Channel state prediction method and device, and storage medium

Abstract

The invention relates to a channel state prediction method and device and a storage medium, and the method comprises the steps: determining a transmitting end modal signal according to different orbital angular momentum modal information generated by transmitting antennas in a preset number of transmitting and receiving antenna array pairs; off-axis offset information of a preset number of receiving and transmitting antenna array pairs is obtained, and a transmission function is determined based on the transmitting end modal signal, the off-axis offset information and the transmission distance; determining a receiving end modal signal of the receiving antenna according to an energy conversion relationship between different orbital angular momentum modal signals and the transmitting end modal signal, and determining a channel transmission coefficient based on the transmitting end modal signal, the transmission function and the receiving end modal signal; and constructing a channel transmission matrix according to the channel transmission coefficient, and predicting a channel state based on the channel transmission matrix. Therefore, the defect that an accurate channel model is lacked in an off-axis offset scene is overcome, and a theoretical basis and a practical tool are provided for improving the communication capacity in a non-ideal alignment scene.

Description

Technical Field

[0001] This application relates primarily to the field of wireless communication technology, and in particular to a channel state prediction method, device, and storage medium. Background Technology

[0002] With the explosive growth of massive multimedia traffic, millimeter-wave communication, with its abundant spectrum resources, has become a key technology for future wireless networks. However, compared with electromagnetic waves in traditional frequency bands, millimeter-wave signals suffer from significant path loss during transmission. In recent years, orbital angular momentum (OAM) electromagnetic waves, due to their unique helical phase structure, have shown unique potential in improving spectral efficiency. Theoretically, OAM modes with different topological charges are orthogonal to each other, which can construct a high-dimensional signal space, thereby significantly increasing communication capacity.

[0003] However, OAM still faces severe challenges in practical systems, especially in integrated millimeter-wave radar and communication applications, as its performance is highly dependent on the precise alignment of the transceiver. In real-world scenarios, off-axis misalignment of the transceiver caused by equipment vibration, thermal deformation, or terminal movement can disrupt the phase structure of the vortex wavefront, leading to two serious problems: first, it exacerbates inter-mode crosstalk, resulting in increased interference in the received signal and increased demodulation difficulty; second, in radar-communication fusion systems, it simultaneously causes a decline in communication quality and a degradation in radar detection performance, such as beam distortion and reduced resolution. Summary of the Invention

[0004] One objective of this application is to provide a channel state prediction method, device, and storage medium to address the problem in the prior art of lacking an analysis and modeling method for energy transfer characteristics between orbital angular momentum modes under off-axis misalignment scenarios at the transceiver end, which leads to unpredictable and unoptimized system capacity and degraded channel performance.

[0005] According to one aspect of this application, a channel state prediction method is provided, the method comprising: determining a transmitting mode signal based on different orbital angular momentum mode information generated by transmitting antennas in a preset number of transmitting and receiving antenna array pairs; acquiring off-axis offset information of the preset number of transmitting and receiving antenna array pairs, and determining a transmission function based on the transmitting mode signal, the off-axis offset information, and the transmission distance; determining a receiving mode signal of a receiving antenna based on the energy conversion relationship between different orbital angular momentum mode signals and the transmitting mode signal, and determining channel transmission coefficients based on the transmitting mode signal, the transmission function, and the receiving mode signal; constructing a channel transmission matrix based on the channel transmission coefficients, and predicting the channel state based on the channel transmission matrix.

[0006] Optionally, determining the transmitting mode signal based on the different orbital angular momentum mode information generated by the transmitting antenna in a preset number of transceiver antenna arrays includes: acquiring different orbital angular momentum mode information generated by the transmitting antenna in a preset number of transceiver antenna arrays; modulating a preset baseband signal based on the transmitting power of the transmitting antenna and the different orbital angular momentum mode information to obtain a sub-transmit signal for each orbital angular momentum mode; and linearly superimposing the sub-transmit signals of each orbital angular momentum mode to determine the transmitting mode signal.

[0007] Optionally, the orbital angular momentum mode information includes topological charge, helical phase distribution parameters, and beam amplitude distribution parameters. The step of modulating a preset baseband signal based on the transmit power of the transmitting antenna and the different orbital angular momentum mode information to obtain a sub-transmitted signal for each orbital angular momentum mode includes: amplitude modulation of the baseband signal based on the transmit power of the transmitting antenna and the beam amplitude distribution parameters; and phase modulation of the baseband signal based on the topological charge and the helical phase distribution parameters to obtain a sub-transmitted signal for each orbital angular momentum mode.

