, an optical storage medium, a magnetic storage medium, and a semiconductor memory device). The computer program product includes one or more computer instructions that when loaded and executed by a computer, cause the computer to carry out the processes or functions described in the embodiments of the present application. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable apparatus. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium, such as from a website, a computer, a server, or a data center to another website, computer, server, or data center through a wired (for example, infrared, wireless, microwave, or the like) manner. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, data center, or the like, including one or more collections of available media. The available media can be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (for example, a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state disk.

[0077] The embodiments of the present application are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a general-purpose computer, an embedded processor, or a processor of another programmable data processing terminal device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate a device that implements the flow Figure 1 The flow or the plurality of flows and / or blocks Figure 1 The device that implements the functions specified in the flow or the plurality of flows and / or blocks.

[0078] These computer program instructions can also be stored in a computer-readable storage medium that can guide the computer or other programmable data processing terminal device to work in a specific manner, so that the instructions stored in the computer-readable storage medium produce a product including instruction devices that implement the flow Figure 1 The flow or the plurality of flows and / or blocks Figure 1the functions specified in the individual block or blocks. Such computer program instructions can also be loaded into a computer or other programmable data processing devices, so that a series of operational steps are performed on the computer or other programmable devices to generate a computer-implemented process, thus the instructions executed on the computer or other programmable devices provide a process for implementing the functions specified in the flowchart block(s). Figure 1 the functions specified in the individual block or blocks. Such computer program instructions can also be loaded into a computer or other programmable data processing devices, so that a series of operational steps are performed on the computer or other programmable devices to generate a computer-implemented process, thus the instructions executed on the computer or other programmable devices provide a process for implementing the functions specified in the flowchart block(s). Figure 1 the functions specified in the individual block or blocks. Such computer program instructions can also be loaded into a computer or other programmable data processing devices, so that a series of operational steps are performed on the computer or other programmable devices to generate a computer-implemented process, thus the instructions executed on the computer or other programmable devices provide a process for implementing the functions specified in the flowchart block(s).

[0079] It should also be noted that, in the present document, the terms such as first and second, etc. are merely used to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. The terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal device including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or further includes elements inherent to such process, method, article or terminal device. Without more limitations, the element defined by the statement "including a…", does not exclude the presence of other identical elements in the process, method, article or terminal device including the element. In addition, the term "and / or" is merely a description of the association relationship between the associated objects, which means that there can be three relationships, for example, A and / or B, which means that there are three cases of A alone, A and B together, and B alone, where A and B can be singular or plural. In addition, the character " / " in the present document generally represents an "or" relationship between the front and rear associated objects, but it can also represent an "and / or" relationship, which can be understood in the context before and after. "One or more" means one or more, and "multiple" means two or more. "At least one of the following" or similar expressions means any combination of these items, including any combination of single or multiple items. For example, at least one of a, b or c can mean a, b, c, a-b, a-c, b-c, or a-b-c, where a, b, and c can be single or multiple.

[0080] In addition, it can be understood that in various embodiments of the present application, the size of the sequence number of the above processes does not mean the order of execution, and the execution order of the processes should be determined by their functions and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0081] Those skilled in the art can appreciate that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be realized in electronic hardware or in a combination of computer software and electronic hardware. Whether the functions are realized in hardware or software depends on the specific application and design constraints of the technical solutions. Those skilled in the art can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0082] In several embodiments provided by the present application, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely schematic, for example, the division of functional modules / units is merely a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another device, or some features can be omitted or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed units can be indirect coupling or communication connection through some interfaces, devices or units, and can be electrical, mechanical or other forms. The units described as separate components can be or can not be physically separated, and the components displayed as units can be or can not be physical units, that is, can be located in one place, or can be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiment. In addition, the functional units in each embodiment of the present application can be integrated in one processing unit, or each unit can be physically present, or two or more units can be integrated in one unit.

[0083] If the method is realized in the form of a software function unit and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application essentially or the part that contributes to the prior art or part of the technical solutions can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a plurality of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the method described in the embodiments of the present application. The foregoing storage medium includes a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0084] Finally, it should be noted that the above description is only the preferred embodiment of the application, it should be pointed out that although the preferred embodiment of the application has been described, for those skilled in the art, once the basic creative concept of the application is known, several improvements and refinements can be made without departing from the principles of the application, and these improvements and refinements should also be considered as the protection scope of the application. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the embodiments of the application.

