Multi-device ad hoc network communication method, device and storage medium

Abstract

The invention relates to a multi-device ad hoc network communication method and device and a storage medium, the polarization phenomenon can be accurately monitored and analyzed by collecting the magnetic field intensity vector of the device in real time, calculating the magnetic field gradient tensor and generating a medium polarization intensity distribution diagram, and when it is detected that the polarization angle deviation exceeds a threshold value, the system can quickly respond, and the communication efficiency is improved. A polarization compensation instruction is automatically sent to related equipment, by extracting a multipath component and a historical polarization residual component, the failure of a traditional channel estimation method is avoided, the prediction and compensation capability of a channel is optimized, the establishment of a dynamic compensation codebook is combined with a phase pre-compensation technology, and a phase adjustment process is optimized by using a symbol error fed back by a receiving end. By constructing the polarization memory attenuation prediction model, the channel state change can be learned and predicted in real time, an efficient compensation strategy is provided for the system, the communication requirement of each device is met, stable transmission of signals is ensured, and the communication performance and reliability of the system are improved.

Description

Technical Field

[0001] The present invention relates to a multi-device self-organizing network communication method, equipment and storage medium, belonging to the technical field of networking communication. Background Art

[0002] When ad hoc network devices are deployed in an atmospheric environment containing ferromagnetic particles (such as sandstorms and industrial dust), the suspended particles will produce polarization memory under the action of the alternating electromagnetic field. The residual magnetization intensity of the particles will continue to affect the propagation characteristics of subsequent electromagnetic waves, forming a channel polarization memory effect with time correlation.

[0003] This effect causes traditional channel estimation methods to fail, because the channel state at the current moment actually contains the medium polarization residue left over from the previous communication process, resulting in continuous distortion in signal propagation.

[0004] Therefore, how to slow down the polarization memory phenomenon in device communications and improve the accuracy of signal propagation is an urgent problem that needs to be solved. Summary of the invention

[0005] In order to solve the above problems existing in the prior art, the present invention proposes a multi-device self-organizing network communication method, device and storage medium.

[0006] The technical solution of the present invention is as follows: In one aspect, the present invention provides a multi-device self-organizing network communication method, comprising the following steps: Collect the magnetic field strength vector of each device in the ad hoc network, generate a medium polarization intensity distribution map based on the magnetic field strength vector, monitor the area in the medium polarization intensity distribution map that exceeds a preset polarization angle deviation threshold, and send a polarization compensation signal to the device in the area; The devices receiving the polarization compensation signal are grouped, and each device group is analyzed independently to extract the multipath components exceeding the preset channel coherence time threshold in the communication signal of the communication channel of the device group, and separate the channel response and the historical medium polarization residual component in the multipath components; A compensation codebook is constructed based on the historical medium polarization residual component of the current device group. The compensation codebook includes the medium polarization residual component information at the historical moment and the corresponding pre-distortion phase rotation amount. According to the current medium polarization residual component, the corresponding pre-distortion phase rotation amount is queried in the compensation codebook to perform phase compensation on the symbols to be transmitted, and then the signal transmitter is controlled to transmit the symbols to the corresponding device group; Calculate the error vector amplitude between the transmission symbol received by the device group and the transmission symbol sent by the signal transmitting end, update the corresponding pre-distortion phase rotation amount in the compensation code book of the device group based on the error vector amplitude, and the signal transmitting end performs phase compensation on the transmission symbol again according to the compensation code book and sends it to the device group, repeat the iteration until the error vector amplitude reaches the preset error vector amplitude threshold, stop the iteration, and obtain the optimal pre-distortion phase rotation amount of the device group under the current medium polarization residual component; Before the signal transmitter communicates with any device group, it searches the compensation codebook for the corresponding predistortion phase rotation amount through the current medium polarization residual component of the device group, performs phase compensation on the transmission symbol, and then sends it to the corresponding device group.

[0007] Preferably, the method further comprises the following steps: A polarization memory decay prediction model is constructed based on a machine learning model, a training sample set is constructed based on the historical polarization residual component of the device group, the polarization memory decay prediction model is trained through the training sample set, and the trained polarization memory decay prediction model outputs the polarization memory decay rate corresponding to the device group; The future medium polarization residual component of the current device group is calculated by the polarization memory attenuation rate, and the pre-distortion phase rotation amount is queried in the device group compensation codebook based on the future medium polarization residual component. Based on the queried pre-distortion phase rotation amount, phase pre-compensation is performed on the future transmitted signal of the signal transmitting end.