[0008] Optionally, obtaining the off-axis offset information of the preset number of transceiver antenna array pairs and determining the transmission function based on the transmitting end mode signal, the off-axis offset information, and the transmission distance includes: obtaining the geometric model of the transmitting antenna and receiving antenna in the preset number of transceiver antenna array pairs in an off-axis offset state; determining the off-axis offset information of the preset number of transceiver antenna array pairs according to the geometric model; and determining the transmission function based on the transmitting end mode signal, the off-axis offset information, and the transmission distance.

[0009] Optionally, determining the receiving mode signal of the receiving antenna based on the energy conversion relationship between different orbital angular momentum mode signals and the transmitting mode signal includes: determining the energy conversion relationship between different orbital angular momentum mode signals; constructing a multi-mode hybrid signal based on the energy conversion relationship and the transmitting mode signal; and determining the receiving mode signal of the receiving antenna based on the multi-mode hybrid signal.

[0010] Optionally, constructing the channel transmission matrix based on the channel transmission coefficients includes: determining the matrix elements of the channel transmission matrix based on the channel transmission coefficients, and determining the order of the channel transmission matrix based on a preset number of orbital angular momentum modes, so as to complete the construction of the channel transmission matrix.

[0011] Optionally, the prediction of channel state based on the channel transmission matrix includes: normalizing the channel transmission matrix to obtain an orbital angular momentum mode power distribution feature map, and determining the energy transfer distribution ratio and power distribution characteristics between the transmitting end mode signal and the receiving end mode signal based on the power distribution feature map, so as to achieve prediction of channel state.

[0012] Optionally, the method further includes: modifying the channel transmission coefficients to optimize the matrix elements of the channel transmission matrix; and predicting the channel state based on the optimized channel transmission matrix.

[0013] According to another aspect of this application, an electronic device is also provided, the electronic device comprising: one or more processors; and a memory storing computer-readable instructions, which, when executed, cause the processor to perform the operations of any of the methods described above.

[0014] According to another aspect of this application, a computer-readable medium is also provided, having stored thereon computer instructions that can be executed by a processor to implement the steps of any of the methods described above.

[0015] Compared with existing technologies, this application utilizes the orthogonality of orbital angular momentum modes to achieve multidimensional multiplexing transmission by leveraging mode conversion characteristics and the energy distribution characteristics of mode crosstalk in turbulent environments, thus providing a channel transmission scheme suitable for unaligned scenarios. Attached Figure Description

[0016] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the specific embodiments of this application will be described in detail below with reference to the accompanying drawings, wherein:

[0017] Figure 1 A schematic flowchart of a channel state prediction method according to one aspect of this application is shown.

[0018] Figure 2 This diagram illustrates the off-axis offset geometric model of the transmitting antenna and the receiving antenna in one embodiment of this application.

[0019] Figure 3 This diagram illustrates the energy conversion relationship between different OAM mode signals in one embodiment of this application.

[0020] Figure 4 A schematic diagram of a frame of an electronic device provided according to another aspect of this application is shown.

[0021] The same or similar reference numerals in the accompanying drawings represent the same or similar parts. Detailed Implementation

[0022] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the specific embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0023] Many specific details are set forth in the following description in order to provide a full understanding of this application. However, this application may also be implemented in other ways different from those described herein, and therefore this application is not limited to the specific embodiments disclosed below.

[0024] As indicated in this application and claims, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" are not specifically singular and may include plural forms. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of explicitly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements.

[0025] Existing technologies lack precise analysis and modeling methods for the energy transfer characteristics between orbital angular momentum modes in offset scenarios, leading to unpredictable and unoptimized system capacity, as well as channel performance degradation due to off-axis misalignment at the transmitter and receiver. The proposed solution addresses the real-world situation of off-axis misalignment at the transmitter and receiver by precisely modeling the energy conversion process between orbital angular momentum modes, defining channel transmission coefficients, and constructing a channel matrix accordingly. This model reveals the law that system capacity decreases with increasing offset distance, thus providing a theoretical basis and practical tool for optimizing system design and improving communication capacity in non-ideal alignment scenarios.