Claims

1. A pinching antenna position matching method applied to a CIDS integrated network, characterized in that, The pinching antenna position matching method applied to the integrated communication and sensing network comprises the following steps: A set of deployable positions of the pinching antenna is acquired, a channel model is established, and the data rate requirement of a communication user and the sensing accuracy requirement in the integrated communication and sensing network are determined; Based on the data rate requirement of the communication user and the sensing accuracy requirement, an optimization model is constructed with the data rate of the communication user and the sensing accuracy as optimization objectives by comprehensively considering the communication performance, the sensing accuracy and the resource utilization efficiency; The optimization model is solved by using a preset intelligent algorithm, an optimal pinching antenna position matching subset is explored from the set of deployable positions of the pinching antenna, and optimal position matching of the pinching antenna in the integrated communication and sensing network is realized, so that the communication performance and the sensing accuracy of the integrated communication and sensing network are maximized; The optimization model is represented as: ； ； wherein S represents a set of deployable positions of the pinching antenna; represents a signal-to-interference-plus-noise ratio of the th sensing target; represents a threshold of a preset sensing accuracy; is a spherical wave parameter; represents a position of the th user; represents a power allocated by the base station to the th user; is a noise power; e represents a natural constant; j represents an imaginary unit; represents a preset weight factor; M represents a total number of users; N represents a number of pinching antennas; λ represents a wavelength of a wireless signal; represents a position of the th pinching antenna; represents a phase shift of a signal at the th antenna.

2. The pinching antenna position matching method for a converged network of claim 1, wherein, The optimization model is constructed with the data rate of the communication user and the sensing accuracy as optimization objectives by comprehensively considering the communication performance, the sensing accuracy and the resource utilization efficiency based on the data rate requirement of the communication user and the sensing accuracy requirement, which comprises the following steps: The optimization model is constructed with the data rate of the communication user and the sensing accuracy as optimization objectives by weighting the data rate of the communication user and the sensing accuracy to balance the performance and adapt to different network application requirements.

3. The pinching antenna position matching method for a converged network of claim 1, wherein, The intelligent algorithm is a Q-learning algorithm, a particle swarm algorithm or a genetic algorithm.

4. A pinching antenna position matching device applied to a converged network, characterized in that, The pinching antenna position matching device applied to the integrated communication and sensing network comprises the following steps: A data initialization module is configured to acquire a set of deployable positions of the pinching antenna, establish a channel model, and determine the data rate requirement of a communication user and the sensing accuracy requirement in the integrated communication and sensing network; An optimization model construction module is configured to construct an optimization model with the data rate of the communication user and the sensing accuracy as optimization objectives by comprehensively considering the communication performance, the sensing accuracy and the resource utilization efficiency based on the data rate requirement of the communication user and the sensing accuracy requirement; An optimization calculation module is configured to solve the optimization model by using a preset intelligent algorithm, explore an optimal pinching antenna position matching subset from the set of deployable positions of the pinching antenna, and realize optimal position matching of the pinching antenna in the integrated communication and sensing network, so that the communication performance and the sensing accuracy of the integrated communication and sensing network are maximized; The optimization model is represented as: ； ； wherein S denotes a set of deployable positions of the pinching antenna; denotes a signal-to-interference-plus-noise ratio of the th sensing target; denotes a threshold of a preset sensing accuracy; is a spherical wave parameter; denotes a position of the th user; denotes a power allocated by the base station to the th user; is a noise power; e denotes a natural constant; j denotes an imaginary unit; denotes a preset weight factor; M denotes a total number of users; N denotes a number of pinching antennas; λ denotes a wavelength of a wireless signal; denotes a position of the th pinching antenna; denotes a phase shift of a signal at the th antenna.

5. The pinching antenna position matching device for a converged network of claim 4, wherein, The optimization model construction module is specifically configured to: The optimization model is constructed with the data rate of the communication user and the sensing accuracy as optimization objectives by weighting the data rate of the communication user and the sensing accuracy to balance the performance and adapt to different network application requirements.

6. The pinching antenna position matching device for a converged network of claim 4, wherein, The intelligent algorithm is a Q-learning algorithm, a particle swarm algorithm or a genetic algorithm.

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