[0008] Preferably, the steps of constructing the medium polarization intensity distribution map are: The magnetic field strength vector of each device in the ad hoc network is filtered by the Kalman filter algorithm; The magnetic field intensity vector of each device and its corresponding position coordinates are merged to obtain the magnetic field intensity distribution data of the ad hoc network device; Based on the magnetic field intensity distribution data, magnetic field gradient tensor and device topology information, the medium polarization intensity distribution map is generated through the spatial interpolation algorithm.

[0009] Preferably, the specific steps of monitoring the area in the medium polarization intensity distribution diagram that exceeds a preset polarization angle deviation threshold are: Divide the medium polarization intensity distribution diagram into regions equal to the number of devices according to the device locations; Calculate the polarization angle of each area in the medium polarization intensity distribution diagram, as shown in the following formula: ; in: represents the polarization angle of any region; Indicates that the area is The dielectric polarization intensity in the direction; Indicates that the area is The dielectric polarization intensity in the direction; If the polarization angle of the current area is greater than the preset polarization angle deviation threshold, a polarization compensation signal is sent to the device in the area.

[0010] Preferably, the specific steps of grouping the devices that receive the polarization compensation signal are: Collecting polarization parameters of a device that receives a polarization compensation signal, wherein the polarization parameters include a polarization angle, a polarization mode, and a degree of polarization; For any two devices, the polarization orthogonality between the devices is calculated based on their polarization parameters, as shown in the following formula: ; in: Indicates the device With equipment Polarization orthogonality between them; Indicates the device The polarization angle of Indicates the device The polarization angle of Indicates the maximum range of polarization angle; The device state association matrix is ​​constructed based on the polarization orthogonality between devices, as shown in the following formula: ; in: represents the device state association matrix; Indicates the total number of devices; After sorting the devices according to the order of polarization orthogonality in the device state association matrix, the devices are grouped using the graph theory optimal matching algorithm.

[0011] Preferably, the communication signals received by the device group are analyzed, the time intervals of the communication signal components of different paths arriving at the device group are analyzed, and the communication signal components whose time intervals are greater than a preset channel coherence time threshold are extracted and combined into multipath components; A dual-path filter is constructed based on the filtering algorithm, one path is used to filter the channel response in the multipath component, and the other path is used to filter the historical medium polarization residual component in the multipath component, so as to obtain the separated channel response and the historical medium polarization residual component.

[0012] Preferably, the specific calculation steps of the pre-distortion bit rotation amount in the compensation codebook are: Calculate the normalized ratio of the channel response in the multipath component to the historical medium polarization residual component, as shown in the following formula: ; in: express The normalized ratio of the channel response in the multipath component at the time instant and the residual component of the historical medium polarization; Represents the normalized The channel response in the multipath component at time t; Represents the normalized The historical medium polarization residual component in the multipath component at the moment; The normalized ratio of the channel response in the multipath component and the residual component of the historical medium polarization is converted into the predistortion phase rotation through a nonlinear function, as shown in the following formula: ; in: express The amount of predistortion position rotation at time; represents the scaling factor; Represents a nonlinear function.

[0013] Preferably, the corresponding pre-distortion bit rotation amount in the compensation codebook of the device group is updated based on the error vector magnitude, as shown in the following formula: ; ; in: represents the error vector magnitude; Indicates the total number of symbols received by the device group; Indicates the first symbol value; Indicates The original value of the symbol; Indicates The updated value of the predistortion position rotation after iterations; Indicates The amount of predistortion bit rotation at the iteration; Represents the learning rate.

[0014] On the other hand, the present invention further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described in the present invention when executing the program.

[0015] In yet another aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, which implements the method of the present invention when executed by a processor.

[0016] The present invention has the following beneficial effects: 1. The present invention can accurately monitor and analyze polarization phenomena by acquiring the magnetic field intensity vector of the device in real time and calculating the magnetic field gradient tensor to generate a medium polarization intensity distribution map.

[0017] 2. The present invention combines the establishment of a dynamic compensation codebook with the phase pre-compensation technology, and uses the symbol error fed back by the receiving end to optimize the phase adjustment process, forming a closed-loop feedback control and improving the compensation accuracy.