[0026] Figure 1 The diagram illustrates a method for channel state prediction according to one aspect of this application, the method comprising steps S11 to S14.

[0027] Step S11: Determine the transmitting end mode signal based on the different orbital angular momentum mode information generated by the transmitting antenna in a preset number of transmitting and receiving antenna arrays.

[0028] In the initial step of signal generation, the transmit modal signal is determined based on the different orbital angular momentum mode information generated by the transmitting antenna. The transmit modal signal is a radio frequency signal carrying orbital angular momentum mode information generated by the transmitting antenna based on the characteristic parameters of different orbital angular momentum modes. It can be a superposition signal of multiple single orbital angular momentum mode sub-transmitted signals, integrating the phase and amplitude characteristics of each orbital angular momentum mode. It is the basic transmit signal source for subsequent signal transmission and channel modeling.

[0029] Orbital angular momentum (OAM) is a physical property of electromagnetic waves, characterized by a helical phase distribution along the propagation direction and angular momentum associated with its phase structure. Different topological charge values ​​correspond to different OAM modes, which are spatially orthogonal and can be used to construct independent signal transmission channels. This property allows OAM to be used for mode multiplexing in optical and radio frequency communications, effectively improving the system's spectral efficiency and data transmission capacity.

[0030] Step S12: Obtain off-axis offset information of the preset number of transmit and receive antenna array pairs, and determine the transmission function based on the transmit end mode signal, the off-axis offset information, and the transmission distance.

[0031] The transfer function is a quantitative representation of the channel transmission characteristics, accurately describing the amplitude attenuation, phase distortion, and energy distribution changes of the transmitted mode signal during spatial transmission. In this step, the transfer function is constructed by integrating the characteristics of the transmitted mode signal itself, the off-axis offset information of the transmitting and receiving antennas, and the actual transmission distance, taking into account the actual transmission factors affecting the OAM mode signal.

[0032] Off-axis offset information refers to the axial offset parameters of the transmitting and receiving antennas in the spatial relative position of the transmitting and receiving antenna array, including the relative radial displacement and azimuth displacement of the transmitting and receiving antennas. It is the core influencing factor that causes mode crosstalk and energy conversion during the transmission of orbital angular momentum mode signals.

[0033] Step S13: Determine the receiving mode signal of the receiving antenna based on the energy conversion relationship between different orbital angular momentum mode signals and the transmitting mode signal, and determine the channel transmission coefficient based on the transmitting mode signal, the transmission function, and the receiving mode signal.

[0034] Based on the inherent energy conversion relationship between different OAM mode signals, and combined with the generated transmitter mode signal, the receiver mode signal is determined. Then, based on the transmitter mode signal, the transmission function obtained in the previous steps, and the derived receiver mode signal, the channel transmission coefficient is further quantized and solved.

[0035] Step S14: Construct a channel transmission matrix based on the channel transmission coefficients, and predict the channel state based on the channel transmission matrix.

[0036] Based on the channel transmission coefficients derived from the aforementioned steps, the channel transmission matrix is ​​constructed; based on the quantization characteristics of this matrix, the channel state is predicted.

[0037] In one embodiment of this application, in step S11, information on different orbital angular momentum modes generated by the transmitting antennas in a preset number of transceiver antenna array pairs is obtained; based on the transmitting power of the transmitting antennas and the different orbital angular momentum mode information, a preset baseband signal is modulated to obtain a sub-transmit signal for each orbital angular momentum mode; the sub-transmit signals of each orbital angular momentum mode are linearly superimposed to determine the transmitting end mode signal.

[0038] First, different OAM mode information of the transmitting antenna (such as a millimeter-wave radar antenna) is obtained. Then, based on the transmitting power of the transmitting antenna and the mode information, the preset baseband signal is modulated to obtain the independent sub-transmit signals corresponding to each OAM mode. Finally, the transmitting end mode signal is obtained by linearly superimposing all the sub-transmit signals.

[0039] Furthermore, the orbital angular momentum mode information includes topological charge, helical phase distribution parameters, and beam amplitude distribution parameters. The baseband signal is amplitude modulated based on the transmit power of the transmitting antenna and the beam amplitude distribution parameters. The baseband signal is phase modulated based on the topological charge and the helical phase distribution parameters to obtain the sub-transmitted signal of each orbital angular momentum mode.

[0040] Following the above embodiments, the OAM mode information includes topological charge, spiral phase distribution parameters, and beam amplitude distribution parameters. Amplitude modulation is achieved by combining the transmit power of the transmitting antenna with the beam amplitude distribution parameters, and phase modulation is achieved by combining the topological charge with the spiral phase distribution parameters, ultimately obtaining the sub-transmit signal for each OAM mode. Specifically, the transmitted signal... can be It is composed of the superposition of several independent OAM mode signals, as shown in the following formula:

[0041]

[0042] Where i is the number of the i-th OAM mode; Let be the transmission power of the i-th mode; Let be the modulation signal of the i-th mode; constant Normalization process specifies radial modes ;

[0043] The overall description depicts the distribution of signal amplitude with radial position, conforming to the attenuation law of Gaussian beams. The waist radius of the Gaussian beam determines the spatial divergence characteristics of the beam; The radial coordinates of the beam; Let be the OAM topological charge of the i-th mode, and represent the number of times the spiral phase is wound. Corresponding to different OAM modes.

[0044] For the OAM spiral phase term, The azimuth angle of the beam. The spiral phase distribution, or spatial phase, represents the OAM mode. and These represent the carrier angular frequency and instantaneous phase of the OAM millimeter-wave signal, respectively, which together describe the time-varying phase characteristics of the signal.

[0045] It should be noted that each There is only one corresponding OAM mode. For the i-th OAM mode, It is its topological load (i.e., the number of modes), for example, and These are two completely independent OAM modes, and their spiral phase distribution and spatial transmission characteristics are different.

[0046] The transmitted signal of this millimeter-wave radar is a combination of m topological loads. Signals from different OAM modes are each modulated according to a Gaussian beam amplitude distribution + their own spiral phase + power / modulation information, and then superimposed for transmission. Because different OAM modes are orthogonal, their signals can be transmitted in parallel on the same frequency band, improving the radar's information capacity and target resolution capabilities.

[0047] In one embodiment of this application, in step S12, a geometric model of the transmitting antenna and receiving antenna in the preset number of transceiver antenna array pairs under off-axis offset state is obtained; off-axis offset information of the preset number of transceiver antenna array pairs is determined according to the geometric model; and a transmission function is determined based on the transmitting end mode signal, the off-axis offset information, and the transmission distance.

[0048] Since off-axis offset information is based on geometric feature parameters formed by the spatial relative positions of the transmitting and receiving antennas, it cannot be obtained directly. Therefore, it is necessary to first establish a geometric model of the transmitting and receiving antennas in the off-axis offset state, and then derive accurate off-axis offset information through the spatial parameters of the geometric model. Figure 2 This shows the geometric model of the transmitting and receiving antennas under off-axis offset, in the original coordinate system ( ) represents the reference coordinate system of the transmitting antenna, and the offset coordinate system ( () represents the coordinate system of the receiving antenna, with the X and Y axes parallel to the original coordinate system. The spatial distance between two antenna coordinate systems is denoted as . ; , It is the offset of the receiving antenna in the X and Y directions in the original coordinate system; The off-axis angle is the angle between the line of sight of the transmitting antenna and the Z-axis of the original coordinate system.

[0049] Referring to the geometric model of the transmitting and receiving antennas in an off-axis offset state, Become time-varying , representing the relative radial distance between the transmitting and receiving antennas as it changes over time; It also becomes time-varying. , which represents the azimuth angle between the transmitting and receiving antennas as it changes over time.

[0050] Based on the above dynamic geometric model, a transfer function characterizing the OAM signal transmission characteristics under off-axis offset can be constructed, and the specific formula is as follows:

[0051]

[0052] Where B represents the antenna gain factor; For spatial decay term, d is the wavelength, and d is the transmission distance; For the transmission phase term, Wave number; The Dirac function is used in continuous-domain operations to characterize the discrete properties of orbital angular momentum modes. The part within parentheses in the formula... , The spatial constraint corresponding to the off-axis offset of the transmit and receive antennas indicates that the signal exists only at the relative positions of the transmit and receive antennas. The presence of non-zero values ​​at this point reflects the spatial focusing characteristics under off-axis conditions; Additive white Gaussian noise represents random noise at the receiver.