[0018] 3. By constructing a polarization memory attenuation prediction model, the present invention can learn and predict channel state changes in real time, provide an efficient compensation strategy for the system, adapt to the communication needs of each device, ensure stable signal transmission, and improve the communication performance and reliability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0020] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] It should be understood that the step numbers used in this document are only for convenience of description and are not intended to limit the order in which the steps are executed.

[0022] It should be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0023] The terms “include” and “comprising” indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0024] The term "and / or" means and includes any and all possible combinations of one or more of the associated listed items.

[0025] Embodiment 1: See also Figure 1 , a multi-device self-organizing network communication method, comprising the following steps: Collect the magnetic field strength vector of each device in the ad hoc network, generate a medium polarization intensity distribution map based on the magnetic field strength vector, monitor the area in the medium polarization intensity distribution map that exceeds a preset polarization angle deviation threshold, and send a polarization compensation signal to the device in the area through a dedicated control channel; In this embodiment, each device is equipped with a three-axis magnetometer for collecting the magnetic field strength vector at its location. These devices are deployed in a coverage area. Each device is at a fixed spatial position and can monitor the magnetic field strength information of its location in real time. Each device uses a wireless communication protocol (such as LoRaWAN, Wi-Fi or Zigbee) to broadcast the collected polarized magnetic field data to adjacent device nodes in real time. These data packets contain not only the magnetic field strength vector, but also the spatial coordinate information of the device. The devices that receive the polarization compensation signal are grouped, and each device group is analyzed independently to extract the multipath components that exceed the preset channel coherence time threshold (channel coherence time refers to the time interval for signals from multiple paths caused by historical polarization residual memory to reach the receiving end during signal propagation. The channel coherence time threshold is set based on the communication environment conditions and the moving speed of the device, and is set to 10ms by default) in the communication signal of the device group's communication channel, and perform time domain separation and decoupling of the channel response and historical medium polarization residual components in the multipath components; Since the devices in the device group are still in communication state at this time, in order to effectively communicate and compensate for polarization between the devices, mutually orthogonal reference signal sequences are embedded in a preset position in the underlying frame structure of the device group communication protocol. The reference signal sequence (such as the Zadoff-Chu sequence) is used to synchronize the communication signals between the devices and serves as a reference benchmark for the signal to help the receiving end accurately identify and demodulate the signal. The embedded reference signal sequence should ensure orthogonality, that is, the signals used between the devices are independent of each other and will not interfere with each other; A compensation codebook is constructed based on the historical medium polarization residual component of the current device group. The compensation codebook includes the medium polarization residual component information at the historical moment and the corresponding pre-distortion phase rotation (the angle of the signal can be adjusted to make it closer to the expected phase through phase rotation). According to the current medium polarization residual component, the corresponding pre-distortion phase rotation is queried in the compensation codebook to perform phase compensation on the symbols to be transmitted, and then the signal transmitter is controlled to transmit the symbols to the corresponding device group; Calculate the error vector amplitude between the transmission symbol received by the device group and the transmission symbol sent by the signal transmitting end, update the corresponding pre-distortion phase rotation amount in the compensation code book of the device group based on the error vector amplitude, and the signal transmitting end performs phase compensation on the transmission symbol again according to the compensation code book and sends it to the device group, repeat the iteration until the error vector amplitude reaches the preset error vector amplitude threshold, stop the iteration, and obtain the optimal pre-distortion phase rotation amount of the device group under the current medium polarization residual component; Before the signal transmitter communicates with any device group, it searches the compensation codebook for the corresponding predistortion phase rotation amount through the current medium polarization residual component of the device group, performs phase compensation on the transmission symbol, and then sends it to the corresponding device group.