[0053] The above formula describes how the multi-OAM mode signal at the transmitting end, after passing through antenna gain, spatial attenuation, phase delay, and the spatial constraint of off-axis offset, ultimately forms the received signal after random noise is superimposed at the receiving end. The time-varying off-axis offset effect (through...) , The model is coupled with the inherent transmission characteristics of electromagnetic waves (attenuation, phase change) to accurately quantify the influence of transmit and receive radial displacement and azimuth displacement on OAM signal transmission in dynamic off-axis scenarios.

[0054] In one embodiment of this application, in step S13, the energy conversion relationship between different orbital angular momentum mode signals is determined; based on the energy conversion relationship and the transmitting end mode signal, a multi-mode mixed signal is constructed; and the receiving end mode signal of the receiving antenna is determined according to the multi-mode mixed signal.

[0055] Energy conversion relationship is the inherent characteristic of energy transfer and energy retention between different OAM mode signals during transmission. Figure 3This demonstrates the energy conversion relationships between different OAM mode signals, and the nodes at the transmitting and receiving ends (e.g., , … () represents different orbital angular momentum modes, distinguished by topological charges; the lines connecting the transmitter and receiver nodes and their corresponding... (like , The value represents the energy conversion coefficient from the i-th OAM mode at the transmitter to the j-th OAM mode at the receiver, quantifying the energy transfer ratio between the two modes. Based on this characteristic and the transmitter mode signal, a hybrid signal incorporating the characteristics of multiple orbital angular momentum modes can be constructed first, and then the receiver mode signal for matching the receiving antenna can be determined based on this.

[0056] Specifically, in an ideal scenario, each sub-channel at the transmitter carries a single OAM mode. However, in actual transmission scenarios, energy conversion occurs between different OAM modes. For example, channel interference and off-axis offset can cause mode crosstalk. Therefore, the signal at the receiver will carry multiple OAM modes simultaneously, forming a mixed-mode signal.

[0057] Based on the above energy conversion, parameters are defined. Indicates the transmission mode in actual transmission With receiving mode From the channel transmission coefficients between them, the expression for the distorted OAM millimeter-wave signal can be obtained as follows:

[0058]

[0059] in, This represents the modulation signal of the i-th mode at the transmitting end; For the launch mode Phase terms, including OAM spiral phase ; For receiving mode The radial amplitude distribution term; It is noise.

[0060] Based on the transmission function determined in the preceding steps and the above-described expression for the distorted OAM millimeter-wave signal, the channel transmission coefficient can be further derived. for:

[0061]

[0062] in, It is a Bessel function of order v. For gamma function, It is a Whittaker function, thus fully coupling the inherent characteristics of the OAM mode and the interference factors of dynamic transmission.

[0063] In one embodiment of this application, in step S14, the matrix elements of the channel transmission matrix are determined according to the channel transmission coefficients, and the order of the channel transmission matrix is ​​determined according to the preset number of orbital angular momentum modes, so as to complete the construction of the channel transmission matrix.

[0064] Using the channel transmission coefficients from each OAM mode at the transmitter to each OAM mode at the receiver as matrix elements, the energy transfer allocation ratio from the transmitter mode to each receiver mode is quantified, including inter-mode energy transfer and mode-specific energy retention information. By taking a column of this channel transmission matrix and moduloing each element in the column, the power leaked from the corresponding transmitter OAM mode to each receiver mode, as well as the remaining power gain retained by the transmitter mode itself, can be obtained.

[0065] The order of the channel transmission matrix is ​​determined by the preset number of OAM modes. For example, if there are m OAM modes, then the matrix is... The order is defined as the order of each matrix element. .

[0066] Furthermore, the channel transmission matrix is ​​normalized to obtain an orbital angular momentum mode power distribution feature map. Based on the power distribution feature map, the energy transfer distribution ratio and power distribution characteristics between the transmitting end mode signal and the receiving end mode signal are determined to achieve channel state prediction.

[0067] Channel states can be predicted based on the channel transmission matrix. First, the channel transmission matrix is ​​normalized to eliminate the differences in energy levels between different modes, resulting in a characteristic map of orbital angular momentum mode power distribution that can intuitively reflect the energy distribution. Then, through this characteristic map, the energy transfer and distribution ratio from the transmitter mode to each mode at the receiver, as well as the power distribution characteristics of each mode, are extracted, ultimately achieving accurate prediction of the current channel state (such as the degree of mode crosstalk and power loss).