[0026] As a preferred implementation of this embodiment, the method further includes the following steps: A polarization memory attenuation prediction model is constructed based on a machine learning model (such as online gradient descent, support vector machine, recurrent neural network (RNN), etc.), and a training sample set is constructed based on the historical polarization residual component of the device group (the training sample set also includes environmental parameters, specifically external factors that affect channel attenuation such as temperature, humidity, and air pressure). The polarization memory attenuation prediction model is trained through the training sample set. The trained polarization memory attenuation prediction model outputs the polarization memory attenuation rate corresponding to the device group. The polarization memory attenuation rate reflects the attenuation degree of the polarization characteristics of the signal over time due to changes in the propagation environment. Based on the error feedback between devices, the system starts a collaborative correction mechanism to adjust the parameters of the polarization memory decay prediction model through the mutual feedback information of multiple devices. Each device updates the parameters in the polarization memory decay prediction model according to the feedback error of the neighboring nodes, gradually improving the accuracy of the prediction; The correction process can be achieved by weighted averaging or minimizing the error until the prediction accuracy of the polarization memory decay prediction model reaches the set index; The future medium polarization residual component of the current device group is calculated by the polarization memory attenuation rate. The pre-distortion phase rotation amount is queried in the device group compensation codebook based on the future medium polarization residual component. The phase pre-compensation of the future transmitted signal of the signal transmitter is performed based on the queried pre-distortion phase rotation amount. Specifically, Encapsulate the prediction result into the header control field of the underlying frame (physical layer or link layer) of the communication protocol (the header control field is the management information part of the data frame and is used to carry control information and synchronization signals); The signal transmitter obtains the polarization prediction residual attenuation rate between the signal transmitter and the receiving device at the next moment in the header control field, calculates the predicted polarization residual component in real time, retrieves the phase pre-compensation amount in the dynamic compensation codebook based on the predicted polarization residual component, and performs phase pre-compensation on the transmission symbol of the transmitter.

[0027] As a preferred implementation of this embodiment, the steps for constructing the medium polarization intensity distribution diagram (the distribution diagram reflects the magnetic field intensity distribution at different positions and the polarization intensity of the medium is deduced therefrom) are: The magnetic field strength vector of each device in the ad hoc network is filtered by the Kalman filter algorithm; The magnetic field intensity vector of each device and its corresponding position coordinates are merged to obtain the magnetic field intensity distribution data of the ad hoc network device; Based on the magnetic field intensity distribution data, magnetic field gradient tensor and device topology information, a medium polarization intensity distribution map is generated through a spatial interpolation algorithm; The magnetic field strength vector and its position coordinates of each device are continuously updated. The filtering process ensures that the magnetic field data collected from multiple device nodes are weighted and fused (the weights are set based on the stability of signal transmission), reducing noise and uncertainty to obtain a more accurate magnetic field strength estimate.

[0028] As a preferred implementation of this embodiment, the specific steps of monitoring the area in the polarization intensity distribution diagram of the medium that exceeds the preset polarization angle deviation threshold are: Divide the medium polarization intensity distribution diagram into regions equal to the number of devices according to the device locations; Calculate the polarization angle of each area in the medium polarization intensity distribution diagram, as shown in the following formula: ; in: represents the polarization angle of any region; Indicates that the area is The dielectric polarization intensity in the direction; Indicates that the area is The dielectric polarization intensity in the direction; If the polarization angle of the current area is greater than the preset polarization angle deviation threshold, a polarization compensation signal is sent to the device in the area.

[0029] As a preferred implementation manner of this embodiment, the specific steps of grouping devices that receive the polarization compensation signal are: Collecting polarization parameters of a device that receives a polarization compensation signal, wherein the polarization parameters include a polarization angle, a polarization mode, and a degree of polarization; For any two devices, the polarization orthogonality between the devices is calculated based on their polarization parameters, as shown in the following formula: ; in: Indicates the device With equipment Polarization orthogonality between them; Indicates the device The polarization angle of Indicates the device The polarization angle of Indicates the maximum range of polarization angle; The device state association matrix is ​​constructed based on the polarization orthogonality between devices, as shown in the following formula: ; in: represents the device state association matrix; Indicates the total number of devices; After sorting the devices according to the polarization orthogonality in the device state association matrix, the devices are grouped using the graph theory optimal matching algorithm. All devices in the same device group use the same time slot for data transmission. As a preferred implementation of this embodiment, the communication signal received by the device group is analyzed, the time intervals of the communication signal components of different paths arriving at the device group are analyzed, and the communication signal components whose time intervals are greater than a preset channel coherence time threshold are extracted and combined into multipath components; A dual-path filter is constructed based on Kalman filtering or adaptive filtering algorithm, one of which is used to filter the channel response in the multipath component, and the other is used to filter the historical medium polarization residual component in the multipath component, so as to obtain the separated channel response and the historical medium polarization residual component; When filtering, the suppression weight of the historical polarization residual component is set, which depends on the analysis results of the historical data and the current channel status. When the historical polarization effect is strong, a higher suppression weight needs to be set. However, in order to prevent distortion caused by excessive suppression, the suppression ratio is required not to exceed 50%; As a preferred implementation of this embodiment, the specific calculation steps of the pre-distortion bit rotation amount in the compensation codebook are: Calculate the normalized ratio of the channel response in the multipath component to the historical medium polarization residual component, as shown in the following formula: ; in: express The normalized ratio of the channel response in the multipath component at the time instant and the residual component of the historical medium polarization; Represents the normalized The channel response in the multipath component at time t; Represents the normalized The historical medium polarization residual component in the multipath component at the moment; The normalized ratio of the channel response in the multipath component and the residual component of the historical medium polarization is converted into the predistortion phase rotation through a nonlinear function, as shown in the following formula: ; in: express The amount of predistortion position rotation at time; represents the scaling factor; Represents nonlinear functions, such as Sigmoid function.