[0068] In one embodiment of this application, the channel transmission coefficients are modified to optimize the matrix elements of the channel transmission matrix; the channel state is predicted based on the optimized channel transmission matrix.

[0069] After constructing the channel transmission matrix and performing channel state prediction based on it, the channel transmission matrix can be further optimized to improve the reliability and accuracy of channel state prediction. By correcting and optimizing the channel transmission coefficients, the matrix elements of the channel transmission matrix can be directly adjusted and optimized, achieving precise iterative updates of the channel transmission matrix and obtaining an optimized channel transmission matrix.

[0070] After optimizing the channel transmission matrix, channel state prediction is performed based on the optimized matrix. Utilizing the precise energy transfer allocation ratio and power distribution characteristics represented by the optimized matrix elements, the transmission correlation between the transmitting and receiving mode signals is re-derived, thus completing the channel state prediction. The optimized channel transmission matrix better reflects the actual channel transmission characteristics of orbital angular momentum mode signals, effectively avoiding coefficient deviations caused by off-axis offset, channel interference, and mode crosstalk during transmission. This results in a final channel state prediction that more closely matches the actual channel state in the transmission scenario, significantly improving the accuracy and effectiveness of the prediction results.

[0071] The proposed scheme transforms energy transfer between orbital angular momentum modes from an interference phenomenon into a system characteristic parameter (i.e., channel transmission coefficient) that can be quantitatively analyzed and utilized, and successfully constructs a channel matrix suitable for off-axis scenarios; in addition, energy transfer is redefined as an intrinsic characteristic of the channel and used as the core modeling basis, transforming it from an "interference source" into a "utilizable feature".

[0072] Specifically, this scheme constructs a channel model for a millimeter-wave radar communication system based on the energy transfer characteristics of orbital angular momentum modes under off-axis offset conditions at the transmitting and receiving ends. It then derives the channel transmission coefficients under offset conditions, further constructing the channel transmission matrix. This solves a key channel modeling problem and compensates for the lack of an accurate channel model in off-axis scenarios. The model effectively demonstrates that orbital angular momentum, as a transmission carrier, can significantly improve channel transmission capacity. Furthermore, this channel model provides a theoretical basis for subsequent selection of orbital angular momentum modes to enhance the data transmission performance of millimeter-wave radar systems.

[0073] The proposed solution can be applied to various scenarios. In mobile communication, it helps base stations maintain stable, high-capacity connections with mobile terminals such as phones and vehicles even under non-ideal alignment conditions, significantly enhancing the robustness of 5G / 6G networks in dynamic environments. In high-frequency fixed wireless access, it provides high-bandwidth, high-reliability transmission capabilities for remote nodes that are difficult to align precisely. In the field of integrated sensing and communication, it supports the integrated realization of radar detection and high-speed data transmission in the millimeter-wave band, providing a foundation for synchronous sensing and communication for applications such as vehicle-to-everything (V2X) and drone collaboration. By improving communication capacity under non-ideal conditions and enhancing the user experience of 5G / 6G networks in complex environments, it has broad market application prospects in millimeter-wave base stations, vehicle-mounted communication, and satellite internet. Simultaneously, it promotes the deep integration of the cutting-edge physics theory of orbital angular momentum with communication engineering, laying the foundation for opening up a new spectrum resource of "space mode reuse" and providing new ideas for next-generation communication technology research.

[0074] Figure 4 The diagram shows a schematic frame of an electronic device according to another aspect of this application, the electronic device including at least a processor 401 and a memory 402.

[0075] Processor 401 may include one or more processing cores, such as a quad-core processor or an octa-core processor. Processor 401 may be implemented using at least one hardware form selected from DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). Processor 401 may also include a main processor and a coprocessor. The main processor, also known as a CPU (Central Processing Unit), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, processor 401 may integrate a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the screen. In some embodiments, processor 401 may also include an AI (Artificial Intelligence) processor, which is used to handle computational operations related to machine learning.

[0076] The memory 402 may include one or more computer-readable storage media, which may be non-transitory. The memory 402 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In some embodiments, the non-transitory computer-readable storage media in the memory 402 are used to store at least one instruction, which is executed by the processor 401 to implement a channel state prediction method provided in the method embodiments of this application.

[0077] In some embodiments, the electronic device may also optionally include: a peripheral device interface and at least one peripheral device. The processor 401, memory 402, and peripheral device interface can be connected via a bus or signal line. Each peripheral device can be connected to the peripheral device interface via a bus, signal line, or circuit board. Indicatively, peripheral devices include, but are not limited to: radio frequency circuits, touch displays, audio circuits, and power supplies.

[0078] Of course, the electronic device may also include fewer or more components, and this embodiment does not limit this.

[0079] This application also provides a computer-readable medium having computer instructions stored thereon, which can be executed by a processor to implement a channel state prediction method as described above.

[0080] When the channel state prediction method is implemented as a computer program, it can also be stored as an article of manufacture in a computer-readable storage medium. For example, computer-readable storage media can include, but are not limited to, magnetic storage devices (e.g., hard disks, floppy disks, magnetic stripes), optical discs (e.g., compact discs (CDs), digital multifunction discs (DVDs)), smart cards, and flash memory devices (e.g., electrically erasable programmable read-only memory (EPROM), cards, sticks, key drives). Furthermore, the various storage media described herein can represent one or more devices and / or other machine-readable media used for storing information. The term "machine-readable medium" can include, but is not limited to, wireless channels and various other media (and / or storage media) capable of storing, containing, and / or carrying code and / or instructions and / or data.

[0081] It should be understood that the embodiments described above are merely illustrative. The embodiments described herein may be implemented in hardware, software, firmware, middleware, microcode, or any combination thereof. For hardware implementation, the processor may be implemented within one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, and / or other electronic units designed to perform the functions described herein, or combinations thereof.

[0082] Some aspects of this application can be executed entirely by hardware, entirely by software (including firmware, resident software, microcode, etc.), or by a combination of hardware and software. The aforementioned hardware or software may be referred to as a "data block," "module," "engine," "unit," "component," or "system." The processor may be one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DAPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, or combinations thereof. Furthermore, aspects of this application may manifest as computer products residing in one or more computer-readable media, including computer-readable program code. For example, computer-readable media may include, but are not limited to, magnetic storage devices (e.g., hard disks, floppy disks, magnetic tapes, etc.), optical discs (e.g., compressed CDs, digital multifunction DVDs, etc.), smart cards, and flash memory devices (e.g., cards, sticks, key drives, etc.).

[0083] A computer-readable medium may contain a propagated data signal containing computer program code, for example, on baseband or as part of a carrier wave. This propagated signal may take various forms, including electromagnetic, optical, and so on, or suitable combinations thereof. A computer-readable medium can be any computer-readable medium other than a computer-readable storage medium, which can be connected to an instruction execution system, apparatus, or device to enable communication, propagation, or transmission of a program for use. The program code located on the computer-readable medium can be propagated through any suitable medium, including radio, cable, fiber optic cable, radio frequency signals, or similar media, or any combination of the above media.

[0084] The basic concepts have been described above. Obviously, for those skilled in the art, the above disclosure is merely illustrative and does not constitute a limitation of this application. Although not explicitly stated herein, those skilled in the art may make various modifications, improvements, and corrections to this application. Such modifications, improvements, and corrections are suggested in this application, and therefore remain within the spirit and scope of the exemplary embodiments of this application.

[0085] Furthermore, this application uses specific terms to describe embodiments of the application. For example, "an embodiment," "one embodiment," and / or "some embodiments" refer to a particular feature, structure, or characteristic related to at least one embodiment of the application. Therefore, it should be emphasized and noted that "an embodiment," "one embodiment," or "an alternative embodiment" mentioned twice or more in different locations in this specification do not necessarily refer to the same embodiment. In addition, certain features, structures, or characteristics in one or more embodiments of the application can be appropriately combined.

[0086] In some embodiments, numbers describing the quantity of components and attributes are used. It should be understood that such numbers used in the description of embodiments are modified in some examples with the terms "approximately," "approximately," or "generally." Unless otherwise stated, "approximately," "approximately," or "generally" indicates that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may be changed depending on the characteristics required by individual embodiments. In some embodiments, numerical parameters should take into account specified significant digits and employ a general method of digit reservation. Although the numerical ranges and parameters used to confirm their breadth of scope in some embodiments of this application are approximate values, in specific embodiments, such values ​​are set as precisely as feasible.