[0030] As a preferred implementation of this embodiment, the corresponding pre-distortion bit rotation amount in the compensation codebook of the device group is updated based on the error vector magnitude, as shown in the following formula: ; ; in: represents the error vector magnitude; Indicates the total number of symbols received by the device group; Indicates the first symbol value; Indicates The original value of the symbol; Indicates The updated value of the predistortion position rotation after iterations; Indicates The amount of predistortion bit rotation at the iteration; represents the learning rate; It represents the gradient of EVM with respect to the amount of predistortion position rotation; Monitor the phase pre-compensation process. When the rotation angle exceeds the gradient threshold of the set multi-level angle (for example, 10 degrees, 1 degree, 0.1 degree), the modulation downgrade protection mechanism is triggered, and the modulation format is switched to a low-order modulation format to suppress the spread of nonlinear distortion.

[0031] Embodiment 2: This embodiment provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described in any embodiment of the present invention when executing the program.

[0032] Embodiment three: This embodiment provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the method described in any embodiment of the present invention is implemented.

[0033] In the embodiments of the present application, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent the existence of A alone, the existence of A and B at the same time, and the existence of B alone. Among them, A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b and c can be represented by: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, c can be single or multiple.

[0034] Those of ordinary skill in the art will appreciate that the various units and algorithm steps described in the embodiments disclosed herein can be implemented in a combination of electronic hardware, computer software, and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0035] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0036] In several embodiments provided in the present application, if any function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory; hereinafter referred to as: ROM), random access memory (Random Access Memory; hereinafter referred to as: RAM), disk or optical disk, and other media that can store program codes.

[0037] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A multi-device self-organizing network communication method, characterized in that: The following steps are involved: Collect the magnetic field strength vector of each device in the ad hoc network, generate a medium polarization intensity distribution map based on the magnetic field strength vector, monitor the area in the medium polarization intensity distribution map that exceeds a preset polarization angle deviation threshold, and send a polarization compensation signal to the device in the area; The devices receiving the polarization compensation signal are grouped, and each device group is analyzed independently to extract the multipath components exceeding the preset channel coherence time threshold in the communication signal of the communication channel of the device group, and separate the channel response and the historical medium polarization residual component in the multipath components; A compensation codebook is constructed based on the historical medium polarization residual component of the current device group. The compensation codebook includes the medium polarization residual component information at the historical moment and the corresponding pre-distortion phase rotation amount. According to the current medium polarization residual component, the corresponding pre-distortion phase rotation amount is queried in the compensation codebook to perform phase compensation on the symbols to be transmitted, and then the signal transmitter is controlled to transmit the symbols to the corresponding device group; Calculate the error vector amplitude between the transmission symbol received by the device group and the transmission symbol sent by the signal transmitting end, update the corresponding pre-distortion phase rotation amount in the compensation code book of the device group based on the error vector amplitude, and the signal transmitting end performs phase compensation on the transmission symbol again according to the compensation code book and sends it to the device group, repeat the iteration until the error vector amplitude reaches the preset error vector amplitude threshold, stop the iteration, and obtain the optimal pre-distortion phase rotation amount of the device group under the current medium polarization residual component; Before the signal transmitter communicates with any device group, it searches the compensation codebook for the corresponding predistortion phase rotation amount through the current medium polarization residual component of the device group, performs phase compensation on the transmission symbol, and then sends it to the corresponding device group.