Claims

1. A channel state prediction method, characterized in that, The method includes: The transmitting mode signal is determined by aligning the transmitting antenna with different orbital angular momentum mode information generated by the transmitting antenna based on a preset number of transmitting and receiving antenna arrays; Obtain off-axis offset information of the preset number of transmit and receive antenna array pairs, and determine the transmission function based on the transmit end mode signal, the off-axis offset information, and the transmission distance; The receiving mode signal of the receiving antenna is determined based on the energy conversion relationship between different orbital angular momentum mode signals and the transmitting mode signal. The channel transmission coefficient is determined based on the transmitting mode signal, the transmission function, and the receiving mode signal. A channel transmission matrix is ​​constructed based on the channel transmission coefficients, and the channel state is predicted based on the channel transmission matrix.

2. The method according to claim 1, characterized in that, The step of determining the transmitting end mode signal based on the different orbital angular momentum mode information generated by the transmitting antenna in a preset number of transceiver antenna arrays includes: Acquire information on different orbital angular momentum modes generated by the transmitting antenna in a preset number of transceiver antenna arrays; Based on the transmission power of the transmitting antenna and the information of different orbital angular momentum modes, the preset baseband signal is modulated to obtain the sub-transmitted signal of each orbital angular momentum mode; The sub-transmission signals of each orbital angular momentum mode are linearly superimposed to determine the transmitter mode signal.

3. The method according to claim 2, characterized in that, The orbital angular momentum mode information includes topological charge, spiral phase distribution parameters, and beam amplitude distribution parameters. The process of modulating a preset baseband signal based on the transmit power of the transmitting antenna and the different orbital angular momentum mode information to obtain a sub-transmitted signal for each orbital angular momentum mode includes: The baseband signal is amplitude modulated based on the transmit power of the transmitting antenna and the beam amplitude distribution parameters; The baseband signal is phase-modulated based on the topological charge and the spiral phase distribution parameters to obtain the sub-emission signal of each orbital angular momentum mode.

4. The method according to claim 1, characterized in that, The step of obtaining off-axis offset information of the preset number of transmit and receive antenna array pairs, and determining the transmission function based on the transmit mode signal, the off-axis offset information, and the transmission distance, includes: Obtain the geometric model of the transmit and receive antennas in the off-axis offset state of the preset number of transmit and receive antenna arrays; The off-axis offset information of the preset number of transceiver antenna array pairs is determined based on the geometric model; The transmission function is determined based on the transmitter mode signal, the off-axis offset information, and the transmission distance.

5. The method according to claim 1, characterized in that, The step of determining the receiving mode signal of the receiving antenna based on the energy conversion relationship between different orbital angular momentum mode signals and the transmitting mode signal includes: Determine the energy conversion relationship between signals of different orbital angular momentum modes; Based on the energy conversion relationship and the transmitting end modal signal, a multi-mode hybrid signal is constructed; The receiving mode signal of the receiving antenna is determined based on the multimode mixed signal.

6. The method according to claim 1, characterized in that, The step of constructing the channel transmission matrix based on the channel transmission coefficients includes: The matrix elements of the channel transmission matrix are determined based on the channel transmission coefficients, and the order of the channel transmission matrix is ​​determined based on the preset number of orbital angular momentum modes, so as to complete the construction of the channel transmission matrix.

7. The method according to claim 1, characterized in that, The prediction of channel state based on the channel transmission matrix includes: The channel transmission matrix is ​​normalized to obtain an orbital angular momentum mode power distribution feature map. Based on the power distribution feature map, the energy transfer distribution ratio and power distribution characteristics between the transmitting end mode signal and the receiving end mode signal are determined to achieve channel state prediction.

8. The method according to claim 1, characterized in that, The method further includes: The channel transmission coefficients are modified to optimize the matrix elements of the channel transmission matrix; Predict channel state based on optimized channel transmission matrix.

9. An electronic device, characterized in that, The electronic device includes: One or more processors; and A memory storing computer-readable instructions, which, when executed, cause the processor to perform the operations of the method as described in any one of claims 1 to 8.

10. A computer-readable medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 8.

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