2. A multi-device ad hoc network communication method according to claim 1, characterized in that: The method further comprises the following steps: A polarization memory decay prediction model is constructed based on a machine learning model, a training sample set is constructed based on the historical polarization residual component of the device group, the polarization memory decay prediction model is trained through the training sample set, and the trained polarization memory decay prediction model outputs the polarization memory decay rate corresponding to the device group; The future medium polarization residual component of the current device group is calculated by the polarization memory attenuation rate, and the pre-distortion phase rotation amount is queried in the device group compensation codebook based on the future medium polarization residual component. Based on the queried pre-distortion phase rotation amount, phase pre-compensation is performed on the future transmitted signal of the signal transmitting end.

3. A multi-device ad hoc network communication method according to claim 1, characterized in that: The steps of constructing the medium polarization intensity distribution map are: The magnetic field strength vector of each device in the ad hoc network is filtered by the Kalman filter algorithm; The magnetic field intensity vector of each device and its corresponding position coordinates are merged to obtain the magnetic field intensity distribution data of the ad hoc network device; Based on the magnetic field intensity distribution data, magnetic field gradient tensor and device topology information, the medium polarization intensity distribution map is generated through the spatial interpolation algorithm.

4. A multi-device ad hoc network communication method according to claim 1, characterized in that: The specific steps of monitoring the area in the medium polarization intensity distribution diagram that exceeds the preset polarization angle deviation threshold are: Divide the medium polarization intensity distribution diagram into regions equal to the number of devices according to the device locations; Calculate the polarization angle of each area in the medium polarization intensity distribution diagram, as shown in the following formula: ； in: represents the polarization angle of any region; Indicates that the area is The dielectric polarization intensity in the direction; Indicates that the area is The dielectric polarization intensity in the direction; If the polarization angle of the current area is greater than the preset polarization angle deviation threshold, a polarization compensation signal is sent to the device in the area.

5. A multi-device ad hoc network communication method according to claim 1, characterized in that: The specific steps of grouping the devices that receive the polarization compensation signal are as follows: Collecting polarization parameters of a device that receives a polarization compensation signal, wherein the polarization parameters include a polarization angle, a polarization mode, and a degree of polarization; For any two devices, the polarization orthogonality between the devices is calculated based on their polarization parameters, as shown in the following formula: ； in: Indicates the device With equipment Polarization orthogonality between them; Indicates the device The polarization angle of Indicates the device The polarization angle of Indicates the maximum range of polarization angle; The device state association matrix is ​​constructed based on the polarization orthogonality between devices, as shown in the following formula: ； in: represents the device state association matrix; Indicates the total number of devices; After sorting the devices according to the order of polarization orthogonality in the device state association matrix, the devices are grouped using the graph theory optimal matching algorithm.

6. A multi-device ad hoc network communication method according to claim 5, characterized in that: Analyze the communication signals received by the device group, analyze the time intervals of the communication signal components of different paths arriving at the device group, extract the communication signal components whose time intervals are greater than a preset channel coherence time threshold, and combine them into multipath components; A dual-path filter is constructed based on the filtering algorithm, one path is used to filter the channel response in the multipath component, and the other path is used to filter the historical medium polarization residual component in the multipath component, so as to obtain the separated channel response and the historical medium polarization residual component.

7. A multi-device ad hoc network communication method according to claim 1, characterized in that: The specific calculation steps of the pre-distortion bit rotation amount in the compensation codebook are: Calculate the normalized ratio of the channel response in the multipath component to the historical medium polarization residual component, as shown in the following formula: ； in: express The normalized ratio of the channel response in the multipath component at the time instant and the residual component of the historical medium polarization; Represents the normalized The channel response in the multipath component at time t; Represents the normalized The historical medium polarization residual component in the multipath component at the moment; The normalized ratio of the channel response in the multipath component and the residual component of the historical medium polarization is converted into the predistortion phase rotation through a nonlinear function, as shown in the following formula: ； in: express The amount of predistortion position rotation at time; represents the scaling factor; Represents a nonlinear function.

8. A multi-device ad hoc network communication method according to claim 1, characterized in that: The corresponding pre-distortion bit rotation amount in the compensation codebook of the device group is updated based on the error vector magnitude, as shown in the following formula: ； ； in: represents the error vector magnitude; Indicates the total number of symbols received by the device group; Indicates the device group received the symbol value; Indicates The original value of the symbol; Indicates The updated value of the predistortion position rotation after iterations; Indicates The amount of predistortion bit rotation at the iteration; Represents the learning rate.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the method according to any one of claims 1 to 8 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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